Let’s Play it Safe! Entertainment-Education in the Digital Age – Developing and Testing a Digital Entertainment-Education Game about HIV/AIDS Protection for Female Adolescents by

Yvonne Thies-Brandner

A Thesis submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy in Psychology

Approved, Thesis Committee

______Prof. Dr. Margrit Schreier (Chair) Jacobs University Bremen ______Prof. Dr. Klaus Boehnke Jacobs University Bremen

Prof. Dr. Dagmar Unz University of Applied Sciences Würzburg-Schweinfurt

Date of Defense: May 3, 2013

School of Humanities and Social Sciences

II

“Anyone who tries to make a distinction between education and entertainment doesn’t know the first thing about either” Marshall McLuhan (Canadian Philosopher)

III IV

Table of Contents

Summary XIII

Acknowledges XV

1. Introduction 1

2. Entertainment-Education – A Strategy 7 2.1 Introduction and History 7 2.2 Definition, Strengths, and Challenges 15 2.2.1 Definition 15 2.2.2 Strengths 18 2.2.3 Challenges – and How to Overcome Them 21 2.3 Theories Underlying Entertainment-Education 26 2.3.1 Introduction 26 2.3.2 Models with Steps/Stages 27 2.3.2.1 Hierarchy-of-Effects Model 28 2.3.2.2 Stages-of-Change Model 29 2.3.2.3 Diffusion of Innovations Theory 30 2.3.2.4 Summary – Models with Steps/Stages 30 2.3.3 Social Psychological Models 31 2.3.3.1 Bandura’s Social Learning Theory – Social Modeling 31 2.3.3.2 Theory of Reasoned Action & Theory of Planned 37 Behavior 2.3.3.3 The Health Belief Model 39 2.3.3.4 The Health Action Process Approach (HAPA) 40 2.3.3.5 Summary – Social Psychological Theories 41 2.3.4 Cognitive Models 42 2.3.4.1 Elaboration-Likelihood Model of Persuasion (ELM) 42 2.3.4.2 Theory of the Triune Brain 44 2.3.4.3 Summary – Cognitive Models 45 2.3.5 Drama and Role Models 46 2.3.6 Audience-Centered Models 46 2.3.6.1 Uses-and-Gratifications Theory 47 2.3.6.2 Two-Step Flow Model 48

V 2.3.6.3 Parasocial Interaction 48 2.3.6.4 Audience Involvement 49 2.3.6.5 Summary – Audience-Centered Theories 49 2.3.7 Contextual Theories 50 2.3.7.1 Agenda-Setting Model 50 2.3.7.2 Cultivation Theory 51 2.3.7.3 Summary – Contextual Theories 51 2.3.8 Hybrid Models 52 2.3.8.1 Sabido Method 52 2.3.8.2 An Integrative Model of Entertainment-Education 54 Processes and Outcomes

2.3.8.3 Summary – Hybrid Models 55 2.3.9 Summary – Theories Underlying Entertainment-Education 56 2.4 Effects of Entertainment-Education 56 2.4.1 Introduction and Ways of Evaluation 56 2.4.2 Examples of Entertainment-Education Effects 61 2.4.2.1 Knowledge 61 2.4.2.2 Interest 62 2.4.2.3 Self-efficacy 63 2.4.2.4 Communication 63 2.4.2.5 Behavioral Change 65 2.4.2.6 Summary 67 2.5 Factors Affecting an Entertainment-Education Outcome 67 2.5.1 Introduction 67 2.5.2 Factors Concerning the Entertainment-Education Media Product 68 2.5.3 Factors Concerning the Environment 71 2.5.4 Factors Concerning the Audience 73 2.5.5 Factors Concerning Accompanying Research 76 2.5.6 Summary 76 2.6 Ethical Considerations Concerning the Use of Entertainment-Education 77 2.7 Summary 90

VI

3. (Digital) Game-Playing 99 3.1 Play 99 3.1.1 Introduction 99 3.1.2 Theories of Play 100 3.1.3 Definition and Classification of Play 104 3.1.4 Play and Game 106 3.2 Digital Games 107 3.2.1 Introduction, History, and Definition 107 3.2.2 Classification 110 3.2.3 Why People Play Digital Games 113 3.2.4 Effects of Digital Games 121 3.2.4.1 Negative Effects 121 3.2.4.2 Positive Effects 125 3.2.5 Serious Games – The Use of Digital Games for Education 128 3.2.5.1 Introduction, Definitions, and Classification 128 3.2.5.2 Effectiveness of Serious Games 132 3.2.5.3 Specifics of Serious Games Compared to 133 Traditional Education

3.2.5.4 Possible Advantages of Using Serious Games as 137 Educational Tools

3.2.5.5 Possible Disadvantages of Serious Games 143 3.2.6 Digital Entertainment-Education Games 145 3.2.7 Digital Games for HIV/AIDS Prevention 149 3.2.8 Digital Games and Girls 150 3.2.8.1 Girls’ Use of Digital Games 150 3.2.8.2 Girls and Common Digital Games 152 3.2.8.3 Girls’ Favorite Games and Genres 154 3.2.8.4 Conclusion 156 3.3 Summary 157

4. Female Adolescents 164 4.1 Introduction 164 4.2 Developmental Stage 166 4.2.1 Physical Changes 166

VII 4.2.2 Psychological Changes 168 4.2.3 Cognitive Changes 175 4.3 Female Adolescents in Germany 179 4.3.1 Living Conditions 179 4.3.2 Health 182 4.3.2.1 Introduction 182 4.3.2.2 Somatic Diseases: Acute & Chronic Illness 183 4.3.2.3 Mental Health 184 4.3.2.4 Risk Behavior 184 4.3.3 Sexuality 187 4.3.3.1 Introduction 187 4.3.3.2 Sex Education 188 4.3.3.3 Sexual Orientation of 15-Year-Old Girls in 189 Germany

4.3.3.4 Sexual Experiences of 15-Year-Old Girls in 189 Germany

4.3.3.5 Use of Contraception 189 4.3.3.6 Consequences of Unprotected Sexual Activity 191 4.4 Need for new HIV/AIDS Prevention Ways 191 4.5 Summary 194

5. The Present Study 198

6. Methods 206 6.1 Deduction of Hypotheses 206 6.1.1 Hypotheses concerning Dependent Variables 206 6.1.2 Hypotheses concerning Moderator/Mediator Variables 208 6.1.3 Explorative Questions 209 6.2 Operationalization of the Independent Variable 212 6.2.1 HIV/AIDS as Topic for this Study 212 6.2.2 The Game – Creating a Digital Entertainment-Education 213 Game about HIV/AIDS for Teenage Girls

6.3 Operationalization of the Dependent Variables 222 6.3.1 Introduction 222 6.3.2 Knowledge about HIV/AIDS 223

VIII 6.3.3 Interest in HIV/AIDS 224 6.3.4 Communication about HIV/AIDS 226 6.4 Operationalization of Moderator and Mediator Variables 227 6.4.1 Involvement 227 6.4.2 Personal Risk Perception 228 6.4.3 Experience with Digital Games 229 6.5 Other Measurements 229 6.5.1 Demographic Facts 229 6.5.2 Sexual Behavior 229 6.5.3 Measurements for Explorative Purpose 230 6.5.3.1 Self-Efficacy 230 6.5.3.2 Behavior Intention 230 6.6 Measurements – Overview 231 6.7 Empirical Hypotheses 232 6.8 Qualitative Pilot Study 233 6.9 Design – The Solomon-Four-Group Design 236 6.10 Sample 240 6.10.1 Recruitment 240 6.10.2 Description of Sample 241 6.11 Research Procedures 243

6.12 Ethics and the Present Study 244

7. Data Preparation and Analysis 246 7.1 Introduction 246 7.2 Data Preparation 246 7.2.1 Box Plots 246 7.2.2 Comparison of Subsamples (Bremen/Cologne) 246 7.3 Reliability Analyses – Cronbach’s Alpha 247 7.4 Data Reduction 248 7.4.1 Factor Analysis 248 7.4.2 Sum Variables and Indices 249 7.5 Results 251 7.5.1 Descriptive Statistics 251 7.5.2 Analysis of the Solomon-Four-Group-Plan 260

IX 7.5.2.1 Assumption 260 7.5.2.2 Concerning Hypothesis 1 (Knowledge) 263 7.5.2.3 Concerning Hypothesis 2 (Interest) 264 7.5.2.4 Concerning Hypothesis 3 (Communication) 268 7.5.2.5 Concerning Hypothesis 4 (Involvement) 269 7.5.2.6 Concerning Hypothesis 5 (Risk Perception) 270 7.5.3 Explorative Results 271 7.5.4 Summary of Results 277

8. Discussion and Conclusions 284 8.1 Discussion of Supergöre and the Results of the Present Study 284 8.1.1 The Game Supergöre 284 8.1.2 Effects on Dependent Variables 285 8.1.3 Moderator- and Mediator Effects 288 8.1.4 Other Variables 290 8.1.5 Ethics Statement 290 8.2 Limitations of the Study 291 8.2.1 Limitations Concerning Methodology and Design 291 8.2.2 Checking Required Procedures for Evaluating 293 Entertainment-Education Interventions

8.3 Future Research Directions and Indications for Practice 295 8.4 Conclusions 299

References 302

Appendices Appendix A – Focus group topic guide Appendix B – Photographs Appendix C – Recruitment letters Appendix D – Instruction and questionnaires Appendix E – Statistical analyses

X

List of Tables

Table 1 Matrix Visualization of the Potential Effect Mechanisms Underlying 142 Playing Serious Games on Social Change

Table 2 Overview of measures used for the present study 231 Table 3 Schema of the Solomon Four-Group Design 237 Table 4 Allocation of sample into the Solomon Four-Group Design 242 Table 5 Frequencies of girls participating in the experiment and post-tests sent per 242 mail

Table 6 Level of school education participants aimed for 243 Table 7 Study design 244 Table 8 Scores of the reliability analyses 248 Table 9 Risk perception – Items 3 to 6 254 Table 10 Self-efficacy – Results for Items 3a to 3i 256 Table 11 General interest items 257

List of Figures

Figure 1 Conceptualizations of entertainment and education 17 Figure 2 Stages of change model 29 Figure 3 Sub-processes of observational learning and influencing factors 34 Figure 4 The relation between self-efficacy, outcome expectancy, and behavior 36 as mentioned by Bandura

Figure 5 Schematic presentation of the theory of reasoned action 38 Figure 6 Schematic presentation of the theory of planned behavior 38 Figure 7 The health belief model by Rosenstock, 1974 40 Figure 8 The health action process approach (HAPA) by Schwarzer 41 Figure 9 Schematic diagram of the elaboration-likelihood model 43 Figure 10 The theory of the triune brain 45 Figure 11 The uses and gratifications theory 47 Figure 12 The two-step flow model 48 Figure 13 The agenda-setting model 50 Figure 14 Entertainment-education model by Wilkin and Fernandes 55

XI Figure 15 Schematic representation of hormonal regulation of girls’ puberty 167 Figure 16 Screenshot Level 1 (Discotheque) 217 Figure 17 Screenshot Level 2 (Camp) 218 Figure 18 Screenshot Level 2 – Pop-up window with information 219 Figure 19 Screenshot Level 2 – Pop-up window with positive feedback 219 Figure 20 Screenshot Level 2 – Pop-up window with negative feedback 220 Figure 21 Screenshot Level 3 (Underwater World) 221 Figure 22 Screenshot Level 4 (Scary world) 221 Figure 23 Screenshot Level 5 (Jungle World) 222 Figure 24 Flowchart – Solomon Four-Group Design analysis procedure 239 Figure 25 Risk perception – Item 1 253 Figure 26 Risk perception – Item 2 254 Figure 27 Process sequence – Hypothesis 1 264 Figure 28 Process sequence – Hypothesis 2 266 Figure 29 Process sequence – Hypothesis 3 268 Figure 30 Process sequence – Exploratory questions 1 and 2 272 Figure 31 Flowchart of main findings 279

XII Summary

Entertainment-education is a method to educate people through entertainment media products. This idea of combining entertainment and education is not new and might be as old as mankind, but the entertainment-education strategy is a relatively new concept. Research has shown that entertainment-education can have positive effects on people’s behavior, attitudes, knowledge, and interpersonal (peer) communication, and that it works with various media (products) such as radio, TV soap operas, street theatre, or comics. These have been non-interactive entertainment-education programs; many theories explain their success on the basis of engaging narratives. The question is whether this strategy also works for interactive media like digital games. To test this, a digital entertainment-education game called Supergöre was exclusively developed and created for the present study with the software GameMaker; a major focus was put on interactivity and not on narratives. The game's educational topic was HIV/AIDS and condom use, and it was designed according to entertainment-education guidelines. The information about HIV/AIDS and condom use that was implemented in the game was taken from two brochures published by the German Federal Center for Health Education. To ensure that the game meets girls’ computer game preferences – to meet the “entertainment requirements” – the game was developed in accordance with gender-related digital game research and evaluated by six 15-year-old female adolescents from different types of German schools within a comprehensive qualitative pilot study. Since the participants enjoyed playing the game – and most of them especially liked the level in which the information about HIV/AIDS and condom use was embedded – it can be concluded that this game succeeded in being an entertainment product. To test its effects as an education product, 75 female adolescents (50 in Bremen and 25 in Cologne) aged 13 to 18 (M=14,83 years) took part in the main study. It was hypothesized that girls who play the game Supergöre would reach significantly higher scores on the knowledge, interest, and follow-up communication posttests than girls in the control group. Therefore, data on girls’ knowledge about

XIII and interest in HIV/AIDS and condom use and communication about the topic were collected via questionnaires and used as dependent variables. Additionally, perceived self-efficacy and personal risk perception concerning HIV/AIDS as well as involvement while playing the game were included as moderator/mediator variables. The independent variable, i.e. playing or not playing the game, was varied within a Solomon four-group design so as to avoid any influence of pretest sensitization on the results. The digital game created for the present study led to a significant increase in knowledge about HIV/AIDS and condom use, but no significant increases in interest and communication were observed. Perceived self-efficacy and personal risk perception had no influence on the results while involvement had an influence to some extent; highly involved participants reported significantly higher interest in the topic of HIV/AIDS and condom use than marginally involved participants. For follow-up communication, a marginally significant difference was found in the direction of highly involved participants talking more often about HIV/AIDS after playing the game than marginally involved participants. Overall, the present results imply that the digital game Supergöre was successful in informing the participating girls about HIV/AIDS and condom use, and that involvement seems to be an important mediator variable that needs to be studied in detail in future research.

XIV Thank you!

Above all, I would like to express my deep gratitude to my supervisor Margrit Schreier. I am deeply thankful for having her as my advisor. This dissertation would not have been possible without her comments, suggestions, and advice. Moreover, I would like to thank her for her unlimited theoretical and practical support and guidance on all aspects of academic life and beyond. I also want to thank the members of my dissertation committee, Klaus Boehnke and Dagmar Unz, for their willingness to invest their time and effort in this thesis. There are many people who have helped me during the various stages of this project. I would especially like to thank Mikhail Pushkin for helping me create the digital game. He was always able to realize all my ideas and special requests. This study would not have been possible without all the girls that agreed to participate, many thanks to them and to all the people that helped me find participants. I would like to thank all the people involved as proofreaders during the last years. Special thanks go to Martina Panzer for her very fast and reliable work and her emotional support not only at the end of the writing process, but also during numerous train rides between Bremen and Cologne. There are many other people who have supported me while carrying out this project in Bremen: Özen Odag, Esra Özcan, Jessica Price, Nicola Bücker, Sophie A. Gerlach, Felix Schmitz-Justen, Alexandra und Johannes Rückert, and Lechi Langewand – thank you all! And thanks to all my friends and family in Cologne, in particular to my parents and parents-in-law, and to Dirk for his patience and for always believing in me – you are my bridge over troubled water! I would like to dedicate this work to my beloved daughter Leni: It should always remind you that it is worth to pursue your goals – even if it takes long.

XV 1. Introduction

Imagine you did not need to read up about important health topics with educational booklets or boring textbooks yourself, because you automatically knew all essential information, and so did most of your peers – simply from using mass media like TV or digital games. Of course this idea is utopic; nevertheless, it is possible to embed accurate information about health and other relevant topics in entertaining media products. According to the knowledge gap hypothesis, mass media disadvantage people with a lower socioeconomic status compared to people with a higher socioeconomic status, because those with a higher socioeconomic status improve their knowledge faster because they more often select and use informational mass media sources (Donohue, Tichenor, & Olien, 1975). If people with a lower socioeconomic status cannot be encouraged to use such mass media resources, the mass media they actually consume should contain correct information about important issues. That these people indeed get their health information from fictional mass media was already described as problematic by Gerbner et al. (1986). But it does not necessarily have to be a problem: If the mass media include accurate information, consumers will be well- informed – this is the central idea of the entertainment-education strategy. This idea – to combine entertainment and education – is not new, but became popular again as “entertainment-education” (e.g. Singhal, Cody, Rogers, & Sabido, 2004) during the last decades. First utilized in Latin America, it has also shown to be effective, for instance in the way of radio and television soap operas in many countries allover the world. As most of the evaluated entertainment-education interventions were produced for TV, radio, or print media, their results and the theories underlying these effects cannot be transferred to other media untested. In particular, digital games are a medium that strongly differs from the – linear – media mentioned above, mainly because of its interactive elements (Peng, 2009; Grodal, 2000). Digital games provide not only the opportunity, but even a need for players to interact with them; otherwise nothing happens or the game will be finished. This need to be active is very different from watching, hearing or reading linear media:

1 here the media user is a relatively passive consumer, whereas players enjoy being active users (Vorderer, 2000; Vorderer, Knobloch, & Schramm, 2001). Because media usage has changed in recent years and people spend a lot of time playing digital games (Klimmt, 2004b) it is obviously a good idea to include information about health and other relevant topics in digital games as defined by the entertainment-education strategy. The idea to use digital games for education is interesting for various research fields (psychology, health communication, media studies, public health, social work etc.) and the results are often called “serious games” (Ritterfeld, Cody, & Vorderer, 2009). Digital entertainment-education games can be seen as one sub-category within serious games (Wang & Singhal, 2009). The creation, production, and evaluation of digital entertainment-education games are at early stages (Wang & Singhal, 2009). Therefore, it is not clear whether the entertainment-education strategy will also be effective with digital games. Thus, there is a need for empirical studies. The general aim of this thesis is to test whether a digital game can be successfully used as an intervention within the entertainment-education framework. If so, this would be especially advantageous for adolescents, because this group is used to playing digital games and grew up in the digital age. For adolescents computers, consoles, Internet, and the like are nothing out of the ordinary; they have been called “digital natives” (Prensky, 2001). Furthermore, traditional prevention media, e.g. booklets or lessons with deterrent messages, are a disincentive to adolescents or cause mistrust (Franzkowiak, 1986). Therefore it makes sense to research digital games for entertainment-education targeting young people. To be able to create a successful entertainment-education intervention, it is essential to know the preferences of the target group very well in order to create an intervention that is as appealing to them as possible (Singhal & Rogers, 1999). In the course of digital games research, scholars recently found evidence for gender specific differentiations: females and males need different game characteristics to feel entertained and to be able to enjoy a game (Hartmann & Klimmt, 2006). For this reason it can be assumed that gender-specific digital entertainment-education games need to be produced in order to maximize the games’ potential. Because entertainment-education interventions transport information they are a sort of figurative carrier. To test the effectiveness of a carrier, researchers need to determine whether something is transported. Thus, to test digital games as

2 entertainment-education intervention there must be information about a certain topic included in the game that should be “transported” to the players. Because players should benefit from the information embedded (Wang & Singhal, 2009), using a relevant health topic makes sense. Accordingly, HIV/AIDS prevention seems to be a good topic for the present thesis: Aside from its general importance, it can be implemented specifically for males or females. And because sexuality is an important topic for adolescents – as it meets their developmental tasks in terms of the developmental tasks and education model by Havighurst (1972) – this topic should be of interest to them. As many HIV/AIDS prevention programs focus on men having sex with men, and neglect females being the group with the biggest increase of risk (Welch Cline & McKenzie, 1994), this thesis will test a digital entertainment-education game for female adolescents about HIV/AIDS prevention. Hence the specified research question is: Can a digital entertainment-education game be used to educate female adolescents about HIV/AIDS prevention? To measure the games’ effectiveness, based on the impacts previous entertainment-education interventions have had (Singhal & Rogers, 1999), and what kind of effects can be expected from the game, the following dependent variables are included in the study: It is assumed that the digital entertainment-education game will have an impact on players’ knowledge, interest, and interpersonal peer- communication about HIV/AIDS prevention. Singhal and Rogers (2004) criticize that most previous research on entertainment-education effects was conducted through audience surveys and content analysis of the included messages; experiments were rarely conducted. In the present thesis, an experimental study will be implemented, following the Solomon-four-group-design in order to avoid the typical disadvantage of the before-after design: the sensitization of the participants to the topic in conscious or unconscious ways (Krause & Stark, 2006). Creating a digital game is very complex, time-consuming and expensive. The game created for this thesis cannot be compared to top entertainment games like e.g. Grand Theft Auto. The game created for this study will follow teenage girls’ gaming preferences with the available resources of a PhD-student. But simple games can be very entertaining: For example, Pac-Man is one of the most popular video games ever. It is ranked first among the Top 10 of the most popular games as selected by the KLOV.com (the website of the Killer List of Videogames provided by The

3 International Arcade Museum, 2012) users, although it is rather simplistic compared with other commercial games. If the digital entertainment-education game for this thesis is effective – meaning a significant increase in the dependent variables is measurable – we can conclude that teenage girls can be educated about HIV/AIDS prevention with digital entertainment-education games. This would demonstrate that digital games can indeed be used for entertainment-education interventions, although theories underlying the interactive medium “digital game” are very different from those underlying previously used linear media for entertainment-education. Before the methodology of the present study, its results, and discussion are provided in detail, the theoretical background about the entertainment-education strategy, digital games, and female adolescents is presented: A first chapter focuses on the entertainment-education approach. A historical review of the entertainment-education strategy development in recent years, important definitions, its strengths and challenges – as reported in the scientific literature – are described, followed by theories and models relevant for explaining entertainment- education effects. The effects of entertainment-education interventions are categorized into knowledge, interest, communication, self-efficacy, and behavior, as those variables have been used to study entertainment-education’s effectiveness in previous studies. Next, factors that have been shown to affect or that could potentially affect an entertainment-education outcome are discussed, such as factors concerning the entertainment-education medium itself, the environment, the audience, and the accompanying research that is done while the entertainment-education intervention is conducted. To conclude, ethical considerations concerning the use of entertainment- education are discussed. The following chapter on digital game playing starts with an introduction about play, its definitions and classification, and explains the difference between play and games before focusing on digital games. A short history of digital games is given, followed by definitions and classifications. The question why people like playing digital games is answered; afterwards negative and positive effects of digital game playing are briefly described. The idea of purposefully eliciting positive effects with digital games is the topic of a sub-chapter about serious games. After an introduction, short historical description, and definitions, the specific characteristics of the digital gaming situation are described in order to explain the advantages of serious games

4 compared with traditional education media resulting from the previously mentioned specifics (and, additionally, enjoyment as a factor emerging from those specifics). In contrast to the advantages that result from the comparison between serious games and traditional education media, the disadvantages of serious games become obvious when they are compared to commercial entertainment games. Digital entertainment-education games are slightly different from serious games and rarely researched, and a look at digital games for HIV/AIDS prevention illustrates that the full potential of this field is not yet tapped. Next, aspects concerning girls and digital games are described in detail: girls’ use of digital games, why many commercial games do not address girls as target audience, and what a game should be like in order to be appealing to girls. The following chapter about female adolescents focuses on adolescence as a transitional stage: immense physical, psychological, and cognitive changes take place. After describing the life of female adolescents in Germany, taking into account living conditions, health, and sexuality, the need for new HIV/AIDS prevention strategies is emphasized. At the end of each theory chapter, a summary and a short conclusion about how the chapter contributes to the thesis topic at large (a digital entertainment- education game for girls for HIV/AIDS prevention), are provided. Following the theory section, the development of the research question is described; the main research question is “Can a digital entertainment-education game be used to educate female adolescents about HIV/AIDS prevention?” To measure the successful usage of a digital entertainment-education game, knowledge, interest, and follow-up communication about HIV/AIDS are used as dependent variables. The independent variable is playing the game vs. not playing the game. Additionally, moderator/mediator variables are included that could affect the game’s outcome, namely involvement while playing the game Supergöre, perceived risk of getting HIV/AIDS, and previous experience with digital games. According to the research question and the specified variables, the hypotheses are: Hypothesis 1: Participants in the treatment groups will reach higher levels of knowledge about HIV/AIDS and condom use than those in the groups without intervention.

5 Hypothesis 2: Participants in the treatment groups will achieve significantly higher levels of interest in HIV/AIDS and condom use than the groups without intervention.Hypothesis 3: Participants in the treatment groups will communicate more about HIV/AIDS and condom use than the groups without intervention. Hypothesis 4: The more participants are involved in playing the digital game, the more will they know about HIV/AIDS and condom use after playing the game, and the higher will the levels of interest in and communication about HIV/AIDS and condom use be. Hypothesis 5: The higher the perceived personal risk before playing the digital game, the more will participants know about HIV/AIDS and condom use, and the higher will levels of interest in and communication about HIV/AIDS and condom use be after playing the game. Additionally, several exploratory questions are tested in this study. In the methods part, the reasons for choosing HIV/AIDS as topic for the present study as well as for the creation of the digital entertainment-education game Supergöre for HIV/AIDS prevention are described in detail. Also, the qualitative pilot study that was conducted as a group discussion with six 15-year-old girls to test the entertainment value of the digital game and to test the questionnaires within the target group is described. In the main study, the sample consisted of 75 girls, with 50 girls participating in Bremen and 25 in Cologne. As research design, a Solomon Four-Group design was used to reduce pre-test sensitization. Data reduction and preparation is described before the data analysis and the results are presented. In short, the game Supergöre increases girls' knowledge about HIV/AIDS and condom use but not their interest, communication, self-efficacy, or behavioral intention. A flowchart at the end of the results chapter visualizes the main findings of the present study. This is followed by a discussion of the results, the limitations of the study, future research directions, and indications for practice. At the end it can be finally concluded that digital games can be used as entertainment-education media products.

6 2. Entertainment-Education – a Strategy

“I would rather entertain and hope that people learned something than educate people and hope they were entertained” (Walt Disney, American Cartoonist)

2.1 Introduction and History According to Singhal and Rogers (1999), “the idea of combining entertainment with education is not new: It goes as far back in human history as the timeless art of storytelling” (p. 13; see also Maibach & Holtgrave, 1995). They and other authors state that entertaining activities like music, drama, and dance have been used in many cultures for educational purposes over the past thousands of years (Singhal & Brown, 1996; Singhal & Rogers, 1999, 2003). Piotrow (1994) argues that the basis of entertainment-education rests on Aristotle, because he was the first to write guidelines for moral teaching through the use of drama. Besides Aristotle, other Greek writers made use of traditional drama to address contemporary social problems. For example, the Greek dramatist Euripides wrote one of the earliest “anti-war” plays to address the evils of the Peloponnesian War (Brown & Meeks, 1997). Also the Christian community considered morality plays as powerful evangelical tools during the Middle Ages (Brown & Meeks, 1997). In the 18th century so-called “moral weeklies” [Moralische Wochenzeitschriften] were published as an early form of systematical infotainment (Maar, 1995). Wilkin and Fernandes (2003) stated that “humans have learned values, morals, history, and knowledge of the relationship between men, women, and gods through the Bible, Homer’s poetry, and other forms of narrative” (p. 1). It can be concluded that the idea itself, to combine entertainment and education, is not new, but the entertainment-education strategy is a relatively new concept developed in modern times (Singhal & Brown, 1996; Singhal & Rogers, 1999). In 1927, according to Brown and Meeks (1997), the British Broadcasting Corporation (BBC) was created by royal charter in the UK to “educate and enlighten” (p. 31) the public. The first recognizable entertainment-education interventions broadcast were The Lawsons (in 1944 in Australia) and the BBC radio series, The

7 Archers, in 19511 (Singhal & Rogers, 1999, 2002, 2004). Within the series The Archers, messages about agricultural development were embedded. One of the first television series that can be seen as an entertainment-education program – although it was not planned to be an educational program – was the Peruvian black-and-white television soap opera, Simplemente Maria, broadcast from 1969 to 1971 (Singhal & Rogers, 1999, 2003, 2004). It was broadcast Monday through Friday during prime-time, and each episode lasted one hour (Singhal & Rogers, 1999, 2003). Simplemente Maria was a classic Cinderella-type story of a migrant girl who was able to reach a higher socio-economic status through hard work with her Singer sewing machine and through enrolling in adult literacy classes to learn how to read and write (Singhal, Rogers & Brown, 1993; Singhal & Rogers, 1999, 2003). During the 21 months of broadcasting, four decades of Maria’s life were shown including her wedding as a highlight. Sabina Kamalich – the actress who played Maria – stated in personal communication that Maria’s success “was earned, rather than resulting from winning the lottery or from inheritance” (Singhal & Rogers, 1999, p. 31). The telenovela2 caused a “sewing fever” (Singhal & Rogers, 1999, p. 41) in Peru, and it is reported that Singer earned $20 million in Latin America because of the telenovela’s success (Singhal & Rogers, 1999). Many maids bought sewing machines and enrolled in adult literacy classes as Maria did on television. Of course they did not become rich and famous designers like the character Maria, and thus many were disappointed. This frustration even motivated some women to form a radical group that was called Las Marias and demanded improved payment and better working conditions for maids (Singhal & Rogers, 1999). With Simplemente Maria, a very new entertaining program on television with educational effects was created. The Mexican director, Miguel Sabido, was so overwhelmed by the effects of Simplemente Maria that he tried to understand the mechanisms underlying these impacts and started analyzing the effectiveness of this telenovela. Thus the entertainment-education strategy in television was discovered more or less by accident.

1 According to Singhal and Rogers (1999), The Archers were still broadcast in 1998, meaning that the show ran for 47 years and 12,350 episodes and, hence, “holds the record as the longest running radio serial in the world” (p. 123). 2 Literally “television novels” (Brown & Singhal, 1993, p. 94).

8 In the following years (1975-1982), Sabido produced a series of about half a dozen entertainment-education programs, which were only evaluated “in-house” by Televisa’s Institute for Communication Research, causing some methodological critique in academic circles (Singhal & Rogers, 1999). Singhal and Rogers (1999) report the following generally acknowledged outcomes: Entertainment-education soap operas encouraged enrollment in adult literacy classes, the adoption of family planning, promotion of gender equality, and the like. For example, the Mexican series, Ven Conmigo, was broadcast for about one year in 1976 to raise enrollment in literacy classes. It is reported that during the year of 1976, 839,943 people registered for literacy classes. This was nine times the number of registrants in 1975 and double the amount of those who registered in 1977 (Rogers et al., 1989, cited by Elkamel, 1995, p. 226). Sabido used Bandura’s social learning theory as basis for creating his telenovelas. He designed his own theory for entertainment-education interventions, called the Sabido methodology, which was used by many communication professionals (Singhal & Rogers, 2002, 2004; cf. chapter 2.3.8.1 about the Sabido Method). Besides the entertainment-education program itself, another factor is just as important in successfully educating the audience. Murphy and Cody (2003) mention that Sabido also realized that “the inclusion of health-related storylines could only lead to behavior change if the appropriate infrastructure was already in place to accommodate audience response” (p. 12). During the past several decades, the idea of combining education with entertainment in the mass media has been enhanced and has spread to many countries, especially to so-called “developing countries” in Africa and Asia (Singhal & Rogers, 1999, p.15). The entertainment-education strategy is also used in Western countries, although here the procedure is different. Bouman (2005) suggests that in Western countries no television series exists that meets all entertainment-education criteria, because in most entertainment-education interventions only screen-play participation is arranged. This means that no pre-development of soap operas takes place; instead, educational messages are incorporated into existing programs or screenplays. Bouman (2005, 2004), for example, reports on a Dutch soap opera called Costa! that was broadcast in the Netherlands in 2001 every Monday evening. Its main characters, played by famous actresses, were three young, pretty women in a holiday

9 village in Spain. In cooperation with a Dutch foundation aiming at preventing sexually transmitted diseases (STDs), several scenes with educational intentions were included in Costa! and, hence, the foundation paid 22,500 Euro to the producer, EndeMol Netherland. A rather similar soap opera was broadcast in Germany in the 1990s. The Federal Center for Health Education conducted entertainment-education projects in cooperation with the public broadcasting stations. For example a series called Sterne des Südens [Stars of the South] about a holiday village in Turkey was used to inform the audience about topics like HIV, drug abuse, and pregnancy (Schwarz, 2004). Schnake (2000) mentions two media formats in Germany (Klinik unter Palmen [Palm-lined Hospital] and Tatort – Manila [Crime Scene – Manila]) in which information was embedded to educate audience members about a certain topic. In Klinik unter Palmen [Palm-lined Hospital], a political issue on development aid was included. The German Federal Ministry for Economic Cooperation and Development paid 276,000 DM (about 140,000 Euro) to change the existing story so that an official of the ministry would be included. The aim was to promote the ministry to the public and to show that taxpayers’ money is well spent, e.g., by helping people from other countries who are in an emergency situation.3 The episode Manila of the famous German crime series, Tatort [Crime Scene], was about child trafficking and child abuse tourism. Additional informational material including a documentary film, a book, and a CD-ROM about the topic was available (Schnake, 2000). Recently broadcast on the German TV channel RTL, a popular soap opera called Gute Zeiten, schlechte Zeiten [Good times, bad times] cooperated with the German Federal Center for Health Education concerning the issue of drug abuse. A famous character, Emily, becomes addicted to cocaine and she loses control. In the course of the TV series, different ways of how to get out of the drug scene and how to start a new life are shown. For example, brochures and telephone numbers of a drug help line are visible (Spiegel-Online, 2008; Tagesspiegel online, 2008). RTL reports that they receive large amounts of mail everyday from people who are intrigued by Emily’s story and who want to stop their own drug abuse.

3 The German Federal Ministry for Economic Cooperation and Development was later criticized for wasting taxpayers’ money because of the 276,000 DM paid for the above mentioned measure.

10 The examples mentioned above illustrate how different entertainment- education interventions are implemented in Western countries, compared to “developing countries” where soap operas are exclusively developed for the entertainment-education intervention. In so called “developing countries”, the entertainment-education strategy has been used in recent decades. Singhal and Rogers (2003, 2004) report that, since the early 1980s, more than 200 entertainment- education projects for health-related educational issues in over 50 countries were produced. Many of them cooperate with either Population Communication International (PCI) or Johns Hopkins University’s Center for Communication Programs (Piotrow & Fossard, 2004). In the following sections, a brief overview of the use of entertainment-education in different media is given, illustrating the diversity and the wide-spread use of the approach.

Television Hum Log, an Indian television soap opera, was the first transfer of Sabido’s methodology to Indian television (Singhal & Rogers, 1999). It started in 1984, included 156 episodes in all, and each episode lasted 22 minutes. Hum Log was broadcast for 17 months in the Hindi language, and at the end of each episode a 60- second epilogue about the embedded topic – like family planning, equal status of women and family harmony – was shown. The initial episodes earned disappointing ratings, and after 13 episodes a mid-course correction was implemented. The family planning theme was deleted and the focus was more on status of women, family harmony, and national integration. After these changes were made, Hum Log was popular especially among the Hindi speakers of North India. In all, an average of 60 million people watched each episode of Hum Log. The evaluation was not perfect as only post-hoc research was possible, but a triangulated research strategy was used: 1. Personal interviews with 25 key officials involved in Hum Log were conducted; 2. a content analysis of the scripts was done; 3. a survey of the Indian television audience took place; 4. a content analysis of viewer letters written in response to Hum Log was conducted; and 5. a questionnaire was mailed to a sample of letter writers. In sum, 94% of the viewers thought of the show as entertainment, and 83% said it was educational. In addition, 91% said it addressed social problems.

11 Another outstanding entertainment-education television series is Soul City, which started in 1994 in South Africa. The physician, Dr. Garth Japhet, and Shereen Usdin founded Soul City, and today a NGO, the Institute for Health and Development Communication (IHDC), exists to support it through research and management organization (Tufte, 2001). Soul City is about a fictional South African city and addresses various topics like HIV/AIDS or domestic abuse. The TV series is the “flagship” of Soul City, although an additional radio drama is also broadcast. In addition health brochures, comic books, audiotapes, and posters are available, and a telephone help line can be called. Each year a casting entertainment show called Soul City Search for Stars recruits talents for the next year’s television and radio series, and the “Soul City Health Care Worker of the Year” prize is awarded. Singhal and Rogers (2003) report that an episode of Soul City with a domestic violence story line had an incredible impact. In this episode neighbors started pot- banging in protest of partner abuse, and after this episode pot-banging was reported in several locations in South Africa. Usdin et al. (2004) report that the success of Soul City can be attributed to extensive formative research that was conducted to design the television series. Besides soap operas, talk shows and movies are used for entertainment- education on television. Examples include a talk show format in South Korea for organ donation (Choi et al., 2006) or Good Times with DJ Berry in Uganda as well as movies such as the famous Hollywood production, Philadelphia.

Radio Soaps Sypher, McKinley, Ventsam, and Valdeavellano (2002) point out the educational potential of radio when saying that “past mass communication research suggested that radio is the principle source of family planning information for rural people in developing nations” (p. 196). The BBC not only produced entertainment-education programs but also trained people in other countries on the principles of designing programs like those created by Jamaican Elaine Perkins. She produced popular radio soap operas such as Raymond the Sprayman, broadcast from 1958 to 1959, for the promotion of a mosquito eradication campaign. Literature stated that it was successful, although no summative evaluation was conducted. Another radio soap by Perkins was Naseberry Street, which aired from 1985 until 1989, and focused on the main topic of family

12 planning. Naseberry Street reached about one million listeners or 40% of Jamaica’s total population. Research shows that contraceptive use was higher among listeners compared to non-listeners. What Miguel Sabido did for entertainment-education in television, Elaine Perkins did in radio (Singhal & Rogers, 1999). A very famous African radio soap was Twende na Wakati, which was broadcast in Swahili from 1993 until 1998. It was based on extensive pre-production research, and some scholars call it the best thoroughly researched program in the history of the entertainment-education genre (Singhal & Rogers, 2003). A summary of its effects shows that 23% of listeners reported the adoption of family planning methods in response to having listened to Twende na Wakati; 82% reported adopting a method of HIV prevention, whereas most changed to monogamous sexual relationships. Others adopted the use of condoms or stopped sharing razors and needles (Rogers et al., 1999). This radio soap was quite cost efficient, because it needed less than one US Dollar per adopter of family planning and less than ten cents per adopter of HIV prevention.

Music Rock music, music videos, and celebrity concerts are also used for entertainment- education (Singhal & Rogers, 1999). Music is so widely popular that it is an attractive medium for delivering messages, especially for reaching out to young persons or teenagers. Since the 1980s, the JHU/PCS has used music videos to promote sexual responsibility among young adults in developing countries. In 1986 a project was launched in Spanish-speaking Latin America when two rock music videos were produced to promote teenage sexual responsibility. The songs were called Cuando Estemos Juntos [When we are together] and Détente [Wait] and were produced by PCS. The singers were selected carefully, because their image was a key factor in the effects of entertainment-education music. Tatiana, a 16-year-old singer from Mexico, and Johnny4, a popular 17-year-old boy from Puerto Rico and a former member of Menudo (a famous boy band), were selected for the songs. Cuando Estemos Juntos [When we are together] was number one on popular music charts within six weeks of its release in Mexico, and it became a top-rated song

4 Unfortunately a girl became pregnant because of his irresponsible sexual behavior, and he chose not to marry her. This happened six months after the two songs became popular.

13 in 11 other Spanish-speaking Latin American countries. Thus it was commercially effective and gained huge sales. Radio and TV stations could play the two songs without paying a broadcast fee if they agreed to accompany the music with an announcement of the address and telephone number of a local family planning clinic that offered contraceptive services to teenagers. Summative evaluation showed that the songs informed teenagers about contraception, encouraged teenagers to talk more freely about sex, reinforced teenagers who already decided on sexual restraint, sensitized young viewers to the importance of the topic, and led to a modest increase in demand for services at family planning clinics (Singhal & Rogers, 1999).

Theater Especially in regions where neither television nor radio is available, street theater is a common and effective communication tool. Singhal and Rogers (2003) write about a community street theater in Zimbabwe, the so-called “Chirumhanzu” Home-Based Care Project. The theater worked closely with traditional village leaders, and each drama performance was followed by a discussion about a main topic such as HIV/AIDS. Another example, the Indian street theater, Nalamdana [Are you well?], gave its audience the opportunity to discuss issues mentioned during the play. Usually an open-air performance took place in the evening in a village square or urban slum with an improvised stage and some thousands of audience members. The following day, actors would return to the place to get feedback about the drama and to discuss the issues. This ensures constant learning about audience likes and dislikes, and audience reactions to the drama can be documented directly. For example, it was possible to correct audience members’ misconceptions about HIV/AIDS.

Books/Comics McKee, Aghi, and Shahzadi (2004) describe the famous cartoon figure of a young South Asian girl, Meena. Besides the animated film, comic books and posters of Meena were made available for instance in India, Bangladesh, Nepal, and Pakistan by the Meena Communication Initiative. The production of Meena included two years of formative research to ensure that landscapes, backgrounds, and storylines common to each region were used and to create characters, names, and themes that would apply to a wide audience; “the challenge was to create a character that could be universally

14 loved and identified with across the region” (McKee, Aghi, & Shahzadi, 2004, p. 337). Examples of embedded topics were hygiene and women’s rights. Research has shown that identification with Meena was quite strong among children and that this cartoon character functioned as a positive role model for people from various regional and cultural backgrounds.

As shown above, the entertainment-education approach has been realized with various media products like television, radio soaps, music, theater, or books and comics. Digital games have only rarely been created and evaluated. A few examples of digital entertainment-education games are described in the chapter 3.2.6 about digital entertainment-education games.

This introductory chapter gives a brief overview of the entertainment- education phenomenon. But what exactly is the entertainment-education strategy? How does it work? What effects can be expected? What factors can influence the success of an entertainment-education intervention? Is it ethical to influence people with entertainment-education? These questions will be answered in the following sections.

2.2 Definition, Strengths, and Challenges of Entertainment-Education 2.2.1 Definition First of all, it has to be pointed out that entertainment-education is not a theory but more of a strategy. According to Singhal and Rogers (2002) this strategy is used to distribute ideas that can lead to behavior and social changes. To understand the definition of “entertainment-education”, it is necessary to begin with a short look at “entertainment” and “education” separately. As many different definitions and concepts of entertainment exist (Singhal & Rogers, 1999; Vorderer, 2001, 2003), it can be concluded that there exists no one encompassing definition that covers all aspects. A rather famous definition of entertainment is the one suggested by Zillmann and Bryant (1994). According to them, entertainment is described as “any activity designed to delight and, to a smaller degree enlighten through the exhibition of fortunes and misfortunes of others, but also through the display of special skills by others or self” (p. 438). Singhal and Rogers (1999) – experts in entertainment-education – used the following definition of

15 entertainment, focusing more on the performance aspect of their entertainment- education concept: “we define entertainment as a performance or spectacle that captures the interest or attention of individuals, giving them pleasure and/or amusement” (p.10). Education has also been defined in many different ways. But in the context of entertainment-education, the following definition is especially useful “either a formal or informal program of instruction and training that has the potential to develop an individual’s skill to achieve a particular end by boosting his or her mental, moral, or physical powers” (Singhal & Rogers, 1989, p.10). These two definitions provide background for Singhal and Roger’s (1999, 2003) definition of the entertainment-education strategy, a definition often cited in the literature: Entertainment-education is the process of purposely designing and implementing a media message to both entertain and educate, in order to increase knowledge about an issue, create favorable attitudes, and change overt behaviors. Entertainment-education seeks to capitalize on the appeal of popular media to show individuals how they can live safer, healthier, and happier lives (Singhal & Rogers, 1999, p. 9; see also Singhal & Rogers, 2002, 2003, 2004). 5 In short, entertainment-education is putting educational content into entertainment media messages (Singhal, 1990). Singhal and Rogers (2003, 2004) point out that entertainment-education has the potential to bring about social change in two ways: It can influence individual audience members by changing their awareness, attitudes, and behavior toward a socially desirable aim, and it can have an effect at the group or systemic level by changing the audience’s external environment and creating the necessary conditions for social change. In this case, entertainment-education programs function as a “social mobilizer, an advocate, or agenda-setter, influencing public and policy initiatives in a socially desirable direction” (Singhal & Vasanti, 2005, p. 4). Many different labels exist for entertainment-education. Sometimes it is called edutainment, infotainment, or just enter-education. Pursuant to Singhal and Rogers

5 In 2002 they mentioned a need to adjust this definition of entertainment-education because of its limiting scope. Singhal and Rogers (2002) identified an assumption as problematic, the assumption that behavioral change at the individual level would be the main purpose of the entertainment- education strategy. The problem is that focusing on the individual level contains a risk of mistakenly assuming that all individuals 1) are capable of controlling their environment, 2) are on a level playing field, and 3) make decisions by their own free will.

16 (1999), regardless of the term being used, the basic concept is to join education and entertainment to gain benefits. However there are differences concerning this realization: Compared to infotainment or so-called social marketing (which is concerned with how to sell concepts such as brotherhood in the same way commercial products are sold (Abdulla, 2004), the entertainment-education strategy implies definite pedagogical aims. To achieve these aims, certain topics are systematically embedded in different entertainment media products such as TV and radio programs, music, or comics (see above). This is done to reach as many recipients as possible (Lampert, 2003). In contrast, for example so called “infotainment” is mainly the enrichment of information programs with entertaining elements and, in particular, “emotionally involving” elements (Schwarz, 2004, p. 930). Even though the idea of combining entertainment and education seems to be as old as mankind (cf. chapter 2.1), concerning media products they have been seen as conflictive poles of the same dimension (see Figure 1). This distinction implies that either educational products exist that provide little or no entertainment, or that entertaining products exist that provide little or no education. This view is outdated; the entertainment-education approach shows that it is possible to negotiate this “needless dichotomy” (Singhal & Vasanti, 2005, p.4) and to combine entertaining media products and information successfully so that the result may not be merely educational or entertaining. Thus an entertainment-education intervention can be both: entertaining and educating (Ritterfeld & Weber, 2006). Figure 1 visualizes the differences between the two ways of conceptualization.

Figure 1. Conceptualizations of entertainment and education (Ritterfeld & Weber, 2006).

17 Within the – by now outdated – one-dimensional way of conceptualization, media products range somewhere between entertainment and education. The two- dimensional concept offers the opportunity to locate a media product in the diagram, depending on its characteristics concerning entertainment and education. An entertainment-education media product should be located at the top right corner.

2.2.2 Strengths According to Piotrow (1994), the entertainment-education approach provides several strengths, which he summarized first as “The Rule of 7 P’s” (1994, p.5) and later, in an expanded version with colleagues, as “The Nine Ps of Entertainment-Education” (Piotrow, Kincaid, Rimon, & Rinehart, 1997). They state that entertainment-education programs are 1. pervasive, 2. popular, 3. personal, 4. participatory, 5. passionate, 6. persuasive, 7. practical, 8. proven effective, and 9. profitable6 and thus are an appropriate strategy for successfully educating people.

Pervasive According to Singhal and Rogers (2002), entertainment is becoming noticeably more important in everyone’s life. In many areas of life such as shopping, traveling, eating, driving, or working, entertainment plays a considerable role. Entertainment film and television productions have attained high market penetration (Vorderer, 2001, 2003). For example, in 2007 the German film industry had a business volume of 2.4 billion Euros (statista.com, 2011). People gain knowledge and adapt their behavior as a result of the mass media (Gerbner, Gross, Morgan, & Signorielli, 1986). According to the knowledge gap hypothesis (Donohue, Tichenor, & Olien, 1975) mass media disadvantage people with lower socio-economic status, because compared to them, people with higher socio-economic status receive more information faster by mainly using informational media products. People with lower socio-economic status also receive information, e.g. learn about important health knowledge, but often from entertaining (medical) series (Gerbner et al., 1986; Igersky & Schmacke, 2000). But in case the embedded health information in entertaining medical series is incorrect, it could indirectly contribute to serious health problems for the audience. Thus the information embedded even in

6 These conclusions are mainly based on entertainment-education serial radio / TV dramas.

18 entertainment should be correct, because people adopt fictional content to their real lives (Gerbner, Gross, Morgan, & Signorielli, 1986; Schreier & Appel, 2002). If series are entertaining and include accurate information, they can reach audiences that otherwise could not be reached. Thus, with entertainment-education, even those audiences can be correctly informed. According to Wolf (1999, cited by Singhal & Rogers, 2002), the development toward more entertainment in the media and people’s whole lives can be called “entertainmentization” of the world. The fact that mass media programs are mainly entertainment makes the use of entertainment-education quite logical (Glik et al., 1998, p. 264). Piotrow (1994) points out that we can now have “education as enjoyable entertainment instead of harsh directives or dry prescriptions” (p.4). He even labels entertainment-education as “the Viagra of health communication” (Piotrow quoted in NEEF and JHU/CCP, 2001, p. 2 ), because entertainment- education fits well with the contemporary global trends toward “entertainmentization” and rapidly spreading mass media. Besides the benefit of people liking to consume entertaining programs, they also tend to receive information about personal and health issues from the media anyhow (see above). Thus it is logical to systematically provide media products with reliable information about these issues within entertainment-education interventions.

Popular Entertaining programs like telenovelas or radio soaps reach out to large audiences. Thus entertainment-education can reach out to large voluntary audiences in contrast to mere educational media products (Maibach & Holtgrave, 1995). For example, the entertainment-education TV program, Humraabi (Come along with me), reached an audience of 230 million viewers (Poindexter, 2004); likewise, Heart and Soul, an African TV soap opera, reached an audience of more than 50 million people in 23 African countries (Singhal & Rogers, 2004).

Personal Piotrow (1994) wrote, “Entertainment relies on human interest, characters who share their most intimate ideas, feelings, crises, heartbreaks, and triumphs with their audience” (p.5). Entertainment-education gives the opportunity to show married

19 couples, families, or other persons discussing certain issues. This is more personal, and therefore more effective, than impersonal or formal education programs.

Participatory In TV or radio entertainment-education-programs, people participate by talking to characters, for example by answering questions asked by a character, by singing along to songs played in the series, or by talking with others about characters or story line (in the sense of “follow-up communication”). Within theater or music interventions, people might even sing and dance (Piotrow, 1994). As interactive media products, digital games are participatory by nature.

Passionate Rational arguments and factual information are often not sufficient to cause behavioral changes, but intense emotions are able to change behavior. Piotrow (1994) reports that emotionally intensive sequences can have enormous effects on recipients. For example, in an Indonesian movie, a small girl fell into dirty polluted water, and afterwards she died because of waterborne diseases. Piotrow (1994) states that through this plot “the dangers of too many people living on too little land become real for the viewers” (p. 5), and this creates more effects than mere information about polluted water.

Persuasive Entertainment can persuade – amongst other ways – through audience identification with characters in the drama (Piotrow, 1994). Maibach and Holtgrave (1995) identify a big advantage of entertainment-education as the fact that entertainment can help break down audience barriers and resistance to the educational content. Recipients can be rather skeptical of purely educational programs, resulting in refusal to watch the media product. Maibach and Holtgrave (1995) indicate that “people understand and are receptive to educational messages presented in the context of entertainment experiences” (p.228). Lapinski & Nwulu (2005) points out that defensiveness against formal, fear-based health messages can be avoided by embedding pro-social messages into entertainment programs.

20 Practical Piotrow (1994) argues that, in every country, politicians and professionals are looking for good ideas regarding health education programs, and he also argues that public health experts should form alliances with professional entertainment media producers to create successful entertainment-education interventions.

Proven effective Research provides empirical evidence for the effectiveness of entertainment-education programs (cf. chapter 2.4 about effects of entertainment-education). Entertainment- education can change people’s behavior, the way they think about certain issues, or even their interests.

Profitable Purely educational programs are usually not popular with commercial advertisers (Singhal & Rogers, 1999). However the entertainment-education approach has been very popular and commercially successful in developing countries (Maibach & Holtgrave, 1995; Piotrow, 1994). That entertainment-education programs can be profitable is important – especially for TV and radio shows – because otherwise it can be problematic to obtain timeslots for those programs. As Singhal and Rogers (1999) summarize, “the entertainment strategy thus provides an opportunity for an instructional message to pay for itself and fulfill commercial and social interests” (p.9). On the other hand, commercial advertisements can lead to ethical concerns (cf. chapter 2.6 about ethical considerations concerning the use of entertainment- education).

2.2.3 Challenges – and How to Overcome Them Although the entertainment-education approach provides a number of strengths, several challenges exist that should be taken into account when designing an entertainment-education intervention. As Piotrow and Fossard (2004) report, the Johns Hopkins University’s Center for Communication Programs (JHU/CCP) identifies seven major issues that pose a challenge for transmitting health advice through entertainment-education programs7. They identified these challenges while

7 These conclusions are mainly based on TV and radio series.

21 studying entertainment-education programs in over 40 countries. Nonetheless, their list remains incomplete, as additional challenges certainly exist, such as possible misinterpretation of the educational content, possible weak effects, and ethical concerns.

Too much Education and not enough Entertainment Many people turn to entertainment media as an escape from real-life problems. In case they are too obviously given health or other advice, they might just switch to another program or be skeptical of the entertainment-education intervention. Thus the entertainment-education program should definitely be entertaining enough to attract the target audience.

Too much Entertainment and not enough Education Piotrow and Fossard (2004) point out that a product with too much entertainment and not enough education is probably the most important problem. If a program has too little educational information, it is rather unlikely that it will cause the expected effects. In this case, the entertainment-education intervention would prove rather useless. Therefore it is important to study how much information can be embedded at a minimum and at a maximum in an entertainment-education intervention in order for it to work successfully.

Poor Quality Entertainment In case the quality of the entertainment aspect is poor, entertainment-education interventions might not lead to any desired outcome. Thus, good quality of entertainment is fundamental for the success of an entertainment-education intervention. For this reason the entertainment-education program should be as credible as possible and should attract people so that audience members may watch, hear, or read on a voluntary basis.

Lack of Urgency That many long-term health risks do not have an immediate impact makes them malicious: People do not care about them or they do not believe that they themselves could have health problems caused by their actual health behavior in the future. Since people are more likely to change behavior if they expect immediate dramatic

22 consequences, entertainment-education interventions should be able to show the effects of long-term health risks in an impressive way.

Recommending Routine Actions Most recommendations to reduce long-term health risks are unspectacular; therefore their importance is often underestimated. Thus, entertainment-education interventions need to find ways to overcome this underestimation to illustrate the importance of everyday action, like oral hygiene or washing hands, to enhance the low sense of urgency to the audience members.

No Immediate Personal Relevance People usually ignore health problems that do not affect them, meaning that they tend to ignore health problems they think do not affect them. To make people aware of their risks, entertainment-education should give people a reality check.

Controversies Based on Culture and Tradition The provided educational advice may not follow cultural norms or traditions or even the law, and could therefore cause problems in case of broadcasting. In order to avoid political repercussions in some countries, it is useful to ask for official permission. To ensure that no one is offended, advice should be consistent with culture and tradition. If it is deemed necessary that essential cultural or traditional norms be compromised, entertainment-education design should be sensitive toward everyone, so as not to cause harm.

Misinterpretation of Embedded Educational Content Papa, Singhal, Law, Pant, Sood, Rogers, and Shefner-Rogers (2000) state that an audience can misinterpret educational content and this could even lead to counterproductive effects. One form of misinterpretation that can occur is the so-called Archie-Bunker effect. Archie Bunker was a negative role model8 in the TV series, All in the family, broadcast during the 1970s. The idea behind Archie Bunker was to create a dislikeable character that was highly prejudiced, thus educating people not to be like

8 More information about positive, negative, and transitional role models is provided in chapter 2.3.8.1 about the Sabido method.

23 him (Singhal & Rogers, 1999). Unfortunately the opposite happened; many prejudiced people loved Archie Bunker, and thus All in the family reinforced instead of reduced racial and ethnic prejudice (Vidmar & Rokeach, 1974). Highly prejudiced viewers especially liked this character. The Archie-Bunker effect is defined as the degree to which certain audience members identify with the negative role models in entertainment-education interventions (Singhal & Rogers, 1999, 2004). To reduce the risk of causing an Archie-Bunker effect, it is necessary to research whether an entertainment-education intervention has the potential to cause this effect.

Weak Effects Possible The use of entertainment-education, per se, does not guarantee strong effects. Yoder, Hornik, and Chirwa (1996) find only weak effects when evaluating an entertainment- education campaign (cf. chapter about effects of entertainment-education interventions)

Ethical concerns9 Influencing or manipulating people is a sensitive issue. Therefore entertainment- education interventions should be handled in a responsible way and with care.

To avoid the mentioned problems, solutions have been suggested within the entertainment-education approach, and some of these are already mentioned above. The key issue, however, is proper evaluation. As Glik et al. (1998) note, some TV series with embedded health information – for example, Emergency Room or General Hospital – have won awards for their sensitive coverage concerning health-related topics, but few shows have been formally evaluated to assess audience impact. A positive example is Sesame Street; a major reason for its success is the intense evaluation with positive results (Singhal & Rogers, 1999). Only evaluation of the various entertainment-education media products can provide evidence for impact and bring forward the state of knowledge about entertainment-education. Sood, Menard, and Witte (2004) write that ”a first step in implementing an entertainment-education strategy is formative evaluation, a method of analyzing target audiences to determine their needs, desires, behaviors, and media

9 Read more about ethical issues in chapter 2.6 about entertainment-education and ethics.

24 usage in order to develop understandable, high-quality, culturally appropriate characters and storylines” (p. 133). Greenberg, Beck, Salmon, Cole, and Patel (2004) propose to follow the below mentioned instructions in order to properly evaluate an entertainment-education program (p. 201):

1. Determine if the specific information in the message is salient enough to be recalled with or without prompting 2. Determine if the issue related to the specific information has a high priority for persons. 3. Assess the credibility of the information received. 4. Assess the credibility of the information resource. 5. Find out if the viewer is better informed than prior to exposure. 6. Determine if the message stimulated or strengthened interest in the issue presented. 7. Evaluate any possible change in attitude toward the issue. 8. Determine if any subsequent behavior occurred as a result of the message.

This list can be supplemented with the following points: Singhal and Rogers (2004) mention that the selected medium should be suitable for the target audience. Furthermore the design should be as specific to the target group as possible. In this context, Yahaya and Olajide (2003) point to the importance of entertainment- education intervention being gender sensitive. Entertainment-education is a communication strategy, capable of influencing cognitive, affective, and behavioral outcomes. Aside from its strengths, several challenges need to be taken into account. Systematic evaluation of entertainment- education media is absolutely necessary to optimize the outcome and to understand why it works – or sometimes why it does not work. Also important to an understanding, many theories and models provide a basis for the entertainment- education strategy. The most important theories and models are described in the next subsection.

25 2.3 Theories Underlying Entertainment-Education 2.3.1 Introduction As described in the section about entertainment-education’s definition (cf. chapter 2.2.1 “Definition”), various definitions of “entertainment” exist. Zillmann and Bryant (1994) give a broad definition of entertainment: If Entertainment is crudely defined as any activity designed to delight and, to a smaller degree, enlighten through the exhibition of fortunes and misfortunes of others, but also through the display of special skills by others, and/or self, it becomes clear that the concept encompasses more than comedy, drama, and tragedy. It engulfs any kind of game or play, athletic or not, competitive or not, whether witnessed only, taken part in, or performed alone (p. 438). Several aspects of entertainment can be explained with this definition, but this definition is not all-embracing. Vorderer (2003) writes: If we look at the diversity of entertainment experiences that result from the uncountable combination of different users, different social situations and cultures, and different media offers, we get a clue as to what still has to be done if we want to move further on Zillmann’s tracks toward a better understanding of entertainment (p. 143). This shows that not even one definition or theory can comprise all aspects of entertainment. Therefore it is hardly possible to have an overall entertainment- education theory that would provide a detailed explanation of how it works for several media types, audiences, and situations. Nevertheless various theories and models can be consulted, which can attempt to explain how and why entertainment-education can have certain effects. Especially useful are theories that explain behavioral change, but also learning theories and theories of mass communication. As Singhal and Rogers (2004) report, most researchers – apart from some exceptions – in the past used Bandura’s social learning theory as a theoretical basis for their entertainment-education research. Although some theories exist that try to combine different aspects of other theories and models simultaneously, no all- embracing theory for entertainment-education, which would apply to all possible media, is elaborated yet. Because entertainment-education is a rather practically oriented strategy, most research has focused on the question of whether entertainment-education works or

26 not, but researchers increasingly claim that more theoretically-based research should be done to find out how it works (Singhal & Rogers, 2002). Sood, Menard, and Witte (2004) give an overview of the empirically-based, peer-reviewed theoretical research on entertainment-education. They took into account about 25 studies conducted from 1990 to 2002. Almost all findings are based on TV or radio soap operas and cannot be transferred to other mediums such as digital games10. No systematic overview exists yet that would provide theories behind entertainment-education based on medium. The theories and models most often used for explaining entertainment- education are described below. This description is based on the above-mentioned chapter by Sood et al. (2004). Additionally the cultivation theory, the Sabido method, the health action process approach by Schwarzer (2008), and Wilkin and Fernandes’ (2003) integrative model of entertainment-education are described, as some literature also mention them as theoretical background for entertainment-education interventions (e.g. Singhal & Rogers, 2002; Sabido, 2004). It would go far beyond the scope of this chapter to present all listed theories in detail; hence the most reputable theories and models are elaborated, and others are described briefly. On the basis of Sood et al. (2004), theories behind entertainment-education are divided into seven categories: 1. models with steps/stages, 2. social psychological models, 3. cognitive models, 4. drama and role models, 5. audience-centered models, 6. contextual theories, and 7. hybrid models.

2.3.2 Models with Steps/Stages In this section, relevant theories are summarized that focus on the steps or stages that individuals pass through in the process of adopting and maintaining a new type of behavior. They are useful in understanding the process of change, and they help in the design of messages that may fit the intended target group (Sood et al., 2004): McGuire’s hierarchy-of-effects model, the stages-of-change model originally developed by DiClemente and Prochaska, and Rogers’ diffusion of innovations theory.

10 Only one of the included studies, namely Thomas, Cahill, & Santilli (1997), uses an interactive computer game for entertainment-education.

27 2.3.2.1 Hierarchy-of-Effects Model According to Sood et al. (2004), McGuire’s hierarchy-of-effects model takes into account several factors concerning input and output. It is presented as a diagram with an x-axis for input factors and a y-axis for output factors. Outcome factors include the steps an individual has to pass through for behavior change. These steps are 1. exposure to the message, 2. attention to the message, 3. interest in, or personal relevance of, the message, 4. understanding of the message, 5. personalizing the behavior to fit the individual’s life, 6. accepting the change, 7. remembering the message and continuing to agree with it, 8. being able to think of the message, 9. making decisions based on bringing the message to mind, 10. behaving as decided, 11. receiving (positive) reinforcement for behavioral change, and 12. accepting the behavior into the individual’s life. McGuire (1978) argues that numerous input factors can affect the success of each step mentioned above. For example, characteristics of the message source or the design of the message can influence the outcome. Singhal and Rogers (1999) adapt the model and present a hierarchy of media effects they refer to when reporting effects of entertainment-education interventions: In the first stage – the so-called “Knowledge Stage” – the audience is exposed to message content and becomes aware of the shown message content; audience members should be able to recall the message. Thus the audience is informed about message content, understands this content, and learns about knowledge skills for practicing the recommended behavior. The second stage is called “Persuasion Stage,” when the audience is persuaded by the message content; audience members start to like the recommended behavior, discuss the new behavior with others, are in agreement with the message, and are supported by the local community regarding their new behavior. In the third stage, the “Decision Stage,” audience members intend to change their behavior. Usually they intend to seek additional advice and to practice the new behavior. The “Implementation Stage” is the fourth stage, when the behavioral change takes place. Audience members acquire additional advice and practice the new behavior. The fifth and last stage is the “Confirmation Stage.” Now the audience maintains the behavioral change by recognition of benefits of the new behavior; the new behavior becomes routine, and audience members promote the new behavior to others.

28 2.3.2.2 Stages-of-Change Model This model assumes five major stages for behavioral change, namely, pre- contemplation, contemplation, preparation, action, and maintenance (Prochaska, Norcross, DiClemente, 1957): 1. Pre-contemplation: In this first stage, individuals do not have any intention to change their behavior. The majority of people are unaware of their problematic behavior or they underestimate it. 2. Contemplation: In the second stage individuals are aware of their problem and think about a change but have not yet taken any measures. 3. Preparation: Individuals at this stage have the intention to take action in the next weeks and plan how to do this. 4. Action: People actually do modify their problematic behavior to overcome their problems. This stage usually costs the individuals the most time and energy. 5. Maintenance: Individuals show the newly learned behavior consistently and try to avoid a relapse. As Figure 2 shows, people might go through all five stages several times11 before behavioral change is permanent and individuals perform a stable behavior (this is a difference in comparison to the hierarchy of (media) effects model); thus entertainment-education programs should take this circular process into account.

Figure 2. Stages of change model (retrieved from http://www.addictioninfo.org/articles/11/1/Stages-of-Change-Model/Page1.html).

11 It is also possible that individuals do not repeat all five stages, or only some of them before behavioral change is permanent.

29 2.3.2.3 Diffusion of Innovations Theory Winterhoff-Spurk (1999) identifies the initial point for the diffusion of innovations theory in the two-step flow model (see below), because here opinion leaders spread media messages to other individuals. The diffusion of innovations theory by Rogers (1962) explains the process of individual adoption of ideas, practices, and objects and their diffusion within society (Schweiger, 2007). Thus it explains how an innovation – like a message embedded in an entertainment-education program – migrates from creation to use. Sood et al. (2004) mention that this theory “defines diffusion as the process by which an innovation is communicated through certain channels over time among members of a social system” (p.124). Until today various authors define various numbers of stages for the diffusion of innovations theory (Schenk, 2002; Rogers & Shoemaker, 1971). Katz, Levin, and Hamilton (1963) identify seven elements that specify the above mentioned definition and are important for a diffusion process: 1. Acceptance, 2. within a certain time frame, 3. of specific innovations, 4. through individuals, groups or others, 5. connected with specific communication channels, 6. among each other and with the social structure of the group, and 7. within a certain value system. Usually the dynamics of a diffusion of innovations can be described as follows: After a start-up period, in which only a few innovators and early adopters take on the innovation, the majority becomes interested in the innovation and adopts it. Late adopters take innovation on when almost all other people already have it or use it (Schweiger, 2007).

2.3.2.4 Summary – Models with Steps/Stages The models with steps/stages point out that behavior change is a process that include several primary steps/stages before the actual behavior change takes place. Basing on this view of behavior change also proceeding pre-steps/stages can be classified as positive impacts of entertainment-education. Depending on the model used, different aspects of this process are pointed out as relevant pre-steps/stages for a consistent behavior change. McGuire (1978) points out within his hierarchy-of-effects model that before knowledge can be imparted, it is important that the individual is attended and has interest in the topic. In contrast, Singhal and Rogers (1999) directly start their hierarchy-of-effects model with the knowledge stage where information is given to an individual. However, they add the aspect of discussing the topic with others as important point of the persuasive stage. These aspects – knowledge, interest, and

30 communication – have shown to be important for a behavior change process and will therefore also be used as indicators for the effectiveness of the present study (cf. chapter 6.3). Mentionable in contrast to the hierarchy-of-effects model, the stages-of- change model (Prochaska et al., 1957) considers the way to stable behavior change as a circular process that needs to be repeated. Thus it is useful to create an entertainment-education product in a way that is has an inherently stimulative nature so that the message is released and repeated several times to keep the circular behavior change process going on. As digital games are considered to be stimulative, they seem to be a good medium to make individuals voluntarily deal with the intended topic. The diffusion of innovations theory does not refer to the process of behavior change an individual has go through, but the way an innovation diffuses into a group. Therefore this theory is not relevant for the present study as it is aims at testing whether individuals can be influenced by a digital entertainment-education game.

2.3.3 Social Psychological Theories In social psychological theories, the expected behavioral outcome is influenced by perceptions, beliefs, attitudes, and values of an individual and by elements of the social environment. An outcome can explain why entertainment-education interventions do not always work for everyone, and it can provide researchers with the opportunity to measure attitudes or beliefs so as to adjust a program adequately (Sood et al., 2004). Discussed examples of social psychological theories are Bandura’s social learning theory, the theory of reasoned action by Fishbein and Ajzen and its successor – the theory of planned behavior, the health belief model by Becker and Rosenstock, and the Health Action Process Approach (HAPA) by Schwarzer.

2.3.3.1 Bandura’s Social Learning Theory – Social Modeling Singhal and Rogers (2004) indicate that “a natural fit exists between Bandura’s theory and entertainment-education interventions” (p. 12). In the past, Bandura’s social learning theory was the theory most often used to explain entertainment-education effects. According to Bandura (1977), three major processes enable human beings to integrate themselves into social environments and to influence those environments. First of all,

31 individuals can observe other persons and imitate the observed behavior. Second, individuals are able to symbolize observations, events and experiences. This symbolization enables individuals to remember, think, organize, and be creative. Third, individuals are able to regulate themselves and modify their behavior by producing self-made incentives and consequences. Bandura (1977) points out that these processes account for the freedom of human beings to take their lives into their own hands. Based on these three processes, there are two basic modes of learning: First, people learn through the direct experience of reward and punishment as consequences of their own behavior, or second, they learn through the power of social modeling (e.g., Bandura, 2004). Social modeling means that the learner acts as observer and the observed person functions as a model, where the type of model observed is irrelevant (i.e., real-life, televised, or virtual). The observer learns by watching and imitating the model. This assumption is not new; even Aristotle noted thousands of years ago that the way people learn is by watching and imitating others (Piotrow & Fossard, 2004), but it is Bandura’s merit that a theoretical background for this observation has been achieved (Schenk, 2002). Four sub-processes – divided into the two phases of acquisition and performance – can be seen as necessary conditions for effective modeling (Bandura, 1971, 1977, 1986, 2001; see Figure 3):

I. Acquisition 1. Attentional Processes Individuals are confronted with a variety of behaviors performed by others. Attentional processes determine which modeled behavior will be selected for observation and which aspects will be taken into account. For successful social modeling, it is necessary that the observer concentrate only on important aspects of the modeled behavior and that she or he be able to perceive it exactly (Bandura, 1977). The observer selects certain aspects of the attractive model’s behavior – usually those aspects that seem to be useful for him/her – and observes them. A model can be a concrete person, but it can also be a fictional character in a book or film. Whether attention is high or low depends on several aspects:

32 1. Model characteristics: Research shows (e.g., Bandura, Ross, & Ross, 1963) that persons with social power – meaning such people who can punish or reinforce – are more often used as models compared to powerless people. Persons with social power include those who can punish or reinforce, those with high prestige, likeable and attractive persons, or those who can supply observer’s needs. 2. Behavioral characteristics: Attentional processes are influenced by characteristics of the modeled behavior itself, for example, the noticeability or complexity of it. 3. Observer characteristics: Sensory capacities, arousal level, motivation, perceptual set, past reinforcement, and the like influence the act of observation. For example, low self-efficacy and/or self-esteem usually lead to higher attention paid to a model. Furthermore, observation is influenced by certain aspects of apperception, e.g., experiences, interest, values, emotions, or moods. 4. Relationship between model and observer: A positive relationship and interdependence of observer and model encourage imitation.

2. Retention Processes The observed behavior must be cognitively organized in schemata, so that it can easily be remembered (Bandura, Grusec, & Menlove, 1966; Gerst, 1976). Either a new scheme has to be developed (accommodation) or an old one has to be adjusted (assimilation). The observed behavior can be kept in mind via visual codings or via symbolic/verbal codings. As soon as the observed behavior is transformed into such visual or symbolic/verbal codes, these codes can control the conduction of the previously observed action. Additionally, symbolic and motoric rehearsal take place, whereas mental repeating is an especially effective memory aid.

II. Performance 3. Motor Preproduction Processes The observer is attracted toward a behavior, remembers the observed behavior, and tries to imitate it. The aim is to implement symbolic codes into adequate activity. Depending on his/her creativity, the observer is more or less able to adapt the observed scheme to new situations. In principle, the observer must be able to replicate the observed behavior. For example, playing basketball cannot be learned by watching a model if the observer is not able to throw or catch a ball.

33

Figure 3. Sub-processes of observational learning and influencing factors (Bandura, 2004).

4. Motivational Processes The social-cognitive learning theory distinguishes between acquisition and accomplishment, because individuals are unable to put all observed behavior into action. When a specific observed behavior is imitated, the observer reflects on the success of his/her new behavior compared to his/her expectations. When the new behavior is successful in the observer’s eyes, then s/he will be motivated to repeat it. If it was unsuccessful, the new behavior would not be repeated and thus, would not be learned effectively. Different kinds of motives for imitating behavior exist: 1. external reinforcement – in which an individual’s behavior is reinforced by other persons or instances – can influence an observer’s motivation to repeat an observed behavior (where commendation works better than punishment), 2. vicarious reinforcement, meaning that somebody else’s behavior will be reinforced and the observer expects the same consequences for the case that s/he were to act in the same way (Walter & Parke, 1976), and 3. self-reinforcement, where individuals influence themselves by developing norms concerning specific behaviors and reward or punish themselves relating to their performed behavior.

34 Self-efficacy. Apart from the sub-processes described above, Bandura later started to indicate that other factors are also important for social modeling (Bandura, 2004). He writes among the mechanisms of self-influence, none is more central or pervasive than beliefs in one’s efficacy to exercise control over one’s functioning and events that affect one’s life. The core belief system is the foundation of human motivation and accomplishments. (Bandura, 2004, p. 78) In his self-efficacy theory, Bandura (1977) considers the concept of self-efficacy as a central function of psychological behavior (see Figure 4). Self-efficacy can be defined as an individual’s perception of his or her capability to deal effectively with a situation as well as the individual’s sense of perceived control over a situation (Bandura, 1977, 1997). And Bandura (1977) defines differentiated outcome expectancy as “a person’s estimate that a given behavior will lead to certain outcomes” (p. 193). Therefore perceived self-efficacy is an important condition for the success of social modeling, as well as outcome expectancy. In this context Green (2006) writes that “seeing similar others succeed at a task provides confidence to viewers” (p. 166). Thus if a person is unable to believe that s/he can cause the desired effects by his/her own behavior, s/he has no reason to try to imitate the observed events. In this way, low perceived self-efficacy influences motivation by putting the goals of learning into question and by negative outcome expectations (Bandura, 2004; Singhal & Rogers, 1999). Bandura (2004) mentions four different ways in which people’s beliefs in their efficacy can be improved. These ways are 1. mastery experience, 2. social modeling, 3. social persuasion, and 4. interpretation of physical and emotional states. Bandura (2004) points out that the most effective way to improve one’s self-efficacy is through mastery experience, and the second most effective way is through social modeling. Therefore, if individuals are to learn a specific behavior through social modeling, the model and other factors such as the environment should be observed in a way that the observer’s perceived self-efficacy is increased, creating an attitude of “If s/he can do it, I can do it.” According to Singhal and Rogers (1999) “many types of desired behavior change […] can result from individual-level self-efficacy” (p. 150). Besides the importance of an individual’s self-efficacy, collective self-efficacy is also important. Collective self-efficacy can be defined as the degree to which

35 individuals in a system believe they can organize and execute courses of action required to achieve collective goals (Bandura, 1997; Papa et al., 2000). Social change is often based on changes of collective self-efficacy (Singhal & Rogers, 1999).

Figure 4. The relation between self-efficacy, outcome expectancy, and behavior as mentioned by Bandura (Zimmermann, Noar et al., 2005, p. 7).

Bandura’s Social Learning Theory and Entertainment-Education Although mastery experience is the most effective way to learn and increase self- efficacy, many people watch TV or use other media several hours per day, which reduces time for their own experiences. Therefore “media representations gain influence because people’s social constructions of reality depend heavily on what they see, hear, and read rather than on what they experience directly“ (Bandura, 2004, p. 78). As media have an enormous influence, they can be used to influence people in the desired ways: The media present models that the audience should observe, and thus the audience should learn the modeled behavior. Bandura (2004) writes the “media program model how to translate a vision of a desired future into a set of achievable subgoals” (p. 81). Dramatic series are useful for social modeling, as their construction draws “on the basic principles of social cognitive theory” (Bandura, 2004, p. 82). Bandura (2004) points out that especially everyday topics or problems taken from audience members’ real-life experiences illustrating how characters struggle, suffer, and search for practical solutions “provides people with incentives, support, and strategies for bettering their lives” (Bandura, 2004, p. 85/86). Bandura (1997) identifies three types of social modeling that are directly related to the three

36 types of modeling used in the entertainment-education approach (Sabido, 2004; Bandura, 2004; Singhal & Rogers, 1999): 1. positive role models (likeable persons who show the desired behavior and who will be rewarded), 2. negative role models (dislikeable persons who perform the wrong behavior and who will be punished), and 3. transitional role models (undecided persons who will change into positive role models over the episodes). Identification with a character (for example, identification with the positive, likeable role model) can foster an individual’s perceived self- efficacy; thus it is important to “consider how exactly the program will foster self- efficacy” (Wilkin & Fernandes, 2003, p.19) when designing an entertainment- education media program. The socio-cognitive learning theory by Albert Bandura is mainly used for entertainment-education programs aired on radio or TV. Thus transferring it to another medium like digital games can involve difficulties.

2.3.3.2 Theory of Reasoned Action & Theory of Planned Behavior The core of the theory of reasoned action (Fishbein & Ajzen, 1975) is that certain beliefs produce attitudes concerning behavior and individuals’ subjective norms, and these attitudes/subjective norms influence/predict intentions, which influence/predict behavior (see Figure 5; Stroebe, 2000; Hornung, 1997; Bansen-Engquist & Parcel, 1992). Such attitudes consist of beliefs and persons’ evaluations of these beliefs. Subjective norms also consist of beliefs – especially beliefs of what other persons think about certain behaviors – and the motivation to be consistent with others’ expectations (Stroebe, 2000). In this sense, the more an individual perceives that his/her significant other(s) thinks he/she should perform a certain behavior, the more he/she will be likely to do so. This shows that entertainment-education, in an ideal case, should not only have effects on the individual level but also on the societal level, so that individuals believe that the new behavior is accepted or even expected from the community. Sood et al. (2004) write: the more positive the evaluation of behavioral beliefs and the stronger the motivation to comply with perceived norms, the greater the intention to perform a recommended response and the greater the likelihood that the desired behavioral response is actually performed (p. 125).

37 According to Zimmermann et al. (2005), the theory of reasoned action is the psychological theory most frequently used to explain health behaviors like condom use. The theory of planned behavior is an extension of the theory of reasoned action; Ajzen (1988) argues that intention cannot be the exclusive determinant of behavior, in case an individual’s control over the behavior is incomplete (so-called non-volitional control). Ajzen (1988) includes perceived behavioral control,12 in addition to attitudes and norms, as another predictor of health behavior change. Perceived behavioral control can be defined as a person’s beliefs about the degree of volitional control he/she has over a given action, which can have both a direct influence on behavior and an indirect effect through behavioral intention (see Figure 6).

Figure 5. Schematic presentation of the theory of reasoned action (Zimmermann et al., 2005, p. 6).

Figure 6. Schematic presentation of the theory of planned behavior (Zimmermann et al., 2005, p. 6).

12 This concept is very similar to the construct of “self-efficacy” according to Bandura (1977).

38 2.3.3.3 The Health Belief Model The health belief model is a value-expectancy theory developed in the context of health-related behaviors (Janz, Champion, & Strecher, 2002). It can be seen as an important forerunner model of modern health behavior models (Schwarzer & Renner, 1997; Hornung, 1997). The model is widely used to understand preventive health practices. In this model, Rosenstock (1966) assumes that a person engages in a specific health behavior if 1. the person believes that he/she is susceptible to the particular disease and if 2. the person realizes the severity of the consequences of getting the disease. Susceptibility and severity determine the perceived threat of the disease, which can also be called vulnerability (Stroebe, 2000). In addition to the perceived threat, the engagement in healthy behavior depends on the individual’s perceived benefits of the health action outweighing the perceived barriers associated with the health action. The model contains four key beliefs. Perceived susceptibility to the illness and perceived severity of it are the two components of perceived threat. To determine outcome expectancy, perceived benefits of a specific health behavior for decreasing threat are weighed against perceived costs or barriers for engaging in the action. Lastly, these components lead an individual to the stage of decision-making (Zimmermann et al., 2005). Therefore entertainment-education interventions should address these four key beliefs so that individuals can reach the stage of decision- making. In simple terms, the health belief model assumes that individuals conduct a cost-benefit calculation, that they weigh benefits of a behavior against barriers to being able to show the behavior. A behavior will be performed in case that the benefits are perceived as stronger than the barriers. Therefore the lack of behavioral change toward positive, healthy behavior can be explained through the perceived barriers to the desired behavior (Sood et al., 2004). In 1974 Rosenstock (cited by Stroebe, 2000) further proposed that it would be useful to include a “cue to action,” as a behavioral change might need an impetus. Such cues to action can be of internal or external nature. According to Zimmerman and Vernberg (1994) – compared to the theory of reasoned action and Bandura’s social cognitive theory – the health belief model is less powerful in explaining behavioral change, because research found inconsistency in applying the model to predict health-related behaviors.

39

Figure 7. The health belief model by Rosenstock, 1974 (Zimmermann et al., 2005, p. 9).

2.3.3.4 The Health Action Process Approach (HAPA) As entertainment-education is often concerned with health issues, health behavior theories can help to understand behavioral changes concerning such health issues. One of the modern health behavior theories is the health action process approach (HAPA) developed by Schwarzer (1992, 2001, 2008). It is a social-cognitive process model that divides the process of health behavioral change into two phases, a motivation phase and a volition phase (see Figure 8). Important predictors for health behavioral change in this model are 1. perceived self-efficacy, a basic requirement for health behavioral change that plays an important role at all stages; 2. risk perception, important in laying the foundations for a contemplation process at the beginning of the motivation phase; and 3. outcome expectations, important in the motivation phase when a person calculates the costs and benefits of the intended behavioral change (Schwarzer, 2008). In the motivation phase, people form intentions influenced by their perceived self-efficacy, outcome expectations, and risk perceptions. These intentions have to be transformed into realizable actions, done by planning the first step of the volition phase. This is followed by an initiation, the point when persons start to perform the intended behavior. To be successful in the long run, it is important to be persistent – here, maintenance plays an important role – and to be able to recover in case of unanticipated difficulties that may disrupt the new behavioral pattern.

40

Figure 8. The health action process approach (HAPA) by Schwarzer (Schwarzer, 2008; retrieved from http://userpage.fu-berlin.de/~health/hapa_figures.pdf).

2.3.3.5 Summary – Social Psychological Theories The social psychological theories provide models for behavior change that are more complex than the steps/stage models of behavior change because they include more influencing factors concerning the individuals’ inside view on the one hand and factors concerning the social environment on the other hand. Bandura’s social learning theory is mainly useful for soap operas or similar media products, but it points out a persons’ perceived self-efficacy as fundamental influencing factor. Within the theory of reasoned action and the theory of planned behavior the so called perceived behavioral control is an important aspect for behavior change and it is similar compared to Bandura’s concept of self-efficacy. Consequently it is meaningful to include perceived self-efficacy as influencing factor in the present study. The health belief model points out another factor in addition to perceived self- efficacy that influences the process of behavior change. Here vulnerability, which consists of perceived susceptibility and perceived severity, is a relevant factor for behavior change. This is related to perceived personal risk perception as shown within the health action process approach (HAPA). Thus it makes sense to include perceived risk perception as factor in the current study.

41 According to the health belief model people do a cost-benefit calculation to assess whether a behavior change would be beneficial or not; this means they have expectations concerning the outcome of their own behavior. Also within the HAPA peoples’ outcome expectations are an important factor that influences behavior change. A cost-benefit calculation or to contemplate about outcome expectations seem to be conscious actions. But entertainment-education usually works because of unconscious processes taking place within an individual. Hence it is not promising to include outcome expectations as factors in the present study.

2.3.4 Cognitive Models Cognitive13 models can explain the internal cognitive processes and workings of the mind. They show that people’s predispositions and cognitive schemata have to be taken into account when developing an entertainment-education intervention. Sood et al. (2004) mention amongst others the following theories as important cognitive models in explaining entertainment-education intervention effects: the elaboration likelihood model by Petty and Cacioppo (1986) and the triune brain perspective by MacLean (1990).

2.3.4.1 Elaboration-Likelihood Model of Persuasion (ELM) The elaboration-likelihood model (ELM; Petty & Cacioppo, 1986) deals with people’s information processing and how the processing can cause persuasion effects. The term “elaboration likelihood” refers to individuals’ commitment to think about certain issues, meaning that they perform “issue relevant thinking” (Schenk, 2002, p. 253). The ELM suggests that information can be processed in two different ways (see Figure 9), either along the central path or along the peripheral path (also known as the heuristic route). Which path is used depends upon a) a person’s motivation in the sense of issue involvement and b) his/her ability to process a message. If a person is motivated and able to process a message, then the central path is used. This means that the individual thinks carefully about, elaborates, and critically evaluates the message (Sood et al., 2004; Wilkin & Fernandes, 2003; Schenk, 2002; Schweiger, 2007). This can lead to stable and sustained attitude and behavioral changes. Schenk

13 Sood et al. (2004) call this section „Psychological Models“, but as many of the other sections include psychological models as well, the term “cognitive models” was chosen instead.

42 (2002) points out that, within the ELM, it can be assumed that involvement leads to deeper processing, which determines persuasion effects. In the other case, if a person is not motivated and is unable to process the message, the peripheral path will be used. Then the person will not carefully process the information and might rely on heuristic cues when s/he deals with arguments in a message (Sood, 2002). The outcome here is rather unstable and might change again if a new message is perceived. However, Shrum (2002) points out that the peripheral path can lead to a persuasion effect as well if certain circumstances are given. Thus, even if an entertainment-education intervention does not succeed in engaging the audience through the central path, “the persuasive effort of the program is not necessarily lost; heuristic cues in the programming may still have some effect on the audience” (Wilkin & Fernandes, 2003, p. 9).

Figure 9. Schematic diagram of the Elaboration-Likelihood Model (Hogg & Vaughn, 1995, p. 205).

43 The traditional ELM can be seen in the context of issue involvement; in other words, the kind of involvement is important for the path that is used. Slater and Rouner (2002) extend the ELM and place it in the context of narratives. Within this extended ELM, no clear distinction between central and peripheral processes is possible. Slater and Rouner (2002) demonstrate that by including engagement (a.k.a. absorption14) and identification as important factors in the concept of the ELM, it can be expanded and can help to understand entertainment- education effects. Within the central processing route, counterarguing may take place; engagement with the story line and identification with characters can block counterarguing so that persons who would usually be resistant to persuasion will be influenced as well. Slater and Rouner (2002) even state that “absorption in narrative and counterarguing are fundamentally incompatible” (p. 180). The reason behind this is that counterarguing can stop the suspension of disbelief that is necessary for absorption of a narrative (Slater, 2002). The success of an entertainment-education program can be explained with the extended ELM because of its engaging narratives. These narratives can have an “intensity that most creators of didactic messages could only dream of inducing” (Slater & Rouner, 2002, p. 187), and “absorption in the narrative may motivate deeper processing of a different kind” (p. 187). Thus “involvement with the issue topic is probably less important than involvement with the narrative story line in moderating persuasive effects of the message” (p. 187).

2.3.4.2 Theory of the Triune Brain The basic assumption of the theory of the triune brain (MacLean, 1990) is that persons process messages in three different ways via three different brain centers being engaged (see Figure 10): 1. cognitively in the neo-cortex, which means “thinking”; 2. affectively in the visceral cortex (limbic or mammal brain), which is connected to emotions; and 3. animalistically in the reptilian cortex, where physical needs are positioned.

14 According to Slater and Rouner (2002), “Engagement, absorption, and transportation are three terms used by different researchers to describe the same phenomenon. Each concept is the degree to which a message recipient is cognitively and affectively invested in a narrative. By invested we mean that attention is fully engaged and emotional responses are occurring consistently with the vicarious experience of the fictional events” (p. 179).

44 The effect of a message depends on the way it is processed. Health education usually focuses on cognitive messages but, to be successful, messages should be processed through all three brain centers (Singhal & Rogers, 1999). Therefore entertainment- education interventions should be designed to address all three brain centers. Sabido (2004) describes this process in the following way: When energy goes to the reptilian brain, we are blind victims of our drives, our instincts. When energy goes to the emotional circuits of the mammalian brain, we are moved to identify with a figure (like a telenovela character) that we believe is similar to us, and we react emotionally. When energy goes to our third brain (neo-cortex), we process reality in an intellectual, calculating way (p.65).

Figure 10. The theory of the triune brain (retrieved from www.chekinstitute.com).

2.3.4.3 Summary – Cognitive Models The two cognitive models presented in this sub-section demonstrate that the way information is processed matters in regard to the effectiveness of an entertainment- education product. According to the classical ELM, the degree of issue involvement determines the processing route and thus the possible effects. The extended ELM

45 points out the importance of engaging narratives for the success of an entertainment- education intervention. The classical ELM model and the extended ELM model are like the cognitive way and the affective way of information processing in the theory of the triune brain. In the latter theory, an additional third way, the animalistic way rooted in the reptilian cortex, is taken into account. The ELM and the theory of the triune brain show that different ways of processing are possible and that a successful entertainment-education product should address at least cognitive and affective processing.

2.3.5 Drama and Role Theories Drama and role theories focus on the roles people play in their lives and the scripts they follow during their lifetime. These theories can provide developers and producers of entertainment-education programs with ideas for successful stories in the form of common legends or folktales. For example, Bentley’s dramatic theory, states that five types of theatre genres exist: tragedy, comedy, tragicomedy, farce, and melodrama (Sood et al., 2004; Sabido, 2004; Singhal & Rogers, 1999). These types follow specific structures and can lead to specific effects. Thus the types can be used as frameworks for creating programs, even entertainment-education interventions. At the core of Jung’s theory of the collective unconscious are archetypes – universal scripts or stories that can be identified in folktales, myths, and legends (Jung, 1981; Sood et al., 2004; Singhal & Rogers, 1999). An archetype produces, for example, certain feelings that cannot be rationally explained, because it stimulates the unconscious. In this way, stories or myths can offer solutions to audience members as they affect conscious and unconscious parts of the mind (Singhal & Rogers, 1999). For the creation of entertainment-education media products – especially for those using narratives as engaging element – it is useful to know which kind of frameworks or archetypes work best to involve the audience in the storyline. As the current study is about digital entertainment-education games – and digital games’ most outstanding feature is interactivity – the focus will not be on narratives, hence drama and role theories are not very relevant for the present study.

2.3.6 Audience-Centered Theories Audience-centered theories focus on how audiences interact with and react to media programs. The most important theory to mention here is the uses and gratifications

46 theory; additionally, the two-step flow model, parasocial interaction, and audience involvement are briefly described.

2.3.6.1 Uses and Gratifications Theory Many mass communication theories focus on what the media do with the audience. The uses and gratifications theory has a different perspective, because its basic principle is the question, “What does the audience do with the media?” (Winterhoff- Spurk, 1999; Schweiger, 2007). The main idea is that people are active media users and are aware of their needs, and people use the media to gratify or satisfy these needs (Schenk, 2002; Sood et al., 2004; Schweiger, 2007). The more aspects a medium provides to a media user to gratify or satisfy his/her needs, the more likely this medium will be received. Typical attributes of media programs that can function as gratifications and thus attract users are entertainment, escapism, information, identity, and social interaction. According to Schweiger (2007), entertainment and information are the most important gratifications. This combination is advantageous for entertainment-education programs as they entertain and inform at the same time. Therefore entertainment-education programs should be created that meet audience members’ needs as much as possible; the more gratifications that entertainment- education programs provide so that media users can satisfy their needs, the more likely they will watch, hear, or read the program. Figure 11 illustrates this process:

Figure 11. The uses and gratifications theory.

47 2.3.6.2 Two-Step Flow Model The two-step flow model suggests that the so-called opinion leaders can be influenced by the media and then spread their new knowledge to other people (Lazarsfeld, Berleson & Gaudet 1968; see Figure 12). Also Bandura (2004) mentions that “socially mediated influence can have stronger impacts than direct media influence” (p. 77). This means that interpersonal communication is an important information resource for individuals even if they have access to various media like TV, radio, or the internet. Thus, face-to-face effects should also be measured when evaluating an entertainment-education intervention, and of course an entertainment-education intervention should be addressed to target groups’ opinion leaders.

Figure 12. The two-step flow model (Schenk, 2002, p. 322).

2.3.6.3 Parasocial Interaction The concept of parasocial interaction mainly proposes that individuals can have the impression that they have some kind of personal relationship – even friendship or intimacy – with a media character. This might increase entertainment-education’s impact on audience members. For the present study, parasocial interaction will not be included, because this concept might better work for narratives, and the focus of the

48 study lies on digital games and for this reason on interactivity and not on the narratives.

2.3.6.4 Audience Involvement Another concept to be mentioned is audience involvement. Sood et al. (2004) define audience involvement as the degree to which individuals engage in reflection upon and parasocial interaction with certain media programs, resulting in overt behavioral change. Audience involvement can be separated into two different dimensions: 1. affective-referential involvement and 2. cognitive-critical involvement. Both dimensions rely on reflection, or the degree to which audience members consider a media message and integrate it into their lives. Referential reflection refers to how individuals relate a media program to their own lives in the sense of personal experiences. Critical reflection means the degree to which individuals use their own thoughts and imagination to make sense of a program message (Sood et al., 2004).

2.3.6.5 Summary – Audience-Centered Theories Audience centered theories and models show that audience members interact with and react to media; they are not passive consumers but active media users. The uses and gratification theory in particular points this aspect out: media users actively select media products that help them gratify or satisfy their needs. Therefore, an entertainment-education media product should be created in such a way that it provides as many appealing aspects to the target audience members as possible to make them use it. The two step flow model is not relevant for the current study as it describes processes on the social level that will not be comprised in the present study. Parasocial interaction is important for entertainment-education interventions that are based on narratives; as stated above this study focuses on entertainment- education and interactivity and not on narratives, thus parasocial interaction is not relevant for this study. Audience involvement also shows that media users actively relate media products to their own lives, e.g. by comparing them to their own experiences (referential reflection) or by actively trying to make sense of the program message (critical reflection). According to the focus of this study – creating a digital entertainment-education game based on interactivity instead of focusing on the aspect

49 of narratives – audience involvement in terms of referential or critical reflection is not relevant for the present study.

2.3.7 Contextual Theories Contextual theories examine the interplay between society, institutions, and the broader context. The two most relevant ones are described below: the agenda-setting model and the cultivation theory.

2.3.7.1 Agenda-Setting Model While other theories discuss in which way media messages influence how people think about certain issues, the agenda-setting theory starts one step further and states that the media determine what issues people think about (McCombs & Gilbert, 1986; Cohen, 1963, cited by Schenk, 2002). Therefore this model focuses on cognitive effects of mass media – attention to, knowledge about, and awareness of topics and issues presented in the mass media (Schenk, 2002). Meanwhile two directions under the main concept of agenda-setting have evolved: The “original” agenda-setting approach focuses on the process of how mass media influence the importance of certain issues in people’s lives, whereas the agenda-building approach describes a process through which media and audience agendas influence the agendas of the political elites and vice versa. Put briefly, entertainment-education can influence the audience by placing topics on the agenda so that audience members become aware and think about a topic.

Figure 13. The agenda-setting model.

50 2.3.7.2 Cultivation Theory Gerbner, Gross, Morgan, and Signorielli (1986) describe an approach – the cultivation of beliefs – that explains how television influences attitudes on certain issues presented on TV. A key message of the cultivation approach is that television is considered the great common storyteller (Sherry, 2002) and, hence, forms the worldviews and norms of its users with homogeneous messages that are presented again and again (Winterhoff-Spurk, 1999). Viewers use TV messages in constructing their reality; thus television is the most stable learning environment for society members (Schenk, 2002). This process is unconscious, meaning that individuals are usually unaware of the influence of watching TV. To explore this cultivation process, studies based on the comparison between beliefs (such as stereotypical roles) of “heavy TV viewers” and “light or non-viewers” were conducted (e.g. Morgan, 1987). Differences between heavy and light viewers are an indicator of a cultivation effect; heavy viewers’ worldviews should be more consistent with TV contents and light or non-viewers should have a more realistic worldview. Health-related topics especially point out the consequences of omnipresent, unrealistic media messages. Television presents health risk behavior in an unrealistic, played-down way. At the same time, physicians are shown as supernatural, and an excessive belief in modern medicine and its healing possibilities is transported. Therefore people often underestimate health risk behavior (Schwarz, 2004). Entertainment-education campaigns can cause cultivation effects if they provide homogeneous messages in the long term, as cultivation effects are cumulative. In connection with the elaboration likelihood model (ELM), Shrum (2002) points out that the peripheral path can lead to cultivation effects, because within the peripheral path individuals do not consciously think about the media messages, in doing so counterarguing is reduced and thus rejection of messages could be avoided.

2.3.7.3 Summary – Contextual Theories Contextual theories describe the interplay between society and institutions; the broader context comes into focus when looking at the agenda-building approach. Here, the media selects issues and thus forms agendas that influence audience agendas, which in turn influence political agendas and vice versa. As argued above, for the present study, effects and processes that are not at the individual level are not

51 relevant. But the classical agenda setting theory which states that the media influence what issues people think about is not only generally relevant for the entertainment- education approach, but also for the present study. In case of its successful implementation, participants should think about the embedded issue. Concerning the cultivation theory, the same applies as for the agenda-building approach: It is about processes on the societal level and thus not part of the present study.

2.3.8 Hybrid Models Hybrid Models combine various elements from a variety of theoretical perspectives. Several hybrid models exist; the most famous hybrid model for using entertainment- education programs is the Sabido method. Another promising hybrid model is Wilkin and Fernandes’ (2003) integrative model of entertainment-education.

2.3.8.1 Sabido Method Sabido developed an entertainment-education method for television by integrating his own theory of the tone (see below), Albert Bandura’s social learning theory, Carl Jung’s theory of myths and archetypes, dramatic theories used by Eric Bentley, and McLean’s theory of the triune brain (Brown & Meeks, 1997; Sabido, 2004; Nariman, 1993). Sabido’s theory of tone is based on “the degree of tension and distension (vibration) provoked by the flow in the pattern repertoire formed by the nerve circuits of the receivers” (p.67). He argues that tones are essential to human communication; individuals can perceive tones in the same way and, therefore, can be grouped into “tonal groups” (p.67). Sabido argued that Bandura’s social learning theory (cf. chapter 2.3.3.1 “Bandura’s Social Learning Theory – Social Modeling”) fit with his theory of tone and with an application to soap operas. Based on Bandura’s theory, he developed the idea of positive, negative, and transitional role models. Positive role models perform positive behavior, meaning in accordance with the educational value behind the series, and role models are rewarded with beneficial outcomes. These positive characters should be created in a way that audience members can identify with them and, in an ideal scenario, want to be like them. On the other hand, negative role models perform behavior contrary to the positive role models and should be punished. They should offer as little as possible in identification potential. In the beginning of a

52 series, transitional characters start with performing negative behavior but progressively learn how to do better. They become positive role models in the end, and they tend to be the most effective characters. It seems that audience members like to watch positive changes of people “like themselves” and this could explain the success of various TV programs, such as American Idol or Britain has talent, that show changing processes or that show that a “normal” person can be dressed and styled like a superstar (e.g., Bruce Darnell’s Styling Show) or learn certain skills in a couple of weeks, as for example being a DJ (e.g., MTV Made). Furthermore Sabido used Jung’s theory of archetypes. He was especially interested in specific archetypes like the mother or Prince Charming and their impact on audiences. Within Bentley’s dramatic theory, he was interested in the melodrama, and McLean’s theory of the triune brain helped him understand why it is important that a story not only address a person’s cognitive abilities but also address his/her emotions and basic needs (Sabido, 2004). Sabido realizes the potential of telenovelas/soap operas, which usually follow the same scheme (Sabido, 2004). The characters can be divided into four groups: 1. protagonists who represent a value system shared by the audience and who usually suffer the dramatic action, 2. antagonists who cause the dramatic action so that protagonists suffer and who stand for a conflictive value system, 3. the ‘hotly contested’ (mostly men) for whom the female protagonists and antagonists fight, and 4. satellites/observers who are undecided between the two value systems. In addition, a soap opera/telenovela contains the following aspects that help to create an involving story: 1. remote past: a remote past with secrets and explanations of the status quo. 2. status quo: telenovelas usually start with an event like a wedding. 3. disorderly process: the usually female protagonist suffers major changes (main plot). 4. second plot: mostly less important than the main plot, but useful for cliff-hangers. 5. “daily vibrations”: following Sabido’s theory of tones, telenovelas offer the opportunity for audience members to “affiliate with the daily vibrations offered by the telenovela” (Sabido, 2004, p.69). 6. final combat: the protagonists will win over the antagonists and will establish a new order.

53 Sabido combined all mentioned theories and knowledge about soap operas and made the following decisions concerning the design of soap operas: 1. Satellite characters should be changed into “the target group audiences to whom we want to teach the socially useful educational content of the entertainment-education message” (Sabido, 2004, p. 70). 2. Identification processes should be increased. 3. Reinforcements should be specific to the target group. 4. Positive role models should be rewarded for their good behavior, and negative role models should be punished for their bad behavior. 5. Possibilities how self-efficacy can be increased should be presented to the target audience. 5. Information, about how to find infrastructure services and to increase “access to socially proper behavior” (Sabido, 2004, p. 70) should be provided to the audience. Sabido successfully created several entertainment-education soap operas following this method.

2.3.8.2 An Integrative Model of Entertainment-Education Processes and Outcomes Wilkin and Fernandes (2003) developed an integrative model for explaining entertainment-education effects and how the effects work. They integrated persuasion and behavior change theories with mass media theories. As Figure 14 shows, according to Wilkin and Fernandes (2003) the first important hurdle to clear is the point of attraction to the program. If an entertainment- education program does not attract the target group, it cannot work. In case a program attracts individuals and they hear/read/watch it, there are two different ways of processing the message. These ways are based on Slater and Rouner’s (2002) expansion of the Elaboration Likelihood Model: systematic processing or peripheral processing. With peripheral processing, under specific circumstances, a cultivation effect (Gerbner et al, 1986; cf. chapter 2.3.7.2) can occur (Shrum, 2002; cf. chapter 2.3.4.1 about the elaboration-likelihood model of persuasion). With systematic processing, individuals can show reactions to the characters or the whole program that were not intended by the producer. Then the desired effect will not occur. The other possibility for systematic processing is that individuals show anticipated reactions to the characters/program. Then, as Wilkin and Fernandes (2003) state, the audience

54 experiences identification, empathy, and suspense. The next important factor is whether or not individuals perceive own self-efficacy regarding the topic. If perceived self-efficacy is low, the program might affect an attitude change or might not have an effect at all. If individual’s perceived self-efficacy is high, the program can lead to attitude or even behavior change.

Figure 14. Entertainment-education model by Wilkin and Fernandes (2003, p. 29).

2.3.8.3 Summary – Hybrid Models Sabido successfully used his method to create narrative-based entertainment- education programs. For the present study, the Sabido method cannot be used, as Sabido focuses on and works mainly with narratives. As stated above, the digital entertainment-education game used for this study will not be conceptualized focusing on narratives but on interactivity, therefore the Sabido method cannot be used as theoretical background for the present study. Similarly, the integrative model of entertainment-education processes and outcomes cannot be transferred to the present study. Although it combines many theories and models that are useful for explaining the effects of entertainment-

55 education, it does not take digital games and their special characteristics into account, and those are important for the current study.

2.3.9 Summary – Theories Underlying Entertainment-Education This section aimed to present a variety of models and theories of entertainment- education. The models with steps/stages emphasize that people usually pass through various steps or stages before a behavior change occurs and that this process is not always linear but may also be iterative. The social psychological models emphasize the importance of the individual’s perceptions, beliefs, attitudes, and values, because these aspects can influence entertainment-education effects. Cognitive models are useful for understanding internal cognitive processes as they explain how the mind or the brain respectively works. The kind of story that can successfully be used for entertainment-education is an issue of the drama and role models, as those provide entertainment-education producers with common legends, folktales, or archetypes that affect audience members. Audience-centered models illustrate how audiences interact with and react to media programs. Contextual theories describe media products like entertainment-education in a broader context, emphasizing that the interplay between society, institutions, and the like is an important issue for entertainment-education effects. To combine various theories in explaining how entertainment-education effects occur is the main purpose of hybrid models. The presentation of the theories and models exemplifies that different explanations for entertainment-education effects are possible, and no all-embracing theory or model exists yet. Although various authors have developed hybrid models or combined behavior change theories, mass media theories, and health communication models, a theoretical frame that could explain all effects of all entertainment-education interventions for all different kinds of media – including digital games as entertainment-education media products – remains to be developed.

2.4 Effects of Entertainment-Education Interventions 2.4.1 Introduction and Ways of Evaluation While the previous chapter described how entertainment-education effects can be explained, this chapter focuses on what effects entertainment-education interventions can produce.

56 The summary report of the research conference, “Developing a Research Agenda for Entertainment-Education and Multicultural Audiences” highlights the importance of entertainment-education interventions when stating that worldwide 163 entertainment-education projects have been realized in recent years, often focusing on health-related topics such as reproductive health, family planning, HIV-AIDS and disease prevention (Murphy & Cody, 2003). This report shows that entertainment- education interventions have become more popular and reinforces the fact that a comprehensive treatment of all entertainment-education programs is not possible here. The aim of this section is to show what kinds of effects of entertainment-education programs have been reported. Prior to that, an overview on the ways of evaluation in the context of entertainment-education media products is given. Although it is not yet completely clear which indicators serve best for evaluating entertainment-education interventions (e.g. Lampert, 2003; Sood, 2002), several authors have concluded that entertainment-education is generally effective. For example, Kennedy, O'Leary, Beck, Pollard, and Simpson (2004) note that “there is not only theoretical support for the Entertainment-Education approach, but also empirical evidence that it can be effective” (p. 290); Poindexter (2004) indicates that “the E-E methodology has been demonstrated to be effective” (p. 36); and Singhal and Rogers (1999) point out some rather concrete effects when writing “e-e has effects in creating knowledge, changing attitudes, and influencing individuals to adopt family planning, HIV prevention, and other behavior changes” (p. 143).

Types of Effects – Direct and Indirect Effects Whereas other researchers only accept direct effects as evidence of entertainment- education’s effectiveness (cf. Sood, 2002; Yoder at al., 1996), the last quote above demonstrates that Singhal and Rogers (1999) also interpret indirect effects – e.g. an increase in knowledge or a change of attitudes – as indicators of a successful entertainment-education intervention. Rogers et al. (1999) also note this problem when stating that “direct effects of most mass-media messages on behavioral change are often modest” (p. 208), but they qualify their remark by saying that “the indirect effects of the media (...) can be substantial” (p. 208).

57 Singhal and Rogers (2002) count changes at every stage of the process of behavior change as a success for an entertainment-education program. In accordance with them, other researchers also attach much importance to indirect effects of entertainment-education as a basis for behavioral change (e.g. Piotrow & Fossard, 2004). At times, indirect effects are the only way to test its effectiveness, especially in preventive programs where people should learn the right behavior before they find themselves in a precarious situation. For example, it is sensible to ensure that adolescents learn how to use condoms (thereby significantly reducing their risk of acquiring HIV) before they have any sexual experiences. For the present study, indirect effects also count as success for the digital entertainment-education game, based on Singhal and Rogers (1999) statement that “the implication is that an individual must be informed about a new idea and develop a favorable attitude toward the idea, before changing behaviors” (p. 144). For this reason, in the following sub-sections examples of indirect effects of entertainment- education products – knowledge, interest, self-efficacy, and interpersonal peer communication – are presented first, followed by a presentation of direct effects in terms of behavioral change.

How Entertainment-Education Media Products have been Evaluated Although entertainment-education interventions have a long tradition, no systematic evaluation was undertaken until the mid-1980s (Singhal & Rogers, 1999). Since then, university-based communication researchers have begun to study the subject in earnest. Before that time, entertainment-education interventions – particularly the Sabido entertainment-education programs – were mainly tested using in-house evaluation methods. Such in-house evaluations have been heavily critiqued (see Singhal & Rogers, 1999). Although Sabido's soap operas seemed to be effective, they were not taken into account in communication research literature at that time. As entertainment-education interventions usually vary significantly with regards to medium, target audiences, topic, country of broadcast, etc., their evaluation strategies are also very different. It is not possible to describe each entertainment- education project and its evaluation method in detail when referring to the effects; before starting to report any entertainment-education effects, therefore, entertainment- education evaluation methods in general and their drawbacks and opportunities are described below.

58 Singhal and Rogers (1999) identified five different evaluation methods used for entertainment-education: 1. After-only surveys of effects, meaning that the survey (for example telephone surveys) is undertaken shortly after the entertainment-education program was broadcast. This evaluation method can be problematic, as it is not possible to identify the direction of causality. In the case of Hum Log (an Indian soap opera), it is not clear whether people with higher knowledge and attitudes favoring gender equality were more likely to watch Hum Log or whether they reached higher scores in knowledge and attitudes because of watching Hum Log. 2. Before-after measurement of effects. With this method, the calculation of a change score is possible because data collected before a specific entertainment-education program is broadcast and data collected after the intervention took place can be compared. This method was used for the entertainment-education series Fakube Jarra (“Wise Man;” see Valente et al., 1994) in the Republic of The Gambia. In 1991, 19% of survey respondents used family planning methods; nine months later, 35% of listeners reported using family planning methods. The problems in this case are that the effect could be caused by other factors, and it is not clear whether respondents truly do use family planning methods or only report using them due to social desirability. It is also unclear whether or not family planning methods are used correctly. 3. Interrupted-time series. Before, during and some time after intervention, data is collected and compared. For example, the entertainment-education series In a lighter Mood in Nigeria (Piotrow et al., 1992) was evaluated this way. Health clinics reported data about family planning adopters monthly; in the end they were prompted to increase opening hours from three to six days per week, but it remains unclear whether the increase occurred only due to the entertainment-education intervention or also due to greater clinic accessibility. 4. Field experiments. To evaluate Twende na Wakati – a radio soap opera broadcast in Tanzania – a quasi-experiment was conducted; treatment and comparison groups were not randomly assigned to the eight nationwide radio stations. The station in the “Dodoma” region became a comparison group: Twende na Wakati was broadcast twice weekly in this particular region rather than every day as it was by other

59 stations15. Although control groups would significantly improve the research design, they are ethically problematic (cf. chapter 2.6 “Ethical Considerations Concerning the Use of Entertainment-Education”). Comparison groups could serve as a compromise, but cannot provide the same gain of knowledge as control groups can. 5. Multiple-method triangulation. Multiple research methods are used to measure the same variable or set of variables in different ways, for example by combining surveys (self-reports) and data from health clinics (observations). This method has higher costs compared to others but, according to Sypher, McKinley, Ventsam, and Valdeavellano (2002), “such a multi-method approach makes possible convergent and representational validity, in which the weakness of one method is balanced by the strengths of others” (p. 203). Another indicator that is used is a so called “marker”: “Markers provide additional validation for whether or not audience members were directly or indirectly exposed to the E-E intervention” (Singhal & Rogers, 2004, p. 17). An example of this would be when terms that are only used in an entertainment-education production become commonly used parts of the colloquial language. This was the case with the term “catapult” (from the entertainment-education soap opera Apwe Plezi), which became a term for “condom”, or the term “Scattershot”, the name of a negative character in a Jamaican entertainment-education intervention, which became a common term for sexually irresponsible males. Although such markers can be impressive, they are no definite evidence of the effectiveness of entertainment- education interventions as they do not necessarily imply any indirect or direct effects e.g. on people’s attitudes or behavior. Surveys, field experiments, multi-method triangulation, markers, etc. do not deliver as clear results about the effectiveness of entertainment-education as classical experiments do as the latter can control confounding variables and usually take into account control groups.

15 Poindexter (2004) states that “the Tanzania Project provided such convincing evidence of the strong effects of E-E that later projects have not found it worthwhile to include a control group in their research designs” (p. 34). This practice needs to be viewed critically because entertainment-education media products differ in various ways (medium, topic, target audience, cultural background etc.), so that every entertainment-education program needs its own evaluation.

60 2.4.2 Examples of Entertainment-Education Effects 2.4.2.1 Knowledge Although knowledge in and of itself is not sufficient, it is an essential precondition for behavior change (Roberto et al., 2007). Several authors report that entertainment- education interventions can produce increases in health-related knowledge. For example, in a study by Wilkin, Valente, Murphy, Cody et al. (2006), a telenovela with a storyline addressing the issue of breast cancer was broadcast. A nationwide telephone survey showed that, compared to non-viewers, there was a significant increase in correct knowledge regarding breast cancer issues among viewers before and after the broadcasts. The Henry Kaiser Family Foundation (2004) discovered that people learn about health topics when watching Emergency Room (ER). 53% of regular ER viewers said they learned about important health issues while watching ER, and 32% even said that information from the show helped them to make choices about their own family’s healthcare. It is interesting to note that viewers with lower levels of education were particularly likely to take this opportunity to learn. Consistent with these findings is another study addressing ER and its effects on viewers’ knowledge and interest in the covered health topics. Conducted by Brodie et al. in 2001, researchers confirmed that ER viewers increased their health knowledge by watching ER episodes. Another finding of the same study, however, was that this knowledge decreased again when it was not repeatedly presented (Brodie et al., 2001). ER is not the only hospital series that is used as an entertainment-education program. In the Netherlands, the Heart Foundation implemented cardiovascular health messages in several episodes of Medisch Centrum West (a popular Dutch hospital series). The series was broadcast weekly during prime time; a telephone survey showed that many viewers increased their knowledge about cardiovascular issues (Bouman, Maas, & Kok, 1998). One of the rare experiments to test the effectiveness of entertainment- education interventions was conducted by Ritterfeld and Jin (2005). They screened a movie called Angel Baby – a film about schizophrenia – and various conditions concerning trailers to groups of viewers. The aim was to reduce stigma concerning schizophrenia. All groups had a significant increase in knowledge about the condition. In contrast to the findings of Brodie et al. (2001, see above), Ritterfeld and Jin (2005)

61 showed that the knowledge increase was still present on a follow-up knowledge test administered two weeks later. Issues other than health can be addressed using entertainment-education programs: social change is a frequently addressed topic. Singhal and Rogers (1989) found that 70% of the viewers of Hum Log (a soap opera broadcast in India) indicated that they had learned from watching Hum Log that 1. women should have equal opportunities, 2. women should have the freedom to make their own personal decisions in life, and 3. that family size should be limited. HIV/AIDS awareness is often included in entertainment-education interventions, especially in the so-called developing world. Do and Kincaid (2006) report effects of a television drama in Bangladesh, Shabuj Chaya, writing that “exposure to the drama (…) was found to be statistically associated with HIV/AIDS knowledge. Viewing more episodes of Shabuj Chaya was related to more HIV/AIDS knowledge” (p. 309). Vaughan, Regis, and St. Catherine (2000) evaluated a radio soap called Apwe Plezi, broadcast in St. Lucia from February 1996 until September 1998. The research design consisted of pre- and post-test surveys. Topics addressed included family planning and the prevention of HIV and other sexually transmitted diseases. The authors report that Apwe Plezi was the second most popular program on air in St. Lucia in 1997. Listeners were asked what they had learned from the radio soap: 52-60% of regular listeners said they had learned about HIV/AIDS, teenage pregnancy or drug abuse.

2.4.2.2 Interest As stated above, Brodie et al. (2001) not only studied the effects on knowledge about health topics but also participants' interest in such topics. A telephone survey of regular ER viewers was conducted after a storyline about the HIV infection of the physician Jeanie Boulet was shown in several episodes. The survey showed that 48% of the viewers were very interested in Jeanie Boulet and her HIV status. Kennedy, O'Leary, Beck, Pollard, and Simpson (2004) argue that soap operas serve as a good medium to reach minority women in the US, as they watch soaps and see them as a credible source of health information. The famous TV soap The Bold and the Beautiful, a long-running daytime soap, included a subplot about HIV in August, 2001. For viewers interested in the topic HIV, a hotline call number was

62 shown at the end of the relevant episodes; there was a significant increase in hotline calls16.

2.4.2.3 Self-Efficacy According to Bandura (1971, 1977, 1986, 2001; cf. chapter 2.3.3.1 “Bandura’s Social Learning Theory – Social Modeling”) and many other authors (e.g. Wilkin & Fernandes, 2003), self-efficacy is one of the most important preconditions for behavior change: without a feeling of self-efficacy no effort toward a behavioral change will be expended. Singhal and Rogers (2004) state that: E-E interventions can model either (or both) individual self-efficacy (defined as an individual’s perception of his or her capability to deal effectively with a situation, and one’s sense of perceived control over a situation) or collective self-efficacy (defined as the degree to which people in a system believe they can organize and execute courses of action required to achieve collective goals (p.15) There is general agreement that individuals' perceived self-efficacy concerning HIV/AIDS preventive behavior, such as condom use, is indeed positively related to HIV/AIDS preventive behavior itself. This means that people who believe that they can protect themselves from an HIV/AIDS infection are more likely to use HIV/AIDS prevention methods. Research has provided empirical evidence for this assumption (e.g. Lee, Salmon, & Witte, 2005, 2000; Guttman, Gesser-Edelsburg, & Israelashvili, 2008; Sood, 2002). For example, in a study by Middlestadt et al. (1995), a radio advertising campaign in St. Vincent increased self-efficacy regarding HIV-preventive behavior. Twende na Wakati was also developed to increase viewers' self-efficacy concerning HIV and family planning methods and turned out to be successful in that regard (Rogers et al., 1999).

2.4.2.4 Communication Many researchers provide empirical evidence that interpersonal peer communication can positively influence individuals' path to behavior change (Singhal & Rogers, 2004, 2002; Rogers et al., 1999; Singhal & Rogers, 1999).

16 Unfortunately the incoming call volume far exceeded the Hotline’s surge capacity.

63 According to Jin (2006), by sharing their own health matters with others, people communicate their beliefs about health and influence their own and others' behaviors. Yaser (2004) conducted a study in Turkey about a soap opera called Berdel, focused on a midwife working in the country, that was evaluated with pre- and post-surveys. Results show that more than 60% of viewers discussed family planning issues with their husbands or wives because of watching Berdel. Singhal and Rogers (1999) report that 38% of the listeners of Twende na Wakati talked with peers about family planning issues. Married respondents of the survey in particular discussed family planning methods (Rogers et al., 1999). Bouman, Maas, and Kok (1998) found that 45% of the viewers of Medisch Centrum West (see above) either often or sometimes talk with others about what happened in the series; for about one third of them, these conversations included health issues. This is in line with findings by Brodie et al. (2001): 51% of viewers of ER reported that they talk with family members and friends about the health issues that were addressed in ER. HIV/AIDS has been the focus of several entertainment-education interventions and it appears that people discuss it with peers when the entertainment-education program has been successful. The movie Phir Milenge can be seen as “Bollywood’s answer to Philadelphia” (Singhal & Vasanti, 2005, p.15). It was shown in India in 2004 and evaluated with in-depth interviews with viewers. 87% of participants said that they would recommend the film to others, especially to their friends. Singhal and Vasanti (2005) see this as evidence that “conversations about Phir Milenge occur in people’s social networks, stimulating some form of private and public discourse on the topic of HIV/AIDS.” (p.15). HIV/AIDS was also a topic of Twende na Wakati. Evaluation has shown that those listeners who talked with friends about the soap were much more likely to adopt an AIDS-prevention method (92%) than listeners who did not talk with others about it (69%) (Singhal & Rogers, 1999; see also Vaughan et al., 2000). Mohammed (2001) points out that the effects of Twende na Wakati and the HIV-prevention discussions it prompted were possible because of follow-up communication. Listeners of Twende na Wakati discussed HIV prevention with 81% of their social network partners, whereas non-listeners discussed HIV prevention with 65% of their social network partners. Similar results were reported from another entertainment-education intervention about

64 HIV/AIDS in Africa, Soul City: 43% of people who watched Soul City spoke more openly about HIV/AIDS compared to 25% of people who did not watch Soul City (Tufte, 2001).

2.4.2.5 Behavioral Change As most entertainment-education interventions aim to change people’s behavior, it is very interesting to observe what kind of behavior changes have been produced via entertainment-education so far. Several studies report that audience members changed their behavior because of an entertainment-education program. Yaser (2004), for example, reports about a Turkish entertainment-education intervention called Berdel (see above). The story was centered on a rural midwife and was evaluated with pre- and post-surveys. The comparison of the pre- and post-surveys showed that after watching Berdel, about 350 000 individuals started using modern contraceptive methods (especially the intrauterine device, an effective long-term method that is provided in health clinics). Poindexter (2004) reports that two soap operas in Kenya (a television series with 60 episodes, Tushauriane (“Let’s talk about it”) and a radio series with more than 200, called Ushikwapo Shikamana (“If assisted, assist yourself”; both programs started broadcast in 1987). increased contraceptive use by 58%, while desired family size fell from 6.3 to 4.4 children (on average) by the time the series ended. Poindexter (2004) notes that other factors also contributed to this behavior change, but he indicates that the broadcasting of the two soaps played a considerable role. A very impressive form of behavior change is reported from South Africa; Soul City (cf. chapter 2.1), a famous soap opera, was produced within a large-scale entertainment-education project. Singhal and Rogers (2002) explain that as a cultural rule (the prevailing cultural norm) intervention into private issues is strictly not permitted, even in matters such as domestic violence. In one episode of Soul City, neighbors started to demonstrate against partner abuse by making noise outside the home (by banging on pots). After this episode was broadcast, pot banging to stop partner abuse was reported in several locations in South Africa (Singhal & Rogers, 2002). In the 1970s a telenovela about family planning called Acompaname (Come Along With Me) was broadcast in Mexico. Its effect has been called the “Mexican miracle” (Sabido, 2004, p. 31) because a decrease in Mexico’s population growth rate

65 from 3.7 to 2.4 over a five-year period was observed. Sabido (2004) reports on another noteworthy effect produced by his telenovela in Mexico: Ven Conmigo (Come With Me) was a year-long television serial with daily episodes to reach, enable, and motivate people with illiteracy problems. It is reported that on the day after an epilogue urged viewers to enroll in a particular literacy program, about 25.000 people tried to reach the distribution center in downtown Mexico City to obtain their reading materials, producing a huge traffic jam. Sabido (2004) writes that in the year when Ven Conmigo was broadcast, the rate of enrollment in the program increased from 99.000 up to 900.000 participants. Research has shown (Singhal & Vasanti, 2005) that an entertainment- education strategy can be used effectively to increase/implement HIV/AIDS- prevention behavior. For instance, Singhal and Rogers (2004) found that Twende na Wakati was able to make several hundred thousand sexually-active adults use HIV- prevention methods. In a survey conducted in 1994, 72% of listeners said they had adopted an HIV prevention method because of listening to Twende na Wakati. Such methods included reducing the number of sexual partners, using condoms and not sharing any razors or needles (Singhal & Rogers, 1999). Vaughan et al. (2000) expressed concern that listeners of Twende na Wakati who had adopted an HIV/AIDS prevention method did so mainly by reducing their number of sexual partners (77%) rather than adopting condom use (15%) or not sharing razors (6% ). When focusing on the higher-risk group of individuals with more than one sexual partner, there was an observed increase in condom use from 6% in 1993 up to 13% in 1995 (Vaughan et al., 2000). Similar results were reported in response to an entertainment-education television program in Ghana called Things We Do for Love (Murphy & Cody, 2003). In this case, an indicator was used in place of a survey. This indicator was “condom sales”: It increased from an average of 2.7 million within the six months before the serial went on air to 6.6 million within the six months during the program was broadcast (Murphy & Cody, 2003). HIV/AIDS prevention was a main topic of the Soul City project. Viewers were found to use condoms more often compared to non-viewers. For the age group of 16- to 24-year-olds in particular, Singhal and Rogers (2003) report an increase in condom use from 18% to 27%. In general, 63% of the respondents in the national survey agreed that Soul City “helped me change my life for the better” (Tufte, 2001, p. 45).

66 In Japan, the number of HIV tests and requests for HIV/AIDS counseling more than doubled during the broadcast of Kamisama Mo Sukoshidake (Please God Just a Little More Time), a melodramatic TV series in Japan that was shown from July to September in 1998. During that time, the number of HIV tests and requests for HIV/AIDS counseling increased by about 50% (Singhal & Rogers, 2003). Beyond television and radio series, music videos have also been shown to be effective in prompting HIV-preventive behavior: in the Philippines, more than 150.000 young people called a sexual responsibility hotline that was promoted in an entertainment-education music video (Turner, 1992, cited by Elkamel, 1995).

2.4.2.6 Summary Some researchers accept only direct behavioral changes as evidence of entertainment- education effects, and are rather skeptical concerning its effectiveness (cf. Sood, 2002; Sherry, 2004; Yoder at al., 1996). For other researchers, an entertainment- education intervention is effective as soon as indirect effects can be produced with it (Poindexter, 2004; Singhal & Rogers, 2002, 1999). Indirect as well as direct effects have indeed been reported in the extant academic literature. When taking indirect effects into account, research has shown that increases in knowledge (e.g. Wilkin et al., 2006; Ritterfeld & Jin, 2005), interest (e.g. Kennedy et al., 2004; Brodie et al., 2001), self-efficacy (e.g. Lee, Salmon, & Witte, 2005; Middlestadt et al., 1995), and interpersonal communication (e.g. Yaser, 2004; Tufte, 2001) can be viewed as successful effects of entertainment-education programs. There is also noteworthy evidence for direct effects in terms of behavior change (e.g. Sabido, 2004; Murphy & Cody, 2003). Entertainment-education interventions differ significantly concerning topic, media type, producers, country, etc. and therefore their results cannot automatically be transferred to other media, countries, topics, etc. Each entertainment-education intervention requires its own evaluation.

2.5 Factors that Could Influence an Entertainment-Education Outcome 2.5.1 Introduction The last two sections presented the theoretical backgrounds and important empirical findings concerning the effects of entertainment-education. Because every entertainment-education intervention is necessarily realized with a specific medium,

67 all factors that could affect media processes in general also have the potential to affect entertainment-education interventions. This section describes parameters that have been identified through empirical research or that serve as theoretical assumptions that could affect entertainment-education outcomes. These parameters are divided into four categories: 1. factors concerning the medium, 2. factors concerning the environment, 3. factors concerning the entertainment-education audience, and 4. factors concerning accompanying research.

2.5.2 Factors Concerning the Entertainment-Education Media Product Audience identification and targeting is always important when creating an entertainment-education intervention, as the intervention can only work if it is customized to the predetermined target group. Although every entertainment- education media product is very special, some general conditions that an entertainment-education medium should meet in order to be successful are listed below: 1. The language of broadcast should be chosen so that the target group is able to understand the entertainment-education medium. This point is especially important in countries where various languages are spoken, e.g. in South Africa (Singhal & Rogers, 1999). 2. The choice of format (TV or radio soap, theater performance, etc.) and of program scheduling (in the morning, during prime time, etc.) can have a strong influence on the potential audience size (Singhal & Rogers, 1999). The broadcasting time is particularly important in media saturated environments (Sherry, 2002). 3. The talent and ability of scriptwriters, actors and all professionals involved in the production process are important in order to create a medium that can compete against other programs and thus attract people as regular listeners/viewers of the entertainment-education program (Singhal & Rogers, 1999). 4. One important aspect of an engaging story line are its characters. To be able to create interesting characters, the entertainment-education medium should be theory- based in the sense of following Bandura’s social learning theory (Singhal & Rogers, 1999). Role models are an essential part of this theory (cf. chapter 2.3.3.1) and played a decisive role in Sabido's entertainment-education soap operas. He usually included three different types of characters: a) those who support the value (positive role models), b) those who reject the value (negative role models), and c) those who are

68 somewhere in between (the doubters, so called transitional characters who will become positive role models at the end of the story) (Singhal, Rogers, & Brown, 1993). According to Vaughan et al. (2000), the transitional characters have shown to be the most important ones and can be seen as “the key identification characters” (Vaughan et al., 2000, p. 86) for the audience; their function is to demonstrate to audience members self-efficacious ways to change behavior. Wilkin and Fernandes (2003) identified particularly funny characters as audience favorites and concluded that funny characters increase the chances of attracting a regular audience to the program. Another possibility for creating effective characters is the use of cultural archetypes (Svenkerud, Rahoi, & Singhal, 1995). The evaluation of the Japanese entertainment-education program Oshin indicates that much of its popularity was derived from the archetypes used in character creation. Archetypes make it easier to touch people's emotions and thus to effectively transmit messages (cf. chapter 2.3.5 about drama and role models). 5. The entertainment-education program should maintain a degree of realism such that people can relate it to their own lives (Singhal & Rogers, 1999). Although this aspect seems to be quite simple, it is seldom mentioned in the entertainment-education literature (Guttman, Israelshvilli, & Gesser-Edelsburg, 2005). 6. Entertainment and education should be balanced to avoid having the audience reject the implemented messages (too much education) or miss the message (too little education) (Singhal & Rogers, 1999). 7. To increase entertainment-education effectiveness, the messages should be repeated, for example within a long-running serial or a bigger communication campaign that includes different media products (Piotrow & Fossard, 2004). 8. Celebrities can be very helpful to attract audience attention (Brown & Fraser, 2004). 9. A good epilogue can increase entertainment-education programs' effectiveness: “the inclusion of epilogues to emphasize the program’s message has become well accepted as part of the entertainment-education strategy” (Slater, 2002, p. 162). 10. The trustworthiness of factual and other sources must be assured: in cases where credibility is low, a given entertainment-education program is likely not to have the intended effects (Sherry, 2002; Singhal & Rogers, 1999). 11. A successful entertainment-education program consists of narratives (Kincaid, 2002); such programs attract the audience because they are entertaining because of

69 their compelling drama (Slater & Rouner, 2002). According to Vorderer and Ritterfeld (2003), “Media users who feel entertained are more interested, more attentive, and therefore more eager to select, follow, and process the information given by a program than are those users who are not” (p. 247). If the viewer seeks out entertainment, there is no reason to watch a purely informational program; if the information is integrated into a good storyline, however, and engages the viewer, it will be watched (Slater, 2002). Rogers (2004) takes this a step further; he sees narratives not only as features attractive to the audience because of their entertainment value, but also as essential conditions: he claims that the narratives themselves “transport/involve audience in the story so that behavior change is facilitated “(p. 285). To achieve this desired effect, the quality of the narratives of an entertainment- education medium is important. A good narrative balances two possible outcomes: the first is what the viewer hopes should happen and the other is what the viewer fears could happen (Kincaid, 2002). A narrative should not be perceived as didactic or as “preachy” (Singhal & Vasanti, 2005, p. 5) by the audience. In creating good narratives – and on basing entertainment-education programs on good narratives – interventions can appeal to the emotions of audience members (Singhal & Rogers, 2003) and transport them into the respective narrative world (Slater & Rouner, 2002; Lee, Salmon, & Witte, 2005). This metaphorical transportation can be seen as blending of attention, feelings, and image representation that focus on story events (cf. Green & Brock, 2002; 2000; Gerrig, 1993); it facilitates the changing of real-world beliefs as a consequence of information, statements, or events presented in a story (Slater, 2002). If narratives engage viewers such that they feel transported into the given fictional world, counter-arguing is reduced (cf. chapter 2.3.4.1 about the elaboration-likelihood model; Slater & Rouner, 2002; Green & Brock, 2000). This might be the most relevant reason why “narrative anecdotal arguments could be more effective than fact- based arguments” (Lee, Salmon, & Witte, 2005, p. 4). Storytelling for the purposes of information transfer may well be as old as mankind itself (Slater, 2002); Fisher (1987) even uses the metaphor “homo narrans” (p. 62) and argues that it best typifies “the essential nature of human beings” (p. 62) in contrast to animals. The advantage of storytelling is its ability to “give concrete form of abstract ideas” (Green, 2006, p. 169), which makes it effective in influencing

70 peoples’ attitudes and behaviors (Slater, 2002). Thus, high quality narratives can strengthen entertainment-educations outcome.

2.5.3 Factors Concerning the Environment The environment in which an entertainment-education intervention takes place can influence its effects in different ways, particularly as “environment” can be understood from several different points of view: e.g. socio-cultural, technical, financial, or media related. The most obvious environmental influence is by culture, as a successful entertainment-education program cannot automatically be successfully used in another socio-cultural setting (Kreuter & McClure, 2004; Wilkin & Fernandes, 2003; Singhal, Rogers, Brown, 1993). An entertainment-education program like a radio soap opera that works for adults in Africa, for example, will not necessarily work in Europe. This is because every culture has its own norms and rules (see above) and entertainment-education interventions must be well adapted for target audiences that are formed from a specific culture. Subcultures within a culture also have to be taken into account (for example, youth often have their own subcultures). Since many young people are under enormous pressure from their peer group, it is important for them to use the same media (favorite music, TV series, etc.) as the other members of their subculture do (Vorderer, 2003). Beyond culture, technical and organizational factors influence an entertainment-education's outcome. Financing and consequently the quality of technical expertise, the potential to involve celebrities, etc. all have an influence (Singhal & Rogers, 1999). The access to support services as well as their availability can also be important for facilitating intended behavior changes. For example, when too few literacy booklets were available in Mexico City after the broadcasting of entertainment-education soap on TV, tens of thousands of frustrated people had to return home without it (Sabido, 2004). A similar problem occurs when people want to call an information hotline and cannot get through (Kennedy et al., 2004). In these cases, the entertainment-education intervention can fail: people are motivated to act, but frustrated because they cannot. It is most likely that they will not try again after having encountered this barrier. Adequate infrastructural conditions are necessary for the success of an entertainment-education program if it refers to such support services (Murphy & Cody, 2003; Singhal, Rogers, & Brown, 1993).

71 The most-discussed environmental factor is the degree of media saturation, meaning how many media programs and products are available and thus how many other programs an entertainment-education program has to compete against. Slater (2002) points out that in many countries where entertainment-education programs used to be successful, the number of channels was limited; this situation cannot be compared to a crowded media environment like Europe or the U.S. (Green, 2006). The problems associated with media environment saturation go beyond attracting audiences who have a much wider range of choices; often, other programs present in the media environment transmit messages that are contrary to those of the entertainment-education program (Randolph & Viswanath, 2004; Singhal & Rogers, 2002, 2004). For example, entertainment-education programs about HIV/AIDS often include the message to use condoms, but condom use is rarely topical or even shown on TV. In nations with only few media channels and thus little message competition, entertainment-education interventions are more likely to work (Sherry, 2002). Thus, Sherry (2002) argues that in media-saturated environments, entertainment-education requires message repetition – preferably as multimedia messages within a communication campaign across media and across channels (Singhal, Rogers, Brown, 1993) – if it is to be effective. Bouman (2004) states that in Western countries, no real entertainment- education programs generally exist, as none are designed following the entertainment- education guidelines. That being said, it is common in the Western media environment to include entertainment-education content in preexisting TV serials (cf. chapter 2.1 about how information is embedded in Western countries). Lee, Salmon, and Witte(2005) even argue that it has not yet been shown that entertainment- education works in industrial nations due to the aforementioned media program variation. High media saturation is a challenge for entertainment-education planners; beyond competition provided by other programs and the contrary messages transmitted with them, audience segmentation is also a challenge. The higher the degree of media saturation, the higher is the number of different audience subgroups. To be successful, entertainment-education needs to attract a specific – predetermined – target group (Wilkin & Fernandes, 2003). The greater the number of audience subgroups that exist, the more difficult it is to attract more than one subgroup with the same program.

72 2.5.4 Factors Concerning the Audience The “audience” is never a homogeneous group; it consists of different people with different social backgrounds, which influences the way media users deal with media products (Vorderer, 2003). Relevant audience characteristics can be divided into two categories: the first concerns individual aspects and the second social aspects. Individual differences among audience members such as age, sex, gender, culture, and personality traits affect the use and gratification of entertainment programs (e.g. Wilkin & Fernandes, 2003). Vorderer (2003) writes about this interplay, “Different people entertain themselves differently, according to their personal characteristics, their membership in different social groups, and various social situations in which entertainment may take place.” (p. 141). It can therefore be assumed that such audience characteristics determine the success of a given entertainment-education program (Wilkin & Fernandes, 2003; Weaver, 2000; Oliver, 2002). Socio-demographic factors as the above (age, sex, etc.) are supposed to be salient: Elkamel (1995) found, for example, that women were more likely to remember the promoted health messages in an Egyptian entertainment-education television drama than men. Personality traits can also have an effect. For example, sensation seeking is a personality trait that should be taken into account when creating entertainment- education interventions, especially in the context of risky behavior (Sherry, 2002). Other psychological characteristics are also important for entertainment- education outcomes. In this context, self-efficacy is the most studied factor (cf. also chapter 2.4.2.3). For example, perceived self-efficacy is a significant predictor of reproductive behavior and risky sexual practices (Bandura, 2004). This is in accordance with findings by Lee, Salmon, and Witte (2005), who write that in many studies the hypothesis that individuals’ perceived self-efficacy is positively related to HIV/AIDS preventive behavior were tested and that these studies indeed provide empirical evidence for this hypothesis: When individuals’ self-efficacy toward safer sex increases, then these individuals are more likely to adopt safer sex behavior (e.g. Vaughan et al. 2000). For health prevention programs, one’s personal risk perception is another psychological characteristic that was shown to be influential (Vaughan et al., 2000; cf. chapter 2.3.3.4 about the health action process approach). For example, people often do not have a realistic perception of their risk of contracting HIV. Research has shown

73 that students overestimate the risk of getting infected with HIV when having unprotected sexual intercourse only once, but very much underestimate the risk of contraction when having unprotected sexual intercourse several times (Linville, Fischer, & Fischhoff, 1993). It can be concluded that this is a tendency to underestimate cumulative risk (Slovic, 2000). Additionally, the perception of negative consequences declines the more often a person performs risky behavior (Schwarzer & Renner, 1997). One’s personal risk perception therefore very much influences preventive behavior motivation (Schwarzer & Renner, 1997; Faltermaier, 1994). Addressing HIV/AIDS preventive behavior, Lapinski and Nwulu (2005) revealed that health promotion messages embedded within the content of entertainment films can impact some forms of risk perception. The degree of exposure and selective interpretation can also influence an entertainment-education outcome (Singhal & Rogers, 1999). Selective interpretation involves audience members actively negotiating the meanings they perceive when processing an entertainment-education intervention. A very impressive case of selective interpretation is the so-called Archie-Bunker effect (cf. chapter 2.2.3 about misinterpretation of embedded educational content as challenge): It is defined as the degree to which certain audience individuals identify with negative role-models in entertainment-education interventions (Singhal & Rogers, 1999, 2004). Archie Bunker reinforced (rather than reduced) racial and ethnic prejudice among certain highly prejudiced viewers. In addition to these individual-related audience characteristics, Singhal and Rogers (1999) also point out social aspects of the audience that are supposed to have an influence on the effectiveness of entertainment-education: social norms, the degree of interconnectedness of audience members, and generally accepted values and beliefs. According to Horne (2001), a widely accepted definition of social norms is that “they are statements that regulate behavior” (Horne, 2001, p.4), meaning that they prescribe socially acceptable behavior. Social norms have to be kept in mind when designing an entertainment-education program, because the implemented message or requested behavior change can violate them. When this is the case, it is rather unlikely that people will change their behavior in the intended way. An entertainment- education intervention must therefore find a way to deliver controversial or proscribed behavior in a way that is perceived as normatively acceptable. An alternative is for the entertainment-education program to start one step further and first change the

74 proscribing social norms and then induce behavior change on the individual level. The degree of interconnectedness of audience members can influence entertainment- education effectiveness; research has shown that interpersonal communication can strengthen entertainment-education outcomes (e.g. Jin, 2006; Yaser, 2004). The less audience members are connected – in terms of opportunities of having personal exchange – the less they can communicate about the entertainment-education program (preventing the strengthening effect of interpersonal peer communication from taking place). Common beliefs and values influence entertainment-education effectiveness because a particular entertainment-education message can either be in accordance with a given set of beliefs and values (in which case it is easier to transmit the message to audience members) or it can be conflicting. If so – as described for the social norms – it makes more sense to first try to change beliefs and values and in a second step try to change individuals’ behavior. For example, if a common belief is that AIDS was created by white people to kill black people or to make them use condoms so that they do not reproduce anymore (Scheen, 2004), it is hardly possible to directly effect a behavior change towards condom use with an entertainment- education program. In such cases, the first aim must be to change peoples’ knowledge and attitudes before behavioral changes can occur. There are various audience factors that influence the effectiveness of an entertainment-education program. Entertainment-education producers need to try to ensure that they maximize the potential for the audience to process and interpret the messages as desired (Wilkin & Fernandes, 2003). In constructing a successful entertainment-education program, age, gender, culture, social norms and other important characteristics of the target group audience must be kept in mind “in order, first, to be sure that the target audience is being successfully reached and, second, to avoid offending the audience by presenting material that may be inappropriate or offensive” (Wilkin & Fernandes, 2003, p. 4). As many audience characteristics as possible need to be identified (for example with accompanying research, cf. chapter 2.5.5 below) and considered when designing an entertainment-education program, in order to ensure that it will attract and affect the target group as effectively as possible.

75 2.5.5 Factors Concerning Accompanying Research Accompanying research can influence the effectiveness of entertainment-education programs because it helps to identify the characteristics, needs, and preferences of the target group. Research has shown that for this purpose it is useful to combine qualitative and quantitative data collection and analysis methods (Singhal & Rogers, 1999). Particularly when trying to reach rather unfamiliar audiences from other (sub- )cultures or socio-economic status, it is important to make sure that an in-depth understanding of the target group is given. Audience participation in message design can also be a useful tool in pre-testing the entertainment-education program.

2.5.6 Summary Many factors determine the effectiveness of entertainment-education programs. Concerning the media product itself, rather obvious aspects like choice of language, format, scheduling time etc., as well as the conceptual aspects of an education- entertainment design or the use of celebrities and epilogues are very important. A theory-based design with a good storyline and appealing characters increases the likelihood of achieving the desired entertainment-education outcome. For the purpose of the present study that uses a funny character, it is interesting to know that funny characters have shown to be particularly useful for a successful entertainment- education program (Wilkin & Fernandes, 2003; cf. chapter 2.5.2). Factors concerning the environment refer to socio-cultural, technical, financial, and media related aspects. Media saturation remains the most-discussed environmental factor in the academic literature. If saturation is high, the entertainment-education medium has to compete with many other media products with very different – or even contrary – messages. For the present study it is important to count youth culture as a sub-culture with its own rules and media preferences; as adolescents like to play games, it makes sense to create a digital entertainment-education game. Important audience characteristics concern either the individual (socio- demographic aspects, personality traits, or psychological characteristics) or the given society (social norms, beliefs and values). In accordance with the chapter about direct and indirect effects (cf. chapter 2.4.1), perceived self-efficacy and personal risk perception have again been shown to be important for an entertainment-education

76 program's outcome. An entertainment-education intervention should also be gender- related, as studies have shown that effects can differ between men and women. Accompanying research facilitates the collection of information about the needs and interests of the target group and allows for pre-testing of entertainment- education programs with target group members before broadcasting, ensuring proper compatibility. Unfortunately, this point is often neglected; although people should profit as much as possible from an entertainment-education intervention, accompanying research is not part of every entertainment-education project.

2.6 Ethical Considerations Concerning the Use of Entertainment-Education The aim of this section is to describe the ethical concerns of entertainment-education and how such concerns can be addressed in practice. This section also identifies who is responsible for entertainment-education interventions and provides advice for making appropriate decisions concerning ethical issues. The use of entertainment-education automatically raises ethical concerns (Brown, 1992; Brown & Singhal, 1993) as does any intervention (Bandura, 2004). The possibility to educate people via entertainment media also implies “the potential to spread misinformation or create misimpressions” (Brodie et al., 2001, p. 192). To persuasively influence audience members’ beliefs and behaviors reminds people of times in history when the public opinion of an entire country was controlled by the misuse of media (Brown & Singhal, 1993), as in the instance of Nazi Germany. Although entertainment-education has an “inherently manipulative nature” (Dutta-Bergmann, 2004, p. 19), only a limited amount of literature exists that focuses on its ethical aspects. Brown and Singhal (1993) criticize this fact and, until today, no really “groundbreaking” article or other kind of literature has been published on this subject. Therefore mainly two contributions written by Brown and Singhal (1993) and a chapter by Singhal & Rogers (1999) are used for this chapter to summarize the discussion about entertainment-education’s ethical considerations. According to Brown and Singhal (1993), the use of entertainment-education raises five ethical questions (see below); Singhal and Rogers (1999) formulate seven ethical dilemmas of entertainment-education that accord with most of those questions:

77 1. Is it ethical to use communication and marketing strategies to systematically influence societal beliefs and behaviors? (Prosocial development dilemma; oblique persuasion dilemma) 2. Who is best qualified to make decisions regarding prosocial vs. antisocial or healthy vs. unhealthy messages in the popular media? (Prosocial content dilemma; source-centered dilemma) 3. Is it ethical to target messages to a particular audience in exclusion of others? (Audience segmentation dilemma) 4. Is it ethical for nations that control the media to export their own cultural values and beliefs? (Prosocial content dilemma) 5. Should the risk of unintended consequences of media designed to promote social change be taken? (Unintended Effects dilemma) Before answering these questions, the next subsection briefly takes a look at ethics, explains the relationship between ethics and morality, and discusses in what ways ethical and moral systems or concepts can be used for entertainment-education.

Ethics/Morality Ethics is a major category of philosophy, dealing with right behavior and good life (Löwisch, 1995; Kuhlen, 2004). Ethics concerns theory, while morals (or morality) concern the practice (Krainer, 2001; Leschke, 2001); ethics is about the theory of right and wrong actions, while morals transfer this theory into practice via concrete rules and guidelines. According to Newall (2005), ethics is separated into three sub-branches, namely, meta-ethics, normative ethics, and applied ethics. For entertainment- education, the field of “applied ethics” is especially relevant, because this discipline is about the transfer from ethical theory into real-life situations. As such, real-life situations can be divided into various topics; many subfields of applied ethics exist such as “media ethics” (dealing with the specific ethical principles and standards of any kind of media) and “education ethics” (dealing with the specific ethical principles and standards of education). Greis, Hunold, and Koziol (2003) argue that ethics is necessary because, among other reasons, media products have an effect on people. As soon as somebody is affected by someone or something, e.g., because of a media product, the question of responsibility arises.

78 Since entertainment-education should and does have effects on persons, in accordance with the arguments by Greis, Hunold, and Koziol (2003) stated above, a conclusion can be drawn that “entertainment-education ethics” is absolutely essential. As a subdivision of applied ethics, “entertainment-education ethics” would overlap with other subfields such as the ethics of (entertainment) media, education ethics, and ethics of persuasion.

Values The term “value” is a basic concept in ethics (Löwisch, 1995). Value means that persons or social groups of persons create conceptions about characteristics or qualities of ideas, objects, or relationships that are important and/or desirable for the valuing person(s) (Löwisch, 1995). Therefore values are subjective and differ across persons, nations, and cultures. However, within groups or cultures, the same values are shared overall. If several values are consistent, then they might compose a value system, which can become a moral code. “A moral code is a system or collection of moral precepts - such as the Ten Commandments: ... (it) is applied to a collection of abstract values“ (Wines & Napier, 1992, p. 833). Values can be material (e.g., money) or immaterial like personal values such as trustworthiness or religious values such as faith.

Conflict of Values Because human beings are members of various social groups and each group has its own values or even value systems and, therefore, its own norms, a natural occurrence would be for conflicts of values to emerge (Löwisch, 1995). For example a man can be an employee in a company, a member of a religious denomination, a member of a soccer team, and a father. Then on a Sunday when the employer asks him to work extra hours, his church expects him to worship, his soccer team expects him to play a game, and his children want him to go on an excursion, the values and norms of these different groups (profitability, religiousness, strong team companionship, and being a good father) are in conflict (Löwisch, 1995). Often it is impossible to act in a way in which the requirements of all values can be met. Usually persons or groups try to create a hierarchy of values, where the weighing of values depends on situational factors and cultural backgrounds. Ethical dilemmas of entertainment-education interventions also arise from value conflicts.

79 Before this is discussed on the basis of Brownand Singhal’s(1993) five ethical questions, a recommended procedure to minimize such conflicts and to qualify persons responsible for education interventions will be presented, based on Löwisch’s responsibility discourses (1995).

Responsibility Discourses Löwisch (1995) provides a practical solution for equitable moral actions: responsibility discourses. The aim is to test if the intended action is ethical before it is put into practice. The purpose of a responsibility discourse is to provide decision guidance for those persons in charge of a specific educational intervention. Dialogue partners in a responsibility discourse should include representatives of all persons, both directly and indirectly, affected by the intervention even such as unborn children (in practice, represented by others), decision makers, executors, and the like. The solution is always subjective and depends on historical, cultural, emotional, and environmental factors. According to Löwisch (1995), decision-making based on responsibility discourses depends on the following factors: 1. the concrete situation, 2. concerned persons, 3. environment, 4. public expectations, 5. knowledge on effects and side effects, 6. notion of the future. This implies that such solutions are neither purely rational nor universal. Thus for each and every educational intervention, a new responsibility discourse would be necessary.

Entertainment-Education’s Ethical Dilemmas as Conflicts of Values For entertainment-education interventions, such responsibility discourses should be standardized and mandatory to ensure that all decisions are based on a responsible, comprehensible, and transparent discussion conducted according to the specific case. Murphy and Cody (2003) report that an agreement was reached at the conference “Developing a Research Agenda for Entertainment-education and Multicultural Audiences“, that entertainment-education should, amongst other issues, be ethical. In their opinion this means that researchers, reviewers, and funders must be careful

80 concerning any “unintended or unethical consequences” (Murphy & Cody, 2003, p. 18). However no concrete course of actions was provided to meet these demands. Considering the fact that entertainment-education’s definition states that the purpose of entertainment-education is “to show individuals how they can live safer, healthier and happier lives” (Singhal and Rogers, 1999, p. 9), the main value of entertainment-education can be defined as “helping other people.” Following the rationale about values and the development of conflicts of values, it can be assumed that the “ethical dilemmas” (e.g. Singhal & Rogers, 1999, p. 217) of entertainment-education occur because of such conflicts. In this case, the main value of “helping other people” conflicts with other values (see below). The five ethical questions by Brown and Singhal (1993) should be seen in the context of such conflicts of values and in connection to Löwisch’s responsibility discourses (1995). In this context, the answers to the five ethical questions given by Brown and Singhal (1993) can be meaningfully complemented.

The first question “Is it ethical to use communication and marketing strategies to systematically influence societal beliefs and behaviors?” – and relatedly, the prosocial development and the persuasion dilemmas – are crucial to entertainment- education. They express the conflict between the values “helping other people” and “self-determination of human beings”, as persuasion is an unconscious process of manipulation. On the one hand, entertainment-education interventions have good intentions with the purpose of helping other people. On the other hand, these interventions contradict the value of “self-determination of human beings,” because this strategy is persuasive; people cannot independently decide whether they want to learn the implemented issues or not, meaning that they might not have agreed with these issues had they been asked about them. Or they might not have agreed to being influenced in a manipulative way, even if they had accepted the implemented issues. In short the usual answer to the first question is that media influences audience members anyway and that, because of this influence, entertainment-education can be used if it is for a “good” purpose (Brown & Singhal, 1990) – e.g. by providing accurate health information (Beck, 2004). As mentioned before, the entertainment-education approach has an "inherently manipulative nature" (Dutta-Bergmann, 2004, p. 19); this in fact applies to the entire entertainment genre. According to Singhal and Rogers (1999), entertainment “is the

81 most pervasive mass media genre” (p. 7) and is impossible to produce as “value-free” or “socially innocuous” (Brown & Singhal, 1990, p. 276), because entertainment media always transfers values, beliefs, and behaviors to the audience. Edgerton (1993) even argues that, since the 1990s, entertainment is “the foremost institution in the world for establishing and transmitting human values” (p. 90). This is in accordance with the results of various studies indicating that entertainment media products influence audience members anyway and, for the most part, unintentionally (Piotrow, 1994; Salmon, 2000). Television viewers transfer information and beliefs from fictional media products to their own reality (cf. the cultivation theory: Gerbner, Gross, Morgan, & Signorielli, 1986; Schreier & Appel, 2002). Singhal and Rogers (1999) point out that entertainment media tells the audience how to dress, speak, think, and behave and that this process usually goes unnoticed by the audience. As mentioned in introduction (chapter 1.1) about entertainment-education's history, such an unplanned and unintended effect of entertainment media – namely, young women buying Singer sewing machines and enrolling in adult literacy classes – laid the foundation for the entertainment-education approach as it is used today (Singhal, Rogers, & Brown, 1993). Thus it can be argued that if the media has the power – even unintended – to strongly influence audience members and do so anyway, then using this possibility for 'good' purposes is better than doing nothing. Several authors agree with the idea behind this statement and argue in a similar way. For example Brodie et al. (2001) write that health information is included in entertainment programs anyway and that the aim should be for information to be communicated as accurately as possible. Brown and Singhal (1993) even go one step further; they follow the idea of Bettinghaus and Cody (1987) and state that persuasion is even “a necessary part of a free and democratic society” (Brown & Singhal, 1993, p. 95). Yet simply saying that entertainment media have many (negative and positive) effects anyway, even if unintended, and that for this reason it is ethical to use highly persuasive programs for “good” purposes (whoever decides what can be called “good”; see below) is not enough if the entertainment-education approach is to be a professional and trustworthy method. As mentioned above, entertainment-education needs standardized, mandatory procedures to ensure that an ethical discussion about each individual case takes place.

82 The second ethical question by Brown and Singhal (1993) – “Who is best qualified to make the decision about prosocial and antisocial messages in the popular media?” – in the broadest sense concerns a conflict involving the values of “helping other people” and “democracy”; this is also connected to the “prosocial content dilemma” – dealing with who decides what is prosocial – and the “source-centered dilemma” which is about the question who makes decisions about entertainment- education interventions in general. Usually it is a positive value (at least in most Western countries) that important decisions are made through the democratic processes of voting or electing representatives. Experts often publish recommendations, but even for some health topics (e.g., nutrition) various experts have different opinions. The same applies to the term “prosocial” which can be construed in different ways as well, as there is no overall and universal meaning of “prosocial.” The definition is dependent upon ideologies and worldviews of the decision-maker (Brown & Meeks, 1997). Furthermore power differentials between teachers and learners usually exist. Teachers once had more power than learners, because they decided what “knowledge” was taught and in what way it was taught. Yet according to Löwisch (1995), this does not necessarily become an ethical problem, because the aim of education should be to reduce these distinctions. He argues that an educating person qualifies the learning person – who is reliant on the educating person – in order for the learner to become a responsible member of society. However to fulfill this aim, it is essential to know about a society’s norms and values. This is in accordance with Brown and Singhal (1993) who write that “discerning which values and beliefs promoted by popular media are good for society and which ones hurt society should be based on socially accepted community norms” (p. 96), but they do not make any suggestions on how to properly evaluate these “socially accepted community norms” (p. 96). Bandura (2004) mentions that “extensive cultural and value analyses are conducted before dramas are developed and implemented. In this formative phase, focus groups, representing various constituencies in the society, identify problems of major concern to them and the obstacles they face” (p. 87). Sabido already asked for creating “moral frameworks” (Singhal & Rogers, 1999, p. 58) about the educational issue that should be embedded in the entertainment-education program. Singhal and Rogers (2003) state that such frameworks can be “derived from a nation’s constitution, its legal status, or from

83 documents such as the UN Declaration of Human Rights to which the country is a signatory” (p. 294). Based on such a framework, a values grid can be formulated for the educational messages that state the concrete behavior change aimed for by the program (e.g. “It is good to send a girl to school”, Singhal & Rogers, 1999, p. 58). Formative evaluation research (cf. Chacon-Moscoso, Anguera-Argilaga, Antonio, Gil, & Holgado-Tello, 2002), can help to find out about values in the target group. In the context of entertainment-education interventions “formative research is a type of research conducted while an activity, process, or system is being developed or is ongoing in order to improve its effectiveness” (Singhal and Rogers, 2003, p. 295). An example for extensive formative evaluation was Twende na Wakati. Prior to the development of the entertainment-education radio soap opera Twende na Wakati, formative evaluation – consisting of 160 focus-group interviews, and interviews with 4.800 17 people – was conducted to provide an in-depth understanding of the issues that were to be addressed within the soap opera. The data provided information on how the messages should be embedded into media products in order to be appropriate for the audience (Singhal & Rogers, 1999). This procedure is in line with the above request for standardized, mandatory, and ethical responsibility discourse that would include representatives of all involved groups who decide what prosocial, health, or other topics are appropriate for the individualized entertainment-education intervention. Alternatively, for example, the U.N. Millennium Development Goals can function as an orientation guide, because 189 representatives of developed and developing countries decided upon these goals to combat poverty and its secondary effects. The following are the UN Millennium Development Goals (PCI Media Impact, 2007): 1. Eradicate extreme poverty and hunger; 2. Achieve universal primary education; 3. Promote gender equality and empower women; 4. Reduce child mortality; 5. Improve maternal health; 6. Combat HIV/AIDS, malaria, and other diseases;

17 The responsible organization Population and Family Life Education Programme (POFLEP) argued that this huge sample was necessary to adequately represent the sixteen cultures/tribes in Tanzania.

84 7. Ensure environmental sustainability; 8. And develop a global partnership for development. Dutta-Bergmann (2004) criticizes that much of the entertainment-education scholarship emphasizes questions of effectiveness and pays little attention to questions of ideology and the values that drive entertainment-education campaigns. He takes the fact that many entertainment-education programs are produced by two organizations – Population Communications International (PCI)18 and Johns Hopkins University’s Center for Communication Programs – as an example of paternalism by a dominant culture. According to Dutta-Bergmann (2004), both organizations are funded by the United States Agency for International Development (USAID). His critique focuses on the ways in which the dominant discourse of entertainment- education excludes what he calls “the subaltern voice” (p.7). Dutta-Bergmann (2004) writes that “a review of the literature on entertainment-education reveals the absence of articulation of the broader USAID interests that dictate entertainment-education campaigns (…) as tool of USAID, entertainment-education programs serve as the channels for introducing the commercial logic into subaltern spaces” (p. 8). He cites Singhal and Rogers (1999) as evidence for his statement: “…commercial interest can be served without scarifying social interest… The product advertised was Maggi 2- Minute Noodles, a radical consumer innovation in India” (Singhal & Rogers, 1999, p. 101). Although the USAID policy contains no reference to Dutta-Bergmann’s accusation (USAID, 2006), he raises an additional ethical concern here: the relationship between entertainment-education and commerce. Usual media products must fulfill requirements 1. of the audience and 2. of the advertiser (Krainer, 2001). These requirements are strongly connected since the more the recipients consume a media product, the more the product becomes attractive to advertisers. The most popular media products are aired during the most coveted advertising timeslots in which the greatest number of recipients can be reached. If an entertainment-education intervention is to be able to reach as many recipients as possible on the free media market, then it should become a famous media product shown during the most optimal timeslot. As these timeslots are important to advertisers, the entertainment- education program automatically becomes commercially effective. Thus if

18 Meanwhile Population Communications International (PCI) changed its name to PCI Media

Impact.

85 entertainment-education interventions are broadcast or published on a free media market, entertainment-education programs have to compete with “normal” media products; in case entertainment-education programs become popular and get the most valued airtime, they help in selling the “normal” products that are shown during advertising breaks. These rules need to be accepted if entertainment-education programs are to be implemented into the free media market. However some exceptions could contradict these rules including the fact that public national television broadcast stations have an educational function and, hence, can broadcast media products unconcerned with the advertising business.

“Is it ethical to have messages targeted toward a particular audience group in exclusion of others?” regards the audience segmentation dilemma. This is the third ethical question and involves the values of “helping other people” and “doing accurate scientific work.” Any kind of audience segmentation, either for reasons of targeting special sub-audiences (Fisher, 2003) or for methodological reasons, or when the population is divided into treatment and control groups, is problematic in ethical terms by denying an intervention to people who might have benefited from it (Brown & Singhal, 1993). In both cases people are excluded from the intervention and therefore these people cannot benefit from it. Poindexter (2004) reports that “the Tanzania Project provided such convincing evidence of the strong effects of entertainment-education that later projects have not found it worthwhile to include a control group in their research designs” (p. 34). He does not report whether discontinuing the use of a control group was done because of the ethical dilemma of control groups or to save money through reducing accompanying research. Yet accurate scientific work is the only possibility to enhance the entertainment-education strategy, to make it more effective, and thus to benefit more people in the future. Solutions to this dilemma would be a) to give all people access to the entertainment-education intervention after research completion (Singhal, Rogers, & Brown, 1993), b) to have a comparison instead of a control group, where the intervention is broadcast but less often (Singhal & Rogers, 1999), or c) limiting the size of the control group as much as possible (Singhal & Rogers, 1999).

The fourth question – „Is it ethical for nations that control the media to export their own cultural values and beliefs?” – is related to the prosocial content dilemma

86 and concerns the same values as the second question but goes one step further by asking (after someone has made a decision about what is prosocial, healthy, etc.) if it is ethical to export to another country entertainment-education products that contain values and beliefs that were created for a specific audience. According to Sthapitanonda-Sarabol and Singhal (1999) the degree to which an entertainment- education product can appeal to heterophilous – in sense of dissimilar – audience groups can be called “cultural shareability” (p. 205). In principle it is cost-saving if entertainment-education programs can be effectively used in different countries or for different audiences. For example, in the 1980s the Japanese series Oshin became famous in many cultures and countries such as Belgium, Mexico and Iran (see below) and thus transported its intended educational value to various audiences. The educational messages were about such “human values as love, endurance, forgiveness, and sacrifice, depicted though the life of the central character Oshin” (Svenkerud, Rahoi, & Singhal, 1995, p. 153). But as Dutta-Bergmann (2004) points out transporting values from one culture to another also involves a risk. He writes that the United States export the greatest amount of cultural products compared to other countries and that those cultural exports run the risk of negatively influencing the country to which they are transferred. A responsible discussion and formative research are necessary to clarify whether the intervention is appropriate for the importing country or not (see procedure above). An example for low cultural shareability is the famous U.S. soap opera The Bold and the Beautiful. It was very successful in the U.S. when it included a subplot about a man infected with HIV. Calls to a toll-free hotline increased after these episodes were broadcast (Kennedy et al., 2004). But the same effect cannot be expected in India, as a qualitative study by Rogers, Singhal, and Thombre (2004) found: Indian respondents said that The Bold and the Beautiful “is far removed from Indian culture and values” (p. 447) and that “it is unlikely that Indians would use a toll-free line as they would be loath to discuss HIV/AIDS with others” (p. 454).

The fifth and last question by Brown and Singhal (1993) – “Should we risk the unintended consequences of media designed to promote social change?” (unintended effects dilemma) – also involves the value of “helping other people,” which conflicts with the value of “control.” Not only entertainment-education programs can cause unintended effects; unintended effects of media products without any educational

87 purpose can also be quite effective. When the producers created Miami Vice, a famous 1980s television series, they did not intend to motivate people to buy guns. However, a demand grew for Sonny Crocket's19 gun, and gun shops were flooded with customer calls asking for this special gun (Brown & Singhal 1990). As demonstrated by the Archie-Bunker effect (cf. chapters 2.2.3 “challenges” and 2.5.4 “Factors Concerning the Audience”), however, even intended effects can have unintended consequences. An impressive example – besides the “original” Archie-Bunker effect – is the effects of Bhagwanti, a character in the Indian series, Hum Log. As Brown and Singhal (1990) report, Bhagwanti was created as a negative role model, but many women liked this character and took her as a positive role model instead (Singhal & Rogers, 1989; Brown & Singhal, 1993). As Singhal, Rogers, and Brown (1993) state, “sometimes the potentially powerful effects of soap operas on the social attitudes and beliefs of an audience are difficult to predict. Even the success of a program can produce negative social consequences unexpectedly” (p.14). As an example, they describe the following incident: The Japanese radio series about a poor laundry girl, Oshin, was broadcast in Iran in 1986 and grew in popularity. Women started naming their babies Oshin because of the series, and they accepted the original Oshin as a role model and even began to see her as a better role model than Prophet Muhammad’s daughter Fatima. This provoked the anger of Ayatollah Khomeini who then “imprisoned the head of radio and sentenced the director of Iran’s broadcasting agency’s ideological group to 50 lashes” in 1988 (Singhal, Rogers, & Brown, 1993, p. 14). As another example, Brown and Singhal (1993) again point to the Indian series, Hum Log. They say that the series produced unanticipated social problems, because it led to the “commercialization of Indian television and the proliferation of other advertiser-supported dramatic serials” (p. 98)20. PCI Media Impact presented the same finding in a more positive light. The organization says, “It was the first

19 The character, Sonny Crocket, was played by the actor Don Johnson. 20 In 1999 they valued this fact in a more positive manner when saying “the product advertised was Maggi 2-Minute Noodles, a radical consumer innovation in India” (p.101); or in 1990 they said about HumLog and Nestlé’s Maggi 2-Minute Noodles “The profits generated by the program demonstrated that prosocial television programs can be commercially successful” (p. 276) without mentioning any social problems in this context. In Singhal, Roger, and Brown (1993) it is explained that “financial support must be generated in order to finance the development of the entertainment- education media programs” (p. 11) and here the cooperation between Hum Log and Nestlé’s Maggi 2- Minute Noodles are mentioned as a positive example of commercial sponsoring of an entertainment- education program.

88 commercially sponsored program on Indian television. Hum Log's popularity, and the increased sales of Maggi 2-Minute Noodles, the advertised product, convinced many other advertisers to sponsor television programs. This led to an increase in locally produced television serials and encouraged the Indian film industry to become more involved in television production” (PCI Media Impact, 2007). This shows that the same fact can be interpreted in contradictory ways. But the discussion is not always about facts; sometimes it focuses on assumed rather than proven unintended effects. Brown and Singhal (1993) report that a great deal of discussion surrounded the showing in the U.S. of an AIDS prevention film about correct condom use for teenagers. They say that “concerned individuals” (p. 98) – meaning adolescents’ parents – worry that the film, although its purpose of sexual responsibility has good intentions, could produce antisocial consequences and motivate young people to have sex, thus producing an increase in sexual activity. No research was conducted to clarify whether these concerns are warranted or not. Cho and Salmon (2007) studied unintended effects of health communication campaigns and identified eleven different types of effects that can occur even if unintended (cf. Table 2 in Cho & Salmon, 2007, p. 300): 1. obfuscation, 2. dissonance, 3. boomerang (reaction is the opposite from what it is supposed to be), 4. epidemic of apprehension, 5. desensitization, 6. culpability, 7. opportunity cost, 8. social reproduction, 9. social norming, 10. enabling, and 11. system activation. These kinds of unintended effects can also be produced by entertainment-education programs. Thus, only accurate scientific studies, conducted in advance, can help to identify potential unintended effects of planned entertainment-education interventions (Lee, Salmon, & Witte, 2005). Yet an element of risk still remains; the best solutions would be a) to conduct accompanying research that would enable entertainment- education producers to react to new situations and b) to include potential unintended effects in the responsibility discourse. Yet another ethical problem occurs when using entertainment-education because there is no guarantee that after people change their attitudes, behavior etc. their lives will indeed be safer, healthier, or better. As reported earlier about the effects of Simplemente Maria, this telenovela not only led to young women going to literacy classes and buying Singer sewing machines, it also caused much frustration when women realized that their dream – being like Maria and becoming rich and famous – did not become true. The risk of disappointment should be taken into account when

89 creating an entertainment-education product. Brown and Singhal (1993) conclude that: in summary, whether or not it is ethical to produce and distribute prosocial entertainment media products depends on a number of factors, including the nature of the beliefs and behaviors being promoted, who decides what messages are beneficial to consumers of popular culture, to whom the messages are targeted, and what effects the promotion of certain beliefs or behaviors is likely to have on an audience (p. 98). Finding answers to their ethical question requires carefully conducted responsibility discourse, enabling people to make decisions about individual entertainment- education interventions. Additionally, carefully conducted research (formative and summative evaluation; cf. chapters 2.2.3 & 2.5.5) can provide important information for this discourse (Singhal & Rogers, 1999). Although there are many ethical concerns, one should not lose track of the benefits. Entertainment-education can reach people who otherwise would not be reached (i.e., with the use of brochures or other information sources). As the chapter about entertainment-education effects indicates, this strategy has positive effects on people and thus can help them to have a chance to live “safer, healthier, and happier lives” (Singhal and Rogers, 1999, p. 9). In the long run this can benefit not only individuals but also the entire society, because people who live safer and healthier lives do not incur as many costs (material or immaterial) to the society compared to those people who live unsafe and unhealthy lives.

2.7 Summary The use of entertainment to educate people has been a constant facet of human history; storytelling with intended learning messages has been used by humans for the entirety of recorded history (e.g. Greek theater, the Bible). Miguel Sabido and his work in the 1960s, however, is generally given credit for establishing entertainment- education strategy as it is known today (Sabido, 2004; Singhal & Rogers, 1999, 2003). Entertainment-education is a strategy that aims to inform people about various issues (health, social issues) while entertaining them. It can be implemented using various media (TV, radio, books/comics, theater etc.) and can address numerous topics (health or social issues). The definition of entertainment-education is

90 challenging, “entertainment” as well as “education” can be defined in various ways. The most common definition used in the literature states that: Entertainment Education is the process of purposely designing and implementing a media message to both entertain and educate, in order to increase knowledge about an issue, create favorable attitudes, and change overt behaviors. Entertainment Education seeks to capitalize on the appeal of popular media to show individuals how they can live safer, healthier, and happier lives. (Singhal & Rogers, 1999, p. 9; cf. Singhal & Rogers, 2002, 2003, 2004). An important aspect in relation to other concepts that could be confounded with the entertainment-education strategy is that entertainment-education implies definite pedagogical aims and its fundamental goal is to join education and entertainment in order to gain specific benefits. Piotrow and colleagues (1997) identified – on the basis of several TV and radio serial dramas – several strengths of entertainment-education, the so called “9 Ps”: 1. It is “pervasive” – entertainment is everywhere and important in everyone's life. The fact that mass media programs are mainly entertainment makes the use of entertainment-education logical (Glik et al., 1998). 2. It is “popular” – entertaining programs reach out to large audiences. Entertainment-education can thus reach out to large, voluntary audiences in contrast to more traditional educational media products (Maibach & Holtgrave, 1995). 3. It is “personal” – entertainment programs show characters who express their deepest thoughts and feelings. They can show very intimate conversations, providing the audience with the feeling that they are a participant in these personal moments. 4. It is “participatory” – audience members often talk about characters or stories, and sometimes even take an active part in theater or music performances; playing a digital game would intensify this strength. 5. It is “passionate” – facts seldom make people change their lives, but intense emotions are able to change behaviors. 6. It is “persuasive” – a big advantage of entertainment- education is that entertainment can help break down audience barriers and resistance to the educational content being presented (Maibach & Holtgrave, 1995). Audiences are often not as defensive towards entertainment programs as they might be against formal, often fear-based health messages in pure educational interventions. 7. It is “practical” – in every country, media professionals seek out ways to create popular entertainment programs. Entertainment-education practitioners should therefore collaborate with local professionals. 8. It is “proven effective” – research has shown

91 that entertainment-education can be effective (cf. chapter 2.4 “Effects of Entertainment-Education). 9. It is “profitable” – entertainment-education programs can be very popular and thus can fulfill commercial interests. Besides such strengths, there are also several challenges involved in the delivery and design of entertainment-education strategies. The Johns Hopkins University’s Center for Communication Programs (JHU/CCP) identifies seven major issues that pose a challenge for transmitting health advice through entertainment- education programs (Piotrow & Fossard, 2004). The first two points concern the balance between entertainment and education. Too much education and not enough entertainment as well as too much entertainment and not enough education can be problematic and lead to the loss of its appeal for the audience. The third point, poor quality entertainment, can also cause a reduction in the attention the audience pays to the entertainment-education intervention and thus reduce its effectiveness. Fourth, lack of urgency means that many long-term health risks do not have an immediate impact and therefore people underestimate them; therefore entertainment-education should show the long term consequences of detrimental behavior. Fifth, to avoid such long-term risks, routine actions are often recommended. Routine jobs are often underestimated in its effects and entertainment-education should show how important they are for a healthy or better life. Sixth, topics of entertainment-education often do not have an immediate personal relevance for the audience members. Their subjective risk perception is low, but from an objective point of view it might be high. Entertainment-education should provide the audience with a reality check so that they are sensitive to the issue at hand. Seventh, the embedded information in entertainment-education programs can be contrary to culture and tradition and cause public or inner conflicts. When this occurs, entertainment-education interventions should be designed as sensitively as possible to ensure that they do not provoke a negative or counterproductive reaction from audiences. In addition to the seven aspects listed above, possible misinterpretation of the educational content is a challenge for entertainment-education. The most familiar example is the Archie Bunker effect, which occurs when audience members identify with negative role models and interpret the embedded message in a way contrary to that intended. Another challenge is the kind of effect that can be expected; behavior change is generally the desired main aim of entertainment-education programs, but research has shown that entertainment-education sometimes causes only weak effects,

92 and ethical aspects can be a challenge when creating and broadcasting an entertainment-education intervention. Various theories and models are used to explain how entertainment-education works: models with steps/stages focus on the inner – often iterative – process people pass through before they change their behavior. The social psychological models stress the relevance of the individual’s perceptions, beliefs, attitudes, and values, because they can influence entertainment-education effectiveness. Cognitive models try to explain the functionality of the brain and neural processes taking place while an individual is exposed to an entertainment-education media product. Drama and role models are useful for entertainment-education programs because they can help to create an absorbing storyline that prompts people to watch/listen to/read the given entertainment-education intervention. Explaining audience interaction and reactions to media programs is the aim of audience-centered models, whereas contextual theories take a different approach to the issue and describe media products – and hence entertainment-education – in a broader context. To explain how entertainment- education works, hybrid models combine several theories. However, no all-embracing theory for entertainment-education, which would apply to all possible mediums, target groups, topics, countries etc. has yet been elaborated. This diversity (in media, target groups, topics, and countries) inherent in entertainment-education makes it difficult to say in advance whether an entertainment-education intervention will be effective or not. In fact, each entertainment-education intervention must be evaluated individually to test its effectiveness as well as to contribute to the growing knowledge gain regarding the processes behind entertainment-education effects (to strengthen its theoretical basis). Such evaluations of entertainment-education programs are undertaken in different ways. As noted by Singhal and Rogers (1999), the majority of entertainment- education evaluations involve after-only-surveys of effects, usually conducted as telephone surveys. To only survey after the intervention has taken place is problematic, as the direction of causality behind any changes cannot be defined. Another method is the before-after measurement of effects with pre- and post- surveys, but this is also problematic; a given effect could have been caused by other factors that cannot be controlled for. The same problem occurs when interrupted-time series are used. Before, during and some time after intervention, data is collected and compared, but effects could be caused by other variables that cannot be controlled for.

93 Field experiments – where treatment and comparison group are not randomly assigned – also run the risk that effects are not caused by the intervention but by other factors. To control for such variables, experiments should be conducted, but this is often unfeasible. One argument against experiments is the required use of control groups which can pose ethical problems (cf. chapter 2.6 about ethical considerations concerning the use of entertainment-education). An alternative evaluation strategy is the combination of different methods, so-called multiple method triangulation. Multiple research methods are used to measure the same variable or set of variables in different ways. The Tanzania Project, Twende na Wakati, was evaluated using multiple research methods: the evaluation was conducted with several treatment areas and one comparison group, pre- and post-measurement of behavioral effects, and data from surveys, clinics and other sources were included. This data was combined for data analysis (Singhal & Rogers, 1999). The effects impressed many entertainment- education practitioners to such an extent that later projects undertook evaluation without any control groups (Poindexter, 2004). To be able to write about what effects entertainment-education interventions can have, it is important to define what constitutes effectiveness in this context. Some researchers only accept direct effects – often in terms of behavioral change – as evidence of entertainment-education’s effectiveness (Sood, 2002; Yoder at al., 1996). Others also interpret indirect effects – like an increase in knowledge or change of attitudes – as indicators of an effective entertainment-education intervention (Kennedy et al, 2004; Poindexter, 2004; Piotrow & Fossard, 2004; Singhal & Rogers, 2002, 1999). The idea behind this is that before behavioral change takes place, each person goes through an inner process with several stages. Measuring indirect effects means measuring the status on the way to behavioral change. In case of prevention, measuring indirect effects makes sense, as people should learn the right behavior in advance, i.e. before they find themselves in an awkward or potentially dangerous setting. Concerning indirect effects, several authors have found evidence that knowledge gain is a prevalent effect of entertainment-education interventions (e.g. Roberto et al., 2007; Ritterfeld & Jin, 2005; Vaughan, Regis, & St. Catherine, 2000). Studies included health-related topics like HIV/AIDS or breast cancer, or information about social change. Gains in interest in health topics have been reported (Brodie et al., 2001; Kennedy et al., 2004), as have increases in self-efficacy (Lee, Salmon, &

94 Witte, 2005, Guttman, Gesser-Edelsburg, & Israelashvili, 2008; Sood, 2002; Middlestadt et al., 1995) and communication about the embedded message (Singhal & Vasanti, 2005; Yaser, 2004; Bouman, Maas, & Kok, 1998). Concerning direct effects, contraceptive use (Poindexter, 2004), gains in condom sale (Murphy & Cody, 2003) or actively demonstrating against partner abuse (Singhal & Rogers, 2002) are examples that provide empirical evidence for entertainment-education causing direct effects in terms of behavioral change. It can therefore be concluded that entertainment-education interventions can have positive effects for people. The effects of entertainment-education interventions can be influenced by various factors. These factors can relate to the entertainment-education medium itself, the environment in which entertainment-education is broadcast, the audience that receives an entertainment-education intervention, and the accompanying research that is done. Factors concerning the entertainment-education medium are rather obvious: choice of language and format, or the talent of scriptwriters, actors and all professionals who are involved in the production process all influence the effects of an entertainment-education product. Other factors include how engaging the characters are (the degree of realism should be such that people can relate it to their own lives), that entertainment and education should be balanced, and that positive messages should be repeated. A good epilogue can increase entertainment-education programs’ effectiveness, and the trustworthiness of sources is likewise an important point. An entertainment-education program should be composed of good narratives, essential for an engaging storyline. Influential factors that concern the environment need to take the (sub)cultures of the given audience into account, the range of financial support available (which affects the quality of technical expertise), and access to and availability of support services. The most-discussed environmental factor in the academic literature is the degree of media saturation: High media saturation means that the entertainment- education product must compete for audience attention, as there is a wider choice of media products. This wide range of media products also results in smaller audience sizes, i.e. fewer people can be reached by a given intervention. Additionally, competing media products often contain messages that are contrary to those of the entertainment-education intervention.

95 Audience characteristics can also affect an entertainment-education outcome: these factors are either on an individual level – for example sex, age, gender, personality traits, and psychological factors – or on a social level – for example social norms, the degree of interconnectedness of audience members, and generally accepted values and beliefs. Finally, the manner in which accompanying research is undertaken can influence entertainment-education’s effectiveness. Singhal and Rogers (1999) state that it is useful to combine qualitative and quantitative data collection and analyses methods to gain maximum benefit from the research. Each entertainment-education intervention raises ethical questions (Brown & Singhal, 1993), also called ethical dilemmas (Singhal & Rogers, 1999). These ethical questions and dilemmas can be seen as conflicts of values. The main value of entertainment-education can be interpreted as its ability to “help other people,” this value is in conflict with other values that concern entertainment-education interventions, such as the “self-determination of human beings,” “democracy,” “doing accurate scientific work,” or “control.” According to Löwisch (1995), responsibility discourses would be a practical solution for equitable moral actions. The intended action should be tested for ethical dilemmas before it is put into practice. In this way, a discourse surrounding responsibility of all parties concerned would provide guidance about the appropriateness of entertainment-education interventions. For each entertainment-education intervention, a responsibility discourse should take place to assess the cost-value ratio from an ethical point of view. Relating to the topic of the present thesis – the use of digital entertainment- education games – the chapter about the entertainment-education strategy provides the following insights: Not much information about “real” entertainment-education games exists so far, as only few games (cf. chapter 3.2.6 about digital entertainment- education games) have been conceptualized according to the entertainment-education definition (cf. chapter 2.2.1), and as most of the entertainment-education programs were developed for radio, television, or print media. Therefore, the theoretical background as well as studies about entertainment-education effects do not provide information directly concerning the use of digital games as entertainment-education media products. Nevertheless, some aspects and information from this research can be used for the present study.

96 According to the theories and models that have been used as theoretical background for previous studies, the stages/steps models provide information about useful indicators of indirect effects: knowledge, interest, and communication. Those will be included as variables for indirect effects in the current study. Of the social psychological theories, the best known is Bandura’s social learning theory, which cannot be easily transferred to digital games, but which points out the importance of an individual's perceived self-efficacy for the effectiveness of an entertainment-education program. Therefore, perceived self-efficacy will be included as influencing factor in the present study, as well as personal risk perception, as the Health Action Process Approach (HAPA) emphasizes its importance in the context of health behavior change. Also, the cognitive models do not provide concrete insights for digital entertainment-education games, but the elaboration likelihood model (ELM) and the theory of the triune brain point out that a successful entertainment-education product should at least activate both cognitive and affective processing. As the drama and role theories mainly focus on narratives, they are not relevant for the present study, nor are audience-centered theories, except for the aspect of the uses and gratification theory stating that a media product – in case of the present study the digital entertainment-education game – should be designed in such a way that it provides as many aspects as possible to make target audience members use it. Of the contextual theories only classical agenda setting seems to be useful for this study, as media can influence what issues people think about. Thus, a successful entertainment-education game can make its recipients think about the embedded topic. Hybrid models combine various theories and models to explain effects of entertainment-education programs. But they mainly focus on soap operas for television or radio and cannot be transferred to digital games. Entertainment-education’s effectiveness was reported with regard to increases in knowledge, interest, self-efficacy, communication, and behavior change. This is in accordance with the hierarchy of effects models: It makes sense to count not only direct effects of behavior change as success for an entertainment-education program, but also indirect effects (see above). Thus, it is useful to test the effectiveness of a digital entertainment-education game in terms of both direct and indirect effects. The factors that could affect an entertainment-education outcome (mentioned in chapter 2.5) also provide information/ideas that can be used for the present study: It

97 seems to be useful to create a digital game for adolescents as entertainment-education programs should be sub-culture specific, as appealing to the target group as possible, and as they should take age into account. Also, gender plays an important role, as do perceived self-efficacy and personal risk perception (cf. chapter 2.5). Regarding the theoretical background of digital entertainment-education games, in the following chapter, first play and then digital games are elaborated upon in order to explain their appeal, before the chapter focuses on the use of digital games for education and provides information about digital entertainment-education games in particular.

98 3. (Digital) Game-Playing

“Playing is learning – without realizing it” (Gerhard Hofer, Austrian Professor of Education Sciences)

3.1 Play 3.1.1 Introduction The prevalence of play behavior in humans and in several other species provides some evidence for the assumption that play is older than human species itself (Ohler & Nieding, 2006). Despite this, most research on play has focused on humans. Some authors see play as a need that is part of the basic anthropological configuration of human beings; every people in every era of human history did and does play (Scheuerl, 1986). Mogel (2008) goes one step further by suggesting that play is not only a need, but one of the fundamental systems of human life. He describes such fundamental systems in general as life-supporting and existence-saving; the same would seem to apply for play. This is in accordance with Huizinga (1950), who describes play as a basic need: he views the human being as homo ludens (the playing human), who develops his/her individual skills through play (Flitner, 2002). Play has various manifestations and functions (Mogel, 2008), and indeed the degree of complexity of play in a given society and the degree of complexity of that society's culture correlate (Hauser, 2006); the more complex a culture, the greater the number and the level of sophistication of skills that are needed for survival and for play. This indicates that different cultures use different kinds of play; in relation to youth culture, which can be described as a subculture (cf. Schwendter, 1973), it is noteworthy that adolescents use different forms of play compared to adults (for example, digital games). Games are one aspect of play, often referred to as play with rules. Digital games are one special form of games that require technical equipment to be played and that, compared to other kinds of play and games, are also a potent communication medium. Digital games therefore offer new possibilities as well as challenges in contrast to non-technical games.

99 This chapter gives a brief overview of play in general and its definitions, varieties, and theories, and discusses the distinction between play and game. This is followed by a section addressing digital games in particular, with their definitions and genres, some theories addressing why people play digital games, what negative and positive effects digital games can cause, and the extent to which they are compatible with learning. This is followed by a sub-section about digital games and the possibility of using them as entertainment-education media. The final part addresses girls in particular, focusing on what kind of digital games girls do (and do not) like to play.

3.1.2 Theories of Play Play and games have been the subject of academic and philosophical investigation since ancient times. Plato argued that social values and norms can be effectively imparted to individuals during play, while Aristotle focused on the recreational role of play (Matthies, 2006) and its importance for maintaining mental hygiene (Mogel, 2008). During the Middle Ages play was devalued; it was not in line with the dominant Christian morality of the time and disappeared from scientific discourse (Matthies, 2006). It was during the Enlightenment that interest in play once again arose: Rousseau's novel Émile: or, On Education included aspects of play, while John Locke identified play as a form of recreation. Locke went beyond this, however, in also identifying the potential advantage of combining play and learning. He related play only to children, whereas Johann Christoph Friedrich Guts Muths also examined the playing adult (Matthies, 2006). With the rise of Classicism and Romanticism came an enhancement in the appreciation and valuation of play. Friedrich Fröbel, typically regarded as the intellectual father of the kindergarten (Matthies, 2006; Flitner, 2002), is likely the best-known thinker of this time; he focused on child play, the meaning of toys, and the creation of pedagogical principles of education. With the rise of early psychology in the 19th century, Stanley Hall published his drive theory of play, assuming that play is a natural drive common to all more- advanced life forms, and naming this drive the play instinct (Flitner, 2002). Other psychologists, like Freud and Adler, stated that play acts as a coping strategy that helps children to assimilate or to compensate (Mogel, 2008). Freud suggested that

100 play offers children the opportunity to fulfill their dreams and wishes beyond real life and helps in acting out aggressive drives (Oppl, 2006). Freud describes play as an opportunity to assimilate impressions, strokes of fate, and conflicts with the pleasure principle and the repetition principle (Matthies, 2006). According to Flitner (2002), Freud also highlighted the relaxing aspects of play. Another psychoanalytic perception of play renews the catharsis thesis of play (cf. Flitner, 2002): play is not driven by an instinct but is a way to stress relief, acting as a purifier (Matthies, 2006). The philosopher and psychologist Karl Groos popularized a new point of view on play with his pre-exercise theory around the turn of the century (1901). He assumed that play is neither an instinct nor a way to relax ; he states that play has a functional use, in particular for self-education, practice (Matthies, 2006), and thus as a preparation for adulthood (Mogel, 2008; Flitner, 2002). Groos categorized play on the basis of its practical function and identified three categories: 1. play with sensory functions; 2. play with motor functions; and 3. play with intellectual functions (Matthies, 2006). Shortly thereafter, Eduard Claparede (1909, 1934, cited by Flitner, 2002) presented his theory of play; he supplemented Groos’ theory (see above) by stating that play is not only pre-exercise, but a strategy in creating self-awareness (Flitner, 2002). While playing, the ego is able to reach new areas of action and feeling while learning new skills and social competences. In doing so, the ego is strengthened; this is a process involving self-awareness rather than exercise. In the 20th century, many theories of play and games have been developed. A full review of this literature is beyond the scope of this section, but four examples are briefly described for illustrative purposes. The first three theories try to explain “why” humans play: 1. Piagets cognitive-developmental theory, 2. Heckhausen’s action- theoretical approach to the psychology of play, and 3. an evolutionary perspective of play. 4. the fourth theory is a phenomenological approach suggested by the reformist educator Scheuerl. For Piaget (1969), play serves to activate the process of cognitive development. His theory of play is interwoven with his well known cognitive- developmental theory. Play offers children the opportunity to gain experience in a non-real-life situation. They have the opportunity to test themselves in different contexts and to develop their experiences into skills; it is therefore a very important method allowing children to actively appropriate their worlds (Flitner, 2002).

101 Depending on the developmental stage, the child typically prefers different types of play. Piaget identifies three main types of play: 1. exercise play (during sensory-motor stage; from birth to age two), 2. character play (preoperational stage; age two until seven), and 3. games (in terms of play with rules, beginning with the concrete operational stage; age seven until twelve, and continuing through the formal operational stage starting at the age of twelve) (Flitner, 2002). Additionally, Piaget points out that play is a way for children to deal with the pressures of socialization and to relieve real-life stress (Oerter, 1995). Play has a deeper meaning; it helps to cope with life in situations where other techniques and opportunities cannot be used. Heckhausen provides a motivation psychological view on play (1973, 1978). He analyzed curiosity and exploration activities using intrinsic motivation as his theoretical backdrop (Matthies, 2006). He suggested five characteristics of play (Heckhausen, 1978): 1. play is purposeless, 2. play is an active way to deal with the world, 3. play has an undifferentiated target structure and an instantaneous sense of time, 4. play is a no real-life situation, and 5. play is characterized by an activation circle (a repetitive change between suspense and relief) (Heckhausen, 1978). Suspense is created using discrepancies; those discrepancies can be categorized as follows: 1. curiosity (discrepancy between current and past experiences), 2. surprise (discrepancy between current perceptions and expectations based on former experiences), 3. complexity (discrepancy between parts of current perceptions and experiences), and 4. insecurity (discrepancy between different expectations in terms of success and failure). Players prefer moderate suspense levels (Mogel 2008) and a rapid change between suspense and relief (Matthies, 2006; Flitner, 2002); they require the certainty that following each experience of suspense there will be a relief (Flitner, 2002). Ohler and Nieding (2006) advocate investigating play in an evolutionary context, particularly in light of its ubiquity in other species (cf. Hauser, 2006). Such an evolutionary psychological perspective posits that the ability to play has been an advantage for the species, increasing their fitness and therefore their chances of reproducing (Ohler, 2000; Ohler & Nieding, 2001; Ohler & Nieding, 2006). For Ohler and Nieding (2006), the function of play – and thus its beneficial characteristic – is neither practice nor pre-exercise but behavioral adaptation. Within their behavior- diversification proto-cognition theory of play (BD-PC theory) in animals and humans,

102 they write that “the basic assumption is that the behavior system 'play' was selected in evolution because of its potential to generate behavior variants” (Ohler & Nieding, 2006, p. 104). The BD-PC theory assumes that humans (and all species that show play behavior) have a play module. Such a play module is a feature fixed in the genetic pool of playing species and permitting variability at different behavioral and cognitive levels. This variability “is the invariant key component of the play module that remains stable despite new ontogenetically emerging play forms” (p. 110). The above theories have attempted to explain why humans play; the following is a description of Scheuerl’s (1986) phenomenological approach, focusing on the nature of play. He defines play as an activity that causes and maintains a course of motions that, compared to other courses of motions, has six typical characteristics (which he calls “moments”): 1. moment of freedom: this means that play is an activity unhampered by regulations. It is free from harms and worries. It is without responsibilities and consequences and is undertaken for its own sake; 2. moment of inner infinity: players tend to repeat their activities, they lose track of time, and the activity can feel like an endless extension of time; 3. moment of pseudo-reality: play takes place within non-real conditions, meaning that is has an “as-if” character; 4. moment of ambivalence: play should involve modest suspense levels, the outcome is not definably predictable; 5. moment of closeness: closeness underlines the process- oriented character of play. Play has its own autonomous laws, it is a separate process; and 6. moment of presence: because play is a separate process that takes place in its own pseudo-reality, it has its own temporal structure (cf. Matthies, 2006); a player's attention is focused on the present act of playing and not on an intended outcome (Klippel, 1980). Critics note the lack of a moment of “enjoyment” or “pleasure” or something similar in Scheuerl’s listing (Klippel, 1980); it is commonly accepted that play generates some kind of pleasure, and that pleasure is needed for play, as “when pleasure fades play stops” (Reilly, 1974, p. 60).

103 3.1.3 Definitions and Classification of Play Definitions21 Play is a cross-cultural phenomenon. The term “play” is used to describe various activities in different cultures that have occurred throughout human history – for example parlor games, gambling, playing by children, digital games, etc. Several definitions of the term “play” have been offered, but none has emerged as an unambiguous and widely accepted formalization (Pellegrini et al., 2007; Ohler & Nieding, 2006; Matthies, 2006; Klippel, 1980). Reilly (1974) even writes: only the naive could believe from reviewing the evidence of the literature, that play is a behavior having an identifiable nature. While common sense may confidently assert that there is such a thing as play, the literature assumes a rather weak position about what this phenomenon is (p. 113). That being said, a number of definitions are offered below for analytical clarification. Huizinga (1994) delineates play as a voluntary activity that takes place within certain limits of time and space with determined rules that are followed voluntarily; it is done for its own sake, and is accompanied by feelings of excitement and enjoyment, and the awareness of being in a situation different from normal life. He writes that play is: a free activity standing quite consciously outside “ordinary” life by being ”not serious,” but at the same time absorbing the player intensely and utterly. It is an activity connected with no material interest, and no profit can be gained by it. It proceeds within its own proper boundaries of time and space according to fixed rules and in an orderly manner. It promotes the formation of social groupings which tend to surround themselves with secrecy and to stress their difference from the common world by disguise or other means (Huizinga, 1950, p. 15). For Walter (1993), play is a specific and active form of human activity and behavior that is determined by an intense examination and interaction between individuals and reality, and by subjective (internal) and objective (external) factors. According to Oerter (1995, 1999), the following three characteristics are sufficient to describe play: 1. it is played for its own sake, 2. a change of the player's relationship to reality takes place, and 3. it includes repetition and ritual.

21 Definitions and theories in this context cannot always be separated accurately.

104 Hauser (2006) agrees with Oerter (1995, 1999) that play is played for its own sake and that relationship to reality changes, what he calls an “as-if situation,” but he identifies some additional aspects of play. Hauser’s (2006) five characteristics include: 1. intrinsic motivation, 2. activity being done for its own sake and not for an end, 3. the existence of an as-if situation, 4. the presence of positive emotions, and 5. a relaxed setting. He points out that an activity has to meet all five characteristics to be called play. Schäfer (1993), however, suggests that seven characteristics are needed to define play: 1. intrinsic motivation, 2. concentration on process activity (meaning that it is played for its own sake and that it is an activity for which no result is sought), 3. pleasant feelings, 4. involvement (that can lead to a loss of sense of time and place), 5. an as-if situation, 6. the freedom to give new meanings to objects, and 7. object- related variation of possible activities, driven by the question “what can I do with this object?”. Matthies (2006) reports that a comparison of contemporary definitions of play shows that the definitions indeed focus on different aspects of play, but that two characteristics are used by most authors to describe play: The first characteristic is pleasure. Many definitions state that play somehow causes positive feelings, pleasant emotions, fun, enjoyment or the like. The second characteristic is voluntariness. It is so taken for granted that play is voluntary that voluntariness is not explicitly mentioned in all definitions.

Classification The multifaceted nature of play that creates challenges in defining it also prevent a clear classification or typology of play from being developed (Klippel, 1980); play has, however, been categorized according to different aspects. Some authors focus on the manifestations or structure of the play, others focus on the playing subject (Matthies, 2006). Mogel (2008) categorizes play according to its functions for the player. He states that play and games are used for 1. adaptation, 2. insight, 3. expansion of the self, 4. improvement of one's own activities, 5. establishing order, 6. constitution and development of social behavior, 7. beneficial (positive) emotions, and 8. mental hygiene.

105 Most play categorizations, however, are developed according to the structure of the play activity. As stated above, Piaget identifies three main types of play that occur during cognitive development: 1. exercise play (during the sensorimotor stage; from birth to age two), 2. character play (preoperational stage; age two until seven), and 3. games (in terms of play by rules, this begins with the concrete operational stage; age seven until twelve, and goes on until the formal operational stage starting with the age of twelve) (Flitner, 2002). Other authors identify four main categories of play (e.g. Hauser, 2006; Einsiedler, 1999) that develop during childhood: 1. function play (age one until two), 2. fantasy and role play (two until six), 3. construction play (about three), 4. rule play/games (starts at four). This is in accordance with Scheuerl (1986), who also concludes that human play can appear in four different types that are very similar to those stated above: 1. active games (like function play), 2. competitive games (like play with rules/games), 3. play with acting aspects (like fantasy and role play), and 4. construction play (see above). Schmidtchen (1994) adds one more category (information and exploration play) and divides “fantasy and role play” into two separate categories: “symbol/fiction play” and “role play.” He thus argues that six different categories of play are needed: 1. sensorimotor play, 2. information and exploration play, 3. construction play, 4. symbol/fiction play, 5. role play, and 6. games (play with rules). Given that this section is mainly about digital games, the following subsection will briefly define games before focusing on the main topic itself.

3.1.4 Play and Game Games are usually referred to as play with rules (see above; Pellegrini, Dupuis & Smith, 2007; Schmidtchen, 1994). As games are one aspect of play, it can be concluded that the two general characteristics of play identified by Matthies (2006) – pleasure and voluntariness – also apply to games. As no unambiguous definition for play exists (see above), no unambiguous definition for games exists either. But beyond describing games as play with rules, authors have attempted to give a more nuanced definition of games. A popular definition is that “A game is a form of play in which the players adhere more or less strictly to certain traditions, regulations or rules, written or unwritten” (Johnson, 1925, p. 5). Juul (2005) provides a more detailed definition:

106 A game is a rule-based system with a variable and quantifiable outcome, where different outcomes are assigned different values, the player exerts effort in order to influence the outcome, the player feels emotionally attached to the outcome, and the consequences of the activity are optional and negotiable (p. 23). Games first appeared in cultures as adult activities that helped solve social conflicts (Oerter, 1995). Although play always has rules, within games the rules are predominant compared to all other elements of play (Klippel, 1980). Because it is necessary to follow rules when playing a game, it is logical that games by nature are more competitive than play in general (Klippel, 1980). The outcome can be measured on the basis of the results caused by following (and breaking) predetermined rules and can therefore be compared. Games have the purpose of social comparison using objective criteria. According to Oerter (1995), almost every game is a competition; this social comparison gives the individual the opportunity to self-evaluate. Such a game-based self-evaluation can be life supporting (Oerter, 1995). It makes sense to distinguish between the game itself and the play of the game (Neumann & Morgenstern, 1953). Particularly with reference to digital games, the extant research focuses on the act of playing rather than on the digital game itself.

3.2 Digital Games 3.2.1 History and Definition Digital games are a rapidly growing part of the entertainment industry (Taylor, Gresty, & Baskett, 2006): Wevers stated in 2001 that the international market for digital games was valued at approximately USD $50 billion. According to Klimmt (2004b), digital games are a favorite leisure time activity in Germany and other countries, especially for young people. Digital games’ successful story began in the early 1970s when a home version of Pong was released (Gimmler, 2007; Wink & Lindner, 2002). Pong is a simple but famous game that can still be played online (Wink & Lindner, 2002). The game has a black background with two white bars at both sides of the screen functioning as table tennis rackets that can be moved up and down. A white point functions as ball and moves between these two bars. Players are required to touch the ball with their bars to prevent it going out of bounds and allowing their opponent to gain a point. To play Pong in the 1970s required a special game pad. Another simple but famous game is Pac-Man, which became a best-seller in 1980 and even launched its own merchandise

107 line (Lowood, 2006; Laudowicz, 1998). Today Pac-Man is still popular and even has its own Facebook page. The character is a large circle named Pac-Man that appears to open and close its mouth. The aim of the game is to eat as many dots as possible in a labyrinth without being eaten by four ghosts. Sometimes special dots, so-called pills, appear that enable Pac-Man to eat the ghosts. In the 1980s it was easy to use home computers for playing games and consoles such as Commodore 64, Commodore Amiga, and Atari SF were released and became very successful; more and more games were developed to suit these consoles . In 1985 the game Super Mario Brothers by Nintendo was released and since then many versions of that game have come on the market. It has since become a classic digital game (Laudowicz, 1998) and was recently released for the Wii console (about Wii see below). The rapid development of personal computer technology in the early 1990s also improved the development of digital games . The possibilities offered by the invention of Pentium processors were particularly important for enabling the entertainment industry to provide highly advanced digital games (Klimmt, 2004b). Sony’s release of the Playstation in 1995 marked a turning point in console development (Klimmt, 2004b). Today consoles like Playstation 3, X-Box or Wii are technically able to provide games that look like real life and give the opportunity to play online with thousands of other players at the same time in virtual worlds. Characters are controlled via joystick, keyboard or with a wireless controller that enables the console to detect players’ movements. The player can thus control the character in the game by moving his/her own body. Handhelds, also known as portable consoles, have become increasingly popular. Many famous games like Super Mario Brothers are also available for handhelds like the Nintendo GameBoy. The GameBoy was mainly advertised for young men, whereas the Nintendo DS Lite is a handheld available in several colors, including pink, white, and black, intended to attract a new female audience (e.g. with Nintendogs – a game about taking care of and educating virtual dogs) as well as seniors (e.g. with Dr. Kawashima's Brain Training – a game to train cognitive skills). Digital games require electronic equipment, known as hardware, to be played. This hardware can be diverse and can include personal computers (PC), consoles, arcade games (in amusement arcades), handhelds (portable consoles), cell phones, and Personal Digital Assistants (PDA) (Gimmler, 2007). Depending on the hardware (PC, console etc.) that is used, the terms used for of the game tend to vary. For

108 example,“video games” are software for consoles (Klimmt, 2004b) and “computer games” in the traditional sense are played on a PC. “Digital games” is a term that includes all kind of game-software for all kind of hardware, but in general linguistic usage the term “computer game” is used to refer to digital games played with electronic equipment. From a purely technical point of view, it is logical to simply define digital games as software products (Klimmt, 2004b). From the perspective of game-playing research, digital games can be described as electronic toys (Mogel, 2008) based on computer technology (Gimmler, 2007). This technology allows digital games to include aspects of all types of play such as function, exploration, construction, and role play (Mogel, 2008). As mentioned above, digital games are a special type of game that requires electronic technology. But this is only one aspect that needs to be considered when trying to define digital games. They are also a type of medium (like books, TV, or the Internet). Digital games join both categories play and medium and are therefore are a new category (Klimmt, 2001, 2003). Compared to other media products like TV, radio, or print, the main difference is that digital games offer the opportunity to interact (Klimmt, 2004b). Other products like TV are linear and treat the audience as an observer (Zillmann, 1996), but when playing a digital game the player has an active role. The player needs to act to prevent the game from ending. This is in accordance with Gimmler (2007), who defines digital games as an interactive individual medium that is based on computer technology, and Reinhard and Dervin (2007) who define digital games in their study “as any form of interactive gameplay that requires some level of computer technology in order to operate” (p. 24). Klimmt (2004b) gives a definition of digital games that considers both aspects – play and medium – but he includes an important characteristic that was mentioned in most of the play and game definitions (see above, section about “play”), namely entertainment. He writes that “computer and video games are interactive media products that are produced and used for entertainment” (p. 696). The interactivity of digital games affects different levels: the player interacts with a digital game on the level of 1. the game interface, that is how a player gives input (e.g. joystick, key board) and how the output is presented (e.g. computer screen,

109 vibration joypad), 2. the game mechanics, which can be described as the physical laws of the game-world (e.g. it is possible to fly or to ride a broomstick), and 3. the game play in terms of the content of the game or the mission a player has to fulfill (Clanton, 2000). This description of the different interactivity levels implies that many different types of digital games exist. How digital games can be categorized is described in the following sub-section.

3.2.2 Classification The categorization of digital games into genres has become ambiguous with greater complexity and sophistication in game design (Clanton, 2000). Classifications can be established based on a game’s structure. This refers to the kind of hardware used (PC, console, handheld, etc.), how many players can play simultaneously (single player games vs. multiplayer games), if the player plays alone, against the computer or other players, and if the game has a final goal and game-over point once this goal is attained or if the game has no final goal and thus has an open structure. Beyond classifications based on game structure, the categorization of digital games is challenging. This is due to the rapid development of game technology that enables the digital game industry to sell reams of highly developed games every year. Wink and Lindner (2002) note, for example, that any categorization of digital games can only be short term because the development of digital games is faster than the research carried out about them. For example, in recently published classifications, no category exists that would explicitly include the games played with the console Wii or similar ones where the virtual characters are controlled by real moves of the player. Most of the proposed classifications are based on the activities and/or skills that are required to play a digital game: these can either relate to the games’ real-life activities/skills (like pressing a button or thinking about quizzes) or the virtual activities/skills (like shooting, jumping, or driving in a race). Clanton (2000) categorizes digital games according to the actual skills that are needed in order to successfully play them. He suggests 1. games of reasoning, 2. games of hand-eye skill and some luck, and 3. games of attention and strategic thinking. Fritz (1997) combines actual and virtual skills for his typology. He first makes a distinction between brain games and button games. Sub-categories of button games

110 include shooter, sport games, and funny games (those games are fun to play and look comical). Brain games are divided into adventures (with the three sub-categories text adventures, role games, and action/adventures) and simulations, which are sub- classified based on content: economic simulations, military and political simulations, and card and board games. Most categorizations, however, are only based on the virtual activities undertaken in a digital game. Smith (2006), for example, describes seven categories that are normally used in many of the various classification systems. These include: 1. Sports (any digital games with sports as its main topic); 2. Driving/racing (digital games about car racing, e.g. Gran Turismo); 3. Simulation (typically the player operates a vehicle, most often an airplane through a virtual world, for example the Flight Simulator); 4. Strategy (main goal is to acquire and to utilize resources, this can be done within various narrative frames; some games are placed in the Middle Age or in science fiction worlds. But the most famous example according to Smith (2006) is The Sims); 5. Role-playing (these games focus on the creation of a virtual character and its interaction with the virtual environment); 6. Shooting/shooter (players’ task is to eliminate – mostly by shooting – enemies, usually in an first-person perspective, as for example in Doom); and 7. Fighting/fighter (players fight against one or more virtual characters operated by the computer or controlled by other players; fighting is usually boxing or wrestling, with or without weapons; Tekken is a typical fight game). Smith (2006) states that authors are actually implicitly consistent when referring to those seven categories. Less consistent is the usage of categories labeled action, adventure, action-adventure, first-person action, or platform action. Smith (2006) combines action and adventure into one category (the player moves an avatar through a virtual world and solves problems; the Grand Theft Auto series is a typical example for action-adventure games). Additionally, Smith (2006) lists the categories “puzzle games,” for example Tetris, and “quiz games” (e.g. Who Wants to Be a Millionaire?) and states that these are clearly defined. Even Smith’s (2006) consistently used categories, however, can be defined in different ways. For example, Smith (2006) assigns The Sims to the strategy games category, whereas Sellers (2006) mention The Sims as an example of a

111 typical simulation game. For Sellers (2006), strategy games can be described with the 4 X: explore, expand, exploit, and exterminate. The goals generally involve exploring a landscape, expanding areas under control, extracting resources, and exterminating enemies. Neither Sellers (2006) nor Smith (2006) include a category called “jump & run” or platform games (for example, Super Mario Brothers), although this is a term often used by adolescents when asked what games they enjoy playing (Fromme, 2000). Vollmer (2000) takes this category into account. He also takes into account the skills a player needs to successfully play a game; and he attempts to classify adolescents’ favorite games: 1. fight games, 2. jump & run games 3. adventure (with the three sub-categories action-adventures, mystery games and role games), 4. simulation games (divided into economic simulation, military simulations, building up and system simulations), 5. sport games, 6. racing and flight games, and 7. thinking and games of skill. Mogel (2008) rejects categorizing digital games by choosing either one category or the other: he suggests reducing digital games to four elements (skillfulness, strategy, simulation, and role play). According to him each digital game consists of all four elements, but with varying proportions. Another categorization is used by Klimmt (2004b). He criticizes customary classifications as often being incoherent and quickly becoming obsolete. His approach focuses on the characteristics that are important for players’ experience during digital game use and he effects the game can have on players. In doing so, Klimmt (2004b) suggests taking three aspects for classifying digital games into consideration: First, the narrative context, second, the tasks the player has to cope with and third, the form of representation. 1. Narrative context gives sense to a game, it provides a frame in which the game happens and a role to the player. 2. Two different aspects are important in relation to the kind of tasks undertaken: time pressure and complexity. High-speed games require a high level of attention, for example, racing games, whereas adventure games can be played without time pressure. Complexity concerns the number of different elements the player must keep in mind while playing, their interaction and momentum. 3. Forms of representation refer to the ways in which space and time are represented in a game. For example, the use of three-dimensional presentation and real time makes it feel more like a simulation than a game. According to Klimmt

112 (2004b), these three aspects need to be coordinated and harmonized in order to create a coherent and entertaining media product. The spectrum of different approaches to categorization mentioned above demonstrates that this issue cannot be well defined and that any categorization of digital games is a decision that has to be made according to its purpose (e.g. asking adolescents about their gaming habits or giving an overview of up-to-date digital games and their challenges for scholars) and that categorizations are temporary.

3.2.3 Why People Play Digital Games Introduction It would go far beyond the scope of this chapter to discuss all theories used to explain the effects that digital games are assumed to have. As stated above, games are a special type of play and – just as with play – games are also a voluntary activity associated with positive feelings. The same applies to digital games. As voluntariness is a central feature of playing (digital) games and is also important for successful entertainment-education interventions (cf. chapter 2.2 “Definition, Strengths, and Challenges”), it is of special importance for this study to investigate theoretical explanations of why people play digital games. It can be assumed that digital games are played because the players experience enjoyment while playing them (Klimmt, 2003). Mogel (2008) points out that this is the main motivation for playing digital games: it is a pleasurable way to spend time. Flow (Csikszentmihalyi, 1990, 1992) is a concept that is often mentioned when referring to pleasurable activities. During flow experience, people feel merged with their activities; it is like flowing from one moment to another (Wink & Lindner, 2002). Sellers (2006) describes flow as a very attractive state that people want to experience as often as possible. In this state people experience feelings of “pleasure, well-being, and increased cognitive efficiency that occurs during an absorbing task” (Lieberman, 2009, p. 382). This task needs to be challenging enough to encourage people to give their best. If the challenge is too great, people feel overstrained, whereas if the task is not challenging enough, people get bored: in those cases no flow experience will occur (Wink & Lindner, 2002). In relation to digital games this is in accordance with Clanton (2000), who suggests that “successful games present a clear mission early so that the player understands what they are trying to achieve” (p. 309).

113 Flow will emerge when people have a feeling of control and are very concentrated and engaged in their activity (Lee & Peng, 2006). This is why people lose their sense of time and space while experiencing flow (Lieberman, 2009). But flow is only one explanation for the fascination surrounding digital games (see below).

Collections of Reasons for Playing Digital Games Schell (1989) analyzed literature about the topic and conducted surveys; he concludes that nine reasons for playing digital games exist: 1. suspense, 2. relief, 3. immersion into a virtual world, 4. power, 5. success, 6. clearness, 7. esthetics, 8. compensation, and 9. social interaction: Suspense means that playing digital games makes the players feeling stimulated and thrilled. To keep the suspense level high, there is usually an increase in stimulating characteristics during the game, e.g. by the use of more opponents, obstacles, and the like. Relief concerns the fact that players feel relaxed by playing digital games. One aspect that can support relief, but that is according to Schell (1989) also a discrete aspect why people play, is to immerse into a virtual world while playing digital games. The player feels as though they are being transported into the virtual world. Another aspect is power, because playing a digital game is interactive and the player actively participates: everything the player does has an effect on the games’ process. Success means positive feedback that the player gets from the digital game, for example by reaching higher levels or the final end of a game. To be able to act successfully, it is necessary to understand the rules and the possible courses of action of a game. If this clearness is missing, players usually stop playing. Some players like to play digital games because of their appealing esthetics. Digital games are highly developed software products that can either copy reality or create virtual fantasy worlds. Both options can be fascinating. As children and adolescents lead increasingly urbanized and sedentary lives and do not have the opportunity to play outside, playing digital games can be a form of compensation, because here they can satisfy their thirst for adventure by being treasure hunters and going on a journey of exploration.

114 The last aspect Schell (1989) mentions is social interaction, because players not only play with each other, they also communicate about their game processes and the digital games they use to play among each other. Sherry et al. (2006) conducted focus groups to identify the most common reasons for playing digital games: they found evidence for six dominant dimensions that are slightly different from Schell’s (1989) suggestion, but overlap in several respects. Sherry et al. (2006) list 1. arousal, 2. challenge, 3. competition, 4. diversion, 5. fantasy, and 6. social interaction as reasons for playing digital games: Arousal. This means that the individual is physically stimulated. This most often happens because of the fast action in the game and high-quality graphics. Challenge. Players like to solve problems, etc. to reach higher levels or win the game. They want to improve their skills to be able to do so. This reaching out for better scores can be addictive. Competition. Sherry et al. (2006) mention that this category was the one most often mentioned by male participants when people try to explain why they play. Players compete with each other to find out who has the best skills to win the game. Diversion. Some players want to avoid stress, they want to relax, or just to fill time instead of being bored. Fantasy. Players enjoy doing things they normally cannot do in real-life. For example, driving fast cars, fly, or fight. Social interaction. Especially children often report that they play because of social interaction. There is a need to play digital games to be “cool” (Sherry et al., 2006, p. 218). Adult players play digital games to be able to interact with others (e.g. when talking about games) and to learn about other peoples' personalities. Interestingly no dimension called pleasure, fun, or enjoyment is listed by Schell (1989) or Sherry et al. (2006). A possible explanation would be that they asked people why they enjoy playing, so that pleasure etc. was not explicitly mentioned, but rather the reasons why playing digital games is entertaining for them. Raney, Smith, and Baker (2006) studied the appeal of digital games for adolescents; they report psychological as well as social reasons for playing digital games. They also mention the importance of game content to the psychological appeals of digital games.

115 As reasons for the psychological appeal of video games, Raney et al. (2006) list 1. pleasure and enjoyment, 2. excitation and arousal, 3. mood enhancement and management, and 4. mastering the challenge. Pleasure and enjoyment. Enjoyment is a reason why adolescents seek to play digital games, “enjoyment is a motivation itself” (Raney et al., 2006, p. 166), they report that six out of ten participants mentioned playing more and longer than planned because they enjoy playing the game so much. An important question is what causes this feeling of pleasure and enjoyment. Excitation and arousal. Playing digital games can influence players’ physiological level, for example by increasing arousal (e.g. an increase in heart rate); adolescents like these feelings of physical stimulation. Mood-enhancement and -management. Raney et al. (2006) state that according to mood-management theory people use media products – and hence digital games as well – to “utilize specific media content to minimize the life and bad moods and maximize the life and intensity of good moods” (p. 168). Adolescents might use digital games for the “purpose of excitation” (p. 168) excitation in this context being seen as a positive mood state. Mastering the challenge. Participants reported that they like the challenges digital games offer, especially the cognitive ones. They enjoy being able to solve the problems (Raney et al., 2006). Raney et al. (2006) also discuss the importance of game content to the psychological appeal mentioned above. In this context, they name interactive features, suspenseful content, violent content, and other antisocial content like pornography as influencing factors. In terms of the social appeal of digital games, Raney et al. (2006) state that playing digital games is often a social experience. Adolescents either play with or against each other or they play by themselves but talk about their experiences. Raney et al. (2006) write that the adolescents in their focus groups said that they like to buy and play those games that are most often talked about in their peer group.

Models of Digital Game Playing The aforementioned concepts, although attempting to explain why people play digital games, actually list reasons for playing digital games rather than explain it in context. This would require a more nuanced and multifaceted model.

116 Klimmt (2004b) developed a theoretical model to explain the enjoyment of playing digital games. The description of the model below follows Klimmt (2003, 2004b). He provides a three-level hierarchical model to explain how the interactivity of digital games is connected with the entertainment experience of playing digital games. To do so, he first describes the process characteristics of playing digital games within a three-level structure. The first level is the basic level; here loops of players’ input and computers’ output are relevant: for example, the player turns the joystick to the left and the virtual character starts running to the left side of the screen. The second level is the so-called intermediate level. Here, the game process consists of sequenced episodes. An episode usually comprises many loops of input and output. For example, fighting against a monster in order to reach the next gaming level and to get additional skills is an episode. Klimmt (2003) points out that episodes usually have the following four characteristics: First, certain action possibilities are provided. For example, in a fighting scenario, the virtual character can use a sword, move around, or curse the enemy, but cannot sing, dance, or fly. Second, an action is generally necessary. For instance, the enemy in the fighting scenario makes an assault upon the virtual character, prompting a response. Third, the player performs an action, like fighting back and beating the enemy. Fourth, a result happens that connects one episode to another, for example, if the enemy is beaten, a new challenge in the form of two monsters appear. The third level of the game-playing process is the so-called general activity level. Here, narratives emerge as the player takes part in the plot of the game. On this level, many episodes and reams of loops of input and output merge to a form of general activity that is related to the whole gaming session. For example, the player has the mission to conquer and colonize a country. On this level “narrative interconnections between episodes” (Klimmt, 2003, p. 250) are important (for example, magic skills acquired at the beginning of the game can be essential for the final showdown). Based on this three-level structure, Klimmt (2003, 2004b) provides his model of enjoyment of playing digital games. Concerning the basic level, with its loops of input and output, the player enjoys the directness to which the digital game reacts on the players’ input. Computer systems can register, process, and give feedback to the player depending on the input given by the player. The computer system used changes

117 depending on the actions involved in the game and in terms of input by the user. Therefore the player experiences a high level of affective stimulation when interacting with a computer system. This experience is a reason why people like to use computer (games). Klimmt (2003) writes, “such direct connections between actions and outcomes make the individual perceive her-/himself as causal agent” (p. 250). The direct feedback to the users’ input makes digital games attractive for people, thus users are intrinsically motivated to use digital games and spend much time playing (see also Oerter, 1999, cited by Klimmt, 2004b). On the second level – the intermediate level – which involves episodes, the computer system is autonomous to some extent as the digital game consists of static elements – in terms of components that cannot be influenced, e.g. the course of roads – and dynamic elements that react to the players’ input (for example, the car on the road that can be controlled). Klimmt (2003) identifies four relevant dimensions of digital game enjoyment on this level: curiosity, suspense, relief, and increase of self- esteem. Curiosity occurs if the offered possibilities to act arouse players’ interest and the player starts exploring. This “exploratory behavior is linked to the state of curiosity and pleasurable levels of excitation” (p. 247). Suspense and relief emerge in situations where a game produces a necessity to act. The player will then be uncertain about the result of the episode, initiating feelings of suspense and thus the hope for a happy ending and hence the hope for feelings of relief. Such chains of feelings of suspense and relief usually cause pleasurable feelings for the player. Furthermore Klimmt (2003) suggests that successfully dealing with an episode is experienced as a mastery experience that can cause “intense feelings of relief, because the players' perceive themselves as originators of the victory” (p. 249). This can prompt an increase in self-efficacy “which is always experienced as highly pleasurable” (p. 251). In the contrary situation, however, when the player fails to deal with the episode, feelings of frustration will occur. In this situation a player can react either by trying again or by stopping the game. The third level of the model is the general activity level. Here the interactive gaming elements and game narratives are connected and the player becomes a part of the game world. This game world has its own rules and is usually very different from reality. Players can have experiences that they could not have had in the real world (Klimmt, 2004b). The game offers the opportunity for new experiences and in situations where the player assumes a new role; s/he can vicariously gain experiences

118 that s/he otherwise could not have had. This can function as an escape from real life and can be a compensation for real-life problems by causing feelings of “importance and competence” (Klimmt, 2003, p. 254). In sum, Klimmt (2003, 2004b) identifies three key elements for the enjoyment of digital games: 1. effectance, 2. cycles of suspense and relief, and 3. the possibility to escape from real life. Gimmler (2007) identifies other reasons for playing digital games: he suggests that people play digital games because of 1. primary motivation (selecting digital games because of interest in specific topics like soccer or adventures), 2. secondary motivation (selecting digital games to supply needs like control, power, or success), and 3. situational reasons (like boredom, stress, or the release of a new digital game). These reasons are related to some aspects that Fritz (1997a,b) provides in his model to explain why people play digital games. He points out that players want to achieve positive feelings by using digital games, whereas his main attention focuses to a lesser extent on the appealing opportunities a digital game offers to the players. Fritz (1997a,b) rather provides a model of a process that develops when players select a game and start playing with the aim of evoking positive feelings. According to Wink and Lindner (2002) Fritz states that digital game playing starts with a primary motivation sources – for example, the player is bored, is looking out for distraction, is seeking emotional release, or wants to have success. If this motivation becomes strong enough, people select a digital game. The primary stimulating nature (e.g. how attractive playing the game is; that is, whether it covers interesting topics or includes a famous character, good graphics, sounds and animation, or whatever is appealing to the potential player) of the games defines which kind of game will be played. The player then starts with primary game playing actions: he or she tries to understand the game play, how to handle the virtual character, and how to get into the game (Wink & Lindner, 2002). If the game does not fulfill the players’ expectations, the player will not continue playing. In cases where the digital game meets expectations, the player continues playing. Then the secondary stimulating nature of the digital game becomes relevant: for example, being able to understand the game play, being able to handle the avatar, being able to successfully continue the game. These secondary stimulative natures of the digital game lead to secondary game playing actions like making an effort, being concentrated, enduring stress, and having some kind of failure resistance (Wink & Lindner, 2002). According

119 to Fritz (1997a,b; Wink & Lindner, 2002) the digital games’ appeal consists primarily of achieving success and exercising control. Fritz (1997a,b) identifies two cycles that can explain the captivation digital games can provoke, the spiral of flow or the spiral of frustration. One cycle involves reaching a positive emotional outcome by playing the game, leading to a feeling of success and potentially to flow experience (see above). The player then wants to repeat this positive feeling as often as possible and does not want to stop playing; this can be called a spiral of flow. Game playing will stop once all challenges are successfully met, because in that case the player becomes bored because the digital game cannot provide any new challenges for him/her. Alternatively, the course of the game can lead to a negative emotional outcome, causing the player to stop playing because s/he is frustrated or – because negative feelings can be captivating – efforts are intensified, because the unreached goals become even more desirable (Wink & Lindner, 2002). In this case a spiral of frustration is activated and playing is no longer enjoyable, potentially even leading to negative outcomes (cf. chapter 3.2.4.1 about negative effects below).

Most of the models that describe why people play digital games are in the broadest sense concerned with the opportunity to use digital games as a way to spend time pleasurably. The concept of flow is well-known, but not all players experience flow while playing digital games. Therefore, research has tried to identify additional reasons and motives for playing digital games. This was done either in a theoretical way (e.g., Schell, 1989) or on an empirical basis (e.g., doing focus groups and afterwards conducting factor analysis, cf. Sherry et al., 2006). Several collections of reasons and/or motives for playing digital games exist; most of them include various aspects that lead to the experience of enjoyment, e.g., arousal, challenge, fantasy, or social interaction (e.g., Schell, 1989; Sherry et al., 2006; Raney, Smith, & Baker, 2006). But such collections of reasons for playing digital games only give insight into what players themselves assume to be their reasons and motives or what researchers theoretically assume what players think about the reasons and motives for playing. These collections do not explain the processes that are at the basis of selecting and playing a specific digital game.

120 Klimmt (2004b) provides a model of enjoyment of digital games that considers three levels of interactivity in digital games and how these are connected to the entertainment experience. It goes beyond a simple collection of reasons but neglects an aspect of digital gaming that was included in a model by Fritz (1997a,b): Besides a spiral of flow he also considers a spiral of frustration as a reason why players are not able to stop playing even when they experience strong negative emotions and outcomes. The next sub-section addresses such negative effects potentially produced by digital game playing, followed by a description of positive effects.

3.2.4 Effects of Digital Games As digital games differ a lot regarding content and activities, as do players (for example in terms of personality traits, competencies, or experiences) (Gimmler, 2007), and the way studies are conducted, heterogeneous findings about the effects of playing digital games have been reported. Many studies were either conducted to research the negative effects of digital games with violent content, or the positive (educational) effects entertainment games could have. Few or no results can be reported suggesting the existence of positive effects of violent games or negative effects of educational games (Lee & Peng, 2006).

3.2.4.1 Negative Effects A special case: Violence When referring to the negative effects of digital games, the debate surrounding violence automatically arises: Do violent digital games make players violent? This concern that violent digital games make players violent in reality is the most frequently researched effect concerning digital games and negative effects (Klimmt, 2004b). It would, however, go far beyond the scope of this thesis to present the whole discussion about digital game use and violence as its focus is on the positive effects that could be produced with a digital entertainment-education game; violence is therefore described only briefly. Many experimental single studies have been conducted addressing digital games and violence, but results are inconsistent (Griffiths, 1997). Lee and Peng (2006) provide an overview of negative effects of violent digital games and categorize

121 them as follows: 1. aggressive affects, 2. aggressive behavior, 3. aggressive thoughts, 4. physiological arousal, and 5. other social and psychological variables. Aggressive Affects. Lee and Peng (2006) state that several studies indicate that violent digital games lead to feelings of aggression compared to nonviolent digital games (Ballard & West, 1996), and can occasionally lead to an increased level of anxiety (Anderson & Ford, 1986). But Lee and Peng (2006) also report that some studies did not find any significant effects of digital game playing on aggressive affects (Scott, 1995). They state that Anderson and Dill (2000) explain this fact by concluding “that playing violent video games affects violent behavior through a cognitive path, not through an affective path” (Lee & Peng, 2006, p. 330; see aggressive thoughts). Aggressive behavior. The results concerning aggressive behavior are also heterogeneous. According to Lee and Peng (2006), several studies provide evidence that playing digital games with violent content results in aggressive behavior afterwards (Anderson & Dill, 2000; Cohn, 1996; Schutte et al., 1988; Silvern & Williamson, 1987), where aggressive behavior is measured in various ways, for example in children's free play (Subrahmanyam et al., 2001; Cooper & Mackie, 1986; Irwin & Gross, 1995). Studies also exist, however, that could not find such a relationship (e.g. Winkel et al., 1987; Graybill et al., 1987; Cooper & Mackie, 1986; Kirsh, 1998). Aggressive thoughts. Lee and Peng (2006) report that results regarding aggressive thoughts are rather consistent. Aggressive thoughts are measured, for example, as short-term effects in terms of time needed to react to aggressive words (Anderson & Dill, 2000). Subrahmanyam et al. (2001) report that, concerning long- term effects, the regular playing of digital games with violent content makes aggressive thoughts persistently available to players’ minds (Bushman, 1998), as well as increasing aggressive responses on ambivalent open-ended questions (Kirsh, 1998). Physiological arousal. Lee and Peng (2006) found studies that provide evidence for the effects of violent digital games on physiological arousal: Playing violent digital games thus leads to increases in heart rate (Ballard & West, 1996, Fleming & Rickwood, 2001) and in blood pressure compared to playing nonviolent digital games (Ballard & West, 1996). Other social and psychological variables. Lee and Peng (2006) point out that not only violent effects are of interest, but those that may prompt antisocial behaviors;

122 this was addressed in a study by Wiegman and Schie (1998). Using a survey, Anderson and Dill (2000) found that playing violent digital games functions as predictor for various delinquent behaviors, for example, drinking alcohol or vandalism. The aforementioned – rather mixed – results refer to single studies or surveys. Three major meta-analyses exist (Anderson, 2004; Anderson & Bushman, 2001; Sherry, 2001) that found small but significant effects of playing violent digital games on aggression. For Anderson (2004), there is no doubt that playing violent digital games results in aggression on a behavioral, cognitive, and emotional level. Weber, Ritterfeld, and Kostygina (2006) also state that they are “forced to conclude that within the bounds of the social science methodology, playing violent video games does increase aggressive reactions” (p. 355). But not all scholars come to the same conclusion. Several authors state that no conclusions concerning violent digital games and their effects on players can be drawn for methodological reasons (see Lee & Peng, 2006). For example, some complain that no long-term effects have been studied (Griffiths, 1999; Löschenkohl & Bleyer, 1995) and Gunter (2005) criticizes that aggression is often measured in simulated situations, addressing pretended instead of “real” aggressive behaviors. For example, aggressive behavior within children's free play is observed (Cooper & Mackie, 1986; Irwin & Gross, 1995), but it is questionable if they would also show aggressive behavior in real-life situations. Another methodological problem is the use of nonviolent digital games as comparative stimuli. Ladas (2003) criticize Anderson and Dill’s (2000) study because he states that the nonviolent game that was played by the comparison group (Myst) is a very slowly digital game without any action compared to the action game Wolfenstein played by the experimental group. For Ladas (2003), it is not surprising that the results between those two groups differ. He recommended using nonviolent but action digital games as comparative stimulus material (for example, sports games). Additionally, critics complain that surveys often only measure correlative relationships and that it is not clear whether people are aggressive because of playing violent digital games or whether aggressive people a priori select violent games (Weber, Ritterfeld, & Kostygina, 2006). Even within an experiment it is not easy to generate conclusions, as it can be criticized that a digital game as stimulus can be very

123 different for the participants as various possibilities exist concerning the way it can be played (Weber, Ritterfeld, & Kostygina, 2006; Klimmt, Vorderer & Ritterfeld, 2004). Thus participants’ gaming experience can differ greatly, for instance, in cases where a violent digital game is played, some players might make use of all violent options and pass through all challenges whereas others might not do so. For that reason, it is impossible to conclude that found effects are due to the game played in the course of the experiment (Klimmt & Trepte, 2003). Therefore field studies and longitudinal studies are required to clarify this issue in the future. Weber, Ritterfeld, and Kostygina (2006) expect higher effect sizes in the future because digital games become more and more realistic in design and more captivating in their story, and because Sherry (2001) found a positive relationship between the year a violent digital game was released and its effect on players. Time will therefore tell whether digital games with violent content make players behave aggressively in real life.

Negative Effects of Non-Violent Digital Entertainment Games As stated above, there is a lack of studies researching the negative effects of digital entertainment games without violent content (Lee & Peng, 2006). Lerchenmüller- Hilse and Hilse (1998) list some of these negative effects. They suggest that playing digital games for too long can lead to physical troubles such as headaches, irritated eyes, and muscle hardening, as well as to short-term effects on an emotional level such as fear, anger, and frustration. They also mention the risk of excessive playing with the aim of escapism or using games as a form of vicarious satisfaction (Lerchenmüller-Hilse & Hilse, 1998). Lee and Peng (2006) report that Griffiths and Hunt (1998) found out that one out of five adolescents are “dependent” on digital games. They prefer to use the term “dependent” instead of “addicted,” but nevertheless the term describes a predominantly negative state as it implies that players experience a need to play. Other negative emotional states are reported by Roe and Muijs (1998) (cited by Lee & Peng, 2006). They found that low self-esteem, poor academic achievement, and less sociability can be the result of excessive digital game playing.

124 3.2.4.2 Positive Effects Research has focused on negative outcomes of playing digital entertainment games before positive outcomes were noticed and studied (cf. Conolly, Boyle, MacArthur, Hainey, & Boyle, 2012). Just like the negative effects mentioned above, most of the positive effects of playing digital entertainment games that have been found (see below) were also not intended by game developers and producers. Although mostly unintended and incidental, positive impacts in terms of learning and behavioral outcomes can be found concerning knowledge acquisition/content understanding, perceptual and cognitive skills, affective outcomes, behavior change, and social outcomes (cf. Conolly et al., 2012).

Knowledge Acquisition/Content Understanding Connolly et al. (2012) found in their narrative literature review that several papers provide evidence that digital games can improve players’ knowledge concerning various subject disciplines, such as geography, mathematics, or history, but also concerning health and social issues.

Perceptual and Cognitive Skills Most of the research concerning the positive effects of digital entertainment games concerns cognitive skills. As Subrahmanyam et al. (2001) state, the term “cognitive skills” includes a wide range of aspects. Lerchenmüller-Hilse and Hilse (1998) see a great potential in digital games as they can improve children’s cognitive abilities such as logical reasoning or abstract thinking (Laudowicz, 1998). Wink and Lindner (2002) point out that increases in the parallel processing of different informational stimuli can be reported, and playing digital games can develop complex thinking strategies that are useful for problem solving (Lee & Peng, 2006; Connolly et al., 2012). This is in accordance with Doolittle (1995, in Lee & Peng, 2006), who concludes that playing digital games improves flexibility in the handling of knowledge structures, which are advantageous for solving problems. Van Schie and Wiegman (1997) found a positive relationship between intelligence performance and the amount of time spent with digital entertainment games, but as it is a correlation, the direction of causality cannot be defined. Several studies indicate that playing digital games can improve spatial abilities (Lee & Peng, 2006; Klimmt, 2004b). Especially females benefit from playing

125 digital action games, as their attentional and spatial skills can be improved, thus reducing the gender differences found in this area (Connolly et al., 2012). Subrahmanyam and Greenfield (2001, 1998) provide findings that suggest that playing digital games leads to an increase in spatial perception, and de Lisi and Wolford (2002) found that children's spatial abilities could be improved by digital games. This is in accordance with the results of Greenfield and Cocking’s (1996) study: Children with poor performance in spatial representation pre-tests benefited in particular from playing the digital game Marbele Madness. Subrahmanyam et al. (2001) conclude that “overall the research suggests that spatial skills are related to video game playing” (p. 14). Many scholars report improvements in hand-eye coordination (Neuß, 2006; Wink & Lindner, 2002; Lerchenmüller-Hilse & Hilse, 1998; Griffith, Voloschin, Gibb, & Bailey, 1983). Neuß (2006) suggests that this increase is due to using the mouse or a joystick to control a digital game. According to Subrahmanyam et al. (2001), iconic skills involve being able to read images such as diagrams or pictures. In digital games, much information is provided in picture/diagram form and players need to be able to capture and interpret the information embedded in it. Thus, these skills can be improved by playing digital games (see also Greenfieldet al., 1996).

Affective Outcomes Whereas many results about positive cognitive effects exist, less is known about the positive emotional effects of playing digital entertainment games. As players are often pressed for time when playing, children can learn to cope with stress and time pressure and become more stress resistant (Kraam, 2004; Lerchenmüller-Hilse & Hilse, 1998). Neuß (2006) observed that children who play digital games display emotional expressions such as amazement and curiosity, and pride in case of successful play.

Behavioral Change Digitally active games influence players’ behavior especially as they stimulate players to join in activities like dancing, singing, and clapping (Neuß, 2006). Digital games offer the opportunity to easily gain access to computer literacy and therefore to use computers more often than non-players do (Agosto, 2004).

126 Social Effects Concerning sociability, Lee and Peng (2006) report that playing digital games leads to an improvement, because adolescents in particular play together with friends and communicate about their gaming experience either face-to-face or online. Similar findings are reported by Neuß (2006), who also found that children tend to talk to each other about their gaming experiences and that they help each other to solve challenges, but that they also learn to establish themselves. Durkin and Barber (2002) also found positive effects of playing digital games in their survey. They mention that adolescents who play digital games reach more favorable scores compared to adolescents who never play digital games on family closeness, positive school engagement, positive mental health, self-concept, and friendship for example. They even conclude that “computer games can be a positive feature of a healthy adolescence” (Durkin & Barber, 2002, p. 373). The methodological critique concerning these studies is the same as for studies that have demonstrated negative effects (see above). Players who successfully solve the problems in a specific digital game must have the skills to be able to do so. But it is not clear whether the players learn these skills while playing or had the required skills a priori (Wink & Lindner, 2002). Even if players acquire skills through playing, this does not automatically indicate that these skills can be transferred and used in real life (Wink & Lindner, 2002; Sims & Mayer, 2002; Vollmer, 2000). The aforementioned positive effects indicate that digital games are not negative in general and that they can be used for meaningful outcomes. If so, this would be especially advantageous for adolescents, because this group are used to playing digital games. They have grown up in the digital age. For them computers, consoles, Internet, and the like are nothing out of the ordinary, thus they can be called “digital natives” (Prensky, 2001). This provides new perspectives on digital games: using them for beneficial purpose has potential. This is the topic of the next sub-section about digital games and learning.

127 3.2.5 Serious Games – The Use of Digital Games for Education 3.2.5.1 Introduction, Definition, and Classification The previous sub-chapter has shown that despite the discussion surrounding violent digital games, digital games can have positive effects, although those are unintended by game producers and players (cf. chapter 3.2.4.2 about positive effects). Thus, playing digital games can be beneficial for players, for example, by increasing players’ ability to think logically, or by training their problem solving skills (e.g. Kirriemuir & McFarlane, 2004). Research has shown that digital games can help players learn new skills, knowledge, attitudes, and even behaviors (Lieberman, 2009; Papastergiou, 2009). If playing digital entertainment games can lead to such positive outcomes, they have great potential as learning tools. This idea is not new; in fact, it is almost as old as digital games and was already discussed in the 1970ies (Lampert, Schwinge & Tolks, 2009; Abt, 1971). From time to time, digital entertainment games with learning aspects were created (e.g. Hawkins & Gustafson, 1987), but with the recent rapid development of technical opportunities of digital entertainment games and their increasing popularity, this idea came back into research focus. Digital entertainment games are very important and a favorite leisure time activity not only for some individuals, but for millions of players who use them regularly (Vorderer & Bryant, 2006). Peng (2009) points out that playing digital games is “one of the most dominant forms of entertainment” (p.2); accordingly Sellers (2006) conclude that “Games fill no practical need, but we play them anyway” (p. 21). Consequently, it makes sense to use digital games as an educational tool: they are played anyway and they can impact players (cf. chapter 3.2.4 “Effects of Digital Games”). The challenge is to control what kind of impact digital games have. Recently, some research on this issue has been done and many theoretical articles have been written about the combination of digital games and learning/education (e.g. Ritterfeld, Cody, & Vorderer, 2009). But digital games for learning/education are not only theoretically discussed: In the last years many digital games were released that should combine those two aspects. For example, America’s Army – Operations produced by the United States Army has the goal to inform people about military everyday life and thereby make players understand military life (Belanich et al., 2004). It is a very sophisticated digital game with realistic graphics that is played as a first-person

128 shooter (Shen, Wang, & Ritterfeld, 2009). Another example is the game Electrocardiogram produced by the Nobel Web AB. This game aims at teaching people the fundamental aspects as well as the handling of electrocardiograms. Within the game course the player has to interview patients, organize and operate the electrocardiogram, and to diagnose (Shen, Wang, & Ritterfeld, 2009). Londoner is a digital game created to teach historical information about London in the 17th century. The character lives in London in the 17th century and the player makes decisions about the character’s life and witnesses the outcomes of these decisions (Shen, Wang, & Ritterfeld, 2009). Those three examples show that the combination of digital games and learning/education can be very different in the end. As diverse as the games are the terms used to describe the combination of digital games and learning/education: serious games, educational games, edutainment, digital game-based learning, social impact learning, persuasive games, and games for change (Lampert, Schwinge, & Tolks, 2009). Because so many researchers from diverse disciplines (e.g. psychology, communication theory, game design etc.) are engaged in this rapidly growing field of research, no consistent terms and definitions emerged. Thus “there is still confusion concerning the characterization of a serious game” (Connolly et al, 2012, p. 672). Since 2002, the Serious Games Initiative is “most likely responsible for the visibility and popular adoption of the term serious games” (Wong et al., 2007, p. 50) and it seems that the term “serious games” has been established as scientific publications about digital games used for learning and education make use of it (e.g. Ritterfeld, Cody, & Vorderer, 2009). But that does not mean that a clear and consistent definition of serious games exists (Ratan & Ritterfeld, 2009). Some researchers even argue that every digital game can potentially be seen as a serious game, because theoretically every digital game has the potential to make players learn something (Konijn & Nije Bijvank, 2009). Most other researchers disagree, pointing out that serious games have goals beyond entertainment. For example, the definition given by the Social Impact Game Web site defines serious games as “entertaining games with non-entertaining goals” (Social Impact Games, 2008, cited in Ratan & Ritterfeld, 2009, p. 11). More specifically, Bente and Breuer (2009) indicate that digital games can be called serious only if they have “explicit, a priori defined, measurable learning goals” (Bente & Breuer, 2009, p. 324).

129 Egenfeldt-Nielsen (2006) suggests that learning can be an unintended process that happens accidentally, but if it is intended – meaning that a digital game has a specific goal as supposed for serious games by Bente and Breuer (2009) – it is education. Ritterfeld, Cody, and Vorderer (2009) also point out the explicit educational aspect of serious games: serious games can be customized digital games that were specifically and purposefully developed to educate (i.e. Math or Reading Blaster, Tactical Iraqui), or they can be over-the-counter games that primarily entertain its users while also providing educational opportunities (knowledge, skills) (i.e. World of Warcraft, The Sims) (p. 6, emphasis in the original). Furthermore, they explain that the term “educational” stands for “any desired increase in skills, knowledge, competency, and mastery, and favored changes in attitudes, values, or behaviors” (Ritterfeld, Cody, & Vorderer, 2009, p. 6). Ritterfeld (2009) goes one step further when she supports a conceptualization of serious games that includes goals that are not only educational (see above), but also beneficial for the players: Serious games should “serve the physical and or mental well-being of their user” (p. 213). These advantages for the user can occur “first by facilitating learning experiences and second by not having any negative or harmful impacts” (Ratan & Ritterfeld, 2009, p. 11). At first sight it might feel redundant to stress that serious games should have benefits for the players, but when looking at, for example, serious games produced by the U.S. Army which embedded its own educational goals, the question arises who benefits more: player or producer. In this context Lampert, Schwinge, and Tolks (2009) point out that there is a fine line between a learning tool and a propaganda vehicle. Not every digital game that is labeled as serious game by its producer meets the criteria of every definition mentioned above. To summarize, there are no established terms or consistent definitions of the various terms that are used in the context of serious games. Maybe the lowest common denominator is named by the Social Impact Games Web site where serious games are defined as “entertaining games with non-entertaining goals” (Social Impact Games, 2008, cited by Ratan & Ritterfeld, 2009, p. 11). Also, no established terms or consistent definitions exist yet for the classification of serious games. Fritz (1993) mentions that it is not possible to

130 definitely classify digital games for learning, because there are so many criteria a classification could be based on. Nevertheless, classifications have been done. It is quite obvious that such games can be grouped according to their content, e.g. serious games for health or serious games for political education (cf. Lampert, Schwinge, & Tolks, 2009). Another way to classify such games is according to the type of learning aimed at (Buckingham & Scanlon, 2003; Gee, 2009), e.g. knowledge acquisition, skill practice, or problem solving. But both ways can only be rough divisions, because serious games can include more than one topic and various types of learning (Ritterfeld, Cody, & Vorderer, 2009). Some researchers conceptualize digital learning games based on their level of qualification aspects – the education part – versus their level of fun – the entertainment part (e.g.Lee & Peng, 2006). In doing so, education and entertainment function as two opposite poles of the same dimension. From this point of view, they cannot be combined: The main focus is either education or entertainment. This means that a game can either be entertaining or educational. In contrast, Ritterfeld and Weber (2006) conceptualize entertainment and education as two different dimensions (cf. chapter 2.2.1 “Definition”). In this way, one and the same game can reach high scores on both dimensions, meaning that the game can be entertaining and educational at once. This is typical for so called entertainment-education interventions; the potential of serious games for entertainment-education is discussed below (cf. chapter 3.2.6 “Digital Entertainment- Education Games”). Ratan and Ritterfeld (2009) included more than 600 games in a study; their classification system for serious games took at least four dimensions into account: 1. primary educational content, 2. primary learning principle, 3. age of target players, and 4. platform used. Concerning primary educational content, 63% of the sample had an academic background, 14% dealt with social change, 9% with occupation, 8% focused on a health topic, 5% had a military background, and less than 1% aimed at marketing a certain issue. The primary learning principle used in serious games was mostly practicing skills (48%), gaining knowledge through exploration (21%), cognitive problem solving (24%), and social problem solving (7%). Results indicate that most of the games were either created for elementary school (39%) or for middle and high school

131 students (39%). 16% aimed at adult and senior people, and only 5% of the games were produced for children of preschool age and younger. Regarding the platform used for playing, most of the games (90%) were designed for the computer, the rest were created for DVD, the Nintendo game boy, Nintendo 64, Nintendo DS, Palm Pilot, Playstation, and Plug-and-Play consoles. Ratan and Ritterfeld (2009) conclude that the classification system they used for their study should function “as a guide to understanding and interpreting serious games as a medium” (p. 21). The specific characteristics of the medium “serious games” – especially those that differentiate them from traditional education – are considered in the next sub- chapter.

3.2.5.2 Effectiveness of Serious Games As described in the previous sub-chapter, the term serious game can have very different meanings and no generally accepted definition has emerged yet (see above). Accordingly, it is challenging to make definite statements about the effectiveness of serious games as the diversity of serious games, their underlying theories and empirical studies make it impossible and meaningless e.g. to conduct meta-analyses (cf. Connolly et al., 2012). More promising are narrative reviews about serious games and their effects to delineate the phenomenon serious games. Connolly et al. (2012) focused in their review on positive outcomes of digital games in general and of serious games in particular. They concluded that digital game playing “is linked to a range of perceptual, cognitive, behavioural, affective and motivational impacts and outcomes” (p. 661). A current review of the effectiveness of serious games was done by Wouters, van der Spek, and Oostendorp (2009). They reviewed 28 studies that provided empirical data about the effectiveness of serious games taking into account learning outcomes. Concerning knowledge skills Wouters et al. (2009) sum up that serious games increased knowledge acquisition, as three out of four papers reported serious games being effective that way. Specific game features sometimes did have an effect on players’ knowledge acquisition, as had relevance of information, game task and game type, but other studies showed that the game features level of stress, instructional guidelines and interactivity did not support knowledge acquisition (Wouters et al., 2009)

132 Similar conclusions can be drawn for cognitive skills: Four out of five studies in the review by Wouters et al. (2009) have shown that serious games are beneficial in training cognitive skills. For motor skills, findings have been different. Serious games have been created to teach surgery skills, but results about their effectiveness are inconsistent. Concerning affective learning outcomes Wouters et al. (2009) differentiate between changes of attitude and motivation. Concerning changes of attitude, for example concerning phobias (like the fear of spiders or accidents), serious games were found to change attitudes positively, but individual characteristics, e.g. being traumatized or not, have to be taken into account. Positive effects have also been found concerning attitudes towards school subjects (Wouters et al., 2009). A different picture emerges with regard to changes in motivation towards a certain subject or topic. It is not clear to what extent serious games are as motivating as digital entertainment games, as results are inconsistent. According to Wouters et al. (2009), some studies provide evidence that serious games can train communicative skills, whereas others did not find such evidence. Thus it remains unclear whether serious games train communicative skills or not. Wouters et al. (2009) criticize the widespread use of serious games without substantiated state of knowledge concerning their effectiveness; they sum up their review by stating that serious games are promising, but more research is required.

3.2.5.3 Specifics of (Serious) Games Compared to Traditional Education As education is mostly based on traditional media, the question arises what differentiates the digital gaming situation from traditional education, e.g. reading a book (Egenfeldt-Nielsen, 2006). Digital game technology features characteristics that clearly separate digital games from traditional media (Wang, Shen, & Ritterfeld, 2009). The characteristics of serious games mentioned in this chapter overlap with non-digital games (e.g. specific frame of play situations) as well as digital entertainment games (e.g. multimodality). The most obvious characteristic of digital games compared to traditional education tools is interactivity: with the opportunities for interactive features, the media user is no longer a passive consumer (Vorderer, 2000; Grodal, 2000); a player can actively influence the course of the game.

133 But there are more specifics to be considered. Klimmt (2009) suggests that aside from interactivity the following features distinguish traditional education from digital games for education: multimodality, narrative, option for social (multiplayer) use, and the specific frame of play situations. These five characteristics are described below, starting with multimodality because that is essential for interactivity, which will be second. Thirdly, the aspects of including narratives will be described, followed by the option for social (multiplayer) use, and the specific frame of play situations. In the following sub-chapters, the potentials and limitations that arise from these characteristics for serious games as education tools are discussed.

Multimodality Media use different information systems, also called “codes” (Paechter, 2007, p. 375). For instance, the verbal system uses words, the number system uses numbers, and the visual system uses visual material like pictures and films. A plain text is monocodal (for example, a textbook without any pictures), a website with text and photographs is multicodal, because two different information systems are used (Schaumburg & Issing, 2004; Paechter, 2007). Additionally, information can be addressed at different senses: for example, photographs and written text are experienced visually, music or spoken word aurally. While watching a movie, eyes and ears are used. Watching a movie is multimodal because more than one sense is addressed (Weidenmann, 2002). Digital games are mostly multimodal because of their graphics and sounds. Additionally, in recent years a haptic modality is included in digital games, mostly realized with vibrations (Klimmt, 2009). Most traditional education products have a lower degree of modality compared with digital games. Digital games are often called “multimedia”, but in this case the term “multimedia” is misused to describe a multicodal and multimodal media product. Strictly speaking there is no mixture of different media as the term “multi-media” suggests, but of different codes and/or modalities (cf. Schaumburg & Issing, 2004; Weidenmann, 2002).

134 Interactivity Interactivity is the main aspect that distinguishes digital games from traditional (entertainment) media (Peng, 2009; Vorderer, 2000; Grodal, 2000). The term “interactivity” is a combination of the Latin words “inter”, which means “between” and “agere” which means “to act” (Fritz, 1997). Originally, the term applied to two or more (human) beings that interact. In human interaction, it is important that the interacting persons understand each other. Every action – and even every non-action – includes a message and therefore influences the other person(s). The exchange process between human and computer is also called interactivity, but here it is different: it is not about understanding each other, but about controlling the program (Fritz, 1997). A human can control a computer system, meaning that a person gives input and awaits the computers’ reaction. Here, the focus lies on the technical aspects of interactivity, in accordance with Steuer (1988, cited in Peng, 2009), who states that interactivity is “the extent to which users can participate in modifying the form and content of a mediated environment in real-time“ (Steuer, 1988, p. 84, cited in Peng, 2009, p. 12). Klimmt (2009) also focuses on this technical aspect. For him, “interactivity is defined as a game property that allows users to influence the quality and course of events occurring in the game world” (Klimmt, 2009, p. 251. But humans and computers do not communicate with each other like humans do with each other. Instead, there is an exchange of information, in which the computer has a fixed amount of output options to give feedback to the player (Baranowski et al., 2008; Fritz, 1997). Thus it is not only the users’ control, but also the feedback given to the user that is important for perceived interactivity (Haack, 2002; Peng, 2009; Rafaeli, 1988). As the user reacts to the feedback, and his or her reaction leads to new feedback, loops of input and output emerge (Klimmt, 2003, 2004b; cf. chapter 3.2.3 “Why People Play Digital Games”). According to Sellers (2006), a common definition of interactivity used in game development requires the following aspects for a software to be called interactive. First, it needs to present state information to the user; second, it needs to enable users to take actions indirectly related to that state; third, it changes its state based on the user's action; and fourth, it should display the new state. Or in short, as Vorderer et al. (2006) suggest, “Interactivity...assumes that content evolves as the user participates with the medium” (p.2).

135 Narrative Context “Interestingly enough, narrative is also one of the most attractive features of video games” (Peng, 2009, p. 9) – at least in recent years, digital games include complex and appealing narrative frameworks (Klimmt, 2009). According to Dondlinger (2007), there is general consensus that narratives not only attract players, but also play an important role for a games’ effectiveness. In short, narratives motivate players and influence the processing of game content (Klimmt, 2009). Traditional education media are mostly based on facts (e.g. schoolbooks), not on narratives.

Social (Multiplayer) Use Klimmt (2009) indicates the technical requirements for multiplayer capabilities (on local networks or Internet servers) that have improved enormously in recent years. The experience of playing together modifies the playing situation to a new quality that has been shown to function as a new possibility for entertainment (Klimmt, 2009; Klimmt & Hartmann, 2008). This experienced entertainment could have motivational and cognitive effects on the player (Klimmt, 2009). In contrast, traditional education media often lacks social use.

Game Frame “…perhaps what differentiates digital games from most other entertainment vehicles is its attribute of experiential play” (Wang & Singhal, 2009, p. 274; cf. chapter 3.1.3 “Definition and Classification of Play”). Players are in a special mode when playing a digital game, Klimmt (2009) calls it the “specific frame of play situations” (p. 252). Individuals who play expect a playful action that should differ from non-playful, consequential kinds of action (Klimmt, 2009) like school or work. Play can function as a bridge between reality and fantasy (Sutton-Smith, 1997, cited in Klimmt, 2009). Although play is a great learning tool for children, it is not positively associated with traditional education media – quite the opposite: play and traditional education are often seen as two poles of the same dimension, meaning that they are mutually exclusive. Digital entertainment-education games resolve this view and combine both: play and education (cf. Ritterfeld & Weber, 2006).

136 3.2.5.4 Possible Advantages of Using Serious Games as Educational Tools The above mentioned characteristics of the serious gaming situation (multimodality, interactivity, narrative context, social (multiplayer) use, and game frame situation) that distinguish serious games from traditional education media might lead to several advantages (e.g. Prensky, 2001). Below, the expected benefits of each of the five characteristics are described. Additionally and first of all, enjoyment – as an assumed result of the five characteristics and source of many expected advantages – is taken into consideration. The fifteen mechanisms mentioned by Klimmt (2009) in his model Potential Effects Mechanisms in Serious Games Effects for Social Change are also included below. For a better understanding of the relations between characteristics and potential advantages resulting from these characteristics, the mechanisms mentioned in Klimmt’s (2009) model are not structured the same way as in his matrix (cf. Klimmt, 2009; see Table 1); instead their classification is based on the very characteristics mentioned above (plus enjoyment).

Advantages of Serious Games Resulting from Enjoyment The most obvious potential mentioned in the literature is enjoyment (e.g. Papastergiou, 2009; Wang, Shen, & Ritterfeld, 2009; Baranowski et al., 2008). As described above (cf. chapter 3.2.3 “Why People Play Digital Games“), players often report that they play games for “fun”, “entertainment”, or “enjoyment”, trying to explain that they experience a however named status that is positive at least for them. Below, the term enjoyment is used as specified by Ritterfeld and Weber (2006): “enjoyment is considered the core experience of entertainment (Vorderer, Klimmt, & Ritterfeld, 2004), defining the sum of positive reactions toward media experiences being cognitive, affective, or conative” (p. 405). It is not yet clearly explained how enjoyment occurs, but studies suggest that multimodality, interactivity, narrative, and social (multiplayer) use facilitate players’ experience of enjoyment (Wang, Shen, & Ritterfeld, 2009). An empirical study by Wong et al. (2007) found evidence that participants enjoyed new media formats – digital games, replays of games, and hypertext – much more than education in terms of text books.

137 Enjoyment is expected to have motivational power22 (Kirriemuir & McFarlane, 2004) by intrinsically motivating players to select a game (Entertainment capacity of serious games increases likelihood of selection change-related message, mechanism 1, cf. Klimmt, 2009). And enjoyment motivates players to become engaged in a digital game (Papastergiou, 2009; Baranowski et al., 2008) so that it is repeatedly played – with, in the case of serious games, positive effects for the behavior change process (cf. mechanism11 Enjoyment promotes involvement and motivation for repeated exposure, Klimmt, 2009). Thus, enjoyment motivates players to voluntarily use an educational tool (Dondlinger, 2007). In promoting enjoyment, digital games are especially motivational for adolescents, who may be difficult to reach via traditional education interventions (Lieberman, 2009). Intrinsically motivated learning has been shown to be the most effective way of education (Hauser, 2006; Schiefele & Schreyer, 1994; Hartinger & Fölling-Albers, 2002; Csikszentmihalyi, 1996), and therefore it can be assumed that enjoyable serious games could be “more effective than traditional learning modes” (Papastergiou, 2009, p. 603). Aside from supporting motivational aspects, enjoyment also generates attention and interest during the digital gaming situation (mechanism 4, cf. Klimmt, 2009). As Klimmt (2009) states, an increase in knowledge can only be expected in case attention is drawn to the learning matter. While attention affects learning processes during playing, enjoyment also facilitates processes of elaboration of learning content in the phase between games (cf. Klimmt, 2009, Mechanism 12 Enjoyment promotes Involvement and Motivation to Elaborate on Game Content between Exposure Situations). And enjoyment promotes communication about the game content, which can also facilitate behavior change (cf. Klimmt, 2009, Mechanism 13 Enjoyment promotes Involvement and Motivation to Talk about Game Content).

22 Ritterfeld & Weber, 2006, p. 405: “However, authors disagree about whether enjoyment and intrinsic motivation are distinct qualities (e.g. Sansone & Smith, 2000) or one and the same (e.g. Linnenbrink & Pintrich, 2000)”.

138 Advantages of Serious Games Resulting from Multimodality Klimmt (2009) states that multimodality increases the chances of knowledge acquisition (mechanism 6, cf. Klimmt, 2009) via observation of behavior and its consequences, e.g. while watching TV or playing digital games (see also below about “narrative context”; Vorderer & Ritterfeld, 2003). Because multimodality and interactivity give the opportunity to execute the new learned behavior in a virtual environment in the post-exposure stage, which is seen as important for behavior change processes, serious games increase the likelihood of knowledge application (cf. mechanism 14, Klimmt, 2009). This assumption is consistent with findings by Ritterfeld, Shen, Wang, Nocera, and Wong (2009): They studied the respective influence of multimodality and interactivity on educational outcomes and found that both play a part, mainly on increase in knowledge.

Advantages of Serious Games Resulting from Interactivity As a consequence of interactivity, digital games can immediately provide feedback to their players (Baranowski et al., 2008; Dondlinger, 2007). As Cameron and Dwyer (2005) found out, a digital game can increase players’ knowledge performance if the players get immediate feedback about the correctness of their reactions. Peng (2009) points out that within the digital gaming situation, players can “directly experiencing the rewards and punishments resulted from their own actions” (p. 5/6), therefore players can have an immediate experience (Klimmt, 2004b) and can draw conclusions from their actions (e.g. Papastergiou, 2009) just as in real life. Thus, digital games can increase players’ feelings of self-relevance, because they do not only witness characters acting and see the consequences of this behavior; they (the avatar respectively) experience the consequences themselves (Vorderer, 2000; cf. mechanism 7, Klimmt, 2009). This can be seen as a source of mastery experience. According to Bandura (2004; cf. chapter 2.3.3.1 “Bandura’s Social Learning Theory”), mastery experience is the most effective way of producing a strong feeling of self-efficacy, which is important for behavior change (e.g. Bandura, 2004). Playing digital games can be seen as a simulated mastery experience (Peng, 2009). In this way, playing digital games could evoke feelings of self-efficacy (Buckley & Anderson, 2006; Lieberman, 2001) that could positively influence behavior change (Bandura, 2004). Thus, interactivity may contribute to making digital gaming an effective intervention tool (Peng, 2009).

139

Advantages of Serious Games Resulting from Narrative Context Narratives are like an adhesion that keeps the different sequences and tasks of a digital game together, and so provide a sense-making framework that can support understanding (cf. mechanism 8, Klimmt, 2009). Storyline and characters can function as dramatic elements that can increase players’ identification with the game character (Peng, 2009; Wang & Singhal, 2009); identification is important for behavior change processes (cf. chapters 2.3.3.1 “Bandura’s Social Learning Theory”; 2.3.4.1 “Elaboration-Likelihood Model of Persuasion (ELM)”; 2.3.8.1 “Sabido Method”). Additionally, stories are used in digital games to increase players’ involvement and to insert behavior change concepts that players can watch (Baranowski et al., 2008). This witnessing while playing provides the opportunity for observing cause-and-effect relationships (Baranowski et al., 2008) and thus for social modeling (Peng, 2009; cf. chapter 2.3.3.1 “Bandura’s Social Learning Theory”). Another positive aspect of narratives is mentioned by Slater and Rouner (2002). They suggest that cognitive processing of narrative persuasion in entertainment-education programs prevents counterarguing, and can cause suspension of disbeliefs (Green & Brock, 2000; cf. mechanism 10 Game Narrative Contributes to Persuasion, Klimmt, 2009). Therefore, it allows for behavior change even when the behavior embedded in the entertainment-education program is inconsistent with individuals’ beliefs and attitudes (Peng, 2009; Wang & Singhal, 2009).

Advantages of Serious Games Resulting from Social (Multiplayer) Use The possibility of multiplayer use in digital games provides the opportunity for direct interpersonal communication “in a more direct, spontaneous, informal, and potentially intimate fashion” (Wang & Singhal, 2009, p. 278). This way of in-game communication facilitates understanding, as the players can directly clarify any misapprehension (cf. mechanism 9, Klimmt, 2009). The sense of community in multiplayer digital games “legitimizes interest in controversial change-related messages” (Klimmt, 2009, p. 275, cf. mechanism 5) that makes players feel more comfortable with being engaged in the learning content.

140 Advantages of Serious Games Resulting from Game Frame As Klimmt (2009) describes, the situation of playing with its “as-if”-mode is very different from “real-life” and its consequences (cf. chapter 2.1.3 “Definition and Classification of Play”). Change-related messages that are inconsistent with a players’ value system could cause resistance to exposure, but the specific frame of play situations decreases such resistance and thus allows for dealing with controversial learning-content (cf. mechanism 2, Klimmt, 2009; Wang & Singhal, 2009). And as players define a gaming situation as play, potential anti-persuasion stances are minimized (cf. mechanism 3, Klimmt 2009).

141

Table 1. Matrix visualization of the potential effect mechanisms underlying playing serious games on social change (Klimmt, 2009, p.255)

Stage Effect Preexposure / Selection of Exposure / Processing of Content Postexposure Category Medium

Motivation to (1) Entertainment capacity of (4) Enjoyment generates attention and (11) Enjoyment promotes involvement with games and elaborate serious games increases interest for game world and content thus facilitates motivation for repeated, prolonged content of likelihood of selection of (5) Social game play renders elaboration of game play (redundancy) desired social change-related message change-related content as socially (12) Enjoyment promotes involvement with games and change (2) As-if quality of game play acceptable (“I am not the only one thus facilitates motivation to think about game weakens refusal to expose doing it”) content (e.g. planning strategies for next session) to change-related content (13) Enjoyment promotes involvement with games and thus facilitates motivation to talk about the game (content) with other individuals (14) Multimodality and interactivity increase likelihood Knowledge (6) Multimodality increases likelihood of of knowledge application to real-world settings, acquisition / knowledge acquisition about the content which substantiates learning processes (“This comprehension of desired behavioral/social change situation is just like in that game”) (7) Interactivity increases likelihood of connection of content to player self (8) Narrative creates sense-making framework that facilitates comprehension (9) Multi-user play facilitates in-game communication that may resolve (3) Activation of inoculation- comprehension problems and support (15) Narrative persuasion theory: misattribution of Attitude change based anti-persuasion- further elaboration of change-related attitude to serious/real-life source and / persuasion stances less likely through content argumentation entertainment-quality of (10) Narrative persuasion theory: serious game (no attempt to Suppression Counterarguing, increased persuade expected) salience of values connected to desired change

Additional Advantages of Serious Games Klimmt (2009) mentions a mechanism that is not based on the five characteristics of the digital gaming situation (multimodality, interactivity, narratives, social (multiplayer) use, or specific game frame situation), but might still affect behavior change: “Attitude Change May Result from Misattribution of Attitude to Real-Life Source” (mechanism 15, Klimmt, 2009, p. 264). Research has shown that individuals often confuse sources of information and in this way fictional information can influence players’ beliefs and thoughts (e.g. Appel, 2005; Schreier, 2002; Schreier & Appel, 2002).

To sum up, it is expected that serious games can be “powerful educational tools” (Wechselberger, 2009, p. 91) because of the aspects mentioned above and because of resulting mechanisms that should positively influence the behavior change process. Based on these expected advantages, there has been a growing interest in serious games as educational tools (Ritterfeld, Cody, & Vorderer, 2009). Whether the expected advantages can be realized with a digital game is crucial. If not, concerns about the possible effectiveness of serious games arise; these are described in the following sub-chapter.

3.2.5.5 Possible Disadvantages of Serious Games There are three very different areas in which serious games could be at a disadvantage. In contrast to the above mentioned anticipated advantages which arise from a comparison of serious games and traditional education, the expected limitations arise either from a comparison of serious games for education and mainstream entertainment games (the budget and design aspect), or from aspects of information processing (cognitive load), or players’ attitudes activated by the label “educational”.

Disadvantages of Serious Games Resulting from Game Design Aspects Although digital games are very entertaining, serious games for education are not necessarily fun (Wechselberger, 2009). The anticipated advantages mentioned in the sub-chapter above can only be realized in case serious games are comparable to digital mainstream entertainment games. Especially the game design should be on the

143 same level: Simplistic, poorly designed games might not be able to reach the expected effects (Mitchell & Savill-Smith, 2004; Kirriemuir & McFarlane, 2004). “Poorly designed” is not limited to the graphics; the gameplay can also be poor, either because of repetitive tasks, or because of a limited range of possible activities while playing (Kirriemuir & McFarlane, 2004). If serious games are supposed to work, they need to be perceived as good as mainstream games by the favored target audience (Prensky 2001).

Disadvantages of Serious Games Resulting from Cognitive Load Other disadvantages are not related to the design. Even a good design and gameplay can hold some problematic issues. It might be that too many stimuli and too much information are included in the game and that for this reason so-called “cognitive load” emerges (Peng, 2009). In short, the cognitive load theory (CLT) assumes that the working memory has only limited processing capacity, meaning that only a defined amount of information can be processed at the same time. If too much information is included in a digital game, not all information will be processed properly. Thus, it is possible that relevant information is missed. A learning process can only be successful if the load of cognitive requirements does not exceed players’ individual existing processing capacities (Hannafin et al., 1996; Sweller, van Merrienboer, & Paas, 1998). There is a relation between cognitive capacity, interactivity, and entertainment: Vorderer, Knobloch, and Schramm (2001) conducted a study about movies with and without interactive elements. They showed that persons with less cognitive capacity feel more entertained without interactive elements while watching a movie, whereas persons with more cognitive capacity feel more entertained when they have the opportunity to use interactive elements that enable them to influence the movies’ storyline. Thus, it can be suggested that serious games should meet target groups’ cognitive capacity to be successful; otherwise games could be too difficult or too easy (Mitchell & Savill-Smith, 2004). And because of the risk that not all information might be processed, the content should not be too broad; it is better to choose a specific topic for a specific target group (Lampert, Schwinge, & Tolks, 2009).

144 Disadvantages of Serious Games Resulting from the Marketing Strategy Interestingly, the marketing strategy can inherently influence the success of serious games. The marking strategy often caters to parents or teachers, and it points out the educational usefulness and lists recommendations from educational professionals to promote serious games (Mitchell and Savill-Smith, 2004). But simply calling a game serious can decrease its attractiveness to players (Shen, Wang, & Ritterfeld, 2009) because the potential users realize that they are supposed to learn something from the game, and therefore automatically dislike and avoid it (Kirriemuir & McFarlane, 2004; Mitchell & Savill-Smith, 2004). Therefore, the marketing strategy should avoid such effects by aiming at the target audience and presenting the game as entertainment.

To sum up, the usage of digital games as education tool does not automatically lead to advantages compared to using traditional media. Several aspects have to be taken into account when designing a digital game for educational purposes (e.g., the quality of design or the optimal level of cognitive load) or when promoting it.

3.2.6 Digital Entertainment-Education Games While Ritterfeld, Cody, and Vorderer (2009) state that “serious games are a sort of entertainment-education media” (p. 4), Wang and Singhal (2009) see it the opposite way. They emphasize that not every serious game is automatically an entertainment- education game; they even state that most of the serious games do not meet their criteria for entertainment-education, but that digital entertainment-education games are serious games as well. Sostmann, Tolks, Fischer, and Buron (2010) point out that serious games and digital entertainment-education games have much in common, and that it is therefore very difficult to distinguish between them. In conclusion, they follow Ritterfeld, Cody, and Vorderer (2009) and agree to define serious games as a sub-category of entertainment-education, but this does not clarify the relation between serious games and digital entertainment-education games. This relation is more visible when looking at Wang and Singhal’s (2009) redefinition of the entertainment-education strategy which includes digital games: Entertainment-education is a theory-based communication strategy for purposefully embedding educational and social issues in the creation, production, processing, and dissemination process of an entertainment program,

145 in order to achieve desired individual, community, institutional, and societal changes among the intended media user populations (p. 272/273). In contrast to serious game definitions (cf. chapter 3.2.5.1 about introduction, definitions, and classification of serious games), entertainment-education interventions in the form of digital games also include the whole process from creation to release. Wang and Singhal (2009) point out that it is important to involve target audience members in the creation process from design to development to make sure that the game is appealing to the intended audience. And digital entertainment- games should have a useful purpose aiming at being beneficial for their players (cf. Singhal & Rogers, 1999, 2002, 2003, 2004). Hence, the criteria for digital entertainment-education games following Wang and Singhal (2009) are more stringent compared to those of the various other serious games definitions. Theoretically, digital games show great promise for entertainment-education interventions, especially as tool for teaching health (Peng, 2009) or sensitive content, such as sex education (Wang & Singhal, 2009). There is not much empirical literature showing how well serious games work (Graesser, Chipman, Leeming & Biedenbach, 2009), but for several serious games empirical studies exist that evaluate their impact (Papastergiou, 2009) and that provide empirical evidence for their effectiveness in the areas of learning and health (Lieberman, 2009; Mitchell & Savill-Smith, 2004). But not many explicit digital entertainment-education games that would meet Wang and Singhal’s (2009) criteria (see above) were developed and evaluated in practice (Lampert, Schwinge, & Tolks, 2009). And those games that do satisfy these criteria are not necessarily considered digital entertainment-education games. In the following, some digital entertainment-education games that were evaluated are exemplified, starting with one of the most frequently mentioned games in this research area: Re-Mission. Re-Mission is a digital game for a rather specific target group – children and adolescents suffering from cancer. Psychologists, oncologists, and video game design professionals were involved in the production process; it was developed with a budget of 4.5 million US dollars by Realtime Associates on behalf of a non-profit organization called HopeLab (Beale, Kato, Marin-Bowling, Guthrie, & Cole, 2007). Re-Mission aims at involving players in their own treatment by informing them about cancer and cancer therapies. The player navigates an avatar through bodies of adolescents who are suffering from different cancers. The aim is to destroy cancer

146 cells and other enemies by using weapons like antibiotics, radiation, and chemotherapy. The avatar is in the company of a little robot called Roxxi, who gives information about cancer and its treatments. To fulfill missions, the player has to convince the virtual patients to be compliant with self-care behaviors. Such positive behaviors are, for example, practicing good mouth care to combat mucositis (an oral infection of the mouth lining), or using relaxation techniques to reduce stress. The game was evaluated with knowledge tests. In the main study, adherence, self-efficacy, knowledge, control, stress, and quality of life were measured as self-reported data with various scales. Additionally for those patients who took special medication (e.g. antibiotics or 6-mercaptopurine), compliance with them was measured by electronic pill-monitoring equipment (antibiotics) or through blood tests (6-mercaptopurine, Kato et al., 2008). The test scores indicate that Re-Mission increases adherence of antibiotics and or 6-mercaptopurine as well as patients’ self-efficacy and knowledge about cancer (Kato et al., 2008). Beale at al. (2007) describe two different possibilities for the increase in knowledge: either the information provided in Re-Mission caused the increase in knowledge itself, or Re-Mission aroused players’ interest in the topic so that they looked for more information on the Internet, in books, by talking to physicians, etc. The authors conclude that digital games can be effectively used for educating young people with chronic illness. Another digital entertainment-education game that was evaluated is the Heart Sense Game (Silverman, B. G., Holmes, W., Green, M., Holmes, J., Kimmel, S., Mosley, J., et al., 2003; Silverman, Holmes, Kimmel, Branas & Ivins, 2000). It was created at the University of Pennsylvania and is about heart attack and the need for seeking care immediately. The game starts with an introduction in which heart attack symptoms and the heart attack itself are explained. Afterwards, players enter a fictitious village where they meet characters with heart attack symptoms and have to convince them not to lose time and to promptly seek medical care. The aim is to sensitize players to heart attack symptoms and the need for quick medical help. Evaluations of the game have shown that people who played the game are more likely to call 911 (the American emergency number), and to avoid a delay in seeking medical care compared with those people who did not play the Heart Sense Game (Silverman et al., 2003; Silverman et al., 2000).

147 VR-ENGAGE is an educational digital game that was created for transferring knowledge taught at schools. It demonstrates the potential of digital entertainment- education games compared to conventional education software, because students with previously poor performances benefited the most from the game. The game VR- ENGAGE was developed by Virvou, Katsionis, and Manos (2005) to teach geography. It looks like the popular digital game Doom, but unlike Doom, it is completely non-violent. The player has to navigate an avatar through different environments with castles, dragons, dungeons etc., and the aim is to find missing pages of the book of wisdom. The player can reach this goal by successfully passing the virtual world and reaching a high score. Points can be collected by answering questions correctly. For example, guard dragons ask questions about geography; in case the player gives the right answer the dragon clears the way for the player's avatar. Evaluation of the players’ learning outcomes shows that VR-ENGAGE worked better than conventional educational software and, as stated above, especially students with formerly poor performance benefited from the game (Virvou, Katsionis, & Manos, 2005). The digital entertainment-education games described above show that such games can be effective on cognitive level, e.g. Re-Mission increased patients’ knowledge about their cancer and their treatments, the Heart Sense Game increased players’ knowledge about how to react properly in case of heart attack, and VR- ENGAGE increased players’ knowledge in geography. The games have also been effective on affective level, e.g. Re-Mission increased patients' self-efficacy concerning their therapy, and on the conative level as players of the Heart Sense Game are more likely to act in case of heart attack, e.g. by calling 911. Nevertheless, the purpose of education is obvious in case of all three games described above: it is clear from their titles and game action that Re-Mission aims at educating about cancer, that the Heart Sense Game aims at educating about appropriate behavior in case of a heart attack, and that VR-ENGAGE should teach about geography. But the aim of entertainment-education interventions should not be too obvious (Piotrow & Fossard, 2004); an entertainment-education game that does not reveal its educational purpose at first sight does not exist yet.

148 3.2.7 Digital Games for HIV/AIDS Prevention Concerning HIV/AIDS prevention – the health topic of this thesis – no digital entertainment-education game could be found, although various educational games for HIV/AIDS prevention exist. Not empirically tested, but very popular is the game Catch the sperm. It was created for the Swiss Federal Office of Public Health and released in 2001. The game is entertaining and aims at bringing back the risk of HIV/AIDS into the player’s mind. Playing Catch the sperm is quite simple: inside a vagina, the player has to catch sperms and viruses with condoms that are shot with a “condom cannon“. The aim is to catch as many sperm, viruses, and bacteria as possible in 90 seconds. Several editions exist, for example a carnival version in which the sperm wear cardboard noses and fancy dresses. The game is a worldwide success: In the first year, 18 million people from 104 countries downloaded it. Thus, it can be concluded that it is a very entertaining game (Condomunity, 2009). Unfortunately, it is not possible find any studies about Catch the sperm. Therefore, it cannot be determined whether the game actually has the intended effects on the players. The same applies to another HIV/AIDS education game, called The Aids Avenger (subtitled “Fight Fear and Ignorance in the HIV Prevention Game”; Der Spiegel, 1993, p. 262). It was created at Stanford University and released in the early 1990s and contains a mixture of robots and policemen fighting against the enemies of HIV/AIDS prevention by trying to prevent new infections and coming to the defense of HIV-infected persons. Super Shagland is another game for HIV/AIDS prevention that has not been evaluated, but is very popular. It was produced and released in the Netherlands with the aim to support responsible sexual behavior, e.g. by showing the importance of condom use (Wang & Singhal, 2009). Some HIV/AIDS prevention games that focus more on the prevention aspect than on entertaining the player have been evaluated. For example, Life Challenge is a digital adventure game produced by the New York State Department of Health to teach adolescents HIV/AIDS prevention skills and increase their self-efficacy concerning this topic. Empirical evidence for its effectiveness was found as increases on knowledge and self-efficacy were reported (Thomas, Chahill, & Santilli, 1997). Another computer-based education intervention about HIV/AIDS prevention was created by Roberto et al. (2007) in the course of the Reducing the risk curriculum in the U.S. This is a “skills-based 16-lesson curriculum founded on social learning

149 and social influence theories” (Roberto et al., 2007, p. 13). It aims at changing rural adolescents’ perceived threat, their perceived efficacy, attitudes, and knowledge about pregnancy, sexually transmitted diseases, and HIV prevention. The intervention consisted of various activities such as rating risky behavior, identifying truth or myth in statements, and a “best delaying tactics” contest. Results show that students in the treatment group, compared to those in the control group, reached higher scores on knowledge, condom self-efficacy, attitude toward waiting to have sex, and perceived susceptibility to HIV (Roberto et al., 2007). Interactive Nights Out was produced by the World Institute of Leadership and Learning (WILL) Foundation. It is an interactive movie game. Thus, the user is a viewer rather than a player, but with opportunities to make decisions that influence the storyline. Michael and Chen (2005) note that empirical evidence for the games’ effectiveness was found. To summarize, entertaining as well as educational digital games for HIV/AIDS prevention were produced and released: As Catch the sperm has illustrated, a digital game about HIV/AIDS can be very funny and engaging, whereas Reducing the risk successfully functioned as educational tool. But so far, no digital HIV/AIDS prevention game has been empirically shown to be entertaining and HIV/AIDS-educational at the same time. The current study aims at closing this gap by creating a digital entertainment-education game about HIV/AIDS prevention.

3.2.8 Digital Games and Girls 3.2.8.1 Girls’ Use of Digital Games Studies suggest that general interest in digital games is equal for boys and girls in their early years (see Agosto, 2004), with girls’ interest decreasing as they grow older. The exact age at which girls and boys begin to differ significantly is subject to debate: some studies indicate during kindergarten, others with the onset of puberty (cf. Agosto, 2004). One reason for girls' decrease in interest could be that children of both sexes consider both computers and digital games “to be boys’ toys” (Cassell & Jenkins, 1998, p. 14). This might establish a self-fulfilling prophecy: boys expect themselves to be successful players, they “work” harder to reach success, whereas girls expect themselves to lose and stop playing earlier instead of trying to reach success. Girls therefore choose to play less and boys to play more, causing a noticeable effect on their respective motivations and experiences (Klimmt, 2004b).

150 Although computers can be used for various purposes, numerous studies have found that both boys and girls use them most frequently for gaming (Feierabend & Klingler, 2003). Others have concluded that boys generally play digital games, while girls more often make use of word processing and data management programs such as the Microsoft Office suite (Schwab & Stegmann, 2000). Schwab and Stegmann (2000) conclude that girls do not have deficits in computer use, but rather that they interact with computers in a different way. This is in line with Agosto (2004), who states that boys and girls are generally equally skilled at using computers, but that girls use them less often for playing games compared to boys. Fromme (2000) found empirical evidence for different digital game usage among girls and boys. Adolescents were asked about 60 characteristics of digital games, the aim being to identify different types of players. Cluster analysis demonstrated that the biggest differences between types of players occur between two predetermined clusters: in this case girls and boys are the most distinguishable types of computer players. This is consistent with findings by Schindler (1996), who also reports that no other characteristic (for example, age, nationality, type of school, socioeconomic status) led to as strong differences in digital game preferences as gender. These results support Hartmann and Klimmt (2006), who suggest that “it seems plausible that gender-specific entertainment preferences exist” (p. 911). This being said, the number of girls playing digital games has increased in recent years (Oppl, 2006; Agosto, 2004); boys still spend more time playing digital games than girls do, but according to Feierabend and Klingler (2003), in 2000, 58% of German girls reported playing digital games at least once a week. Two years later, the amount of girls reporting having played digital games at least once a week increased to 65% (Feierabend & Klingler, 2003). Other studies indicate that an increase in computer gaming by girls is also occurring in the U.S. and the U.K. (see Hartmann & Klimmt, 2006). An explanation for these increases could be that the digital game industry has discovered the potential market of female consumers interested in gaming and has begun to produce more digital games tailored in particular to girls (Deutsche Presse-Agentur, 2009). The following subsections will take a closer look at why digital games designed for boys might be inappropriate for attracting girls and at what characteristics a digital game should have in order to make it appealing to girls.

151 3.2.8.2 Girls and Common Digital Games Girls and boys not only differ according to the amount of time they spend playing digital games, but also according to the kind of games they like to play (Wink & Lindner, 2002). The digital game industry is male dominated. Men tend to create games for men and usually neglect girl’s preferences (Wink & Lindner, 2002). In recent years, however, the digital game industry has sought out new target groups and has begun designing digital games for female consumers (Deutsche Presse-Agentur, 2009; see above); that being said, most games continue to be produced by men, as has been the case for decades. What does a typical digital game look like? Dietz (1998) discovered that 79% of the content in digital games is composed of physically aggressive activities such as shooting, fighting and beating. In addition, Agosto (2004) found empirical evidence that most digital games have strongly competitive elements; 78.7% of internet-based games analyzed were competitive in nature, and most included a contest between good and evil (it should be noted that this does not automatically imply that the player plays for the “good” side; in games such as Grand Theft Auto, the main character is a delinquent conducting criminal activities, and in Counter-Strike, the player can choose to play as a terrorist or counter-terrorist). In sum, typical digital games designed for male players are competitive, violent, and mostly include male characters. Grodal (2000) argues that digital games’ core elements usually match masculine hunting tendencies, and that these same core elements are particularly disliked by female players. Hartmann and Klimmt (2006) have provided empirical evidence for this assumption. They conducted two studies and analyzed single-player digital games in order to find out what aspects girls dislike. In the first study, female participants (N = 317) rated fictional digital games. A conjoint analysis identified the main reasons why girls dislike the content of many digital games: a lack of meaningful social interaction, too much violent content, and sexual gender role stereotyping of figures shown in the games. In a second study, Hartmann and Klimmt (2006) conducted an online survey with 795 participants; one result was that females do not like the competitive elements ubiquitous in most digital games. These four factors identified by Hartmann and Klimmt (2006) are consistent with findings by other researchers.

152 The lack of social interaction identified above has also been addressed by Schlüter (2000), who identified that girls prefer to play with each other rather than against each other. Yee (2002) also states that female players enjoy digital games with elements of social interactivity (see also Agosto, 2004). Girls dislike violence in digital games (Laudowicz, 1998; Kafai, 1996) even if it is framed as a fight between good and evil (Agosto, 2004). Violence is also a rather male characteristic and is not compatible with typical female gender roles like passivity, nurturance and dependency (Ragins & Scandura, 1995). Digital games with violent content, like shooter or war games, do not match female gender roles (Klimmt, 2004b) and are thus played less often by females. Stereotypical gender-role portrayals can be commonly found in digital games (Klimmt, 2004b; Norris, 2004; Wink & Lindner, 2002; Dietz, 1998). Many studies found evidence that stereotypical sexual gender roles in digital games alienate female players. These stereotypes can be observed in different aspects of games. Female characters are generally underrepresented in digital games (Smith, S.L., 2006; Kafai, 1996); the research organization Children Now, for example, states that only 16% of game characters are female (Children Now, 2001). Even when characters in digital games are female, they usually do not play an important (i.e. active) role in the game; they are inactive bystanders (Agosto, 2004; Kafai, 1996) or help the male hero (Dietz, 1998; Children Now, 2001). This is in line with findings by Dittler (1995a,b), who also identified a lack of female heroes in digital games. Females in digital games are not only underrepresented in general and overrepresented in unimportant roles, they are also portrayed in negative ways, for example as sex objects or extremely unattractive characters (Dietz, 1998). They are shown either as helpless victims (Dietz, 1998; Lerchenmüller Hilse & Hilse, 1998) as princesses in distress (Schindler, 1996), as prizes (Provenzo, 1991), or as ultra-sexual decorations (Dietz, 1998). In the latter case, the figures often have unrealistic body images (Smith, 2006), being shown with large breasts and undersized waists (Dietz, 1998). According to Reinhard (2006), the gaming industry argues that male players want hyper-sexualized female figures in digital games, this despite the result of her study that men prefer realistic curvy women to hyper-sexual figures. A well known digital game character with such hyper-sexualized characteristics as large breasts and an undersized waist can be found in Lara Croft from Tomb Raider, a blockbuster

153 game (Oppl, 2006; Subrahmanyam & Greenfield, 1998). Although Lara Croft is a woman, the digital game is not designed to attract female players.23 Competition is generally perceived as a male rather than a female characteristic (Klimmt, 2004b; Laudowicz, 1998); potential players identifying more with female gender roles (usually girls) do not want to adapt to male gender characteristics like competition and are not accustomed to them. For this reason, girls feel less able to manage competitive situations and do not seek out competition (Laudowicz, 1998). This sub-section shows that most of the typical digital entertainment games, like Grand Theft Auto or Counterstrike do not match female expectations and requirements of digital game playing. Girls and women have been neglected by the digital game industry for a long time although they would like to play digital games – but only if they meet their preferences.

3.2.8.3 Girls’ Favorite Games and Genres Recent studies have shown that girls are interested in playing digital games, but they prefer different games than boys (Agosto, 2004). Although the studies presented above have focused on identifying those aspects of most digital games that girls dislike, research has also identified potential digital game characteristics that have the potential to appeal to female players. These factors go beyond a simple lack (or opposite) of the four discouraging, male characteristics presented above. One of the first successful digital games for girls was released in November 1996: Barbie Fashion Designer. It was the first digital game created for girls and thus has the potential to effectively tap into the female mass market for electronic entertainment products such as digital games (Subrahmanyam & Greenfield, 1998). According to Klimmt (2004b), its success can be seen as evidence for the deterrent effects of common digital games designed for male players. The success of the Barbie Fashion Designer was due to its different content. Subrahmanyam and Greenfield (1998) found that girls like the game because of its non-violent activities, and because it gives the opportunity to role-play in a real-world situation, and thus gives girls the possibility to use one of their common play patterns in a virtual game (Agosto, 2004).

23 Originally the main character was to be male. According to “MTV Special: Computer and Videogames” (2007), the producer changed the male into a female character to avoid legal problems since a male character would have been too similar to Indiana Jones.

154 This might also be an explanation for why girls like to play The Sims, as The Sims allows the player to configure the everyday life of virtual characters (Oppl, 2006) and thus meets girls’ preference for games with storylines and character development (Agosto, 2004). Another explanation for its success could be that it matches girls’ gender roles. Girls tend to enjoy activities with social content such as helping, nursing, and communicating with friends – in real life and in digital games (Laudowicz, 1998). Girls enjoy games involving social interaction; teamwork is much more important for them than competition. Schlüter (2000) writes that girls prefer to play with each other rather than against each other. Girls also enjoy discovering hidden places and objects, but in a different way than boys. They tend to see these types of challenges as “a mystery to be solved, rather than a land to be conquered” (Lucas & Sherry, 2004, p. 519). As stated above, girls reject explicit or gratuitous violence and prefer games in which enemies are not killed (Vollmer, 2000; Laudowicz, 1998). Games should be stress free and relatively peaceful (Fritz & Fehr, 1997; Böck & Weish, 1997, Schlüter, 2000). In games involving eliminating enemies, girls prefer to incapacitate other characters with unusual methods like pinching enemies with a beak rather than using lethal force (Fritz & Fehr, 1997; Schlüter, 2000). This is usually the case in funny, comic-style games such as Super Mario Brothers (Schlüter, 2000; Fritz & Fehr, 1997). This game satisfies girls’ preference for funny, comic-style adventure games (Wink & Lindner, 2002; Schlüter, 2000; Vollmer, 2000; Böck & Weish, 1997). Super Mario Brothers is a so-called jump-and-run or platform game. According to Fritz and Fehr (1997), girls enjoy elements such as jumping, running, collecting things, swimming, diving, unraveling mysteries, and exploring undiscovered landscapes. These elements are usually part of funny jump-and-run games (Schlüter, 2000). This is in line with Fromme (2000), who discovered that 48% of the girls name jump-and-run or platform games as their favorite game genre, followed by mental skill and puzzle games, with 20% of girls preferring this genre (see also Reinhard & Derwin, 2007). The fact that girls enjoy being challenged mentally during play was confirmed in a study by Feierabend and Klingler (2003): unlike boys, girls enjoy playing digital games with educational content. Beyond content and game structure, performance requirements also influence the extent to which players enjoy various games. As described above, girls see computers as boys’ toys (Cassell & Jenkins, 1998) and are therefore more likely to

155 stop playing in case of a defeat. Girls therefore prefer digital games in which they can reach success rather quickly (Laudowicz, 1998), and where game patterns and designs are relatively familiar (Laudowicz, 1998; Fritz & Fehr, 1997).

3.2.8.4 Conclusion Girls do play digital games, but they prefer different games than boys (Subrahmanyam & Greenfield, 1998). These differences can be found in relation to different aspects of digital games such as content, design and image presentation of characters, and game patterns. Concerning content, girls prefer funny, non-violent and non-competitive digital games, where they can participate in social activities in a stress-free and peaceful environment, and discover landscapes and objects. In addition, they enjoy educational topics and mental challenges that are often included in some digital games. As for design and image presentation of characters, girls prefer comic-style games and female characters that are presented in an appropriate – i.e. non-sexual – way, so that girls can identify with them. Moreover, the female characters shown in a digital game for girls should be active main characters so that they enable girls to play the leading part in the game. Girls enjoy game patterns they are familiar with, like role playing or jump- and-run and platform games. They also enjoy the opportunity to interact and communicate with others while playing. Most of these characteristics are in contrast to the digital games that males typically prefer. Hartmann and Klimmt (2006) conclude that: current explanations of why playing video games is fun (e.g., Klimmt, 2003; Vorderer & Bryant, 2006) need extensions to account for gender-specific models of pleasure. If competing, winning, and being a violent superhero does not appeal to women to the extent that they appeal to men, several mechanisms of enjoyment that have been proposed, such as pride in success and identification with attractive role models (e.g., Klimmt, 2003), should be reconsidered (p. 926). In line with this view, it can be concluded that because of the different likes and dislikes of girls and boys concerning digital games, serious games as well as digital

156 entertainment-education games need be to conceptualized in a gender specific way to be successful.

3.3 Summary Play is older than humanity itself (Ohler & Nieding, 2006), and can be seen as a human need (Scheuerl, 1986). Huizinga (1950, 1994) even described man as homo ludens (“the playing human”) who develops his/her individual skills through play activities (Matthies, 2006; Flitner, 2002). Academics already tried to explain man’s play behavior in the ancient world and during the Enlightenment. For this thesis, different approaches of contemporary play theories have to be taken into account: 1. Piaget's (1969) cognitive-developmental theory. Here, play serves to activate the process of cognitive development and thus is closely connected to players’ developmental stages. 2. Heckhausen’s (1973, 1978) action-theoretical approach to the psychology of play, assuming play is a) being purposeless, b) an active way to deal with the world, c) with an undifferentiated target structure, d) no real-life situation, and e) characterized by an activation circle of repetitive change between suspense and relief. 3. Ohler and Nieding's (2006) behavior-diversification proto-cognition theory of play (BD-PC theory) investigating play in an evolutionary context, meaning that the ability to play was an evolutionary advantage for a species, in that it increased its fitness. The above mentioned three theories of play focus on the aspect why people play; the next one focuses on the nature of play: 4. Scheuerl’s (1986) phenomenological approach. He identifies six “moments” of play: a) moment of freedom, b) moment of inner infinity, c) moment of pseudo- reality, d) moment of ambivalence, e) moment of closeness, and f) moment of presence. Several definitions of the term “play” have been offered, but none has emerged as an unambiguous and widely accepted formalization (Pellegrini et al., 2007; Ohler & Nieding, 2006; Matthies, 2006; Klippel, 1980), thus various definitions of “play“ exist. Matthies (2006) identifies two characteristics of play that are included (but only implicitly) in most contemporary definitions of play: pleasure and voluntariness.

157 It is not possible to establish a clear definition of play, and the same applies for its classification (Klippel, 1980). Mogel (2008) categorizes play according to its functions for the player, whereas in contrast, most classifications of play are developed according to the structure of the play activity (cf. Piaget (1969); Scheuerl (1986); Schmidtchen, 1994). Games are usually referred to as play with rules (Pellegrini et al, 2007; Schmidtchen, 1994). Just as no unambiguous definition for play exists (see above), no unambiguous definition for games exists yet, either. In general, games are one subtype of play, and it can be concluded that the two main characteristics of play identified by Matthies (2006) – pleasure and voluntariness – also apply to games. It is commonplace that games are play with rules (Flitner, 2002). Although play activity always follows specific rules, within games the rules are predominant compared to all other elements of play (Klippel, 1980). Because following rules is necessary while playing a game, it is logical that games by nature are more competitive than play in general (Klippel, 1980). Whereas games in general are not limited in any way concerning their ways of implementation, digital games are: they require electronic equipment to be played (Gimmler, 2007). The history of digital games starts in the 1970s when a home version of Pong was released, and emerges closely connected to the development of technical possibilities. Digital games can be defined as software products or as electronic toys. But beyond this game-playing research perspective, digital games can be seen as a new type of medium. According to Klimmt (2001, 2003), digital games join both categories – play and medium – and are therefore a new, unique category. Compared to traditional media, digital games are characterized by their interactive elements. In line with this, Gimmler (2007) defines a digital game as an interactive medium for individuals that is based on computer technologies, and Reinhard and Dervin (2007) define digital games “as any form of interactive gameplay that requires some level of computer technology in order to operate” (p. 24). Today, digital games can be played with various kinds of computer technology, namely PC, consoles, handhelds, cell phones, and PDAs (Gimmler, 2007). Digital games can be classified according to their hardware as listed above. Other possible classifications are based on skills that are needed in order to

158 successfully play (Clanton, 2000), virtual activities undertaken in digital games (Fritz, 1997; Smith, 2006; Sellers, 2006; Vollmer, 2000), or characteristics that are important for players’ experience during the game (Klimmt, 2004b). All classification systems are only temporary as digital games develop faster than the research on them. Digital games are played by millions of users who experience positive feelings in the broadest sense while playing (Klimmt, 2003). The question is what exactly that positive experience is, and where it originates. Different approaches can be used for answering these questions. Some try to explain the success of digital games with the flow concept (Csikszentmihalyi, 1990, 1992), others create lists of reasons for playing digital games, either based on literature (Schell, 1989) or on empirical data (Sherry et al., 2006; Raney, Smith, & Baker, 2006). Klimmt (2004b) developed a three-level hierarchical model to explain the enjoyment of digital games, identifying effectance, cycles of suspense and relief, and the possibility to escape from real life as key elements of the enjoyment of digital games (Klimmt, 2003, 2004b). Another model is provided by Fritz (1997), who explains the continuation of digital playing not only with a spiral of flow, but also with a spiral of frustration. Within a spiral of frustration, playing is no longer enjoyable and has potentially negative consequences (Wink & Lindner, 2002). For the present study, a digital entertainment-education game will be created that is supposed to avoid a spiral of frustration; it is supposed to be played because of its entertainment value, leading to a spiral of flow. Negative outcomes are often debated in the course of the violence discussion; results of single studies are inconsistent and no clear statement about the relation of playing violent digital games and violence can be made, except for aggressive thoughts (e.g. Bushman, 1998). Meta-analyses found small, but significant effects of playing violent digital games on aggression (Anderson, 2004; Anderson & Bushman, 2004; Sherry, 2001), but these results have also been criticized for methodological reasons (e.g. Ladas, 2003). Nonviolent digital entertainment can also cause negative effects, for example physical problems in case of spending too much time with playing (such as headaches, irritated eyes, and muscle hardening; Lerchenmüller-Hilse & Hilse, 1998) or becoming dependent on digital games (Griffiths & Hunt, 1998, cited in Lee & Peng, 2006). Aside from negative effects, digital games can also induce positive effects. In particular, cognitive skills can be improved, for instance spatial skills (e.g. Lisi &

159 Wolford, 2002, hand-eye coordination (e.g. Neuß, 2006), iconic skills (Greenfield, Camaioni et al., 1996), and academic performance (Lerchenmüller-Hilse & Hilse, 1998). Concerning emotional effects, better coping strategies with stress and time pressure were found (e.g. Kraam, 2004). Positive social effects are also reported (Lee and Peng, 2006). Durkin and Barber (2002) even suggest that digital games are important for a healthy adolescence. The above mentioned positive effects were not intended, but occurred nevertheless. It is therefore assumed that digital games have great potential as a learning tool. This research area is rapidly growing, and many different disciplines are involved. This could be reasons for the existence of inconsistent terms and definitions. Various terms for using digital games for educational purposes are used, and it seems that “serious games” is becoming the established term. But no consistent definition has emerged yet (Ratan & Ritterfeld, 2009). Some scholars define every digital game as potentially serious (Konijn & Nije Bijvank, 2009), others point out that games are serious only if they have a priori defined learning goals (Bente & Breuer, 2009; Ritterfeld, Cody, & Vorderer, 2009) and are beneficial for the players (Ritterfeld, 2009). There are also various ways of classification: serious games can be classified according to the included content (Lampert, Schwinge, & Tolks, 2009), type of learning (Buckingham & Scanlon, 2003; Gee, 2009), or according to their level of entertainment versus education (e.g. Seufert, 2003). Ratan and Ritterfeld (2009) constructed a classification system with four dimensions (primary educational content, primary learning principle, age of target group, and platform that is used). But the latter distinction is subject to debate: Ritterfeld and Weber (2006) conceptualized entertainment and education on two different dimensions. In doing so, serious games do not have to be either educational or entertaining, they can be both at the same time. This is in line with the concept of the entertainment-education strategy that is used for the current study. Consensus exists about the specific characteristics that distinguish serious games from traditional education media. The most obvious one is interactivity: because the player acts, content evolves (Vorderer et al., 2006). There is an exchange of input and output, and in contrast to linear media, the user has to act, otherwise the game is over. Due to visual, auditive, and sometimes even haptic elements, digital games are multimodal. Also important are the narrative context, the possibility of

160 social multiplayer use and the specific frame of the play situation characterized by an “as-if”-mode. Expected advantages of these characteristics are described below: 1. Anticipated advantages resulting from enjoyment are motivational power (Kirriemuir & McFarlane, 2004), voluntary use of a serious game (e.g. Baranowski et al., 2008), increased attention and interest during play and afterwards (Klimmt, 2009), and thus facilitation of intended educational effects (Papastergiou, 2009). 2. Anticipated advantages resulting from multimodality are increased knowledge acquisition and application (Klimmt, 2009). 3. Anticipated advantages resulting from interactivity stem from the immediate feedback a game can provide its players with (e.g. Dondlinger, 2007), thus leading them to direct experiences (Klimmt, 2004b) and drawing of conclusions from their actions (e.g. Papastergiou, 2009). The latter can be a source of mastery experience (Bandura, 2004) and thus self-efficacy (Buckley & Anderson, 2006; Lieberman, 2001). 4. Anticipated advantages resulting from narrative context stem from the sense-making framework narratives provide (Klimmt, 2009), identification processes (Peng, 2009; Wang & Singhal, 2009) as well as involvement while playing (Baranowski et al., 2008), social modeling (Peng, 2009) and therefore prevention of counterarguing (Slater & Rouner, 2002), and suspension of disbelief (Green & Brock, 2000). 5. Anticipated advantages resulting from social (multiplayer) use are direct interpersonal communication which can facilitate understanding. The sense of community can also legitimize personal interest in controversial issues (Klimmt, 2009). 6. Anticipated advantages resulting from the specific frame of the play situation are decrease of resistance mode (Klimmt, 2009; Wang & Singhal, 2009) and minimization of potential anti-persuasion stances (Klimmt, 2009). 7. An additional anticipated advantage is the so called misattribution of an attitude to a real-life source, meaning that people tend to confuse sources of information. They often do not remember the source of information correctly and thus transfer information from fictional media products into their real life knowledge and belief system (Schreier & Appel, 2002). However, serious games may also have disadvantages as an educational medium: If the game design is poor, the expected advantages cannot occur (Kirriemuir & McFarlane, 2004). Cognitive load is another

161 potential disadvantage if a game does not meet players’ cognitive capacity (Mitchell & Savill-Smith, 2004), as is wrong marketing strategy which can make target audiences dislike and avoid a serious game (e.g. Shen, Wang, & Ritterfeld, 2009). These advantages and disadvantages would also apply to digital entertainment- education games. Again, definition proves controversial, but Wang and Singhal (2009) provide a redefinition of the entertainment-education strategy in order to include digital games which will be used in this thesis: Entertainment-education is a theory-based communication strategy for purposefully embedding educational and social issues in the creation, production, processing, and dissemination process of an entertainment program, in order to achieve desired individual, community, institutional, and societal changes among the intended media user populations (p. 272/273). Not many digital entertainment-education games have been created and empirically tested (Lampert, Schwinge, & Tolks, 2009). A few prominent exceptions – Re- Mission, the Heart Sense Game, and VR-ENGAGE – have shown that digital entertainment-education games can be effective on cognitive, affective, and conative levels. Re-Mission increased patients’ adherence, knowledge, and self-efficacy (Kato et al., 2008), the Heart Sense Game also increased knowledge and realization of supporting measures such as avoiding delay and calling 911 in case of indicators of heart attack (Silverman et al., 2003; Silverman et al., 2000), and VR-ENGAGE increased players’ learning outcomes in the field of geography (Virvou, Katsionis, & Manos, 2005). Concerning HIV/AIDS prevention, no digital entertainment-education games exist that meet Wang and Singhal’s (2009) requirements. Concerning digital games and girls it can be noticed that the number of girls who play digital games has increased in recent years (Oppl, 2006; Agosto, 2004), as the game industry started to produced games for girls (Deutsche Presse-Agentur, 2009). For a long time, game development was male dominated and thus games followed boys’ and men’s likes and largely ignored females as potential gamers (Wink & Lindner, 2002). In doing so, games contained aggressive content and activities (Dietz, 1998), strongly competitive elements (Agosto, 2004), and mostly male avatars (Grodal, 2000). Girls dislike such games. Hartmann and Klimmt (2006) found empirical evidence for this assumption: Girls dislike the lack of social interaction, violence, and stereotypical gender-role portrayals. Girls prefer digital games with non-violent

162 activities that meet their interests (Subrahmanyam & Greenfield, 1998), like games with storylines and character development (Agosto, 2004), social content (Laudowicz, 1998), funny elements (Schlüter, 2000; Fritz & Fehr, 1997), and jump-and-run design (Fromme, 2000), probably because this is familiar to them (Laudowicz, 1998; Fritz & Fehr, 1997). To sum up, girls do play, and more and more digital games for girls are being produced, but there is still a discrepancy in the amount of games offered for boys’ and girls’ preferences. The distinctions in the ways how males and females report enjoying playing digital games lead to the assumption that entertainment and enjoyment are different for girls and boys. Therefore, Hartmann and Klimmt (2006) suggest that models of pleasure should be extended to include gender-specific aspects. Thus, it can be concluded that serious games as well as digital entertainment- education games need to be conceptualized in a gender-specific way to be successful.

163 4. Female Adolescents

“Educate a woman, you educate a nation” UNESCO mission statement

4.1 Introduction This chapter gives a brief overview of the developmental stages – physical, psychological, and cognitive – of female adolescents in general and of their particular situation in Germany. The purpose of this chapter is to provide information about this study’s target group and why HIV/AIDS and condom use education is an important issue concerning this group. Hence the chapter aims at better understanding why a digital game about HIV is useful to female adolescents. The word, “adolescence,” has its roots in the Latin word, “adolescere,” which means “to grow” or “to prosper” (Löffler, 2001; Grob, 2007). The term refers to the span of life between childhood and adulthood and describes the psychological, social, and cultural aspects of this special phase. The more physical aspects of growth can be described with the term “puberty.” Often “youth,” “teenager,” “adolescent,” and “young person” are used as synonyms (Grob, 2007).24 Although adolescence or youth describes the period between childhood and adulthood, this does not indicate concrete information about how long the period lasts since it varies inherently by culture and society (Grob, 2007; Berk, 2005; Ewert, 1983). According to Hurrelmann et al. (2006), since the 1950s youth has been established as an independent period of life in most Western societies, and nowadays this phase lasts ten, 15, or even 20 years (p. 33). Baacke (2003) argues that this extension is because of the prolonged time that persons stay in the educational system. German law defines youth as persons who are not younger than 14 years of age and who are not older than 18 years of age (Göppel, 2005, p. 3). According to a definition from the World Health Organization (WHO), young persons between ten and 19 years old can be called adolescents. Oerter & Dreher (1995, p. 312) give an overview of the terminological and chronological structure of “youth” as a phase of life: They define “pre-adolescence”

24 In the present study the terms of "adolescents" and "youth" are used interchangeably as a general description of young persons.

164 as the childhood time span that ends with the appearance of first sexual characteristics (see below, chapter 3.2.1 “Physical Changes”). “Adolescence” and “youth” are more universal terms including the time span from ten to 21 years old or 11 to 18 years old, respectively (see above). This phase can be divided into several sub-periods; “transcendence” or “puberty” (Ewert, 1983) ranges from about 11 or 12 to 14 years old, “early adolescence” from 14 to 18 years of age, and “late adolescence” from 18 to 21 years old. With the end of adolescence at about 21 years of age, “early adulthood” starts and then ends at the age of about 25 years, but of course every person has an individual development, thus classifications are approximate. Within the sub-periods described above, different aspects come to the forefront; whereas the term puberty comprises the physical-biological transformation process, the term adolescence focuses more on the mental conflicts of growing up (Göppel, 2005) and here, “identity” becomes a central issue (Oerter & Dreher, 1995, p. 346; cf. chapter 4.2.2 “Psychological Changes”). According to Christie and Viner (2005), the primary challenges of adolescence are 1. the achievement of biological and sexual maturation, 2. the development of personal identity, 3. the development of an intimate sexual relationship with an appropriate peer, and 4. the establishment of independence and autonomy in the context of the socio-cultural environment. Adolescence is a span of life in which complex, interwoven changes proceed to affect all areas of life. Physical, psychological, and cognitive developments interact, and therefore drastic changes occur. Grob (2007) even states that adolescence is an “awkward sandwich-position” (p. 187) between childhood and adulthood. The present study follows the definition of adolescence from the WHO that includes young persons between 10 and 19 years as mentioned above. Next, this study will focus on 15-year-old girls for three main reasons: Firstly, in order to be sure that HIV/AIDS is a topic of interest, the players should be in an age group where sexual issues are personally relevant for them; this can be expected after puberty. Secondly, prevention should take place before persons start to show a certain risk behavior, but not too far in advance; in this context this means several months before girls practice sexual intercourse. The German Federal Center for Health Education reported in 2006 that 12% of the 14-year-old girls, 23% of the 15-year-old girls, 47% of the 16-year- old girls, and 73% of the 17-year-old girls already had sexual intercourse (BZgA, 2006; cf. chapter 4.3.3.4). Thus, it makes sense to create the prevention game for 15- year-old girls, as 14 years and younger might be too early for most of the girls to deal

165 with HIV/AIDS, 16 years and older might be too late for a preventive intervention Third, in the qualitative pilot study the participating girls were asked what they think which age would be best for playing the game. Most of them answered girls who play the game should be about 14 or 15 years old (see chapter 6.8 “Qualitative Pilot Study”).

In the following subsections first the developmental stage of adolescence will be presented from different perspectives, namely considering physical, psychological, and cognitive aspects. Then the general situation of female adolescents in Germany – for example, living conditions, school situation, and leisure time activities – is described, followed by descriptions of the (mental) health status, and issues of sexuality (sex education, sexual orientation, sexual experiences, etc.). The chapter concludes with a subsection on reasons for the need of new HIV/AIDS prevention methods for teenage girls.

4.2 Developmental Stage 4.2.1 Physical Changes To describe the developmental stage of 15-year-old girls, it is necessary to start a few years earlier with the beginning of physical changes, specifically the beginning of puberty. Indeed puberty is the period in life when the “biggest venereal differentiation between the sexes since prenatal life happens” (Berk, 2005, p.476). While children’s bodies – both boys’ and girls’ – do not differ much except for primary sexual characteristics, at puberty the childish body changes into an adult body able to reproduce. For girls the process of puberty starts about one to two years earlier than for boys, but regional and individual differences also occur. On average puberty lasts about four years for girls and about six years for boys (Berk, 2005). The process starts when the brain sends hormone signals to the gonads, meaning girls’ ovaries or boys’ testes. Here diverse hormones are produced that activate several processes such as a growth spurt (Berk, 2005; Silbereisen & Schmidt- Rodermund, 1999; Ewert, 1983) or development of secondary sexual characteristics like pubic hair, growth of breasts, or development of female body shape with fat deposition (Berk, 2005; Berndt, 1982). The most active and thus important hormone

166 during female puberty is estradiol – an estrogen – which causes, amongst other things, growth of breasts and the uterus. Figure 15 shows the hormonal regulation of puberty for girls according to Berndt 1982 (Emanuele, Wezeman, & Emanuele, 2002, p. 275):

Figure 15. Schematic representation of hormonal regulation of girls’ puberty (according to Berndt 1982 (in Emanuele, Wezeman, & Emanuele, 2002, p. 275) Explanation of abbreviations: LHRH: Luteinizing hormone-releasing hormone; LH: Luteinizing hormone; FSH: Follicle stimulating hormone

In sum, the hypothalamus starts to produce LHRH, which activates the pituitary to produce LH and FSH, thus activating the ovaries to produce progesterones and estrogens. Progesterones and estrogen influence the hypothalamus and pituitary and, amongst other aspects, cause the growth of pubic and armpit hair as well as the growth of sexual characteristics like ovaries, uterus, labia, and bosom, thus leading to a female body shape. Oerter & Dreher (1995) describe the different stages of physical development as follows: At the age of about ten or 11 years, the haunches start to become rounder, the female body starts to gain weight, and bosom and nipples start to grow. Between 11 and 14 years old, pubic hair grows; an accelerated growth of ovaries, vagina,

167 uterus, and labia takes place; and also the menarche occurs. At about 14 to 16 years of age, armpit hair grows and the bosom gets its adult shape. However these are only estimated values, as the actual process varies by individual. Thus for 15-year-old girls, the physical changes should be completed, but they need not be (Oerter & Dreher, 1995). Although many authors report that girls reach menarche earlier – within the last 200 years a decrease from 17 to 12.5 years of age on average is reported (e.g. Berk, 2005 and BZgA, 2006) – it can be assumed that most 15-year-old girls are fully developed. A consequence of the decreasing age of sexual maturity to an average of 12.5 years, meaning that some girls even have their menarche at the age of 10 or 11 (see BZgA, 2006), is that precocious girls feel under pressure to act more like an adult and less like their age. Therefore those girls are more at risk of engaging in inappropriate (sexual) relationships with older persons (Berk, 2005). According to Haffner et al. (2006), the physical changes of the body and its proportions are especially problematic for girls. The German Federal Health Education Center reports that only 34% of the 15-year-old girls describe their body as pretty (BZgA, 2004). To integrate the new body shapes into self-perception, to accept a full-grown body with all its sexual characteristics, and to develop an adult sexuality are part of the developmental tasks of adolescents, which will be the topic of the following section about psychological changes.

4.2.2 Psychological Changes Psychological changes accompany the biological processes that are described above (Silbereisen & Schmidt-Rodermund, 1999). Many theories and models exist that try to describe the psychological situation of adolescents, but this section does not aim at providing an overview of all existing theories and models about adolescence. It rather aims at describing adolescents’ key psychological issues. For this purpose the developmental tasks model seems to be the most suitable, because it does not deal with abstract constructs but with concrete – in the sense of comprehensible and demonstrative – tasks that adolescents must fulfill. Therefore it can give an impression of adolescents’ psychological situation. Entitled “Developmental tasks and education,” the model was established by Havighurst and his colleagues and was presented in 1948 and has been further

168 developed since then (Oerter & Dreher, 1995). The authors explicitly pointed out that Erikson’s theory of personality and its stages of psychosocial development influenced their work. Havighurst identified six major stages during a lifetime, within each stage; persons have to cope with specific developmental tasks. These developmental tasks are defined as follows: A developmental task is a task which arises at or about a certain period of life of the individual, successful achievement of which leads to his happiness and to success with later tasks, while failure leads to unhappiness in the individual, disapproval by society, and difficulty with later tasks (Havighurst, 1972, p. 2). Those tasks can have different sources: 1. physical maturation, 2. personal values, and 3. pressures from society. The specific tasks for adolescents (aged 12 to 18 years), according to Havighurst, are listed below (Oerter & Dreher, 1995, p. 328): 1. Achieving new and more mature relations with mates of both sexes and of the same age, 2. Achieving a masculine or feminine social role, 3. Accepting one’s physique and using the body effectively, 4. Achieving emotional independence from parents and other adults, 5. Preparing for marriage and family life, 6. Preparing for working life and career, 7. Acquiring a set of values and an ethical system as a guide to behavior, 8. And desiring and achieving socially responsible behavior.

As the model and the tasks for each stage were developed in the 1940s, until today several researchers advanced the model and the tasks25. Since the 1940s society has changed and thus developmental tasks for youth are different today. Therefore various additional developmental tasks were identified by other authors (for examples, see Dreher & Dreher, 1985; Oerter & Dreher, 1995; Baacke, 2003; Fend, 2003; Göppel, 2005). In the following, all important developmental tasks for adolescents are described in detail. To describe the developmental tasks of Germany's current youth generation, the latest list of such tasks by Göppel (2005) seems to be the best option. “Acquirement of masculine/feminine role” was added as a developmental task (see

25 As this section is about “adolescence,” it will be focused on enhancements of the model concerning this age group only.

169 Oerter & Dreher, 1995; Baacke, 2003) because it seems to be an important aspect of growing up as well.

To Deal with the Physical Changes during Puberty and to Create a Positive Relationship with One's Own Body As described in the subsection about physical changes in girls, an enormous change of all parts of the body starts at puberty. Compared to psychological and cognitive developments, these are the most visible developments during adolescence (Göppel, 2005). Learning how to deal with the “new” body and the reactions of others to it are essential tasks with which adolescents have to cope (Grob, 2007). Girls’ reactions to their body's changes can differ tremendously; some girls can be unsure and afraid, while others can be very happy because of their anticipation of these changes. As Göppel (2005) reports, the menarche is still a drastic experience for many girls; they see it as a farewell to childhood. Compared to the sudden occurrence of menarche, the growth of breasts is a slower process but quite visible to the public. Girls have to accept that boys and men look at them differently and that their bodies develop key sexual stimuli. Peers are an important benchmark indicating what is “normal.” Girls prefer to be in the mainstream; if physical changes happen too early or too late, they risk being an outsider since early or late maturation can lead to teasing (Silbereisen & Schmidt- Rodermund, 1999). Girls who mature early do not have same-aged female friends who could function as role models and show them how to deal with the physical changes (Silbereisen & Schmidt-Rodermund, 1999). Additionally early maturation can often cause depression; girls have problems accepting themselves, and hence their self-concept is adversely affected (Göppel, 2005). As older boys are interested in girls who mature early, these girls sometimes take up risk behavior like smoking, alcohol, drugs, and sexual activity. Girls who mature at a “normal” time often have problems with accepting that their bodies are not as perfect as in advertisements and the media, and for many girls appearance becomes increasingly important. They especially think about their figures, and the high level of attention to appearance sometimes reaches the point of eating disorders (Göppel, 2005). Many girls want to be slimmer than their current size.

170 According to Göppel (2005), between 50% and 80% of all 11- to 19-year-old girls feel too heavy and want to lose weight, although most of them have a normal figure and a healthy weight.

To Create a Positive (Enjoyable, Self-Determined, and Responsible) Sexual Relationship Several authors see coming to accept sexuality as the major task during adolescence (e.g. Fend, 2003). This task accompanies the first one, because acceptance of one's own body is a precondition for developing a healthy and fulfilling sexuality. Adolescents have to learn how to deal with unknown feelings and reactions to their body. Nowadays youth grow up in a cultural environment where sexuality is no longer taboo; instead, the topic is constantly present in the media. Thus sexuality is no longer a mystery or a big secret. Yet a discrepancy exists between the permissive way the topic of sexuality is presented in the media and the bashful way it is dealt with in reality (Göppel, 2005). One of the main sources of knowledge about sexuality is teen magazines like BRAVO (BRAVO, 2006; Göppel, 2005). Here adolescents obtain information they want without asking someone in person. As described above, adolescents compare themselves with peers to discover whether they belong in the mainstream and are thus “normal.” Göppel (2005) criticizes that youth magazines mention age ranges for first sexual intercourse that are much lower than in reality. Therefore adolescents feel under peer pressure, because they want to meet the standard. Becoming sexually active is a balancing act between being too young or being a late bloomer and, in a sense, being perceived as a loose woman or as a prude.

To Acquire a Masculine or Feminine Role According to Berk (2005), early adolescence is a period in life when one's own sex role gains in importance. An increase in gender-specific attitudes and behaviors can be observed as adolescents develop a traditional gender role. Although this happens for both sexes, it is more apparent for girls since they feel less free than in childhood to experience activities with the opposite sex. After all, cognitive developments (cf. chapter 4.2.2 “Cognitive Changes”) – especially the concern about others' perceptions of them – evoke a susceptibility to gender role expectations (Berk, 2005).

171 Softness, compliance, and kindness are typical “female traits” (Baacke, 2003, p. 60), whereas independence and coolness are considered typical for boys. Girls must try to win someone over and are thus socio-emotionally dependent upon others. Analyses of teen girl magazines show that these magazines are designed primarily to tell girls that their most important function in life is to become sexually attractive enough to catch a desirable male (Peirce, 1995, as cited by Brown & Stern, 2002, p. 103). Yet according to Hurrelmann et al. (2006), many girls refuse the traditional role as housewife and instead make high demands upon themselves; they want to be attractive, active, and well educated, and they want to have friends, an interesting job, a home, harmonic relationships, and children in the future. Although girls have such modern ideas for a self-determined life, gender differences can still be found. For example political engagement is an area in which strong differences can be observed. Young women are politically active to some extent, but they engage more often than young men in social domains apart from established politics (Hurrelmann et al., 2006).

To Detach from Parents yet Remain Connected to Them Although the relationship between child and parents changes permanently from early childhood on – for example, as the child gains more autonomy at every stage of development – within adolescence the most drastic changes take place; a young person has to develop his or her own position, make decisions, and take on more responsibility (Göppel, 2005). This increase in autonomy causes some extent of de-idealization of parents. Because of this disillusionment, adolescents are disappointed with parents. On the other hand, parents have to accept that their children are not children anymore but are turning into young adults. Most often parents complain about the fact that adolescents spend less time with the family (Fend, 2003). Yet according to Göppel (2005), not only is less time spent together but the once shared worldview starts to differ. Among other things, this leads to conflicts; adolescents and their parents have different opinions about several areas of life. The maximum of dissent is at the age of 15; from then on, opinions start to converge again (Fend, 2003).

172 When adolescents are asked about the relationship with their parents, they tend to describe it as positive (Grob, 2007; Langness, Leven, & Hurrelmann, 2006). The time period between the ages of 12 and 15 is the only one when it is not described as positively as before and afterwards (Göppel, 2005). Fend (2003) found that the child- parent relationship is the most important predictor for the adolescent-parent relationship, because during childhood the basis for a strong relationship in the future is founded.

To Belong to a Group of Peers and to Develop Mature Friendships The less time adolescents spend with their parents, the more time they spend with peers. According to Fend (2003), 81% of 16- to 18-year-old persons report being a member of a clique. The development of new and responsible friendships is necessary so as to separate from parents (Fend, 2003); adolescents need to “emigrate” from parents and integrate into the world of peers. According to Oerter and Dreher (1995), the function of peers is to replace parents’ role as an attachment figure. As the relationship between parents and child has a basis in the past, the relationship between peers is geared toward the future. This means that peer relationships are proving grounds where adolescents can make meaningful experiences, test autonomy, try out different concepts of identity, and develop ideas of various forms of romantic relationships (Göppel, 2005). Another point of differentiation is that relationships with parents are involuntary, whereas an essential criterion of friendship is “voluntariness” (Göppel, 2005, p. 158). Compared to friendships during childhood, adolescents have different expectations of friendships. Some of these include agreeing with friends about music, clothes, or activities; having intensive, personal conversations about dreams, wishes, problems, or worldviews; and having a trustful and reliable relationship (Göppel, 2005). Fend (2003) reports that the higher the age of adolescents, the more they tend to discuss their problems with peers instead of parents.

To Develop a Positive Relationship to School and Learning Adolescence is, more than ever, time spent in school (Göppel, 2005). The main task for adolescents is to learn and to receive good graduation grades so as to have good prospects.

173 Thus the perspective of school is on the future, and the benefits of high grades lie ahead. The topics at school are neither connected to nor important for adolescents’ present lives. This is the reason for the paradox of school; adolescents want to explore and learn, but school often does not provide learning matter that is of interest to them. To get high grades, they have to learn about topics that are not of use to their present lives (Göppel, 2005). Additionally school requires qualities like adaptation, patience, rationality, self-discipline, motivation, accuracy, ambition, and consistency. These are normally incompatible with typical attributes specific to adolescents like spontaneity, impulsiveness, imbalance, disorganization, or emotionality (Göppel, 2005). Therefore adolescents need deeper insight in order to force themselves to learn in school.

Searching for Meaning and Developing Self-Contained Viewpoints Concerning Moral, Political, and Religious Questions As described above, taking school seriously is an important task, and to do so one needs aims in life. Such aims require adolescents to think about future perspectives regarding what or who they want to be, what they want to do for work, how they want to live, or what is important in their lives. Such thinking is intimately connected to the search for meaning. As cognitive developments enable adolescents to engage in abstract thinking (cf. chapter 4.2.2 “Cognitive Changes”), they begin to think about and imagine utopian worlds and political systems; they are fascinated by these topics and like to discuss them. Compared to adults who have accepted that no general answer to the question of meaning exists and that society has deficiencies, adolescents think about these issues with urgency and intensity (Göppel, 2005). Before long they begin to develop their own viewpoints and opinions.

Work on Personal Identity The search for meaning and the development of one's own viewpoints is closely connected to “identity.” Although many different and no standard or binding definitions of “identity” exist, it is undisputed that developing an “identity” is one of the main issues during adolescence (Grob, 2007; Göppel, 2005). Adolescents are aware of this expectation to shape their identity; they try out different roles, behaviors, and points of view to explore their potential identity. An aspect which is – compared to the inner work on identity – visible to others can be

174 described as “self-portrayal” or “presentation of identity” (Göppel, 2005, p. 237). Even though identity is associated with youth, it is a continuous and lifelong process.

4.2.3 Cognitive Changes As stated in the last section about psychological changes, Piaget (1954) established a theory of cognitive development that is still considered to be the major theory in this area (Flammer, 1996; Oeveste, 1982). It contains four major stages with a final stage starting at puberty, the so-called formal operational period (e.g., Piaget, 1954, 1984). According to Piaget (1984), the cognitive development of each human being can be divided into four periods: 1. Sensori-motor period (birth to two years old), 2. pre-operational period (two to seven years old), 3. concrete operational period (seven to 11 years old), and 4. formal operational period (11 years old to adulthood). While timing can differ individually, the sequence of these stages remains unchanged. Since stages are hierarchically structured, all abilities of the previous stage(s) are required to reach the next one. Thus the characterization of each stage differs, meaning that in each period a different level of thinking is predominant. It can be summarized that, during the sensori-motor period, the infant experiences the world by moving the body and using all senses. In the pre-operational period the child acquires abilities of imagination and language. A child in the concrete operational period acquires an appropriate use of logic. Lastly during the formal operational period, the ability of abstract thinking is the main issue. As the last stage starts with puberty (at about 11 years old) and lasts for some time, this is the stage that 15-year-old girls are experiencing. Therefore this period is described in more detail. In the course of the formal operational period, adolescents not only acquire the abilities of abstract thinking but also those of logical reasoning and drawing conclusions on the basis of given information. This “enormous qualitative change” (Neimark, 1984, p. 155) concerning adolescents’ cognitive abilities enables them to reflect upon themselves (Ewert, 1983). The two main issues of the formal operational stage are “hypothetic-deductive reasoning” and “propositional logic”:

Hypothetic-deductive reasoning. According to Berk (2005), young people are able to use hypothetic-deductive reasoning initially during adolescence. They are able to

175 think in a hypothetical-deductive way, meaning that adolescents can see statements as abstract assumptions and are able to formulate hypotheses and come to logical conclusions (even if the assumption is fictional, see below; Berk, 2005; Oeveste, 1982). When they have to solve a problem, they start with a rather general theory with all possible factors that could influence the result. In accordance with this theory, they formulate hypotheses or predictions about what could happen. Afterwards they test hypotheses in a systematic way to elaborate on whether or not they have evidence for their hypotheses/predictions. An often described example for the ability of hypothetic-deductive reasoning is the pendulum experiment (e.g. Graz, 2006; Flammer, 1996). One pendulum swings faster than another pendulum. The two pendulums differ concerning string length, weight, volume, and starting point. The task is to find out which of these four factors causes the different speeds. Persons at the formal-operational stage are able to systematically vary these four factors to identify the string length as the only reason for swinging speed. In contrast to this procedure, children in the concrete operational stage would start with a quite unsystematic course of action. They are not able to test hypotheses in their minds and start with reality or rather, the most obvious possibility. In case this solution does not work, they are unable to generate any alternatives (Berk, 2005).

Propositional Logic. A second important characteristic of the formal operational stage is the ability to use propositional logic. Adolescents are able to evaluate the logic of propositions even if those predications do not refer to reality (Berk, 2005). While the formal operational stage is reached at about 11 years of age, many authors mention (e.g., Ewert, 1983; Oeveste, 1982; Tomlinson-Keasey, 1972) that not everyone always reaches this stage. Oeveste (1982) states that passing through the developmental stages is not independent from influences of individual experiences and situational factors. Ewert (1983) points out that not every young person has the opportunity to experience the world in different ways, but for Ewert (1983) doing so is indispensable for cognitive development. Keating (1979) states that even well-educated adults have problems with abstract thinking; about 40% to 60% of students are unable to fulfill Piaget's formal operational tasks (see also Berk, 2005). Thus it can be assumed that many

176 adults stay in the concrete operational stage of thinking. On this account, it is presumed that not all 15-year-old girls are formal operational thinkers – a wide range of cognitive abilities can be expected for this group.

For those who reach the formal operational period, the new intellectual power does not only produce positive effects, like the possibility of abstract thinking and better problem solving abilities; it can also cause behavior that can be exhausting for parents and other people. According to Berk (2005), the amount of adolescents’ typical stressful reactions like combativeness, egocentricity, insensitive comments, and indecisiveness is a result of inexperience with the new cognitive abilities.

Combativeness If adolescents reach the formal operational stage, they are highly motivated to use their new cognitive abilities. They are no longer compliant schoolchildren but energetic, disputatious teenagers who are able to sort facts and thoughts as well as to define a viewpoint and persist in it (Elkind, 1994; Berk, 2005). Adolescents’ openness to effective arguments can result in intellectual, inspiring leisure activities like debates and endless meetings with friends about moral, ethical, and political topics. Because of recommending, explaining, criticizing, and defending answers, adolescents reach a higher level of comprehension (Berk, 2005, p. 507).

Egocentricity As adolescents have the opportunity to reflect upon their own thoughts and feelings and perceive all physical and psychological changes happening to them, they start to think more about themselves (Berk, 2005). Piaget suggested a new form of egocentrism at the stage of formal operations, the inability to distinguish between the abstract perspective of one’s own self and the perspective of others (Piaget, 1984; Berk, 2005). If adolescents try to imagine what others think, two different distortions may occur, 1. the anticipated audience and 2. the personal legend:

177 The anticipated audience. Adolescents believe that they always take center stage and that everyone is interested in them. Since they truly imagine themselves on stage, they become timid and try to avoid being at a loss. The personal legend. Because adolescents are certain that others observe them and think about them all the time, they develop an overly high opinion of themselves and their importance. This leads to the fact that they feel as though they are special and unique. However these two ways of thinking occur most frequently at the beginning of the formal operational period and usually decrease with age.

Idealism and Criticism Abstract thinking enables young people to think beyond what is real and open up to a world of ideals and perfection. Adolescents may thus imagine and desire to explore alternative families, religions, and political and moral systems. Adolescents’ idealism leads to construction of an ideal world without injustice, discrimination, or malpractice. Adults with more life experience have a more realistic view of the world, whereas adolescents have no space for the insufficiency of everyday life. Therefore with a perfect family in mind, yet with realistic parents and siblings, adolescents can become “nitpicking detractors” (Berk, 2005, p. 509).

Planning and Decision Making Adolescents who are able to use analytical thinking can handle cognitive tasks with more ease than they did at a younger age. In everyday life they often feel overwhelmed and indecisive; whenever they are required to make decisions, they take all possible opportunities into account, leading to indecisiveness. After gaining more experience with planning and making decisions, they eventually can decide with more self-confidence (Berk, 2005).

To sum up the developmental stage of 15-year-old girls, it can be said that from a biological point of view most of them are fully grown, meaning that they had their menarche and developed a female body shape and secondary sexual characteristics such as pubic hair and breasts. From a psychological perspective, 15-year-old girls are in an “awkward sandwich-position” (Grob, 2007, p. 187) that is an exhausting phase of changes and

178 rearrangements. They have to cope with the physical changes; create a positive sexual relationship; deal with the female role; detach and form an adult relationship with parents; become more involved with peer groups and friends; create a positive attitude toward school and learning; develop viewpoints concerning topics like morals, politics, and religion; and form a personal identity. Cognitive changes, necessary for the many tasks mentioned above, make self- reflection possible. According to Piaget’s theory of cognitive development, 15-year- old girls should have reached the final stage of cognitive development, namely the formal operational period. At this stage they are able to use abstract thinking and can draw conclusions on the basis of logical reasoning. However other authors (Ewert, 1983) point out that not everyone has the reaches the formal operational period; thus it can be expected that not all 15-year-old girls are capable of abstract thought.

4.3 Female Adolescents in Germany 4.3.1 Living Conditions General Living Situation According to the German Federal Statistical Office (Statistisches Bundesamt, 2006), at the end of 2004 altogether 469.200 girls of ages 14 to 15 years lived in Germany. Most of the girls lived with their families or at least with a single parent (Hurrelmann et al., 2006) and, according to Haffner et al. (2006), 90.9% of all female adolescents reported having their own room. Although the importance of peers increased during this time period, adolescents described the relationships with their parents as good and continuing to be of importance to them (Hurrelmann et al., 2006). Compared to boys, girls received more love, praise, and comfort from their parents (Langness et al., 2006). In general the relationship between adolescents and their parents can be described as cooperative rather than conflict-ridden, although arguing about or discussing specific topics is normal (cf. chapter 4.2.3 “Cognitive Changes”). Fend (2003) reports that 15-year-old girls discuss the following topics with their parents (multiple answers were possible): 51.3% of girls discuss politics; 45.8% have disputes over with whom girls associate; 44.6% of girls say that their friendships with the opposite sex are problematic for parents; 43.9% have debates about their clothing; 42.0% debate over girls wanting to go out; 39.5% have discussions about shopping; 37.2% discuss faith; 34.4% discuss school issues; 33.9% discuss girls’ behavior in

179 general; 31.9% discuss girls’ best female friends; and 29.7% discuss pocket money. What is not listed above that might potentially also be an issue for discussion is that 12- to 15-year-old girls do more homework than boys at the same age (Cornelißen et al., 2002; 12. Kinder- und Jugendbericht, 2005).

School Out of German girls, 25.5% go to “Hauptschule,” 33.2% attend “Realschule,” 38.7% go to “Gymnasium,” and 2.6% go to “Förderschule” (a special school). Compared to boys, fewer girls attend “Hauptschule” and more girls attend “Gymnasium” (Haffner et al., 2006). Since the period in life from 12 to 25 years of age sets the course for the future (Langness et al., 2006), a good school education is essential (cf. chapter 4.2.2 “Psychological Changes” about learning as a developmental task).

Leisure Time – Without Media According to Langness et al. (2006), adolescents can test different behaviors and ideas for how they can spend their free time. They can test different possibilities, practice alternatives, and reach their limits. In a report on youth, information, and (multi)media (so called JIM, Südwest, 2006), girls are reported as engaging in the following non-medial leisure activities daily or several times a week (multiple answers possible): 87% meet friends, 63% do sports, 62% do nothing in particular, 17% do activities with family, 15% go shopping, 11% attend sporting events, and six percent paint or do handicrafts. Thus meeting with friends is the favorite activity of girls during adolescence. Haffner et al. (2006) mention that 92.5% of girls report having four or more friends, 6% have two or three friends, 1.2% have one friend only, and 0.3% report having no friends at all. At least every second girl (52.7%) meets her friends outside of school more than twice a week; 40.1% of girls meet them once or twice a week; and 7.2% never or rarely meet them outside of school. Fend (2003) underlines the characteristics of friendships during adolescence as follows: They are important for self-exploration, self-disclosure, gossip, problem-solving, and fusion of logic and emotion. Out of all 15- to 21-year-old adolescents, 76% report being a “member” of a group (Langness et al., 2006). Peer groups influence leisure activities and consumption behavior. Cliques can be a possibility for girls to distinguish themselves

180 from the social environment and to test out roles and learn social rules. Cliques help keep them grounded, and members can help and understand each other (Grob, 2007). At the same time, peer groups can develop negative dynamics such as teasing one another or having rival subgroups (Grob, 2007).

Leisure Time – Including Media In the past years, media usage has been increasing during free time (Haffner et al., 2006). Thus media activities (e.g., DVDs and Internet) have increased in importance for girls (Langness et al., 2006), although more girls than boys like shopping and family activities and more boys than girls have technical and electronic hobbies. According to the youth, information, and (multi)media study (JIM, 2010), almost every adolescent has a TV, cell phone, CD player, computer, VCR, and Internet available at least in the household. Compared to boys, girls have fewer media in their own room (for example, TVs or personal computers); 68% of girls have their own TV set or flat screen and 76% have their own computer or laptop (JIM, 2010). In 2006, 80% of girls had access to the internet with an average usage time of seven hours per week (Langness et al., 2006). There is an increase in Internet access and the time girls spend on the Internet has increased: In 2011, only 2% of the girls report that they never use the Internet, 65% use the Internet daily, and 25% several times per week. On an average day between Monday and Friday, girls use the Internet more than two hours (JIM, 2010). Concerning digital games, 66% report using digital games on an average day between Monday and Friday: 38% percent of girls report using digital games for about one hour, 18% do so one up to two hours, 9% two to four hours, and 1% more than four hours; 34% of the girls report that they do not play digital games from Monday to Friday (JIM, 2010). Girls’ favorite game is The Sims (mentioned by 30% of the participating girls; the game can be played on several consoles and personal computers), followed by the Karaoke game SingStar (played on the console Playstation) mentioned by 14% of the girls, and 13% mention the game Wii Sports that can be played with the console Wii only (JIM, 2010). Girls use online communities more often than boys do: 83% of the girls use them daily or several times a week, 73% of the boys do so (JIM, 2010). The favorite online community is Facebook, as more than three-fourths of the young people (boys and girls) use it (JIM, 2010).

181 Online communities are the most frequently used application for cell phones and smartphones: 56% of the participants use such an app (JIM, 2010). 98% of the girls have a cell phone, and 22% have a smartphone; 94% of the boys have a cell phone and 27% have a smartphone (JIM, 2010).

Money and Jobs Adolescents are an important target group for commerce: They spend money not only on cell phones but on movies, popular music, digital games, and clothing. Langness et al. (2006) mention that adolescents have a considerable amount of money they can spend on brand name clothing, luxury articles, and hobbies. Buying these consumer goods is not only for fulfillment of desires but for social acceptance and self- realization (Langness et al., 2006). One of the most important adolescent experiences is having, in comparison to their earlier years, more autonomy concerning consumption (Baacke, 2003). However money is required to consume all these goods. As adolescents usually go to school or an apprenticeship, they are not employed full-time and do not earn much money. They have two main ways to obtain money; either they receive pocket money from parents, or they have to earn money through after-school or weekend jobs. Haffner et al. (2006) asked adolescents what amount of monthly pocket money they receive: 29.7% received less than 20 Euros per month, 54.7% received between 21 and 50 Euros, 11.5% received between 51 and 100 Euros, 2.8% received between 101 and 200 Euros, and 1.3% report receiving more than 200 Euros per month. According to the Twelfth Children and Youth Report (12. Kinder- und Jugendreport, Bundesministerium für Familie, Senioren, Frauen und Jugend, 2005), 50% of students between the ages of 14 and 16 years (male and female) have a paid job some of the time, while about one-third of 15- to 18-year-olds work regularly. Every tenth adolescent works more than 15 hours per week (Hurrelmann, 2002).

4.3.2 Health 4.3.2.1 Introduction For a long time, a systematic study about the health status of children and youth in Germany was lacking. However in 2007 information about this issue was provided in the “German Health Interview and Examination Survey for Children and Adolescents

182 (KiGGS),” published as a single study in the “Bundesgesundheitsblatt” [Federal Health Newsletter]. The Robert Koch Institute conducted this complex survey from May 2003 to May 2006. Altogether 17.641 children and adolescents took part in the study. Ages ranged between birth and 17 years old, and they were recruited from 167 towns and communities representative of Germany. In general most of the adolescents describe their health status as “excellent” or “good” (90%). The older the adolescents become, the less they call their health status “excellent.” Girls are more dissatisfied with their health status than boys (Langness et al., 2006). Ravens-Sieberer, Ellert, and Erhart (2007) present a study within the KiGGS about health-related quality of life for children and adolescents in Germany. They used two different measures. First they asked children and adolescents themselves about their quality of life on different scales, and second they asked the parents about their children's quality of life on the same scales. Self-reported health-related quality of life increases for the “self-worth” scale: 14- to 17-year-old adolescents report higher scores than do 11- to 13-year-old adolescents. Interestingly parents report a decrease in health-related quality of life, which is more distinctive for girls than for boys. Parents also report that girls between the ages of 11 and 17 years have a lower health-related quality of life especially on the “body” scale. Satisfaction or dissatisfaction with one's body during adolescence often originates from the extreme physical changes within that period of life (cf. chapter 4.2.1 “Physical Changes”). According to Stolzenberg, Kahl, and Bergmann (2007), 15-year-old girls have an average body height of 165 centimeters and body weight of 59.9 kilograms.

4.3.2.2 Somatic Diseases: Acute & Chronic Illness Kamtsiuris, Atzpodien, Ellert, Schlack, and Schlaud (2007) present the first results that provide representative information about prevalence of acute and chronic diseases of children and adolescents in Germany today. Acute diseases in childhood and adolescence are usually benign and do not become chronic. Children and adolescents are most frequently affected by common colds and influenza. Girls are affected more often than boys, especially between the ages of 14 and 17 years (prevalence of 87.8%).

183 With a prevalence of 33.8%, gastro-intestinal diseases are the second most common acute diseases of girls in this age group. The third most common is strep throat, with a prevalence of 22.7%. The following are the most common chronic diseases of girls between the ages of 14 and 17 years: allergic coryza (prevalence of 17.1%); neurodermatitis (prevalence of 14.6%); obstructive bronchitis (prevalence of 9.3%); asthma (prevalence of 6.7%); and migraine (prevalence of 6.6%). For migraines a significant difference between girls and boys could be found, with girls more likely than boys to suffer from migraines (6,6% girls; 4,2% boys).

4.3.2.3 Mental Health Ravens-Sieberer, Wille, Bettge, and Erhart (2007) conducted a study about children’s and adolescents' mental health, called the Mental Health Module (BELLA study), within the KiGGS. Amongst other questionnaires, they used the “Strengths and Difficulties Questionnaire” (SDQ; Goodman, Meltzer, & Bailey, 1998) and its so- called “Impact-Supplement” (Goodman, 1999) and combined the results for those questionnaires. First results focus on depression, anxiety, attention deficit disorder, and problematic social behavior. The results show that in general the prevalence rates of mental health problems are lower for girls than for boys; for depression and anxiety no sex differences could be found but girls, compared to boys, show signs of attention deficit disorder and problematic social behavior less often. Nevertheless, combining the results of all questionnaires used in the study, 22.2% of girls between the ages of 14 and 17 years are assigned to the categories of “possibly have psychological problems” and “likely have psychological problems” respectively. The remaining teenagers are assigned to the category “unlikely have psychological problems” (Ravens-Sieberer et al., 2007, p. 874).

4.3.2.4 Risk Behavior As the above section indicates, adolescents in Germany usually do not suffer from acute life-threatening diseases, but risky behavior can precede serious health threats in the future. Hurrelmann et al. (2006) mention the following risk behaviors that adolescents perform: 1. Lack of physical exercise, 2. malnutrition or eating disorders, 3. lack of stress management, 4. alcohol and tobacco use, and 5. drug abuse. An

184 additional risk behavior that can cause serious disease will also be discussed: 6. unprotected sexual activity.

Lack of Exercise Regular physical activity is an important factor for health and well-being (Lampert, Mensink, Romahn, & Woll, 2007). While 21.5% of adolescent girls (aged 11 to 17) engage in physical exercise less than once a week and can be called “inactive,” 17.5% exercise at least once a week. A total of 43.7% engage in exercise three times a week or more and reach the minimum requirement, and only 17.3% exercise at the optimal amount of once a day. A decrease in exercise for girls can be observed; the older the girls are, the less they exercise (Lampert et al., 2007; Langness et al., 2006). Girls of lower socio- economic status are especially noted as doing fewer sports (Lampert et al., 2007).

Malnutrition and Eating Disorders Although guidelines and recommendations for healthy nutrition are always in flux, it is, for example, common knowledge that too many sweets and soft drinks are harmful to one's health in the long run. Mensink, Kleiser, and Richter (2007) report that childrens’ and adolescents’ consumption of sweets and soft drinks in Germany is relatively high. In general it can be concluded that, with increasing age, fruits and vegetables are consumed less while soft drinks are increasingly consumed. About every second adolescent eats fruit daily, but the recommended consumption of several servings of fruits and vegetables per day is seldom reached. However girls eat more fruits and vegetables than boys (Mensink, Kleiser, & Richter, 2007; Langness et al., 2006). It is a matter of common knowledge that girls especially suffer from eating disorders. Although more and more boys also show symptoms of such a problem (15.2% of all boys), girls are still more affected by eating disorders (28.9% of all girls) (Hölling & Schlack, 2007). Hölling and Schlack (2007) even claim that eating disorders are the chronic illness most often seen in children and adolescents: 21.9% of all children and adolescents between the ages of 11 and 17 years report symptoms of an eating disorder. For the age group of 14 to 17 years old, almost every third girl (32.3%) reports symptoms associated with eating disorders.

185 Additionally those girls and boys who are more affected by eating disorders are also more likely to smoke (Hölling & Schlack, 2007).

Lack of Stress Management In case adolescents do not have adequate strategies to deal with problematic situations that cause stress, they will choose other options for stress reduction. Langness et al. (2006) report that girls who experience personal strain and conflicts are more likely to react in introverted ways; they tend to be more reserved and over careful, and they try to meet society’s requirements. In the long run these tendencies increase the likelihood of developing mental health problems (Langness et al., 2006).

Alcohol & Tobacco Use Haffner et al. (2006, p. 27) found that 40% of female adolescents in Germany smoke at least once in a while and 16% do so daily. Lampert and Thamm (2007) report different results; they mention that 20.3% of the 11- to 17-year-old girls smoke once a week. A look at the results of the 14- to 17-year-old girls shows that 5.7% of the girls smoke at least once a week, and in this age group 20.8% of the girls even smoke daily. Lampert and Thamm (2007) not only asked about active smoking but also about passive smoking; approximately 25% of the 11- to 17-year-old adolescents who do not smoke at least several times a week spend time in rooms where others are smoking. Twenty percent do so even daily26. While 19.4% of 15-year-old girls drink alcohol more than once a week, 32.3% of the 16-year-olds do so (Lampert & Thamm, 2007, p. 604). Again Haffner et al. (2006) report different numbers; according to their study, 30.8% of girls never drink alcohol, 58.7% drink once in a while, 8.0% drink once a week, 2.1% drink several times per week, and 0.4% drink daily. However both studies indicate that girls drink less than boys (see also Langness et al., 2006).

26 This result may be out of date because the German non-smoking law that came into effect in 2008.

186 Drug Abuse Haffner et al. (2006) report that 90.4% of female adolescents never use drugs, 7.6% use them once in a while, 0.6% use them once a week, 0.8% use them several times per week, and 0.6% use drugs daily. Lampert and Thamm (2007) asked for the different drugs that adolescents use. Of 14- to 17-year-old girls, 4.2% smoke marijuana, 0.6% take ecstasy, and 0.8% use amphetamines and the like.

Unprotected Sexual Activity As mentioned above, unprotected sexual activity is also a risk behavior. The use of contraception can be used as indicator for unprotected sexual activity. More than a fourth of all 16- to 24-year-old reported not using contraception (cf. chapter 4.3.3.5 “Use of Contraception”; Hübner et al., 2003), thus they are also not protected against sexually transmitted diseases (STD). But even those who do use contraception, namely with the birth control pill, are not automatically protected against STDs. Therefore it can be concluded that more than a fourth practice unprotected sexual activity. Brown and Stern (2002) explain that, for biological and sociological reasons, girls are more at risk than boys for contracting a sexually transmitted disease from an infected partner. They are less likely to notice symptoms and more likely to suffer from long-term health consequences including infertility, ectopic pregnancies, and cervical cancer.

4.3.3 Sexuality 4.3.3.1 Introduction This sub-section gives an overview of female adolescents’ sexuality and should make clear why new ways of protecting themselves again HIV/AIDS are especially necessary for girls. According to Oerter and Dreher (1995), the development of sexual behavior is a complicated interaction between biological factors – especially hormonal development – and psycho-social conditions like the erotic stimuli of a culture (for example, in the mass media), social contacts, and settings that afford opportunities for erotic experiences. Thus global statements about adolescents’ sexuality in general cannot be made; the cultural and social background should be taken into account. As this study is based on German female adolescents, this section focuses on them.

187 4.3.3.2 Sex Education Along with puberty comes physical maturation. It is therefore necessary that adolescents receive information about sexuality. In the BRAVO Dr. Sommer study (2006), participants were asked, “Who educated you about sexuality?” Girls answered, “my mother” (72%), followed by school (65%), the youth magazine BRAVO (28%), and their best friend (23%). Asked which information source girls actually use, girls gave the following answers (BRAVO, 2006): mother (48%); school (36%); BRAVO (34%); best female friend (35%); female friends (31%); brochures, books (13%); TV (12%); father (5%); friends (4%); and male friend (3%). Thus mothers are female adolescents’ favorite contact person concerning love and sexuality (see also Somers & Surmann, 2004; BZgA, 2006), and in accordance with findings in the BZgA study (2006), 75% of parents provide sex education for their daughters themselves. However parents also report problematic issues concerning knowledge transfer from parents to children, especially to daughters: 57% of parents find it problematic to talk about sexual practices and climax; 43% mention masturbation as a delicate issue; 37% say that pornography is a precarious topic; 25% say homosexuality and 17% say sexual harassment are difficult topics; 15% have problems talking about abortion and 13% about sexually transmitted diseases; for 11% sexual organs are a sensitive issue; and 7% mention menstruation/ovulation as a difficult topic. This shows that parents especially have problems talking about practical aspects concerning sexuality. Dannebeck and Stich (2002) mention that adolescents want to receive factual information from mothers, schools, and print media. As long as adolescents do not have their own sexual experiences, they mainly get their ideas about sexual practices from TV; yet on TV it is almost never shown that the persons having sex use condoms or other methods of contraception or talk about these issues (Brown & Stern, 2002). When forming an opinion about sexual matters, adolescents like to discuss general sexual issues with peers. When these sexual issues become personal, adolescents prefer discussing them with their best friends. It can be concluded that adolescents seek factual information about sexual practices and biological basics (for example, when asking their mothers about sexual issues), and they want to inform themselves about what is “normal” by talking with peers and friends.

188 4.3.3.3 Sexual Orientation of 15-Year-Old Girls in Germany According to a study that was conducted in 1996 by Hübner, Münch, Reinecke, and Schmidt (2003), 92.5% of 16- to 24-year-old women describe themselves as solely or predominately of heterosexual orientation, 2.3% as bisexual, and 0.8% as solely or predominately of homosexual orientation; the remaining women answered “Neither – nor” (2.1%), “I don’t know” (1.8%), or did not answer this item (0.5%). The BRAVO youth study (2006) asked not only explicitly for sexual orientation but also whether participants ever had homosexual feelings. While 88% of the girls answered “never,” 11% said “yes,” and two percent did not give an answer. Thus it can be assumed that some heterosexually-oriented girls also had homosexual feelings at least once. Concerning heterosexual feelings, 85% of the 15-year-old girls reported that they had already fallen in love, and 63% said that they had a boyfriend already (BRAVO, 2006).

4.3.3.4 Sexual Experiences of 15-Year-Old Girls in Germany Although the first time of sexual intercourse can give only a limited impression of adolescents’ sexual behavior since it neglects other non-penetrative sexual practices (Berk, 2005), it is often used as an indicator for sexual activity. The German Federal Center for Health Education reported in 2006 that 12% of the 14-year-old girls, 23% of the 15-year-old girls, 47% of the 16-year-old girls, and 73% of the 17-year-old girls already had sexual intercourse (BZgA, 2006). Similar results were found by the BRAVO youth study (2006). As for heavy petting – which can be defined as sexual activity without penetration – 47% of the 15-year-old girls have experience (BRAVO, 2006). As for lighter caresses, many 15-year-old girls have experience; 79% have experience with hugging and kissing, and 67% have experience with French kissing (BRAVO, 2006).

4.3.3.5 Use of Contraception As 86% of adolescent girls report that their first sexual intercourse happened rather spontaneously, it can be concluded that it was not planned in advance (BRAVO, 2006). This could explain why, according to Brucker (2002), 11% of girls and 16% of boys did not organize contraception before their first sexual intercourse (see also Berk, 2005; BRAVO, 2006). However 14% of the young people reported that they

189 had sexual intercourse without any contraception after their first time of having sex (BRAVO, 2006). This result is similar to Hübner et al. (2003) who report that only 71.5% of adolescents claimed that they always use contraception. That means that more than a fourth of all 16- to 24-year-old participants at least sometimes have sexual intercourse without using any contraception, and more young men than women report doing so (see also Berk, 2005). One factor that influences the use of contraception is familiarity. The less the girls or boys know their sexual partners, the less they protect themselves (Brucker, 2002). As the gap between physical and psychological sexual maturity has widened (Oerter & Dreher, 1995), age is also a relevant factor. Unfortunately those who have matured early often do not use contraception, and they expose themselves to risks like unwanted pregnancy and sexually transmitted diseases (Appel, 2002). According to Bode (2003), it can be observed that the more experience girls have with sexual intercourse, the more they tend to use the birth control pill as a contraception method and the less often they use condoms. In accordance with Appel (2002), Bode (2003) also reports that adolescents stop using condoms if other contraception (e.g., the birth control pill) is used. In the majority of cases, for young people protection from pregnancy has priority over protection from sexually transmitted diseases. In extreme cases, even a negative correlation between use of condoms and taking the birth control pill can be found. One explanation could be that adolescents desire romantic relationships, and the use of condoms as protection against a deadly disease clashes with this idea of romantic love (Kellar-Guenther, 1999; Witte, 2005). Adolescents usually live in “serial monogamy,” meaning that they have committed to relationships for awhile (the first committed relationship usually lasts about six months, BRAVO, 2006) and are usually faithful during that time. The BRAVO youth study (2006) reports that 91% of all adolescents cannot imagine or would never have sex without falling in love. However, as mentioned above, romantic relationships and condom use do not match for many people, and female adolescents focus more on avoiding pregnancy than on avoiding sexually transmitted diseases (STDs). The birth control pill is the most used contraception method with 69.4% of sexually active female adolescents using it (Hübner et al., 2003). As “serial monogamy” implies that partners change after some weeks, months, or years – even though partners are faithful during the relationship – there is a risk of being infected

190 with STDs (Appel, 2002; Thompson, Kyle, Swan, Thomas, & Vrungos, 2002). One author even argues that “serial monogamy” should more appropriately be termed “serial risk” (Witte, 2005).

4.3.3.6 Consequences of Unprotected Sexual Activity Teenage Pregnancy For two-thirds of girls between 14 and 17 years of age, pregnancy would be a disaster (Stern, 2006), but according to Brucker (2002) the German Association of Pediatricians reports that every year over 10.000 girls under the age of 18 get pregnant. The German Federal Statistical Office reported that 6.327 induced abortions for girls under the age of 18 occurred in the year 2000. In a study by Bardeleben, Fieberg, and Reimann (1995), 10.4% of the sexually active female adolescents said that they accidentally became pregnant at least once.

Sexually Transmitted Diseases (STD) Another problem, besides pregnancy, of carelessly handled contraception is sexually transmitted diseases (STD). Berk (2005) reports that sexually active adolescents are more at risk for being infected with sexually transmitted diseases than any other age group. Young women between the ages of 20 and 24 years are often infected (Bremer, 2003). Heinz (2001) reports on the website of the German “Consortium for Children and Youth Gynecology” that about 60% of all people infected with an STD are younger than 25 years of age, and 30% are even under the age of 20. Girls in the age group between 14 and 19 are infected twice as much as boys in the same age group (see also U.S. Centers for Disease Control, 2001, cited by Berk, 2005). Heinz (2001) suggests that specific physiological conditions during the development of female genitals might be conducive to infections. A female adolescent who has unprotected sex with an infected partner just one time has a one percent chance of contracting HIV, a 30% chance of contracting genital herpes, and a 50% chance of contracting gonorrhea (Alan Guttmacher Institute, 1994, as cited by Brown & Stern, 2002).

4.4 Need for New HIV/AIDS Prevention Methods As mentioned above, although female adolescents’ main focus of contraception use is on avoiding pregnancy, many girls get pregnant and it can be assumed that sexually

191 transmitted diseases are widespread (Bremer, 2003; Heinz, 2001). This happens despite sex education being a part of the school curriculum in Germany and sex being omnipresent in the media (Berk, 2005). Several reasons indicate that new communication and prevention ways for girls concerning sexuality and HIV are needed:

Increasing Infection Rates It can be assumed that in Germany most of the HIV-positive persons were infected during youth or young adulthood (Schwerpunktbericht der Gesundheitsberichterstattung des Bundes [Focus Report of the Federal Health News Coverage], 2004; Appel, 2002). Although most newly infected persons are men having sex with men, the infection rate has increased for heterosexual persons as well, with the growth rate being highest for women (Schwerpunktbericht der Gesundheitsberichterstattung des Bundes [Focus Report of the Federal Health News Coverage], 2004; Appel, 2002; see also chapter 6.2.1 about HIV/AIDS prevention as topic for the present study).

Poor Knowledge Adolescents know more about sexuality and at an earlier age when compared to the past, but studies show that they still have deficits in knowledge concerning these issues (Baacke, 2003). Brucker (2002) mentions that the knowledge about essential biological processes – despite all efforts made by schools and parents – is rather poor. Knowledge deficits can be identified, for example, about the period of conception (BZgA, 2006), and many students think that “testing” protects from HIV/AIDS (Franzkowiak & Sabo, 1996). Adolescents are unsure about how HIV is transmitted; every tenth participant believes that only homosexuals can be infected with HIV or that French kissing is a way of infection (BRAVO, 2006). According to the German Federal Health Education Center study (BZgA, 2006), girls report that their biggest gap in knowledge is about sexual practice and reactions (43%) and sexually transmitted diseases (40%). Furthermore 38% would like to have more information about abortion, 34% about pregnancy and birth, 34% about sexual harassment, 32% about contraception, and 31% about tenderness and love. This shows an unsatisfied demand; girls want to know more about sexual issues and especially more about concrete practices.

192 Difficulties with Transferring Theoretical Knowledge into Practice As stated above, girls want to know more about sexual practices. Although students are instructed about sexual issues in school, a remarkable number of all 12- to 14- year-old girls report that they did not receive any useful information about HIV/AIDS in school (Franzkowiak & Sabo, 1996). Schools tend to address sexuality in clinical terms rather than in the context of relationships, emotions, and desires (Brown & Stern, 2002; Franzkowiak & Sabo, 1996). Hence adolescents are informed, but many are unable to transfer their knowledge about sexuality into practice (Baacke, 2003). This shows that being educated about sexuality is not the same as knowing how to use contraception or how to protect oneself from HIV infection. Thus adolescents have an information deficit concerning practical realization (BRAVO, 2006).

Uninformed Contact Persons Besides school, mothers are girls’ favorite contact persons to talk about issues like sexuality (see above; BRAVO, 2006; BZgA, 2006; Somers & Surmann, 2004). But according to Brown and Stern (2002), parents often address sexual topics awkwardly, if at all. Many parents lack information about sexuality and HIV/AIDS, and they do not possess the appropriate communication skills. Parents should be addressed through special preventive interventions so as to avoid passing on deficits to their children (Franzkowiak & Sabo, 1996).

Not Thinking About HIV The BRAVO youth study (2006) asked the participating adolescents if they worried about being infected with HIV in the future. At 42%, most of them answered, “I have not thought about this issue yet”; 25% answered, “No, I know how to protect myself”; and 24% said, “Yes, although I know how to protect myself.” Four percent did not answer this question. Hence it is necessary to make adolescents aware of the risks of an HIV infection.

Negated Sex Differences Unfortunately most of sex education at school negates sex differences; girls and boys are taught about sexuality in the same way and only seldom are they separated for sex education lessons. Yet of course sex-related differences exist. Among other aspects,

193 those differences can be explained with different developmental tasks for girls and boys to fulfill (chapter 4.2.2 “Psychological Changes”). Differences exist concerning health behavior, substance abuse, media usage, perception of problems, and worries. Concerning HIV/AIDS, Welch Cline & McKenzie (1994) identified sex differences in knowledge, attitudes, behavior, and communication. Therefore sex-related prevention and health promotion interventions are needed to help girls and boys with their specific tasks (Haffner et al., 2006). This means that more gender-separated sex education strategies and methods should be developed.

Rejection of Usual Prevention Methods Franzkowiak and Sabo (1996) point out that adolescents often reject or react skeptically toward usual informational or educational intervention (Kromer, 2002) especially if these prevention methods contain “daunting messages” (p. 197; see also Reschke, 1990, or Barth, 2002, about fear appeals in health communication) that serve as a disincentive to adolescents.

4.5 Summary Adolescence is the time span between childhood and adulthood, starting with puberty, in which drastic biological processes occur. The biological changes occur because of hormonal changes starting with puberty. 15-year-old girls in general should have reached a final stage of physiological development. These physical changes lead to psychological processes, as the adolescent has to deal with the “new body” and has to accept her new body shape. The described developmental tasks by Göppel (2005) are useful in understanding the inherent psychological process of adolescents, and they give an impression of the topics this age group must deal with. Especially for girls, it is often not easy to accept the body changes, and they feel more under pressure to meet standards in all areas of life. In addition to biological and psychological processes, at puberty a new stage of thinking is usually reached and thus cognitive abilities increase; adolescents reach the formal operational period according to Piaget’s developmental theory, meaning that they are able to think abstractly. However not all 15-year-old girls reach this stage, because this level needs optimal preconditions that might not be available for all.

194 In sum, the descriptions of physical, psychological, and cognitive stages show that adolescents are in a stage of enormous changes that affect all aspects of their lives. The living conditions of female adolescents in Germany can be described as good in general. Most of them have their own rooms at home, go to school, and can spend their leisure time with various activities. Especially noteworthy, a broad range of media equipment is available to them. Almost all 15-year-old girls have a mobile phone, and most of the girls have access to the internet as well as radio, television, and a VCR. Female adolescents receive pocket money from their parents, and many of them work to earn money for luxury articles like brand-name clothing and for leisure time activities. The health situation of 15-year-old girls in Germany can also be described as good. Girls usually do not suffer from life-threatening diseases, and the prevalence of other kinds of illnesses is rather low. Also, mental health problems are likely to occur, as the study by Ravens-Sieberer, Ellert & Ehrardt (2007) indicates. Especially problematic for girls’ futures could be the risk behavior that girls start to engage in during adolescence like lack of exercise, malnutrition, eating disorders, lack of stress management, alcohol and tobacco use, drug abuse, and unprotected sexual activity. These risk behaviors could impact disease contraction during adulthood as well. One of these risk behaviors, unprotected sexual activity, can lead to serious consequences like HIV or other sexually transmitted diseases. Although most of the girls have received sexual education at home and in school, it seems that knowledge about sexual issues – especially concerning the transfer from theory to practice – is low. Adolescents seek factual information about sexual practices and biological basics, and it is important for them to know whether they are “normal” compared to other girls. To find this out, they talk with peers and friends about sexual issues. According to a study by Hübner et al.(2003), it can be assumed that 15-year- old girls in Germany are mainly heterosexual (92.5%), in addition some describe themselves as bisexual and a few as homosexual. Concerning sexual experiences of 15-year-old girls, it can be supposed that almost every fourth girl (23%) has already had sexual intercourse and that almost every second girl (47%) has had experiences with other non-penetrative sexual activities like heavy petting.

195 Although 71.5% of adolescents claimed, in a study by Hübner et al. (2003), that they always use contraception, this also means that 28.5% do not do so regularly, which can lead to teenage pregnancies. Since many girls only use the birth control pill for contraception and do not protect themselves against sexually transmitted diseases by using condoms, the risk for being infected with STDs – and in this context also with HIV – increases. The girls only have low awareness of being at risk, as most young people are faithful and live in serial monogamy and thereby feel protected. However serial monogamy means that sexual partners change after a while; therefore Witte (2005) points out that it should more appropriately be called “serial risk.” This shows – amongst other points (see below) – that there is a need for new HIV/AIDS prevention methods. Factors that especially illustrate the importance for new prevention methods are the increasing infection rates for heterosexual females, their poor knowledge about HIV infection ways, the difficulties of transferring knowledge into practice, uninformed contact persons, girls’ carelessness, neglected sex differences in the context of sex education, and the rejection of usual prevention methods. Therefore, it is an important task to develop additional methods for HIV/AIDS prevention that take the problems mentioned above into account. As shown in the chapter about the entertainment-education strategy (cf. chapter 2 about the entertainment-education strategy), this strategy can be used to make people aware of their risks, give them accurate information and practical advice in a gender sensitive way without being rejected by the recipients. Therefore, the entertainment-education strategy is a promising way to educate female adolescents about HIV/AIDS. When choosing an appropriate medium for such an entertainment-education intervention for educating female adolescents about HIV/AIDS, girls’ media usage habits show that computer and Internet became very important activities (cf. chapter 4.3.1) and also digital games are on the rise as 66% of the girls play them on workdays (cf. chapter 4.3.1 and chapter 3.2.8.1 “Girls’ Use of Digital Games”). Furthermore, digital games about HIV/AIDS prevention have been shown to be entertaining (cf. chapter 3.2.7 about digital games for HIV/AIDS prevention). Digital entertainment-education games are rare, but promising in terms of being an effective education tool (cf. chapter 3.2.6 “Digital Entertainment-Education Games”).

196 Thus, a digital entertainment-education game – like the game Supergöre that is created for this study – could be a useful medium to educate female adolescents about HIV/AIDS prevention.

197 5. The Present Study

The aim of this thesis is to test whether the entertainment-education strategy can be successfully combined with the use of digital games. In this chapter the conceptual framework of the present study will be specified according to the theoretical background provided above. To do this, firstly a research question is developed, secondly all important variables are described, and finally, the research design is presented.

Entertainment-education is a strategy whose core is as old as mankind and story telling, but only within the last decades did the entertainment-education strategy receive scientific attention (cf. chapter 2.1). Thus, more and more scientists from different research fields are interested in this strategy of combining entertainment and education to educate an entertained audience. And entertainment-education seems to be an especially promising way to educate hard-to-reach persons, meaning people who would not learn about certain issues on their own (cf. chapter 2.2.2). Many theories and models (for example Bandura's Social Learning Theory, the extended ELM, the Sabido Method, etc., cf. chapter 2.3) explain entertainment- education effects by drawing upon the engaging nature of narratives. Many successful entertainment-education soap operas or other programs work because they contain characters suitable for social modeling, film sequences that foster engagement in a story line or other narrative-based characteristics (cf. chapter 2.4; e.g. Sabido, 2004; Singhal & Rogers, 2003). The present study is about the usage of digital games for entertainment- education. Although some digital games are also based on narratives, a narrative is not part of every digital game. But every digital game is interactive; interactivity is the key feature of all digital games (Klimmt, 2004b; cf. chapter 3.2.5.3). Thus, interactivity is the most important difference between traditional entertainment- education programs developed for TV, radio, or print media on the one hand and digital games on the other hand. For this reason, the present thesis will focus on interactivity as the main characteristic of digital entertainment-education games. Hence the digital game

198 created for this study is mainly characterized by interactivity and not narrativity, in order to test whether interactive media can be used for entertainment-education. Thus the game to be created for this study will not contain more narrative elements than necessary for the process of game playing. Not only the theory, but also effects and strengths of the entertainment- education approach were identified in the context of non-interactive entertainment- education media, e.g. radio or television soap operas, songs, or books (cf. chapter 2.4). Therefore, previous findings and knowledge about entertainment-education cannot be automatically transferred to interactive media like digital entertainment-education games. Digital games have not yet definitively been shown to be an effective entertainment-education medium, as research is at an early stage (cf. chapter 3.2.6). Although a few entertainment-education games exist, for example the Heart Sense Game, that have shown to be effective, those games do reveal their educational purpose promptly in the course of game playing. To really reach hard-to-reach persons it can be assumed that the purpose should not be obvious; otherwise a game might evoke reactance and thus be ineffective (cf. chapter 4.4; Franzkowiak & Sabo, 1996; Kromer, 2002). Nevertheless, the use of digital games for entertainment-education is promising. Research has shown that digital entertainment games can produce positive outcomes for players (cf. chapter 3.2.4.2). Although research about digital games focused on negative effects of entertainment games for years, positive effects have also been reported: e.g., a wide range of cognitive skills can be improved by playing digital games, such as spatial skills (e.g. Lee & Peng, 2006; Subrahmanyam & Greenfield, 1996, 1994), hand-eye coordination (e.g. Neuß, 2006; Wink & Lindner, 2002; Lerchenmüller-Hilse & Hilse, 1998), iconic skills (e.g. Subrahmanyam et al., 2001), and academic performance (Connolly et al., 2012). Furthermore, digital games can lead to improvements concerning emotional and social issues (cf. chapter 3.2.4.2; e.g. Neuß, 2006; Kraam, 2004). Although the studied effects mentioned above mostly occurred unintentionally, it can be concluded that digital games can actually be used for attaining positive effects. Using digital games for positive educational effects is the primary aim of serious games (cf. chapter 3.2.5). Serious games are digital games intentionally designed to educate players, or digital entertainment games that consist of educational elements (cf. Ritterfeld, Cody, & Vorderer, 2009).

199 Serious games are different from traditional education, mainly because they offer the following characteristics that are seen as advantageous for the education process: multimodality, interactivity, narrative context, option for (social) multiplayer use, and the specific frame of the gaming situation (e.g. Klimmt, 2009; cf. chapter 3.2.5.3). Those specifics are presumed to lead to advantages of serious games over traditional education media. For example, multimodality is supposed to increase the chances of knowledge acquisition as well as the likelihood of knowledge application (Klimmt, 2009, mechanisms 6 and 14; cf. chapter 3.2.5.4). Generally, it is expected that the specific elements mentioned above increase enjoyment, which is intrinsically motivating, engaging, stimulating: because of enjoyment, people tend to voluntarily select and play a game, have a higher degree of attention and interest, and talk more about the game content (e.g. Klimmt, 2009). According to Klimmt (2009, cf. mechanisms 11 and 13), enjoyment increases involvement; involvement has in turn been shown to function as a mediator variable concerning entertainment-education effectiveness. It can therefore be seen as a “key factor” (Sood, 2002, p.154) and will also be included as a mediator variable in the present study. The expected advantages of serious games as educational tools might only appear if they meet a certain qualitative standard. Otherwise, problems might arise (cf. chapter 3.2.5.5). Disadvantages of using serious games as educational tools could result from the game design (a poor design might not yield the expected effects, Mitchell & Savill-Smith, 2004; Kirriemuir & McFarlane, 2004), from too many stimuli or too much information (which increases so-called cognitive load, Peng, 2009), or a bad marketing strategy which could directly cause rejection (Kirriemuir & McFarlane, 2004; Mitchell and Savill-Smith, 2004). For this study, problems of game design in particular need to be taken into account because of the limited financial budget. But this is not necessarily a problem: Some games are very famous although their design is simple (e.g. PacMan or Tetris), so it is possible to create entertaining games with limited resources. Serious games have been shown to be effective – however, they are related but not identical to digital entertainment-education games. Thus the possibility of explicitly using digital games as entertainment-education interventions still has to be examined (see above). Particularly with regard to the fact that media usage has

200 changed in recent years and people spend more and more time playing digital games (Klimmt, 2004b), it seems to be a promising way for (health) knowledge transfer to include information about health and other relevant topics in digital games as defined by the entertainment-education strategy. Apart from that, using digital entertainment-education games is also in accordance with Singhal and Rogers (2004) who propose expanding entertainment- education to other media, countries, and topics – and one of those expansions are entertainment-education interventions in the form of digital games (Singhal & Rogers, 2004). Wang and Singhal (2009) redefine the entertainment-education strategy in order to include digital games: Entertainment-education is a theory-based communication strategy for purposefully embedding educational and social issues in the creation, production, processing, and dissemination process of an entertainment program, in order to achieve desired individual, community, institutional, and societal changes among the intended media user populations (p. 272/273). According to them, the whole process of design, production, and release should follow entertainment-education guidelines. They state that among other things, entertainment-education interventions should have a useful purpose by aiming at being beneficial for their players, and target audience members should be involved from the beginning (Wang & Singhal, 2009). This calls for carefully selecting target groups and topics to make sure that the topic is compatible with and beneficial to the target group, like HIV/AIDS for adolescents in the present study (see below). Because entertainment-education programs should be as target-group-specific as possible (Singhal & Rogers, 2004) the medium selected for should be as compatible with the target group as possible, too. Digital games are played by adolescents (cf. chapter 3.2.8); therefore it seems promising to create a digital entertainment-education game for adolescents. And the game should not only be target-group-specific, it should also be as appealing to and as easy to understand as possible for the target group, to make sure that audience members like and use it. This is in accordance with the uses and gratifications theory: Media products should provide characteristics that help media users to gratify or satisfy their needs.

201 Entertainment and information are the most important gratifications (Schweiger, 2007; cf. chapter 2.3.6.1), thus entertainment-education is an advantageous combination in terms of the uses and gratification theory. Gender is an important issue when creating a target-group-specific digital entertainment-education game, because entertainment-education (Yahaya & Olajide, 2003) as well as digital game research (Hartmann & Klimmt, 2006) have shown that gender matters concerning the effects of entertainment-education programs as well as in the context of digital games. Therefore it makes sense to create a gender-specific digital entertainment-education game. Research has shown that female players are a rapidly growing group, but they enjoy different digital games than male players (e.g., Hartmann & Klimmt, 2006; cf. chapter 3.2.8). Girls like funny, comic-style games with non-violent and non-sexual elements, games that provide opportunities for communication and interaction with other players, for to identifying with a female main character, and games that include familiar game patterns (cf. chapter 3.2.8.4). Thus, digital entertainment-education games need to be gender-specific in order to maximize their effectiveness. The topic chosen for the present study should be of general importance and be of benefit to the target audience members; the topic of the present study – HIV/AIDS prevention – is one of the UN Millennium Development Goals (PCI Media Impact, 2007) and thus widely accepted as important; and being able to protect oneself from HIV/AIDS is advantageous for individuals. As HIV infection rates in Germany are still an issue (Robert-Koch-Institut, 2012) and heterosexual females are an often neglected group (Appel, 2002), it seems plausible to create a digital entertainment-education game about HIV/AIDS for adolescent females. Girls start displaying risk behavior during adolescence that can lead to serious problems in the future, for example unprotected sexual activity. Females are more at risk of becoming infected with sexually transmitted diseases during heterosexual intercourse than males (e.g. Berk, 2005; cf. chapter 4.3.3.6). In Germany, sexually active female adolescents mainly use birth control pills for contraception; condoms are often not used in relationships because partners feel safe (Bode, 2003). As these relationships are only serial, there is a so called serial risk (Witte, 2005) of becoming infected with a sexually transmitted disease like HIV. But many female adolescents do not feel at risk, they do not think about HIV, and they often reject traditional prevention methods (Franzkowiak & Sabo, 1996). And again,

202 research has shown that gender matters as sex education should be gender-specific in order to really reach females and males (Haffner et al., 2006). Therefore, a digital game about HIV/AIDS for female adolescents is a promising way to educate girls about HIV/AIDS prevention. Digital games for HIV/AIDS prevention have been created, but not as gender- specific, distinct entertainment-education games (cf. chapter 3.2.7). Games are either entertaining, but provide little information (like Catch the sperm), or very informative, but less entertaining (e.g. Reducing the risk). Games researched so far were not found to be both entertaining and effective in educating about HIV/AIDS prevention. The literature does not provide references to well-defined, empirically tested digital entertainment-education games for HIV/AIDS prevention. Hence the general research question for the present thesis is: Can a digital entertainment-education game be created and used to educate female adolescents about HIV/AIDS prevention? The literature provides some indicators that can be used for answering this research question (cf. chapter 2.3), although most of the theories and models that are assumed to explain why entertainment-education is effective originate from mass communication and were originally developed for non-interactive mass media and cannot be transferred to digital entertainment-education games (see above). The models with steps/stages to behavioral change (chapter 2.3.2) agree on change being a multilayered process that includes several primary steps/stages – like attention (McGuire’s hierarchy-of-effects model), increases in knowledge (Singhal and Rogers hierarchy of media effects model) and interest (McGuire’s hierarchy-of- effects model) as well as interpersonal communication (Singhal and Rogers hierarchy of media effects model) about the topic – as important pre-conditions for behavior change. Based on this view of behavioral change, preceding pre-steps/stages – so- called indirect effects – can also be classified as positive impacts of entertainment- education. The agenda-setting model provides additional reasons why entertainment- education programs can influence audience members’ interest in a topic: People might add the topic to their personal agendas. In that case a person starts turning attention to the intended topic, being interested in it and thinking about it (cf. chapter 2.3.7.1). But not only theoretical reasons for surveying indirect effects exist, empirical reasons have also been found. Research has shown that entertainment-education

203 programs indeed had positive outcomes concerning people's knowledge, interest, and interpersonal communication (chapter 2.4). Knowledge, interest, and interpersonal communication have in turn been shown as important for a behavior change process. For this reason it can be assumed that the present game should increase knowledge about HIV/AIDS prevention, interest in this topic, and interpersonal communication about it. Therefore knowledge, interest and communication will be used as indicators for the effectiveness of the digital entertainment-education game created for the present study and function as dependent variables (cf. chapter 6.3). Social-psychological theories – the most important one to mention is Bandura’s Social Learning Theory – predict that behavior change is influenced by perceptions, beliefs, attitudes, and values of an individual, and by elements of the social environment (cf. chapter 2.3.3). Bandura (1977, 2004) points out the importance of self-efficacy for behavior change, which is defined as an individual’s perception of his or her capability to deal effectively with a situation as well as the individual’s sense of perceived control over a situation (Bandura, 1977, 1997). Self-efficacy is related to the concept of perceived behavioral control which is an important precondition for behavior change within the theory of reasoned action and the theory of planned behavior (cf. chapter 2.3.3.2). Thus, there is agreement that perceived self-efficacy is an influencing factor for the process of behavioral change, especially in the case of risky sexual behavior (Bandura, 2004). Vaughan et al. (2000) state that if a person’s self-efficacy toward safer sex increases, this person is more likely to adopt safer sex behavior. Hence it is meaningful to include perceived self- efficacy toward safer sex in the present study, as it could influence the effectiveness of the digital entertainment-education game about HIV/AIDS prevention created for the present study. The health belief model (Janz, Champion, & Strecher, 2002) points out another important factor for health-related behavior change in addition to perceived self-efficacy. Here vulnerability, which consists of perceived susceptibility and perceived severity, is a relevant factor for behavior change. This is related to personal risk perception that is an important predictor for health behavioral change as shown within the health action process approach (HAPA; Schwarzer, 1992, 2001, 2008). Risk perception is important at the beginning of the behavioral change process as it influences motivation: Those people who perceive a high personal risk are more likely

204 to change the risky behavior than people who do not perceive any personal risk (Schwarzer & Renner, 1997; Faltermaier, 1994). This can also be expected for the present study: here girls who feel at risk of being infected with HIV should be more likely to change their behavior than girls who do not feel at risk. Therefore it makes sense to include personal risk perception as moderator variable in the current study (cf. chapter 6.4). Another moderator variable that will be included is previous experience with digital game playing as this might have an influence on the degree of involvement during playing. As involvement is expected to influence the effects on knowledge, interest and communication, previous experience with digital game playing could affect the games’ outcomes as well. All dependent, moderator, and mediator variables will be measured with questionnaires (cf. chapters 6.3, 6.4, & 6.5). The independent variable of the present study is playing/not playing the created digital entertainment-education game about HIV/AIDS prevention for adolescent girls (cf. chapter 6.2). The game Supergöre was exclusively developed and created for the present study, with the software GameMaker and following the findings of gender-specific game preferences to meet girls' likes (cf. chapter 3.2.8). The information about HIV/AIDS and condom use that is implemented in the game was taken from two brochures published by the German Federal Center for Health Education (Bundeszentrale für Gesundheitliche Aufklärung, 1996, 2006). The effectiveness of the game will be tested as experiment. Various entertainment-education interventions have been shown to be effective (cf. chapter 2.4), but evaluation methods are often not experimental. As experiments are rare, more experiments should be conducted to yield clearer results about the effectiveness of entertainment-education by controlling confounding variables and taking control groups into account. This would extend the current state of research towards appealing and effective entertainment-education interventions (Singhal & Rogers, 2004), and towards finding out more about factors that can affect such entertainment- education outcomes. For the present study the experimental design will follow the Solomon four-group plan (Walton Braver & Braver, 1988; Solomon, 1949) to strengthen the gain of scientific insight by avoiding unnoticed premeasurement sensitization (cf. chapter 6.9). More details about the methodological procedures are provided in the following chapter about the methods used for the present study.

205 6. Methods

6.1 Deduction of Hypotheses 6.1.1. Hypotheses Concerning Dependent Variables According to the entertainment-education literature, an entertainment-education intervention can have effects on knowledge (Valente et al., 1994; Law & Singhal, 1999; Valente & Bharath, 1999; Soul City, 2001; Piotrow & Fossard, 2004), interest (Vaughan et al., 2000), attitudes (Piotrow et al., 1992; Kim & Maragwanda, 1997; Valente & Bharath, 1999; Piotrow & Fossard, 2004), self-efficacy (Law & Singhal, 1999; Rogers et al., 1999; Papa et al., 2000), interpersonal communication (Valente et al. 1994; Yoder, Hornik, & Chirwa, 1996; Kim & Maragwanda, 1997; Storey, et al., 1999; Vaughan et al., 2000; Sood, 2002), behavioral intention (Vaughan et al., 2000; Soul City, 2001), and behavior (Brown & Cody, 1991; Singhal, Obregon & Rogers, 1994; Piotrow & Fossard, 2004; Sabido, 2004; Poindexter, 2004), but these results were obtained using other media products like soap operas and radio shows with many episodes and characters with whom people could identify. And these interventions have been mostly applied to linear narratives. Therefore these findings cannot transfer automatically to an interactive medium like digital games, because playing a digital game is a completely different situation (Vorderer, 2000; Grodal, 2000; Klimmt, 2001). To affect, for example, self- efficacy or behavior, an entertainment-education program should be a long-term intervention (Singhal & Rogers, 2004) ideally with different characters (good, bad, transitional; see chapter 2.3.3.1 “Bandura’s Social Learning Theory – Social Modeling”) and an engaging story that consists of many episodes (Piotrow & Fossard, 2004). A small digital game like Supergöre that is played only once during participation in the study will not be able to produce all listed effects. Singhal and Rogers (1999) state that “the effects produced by a single-shot message are vastly different from effects produced by repeated persuasive messages” (p. 212). Thus for the present study it does not make sense to create hypotheses for all effects mentioned above. However, as serious games have been shown to be effective in teaching knowledge (cf. chapter 3.2.5.2 about effects of serious games) and as an increase in

206 knowledge is an important pre-condition for behavior change (cf. chapter 2.3.2.1 “Hierarchy-of-Effects Model”; 2.3.2.3 “Steps to Behavior Change”), it would be realistic to suggest that the game could increase knowledge about HIV/AIDS and condom use. The reason is that the information shown during the game has to be evaluated, meaning cognitive performance is more engaging than passive reception (Sood et al., 2004; Wilkin & Fernandes, 2003; Schenk, 2002, Schweiger, 2007; cf. chapter 2.3.4.1 “Elaboration-Likelihood Model of Persuasion (ELM)”). Since sexual issues are of interest to 15-year-old girls (BRAVO, , 2006) and the game, in all likelihood, includes information about HIV/AIDS and condom use the girls might not know, an increase in interest concerning this topic can be expected. Measuring whether the game increases interest is also useful in order to fulfill the evaluation instructions by Greenberg et al. (2204) as they request to determine if the message stimulated or strengthened interest in the issue presented (cf. chapter 2.2.3 “Challenges”). Follow-up communication about HIV/AIDS and condom use should also increase, because the game is something new and unknown to the participants; they should be more willing to talk about the game and hence about HIV information with their peers. According to Lazarsfeld, Berelson, and Gaudet (1968), interpersonal communication is a pre-condition for behavioral change (Schenk, 2002; cf. chapter 2.3.6.2 about the “Two-Step Flow Model”). In sum increase in knowledge about, interest in, and communication about HIV/AIDS and condom use can be expected as a result of playing the game created for this study. Therefore the hypotheses are as follows: Hypothesis 1: Participants in the treatment groups will reach higher levels of knowledge about HIV/AIDS and condom use than those in the groups without intervention. Hypothesis 2: Participants in the treatment groups will achieve significantly higher levels of interest in HIV/AIDS and condom use than the groups without intervention. Hypothesis 3: Participants in the treatment groups will achieve significantly higher levels of communication about HIV/AIDS and condom use than the groups without intervention.

207 6.1.2 Hypotheses Concerning Moderator/Mediator Variables Involvement and personal risk perception might function as moderator/mediator variables (Choi et al., 2006; Bae & Lee, 2004; Sood, 2002; Brown, 1990; Renner, 2003a, 2003b). As Sood (2002) states, involvement can serve as a mediator variable for entertainment-education effects and he argues that “audience involvement is a key factor in the effectiveness of entertainment education interventions” (p. 154). However as involvement within an entertainment-education intervention is a “complex process” (Sood, 2002, p. 155) he asks for more research to clarify this issue. In the case that involvement during reception is a key issue of entertainment- education intervention effectiveness, it should also influence effects on participants in the current study: To the extent that participants like the game, involvement while playing should influence the increase of knowledge, interest, and communication positively. Thus the following can be assumed: Hypothesis 4: The more participants are involved in playing the digital game, the more will the participants know about HIV/AIDS and condom use after playing the game and the higher will be the levels of interest in and communication about HIV/AIDS and condom use.

As recent theories and intervention approaches to health-behavioral change indicate – for example the health action process approach – awareness of being at risk is an essential precondition for health-related behavioral changes (e.g. Schwarzer, 1996; Renner & Schwarzer, 2003; cf. chapter 2.3.3.4 “The Health Action Process Approach (HAPA)“). Vaughan et al. (2000) identified self-perception of risk of contracting HIV/AIDS as an intervening variable on knowledge about HIV/AIDS, attitudes towards HIV/AIDS and adoption of prevention methods. Hence, in this study, it can be assumed that personal risk perception could also moderate the effects on knowledge, interest, and communication. It can be supposed that the more persons feel at risk, the more they are willing to reduce risk behavior. As people pass through various stages before behavioral change occurs, the willingness to change should also be visible at preliminary stages, i.e. in terms of increase in knowledge, interest, or communication about a certain topic. Concerning the current study, the hypothesis thus is the following: Hypothesis 5: The higher is the personal risk perception before playing the digital game, the more will participants know about HIV/AIDS and condom use and

208 the higher will be levels of interest in and communication about HIV/AIDS and condom use, after playing the game.

6.1.3 Exploratory Questions In addition to the hypotheses, some exploratory questions were included in the present study. The first questions focus more on the game and the dependent variables, while the others are about relationships that might exist between the measured variables. Although it is unlikely that a one-time intervention like the digital game created for this study leads to behavior change (see above) – and thus this study concentrates on knowledge, interest, and follow-up communication – nevertheless “behavioral intention concerning condom use” was measured. Even though it can be assumed that the intervention is too short so as to affect behavioral intention, for completeness’ sake, the first exploratory question concerns the influence of the game over behavioral intention. The same applies to self-efficacy (see above); self-efficacy is assumed to be a requirement for health behavior change (Schwarzer, 2008), thus it would be beneficial to know if the game increases girls’ self-efficacy concerning condom use, as Lee, Salmon and Witte (2005) report that individuals’ perceived self-efficacy is related to HIV/AIDS prevention behavior. And it would be of interest if self-efficacy influences knowledge about, interest in, and communication about HIV/AIDS and condom use. Knowledge about, interest in, and communication about HIV/AIDS and condom use might also be influenced by the previous experience with digital games (moderator variable), because advanced players and those who play less often might have a different level of concentration while playing. This could be because girls with low experience might concentrate more on the gaming procedure itself, whereas girls with digital game experience might concentrate on the topic. But the situation may also be the other way around: Girls with more game experience could be bored by such a small digital game. Therefore the involvement during computer playing might also be affected by previous experience with digital games. Of course, age and education may also affect knowledge about, interest in, and communication about HIV/AIDS and condom use as a result of playing the digital game. The older the girls, the more sexual experience and knowledge they might have. Also different types of schools have different curricula which might lead to

209 different levels of knowledge about, interest in, and communication about HIV/AIDS and condom use. The following exploratory questions are not directly related to the digital game and its effects, but they explore interesting relations between the measured variables. It is possible that girls who deal more often with the topic of HIV/AIDS and condom use (for example if they are dating someone and/or are sexually active) have higher – or depending on their experience, even lower – self-efficacy scores, risk perception, pretest knowledge, or communication scores. For purposes of clarity, all mentioned exploratory questions are listed below:

Exploratory Question 1 Does playing the digital game Supergöre affect behavioral intention concerning condom use?

Exploratory Question 2 Does playing the digital game Supergöre affect girls’ self-efficacy?

Exploratory Question 3 Does self-efficacy mediate the results on knowledge about, interest in, and communication about HIV/AIDS and condom use?

Exploratory Question 4 Does previous experience with digital games moderate the results on knowledge about, interest in, and communication about HIV/AIDS and condom use?

Exploratory Question 5 Is there a relation between previous experience with digital games and involvement while playing the digital game Supergöre?

210 Exploratory Question 6 Does education affect the results on items concerning knowledge about, interest in, and communication about HIV/AIDS and condom use?

Exploratory Question 7 Does age affect the results on knowledge about, interest in, and communication about HIV/AIDS and condom use?

Exploratory Question 8 Is there a relation between self-efficacy and personal risk perception?

Exploratory Question 9 Is there a relation between self-efficacy and communication about HIV/AIDS and condom use?

Exploratory Question 10 Is there a relation between sexual activity and self-efficacy?

Exploratory Question 11 Is there a relation between sexual activity and personal risk perception?

Exploratory Question 12 Is there a relation between self-efficacy and dating someone?

Exploratory Question 13 Is there a relation between personal risk perception and dating someone?

Exploratory Question 14 Is there a relation between knowledge about HIV/AIDS and condom use and sexual activity?

211 6.2 Operationalization of the Independent Variable 6.2.1 HIV/AIDS as Study Topic Entertainment-education is a technique to inform and educate an audience about a topic. Therefore it cannot be studied on its own but only in relation to a specific topic. Entertainment-education products should be consistent with topic and target group (Singhal & Rogers, 2004; Lee, Salmon & Witte, 2005). In case topic and medium are not adequate for the target group, the intervention may prove useless or even produce an adverse effect (for example an Archie Bunker-effect, cf. chapter 2.2.3 about misinterpretation of embedded educational content as challenge). To create a successful intervention, the selected topic should meet the following criteria: 1. Although entertainment-education is often used for social change, the education should be health-related for the game. While social change can only proceed in the long term, increasing knowledge about a health topic, sparking interest in it, and raising communication about it could, by all means, occur in a short time (see above). Thus educating people about a health topic should be possible within a single intervention. 2. Concrete information should be available rather than vague instructions; the information given during the game should be clear and brief. 3. Some aspects of the topic should be widely unknown. Otherwise no learning effects could be measured on account of a ceiling effect. 4. The selected topic should be important to teenage girls. A need should be present and, in case the game succeeds, it should be of practical use even after the study. There is one topic that meets the stated criteria above, namely HIV/AIDS and condom use. It is a health topic, concrete information about how to protect oneself from HIV/AIDS is available and several pieces of information about HIV/AIDS are available that people usually do not know. Furthermore HIV/AIDS is an important issue for teenagers in Germany; younger people especially, who did not witness the AIDS shock in the 1980s, have dangerous gaps in their knowledge and behave carelessly (Kirbach, 2004a,b). Many do not know how infection occurs or how to prevent it (BRAVO, 2006). Until 2001, infection rates in Germany were decreasing but then began to increase again: between 2001 and 2006, the rate of newly diagnosed HIV-infections increased about 80% (Robert-Koch-Institut, 2007).

212 Since then, infection rates were decreasing again in the year 2011, but only by about 1.7% compared to the year 2010 (Robert-Koch-Institut, 2012). HIV/AIDS is not just a problem for gay people, increasingly heterosexual people are especially at risk; in 2006, for the first time since 2001, unprotected heterosexual intercourse was with 17% of all new registered HIV-infections the second largest group of all relevant people (Robert Koch-Institut, 2007). Combined with the decreasing age of first sexual intercourse (BZgA, 2006) and the fact that only 36% of girls reported seeing their school as an information resource about sexual issues (BRAVO, 2006), it is absolutely necessary to develop additional avenues to help prevent HIV/AIDS. As an entertainment-education game about HIV/AIDS does not exist yet, this would be an innovation useful in educating girls on this topic, especially as digital games about HIV/AIDS prevention have shown to be entertaining (cf. chapter 3.2.7 about digital games for HIV/AIDS prevention).

6.2.2 The Game Supergöre – Creating a Digital Entertainment-Education Game about HIV/AIDS for Teenage Girls The core of this study is the self-developed digital game Supergöre that functioned as stimulus in the experimental groups. There was a need to create a new game, because no entertainment-education digital game that provides information exists about HIV/AIDS and condom use. As stated in the chapter about girls and digital games (cf. chapter 3.2.8 “Digital Games and Girls”), several differences exist between girls’ preferences and the majority of digital games available, which tend to be produced for boys (Calvert, Kotler, Murray, Gonzales, Savoye, Hammack, et al., 2001). In sum (Hartmann & Klimmt, 2005; Fritz & Fehr, 1997), girls dislike digital games because of 1. archaic gender role portrayals, 2. violence, 3. lack of social interaction, and 4. competitive elements. Unfortunately these are typical characteristics of many games. Moreover Dittler (1995a,b) pointed out the lack of female heroes and there is a tendency for female figures in games to be sexy victims, assistants to the male hero, or only sexy decoration (Dietz, 1998; Children Now, 2001; Media Report to Women, 2003). Girls’ typical preferences are platform games (48%) and mental skill and puzzle games (20%) (Fromme, 2000). One of the most popular girls games overall is Super Mario (Fritz & Fehr, 1997; Schlüter, 2000). Girls like games that are funny and look like a comic (Böck & Weish, 1997; Schlüter, 2000), where hidden places and

213 objects can be discovered (Lucas & Sherry, 2004) and mysteries can be unraveled. Girls like games with “social interaction,” as teamwork is much more important than competition. Schlüter (2000) writes that girls prefer to play with each other rather than against each other. According to Yee (2002), especially women enjoy the social interactivity of digital games, as it is possible in multiplayer games. Furthermore games should be peaceful (Fritz & Fehr, 1997; Böck & Weish, 1997, Schlüter, 2000) – girls do not like to kill or be killed. They prefer to incapacitate other figures with rather unusual methods like pinching enemies with a beak (Fritz & Fehr, 1997; Schlüter, 2000). The newly created game should comprise those preferences: a funny, comic style platform game similar to Super Mario without violence (in the sense that nobody is killed), sexist gender role stereotypes, or competition. The main character should be a female hero. To meet these criteria the digital game called Supergöre [Super Gal] was developed27. Supergöre is conceptualized as a cute little comic heroine. The background story is that this heroine has to protect different persons/environments from harm. The player leads the figure through various levels, each with a different surrounding. The aim of the game is to obtain as many points as possible with points being gained by collecting specific objects or by making right decisions concerning information given via pop-up windows. Making wrong decisions and touching forbidden figures leads to a deduction in points. The only unfeasible point for inclusion in the game concept was “social interaction,” because it would have been impossible to have virtual people interact within the game or to have more than one player. According to the entertainment-education approach, it had to be taken into account that the aim of the game should not be too obvious (Piotrow & Fossard, 2004); meaning girls should not realize that the main topics are HIV/AIDS and condom use. Thus HIV/AIDS should not be an issue during the entire game. There should be other topics in other levels that the heroine has to deal with so that no suspicions are created as to the purpose of the study. The question then arises, however, which level might be the most adequate for the game’s purpose. The first level would be too obvious, and not every girl might reach

27 This is a word play, because the German pronunciation of “Göre” sounds a bit like “Girl.”

214 the last one; therefore the second level would be the best choice. During the first level, girls can understand and practice playing the game, and every participating girl should reach the second level. The cover story’s main topic is “helping,” because heroes usually help other people and “helping” is a stereotypical activity girls often like to fulfill (Hurrelmann et al., 2006). As stated above, in every level the heroine has to protect someone or something from harm. The background story is that a female superhero helps out in various environments; she has to save a party, protect teenage girls in a camp from HIV, help prevent marine pollution, make sure that evil ghosts leave an old lady’s garden, and stop illegal uprooting in the rain forest (see below for details). By touching particular objects, pop-up windows appear with specific background information. This information has to be evaluated for the purpose of cognitive performance. This is to ensure that the information is not only noticed but cognitively processed (cf. chapter 2.3.4.1 “Elaboration-Likelihood Model of Persuasion (ELM)”). In case the information contains evidence of danger, the player has to “destroy” the dangerous object. Since girls do not like to kill other figures while fighting, another method to incapacitate dangerous objects or characters is needed. Fritz and Fehr (1997) point out that girls prefer humorous ways to do so; therefore a solution might be to throw ice cream at such objects. In case the information shown in the pop-up window is not dangerous, the heroine has the opportunity to give balloons to other figures. Then feedback appears to clarify that the decision made was correct; another pop-up window appears with the title, “That was right,” and applause can be heard. If the player makes a wrong decision, such as throwing ice cream at innocuous objects or giving balloons to dangerous ones, then the feedback window clarifies that the decision was wrong along with a loud warning tone. Right decisions are awarded with points, and wrong decisions are punished with a point detraction. Additionally Supergöre has to collect small objects to earn points, and she must not touch various hazardous moving figures. Since girls dislike game deaths (Fritz & Fehr, 1997), the main character Supergöre is created as an immortal figure although touching these specific objects leads to a restart of the level and a loss of points. This was also done to make sure that all girls do in fact reach the relevant HIV level.

215 Specific sounds are heard throughout the game for occurrences such as the appearance of pop-up windows, throwing ice cream, or the appearance of feedback. For a better understanding, an introduction with explanations on how to play the game was created, and a short introduction explaining the level’s task appeared before each level. If players press the escape button, the game is over (see below for a detailed description of all five levels and screenshots). To translate the digital game idea into practice, appropriate game-making software was needed. Several possibilities were taken into account, but GameMaker, a program created by Mark Overmars28, seemed to be the best choice for creating Supergöre. It is – compared to other methods of creating games – relatively easy to manage, because no programming language is required29. Moreover, the software comes with the timesaving and convenient option to use available graphics (called “sprites” and “gifs”) and sounds downloadable from the Internet. Here follows a description of the different levels:

Level 1 (Discotheque) The first task is to save the mood of a party. Supergöre has to collect CDs with good music and make sure that all awful singers are quiet; otherwise the party cannot go on. Also robots must not be touched or else the level will restart. On this level, the “dangerous” objects are the band (“These guys cannot be stopped!”), the folk music guy (“Folk music in a disco?”), and the Elvis Presley figure (“He is dead, isn’t he?”). Innocuous objects are the Mexican man (“Fortunately he does not sing!”) and Michael Jackson (“Michael Jackson only shakes a leg!”). At the initial level, the player is able to understand the game’s structure before reaching the HIV level.

Level 2 (Camp – HIV and Condom Use) This level is the heart of the game. Here the task is to protect girls in a tent camp from HIV infection. The “viruses” must not be touched and all visible condoms must be collected. Dangerous situations include the following examples: using a condom that

28 Mark Overmars is a Professor at the Institute of Information and Computing Sciences at the University of Utrecht; more information about GameMaker can be found on the website www.gamemaker.nl. 29 As I am neither a professional software designer nor an expert with computers, my next step was to find someone who could help with the technical part. I was very happy that Mikhail Pushkin agreed to work with me, and he was able to manage several problems that came up during the development of the game. I thank him for his reliable and fast work.

216 has been in hot surroundings (“Jenni and Kevin have sex in this car, and the condom used was kept in the glove box during summer”); using a condom past its date of expiration ("Tina and Stefan want to have sex and use a condom past its expiration date”); using a vaginal contraceptive to avoid HIV infection ("Maria wants to protect herself from HIV by using a diaphragm”); using the same condom more than once (“Elli wants to use those condoms more than once”); using two condoms at the same time ("To make it safer, Kathrin and Dennis use two condoms at the same time"); using a condom that has been under pressure ("Ulf and Nina want to use a condom which has been in his wallet for quite a while"); using the morning-after pill to protect against HIV infection ("Jennifer believes the morning-after pill protects her from HIV"); and using a natural gut condom ("Because of an allergy, Erik and Anne use a natural gut condom to protect themselves from HIV").

Figure 16. Screenshot Level 1 (Discotheque)

Innocuous situations include the following examples: kissing ("Jacqueline and Simon are kissing on the bus"); hugging ("Leon and Bianca are kissing and hugging behind this tree"); having sex using a condom ("Petra and Matze have hidden in this tent to

217 have sex using a condom"); and practicing safe sex (“What’s going on here? Pascal and Christina practice safe sex in the tent”). All information was taken from two brochures by the German Federal Center for Health Education that were evaluated positively (BZgA, 2004, 2006; Krahe, Abraham, Scheinberger-Olwig, & Waizenhöfer, 2001). The brochures are called “Ach, Übrigens…” [“Oh, by the way…”] and “Safer sex – sicher!” [“Safe sex – risk less!”].

Figure 17. Screenshot Level 2 (Camp)

218

Figure 18. Screenshot Level 2 – Pop-up window with information

Figure 19. Screenshot Level 2 – Pop-up window with positive feedback.

219 . Figure 20. Screenshot Level 2 –Pop-up window with negative feedback

Level 3 (Underwater World) The third task is to avoid marine pollution. The sharks must not be touched, and the barrels must be collected. Dangerous situations include hidden barrels, illegal pipelines to channel waste into the sea, atomic waste, and other garbage. Safe situations are a hidden treasure, a crawfish waiting for prey, and a Greenpeace activist.

Level 4 (Scary World) Here the task is to help an old lady chase away ghosts from her garden. To accomplish this, brains lying around have to be collected and the ghosts are exorcized by throwing ice cream at them. There is also a spider on the move that must not be touched. Dangerous situations all somehow involve ghosts (e.g., “This owl is a camouflaged ghost” or “A poltergeist has hidden behind this tree”), and safe situations exclude any ghosts (e.g., “This is the old lady’s best friend” or “Somebody should clean here once in a while”).

220

Figure 21. Screenshot Level 3 (Underwater World).

Figure 22. Screenshot Level 4 (Scary world).

221 Level 5 (Jungle World) The superhero’s last task is to stop illegal uprooting of trees. Diggers as well as other tree-cutting conspirers must be stopped and pelted with ice cream. The small animals have to be collected to protect them, except for snakes which must remain untouched. Thus dangerous situations involve destruction of the jungle (e.g., “This digger can chop down hundreds of trees per day” or “The truck takes away the cut-down trees”), while everything that cannot harm the jungle is considered safe (e.g., “This guy could not harm a fly!”).

Figure 23. Screenshot Level 5 (Jungle World)

6.3 Operationalization of the Dependent Variables 6.3.1 Introduction As stated above, it is expected that the entertainment-education digital game Supergöre increases participants’ knowledge about, interest in, and communication about HIV/AIDS and condom use. Therefore these are the dependent variables. Below, all instruments used in the current study are presented, and the reasons for their selection and construction are briefly described. Since the annual study by the German Federal Center for Health Education (cf. Bundeszentrale für

222 Gesundheitliche Aufklärung (BZgA), 2003a) has a good reputation, items from its interview guide were used in the present study whenever possible.

6.3.2 Knowledge about HIV/AIDS No adequate knowledge questionnaire concerning HIV/AIDS and condom use was available, therefore one was developed for this study. Participants’ evaluations of 20 statements about HIV/AIDS and condom use served as the basis for knowledge measurement in this area. Response options to the statements were “That’s right,” “That’s not right,” and “I do not know.” This questionnaire was created so as to refer to the information presented in the HIV level of the digital game, Supergöre (see Chapter “The Game”). As mentioned before, this information was taken from two brochures created by the German Federal Center for Health Education, "Ach, übrigens..." ["Oh, by the way…"] and "Safer Sex...sicher" ["Safer sex… risk less!"]. For additional information about HIV/AIDS and condom use that was not part of the game, questions were also formulated using information from these brochures. The items were presented in a random sequence. The following items contain information that was shown during the game (source in parentheses): - Item 3: “A condom can be used more than once” (inverse) (Ach, übrigens, p. 12). - Item 6: “The Pill does not protect against HIV infection” (Ach, übrigens, p. 20). - Item 7: “Natural gut condoms protect against HIV infection” (inverse) (Safer Sex... sicher, p. 36). - Item 8: “To use two condoms at the same time is much safer” (inverse) (Ach, übrigens, p. 13). - Item 9: “By kissing you can be infected with HIV” (inverse) (Safer Sex...sicher, p. 19). - Item 10: “The morning-after pill protects against HIV infection” (inverse) (Safer Sex...sicher, p. 23). - Item 13: “When correctly performed, safe sex protects against HIV” (Ach, übrigens, p. 40).

223 - Item 14: “Pressure (e.g., from being in a wallet) does not harm condoms” (inverse) (Ach, übrigens, p. 13). - Item 15: “HIV infection may occur even while using a vaginal suppository” (Safer Sex...sicher, p. 23). - Item 18: “Condoms have a date of expiration” (Ach, übrigens, p. 13). - Item 19: “Heat (e.g., from a radiator, blazing sun, glove box) can harm condoms” (Ach, übrigens, p. 13).

These items comprise information about HIV/AIDS and condom use that was not included in the game (source in parentheses): - Item 1: “Condoms protect against HIV infection when used during oral sex” (Ach, übrigens, p. 9). - Item 2: “If a condom's packing is broken, the condom should not be used anymore” (Safer Sex...sicher, p. 33). - Item 4: “Before using a condom, its intactness should be tested by rolling it out” (inverse) (Ach, übrigens, p. 12). - Item 5: “Condoms can be used together with lotion (e.g., Nivea)” (inverse) (Ach, übrigens, p. 13). - Item 11: “Branded condoms have a CE label and a testing number” (Ach, übrigens, p. 13). - Item 12. “You can be infected with HIV by hugging another person” (inverse) (Safer Sex...sicher, p. 19). - Item 16: “During menstruation the risk of being infected with HIV is increased for both partners” (Safer Sex...sicher, p. 38). - Item 17: “Other sexually transmitted diseases (e.g., gonorrhea, syphilis) increase the risk of HIV infection” (Ach, übrigens, p. 4). - Item 20: “Joke condoms (e.g., with animal heads or comic figures) protect against HIV” (inverse) (Safer sex...sicher, p. 34).

6.3.3 Interest in HIV/AIDS and Condom Use An entertainment-education intervention can increase interest in a specific topic (cf. chapter 2.4 “Effects of Entertainment-Education”). “Interest” is an abstract term, and can be defined and operationalized in various ways.

224 In the current study different kinds of interest are measured, namely general interest in HIV/AIDS and condom use as well as concrete interest in specific media products informing about HIV/AIDS and condom use. Therefore different sources for measuring interest were taken into account.

Pretest The first three items refer to 1. general interest in HIV/AIDS, 2. general interest in the ways AIDS transmission occurs, and 3. general interest in condom use. The participants were asked to answer questions about these three kinds of interest on a five-point scale that ranged from 1 (extremely) to 5 (not at all). The first item was taken from a study by Fink (1996), and the second and third items were paraphrased to mirror the first item's style. Item 4 was taken from a study conducted by the German Federal Center for Health Education (BZgA, 2003a). The question of concern is in what ways participants have informed themselves about HIV/AIDS in the past. Thirteen response options were provided (e.g., “Books,” “Brochures about HIV/AIDS,” “Telecast about HIV/AIDS,” “Talking to friends”); girls could also provide their own answers. Item 5 refers to the topics concerning HIV/AIDS participants wanted more information about. Again response options were provided (e.g. “ Safe sex,” “HIV anti-body test,” “Correct condom use”) and the possibility to enter own answers was given. Items 6 to 11 measure interest in obtaining information about HIV/AIDS and condom use via various mediums; the items were self-developed. Participants were asked whether they would like to watch/read/hear on HIV/AIDS or condom use in a given medium on a five-point scale ranging from “I would definitely watch/read/hear it” to “I would in no way want to watch/read/hear it.” Concrete items were, for example, “Imagine there were an article on condom use in your favorite magazine. Would you read it?”, “Imagine you were to run across a web page on the internet on condom use. Would you take a look at it?”, or “Imagine your favorite telecast would broach the issue of HIV. Would you watch it?”

Posttest I The experimental group and Control Group 1 had to fill out the interest questionnaire twice (before and after the game/break) (see section about “The Solomon Four-Group

225 Design” below). For the second measurement, Item 4 was removed since it refers to the past.

Posttest II About one week after the participants came to the laboratories/study room, another questionnaire was sent to them. It consisted of general interest items (Items 1, 2, and 3) and items concerning interest in media products about HIV/AIDS and condom use (Items 6 to 11 of the pretest). These items were chosen since an effect of Supergöre’s intervention might be increased general interest, which could lead to increased interest in specific media products.

6.3.4 Communication about HIV/AIDS Pretest The questionnaire described here is a modified version of the interview guide used for the annual study on HIV/AIDS in Germany by the German Federal Center for Health Education (BZgA, 2003a). It was chosen for its reputation and detailed information. The first item concerns the frequency in which participants talk with friends about HIV/AIDS. Response options are “often,” “sometimes,” “seldom,” “never,” and “I don’t know.” The second item asks participants to note concrete topics talked about with friends. The third item is quite similar to the first one, but this time the question refers to the frequency in which participants talk about HIV/AIDS with people other than their friends. In the next question, participants are asked to note with whom they talk about HIV/AIDS (e.g., mother, sister, doctor). Item 5 then asks for concrete conversational topics. The items listed above do not give any information as to which dialogue partner started to talk about the topic; therefore the next items clarify this direction. Item 6 asks participants whether they ever asked someone for advice concerning HIV/AIDS, and Item 7 asks whether the participants were ever asked for advice. Response options were “yes,” “no,” and “I don’t know.” The last two items were again based on the interview guide from the German Federal Center for Health Education study (BZgA, 2003a): “Do you talk to friends or other people about HIV/AIDS and how infection occurs?” and “Do you talk to friends

226 or other people about condoms and how to use them?” For both questions response options were “often,” “sometimes,” “seldom,” “never,” and “I don’t know.”

Posttest The communication posttest includes three items analogous to items used in the pretest. First, “How often did you talk with friends about HIV/AIDS since the first day you took part in the study?”; second, “How often did you talk with other people besides friends about HIV/AIDS since the first day you took part in the study?”; response options were again “often,” “sometimes,” “seldom,” “never,” and “I don’t know.” The third item asks who began the conversation; here response options are “me,” “dialogue partner,” and “I don’t know.”

6.4 Operationalization of Mediator and Moderator Variables 6.4.1 Involvement Several studies indicate that “involvement” is an important mediator variable for entertainment education effects (Sood, 2002; Brown, 1990). The more involved the recipients are, the higher is the likelihood that the entertainment education product will have an effect (e.g. Lampert, 2003; Sood, 2002). Involvement can generally be defined as “direct personal experience” (Krugman, 1966, p. 583); however as “involvement” is part of various fields of media research and “may be a rather complex process” (Sood, 2002, p. 156), it has been conceptualized in a number of different ways (Gimmler, 2007a,b; Schweiger, 2007; Schenk, 2002; Sood, 2002; Donnerstag, 1996); some conceptualizations rely exclusively on emotions toward media characters and events whereas other conceptualizations also include cognitive aspects like reflection. In this study involvement is conceptualized according to Appel, Koch, Schreier, and Groeben (2002). For developing the involvement questionnaire, four subscales from the Instrument for Accessing Experimental States during Reading (Appel et al., 2002) were adapted for digital game involvement. Each subscale consisted of five items (examples in brackets): - Scale 1: “Focus of attention” (e.g., “I played the game with full concentration”) - Scale 2: “Immersion” (e.g., “While playing the digital game, time flew”)

227 - Scale 4: “Being there” ( e.g. “I felt like being in the digital game world”) - Scale 8: “Pleasure” (e.g., “Playing the digital game was fun”)

Additionally three items from an involvement scale included in a questionnaire by Klimmt (2004a) were added as supplement (Item 3: “I was so riveted by playing the digital game that I was not able to tear myself away”; Item 5: “While playing I was lost in the game”; and Item 6: “I really merged into my part as female hero”). The first two items measure the extent to which participants lose themselves in the game, and the third item measures to what extent girls are convinced of being a heroine. In addition, two self-developed items were included (Item 24: “I would play Supergöre at home”; Item 25: “I would recommend Supergöre to my friends”) to additionally assess aspects of the degree to which participating girls liked the game. Items were rated on a six-point Likert scale ranging from 1 ("strongly disagree") to 6 ("strongly agree"). The sequence of items was random, except for the first item, because it asks participants which game level they reached.

6.4.2 Personal Risk Perception Personal risk perception is included as potential moderator variable in this study. To measure participants’ personal risk perception, items from two studies were used. According to Renner (2003b) – on the basis of Perloff and Fetzer (1986) – participants were asked 1. to rate their own perceived risk perception concerning HIV infection and 2. to rate the risk they assume other girls of their same age and life situation have. The following are concrete items: “How likely is it that you might be infected with HIV through sexual activities within the next ten years?” and “How likely is it that another woman of your age and in a similar life situation might be infected with HIV through sexual activities within the next ten years?” Both items were rated on a seven-point Likert scale ranging from 1 (“extremely unlikely”) to 7 (“extremely likely”). Additionally four items by DeHart and Birkimer (1997) were used loading on their susceptibility factor: “I am at risk for HIV/AIDS,” “There is a possibility that I have HIV/AIDS,” “I may have had sex with someone who was at risk for HIV/AIDS,” and “My sexual experiences do not put me at risk for HIV/AIDS.”

228 Response options were “strongly agree,” “inclined to agree,” “I don’t know,” “inclined to disagree,” and “strongly disagree.”

6.4.3 Experience with Digital Games Former experience playing digital games is also included as a potential moderator variable in the present study. As mentioned in chapter about digital games (3.2.2 “Classification”), there are various ways to categorize and thus to ask for digital game genres. In this study, former experience with digital games is measured by a part of the media use scale that was developed by the Kriminologisches Forschungsinstitut Niedersachsen (KFN) [Criminological Research Institute Lower Saxony] (Baier, Rabold, Lüdders, Pfeiffer, & Windzio, 2006) for children and adolescents. The first question is whether the participating girl habitually plays digital games or not. In case she does, the next items are about different computer hardware and how often these are used for playing. The subsequent questions focus on the time girls spend playing digital games. For this purpose, girls were asked to write down how many minutes/hours they play digital games during weekdays and during weekends. Then subjects were asked to name their three favorite digital games. The last items are about different kinds of digital games (e.g., adventures, first-person shooters) and how often girls play these games.

6.5 Other Measurements 6.5.1 Demographic Information The demographics asked for age, relationship status (“I don’t have a boyfriend,” “I do have a boyfriend, but we don’t live together,” “I live together with my boyfriend,” and “miscellaneous") and level of school education aimed for.

6.5.2 Sexual Behavior To assess girls’ sexual orientation, the following response options were given: “I am heterosexual, meaning that I am attracted to men,” “I am homosexual, meaning that I am attracted to women,” “I am bisexual, meaning that I am attracted to men and women,” and “I don’t know.” To ask about participants’ sexual behavior, again the interview guide from the study conducted by the German Federal Center for Health Education was used (BZgA, 2003a). The second item asked whether girls had already had sexual

229 intercourse or not. In case girls answered “Yes,” they were asked to note down how old they were when they had sexual intercourse for the first time. The next question was about sexual behavior within the last 12 months; if girls answered that they were sexually active during that time, the next question was whether they had more than one partner and if yes, how many during the last 12 months. The last two items (Items 6 & 7) were used in accordance with a study by Jacob, Eirmbter, Hahn, Hennes, and Lettke (1997). These asked whether girls would use condoms at the start of a relationship with an unknown person and at which point, if any, within a new relationship they would abstain from using condoms.

6.5.3 Measurements for Exploratory Purposes 6.5.3.1 Self-Efficacy Perceived self-efficacy was measured in two different ways. The girls were first asked to rate how confident they feel in general about using condoms and whether they think using them is difficult (Plies & Schmidt, 1996); both items were rated on a seven-point Likert scale. Following Bandura (1997) – who argues that measurement of self-efficacy should be as specific to the situation as possible – perceived self- efficacy was secondly measured by asking participants how certain they were that they would insist on using condoms in specific situations. This procedure was used on the basis of the “Health-specific self-efficacy scales” developed by Schwarzer and Renner (2005) and adapted to the topic of condom use (e.g., “I would be able to insist on using a condom even if my partner told me that I was the only woman he knows who ever wanted to use condoms” or “I would be able to insist on using a condom even if my partner ignored my request”). Participants were asked to indicate how confident they would feel about using condoms in certain situations (“definitely not confident,” “probably not confident,” “probably confident,” and “definitely confident”).

6.5.3.2 Behavioral Intention Although an effect of the intervention on behavioral intention is rather unlikely (see above), a short behavioral intention questionnaire was used for the present study. Items were taken from the annual study by the German Federal Center for Health Education (BZgA, 2003a): “If a partner in a new relationship or one-night stand would like to have sex without a condom, would you agree or disagree?”, “Would you

230 agree or disagree if your partner would like to have sex only with a condom?” (response options: “I would agree,” “I would disagree,” and “I don’t know”), and “Would you ask, on your own accord, to use a condom in a new relationship or one- night stand?” (response options: “probably will,” “probably won’t,” and “I don’t know”). The condition, “or one-night stand,” was added to the original phrase.

6.6 Measurements – Overview Table 2 summarizes the measures used for the present study. All questionnaires are provided in original in Appendix C.

Table 2. Overview of measures used for the present study.

Questionnaire Source Dependent Variables

Knowledge about HIV/AIDS & Self-developed items with information from two brochures condom use by the German Federal Center for Health Education (BZgA) called "Ach, übrigens..." [“Oh, by the way…"] and "Safer Sex...sicher" [“Safe sex… risk less”].

Items 3, 6, 7, 8, 9, 10, 13, 14, 15, 18, and 19 contain information that is included in the game.

Items, 1, 2, 4, 5, 11, 12, 16, 17, and 20 contain information that is not part of the game.

Interest in HIV/AIDS & condom Item 1 according to Fink (1996). use Items 2, 3, and 5 to 11 self-developed. Item 4 from BZgA study (BZgA, 2003a).

Communication about pretest HIV/AIDS & condom use Items 1 to 7 from BZgA study (BZgA, 2003a). Items 8 and 9 self-developed.

posttest Self-developed items based on the BZgA interview guide.

Potential Moderator Variables

Personal risk perception Items 1 and 2 taken from a study by Renner (2003b; on the basis of Perloff and Fetzer, 1986). Items 3 to 6 from a study by DeHart & Birkimer (1997).

Experience playing digital games Items taken from a questionnaire by the „Kriminologisches Forschungsinstitut Niedersachsen“ (Baier et al., 2006).

231 Assumed Mediator Variable

Involvement while playing Sub-scales from the Instrument for Accessing Experimental Supergöre States During Reading (Appel et al., 2002) adapted to digital games: Scale 1: “Focus of Attention” Scale 2: “Immersion” Scale 4: “Being there” Scale 8: “Pleasure”. Additional 3 items (Items 3, 5, and 6) included from a questionnaire by Klimmt (2004a). Items 24 and 25 are self-developed.

Miscellaneous

Demographic Information Self-developed

Sexual Orientation/Behavior Item 1 about sexual orientation self-constructed Items 2 to 5 taken from BZgA study (BZgA, 2003a) Items 6 and 7 taken from Jacob et al. (1997)

Self-Efficacy Items 1 and 2 taken from Plies & Schmidt (1996) Item 3 created on the basis of Schwarzer & Renner (2005) and adapted for HIV/AIDS and condom use

Behavioral Intention Items from BZgA study; "one-night-stand" added

6.7 Empirical Hypotheses Based on the above operationalization of all variables, the following empirical hypotheses result:

Hypothesis 1 Girls in the treatment groups who play the digital game Supergöre will reach significantly higher scores on the knowledge posttest questionnaire about HIV/AIDS and condom use than girls in the groups without intervention.

Hypothesis 2 Girls in the treatment groups who play the digital game Supergöre will reach significantly higher scores on the interest in HIV/AIDS and condom use posttest questionnaire than girls in the groups without intervention.

232 Hypothesis 3 Girls in the treatment groups who play the digital game Supergöre will reach significantly higher scores on the follow-up communication about HIV/AIDS and condom use posttest questionnaire than girls in the groups without intervention.

Hypothesis 4 The higher are girls’ scores on the involvement questionnaire, the more questions will girls answer correctly on the knowledge about HIV/AIDS and condom use posttest questionnaire and the higher will be their scores on the interest in and communication about HIV/AIDS and condom use posttest questionnaires.

Hypothesis 5 The higher are the girls’ scores on the personal risk perception questionnaire before playing the digital game Supergöre, the higher will be their scores on the knowledge about HIV/AIDS and condom use posttest questionnaire and the higher will be their scores on the interest in and communication about HIV/AIDS and condom use posttest questionnaires.

6.8 Qualitative Pilot Study To measure the impact of entertainment-education interventions requires developing entertainment-education products for a specific target group. Wilkin and Fernandes (2003) state that: in constructing a successful entertainment education program, the age, gender, and culture of the target group audience must be kept in mind in order, first, to be sure that the target audience is being successfully reached and, second, to avoid offending the audience by presenting material that may be inappropriate or offensive (p. 4). Another reason is that usually persons are more likely to adopt behavior of models that are like themselves, e.g. having the same gender (Lee, Salmon & Witte, 2005). To meet these requirements, Gunter (2005) points out that “message producers must learn as much as they can about the personal characteristics, interests and needs of their target audiences so that they can customize message content to appeal to specific recipients” (p.136).

233 This was done in two steps. First informal talks with teenage girls took place during the whole developmental phase; secondly a qualitative pilot study was conducted as a group discussion with six 15-year-old girls. One goal of the qualitative pilot study was to test the digital game Supergöre especially to ensure that it is an entertainment product, because an entertainment-education intervention needs to attract the audience, otherwise it cannot have effects (Singhal & Rogers, 1999); another was to test the questionnaires within the target group. The qualitative pilot study for the material check took place on Tuesday, 25 April 2006 from 15:00 to 18:00 in the school center, Rockwinkel, in Bremen- Oberneuland. Six girls – two from the “Hauptschule,” two from “Realschule,” and two from “Gymnasium” – participated in the study. They were all 15 years old and in the ninth grade. Their teachers asked for volunteers for a study about girls and digital games some days in advance, and each girl received 20 Euros for her participation. The qualitative pilot study was divided into two parts; during the first part the girls played the game Supergöre for about 30 minutes, and in the second part they filled out the questionnaires. It was explained to the girls that the game and the questionnaires were preproduction models, and for both parts they had instructions to mark or note anything that seemed strange, unclear, or too intimate. Afterwards a focus group took place (the topic guide for the focus group is included in Appendix A). The focus group meeting had a relaxed atmosphere. All girls seemed comfortable and performed their tasks with motivation and precision. The girls reported that they liked the game, and some even expressed enthusiasm during the game. They especially liked the HIV level, calling it the “girl’s level,” and wanted more levels like this. One girl said ”All in all the game is totally awesome.” The two participants from the “Gymnasium” preferred the ghost level but also liked the game in general. In inquiring why they liked the camping level (HIV), the girls responded that it was funny yet they learned something at the same time. When asked what they had learned, two participants said, “We should not use two condoms together simultaneously.” When asked about details they especially liked, the girls answered: 1. “that Supergöre is able to jump that high”; 2. the character Supergöre is “cute”; 3. the camping level (HIV-level); and 4. the style of the game is good. When asked what details could have been improved, they mentioned the following: 1. the protagonist Supergöre could be larger and more visible; 2. sometimes there were too many figures on screen at the same time; 3. more time should be provided for reading the

234 information at the beginning of each level; 4. sharks in the underwater world killed without Supergöre touching them; 5. the music was “cool” but did not vary; and 6. on some levels, the score indicator was hidden. Another question asked what the girls would change if they were able to do so. They would have liked to add more levels (with girls’ topics), the option of two players playing against each other, and the ability to trade in bonus points for new lives. When asked what age they thought would be the ideal target group, they answered, “It’s for us, for girls about 14 or 15 years old.” They went on to explain that 13 and younger would be too young, and 17 and older would be too old for playing the game. The girls added that they would like to have Supergöre as a cell phone game and that they would recommend it to friends, cousins, and sisters. The questionnaires the girls filled out in the qualitative pilot study included a lot of questionnaires about other topics in order to distract from the topic HIV/AIDS. But as some girls mentioned that there was too much material to fill out, and some other girls mentioned that they were not able to concentrate for so long and that they started losing interest after a while, the distraction questionnaires were removed and not used for the following main study. In the sexual behavior questionnaire, some girls reported that they felt a bit uncomfortable in filling them out while others sat next to them, but they mentioned that they would not have a problem with those items if they filled out the questionnaires while alone. To find out whether girls guessed the purpose of the study and the game, they were asked what they thought the study was about. They came up with the following possibilities: 1. a study about sexual behavior of teenage girls, 2. a study on the modern girl’s living conditions, and 3. a chance to learn what is right or wrong and how to learn to make decisions in life. Thus none of the girls guessed that the game was created to educate them about HIV/AIDS and condom use. In the end the girls were asked to give a general comment on the study. All girls said they very much liked the game (“It’s so cool!”) and its purpose, and they said that it was fun to take part in. It can be concluded that the game is adequate for the target group and that the participating girls especially liked the HIV level. Afterwards the technical problems and helpful suggestions that could be solved with the GameMaker software were added or improved in the following ways: 1. A big arrow was included at the beginning of every level that pointed toward the

235 Supergöre figure; 2. the presentation time of the information shown during the game was extended; 3. the sharks in the underwater world level were adjusted; and 4. the score indicator was made visible for all levels. Due to technical limitations, it was not possible to enlarge the Supergöre figure or to trade in bonus points for new lives. To avoid infringing copyright laws, no additional music was used. For the questionnaires the original plan to include HIV topic distractors was abandoned, and it was made certain that during the main study all girls filled out the material in separate rooms.

6.9 Design – The Solomon Four-Group Design To measure change, a design with pre- and posttest groups (before-after design) would typically be used. This design, however, has a disadvantage in that the pretest might sensitize participants to the topic in conscious or unconscious ways (Krause & Stark, 2006). More specifically pretests about HIV/AIDS could sensitize the participating girls to the subject matter through prior knowledge activation (Krause & Stark, 2006; Spires & Donley, 1998; Dochy & Alexander, 1995; Pressley, Wood, Woloshyn, Martin, Kling & Menke, 1992; Schmidt, De Volder, De Grave, Moust & Patel, 1989). This might, for example, result in better knowledge, increasing interest and communication that would lead to a gain in posttest scores even without any treatment. Another design frequently used for studying the effects of an intervention is the posttest-only control group design (after-only design). Although subjects should be randomly assigned to experimental and control groups, there is always a risk that the two groups are significantly different a priori – though this fact would remain undetected because of the missing pretests. For instance, if experimental and control groups differed in interest in or knowledge about HIV/AIDS from the outset (e.g., the experimental group is more informed about HIV/AIDS or more interested in the topic), the conclusion that the game produced these effects would be false. In the 1940s Solomon explored a new experimental design that combines before-after design and after-only design (Solomon, 1949).

236 Table 3. Schema of the Solomon Four-Group Design. Group Pretest Intervention Posttest Experimental Group yes yes yes Control Group 1 yes no yes Control Group 2 no yes yes Control Group 3 no no yes

The experimental group first fills out the pretest and takes part in the intervention and afterwards fills out the posttest. Control Group 1 fills out the pre- and posttests but does not have any intervention in between. Control Group 2 starts with the intervention followed by the posttest, and Control Group 3 fills out the posttest only. This design enables researchers not only to measure the influence of premeasurement sensitization on intervention effects but “to evaluate separately the magnitudes of effects due to treatment, maturation, history” (p. 160, Dimitrov & Rumrill, 2003). The Solomon Four-Group Design is underused for various reasons. An often lamented reason is the lack of appropriate statistical methods for analysis. There is no known single statistical test that incorporates all data of the Solomon Four-Group Design, but Walton Braver and Braver (1988) demonstrate a meta-analytic solution for adequate analysis and present a clearly arranged flowchart that shows all necessary steps for analysis (see Figure 24 below). As the present study will use a Solomon-Four-Group design, these instructions will be followed for data analysis. The analysis procedure starts with an ANOVA including intervention (yes/no) and pretests (yes/no) as fixed factors. If the interaction (Test A) between intervention and pretest is significant, pretest sensitization might be present. Then to clarify whether pretest sensitization is definitely present or not, tests B and C are conducted (see flowchart). In case the interaction between intervention and pretest is not significant (Test A), it can be assumed that pretest sensitization is not present. In this case the following steps are taken to test whether the intervention has an effect or not. The second step is to test the main effect of the intervention (Test D). If it is significant, simple main effects are tested on the pretested groups (Test B) as well as groups without pretests (Test C). In case this result is significant, it can be concluded that the “…intervention has an effect even on unpremeasured groups” (p. 152, Walton Braver

237 & Braver, 1988). If the result is not significant, the conclusion should be that “…intervention does not have an effect unless there is premeasurement” (p. 152, Walton Braver & Braver, 1988). If Test D is significant, it can be concluded that the intervention has an effect – no qualification needed (p. 152, Walton Braver & Braver, 1988). If Test D is not significant, three different tests can be conducted: 1. ANCOVA (Test E), 2. Gain score analysis (Test F), or 3. repeated measures ANOVA (Test G). Of note, all three tests are conducted for the premeasured groups only. According to the literature (Walton Braver & Braver, 1988) Test E is the most preferable of these three. If these tests are significant, it can also be concluded that the intervention had an effect – no qualification needed (p. 152, Walton Braver & Braver, 1988). If the results are not significant, the next step is to perform a t-test on the groups without pretests (Test H). Again if this is significant, it can be concluded that the intervention has an effect – “no qualification needed” (p. 152, Walton Braver & Braver, 1988). In case it is not significant, the results of Test E, F, or G are combined with the results of Test H using Stouffer’s z method for meta-analysis. If this result is significant, again the conclusion can be drawn that the intervention had an effect – no qualification needed (p. 152, Walton Braver & Braver, 1988). If Test I is not significant, it should be concluded that no evidence of the intervention effect is present.

238

Figure 24. Flowchart – Solomon Four-Group Design analysis procedure (Walton Braver & Braver, 1988, p. 152).

6.10 Sample 6.10.1 Recruitment Information Given to Schools, Parents, and (Potential) Participants about the Study Schools were informed that participants were searched for a study by a PhD-student at International University Bremen (now Jacobs University Bremen). It was explained that the study would be about HIV/AIDS prevention. Parents and potential participants were informed that a study about young females and HIV would take place at International University Bremen (now Jacobs University Bremen) and the PhD-student’s home office in Cologne, respectively. The aim of the study was briefly described as finding out what female adolescents nowadays think about the risks of HIV infections (see Appendix C for all letters sent to schools and parents).

Bremen Letters were sent to ten schools in Bremen North with information about the project along with a request for permission to present the project in the schools to 15-year-old girls and to give them information letters and parental agreement forms30. In four schools (Sandwehen, Lerchenstrasse, Gerhard-Rohlfs-Straße, Schulverbund Lesum), the study was presented to girls of the target age in assembly halls. Envelopes with information letters and parental agreement forms were given to interested girls; signed parental agreement forms had to be sent back with the pre- stamped return envelope. Upon receipt the girls were called to make an appointment, and a reminder postcard was sent to them about two days before the appointment. Because fewer schools took part and overall fewer responses were received than expected, a press release was published in several local papers that resulted in some more participants. Fifty-three appointments were made with altogether 50 girls showing up and participating in the Bremen study. As 50 participants would not have been enough subjects, a second recruitment wave took place in another town, Cologne. Although recruiting in two different cities is a disadvantage – because of the risk of confounding – it is better to recruit in two different cities than having not enough participants taking part in the study. In the

30 The schools dealt in different ways with the request; some schools refused directly while some school principals asked for more information and a meeting. In one school the project had to be presented to the parents’ association, and one school immediately invited the researcher to an assembly of the ninth and tenth grades.

240 analysis section (cf. chapter 7.2.2 “Comparison of Subsamples (Bremen/Cologne)”) differences between the two subsamples are checked.

Cologne As mentioned above the second wave of recruitment took place in Cologne. The first step was to contact schools as was done in Bremen. Four schools, within a radius of about five kilometers around the home office where the study took place, were contacted. Unfortunately all of those schools refused cooperation31. Several youth centers and protestant churches with youth groups were then contacted (no catholic churches since condom use is a sensitive issue). In one youth center (Picco-Treff) and in two youth work groups of two protestant parishes (Christuskirche and Pauluskirche), information about the project was presented to teenage girls. To reach more girls, a request for addresses of families with teenage girls was submitted, but city officials refused on the grounds that the topic of the study would not be of public benefit. Finally one employee of a youth center gave permission to send information letters to all 15-year-old girls who were included in their data set (altogether 75 girls), and a local paper published an article about the project with an appeal for teenage girls to participate. In the end 20 appointments were made and 25 girls participated in the Cologne study.

6.10.2 Description of Sample Altogether 75 girls participated in the study (50 girls in Bremen and 25 in Cologne). 17 girls were placed in the experimental group, 18 in Control Group 1, 17 in Control Group 2, and 23 in Control Group 3 (see Table 4; and see Table 5 for the frequencies of girls participating in the experiment and post-tests sent per mail). In Control Group 3 five more participants than scheduled appeared, because they spontaneously showed up with friends. The age of the participating girls ranged from 13 to 18, but most of the participants were at the age of 15 (70.7%) or 14 (21.3%) with a mean age of 14,83 years (SD= .705).

31 This seemed to happen because of the changes schools were undergoing since the new official school guidelines were enacted shortly after the change of government in North-Rhine Westphalia.

241 Table 4. Allocation of sample into the Solomon Four-Group Design Group Frequency Percent Cumulative Percent Experimental Group 17 22.7 22.7 Control Group 1 18 24.0 46.7 Control Group 2 17 22.7 69.3 Control Group 3 23 30.7 100.0 Total 75 100.0

Table 5. Frequencies of girls participating in the experiment and post-tests sent per mail. Group Frequency Frequency Postal Experiment Posttest

Experimental Group 17 12 Control Group 1 18 10 Control Group 2 17 10 Control Group 3 23 19 Total 75 51

Most of the girls (49.3%,) aim at “Realschulabschluss” (junior high school examination); 38.7% want to reach “Abitur” (high school diploma); 9.3% aim at “Hauptschulabschluss” (CSE – Certificate of Secondary Education); and 2.7% go for “Fachabitur” (vocational baccalaureate diploma; see Table 6). Summarized into a dichotomous variable (see “Data Reduction” below), 58.7% do not aim at Abitur, whereas 41.3% do.

242 Table 6. Level of school education participants aimed for. School Frequency Percent Cumulative Percent

Hauptschule 7 9.3 9.3 Realschule 37 49.3 58.7 Fachhochschule 2 2.7 61.3 Abitur 29 38.7 100.0 Total 75 100.0

6.11 Research Procedures The opportunity to take part in the study was presented to girls in different ways. Either they attended a talk about the study at school where information material and parental agreement forms were given to interested girls afterwards or they read about the study it in a newspaper or received a letter about it. In the last two cases girls had to call the researcher to get more information material about the study and the parental agreement forms via mail. Only after parents had signed the letter of agreement, girls were contacted to make an appointment. They were asked to come to the laboratories of the International University Bremen (now Jacobs University Bremen) or to the researcher’s home office in Cologne (see photographs in Appendix B). Upon arrival, participants received general instructions explaining the tasks they would be asked to perform and a brief description of the whole study. The participating girls were then randomly assigned to the groups of the Solomon Four-Group Design. They filled out the questionnaires and played the game alone in the experimental rooms. The experimental group began with pretests followed by playing the game Supergöre for about 20 minutes and then filling out the posttest questionnaires. Control Group 1 also started with the pretests but had a break for about 20 minutes before filling out the posttests. Control Group 2 played the game Supergöre and then filled out the posttests. Control Group 3 filled out the posttests only (see schema below for details). Finally the girls were thanked and given five Euros. About one week later the girls were asked to fill out two more questionnaires that were sent to them via mail (with a pre-stamped return envelope included). Upon returning these questionnaires, H&M vouchers were awarded for participation.

243 Several months later, a letter with key results of the study was sent to all participating girls, their families, and others involved.

Table 7. Study design.

6.12 Ethics and the Present Study As stated in the chapter about the ethical considerations concerning the use of entertainment-education interventions (cf. chapter 2.6) it would be desirable to establish specified procedures to ensure that the persuasive nature of entertainment- education is not abused and that the intervention is beneficial for its recipients. According to Löwisch (1995), responsibility discourses about a specific educational intervention would be a practical solution to provide decision guidance for those in

244 charge. Dialogue partners in such a discourse should include representatives of all persons affected – directly or indirectly – by the intervention. Concerning the present study, those aspects were taken into account during research by informal talks with parents who had daughters in the target age, teenage girls, physicians, an editor of a magazine for and about HIV-positive women, and HIV-positive persons. This is also in accordance with Wang and Singhal (2009) who require that target audience members should be involved in the digital entertainment- education game design from the beginning (cf. chapter 3.2.6). The essence of those talks was that a digital game to educate teenage girls about HIV/AIDS and condom use would be a good cause and beneficial for the participating girls. As all information about HIV/AIDS and condom use in the game is provided as text and not as graphical material – and thus no images with sexual content are presented – it can be assumed that participants will not be harmed by the game’s content. To be on the safe side, parents are informed about the study’s topic in advance as participating girls are underage.

245 7. Data Preparation and Analysis

7.1 Introduction Before data was analyzed, several steps of data preparation were made to either identify possible problems (box plots for detecting outliers, comparison of partial samples to check for consistency, and Cronbach’s Alpha to test for scales’ reliability) or to condense items into factor scores, summing variables or indices for further analyses. Afterwards descriptive statistics were computed before hypotheses and exploratory questions were tested.

7.2 Data Preparation 7.2.1 Box Plots Box plots were constructed for the metric variables that were measured by participants entering values themselves without a given scale. Those variables are “age of first sexual intercourse,” “time spent playing digital games during weekdays,” and “time spent playing digital games during weekends.” Almost no outliers or extreme cases were found; thus the decision was made not to exclude any cases from further analyses (for details, see Appendix E).

7.2.2 Comparison of Subsamples (Bremen/Cologne) Comparisons between the Bremen and Cologne partial samples were conducted. As the independent variable of these tests (Location Bremen/Cologne) is dichotomous, t- tests were conducted in case the dependent variable was metric and Chi-Square tests in case the dependent variable was also nominal. Almost all tests showed no significant differences between the two groups. The only exception was “age of first intercourse”; here the mean for Bremen girls is 13.93 years and for Cologne girls it is 15 years. Twenty one girls in total reported that they already had sexual intercourse (15 girls of the Bremen sample and 6 of the Cologne sample). Reasons contributing to this difference include one Bremen girl reporting that she had her first sexual intercourse at the age of 12 and four other girls reporting this at the age of 13. Fourteen was the youngest age for first sexual intercourse reported in the Cologne partial sample.

246 To have a closer look at the difference, two variables that capture the time span of previous sexual experience were computed32. The first variable calculates how much time went by since a girl had her first sexual intercourse. For that purpose the girls’ age at the first sexual intercourse was subtracted from the current age. All girls who had not yet had sexual intercourse were assigned the value -.01. In calculating the second variable, the difference between the mean age of girls with sexual intercourse experience (14.24) and the current age of girls without sexual intercourse experience was determined. Thus older girls without sexual intercourse experience are assigned lower values. For both variables a Mann–Whitney-U test was conducted, comparing the Bremen and Cologne subsamples. Results show that the Cologne and the Bremen subsamples do not differ significantly with respect to girls’ time span of sexual experience. Therefore it can be assumed that the groups are largely equivalent and as the Cologne and Bremen subsamples do not differ concerning their distribution to the Solomon-Four-Group design, the subsamples will be combined for subsequent analyses in the interest of sufficiently large cell frequencies.

7.3 Reliability Analyses – Cronbach’s Alpha Sufficient reliabilities were found for most of the scales (see Table 8 below), but the personal risk perception scale reveals a reliability score of .605, and the general interest scales reveal reliability scores of 0.652 (pretest) and 0.621 (posttest I), which fall into the “questionable” category according to George and Mallery (2003). As the Solomon-Four-Group Design is calculated mainly with the posttests, the pre-test reliability of interest cannot have much effect on the results. Since the reliability of the second interest posttest is good (see Table 8 below), only this is used in the analyses. As no alternative for personal risk perception exists and the deletion of any item would not improve the reliability, this scale is used in the analyses, although its reliability is questionable. The same applies to the general interest scales of the pre- test and the first post-test as no reason for the questionable result of the reliability analyses could be identified.

32 I want to thank Klaus Boehnke for this idea.

247 For the behavioral intention items, no Cronbach’s Alpha was computed since the level of measurement is not metric. The same applies for the communication posttest.

Table 8. Scores of the reliability analyses. Scale Cronbach’s Category according to Alpha George and Mallery (2003) Involvement (factor scores) 0.940 excellent General interest (pre) 0.652 questionable General interest (post I) 0.621 questionable General interest (post II) 0.829 good Interest in media products (pre) 0.758 acceptable Interest in media products (post I) 0.865 good Interest in media products (post II) 0.789 acceptable Communication (pre) 0.973 excellent Self-efficacy (Items a – i) 0.950 excellent Personal risk perception 0.605 questionable

7.4 Data Reduction To condense raw data, two methods were used, factor analysis and index variable calculations.

7.4.1 Factor Analysis First, an un-rotated factor analysis for all items of the involvement questionnaire was conducted. According to the Kaiser criterion, this produced a strong first factor explaining 43.44% of the variance and five other factors. The loading of the items on the first factor ranged between .318 and .91 (see Appendix E). Because of the strong first factor, another factor analysis was performed with the specification to create one factor only; no items were deleted (for both factor analyses, see Appendix E). The factor scores for all participants were saved and then divided into two groups by median split.

248 7.4.2 Sum Variables and Indices Since such complex concepts like knowledge about HIV/AIDS and condom use or interest in and communication about it cannot be measured with a single item only, several items were included in the questionnaires to measure diverse aspects of these concepts. For data analysis, the items of the questionnaires were combined into index variables. Those are used as dependent and moderator/mediator variables in the statistical tests. For details about how each index was created, see below.

Dependent Variables Knowledge about HIV/AIDS and Condom Use To create an index for knowledge about HIV/AIDS and condom use, for every correct answer one point was given (+1), for every wrong answer one point was detracted (- 1), and for every “I don’t know” no points were given or detracted. For all items that contained information about HIV and condom use presented during the game (Items 3, 6, 7, 8, 9, 10, 13, 14, 15, 18, and 19), this data was added and divided by eleven. This was done separately for the pre- and posttests. The same procedure was conducted for the items that contained information that was not part of the game. Because this index consisted of only nine items (Items 1, 2, 4, 5, 11, 12, 16, 17, and 20), the sum was divided by 9 instead of 11.

Interest in HIV/AIDS and Condom Use The more general Items 1, 2, and 3 were summed up and divided by three; this was done for the pretest and the two posttests (index “general interest in HIV/AIDS and condom use”). In addition the items for interest in media products about HIV/AIDS and condom use (Items 6 to 11) were added and divided by six; the same procedure was carried out for the pretest and the two posttests.

Communication about HIV/AIDS and Condom Use To measure communication about HIV/AIDS and condom use, pretest Items 1 and 3 and posttest Items 1 and 2 were averaged.

Moderator Variables Previous Digital Game Playing Experience

249 First a dichotomous classification into “players” and “non-players,” based on the answers to the question “Do you play digital games?”, was made. To create an index for “digital game playing intensity” as indicator for previous digital game playing experience, first the responses to “Which hardware is used?” and “How often is each type used for digital game playing?” were added into an overall digital game consumption variable that was split into three groups with the values of 1 for “low,” 2 for “middle,” and 3 for “high.” Second, the play time variables for weekdays and weekend were added into an overall game time variable that was split into three groups, again using the values of 1 for “low,” 2 for “middle,” and 3 for “high.” Third, these two new variables were added; hence the digital game playing intensity can range between 0 (non-players) and 6 (heavy players).

Personal Risk Perception An index variable of personal risk perception was computed by summing up the items about participants’ self-assessed risk (Items 3, 4, 5, and 6) and then dividing by four.

Mediator Variable Involvement See above (factor analysis, chapter 7.4.1)

Miscellaneous Variables Demographic Data For “relationship,” a dichotomous variable with the values “Participating girl is not in a relationship” and “Participating girl is in a relationship” was created, because only two participants answered that they were in a relationship with a girl. Thus the data of those two girls and those with a male partner were combined into one variable of “Participating girl is in a relationship.” For educational level, a dichotomous variable was generated with the values “no Abitur goal” and “Abitur goal.” “No Abitur goal” comprises all girls who aim at “Hauptschulabschluss” or “Realschulabschluss” while “Abitur goal” consists of all girls who aim at “Fachabitur” or “Abitur.” A dichotomous variable was created, because most of the girls either aim at “Realschulabschluss” or at “Abitur.” “Hauptschulabschluss” and “Fachabitur” were stated less often (see descriptive statistics).

250 Sexual Behavior An index variable that represents “sexual activity” was calculated by combining the items “I had sex within the last 12 months” and “I had more than one sexual partner within the last 12 months.” Thus the “sexual activity” index variable has the following values: “Participant had more than one sexual partner within the last 12 months,” “Participant had one sexual partner within the last 12 months,” and “Participant was not sexually active within the last 12 months.”

Self-Efficacy about Using Condoms Items 3a to 3i were summed up and divided by nine (for pretest and posttest). Next, a median split was carried out, dividing the participants into two groups with the values “high self-efficacy” and “low self-efficacy.”

Behavioral Intention For pre- and posttests, all items (Items 1, 2, and 3) were summed up and divided by three.

7.5 Results 7.5.1 Descriptive Statistics Sexual Behavior Most of the girls were not in a relationship at the time the study was conducted (62.7%); 37.4% reported that they were in a relationship with a boy and two participants (2.7%) answered that they were in a relationship with a girl. 93.2% described themselves as heterosexual, 4.1% as bisexual, one girl (1.4%) as homosexual, and another (1.4%) as not knowing yet. Over one fourth (28.4%) reported that they already had their first sexual intercourse, most of them at the age of 14 (33.3%) or 15 (33.3%). One girl had her first sexual intercourse at age 12 (4.8%), four girls at age 13 (19.0%), and two (9.5%) at age 16. 39.2% had sex within the last 12 months, and 12 participants (16.2%) reported that they had sex with more than one person within the previous 12 months. Eight girls had sex with two different partners, two girls with three, and one girl with four persons.

251 To the question, “In case you had a sexual relationship with an unknown person, would you always use a condom?”, 74.0% of the participating girls responded “Yes, always” and 6.8% answered “Yes, but sometimes I might forget.” 19.2% replied, “I would never have a sexual relationship with an unknown person.” Asked at which point in a relationship they would stop using condoms even though condoms were used at the beginning, most of the girls answered “When I know more about his sexual past life and trust him” (51.4%). 40.3% would prefer he or she take an HIV test before they would abstain from using condoms; 5.6% selected “After a while” and 2.8% agreed “From the beginning, because I would only have sexual relationships with someone I know very well.”

Digital Game Playing 85.3% of all participants reported that they play digital games. Most of the girls play digital games on a personal computer; every fifth girl plays daily and almost every fourth girl plays every week. 24% never use a game console, while 33.3% use one every month. Even fewer girls use portable game consoles; 44% reported that they never use them while 24.0% use them every month. More popular are games for cellular phones; 24% use them daily, 17.3% at least once a week, and 20% at least once every month. On weekdays the average time spent playing digital games is 99.76 minutes, ranging from 10 to 360 minutes (SD = 75.04). On weekends the girls tend to play more (M = 171.37, min = 10 minutes, max = 540 minutes, SD = 122.49). Concerning different kinds of digital games, girls preferred games requiring (mental) skills (14.7% play them very often, 17.3% often, and 24.0% sometimes) and simulation or strategy games (13.3% play them very often, 18.7% often, and 22.7% sometimes). First-person shooter games (56.0% never play them), adventures (42.7% never play them), and fighting games (46.7% never play them) are not as popular. The most frequently mentioned game was Sims (19.6%) followed by Super Mario (7.2%), Sing Star (6.5%), and Tetris (6.5%) (multiple answers were possible).

Involvement 35.3% of those who played Supergöre stopped playing at the end of the second level (HIV), 50.0% stopped playing at the end of the third level (underwater world), 8.8% stopped playing at the end of the fourth level (ghosts), and 5.9% stopped playing

252 during the last level (jungle). This means that all girls who played the digital game at least played the level with the entertainment-education intervention. Asked if playing Supergöre was fun, 14.7% answered “strongly agree,” 44.1% “agree,” and 23.5% “somewhat agree.” Thus 82.4% rather liked the game. Collapsing the answers “somewhat agree,” “agree,” and “strongly agree”, 57.6% would play Supergöre at home, but only 40.6% would recommend Supergöre to their friends.

Risk Perception Participants overestimate the risk that other girls of the same age and socio-cultural status might be infected with HIV: 18.7% consider it “extremely unlikely” and 26.7% “quite unlikely” that they themselves might become infected with HIV within the next ten years, but only 1.3% think that it is “extremely unlikely” and 9.3% “quite unlikely” that other girls of the same age and socio-cultural status might contract an HIV infection (cf. Figures 25 and 26 below).

Risk that I would be infected with HIV extremely unlikely very unlikely quite unlikely neither quite likely

Figure 25. Risk perception - Item 1.

253 Risk that other girls would be infected with HIV extremely unlikely very unlikely quite unlikely neither quite likely very likely extremely likely

Figure 26. Risk perception - Item 2.

Concerning the other concrete risk perception items, most of the girls reported that they were not at risk for HIV infection (see Table 9 below).

Table 9. Risk perception - Items 3 to 6. Item strongly disagree don’t agree strongly disagree know agree

I am at risk for HIV infection 22.7% 41.3% 22.7% 8.0% 5.3%

It is possible that I am 73.3% 17.3% 6.7% 2.7% 0% infected with HIV

It might be that I had sex 81.3% 9.3% 8.0% 1.3% 0% with someone who is at risk for HIV infection

My sexual experiences 72.0% 16.0% 9.3% 2.7% 0% represent a risk for HIV infection

Self-Efficacy To the question of how likely the girls think it is that they would be able to use condoms, most of the girls (47.3%) answered that they would do so “in all

254 probability.” 21.6% answered “quite likely,” 5.3% “somewhat likely,” and 16.0% “do not know.” 9.5% of participants responded in the negative. Asked how difficult the girls think using a condom is, most of the participants (21.3%) answered “very easy,” 18.7% answered “quite easy,” 18.7% “somewhat easy,” and 16.0% “do not know.” “Somewhat difficult” was chosen by 18.7% of the girls, “quite difficult” by 2.7%, and “very difficult” by 4.0%. For the following items, the participants were asked to estimate how confident they would feel about insisting on a condom in different situations. The scale range consists of “definitely not confident,” “probably not confident,” “probably confident,” and “definitely confident” (see Table 10 below). Most of the participants (76%) feel definitely confident that they would insist on using a condom in case the partner ignored their initial request. Many participating girls (73.3%) feel definitely confident in insisting on condom use even if the partner said that she was “uncool” for insisting on condom use. 60.0% feel definitely confident in insisting on condom use even if their partner ensured them that he or she was HIV negative. 14.7% say that they feel definitely not confident that they would insist on using a condom if the hypothetical partner was allergic to condoms; 12% said they would give in if insisting on condoms would lead to breaking off the sexual intercourse, and 12% would give in if there were no condoms at hand (i.e., if the condoms would have to be bought or borrowed from a roommate).

255 Table 10. Self-efficacy – Results for Items 3a to 3i. How confident do you feel about Definitely Probably Probably Definitely being able to insist on a condom in not not confident confident case… confident confident

…you would be the one initiating 1.3% 17.3% 28% 53.3% talk about HIV and condoms

…my partner tells me that I would be 8% 13.3% 20% 58.7% the only woman he knows who ever wanted to use condoms

…partner was allergic to condoms 14.9% 21.6% 21.6% 41.9%

…this led to an interruption in 8.1% 12.2% 21.6% 58.1% sexual activity

…this led to breaking off sexual 12.2% 13.5% 20.3% 54.1% intercourse

… there were no condoms at hand 12.2% 10.8% 27% 50% (i.e., if the condoms would have to be bought or borrowed from a roommate)

…my partner ensured me that he was 6.8% 8.2% 23.3% 61.6% HIV negative

…my partner ignored my request 10.8% 4.1% 8.1% 77%

…my partner said that I was “uncool” 9.5% 1.4% 14.9% 74.3% because I insisted on condom use

Knowledge about HIV/AIDS and Condom Use (Pre-Test Results) Twenty statements about HIV/AIDS and condom use were presented, and participants were asked to assess them as “true,” “false,” or “I don’t know.” Almost every girl assessed the following items correctly: - A condom should not be used more than once (98.7% gave the correct answer). - You cannot be infected with HIV by hugging someone (96.0% gave the correct answer). - If the package of a condom is broken, it should not be used (94.7% gave the correct answer).

256 - The morning-after pill protects against HIV (93.3% gave the correct answer) - Condoms have a date of expiration (93.3% gave the correct answer).

Concerning the following items, the participants are much less knowledgeable (more than 75% of the girls answered the items incorrectly or selected “I don’t know”): - Natural gut condoms protect against HIV (84% wrong or did not know). - Other sexually transmitted diseases (e.g., syphilis or gonorrhea) increase the risk of being infected with HIV (82.7% wrong or did not know). - During menstruation the risk of being infected with HIV is increased for both partners (78.7% wrong or did not know).

The item most frequently chosen incorrectly (49% answered incorrectly) was “A condom should be tested for impermeability by rolling it out before using” followed by “Pressure (e.g., in a wallet) does not harm the condom” (25.3% answered incorrectly).

Interest in HIV/AIDS and Condom Use (Pre-Test Results) The first three items consisted of general questions concerning interest in HIV, its transmission, and condom use. As Table 11 shows, girls are more interested than uninterested in the topic. In each case more than half of the participating girls selected "extremely" or "very interested."

Table 11. General interest items. Item extremely very neither slightly not at all

General interest in the topic of HIV/AIDS 6.8% 47.3% 43.2% 2.7% 0%

General interest in information about 16% 53.3% 24% 6.7% 0% ways of HIV infection

General interest in topic of condom use 20% 49.3% 21.3% 9.3% 0%

257 For items concerning which resources the girls used for HIV/AIDS information, descriptive results are as follows (multiple responses possible): - School (86.7% used) - Articles in newspapers and magazines (61.3% used) - Leaflets about AIDS (46.7% used) - Talks with friends (44.0% used) - TV program about AIDS (41.3% used) - Doctor (34.7% used) - Talking with family members (34.7% used)

These sources were rarely used for information on HIV/AIDS: - Radio shows about AIDS (96% did not use) - Consulting with organizations (96% did not use) - Local health authorities (97.3% did not use) - Presentations or courses (74.7% did not use) - AIDS television spots (72% did not use) - Books (70.7% did not use)

Asked about HIV/AIDS topics on which participants would like to have more information, the girls gave the following answers (multiple responses possible): - HIV transmission (72%) - Testing for HIV (58.7%) - Treatment options for HIV/AIDS (56.6%) - Correct condom use (53.3%) - Safer sex (41.3%)

The participants mentioned no additional HIV related topics on which they would like to have more information. Various media for information about HIV/AIDS were assessed by the participating girls. They most preferred the “favorite TV program” (M =1.48, SD = .723), followed by “article in favorite magazine” (M =1.44, SD = .793), and a “leaflet” (M =1.12, SD = .915). Less favored were a “presentation” (M = 0.96, SD = 1.0), a “TV program about HIV” (M = 0.89, SD = 1.09), and an “Internet page found by chance” (M = 0.29, SD = 1.15).

258 Communication about HIV/AIDS (Pre-test results) Asked how often the participants talked with friends about HIV/AIDS, most of them answered “sometimes” (41.4%) or “seldom” (34.7%). “Never” was mentioned by 17.3% of the participants, and only two participants (2.7%) responded that they frequently talk about HIV/AIDS with friends. Participants were asked to write down the topics concerning HIV/AIDS that they talk about with friends (multiple responses possible): 32.8% wrote down infection ways, 10.2% course of disease, 8.0% how to prevent HIV/AIDS, 5.8% medical treatment, and 5.1% risk of infection. This result might be influenced by the questionnaire's mentioned examples of “infection ways,” “course of disease,” and “medical treatment.” Asked how often they talk about HIV/AIDS with persons other than their friends (family members, doctors, etc.), 40% of the girls answered that they do so seldom; 33.3% said they do sometimes, 22.7% never, and one person (1.3%) frequently. The participants were asked to write down with whom they talk about HIV/AIDS; most frequently they talk about HIV/AIDS with their mothers (29.5%) followed by friends (11.6%) and best female friend (10.7%). Other family members, sisters (9.8%), and fathers (9.8%), are also among the persons with whom they talk about this topic. Surprisingly “school education” was only mentioned by one participant (0.9%)33. Asked whether the participants ever asked for someone’s advice regarding HIV/AIDS, 68 percent answered “no.”; and 60 percent said that no one had ever asked them for advice.

Behavioral intentions (Pre-Test Results) 81.1% of the participants would not agree if a new partner insisted on only having sexual intercourse without a condom, while 17.6% said they were uncertain on how they would react. Only one girl selected that she would agree (1.4%). The other way around – in case a new partner would like to only have sexual intercourse with a condom – 90.5% would agree to do so, 2.7% do not know yet and 6.8% would not

33 This result contradicts previous results reported above. Possible explanations are that participants were asked to write down with WHOM and not WHERE they talk about HIV/AIDS and condom use, and school is already a response option for the fourth question in the interest questionnaire.

259 agree. 86.5% of the participating girls would suggest using condoms in a new sexual relationship, 10.8% do not know yet, and two girls (2.7%) would suggest not using condoms.

7.5.2 Analysis of the Solomon Four-Group Design 7.5.2.1 Assumption As mentioned above (see chapter 6.9 “Design - The Solomon Four-Group Design” above), no statistical procedure exists for analyzing all four groups of the Solomon Four-Group Design simultaneously. Therefore Walton Braver and Braver (1988) suggest carrying out various statistical procedures with different groups from the design for an extensive analysis. They created a clearly arranged flowchart that provides the sequence of the tests and conclusions that can be drawn according to the tests’ results. Following the procedure suggested by Walton Braver and Braver (1988), the starting point is a 2 x 2 ANOVA with “intervention” (yes/no) and “premeasurement” (yes/no) as fixed factors. Test A refers to the interaction between those two factors. This interaction is important for the entire following procedure, because in case of significance the pretest might have sensitized the girls to the topic; other steps would have to follow to check this possibility. In case the test is not significant, it is rather improbable that the pretest has an effect on the result; hence the following steps focus on the possible effect the intervention might have. The testing of the first three hypotheses and some exploratory questions starts with this 2 x 2 ANOVA. For clarity, a flowchart for each procedure was created that illustrates the steps done for the analyses. To test the hypotheses and to answer the research questions, several statistical procedures are used to analyze the data. These methods have assumptions that should not be violated. For the sake of clarity all assumptions are checked in advance. In addition to general assumptions such as appropriateness of the chosen test or appropriateness of the required level of measurement, the most important assumptions for the chosen tests are listed below: for an ANOVA/ANCOVA: - normal distribution - homogeneity of variance - independence of cases

260 for a t-test: - normal distribution - homogeneity of variance for a Pearson correlation: - interval or dichotomous measurement - normal distribution

Independence of cases in general cannot be tested (see below); normal distribution of scores is tested with the Kolmogorov-Smirnov Test and homogeneity of variance with the Levene Test. In case assumptions are violated, non-parametric methods should be chosen for analyses. However, several authors indicate that the F-test and the t-test yield relatively robust results to violations of the “normalcy” assumption (e.g., Schlittgen, 2003; Ferguson & Takane, 1989), meaning that ANOVAs/ANCOVAs and t-tests can still be used even if the scores are not normally distributed. In the following paragraphs, the assumptions of independence of cases, homogeneity of variance, and normality are checked for the current study.

Independence of Cases Independence of cases is given because of the structure of the Solomon Four-Group Design, as the cases are not correlated or related to one another even though two groups filled out the questionnaires twice (as a pre-test and a post-test). In the analysis of the Solomon-Four group design only the posttests are used and the pretests are in some cases included as covariates. Therefore it is not necessary to use an ANOVA for repeated measurements.

Homogeneity of Variance None of Levene tests that were routinely calculated with each t-test or ANOVA/ANCOVA to test homogeneity of variance were significant; this means that the assumption was met. Only one t-test (see Hypothesis 4, t-test with “knowledge” as dependent variable) does not meet the homogeneity of variance assumption, but SPSS automatically calculates an alternative in the case that equal variances are not assumed. This result will be presented below.

261 Normal Distribution of Scores Normal distribution of scores can be tested with the Kolmogorov-Smirnov Test, and all variables that will be used in the analyses were checked for normal distribution of scores with this test.

These variables meet the assumption of normal distribution of scores:

- knowledge about HIV/AIDS and condom use pre- and post-tests - general interest in HIV/AIDS and condom use post-test - interest in media products about HIV/AIDS and condom use pre- and post-tests - communication about HIV/AIDS and condom use post-test - involvement while playing the game Supergöre

The following variables are not normally distributed (possible explanations for the lack of normal distribution given in parentheses):

- age (the study is for girls at the age of about 15 years and because of this mainly 14- and 15-year-old girls were recruited) - education (as described in the chapter about female adolescents, education is not normally distributed for girls in Germany) - sexual activity (most of the girls (71.6%) report that they have not had sexual intercourse yet, a result also reported in other studies; thus it can be assumed that sexual activity is not normally distributed within the population of 15-year- old girls in Germany) - previous experience with digital games (14.7 percent of the participants do not play digital games at all, this is similar to results of other studies; thus it can be assumed that digital game playing is not normally distributed in the population of 15-year-old girls in Germany.) - risk perception (most of the girls do not feel at risk and, since they do not have sexual relationships, they really are not at risk of being infected with HIV because of unprotected sexual intercourse.) - self-efficacy (girls’ perceived self-efficacy is rather high, which might be a social desirability -effect.)

262 - behavioral intention (most of the girls want to use condoms, which could also be a social desirability-effect) - general interest (participants were quite interested in the topic of HIV/AIDS and condom use. Since the girls knew in advance that the study would be about HIV, it is possible that mainly girls who were already interested in the topic took part in the study.) - communication (most of the girls do not talk about HIV/AIDS and condom use or only sometimes talk about it)

Variables that do not meet the normality assumptions are still used in an ANOVA/ANCOVA or t-test, because as mentioned above violation of this assumption does not have much effect on F-tests and t-tests. If the variable is used for calculating correlations, Spearman’s Rho will be calculated in place of a Pearson correlation.

7.5.2.2 Hypothesis 1 (Knowledge) The first hypothesis stated that playing the game Supergöre will lead to higher scores on the knowledge questionnaire. Figure 27 illustrates all steps that were necessary to test Hypothesis 1. As mentioned above, first the 2 x 2 ANOVA – with knowledge posttest scores as dependent variable and intervention (yes/no) and pretest (yes/no) as fixed factors – was computed. No significant interaction between pretest and treatment was observed (Test A: F(1, 70) = 1.366, p > .05); thus it can be assumed that pretest sensitization does not occur. Therefore the next steps were made to test whether the intervention had an effect. Test D showed no significant main effect for intervention (F(1, 70) = 3.910, p > .05), but this does not mean that the intervention does not have an effect. As the next step, an ANCOVA (Test E: with pretest results as covariate) was calculated for the premeasured groups (experimental group and Control Group 1) only.

263

Figure 27. Process sequence – Hypothesis 1

In Test E the main effect for intervention was also not significant (F(1, 31) = 2.035, p >.05). On that account, an independent-samples t-test was computed (Test H) for participants of the posttest-only groups, Control Group 2 and Control Group 3. The test showed a significant difference in knowledge about HIV/AIDS and condom use between participants with digital game play and those without digital game play (t(38) = 2.149, p < .05); girls who played the game reach higher scores on the knowledge posttest (M = 0.668, SD = 0.265) compared to girls who did not play the game (M = 0.502, SD = 0.224). According to Walton Braver and Braver (1988), the “Intervention has an effect – no qualification needed” (p. 152). For this reason, Hypothesis 1 can be confirmed: the digital game Supergöre increases knowledge about HIV/AIDS and condom use.

7.5.2.3 Concerning Hypothesis 2 (Interest) In Hypothesis 2 it was assumed that participants who played the digital game would show higher interest in HIV/AIDS than participants who did not play the game. Two analyses were conducted, the first one for the general interest sum variable

264 (summarizing Items 1 to 3) and the second one for the sum variable of interest in media products about HIV/AIDS and condom use (summarizing Items 6 to 11) (for details, see section about Data Reduction). The analyses were also done following the instructions by Walton Braver and Braver (1988). Because both analyses required the same calculation procedure, only one flowchart for both analyses is presented here:

General Interest Items The analysis again started with a 2 x 2 ANOVA with “intervention” (yes/no) and “premeasurement” (yes/no) as fixed factors and the general interest posttest scores as dependent variable. No significant interaction of general interest between pretest and intervention was observed (Test A: F(1, 47) = .008, p > .05); hence pretest sensitization can be ruled out. The next step was to check whether the test showed a significant main effect for intervention, but the main effect was not significant (Test D: F(1, 47) = .653, p > .05). Therefore an ANCOVA on the pretested groups (experimental group and Control Group 1) was performed with “intervention” (yes/no) as fixed factor and the general interest pretest scores as covariate, and the general interest posttest scores as dependent variable. Again no significant main effect for intervention was observed (F(1, 19) = .748, p > .05). The next step, according to Walton Braver and Braver (1988), was to perform an independent-samples t-test (Test H) on Control Groups 2 and 3 (the posttest-only groups).

265

Figure 28. Process sequence – Hypothesis 2

Because there were no significant differences between participants who played the game (M = 3.4667, SD =.72350) and those who did not play it (M = 3.6316, SD = .76089; t(27) = -.564, p > .05), the results of Test H and Test E were combined using a meta-analysis procedure (Test I) called Stouffer’s z method. This method allows combining the results of two different statistical techniques, like t-test and ANCOVA. For Stouffer’s z method the p-level is converted to a normal (z) value, “then the resulting single z scores are combined into a single zmeta using the following formula zmeta = Σi zpi / √k” (Walton Braver & Braver, 1988, p. 152). zpi is the z value corresponding to the one-tailed p value of the ith statistical test, and “k” is the number of such tests (2 in this case)34. The p-levels were converted for Test E (p = 0.398 => z = 0.8452) and Test H (p = 0.578 => z = 0.5563); afterwards the meta-analysis was performed:

zmeta = Σi zpi / √k = (0.8452 + 0.5563)/ √2 = 0.991 => p = 0.3217 > .05.

34 The p-levels were converted into z values with the aid of an online transformation tool: http://eswf.uni-koeln.de/glossar/surfstat/normal.htm.

266 The result of the meta-analysis is not significant. There is thus no evidence of an intervention effect, i.e. the game does not increase participants' general interest in the topic.

Interest in Media Products about HIV/AIDS and Condom Use For interest in media products about HIV/AIDS (questionnaire Items 6 to 11; see Section “Operationalization of the Dependent Variables”), the same procedure as for general interest was conducted. Again the procedure started with a 2 x 2 ANOVA with “intervention” (yes/no) and “premeasurement” (yes/no) as fixed factors and this time interest in media products about HIV/AIDS and condom use posttest scores served as dependent variable. No significance of the interaction between intervention and pretest was observed (Test A: F(1, 40)= 0, p > .05); the main effect for intervention was not significant, either (Test D: F(1, 40) = 3.485, p > .05). The next step was to conduct an ANCOVA on the premeasured groups but with "intervention" (yes/no) as fixed factor and interest in media products pretest scores as covariate (Test E). Again the main effect for intervention is not significant (F(1, 19) = .002, p > .05). Because of this lack of significance, an independent-samples t-test was performed for the posttest-only groups (Control Groups 2 and 3). No significant differences between the two groups were found (t(20) = -1.312, p > .05). Finally the meta-analysis using Stouffer’s z method (Test I) was conducted to combine the results of Test E and Test H. First the p-levels were converted (Test E: p = 0.964 => z = 0.04513; Test H: p = 0.204 => z = 1.27); then the meta-analysis was performed:

zmeta = Σi zpi / √k = (0.04513+1.27)/ √2 = 0.030 => p = 0.3524 > .05

Again, the result of the meta-analysis is not significant. Thus no evidence of a treatment effect can be observed (Walton Braver & Braver, 1988); the game does not increase interest in media products about HIV/AIDS and condom use. Hence the digital game Supergöre increased neither participants’ general interest in HIV/AIDS nor their concrete interest in various media about HIV/AIDS. Therefore Hypothesis 2 must be rejected.

267 7.5.2.4 Concerning Hypothesis 3 (Communication) Hypothesis 3 states that girls who played the digital game would talk more often about HIV/AIDS and condom use during the week after the study than girls who did not play the game. Again the procedure is illustrated (see Figure29).

Figure 29. Process sequence – Hypothesis 3

Again, a 2 x 2 ANOVA was conducted with “intervention” (yes/no) and “premeasurement” (yes/no) as fixed factors and follow-up communication scores as dependent variable. No significant interaction between intervention and premeasurement was observed (Test A: F(1, 47) = .652, p > .05). The main effect for intervention (Test D) was not significant either (F(1, 47) = 2.877, p > .05); thus Test E was performed. Here the main effect for intervention was significant (F(1, 18) = 5.935, p < .05). Yet a look at the means shows that the effect is not in the expected direction; those girls who did not play Supergöre achieved higher scores on the communication

268 questionnaire (M = 2.58, SD = .208) than the girls in the intervention group (M =1.882, SD = .198). Therefore Hypothesis 3 cannot be confirmed; girls who played the game do not talk about HIV/AIDS and condom use more often than girls who did not play the game.

7.5.2.5 Concerning Hypothesis 4 (Involvement) Walton Braver and Braver (1988) present a procedure to analyze a Solomon Four- Group Design concerning main effect hypotheses (as was done above). Their procedure does not indicate how to analyze a Solomon Four-Group Design concerning the effects of moderator and/or mediator variables. The usual way would be an ANOVA with the moderator/mediator variables and intervention as fixed factors; the moderator/mediator is assumed to have an effect if the interaction is significant. This procedure cannot be used for “involvement,” because only the experimental group (Group 0) and Control Group 2 had the game intervention and filled out the involvement questionnaire afterwards. Therefore it is not possible to conduct an ANOVA with involvement and intervention (yes/no) as fixed factors. For this reason t-tests were conducted to test for a potential mediator effect of “involvement”. Hypothesis 4 states that the more participants are involved in playing the digital game, the more questions will be answered correctly on the knowledge posttest and the higher the levels of interest and communication. Several t-tests were conducted for the posttest scores of knowledge, general interest and concrete interest in media products about HIV/AIDS, and communication with involvement (high/low; for details about factor scores see Appendix E) as grouping variable. As reported above, the Levene Test for homogeneity of variance is significant for the t-test with “knowledge” as a dependent variable and, therefore the “equal variances not assumed” version of the t-test will be used (see Appendix for details). A significant difference could be found for "general interest" (t(18) = -2,520, p < .05); highly involved participants reported higher general interest (M = 3.8788; SD = .54309) than marginally involved participants (M = 3.1852; SD = .68943). For follow-up communication, a marginally significant difference could be found (t(18) = -1.878, p = .077); marginally involved participants reached lower scores on the communication posttest (M = 1.5556; SD = .72648) than highly

269 involved participants (M = 2.2273; SD = .84746). Thus it can be assumed that highly involved participants tend to talk more often about HIV/AIDS after playing the game Supergöre than marginally involved participants do.

7.5.2.6 Concerning Hypothesis 5 (Risk Perception) Hypothesis 5 states that the higher personal risk perception before playing the digital game, the more questions will be answered correctly on the knowledge posttest and the higher will be levels of interest and communication. To test whether risk perception influences the results of knowledge about, interest in (general interest as well as interest in media products about HIV/AIDS and condom use), and communication about HIV/AIDS, ANOVAs with risk perception scores (high/low) and intervention (yes/no) as fixed factors were conducted for each dependent variable (posttest scores of knowledge, general interest and interest in media products, and communication). For knowledge, interest in media products, and communication no significant interactions between risk perception scores and intervention were observed (all p > .05; see Appendix E). However for “general interest,” a marginally significant interaction between risk perception and intervention was found (F(1, 47) = 3.751 , p = .059). Means show that girls with high risk perception reach higher scores on the general interest scale after playing the game (M = 3.83; SD = .52223) compared to girls with a low risk perception who also played the game (M = 3.10; SD =.78646). The means for girls with high (M = 3.625; SD =.80623) and low risk perceptions (M = 3.718; SD =.82604) who did not play the game Supergöre do not differ to the same extent, but are both higher compared to the mean of girls with low risk perception and intervention. Hypothesis 5 was partially rejected, because in this study risk perception does not influence the results of knowledge, interest in media products, and communication about HIV/AIDS and condom use. Because of the marginally significant result, it can be assumed that general interest in HIV/AIDS and condom use may be influenced by participants’ risk perception.

270 7.5.3 Exploratory Results Exploratory Question 1: Does playing the digital game Supergöre affect behavioral intention concerning condom use? Figure30 shows the procedure for analyzing the first exploratory question. The procedure started with a 2 x 2 ANOVA with behavioral intention posttest scores as dependent variable and intervention (yes/no) and pretest (yes/no) as fixed factors. No significant interaction between pretest and treatment was observed (Test A: F(1, 68) = .005, p > .05); thus it can be assumed that no pretest sensitization exists. The main effect for intervention is not significant either (Test D: F(1, 68) = .059, p > .05); thus Test E, an ANCOVA, is computed for the premeasured groups (experimental group and Control Group 1) with intervention (yes/no) as fixed factor and behavioral intention pretest results as covariate. The main effect for intervention is not significant (Test E: F(1,30) = .173, p > .05). The next step was to conduct an independent-samples t-test (Test H) for participants of the groups without premeasurement (Control Groups 2 and 3). No significant difference in behavioral intention for participants with digital game playing (M = .875, SD = .2396) and without digital game playing (M = .8551, SD = .2986) could be observed (t(37) = .222, p > .05). The last step of the procedure is a meta-analysis (Stouffer’s z-method; Test I) that combines the results of Test E and Test H. The p-levels were converted for Test E (p = .681 => z = .4111) and Test H (p = .826 => z = .2198), and afterwards the meta- analysis (for more details see above) was performed:

zmeta = Σi zpi / √k = (0.411 + 0.2198)/ √2 = 0.31545 => p = 0.7524 > .05

The meta-analytic result is not significant. Thus according to Walton Braver and Braver (1988, p. 152), evidence of treatment effect cannot be observed; the game Supergöre does not increase girls’ behavioral intention concerning HIV/AIDS and condom use.

271

Figure 30. Process sequence – Exploratory questions 1 and 2.

Exploratory Question 2: Does playing the digital game Supergöre affect girls’ self- efficacy? The same procedure as for the first exploratory question was conducted for the second one (see Figure 30). Again the procedure starts with a 2x2 ANOVA including intervention (yes/no) and pretest (yes/no) as fixed factors and self-efficacy posttest scores as dependent variable. The interaction between intervention and premeasurement was not significant (Test A: F(1, 69) = .056, p > .05); the main effect for intervention was also not significant (Test D: F(1, 69) = .034, p > .05). Thus an ANCOVA for the pre-tested groups only was conducted with intervention (yes/no) as fixed factor and self-efficacy pretest scores as covariate. The main effect for intervention remains non-significant (Test E: F(1, 32) = .091, p > .05). For the non-premeasured groups an independent-samples t-test (Test H; homogeneity of variance is not violated) was conducted, but no significant differences

272 in self-efficacy could be observed for participants with intervention (M =3,3333 , SD = .6706) and without intervention (M = 3.236, SD = .749; t(36) = .040, p > .05). Again the last step was to compute a meta-analysis (Test I; Stouffer’s z- method); the p-levels were converted for Test E (p = 0.765 => z = 0.2989) and Test H (p = 0.968 => z = 0.04012). Afterwards the meta-analysis was performed:

zmeta = Σi zpi / √k = (0.2989 + 0.04012)/ √2 = 0.16951 => p = 0.8654 > .05

The meta-analytic result is not significant. Thus, according to Walton Braver and Braver (1988, p. 152), no evidence of treatment effect can be observed; the game Supergöre does not affect girls’ self-efficacy scores.

Exploratory Question 3: Does self-efficacy mediate the results on knowledge about, interest in, and communication about HIV/AIDS and condom use? To test whether self-efficacy influences the results of knowledge about, interest in, and communication about HIV/AIDS and condom use, ANOVAs with self-efficacy pretest scores (high/low) and intervention (yes/no) as fixed factors were conducted for each dependent variable (posttest scores of knowledge, general interest and interest in media products, and communication). For knowledge, general interest, and communication no significant interactions between risk perception scores and intervention were observed (all p > .05; see Appendix E). However, for interest in media products about HIV/AIDS and condom use, a marginally significant interaction between risk perception and intervention can be found (F(1, 38) = 3,682, p = .063). Means show that girls who played the game Supergöre reached higher scores on the interest in media products posttest if their self-efficacy was high (M = .9333; SD = .64884), compared to girls with low self-efficacy who also played the game (M = .2037; SD = .62793). Thus it can be assumed that self-efficacy influences interest in media products about HIV/AIDS and condom use to a certain degree but does not influence knowledge about, communication about, and general interest in HIV/AIDS and condom use.

273 Exploratory Question 4: Does previous experience with digital games moderate the results on knowledge about, interest in, and communication about HIV/AIDS and condom use? To test whether previous experience with digital games influences the results of knowledge about, interest in, and communication about HIV/AIDS and condom use, ANOVAs with game intensity scores (high/low) and intervention (yes/no) as fixed factors were conducted for each dependent variable. For knowledge about, general interest in, and concrete interest in media products about HIV/AIDS, no significant interactions between game intensity scores and intervention were observed (all p > .05; see Appendix E). However, for communication, a significant interaction between game intensity and intervention was found (F(1, 36) = 4.193, p < .05); participants who played the game Supergöre and had only little experience with digital games reached higher scores on the communication posttest (M = 2,1364; SD = .89696) than girls who played the game and had more previous experience with digital games (M = 1,4286 ; SD = ,53452). For girls who did not play the game, no difference is found between girls with low (M = 2.30; SD = ,99642) and high (M = 2.7857; SD = .80917) previous experience with digital games, but both groups reached higher scores on the communication posttest compared to girls who played the game.

Exploratory Question 5: Is there a relation between previous experience with digital games and involvement while playing the digital game, Supergöre? As the assumption of normality was violated for the variable “previous experience with digital games,” Spearman’s Rho was computed instead of a Pearson correlation. The relationship between previous experience playing digital games and involvement while playing the digital game Supergöre was significantly correlated (r = -.418, p < .05). The correlation is negative; the less previous experience the girls had with digital games, the more involved they were while playing Supergöre. Accordingly, the more experience girls had playing digital games, the less involved they were while playing.

274 Exploratory Question 6: Does education affect the results of items on knowledge about, interest in, and communication about HIV/AIDS and condom use? ANCOVAs – with intervention (yes/no) and premeasurement (yes/no) as fixed factors and education as covariate – were computed for knowledge, general interest, interest in media products about HIV/AIDS and condom use, and communication posttest scores as dependent variables. The main effect of intervention for knowledge as dependent variable is only marginally significant (F(1, 69) = 3.824; p = .055). Had it been significant, it could be clearly stated that education does not affect the results. But as it is marginally significant, an additional analysis was conducted to clarify this issue. Therefore the same ANCOVA, but this time with school as a dichotomous variable (aiming at Abitur / not aiming at Abitur), was conducted. Here a significant main effect of intervention was observed (F(1, 69) = 6.265, p < .05). It can be concluded that education does not affect the results, therefore Hypothesis 1 (knowledge) remains confirmed when controlling for participants’ education.

Exploratory Question 7: Does age affect the results on knowledge about, interest in, and communication about HIV/AIDS and condom use? To control for age as an intervening variable, ANCOVAs with intervention (yes/no) and premeasurement (yes/no) as fixed factors and age as covariate were computed for knowledge, general interest, interest in media products about HIV/AIDS and condom use, and communication post-test scores as dependent variables. When controlling for age, main effects of intervention were confirmed for knowledge about HIV/AIDS (F(1, 69) = 4.04, p < .05). For general interest in HIV/AIDS (F(1, 46) = ,878 p > .05), concrete interest in HIV/AIDS (F(1, 39) = 3.629, p > .05), and communication about HIV/AIDS (F(1, 46) = 2.928, p > .05), no significant main effects of intervention could be observed. Thus Hypothesis 1 (knowledge) remains confirmed when controlling for participants’ age.

Exploratory Question 8: Is there a relation between self-efficacy and personal risk perception? A correlation (Spearman’s rho) was computed between self-efficacy and personal risk perception, but was not significant (r = -.229, p >.05). Thus it can be argued that no relation between self-efficacy and personal risk perception exists.

275 Exploratory Question 9: Is there a relation between self-efficacy and communication about HIV/AIDS and condom use? An independent-samples t-test was computed for the pretest communication scores with self-efficacy (high/low) as grouping variable. Significant differences could be observed (t(69) = -3.276, p < .05): Girls with higher self-efficacy scores also reached higher scores on the communication pretest (M = 2.47, SD = .6953) than girls with lower self-efficacy scores (M = 1.93, SD = .6795). Hence it can be concluded that a relationship between self-efficacy and communication about HIV/AIDS and condom use exists: The higher girls self- efficacy concerning condom use, the more they talk about HIV/AIDS and condom use and vice versa: The lower the girls’ self-efficacy, the less they talk about HIV/AIDS and condom use.

Exploratory Question 10: Is there a relation between sexual activity and self-efficacy? Correlation (Spearman’s rho) between sexual activity and self-efficacy was computed, but was not significant (r = -.102, p >.05). Therefore no evidence for a relation between sexual activity and self-efficacy could be found.

Exploratory Question 11: Is there a relation between sexual activity and personal risk perception? The relationship between sexual activity and personal risk perception was significantly correlated (r = .278, p <.05). The more a girl was sexually active, the higher were the personal risk perception scores; and the lower were girls’ sexual activity scores, the lower were their personal risk perception scores.

Exploratory Question 12: Is there a relation between self-efficacy and dating someone? Spearman’s Rho was computed, but the relationship between sexual activity and self- efficacy was not significant (r = -.025, p >.05).

Exploratory Question 13: Is there a relation between personal risk perception and dating someone? Again Spearman’s rho correlation was used. The relationship between dating someone and personal risk perception was significantly correlated (r = .254, p <.05); girls who

276 date someone have higher personal risk perception scores than girls who do not date anyone.

Exploratory Question 14: Is there a relation between sexual activity and pretest knowledge about HIV/AIDS and condom use? Correlations (Spearman’s rho) were computed between sexual activity and knowledge about HIV/AIDS and condom use pretest scores. The correlation was significant (r = .304, p <.05). The higher were the sexual activity scores, the higher were the scores for the pretest knowledge about HIV/AIDS and condom use; the lower were the sexual activity scores, the lower were the scores for the knowledge pretest.

7.5.4 Summary of Results Descriptive results show that most girls are willing to use condoms and feel confident in being accepted by their partner in doing so. The attitudes about the point at which they would stop using condoms, however, are not satisfactory: More than every second girl would stop using condoms once she knows more about the sexual history of her partner and trusts him. Decidedly the best procedure – with 40.3% who would do so – would be for both partners to take an HIV test before they abstain from using condoms. The following are typical responses to the risk perception items: Girls underestimate their personal risk in becoming infected with HIV compared to other girls of the same age and living conditions. Girls’ self-efficacy is rather high, especially if it is measured with more general items. When asked for concrete situations, the level of self-efficacy differs. For example, more girls feel definitely confident in their ability to insist on condom use in case the partner ignores her request as compared to the case of the partner being allergic to condoms. Concerning knowledge about HIV/AIDS and condom use, the most frequently selected wrong items were “A condom should be tested for impermeability by rolling it out before using” and “Pressure (e.g., from being in a wallet) does not harm the condom.” Those two statements are incorrect, and these actions increase the risk of breaking the condom. Girls are rather interested in HIV/AIDS and condom use and want to know more about concrete ways of transmission, testing for HIV, treatment options for HIV/AIDS, and correct condom use and safer sex. Although interest is quite high,

277 communication about HIV/AIDS with friends takes place rather seldom or never. Only two participants reported that they talk frequently about the topic. The game Supergöre increases girls’ knowledge about HIV/AIDS and condom use but not their interest, communication, self-efficacy, or behavioral intention. Age does not affect these results; education as a dichotomous variable (aiming at Abitur / not aiming at Abitur) does not affect the results either. Involvement while playing the digital game affects general interest in HIV/AIDS and condom use; a marginally significant result was found indicating that involvement also affects follow-up communication. It seems that highly involved girls have more interest in and talk more about HIV/AIDS and condom use than marginally involved participants. A marginally significant result was also found for the influence of personal risk perception on general interest in HIV/AIDS and condom use; girls who played the game and who perceived their risk as high are more interested in the topic of HIV/AIDS and condom use after playing the digital game, Supergöre. For the influence of self-efficacy, a marginally significant result was found concerning interest in media products about HIV/AIDS and condom use; girls with high self-efficacy who played the game are more interested in the media products after playing the digital game. Previous experience with digital games affects follow-up communication; the less the previous experience of participants, the more they talked about HIV /AIDS after playing the game Supergöre. A significant negative correlation exists between involvement while playing the digital game and previous experience with digital games; this means that the fewer girls previous experience with digital games, the more they were involved and vice versa. Significant relations are found between self-efficacy and communication pretest scores, sexual activity and risk perception, risk perception and dating someone, and sexual activity and knowledge about HIV/AIDS and condom use.

278

Figure 31. The flowchart visualizes the main findings (including causal and correlational relations, and also marginally found differences) of the present study to illustrate the complexity of the effects. Highlighted in blue are those variables surveyed with pre-tests, the intervention playing the game Supergöre is highlighted in yellow, and variables measured with post-tests are highlighted in green. Colors of arrows are used for better visualization and are irrelevant to content; the same applies for crossing arrows. Please note: This chart is not based on structural equation modeling or similar theories/models.

Figure 31 visualizes the main findings (including causal and correlational relations, and also marginally found differences) of the present study in a flowchart to illustrate the complexity of the effects.

The following list gives a brief overview of the results:

Hypothesis 1 (knowledge): Participants in the treatment groups will have significantly greater knowledge about HIV/AIDS and condom use than those in the groups without intervention. Hypothesis can be confirmed (p < .05); the game Supergöre increases girls’ knowledge about HIV/AIDS and condom use.

Hypothesis 2 (interest): Participants in the treatment groups will achieve significantly higher levels of interest than participants without intervention. Hypothesis cannot be confirmed (p > .05); the game Supergöre does not increase girls’ interest in the topic.

Hypothesis 3 (communication): Participants in the treatment groups will achieve significantly higher levels of communication than participants without intervention. Hypothesis cannot be confirmed (p > .05); the game Supergöre does not increase girls’ communication about HIV/AIDS and condom use

Hypothesis 4 (involvement): The more participants are involved in playing the digital game, the more questions will be answered correctly on the knowledge posttest and the higher will be the levels of interest and communication. This hypothesis can be confirmed for general interest (p < .05) but not for knowledge and interest in media products (all p > .05). For communication, a marginally significant difference can be found (p = .077).

280 Hypothesis 5 (risk perception): The higher personal risk perception before playing the digital game, the more will questions be answered correctly on the knowledge posttest and the higher the levels of interest and communication. This hypothesis cannot be confirmed (p > .05) for knowledge about, interest in media products, and communication about HIV/AIDS and condom use. For general interest, a marginally significant difference was found (p = .059).

Exploratory Question 1: Does playing the digital game Supergöre affect behavioral intention concerning condom use? No effect on behavioral intention could be observed (p > .05); the game Supergöre does not affect girls’ behavioral intention.

Exploratory Question 2: Does playing the digital game Supergöre affect girls’ self- efficacy? No effect on self-efficacy could be observed (p > .05); the game Supergöre does not affect girls’ self-efficacy concerning condom use.

Exploratory Question 3: Does self-efficacy mediate the results on knowledge about, interest in, and communication about HIV/AIDS and condom use? Self-efficacy does not mediate the results on knowledge about, general interest in, and communication about HIV/AIDS and condom use (p > .05). For interest in media products about HIV/AIDS and condom use a marginally significant result was found; the higher girls’ perceived self-efficacy, the more they are interested in media products about the topic of HIV/AIDS after playing the game (p = .063).

Exploratory Question 4: Does previous experience with digital games moderate the results on knowledge about, interest in, and communication about HIV/AIDS and condom use? Previous experience with digital games does not moderate the results on knowledge, general interest, and interest in media products, (all p > .05). However previous experience with digital games influences follow-up communication (p < .05); the less

281 previous experience girls have with digital games, the more they talk about HIV/AIDS and condom use after playing the game, Supergöre.

Exploratory Question 5: Is there a relation between previous experience with digital games and involvement while playing the digital game, Supergöre? Yes, there is a significant relationship between previous experience with digital games and involvement while playing the digital game, Supergöre. The less previous experience girls had with digital games, the more involved they were while playing Supergöre; the more experience girls had with playing digital games, the less involved they were while playing (p < .01).

Exploratory Question 6: Does education affect the results on items for knowledge about, interest in, and communication about HIV/AIDS and condom use? With knowledge as a dependent variable and education as a covariate in an ANCOVA, the main effect of intervention is only marginally significant (p = .055). A second ANCOVA was computed with education as a dichotomous variable (aiming at Abitur / not aiming at Abitur); here the result was still significant (p < .05). Thus it can be concluded that education does not affect the results on knowledge about, interest in, and communication about HIV/AIDS and condom use.

Exploratory Question 7: Does age affect the results on knowledge about, interest in, and communication about HIV/AIDS and condom use? No, age does not influence the results (all p > .05).

Exploratory Question 8: Is there a relation between self-efficacy and personal risk perception? No relation between self-efficacy and personal risk perception could be found (p > .05).

282 Exploratory Question 9: Is there a relation between self-efficacy and communication about HIV/AIDS and condom use? Yes, girls with higher self-efficacy scores also achieve higher scores on the communication pretest than girls with lower self-efficacy scores (p < .05).

Exploratory Question 10: Is there a relation between sexual activity and self-efficacy? No relationship between sexual activity and self-efficacy could be found (p > .05).

Exploratory question 11: Is there a relation between sexual activity and personal risk perception? Yes, the more a girl was sexually active, the higher her personal risk perception scores; the lower the sexual activity scores, the lower were the personal risk perception scores (p < .01).

Exploratory Question 12: Is there a relation between self-efficacy and dating someone? No significant relation between self-efficacy and dating someone can be found.

Exploratory Question 13: Is there a relation between personal risk perception and dating someone? Yes, girls who have experience dating someone have higher personal risk perception scores than girls without dating experience (p < .05).

Exploratory Question 14: Is there a relation between knowledge about HIV/AIDS and condom use and sexual activity? Yes, the higher the sexual activity scores, the higher were the scores for the pretest on knowledge about HIV/AIDS and condom use; the lower the sexual activity scores, the lower were the scores on the knowledge pretest (p < .05).

283 8. Discussion and Conclusions

8.1 Discussion of Supergöre and the Results of the Present Study So far, the results of the present dissertation have been presented and summarized; in the following subsection they are discussed in their context. This discussion is followed by a presentation of limitations of the present study, future research directions and indications for practice before, finally, conclusions are drawn. Results indicate that the game Supergöre led to increases in knowledge about HIV/AIDS and condom use, but not in interest in HIV/AIDS and condom use and follow- up communication about the topic; involvement increased general interest in HIV/AIDS and follow-up communication, but not knowledge and interest in media products; perception of one’s individual risk influenced general interest, but not knowledge about or interest in media products about HIV/AIDS and condom use, and follow-up communication. Exploratory findings provide additional information about the effectiveness of the digital entertainment-education game Supergöre.

8.1.1 The Game Supergöre In the qualitative pilot study girls reported that they liked the game Supergöre; they said that it was “cool”, “funny”, and “awesome” (cf. chapter 6.8). And most of them especially liked the level about HIV protection, because it met their interests and they learned something important. In the main study, over 80% of the participating girls rather liked the game, more than every second girl said she would play Supergöre at home, and about 40% would recommend the game Supergöre to their friends (cf. chapter 7.5.1 for descriptive statistics). Thus it can be concluded that the girls liked playing the game Supergöre, which is an important requirement of an entertainment-education intervention. According to the uses-and-gratifications theory (cf. chapter 2.3.6.1) Supergöre provides game elements that meet girls’ interests and offer them opportunities to satisfy their needs. This was especially visible in the pilot study: some girls wanted to have more

284 levels like the HIV-level, they called it “the girls’ level”, and were enthusiastic about the game. Therefore it can be concluded that the game Supergöre succeeded in being target group specific. Another important point is that none of the girls in the qualitative pilot study guessed that the game was created to educate them about HIV/AIDS and condom use. Thus, the game’s educational aim was not apparent (even though the topic HIV/AIDS and condom use had to be communicated before the main study took place, see below); this is contrary to previous digital entertainment-education games (cf. chapter 3.2.6)

8.1.2 Effects on Dependent Variables Knowledge The findings indicate that the digital entertainment-education game Supergöre increased participants’ knowledge about HIV/AIDS and condom use; thus it can be concluded that the game can be used to inform female adolescents about this topic. When looking at the advantages of serious games – which might also apply to entertainment-education games – multimodality and interactivity were assumed to play a role in increasing knowledge (cf. chapter 3.2.5.4 “Possible Advantages of Serious Games”). As the game Supergöre focuses on interactivity (and not narratives), the observed increase in knowledge provides an indication of the truth of this assumption. This result is in accordance with findings by Cameron and Dwyer (2005) who found that players’ knowledge performance can be increased if the players get immediate feedback about the correctness of their reactions. Several theories and models assume that knowledge is a precondition for behavior change (cf. chapters 2.3.2 “Models with Steps/Stages”; 2.3.3 “Social Psychological Models”). This is in accordance with Singhal and Rogers (1999) who implemented a hierarchy-of-media-effects-model they refer to when they present effects of entertainment-education interventions (see chapter 2.3.2.1). In the so-called “knowledge stage”, the first stage of this model, participants are able to remember the embedded information, as participating girls did in the present study. Thus, it can be concluded that Supergöre is successful at leading participants to the first stage of behavior change.

285 Interest A direct influence of playing Supergöre on girls’ interest in the topic HIV/AIDS and condom use could not be found. Because interest was on a high level in the pre-tests (asked for their level of interest, no girl indicated “not at all”, more than half of the girls indicated being “extremely” or “very” interested in the topic), it is possible that a ceiling effect occurred – interest in the topic has been on a high level from the beginning of the study and could not be increased. Another explanation is that moderator variables have to be taken into account when measuring an increase in interest: as a marginally significant increase was found, it is possible that girls’ risk perception has an influence on general interest. The higher the risk perception before playing Supergöre, the higher was the interest in HIV/AIDS and condom use after playing the game. The same goes for involvement. Involvement while playing Supergöre had an influence on general interest in HIV/AIDS and condom use: participants who were highly involved while playing the game Supergöre reported significantly more interest in the topic of HIV/AIDS and condom use after playing the game than marginally involved participants did. This is in accordance with Klimmt (2009), who assumed in his model that enjoyment promotes involvement and motivation to elaborate on game content between exposure situations (cf. Klimmt, 2009; mechanism 13), which could result in general interest in the topic. This is also in line with suggestions by Sood (2002), who mentions that involvement as a key factor for the effectiveness of entertainment- education interventions can function as a mediator variable for entertainment-education effects; he further points out that involvement is a complex process that still needs to be studied. Also, girls’ perceived self-efficacy seems to influence interest, as a marginally significant result was found concerning girls’ interest in media products about HIV/AIDS and condom use. Girls whose self-efficacy scores before playing the game Supergöre were high reported more interest in media products about HIV/AIDS and condom use after playing the game than girls with lower self-efficacy scores. It is possible that girls with higher self-efficacy feel generally more able to actively request condoms and thus are interested in concrete media products to improve their skills.

286 Communication For follow-up communication the findings are contrary to the expected results, meaning that girls who did not play the game talked more about the topic. This result might be an artifact of the return rate (51 out of 75); the result could be different if all participants had sent the follow-up questionnaires back. Another possible explanation is that a Zeigarnik effect (Baumeister & Bushman, 2008) occurred: those girls who did not play the game Supergöre, but who filled out the questionnaires about HIV/AIDS and condom use might have become curious about these questions and wanted to know the right answers. Thus, they might have had the feeling that the tasks (e.g. the questions about HIV/AIDS and condom use they were not able to answer or the ones where they were unsure about their answers) were not completed; this could have been their motivation to talk about the topic. Whereas those girls who played the game received the answers while playing, thus for them, no tasks were left incomplete as no unanswered questions remained. When looking at those participants who did play the game Supergöre, a marginally significant difference could be found for follow-up communication and involvement while playing, in the direction of highly involved participants talking more often about HIV/AIDS and condom use after playing the game than the marginally involved participants. This is a possible explanation for the above mentioned increase of general interest in involved players, because it is be possible that higher interest in a topic is reflected in communication about the topic.

Behavioral Intention Results show that playing the digital game Supergöre does not affect intentions concerning condom use; probably no increase could be measured because intention to use condoms was already on a very high level in the pre-tests.

287 8.1.3 Moderator and Mediator Effects Involvement The present study shows that involvement can moderate effects of interest in HIV/AIDS and condom use to some extent, but concerning interest in media products about HIV/AIDS and condom use, no effect could be found. This could be because the game was about HIV/AIDS and condom use and provided rather general information about the topic, no special media products were mentioned in the game. Involvement did not affect knowledge about HIV/AIDS and condom use, but it did affect general interest in the topic, and involvement seems to affect follow-up communication to some extent as a marginal effect was found for it. Thus, according to the present study, involvement seems to be an important mediator variable in the context of interactive entertainment-education interventions: Interactive game elements seem to be insufficient for producing effects apart from the cognitive level, thus high involvement while playing is required, as it is important for effects on interest and follow-up communication.

Risk Perception Aside from the marginal difference found for general interest mentioned above, participants’ risk perception did not affect the game's effects concerning knowledge about HIV/AIDS and condom use or interest in media products and follow-up communication about HIV/AIDS and condom use. As the descriptive results show, most participants had not had sexual intercourse (71.6%) and are thus not yet at risk. Thus, it may be that the game was unable to affect girls’ actual risk perception. But there is a relation between sexual activity and risk perception: the more frequently a girl was sexually active, the higher her risk perception score; the lower the sexual activity scores, the lower the risk perception scores. This implies that as soon as girls have sexual intercourse, their awareness of being at risk rises. Perceived risk rises for girls who date someone as well; those girls who date someone might also be more likely to be sexually active, even though not necessarily practicing sexual intercourse.

288 Previous Experience with Digital Games There is a relation between previous experience with digital games and involvement while playing: the less previous gaming experience girls had, the more involved they were while playing Supergöre; the more experience girls had with playing digital games, the less involved they were while playing. This might have prevented positive effects like an increase general interest (see below). For those girls who regularly play commercial entertainment games, the game Supergöre might have been too easy and thus too boring to become involved in the game. There is a visible tendency for girls with high digital game experience to be less interested in HIV/AIDS in general after playing the game than before: As mentioned above, previous gaming experience led to low involvement (maybe those girls felt bored) while playing. Low involvement means that information presented in the game was more likely to be processed via the central route of the ELM (see above); within the central path, counterarguing may take place which could lead to reactance and thus a decrease in interest in the topic. For those girls with less previous digital game experience, the gaming level might have been optimal, so that involvement (see above) was high. This may have positively affected their level of interest, as they report higher interest in HIV/AIDS and condom use after playing Supergöre.

Self-Efficacy Supergöre did not affect girls’ self-efficacy concerning the use of condoms. This result is in accordance with Sabido (2004) who assumes that changes in self-efficacy are very complex; furthermore such changes in self-efficacy are usually based on narratives and need long-term interventions (Sabido, 2004), both aspects that were not realized within the present study. Perceived self-efficacy did not mediate the effects of game playing on knowledge about, general interest in, and communication about HIV/AIDS and condom use; for interest in media products see the section about “interest” above. Also, no relation between self-efficacy and risk perception was found, nor between sexual activity and self-efficacy or dating someone. But a relation between self-

289 efficacy and communication about HIV/AIDS and condom use was found: girls with higher levels of self-efficacy talked more about the topic than girls with lower self- efficacy. It is not clear whether self-efficacy leads to communication about HIV/AIDS and condoms or vice versa. Either is possible: feelings of self-efficacy might encourage girls to talk about HIV/AIDS and to request condom use, but talking about the topic with friends, partners, or other people might also increase self-efficacy.

8.1.4 Other Variables Demographics Age does not affect the results on knowledge about, interest in, and communication about HIV/AIDS and condom use, nor does education: this indicates that the game was created for a coherent group concerning age and education, otherwise age and/or education would have been shown to affect the results.

Miscellaneous There is a relation between previous knowledge about HIV/AIDS and condom use and sexual activity: the higher the sexual activity scores, the higher the pretest scores for knowledge about HIV/AIDS and condom use; the lower the sexual activity scores, the lower the scores on the knowledge pretest. This shows that girls seek information about HIV/AIDS and condom use as soon as they are sexually active. School is unlikely to be the main information source, because if it were, there would not have been a relationship between sexual activity and knowledge about HIV/AIDS and condom use as sexually active and inactive girls get the same information at school.

8.1.5 Ethics Statement As stated in the chapter about ethical considerations (cf. chapter 2.6), entertainment- education interventions can be ethically problematic. To ensure that the present study is ethical, informal talks to concerned persons (parents who had daughters in the target age, teenage girls, physicians, an editor of a magazine for and about HIV-positive women, and HIV-positive persons) took place to hear their concerns and suggestions. In summary,

290 dialog partners recommended the present study and appreciated it as beneficial for the participating girls. Thus it can be concluded that the study was in principle ethical. An improvement for further studies would be conducting standardized interviews and/or group discussions when indicated.

8.2 Limitations of the Study 8.2.1 Limitations Concerning Methodology and Design Although the study has some methodological strengths because of the Solomon-four- group design and the combination of qualitative (focus group) and quantitative (questionnaires) methods, there are limitations that need to be acknowledged. First of all, only short-term effects were measured. Although some questionnaires were sent to the participating girls about one week after they had taken part in the study, the main results rely on short-term effects of a single intervention. It was not easy to get a high return rate after about one week, thus it can be assumed that it would have been even more problematic to measure longitudinal effects or to organize repetitions of game playing. Another problematic fact is that the participants knew about the topic HIV/AIDS and condom use before the study took place as they were underage and parents had to be informed about the study and the topic in advance. This was based to the findings of the qualitative pilot study: Originally, the use of distractors was planned, so that HIV/AIDS and condom use would have been one topic amongst others. In that case, parents and participating girls would have been informed about the study’s topic as “girls and their environment”. But as some girls were not able to fill out all the questionnaires because they were not able to concentrate for so long and hence they started losing interest after a while, all distractor questionnaires had to be removed from the study to make sure that the amount of material was practicable for the participating girls. Therefore, only questionnaires about HIV/AIDS and condom use were included in the main study as they were most important; hence the information that the study is mainly about the topic HIV/AIDS and condom use was essential for parents. The question is whether results would have been different had girls not known about the topic in advance (as originally intended); this limits the generalizibility of the results.

291 But the fact that the topic was known beforehand can also provide evidence for the game’s effectiveness: entertainment-education usually works because it is not perceived as educational. This is due to the fact that educational tools often evoke reactance (cf. chapter 4.4). The game Supergöre had effects on the knowledge level, although the topic was announced in advance and hence study participants knew the educational aim of the game. The next limitation concerns the data, as the questionnaires asked for self-reported data that cannot be independently verified, meaning that there is a risk of bias. Especially intimate, personal questions about personality and sexuality, and questions about sensitive issues like HIV/AIDS prevention carry the risk of evoking socially desired response tendencies. Although the instructions made it clear that there were no “right” or “wrong” answers and that the data would be treated anonymously, participants may have given answers they thought they were expected to give, instead of answers that reflect their real opinions. Missing data is another limitation of the present study. Girls were asked to fill out the follow-up communication and the interest questionnaires about one week after they had taken part in the study, and to send them back. 51 girls did so, thus it remains unclear what answers and statements the remaining 24 girls would have given and whether their answers would have changed the results. Yet another aspect concerning the data has to be mentioned: For three scales, the reliability scores were somewhat questionable. No plausible explanations for these scores could be identified. The scales with questionable scores are the personal risk perception scale as well as the “pre-test” and “post-test I” of the general interest in HIV/AIDS and condom use scale. This could be one explanation why no expected increases in interest in the topic were observed. Besides data and questionnaires, the sample size also needs to be mentioned as a limitation of the study. Although many schools were contacted in two towns (Bremen and Cologne), hundreds of girls and their parents were informed about the opportunity to take part in the study, and articles in newspapers were published asking for girls participating in the study, 75 girls took part in the study. Aside from sample size being relevant for statistical testing, it is also debatable whether those 75 girls represent typical female

292 adolescents in Germany or whether they are a selective group that differs – at least concerning motivation – from girls who did not volunteer to take part in the study. Concerning game design, budget constraints posed a limitation of the present study. Budget limits made it impractical to produce a commercial-quality digital game. Although the game Supergöre was rated as entertaining in the focus group, the design was not realized with professionals and thus the game design was rather simple; it was obvious to the participating girls that the game Supergöre is not a commercial digital entertainment game. Digital game development is a rapidly growing field with numerous innovations coming on the market every year. For example, during the present study smartphones became very popular and digital games that are played with a touch screen on smartphones became common. Research can hardly keep up with such rapid developments. To sum up, the present study is limited concerning methodical reasons like measuring short-term effects, the need to inform participants about the topic in advance because it was not possible to use distractors, self-reported and missing data, as well as questionable reliability scores of three scales, and limited sample size. Concerning game design, the budget limitations and the impossibility of research to keep up with digital game development need to be mentioned. These limitations point to the need for further research (see chapter 8.3 below).

8.2.2 Checking Required Procedures for Evaluating Entertainment-Education Interventions Greenberg et al. (2004) specified certain procedures in order to properly evaluate an entertainment-education intervention (cf. chapter 2.2.3 about entertainment-education's challenges). Whether the present study fulfills those requirements is discussed next. a) Determine if the specific information in the message is salient enough to be recalled with or without prompting Girls participating in the focus group mentioned that they learned from playing the game Supergöre and referred to information about HIV/AIDS and condom use embedded in the game. Thus, it can be concluded that this requirement is met.

293 b) Determine if the issue related to the specific information has a high priority for persons As HIV/AIDS and condom use is part of sex education and sexuality, as finding one's sexual role is a developmental task of adolescents (cf. chapter 4.2.2 “Psychological Changes”), and as the girls in the focus group especially liked the HIV-level and called it “the girls’ level”, it can be assumed that this requirement is fulfilled. c) Assess the credibility of the information received The information about HIV/AIDS and condom use was taken from educational brochures from the German Federal Center for Health Education and is thus credible. d) Assess the credibility of the information resource The German Federal Center for Health Education is a trustworthy information source concerning any kind of health topic, because it is financed with public funds and therefore independent from companies and other institutes. e) Find out if the viewer is better informed than prior to exposure Results have shown that playing the digital game Supergöre led to an increase of knowledge about HIV/AIDS and condom use. f) Determine if the message stimulated or strengthened interest in the issue presented General interest in the topic was strengthened only for those girls who were highly involved in the game; thus this requirement is not fully met. g) Evaluate any possible change in attitude toward the issue No change in intention to use condoms was measured. This may be due to the high level of intention in the pre-tests; girls already intended to prevent HIV-infection by using condoms before they participated in the study.

294 h) Determine if any subsequent behavior occurred as a result of the message Behavior change was not measured in the present study for two reasons: firstly, most of the girls were not sexually active yet, thus no behavior change in terms of using condoms could have occurred; secondly, it was not expected that a single entertainment-education intervention would be strong enough to evoke a behavior change. In order to promote behavior change, further research has to be done.

To sum up, the present study met most of the requirements suggested by Greenberg et al. (2004).

8.3 Future Research Directions and Indications for Practice The present study is a piece of the puzzle in the research field of digital games as entertainment-education interventions. It explored whether interactive entertainment- education games can be used successfully for educating girls about HIV/AIDS and condom use. Results indicate that this is possible to some extent: The entertainment- education game Supergöre can inform participants about HIV/AIDS and condom use, and it can increase interest in the topic if involvement while playing is high. Involvement depends on previous game experience, as girls who were not used to playing games were more highly involved in playing the game Supergöre than girls who were used to playing digital entertainment games. Interestingly, girls who did not play the game Supergöre talked more about the topics HIV/AIDS and condom use than girls who did play the game. Some of the results suggest that players’ characteristics and past experience are crucial for entertainment-education outcomes. In the present study, previous experience with digital gaming, involvement while playing, perceived risk, and self-efficacy towards condom use were identified as factors that can affect the outcome of an entertainment- education intervention. The present results could thus be useful in guiding the selection of variables researched in further studies; it would be interesting to further explore additional factors in order to learn as much as possible about entertainment-education’s effectiveness. And it would generally be interesting to study what effects digital entertainment-education games with different topics target groups would produce.

295 As stated above regarding the study’s limitations, long-term studies need to be conducted to get more information about the effect duration, and about participants’ patterns of use of the digital entertainment-education game. If a game meets players’ needs, it can be assumed – in accordance with the uses-and-gratifications theory (cf. chapter 2.3.6.1) – that it is played because players want to satisfy their needs, e.g. their needs for entertainment or information, by playing the game. And to learn whether an entertainment-education game would work in the field, it is necessary to find out whether it is played voluntarily by target audience members. This could be studied with an online- study or by distributing the game as smartphone application. In this way, not only self- reported data, but also data about playing time, success of game playing etc. could be collected. As self-reported data carry the risk of bias, it would be beneficial to get additional information that way. As participants of an online study do not have to send questionnaires back via mail and all data could be collected online, it could reduce missing data. And it could improve the sample size as it is easier to fill out questionnaires online at home than to visit a researcher in the lab (nevertheless, online studies also carry some risks and methodological disadvantages that would need to be taken into account). Another limitation was that the participating girls knew about the topic HIV/AIDS and condom use in advance. For future studies, topics should be chosen that are less delicate and that can be kept secret during study process. The dependent variables included in the present study (knowledge, interest, and communication) were assessed with questionnaires. As interest questionnaire reliability scores were questionable and not all communication questionnaires were sent back it would be of interest to know whether different questionnaires would have led to the same results. And it would be interesting to use qualitative data collection techniques (e.g., interviews) in future studies as that might give a deeper insight into the process of behavioral change and could detect outcomes that could not be found by the questionnaires used in this study. As entertainment-education interventions have shown to be effective not only on the individual level, it would be of interest to study what kind of effects a digital entertainment-education game produces on a group level. In the long run, it would be important to know about more about how digital entertainment-education game effects

296 diffuses into a group. Besides adolescents, various other target groups are conceivable. For example, older people can also be target groups for digital entertainment-education games: senior citizens increasingly use games to train their mental activity, to stay connected to other people, and for recreation (Wang & Singhal, 2009). Thus it would be useful to embed information about health topics relevant for this age group in such games. As stated in the chapter about hypotheses concerning dependent variables (cf. chapter 6.1.1), it was not expected that Supergöre would be able to affect players’ self- efficacy, as changes in self-efficacy are very complex, usually based on narratives, and based on long-term interventions (Sabido, 2004). But the main focus was to test whether this game's interactive elements are sufficient for causing effects, therefore only as many narrative elements as necessary to make the game playable were included. It would be interesting to know how Supergöre would need to be designed and created to affect players’ self-efficacy. Thus, future research is needed to explore entertainment-education games that include narrative elements, such as video clips, to study whether it is possible also to increase self-efficacy by playing entertainment-education games. Including narratives in a digital entertainment-education game would provide additional possibilities besides studying effects on self-efficacy. It could possibly raise personal risk perception and foster behavioral change because all outcomes that have been produced with non-interactive, but narrative-based entertainment-education interventions can conceivably be produced with digital games containing engaging narrative elements. But in practice this is up for debate, as some differences between digital games and non-interactive programs can be identified. For example, narrative based entertainment-education TV and radio interventions often end an episode with a cliffhanger to use the Zeigarnik effect. Research is needed that clarifies how a Zeigarnik effect could be used within digital entertainment-education games, as results of the present study indicates that playing the game did not yield any open questions that could produce a Zeigarnik effect that could positively influence the intended effects. One way to reach out to as many members of the target group as possible is to conduct a formative evaluation to identify target audience members’ needs and

297 preferences in advance to produce a custom-tailored entertainment-education product (cf. Gunter, 2005). But it would be interesting to focus also on resistance to entertainment- education, i.e. why entertainment-education does not work for all recipients (Singhal & Rogers, 2002). For example, concerning the effects of Supergöre involvement has shown to be a relevant mediator variable: no effects for marginally involved players could be found. Involvement was depended on previous experience with digital games: the more previous experience the participating girls had, the less they were involved. Thus, it would be interesting to know how the game Supergöre should have been designed to involve players who were used to playing common digital entertainment games. Probably, game design would play a role. The design of Supergöre was limited due to the available budget. To reach out to girls with more experience playing commercial digital entertainment games, a professional game design would be needed. For future research, ways to realize digital entertainment-education games with professional game design need to be found. Under ideal conditions, a digital entertainment-education game could be created that automatically changes design, topics, its course of action, or its degree of difficulty like a computer-tailored program (cf. Jibaja, Kingery, Neff, Smith, Bowmann, & Holcomb, 2000) according to personal information that players provide at the beginning and during the game session. In that case it can be assumed that more players are involved during playing and benefit from the game as the optimal level of requirements could be met for each player. This approach also promises to reduce the problem of media saturation, i.e. the competition of the game with other leisure time activities (Lieberman, 2009). A game that is created for a very specific target group and that adapts to individual players should be appealing to the target audience and it should thus be played by the target audience, assuming they know about the game. For this purpose, it is necessary that games are widely spread, for instance on the internet (Greenberg et al., 2004), to reach their target audience. Future research could focus on marketing strategies for distributing entertainment-education games on platforms like Facebook or as free apps for smartphones. Another way of dealing with the problem of media saturation is including entertainment-education games into the school curriculum. What Shen, Wang and

298 Ritterfeld (2009) assume about serious games could also apply to digital entertainment- education games: the games might be effective if they need not to compete with favorite leisure time activities but with traditional education media at school (Lieberman, 2009). In summary, the present study indicates that digital entertainment-education games – like all entertainment-education interventions – are a very complex field of research and a challenge for practice as many factors concerning target audience, produced entertainment-education medium, environment, and accompanying research need to be taken into account. To not lose track of all researched entertainment-education interventions and their findings, it would be useful to implement a worldwide, cost-free database where all entertainment-education interventions, their preconditions, media used, target group, marketing strategies, whether they compete with leisure time activities or are integrated into a curriculum, the effects found, and especially also those entertainment-education programs that have not shown to be as effective as expected and failed to work (Yoder, Hornik, & Chirwa, 1996) are collected to consolidate theoretical and practical knowledge about entertainment-education to avoid redundant research and ineffective entertainment-education interventions. Yet another aspect should be either part of this database or dealt with in a special committee: ethical considerations of each entertainment-education intervention. When technical capabilities further develop and more and more (digital) entertainment- education interventions can be realized, new ethical questions about topics, target groups, or applications might emerge. Therefore, it would be desirable to implement national or international ethics review committees that control the aims, embedded information, and planned realization of planned entertainment-education interventions in advance in order to have “certified” entertainment-education interventions to avoid misuse of or in the name of entertainment-education.

8.4 Conclusions The game Supergöre focused on interactivity as a key feature of digital games compared to narrativity. This was done because every digital game is interactive, but not necessarily narrative, and because interactivity is the main difference between digital games and the non-interactive mass media used for entertainment-education interventions in the past

299 that have shown to be effective. Also, many famous theories and models used for explaining entertainment-education’s effectiveness (e.g. Bandura’s Social Learning Theory or the Sabido Method) are based on the engaging nature of narratives. The present study tested with the game Supergöre whether interactive entertainment-education interventions without engaging narrative elements can also lead to positive outcomes. In summary, the present study indicates that digital entertainment-education games – although they do not focus on narratives – can be effective in furthering players’ knowledge about a certain topic, which can be seen as one of the first steps towards behavior change (cf. chapter 2.3.2 about models with steps/stages). As described in the chapter about game development (cf. chapter 6.2.2), the evaluation of the information given during the game leads to cognitive processing of the content, which in turn might lead to increases in knowledge. That interactivity can increase knowledge acquisition is also in accordance with findings by Ritterfeld et al. (2009). But those interactive game elements that evoke a cognitive evaluation-process during game play do not directly affect interest in the topic and follow-up communication about HIV/AIDS and condom use. Results indicate that the degree of involvement while playing the game Supergöre influences the effects on interest and communication about the topic: The more players are involved in playing the game the higher are their levels of interest in and communication about HIV/AIDS and condom use afterwards. Hence it can be concluded that involvement is an important mediator variable for interactive entertainment-education interventions. By this conclusion, the theoretical background of the entertainment-education approach is extended: interactive entertainment-education products can have direct effects on the cognitive level, but effects on other levels depend on influencing variables. Intensive evaluation of the target group is necessary to tailor the entertainment- education game as well as possible to the desired target audiences. Future research is needed to clarify various issues like inclusion of other topics and target groups, or the possibility to produce changes in self-efficacy and behavior change as well as long-term effects. Dreams of the future – as part of health campaigns that consist of various media products – are complex digital entertainment-education games that automatically adapt to

300 the individual player and that are produced and widely spread in the Internet, for instance as games on Facebook or as smartphone apps. The central collection of entertainment- education interventions and their effects is important, as is the implementation of a mandatory ethical review committee that reviews every entertainment-education with regard to its ethical correctness to avoid any misuse of entertainment-education interventions and to protect audiences from harm. These would be important steps towards the utopic idea mentioned in the introduction: closing the knowledge gap by simply providing all essential information via mass media, be it TV or digital games.

301 References

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340 Wilkin, H. A., Valente, T. W., Murphy, S. T., Cody, M. J., Huang, G., & Beck, V. (2006). The effects of a telenovela storyline on breast cancer knowledge and behaviors among hispanic/latino audiences. Paper presented at the annual meeting of the International Communication Association, Dresden, Germany. Wines, W. A., & Napier, N. K. (1992). Toward an understanding of cross-cultural ethics: A tentative model. Journal of Business Ethics, 11, 831- 841. Wink, S., & Lindner, K. (2002). Kids und Computerspiele. Eine pädagogische Herausforderung [Kids and computer games. A pedagogical challenge]. Mainz: Logophon Verlag. Winkel, M., Novak, D., & Hopson, H. (1987). Personality factors, subject gender and the effects of aggressive video games on aggression in adolescents. Journal of Research in Personality, 21, 211-223. Winterhoff-Spurk, P. (1999). Medienpsychologie. Eine Einführung. [Media Psychology. An Introducation] Stuttgart: Kohlhammer. Witte, C. (2005). Wer hat noch Angst vor AIDS? [Who is still afraid of AIDS?]. NEON, 5. Wong, W. L., Shen, C., Nocera, L., Carriaizo, E., Tang, F., Bugga, S., et al. (2007). Serious video game effectiveness. Paper presented at the ACE '07, Salzburg, Austria. Wouters, P., van der Spek, E., & van Oostendorp, H. (2009). Current practices in serious game research: A review from a learning outcomes perspective. In T. M. Connolly, M. Stansfield & L. Boyle (Eds.), Games-based learning advancements for multisensory human computer interfaces: Techniques and effective practices (pp. 232-250). Hershey, PA: IGI Global. Yahaya, M. K., & Olajide, B. R. (2003). Challenges of entertainment-education. Format utilization for agricultural information dissemation in Nigeria. The Journal of International Communication, 9(1), 127-142. Yaser, Y. (2004). The Turkish family and health planning foundation's entertainment- education campaign. In A. Singhal, M. J. Cody, E. M. Rogers & M. Sabido (Eds.), Entertainment- Education and social change. (pp. 321-330). Mahwah, NJ: Lawrence Erlbaum Associates.

341 Yee, N. (2002). Facets: 5 motivation factors for why people play MMORPG's. Retrieved 16.07.2008, from http://www.nickyee.com/facets/home.html Yoder, P. S., Hornik, R., & Chirwa, B. C. (1996). Evaluating the program effects of a radio drama about AIDS in Zambia. Studies in Family Planning, 27(4), 188-204. Zillmann, D. & Bryant, J. (1994). Entertainment as media effect. In J. Bryant & D. Zillmann (Eds.), Media effects. Advances in theory and research (pp. 437-462). Hillsdale: Erlbaum. Zimmerman, R., Noar, S., Chaisamrej, R., & Thomas, L. (2005). A comparison of five social psychological models of condom use: Implications for designing prevention messages. Paper presented at the International Communication Association, 2005 Annual Meeting,, New York, NY. Zimmerman, R. S., & Vernberg, D. (1994). Models of preventive health behavior: comparison, critique and meta-analysis. In G. Albrecht (Ed.), Advances in Medical Sociology, Health Behavior Models: A Reformulation (Vol. 4, pp. 45-67). Greenwich, CT: JAI Press.

342 Appendix A

– Focus Group Topic Guide – Gruppendiskussion Ziel: Überprüfen ob die Zielgruppe 15-jährige Mädchen mit dem Spiel und dem Untersuchungsmaterial zu Recht kommt.

Teilnehmerinnen: 2 Hauptschülerinnen, 2 Realschülerinnen, 2 Gymnasiastinnen; jeweils 15 Jahre alt

Grober Ablauf: 1. Begrüßung 2. Instruktion (Spiel spielen, Material ausfüllen, auf Probleme achten, entweder aufschreiben (Spiel) oder im Fragebogen markieren). (Die Teilnehmerinnen dürfen das ausgefüllte Material behalten, damit ich die Antworten nicht sehe um so die Anonymität gewahrt bleibt. Ich markiere auf einem separaten Bogen die angesprochenen Probleme) 3. Etwa 20 Minuten Supergöre spielen 4. Instruktion lesen + Material ausfüllen 5. Gruppendiskussion 6. Bedanken, Verabschieden & Vergütung

Gruppendiskussion: Start: - Wie alt seid ihr denn? - Wo geht ihr zur Schule? - Was macht ihr in eurer Freizeit gerne? - Spielt ihr in eurer Freizeit Computerspiele? Falls ja, welche? Bei JA: - Was gefällt euch an diesen Spielen? - Wie oft spielt ihr am Tag oder pro Woche?

Bei NEIN: - Was gefällt euch an Computerspielen nicht? 1. Teil: Das Spiel Supergöre - Wie hat euch denn das Spiel gefallen, das ihr gerade eben gespielt habt? - Gibt es etwas, das euch an dem gerade eben gespielten Spiel besonders gefallen hat? - Würdet ihr etwas in dem Spiel anders gestalten? Wenn ja, was? - Was hat euch nicht gefallen? - Wie müsste das Spiel sein, damit es euch gefällt? - War das Spiel eventuell zu schwierig oder zu leicht? - Welches Level hat euch am besten gefallen? Warum? - Welches Level hat euch nicht so gut gefallen? Warum? - Hattet ihr Probleme an bestimmten Stellen, z.B. lief etwas nicht richtig oder war etwas zu schnell? - Habt ihr euch zum Spiel etwas notiert? - Waren die Informations-Texte verständlich? Oder gab es Wörter, die euch komisch vorkamen? - War die Zeit zum Lesen der Texte lang genug? - Habt ihr den Ablauf des Spiels gut verstanden oder gab es evtl. Unklarheiten oder Missverständnisse? - Wie gefallen euch die Figuren und Grafiken? - Für welches Alter sollte eurer Meinung nach dieses Spiel sein? - Wann würdet ihr es spielen? Zuhause oder auf dem Handy unterwegs etc.? - Würdet ihr dieses Spiel anderen weiterempfehlen? Wem? - Gibt es noch etwas über das Spiel, was ihr mir gerne sagen möchtet?

Dann kommen wir nun zu den Fragebögen und fangen hier mit dem Begleitbrief an.

2. Teil: Instruktion - War der Brief verständlich oder eher nicht? - Gibt es im Anschreiben Wörter oder ganz Sätze, die euch komisch vorkamen, ich meine, die ihr nicht verstanden habt oder die ihr seltsam formuliert fandet? - Waren die Erklärungen zu den verschieden Antwortmöglichkeiten verständlich? - Habt ihr etwas unterstrichen? - Gibt es zum Anschreiben noch irgendetwas, das ihr mir sagen möchtet?

Dann sprechen wir jetzt über die eigentlichen Fragebögen.

3. Teil: Fragebögen (einzeln durchgehen) - Wie lange habt ihr insgesamt gebraucht? - Wie gut seid ihr insgesamt mit dem Ausfüllen der Fragebögen zurecht gekommen? - Was hat euch gut gefallen? - Was nicht? - Gab es etwas, dass euch komisch oder seltsam vorkam? - War das Ausfüllen anstrengend oder eher nicht? - Hattet ihr mit manchen Fragebögen Probleme, ich meine, gab es evtl. ganze Fragebögen mit denen ihr nicht zurecht gekommen sied? Wenn ja, mit welchen und warum? - War die Sprache verständlich, ich meine gab es z.B. Wörter, die euch komisch vorkamen oder die ihr nicht verstanden habt? Gabt es Wörter, die ihr zu „wissenschaftlich“ oder zu „gestochen“ fandet? - Welcher Fragebogen hat euch keine Probleme bereitet? - Hattet ihr manchmal Schwierigkeiten mit dem Inhalt, z.B. habt ihr Fragen nicht beantwortet, weil ihr die Antwort nicht wusstest oder sie euch peinlich war? - Die nächste Frage ist sehr wichtig. Ihr könnt mir helfen die Fragebögen so zu gestalten, dass sie nicht unangenehm oder unverständlich sind. Diese Frage jetzt vielleicht etwas sehr direkt, aber wie gesagt sehr wichtig: Habt ihr bei manchen Antworten gelogen? - Falls gelogen: Darf ich fragen, warum ihr geflunkert habt? - Wir gehen jetzt die Fragebögen einzeln durch. Würdest ihr mir bitte sagen, ob ihr bei den jeweiligen Bögen etwas markiert habt, weil es unverständlich oder seltsam war oder aus anderen Gründen? - Würdet ihr euren Freundinnen empfehlen an der Studie teilzunehmen? - Gibt es abschließend noch etwas, das ich eventuell vergessen habe zu fragen, was ihr mir gerne sagen möchtet?

Dann bedanke ich mich ganz herzlich dafür, dass ihr mir geholfen habt! Appendix B

– Photographs – Photographs – Lab III (Bremen)

Photographs – Home Office (Cologne)

Appendix C

– Recruitment Letters and Letter of Agreement –

Sehr geehrte/r Klassenlehrer/in, ich schreibe an der International University Bremen eine Doktorarbeit zum Thema „Entertainment Education und Computerspiele – Eine bisher ungenutzte Chance“. Dabei handelt es sich um eine neue Methode der Gesundheitskommunikation, die ich erproben möchte. Als konkretes Gesundheitsthema habe ich „AIDS/HIV“ für meine Studie ausgewählt, da die Zahl der Neuinfektionen, insbesondere bei jungen, heterosexuellen Menschen, derzeit wieder ansteigt.

Ich habe bei der Schulleitung angefragt, ob ich mein Projekt kurz in den Klassen vorstellen darf, um jugendliche Teilnehmerinnen für meine Studie gewinnen zu können.

Ich habe hier die wichtigsten Informationen zum Projekt hier für Sie zusammengestellt:

‹ Ich führe an der International University Bremen ein Forschungsprojekt zum Thema „Mädchen und HIV“ durch.

‹ Hierfür suche ich noch jugendliche Teilnehmerinnen (nur Mädchen) im Alter von 15 Jahren.

‹ Die Teilnahme beinhaltet einen einmaligen Termin an der International University Bremen (nachmittags bzw. samstags) und das Ausfüllen von zwei Fragebögen, die etwa eine Woche nach diesem Termin per Post zugeschickt werden.

‹ Alle Daten werden selbstverständlich anonymisiert und streng vertraulich behandelt, d.h. ich gebe keine Daten weiter (auch nicht an die Schulen oder Eltern).

‹ Der Termin dauert max. zwei Stunden und wird mit 5 Euro Aufwandsentschädigung vergütet, außerdem gibt es noch eine Verlosung von H&M-Gutscheinen.

Ich möchte mein Projekt gerne in den 9. bzw. 10. Klassen Ihrer Schule vorstellen. Dazu benötige ich ca. 10 Minuten am Anfang oder Ende einer Unterrichtsstunde. An interessierte Schülerinnen teile ich eine Information und Einverständniserklärung für die Eltern aus. Sollten die Eltern der Teilnahme zustimmen, so senden diese die Einverständniserklärung sowie Name und Telefonnummer ihrer Tochter an mich zurück, damit ich telefonisch einen Termin vereinbaren kann.

Im Voraus schon einmal vielen Dank für Ihre Unterstützung!

Mit freundlichen Grüßen, Yvonne Thies-Brandner (Dipl.-Psych.)

An die Schulleitung der xxx-Schule Herr/Frau xxx Xxxxx Xxxx

Xxxxx Bremen

Yvonne Thies-Brandner Bremen, den xx.10.2006 DIPLOM-PSYCHOLOGIN

SCHOOL OF HUMANITIES

AND SOCIAL SCIENCES

Campus Ring 1 D – 28759 Bremen Sehr geehrte/r Herr/Frau XXX, Germany

POSTAL ADDRESS P.O. Box 750 561 an der International University Bremen führe ich zur Zeit im Rahmen D – 28725 Bremen meiner Dissertation ein medienpsychologisches Forschungsprojekt PHONE ++49 (421) 200-34 07 FAX ++49 (421) 200-33 03 EMAIL [email protected] durch, das von Frau Prof. Dr. M. Schreier betreut wird. In diesem Projekt gehe ich der Frage nach, ob und inwiefern jungen Menschen Informatio- nen zu einem Gesundheitsthema mit Hilfe von Computerspielen vermit- telt werden können. Als konkretes Thema habe ich die Gefahren einer HIV-Ansteckung ausgewählt.

Ich gehe davon aus, dass Computerspiele, die zielgruppenorientiert ent- wickelt wurden, einen positiven Einfluss auf Jugendliche haben können. Ich verfolge mit dieser Studie einen neueren Ansatz psychologischer For- schung, der sich mit dem sogenannten „Entertainment-Eduaction“ be- fasst.

Da für die Studie ein Computerspiel speziell für Mädchen im Alter von etwa 15 Jahren entwickelt wurde, führe ich die Studie zunächst nur mit Mädchen durch.

Eine erfolgreiche Voruntersuchung des Computerspiels und der Fragebö- gen fand im April dieses Jahres in Kooperation mit dem Schulzentrum Rockwinkel in Bremen-Oberneuland statt. Nun läuft bald die Hauptstudie des Projekts an und hierzu wende ich mich nun an Sie und andere Bremer Schulen mit der Bitte, mich in der Kontaktaufnahme mit den Schülerinnen zu unterstützen.

Die wichtigsten Eckdaten zu dem Projekt sind:

Die Teilnahme... - ist möglich für Schülerinnen im Alter von 15 Jahren - umfasst einen einmaligen Termin von ca. 90 Minuten; etwa eine Wo- che nach dem Termin werden den Mädchen einige Fragebögen zum Ausfüllen zugeschickt - wird mit einer Aufwandsentschädigung von 5 Euro pro Teilnehmerin vergütet - unterliegt selbstverständlich allen Regeln des Datenschutzes - ist keine Testsituation, es geht nicht um die Leistung der Schülerin- nen - die Erhebung findet im November/Dezember statt

Das Projekt wird nachmittags bzw. samstags in den Räumen der IUB durchgeführt, also außerhalb der Unterrichtszeiten.

Die IUB ist mit öffentlichen Verkehrsmitteln gut ereichbar, was eine problemlose Anreise gewährleistet.

Ich habe Ihnen eine Beschreibung meines Projekts und einen Entwurf des Infoblattes für die Eltern beigelegt. Sollten Sie Fragen haben, so errei- chen Sie mich telefonisch unter 0421 / 200 34 07 (gerne auf AB spre- chen, ich rufe zurück) oder per E-Mail [email protected].

Ich würde mich über eine Unterstützung seitens Ihrer Schule sehr freuen. Gerne würde ich zu einem persönlichen Gespräch bei Ihnen vorbei kommen um mich vorzustellen und das weitere Vorgehen mit Ihnen ab- zusprechen. Ich werde mich diesbezüglich in den nächsten Tagen telefo- nisch bei Ihnen melden.

Ich verbleibe mit besten Grüßen und hoffe auf eine positive Antwort,

Yvonne Thies-Brandner

Anlagen

2

Yvonne Thies-Brandner Bremen, den 05.11.2006 DIPLOM-PSYCHOLOGIN

SCHOOL OF HUMANITIES AND SOCIAL SCIENCES

Campus Ring 1 D – 28759 Bremen Germany Sehr geehrte Eltern/ Erziehungsberechtigte, POSTAL ADDRESS P.O. Box 750 561 D – 28725 Bremen an der International University Bremen führe ich zur Zeit ein psychologi- PHONE ++49 (421) 200-34 07 sches Forschungsprojekt zum Thema „Jugendstudie – Mädchen und FAX ++49 (421) 200-33 03 EMAIL [email protected]

HIV“ durch. Ziel dieser Studie ist es, Näheres darüber zu erfahren, wie Jugendliche heutzutage über die Gefahren einer HIV-Ansteckung den- ken.

Um jugendliche Teilnehmerinnen für unsere Untersuchung zu gewinnen, sind wir an die Schule Ihrer Tochter herangetreten. Die Schulleitung und der/die Klassenlehrer/in sind über das Projekt informiert und unterstützen unser Vorhaben. Ich habe das Projekt auch persönlich in den Klassen vorgestellt. Insbesondere wurde dabei auf die Freiwilligkeit der Teilnah- me hingewiesen. Ihre Tochter hat sich für die Teilnahme an diesem Pro- jekt interessiert.

Wir möchten Sie nun über die wichtigsten Eckpunkte informieren und Sie darum bitten, einer Teilnahme Ihrer Tochter zuzustimmen. Was be- deutet eine Teilnahme an meinem Projekt? - Ihre Tochter nimmt an einer ca. zweistündigen Studie teil (kein Test, es geht nicht um Leistung), in der sie Fragebögen ausfüllt und even- tuell ein Computerspiel spielt. Etwa eine Woche nach diesem Termin erhält sie weitere Fragebögen per Post, die sie mit dem beiliegenden, frankierten Rückumschlag ausgefüllt an mich zurücksendet. - Sie erhält dafür 5 Euro Aufwandsentschädigung, außerdem werden unter allen Teilnehmerinnen noch H&M-Gutscheine verlost.

- Die Befragung findet außerhalb der Unterrichtszeit an der Internatio- nal University Bremen (IUB) statt. Die IUB ist mit öffentlichen Ver- kehrsmitteln gut zu erreichen. Wir haben für Ihre Tochter ein Infor- mationsblatt mit allen wichtigen Angaben zusammengestellt. Ebenso finden Sie auf dem Informationsblatt eine Wegbeschreibung, wie Sie mit dem Auto am besten zur IUB gelangen.

Bisherige Erfahrungen haben gezeigt, dass jugendliche Teilnehmer/innen durchgängig sehr positiv auf die Befragungssituation reagieren und sich über die Aufwandsentschädigung freuen.

Ich würde mich sehr freuen, wenn Sie Ihr Einverständnis geben, dass Ihre Tochter an der Untersuchung zum Thema „Mädchen und HIV“ teilneh- men kann. Ich versichere Ihnen, dass bei einer Teilnahme alle Regeln des Datenschutzes konsequent eingehalten werden. Ich werde die Daten nur anonym und ausschließlich zu wissenschaftlichen Zwecken nutzen und unter keinen Umständen an Dritte weitergeben, d.h. auch nicht an Sie oder die Schule.

Diesem Schreiben habe ich eine Einverständniserklärung und einen fran- kierten Rückumschlag beigefügt. Falls Sie einer Teilnahme Ihrer Tochter zustimmen, ist es sehr wichtig, dass Sie mir gleich nach Erhalt dieses Briefes die Einverständniserklärung zuschicken. Ohne diese kann Ihre Tochter aus Gründen des Datenschutzes nicht teilnehmen.

Ich danke Ihnen für Ihre Unterstützung und bin im Anschluss an die Auswertung der Daten gerne bereit, Ihren Kindern und Ihnen eine Rück- meldung über die Ergebnisse der Untersuchung zu geben. Für Rückfra- gen stehe ich Ihnen gerne unter 0421 / 200 3407 zur Verfügung.

Mit freundlichen Grüßen Yvonne Thies-Brandner

2 Bitte schicken Sie uns diese Seite innerhalb der nächsten drei Tage zu. Wir werden Sie dann umgehend anrufen, um einen genauen Teilnahmetermin mit Ihrer Tochter zu vereinbaren.

Einverständniserklärung

Ich bin einverstanden, dass meine Tochter an der Untersuchung „Jugendstudie – Mädchen und HIV“ teilnimmt. Ich kann meine Zustimmung jederzeit widerrufen und bei einer Ablehnung der Zustimmung entstehen keinerlei Nachteile für mich oder meine Tochter. Ich bin darüber informiert, dass alle Daten ausschließlich in anonymisierter Form und zu wissenschaftlichen Zwecken an der International University Bremen verwendet werden.

Name der Schülerin Datum, Unterschrift eines/einer Erziehungsberechtigten

......

Angaben zur jugendlichen Teilnehmerin:

Name, Vorname: ______Alter:______

Adresse: ______

Telefon (am besten zu erreichen unter): ______

Schule:______Klasse:______

Angestrebter Schulabschluss:______

Appendix D

– Instruction and Questionnaires –

(Posttests are only included in this Appendix in case they differ much from the pretests, otherwise only the pretests are presented)

Instruction

Jugendstudie – Mädchen und HIV

Liebe Untersuchungspartnerinnen, die vorliegende wissenschaftliche Untersuchung ist Teil meiner Doktorarbeit, in der ich das Thema „Mädchen und HIV“ näher erforschen möchte. Dazu habe ich einige Frage- bögen entwickelt und bitte Dich darum, diese auszufüllen.

Zur Bearbeitung der folgenden Studie wirst Du voraussichtlich etwa 1,5 Stunden benö- tigen.

Als kleines Dankeschön für Deine Teilnahme erhälst Du am Ende der Untersuchung von mir 5 Euro. Zusätzlich gibt es eine Verlosung von Gutscheinen, an der alle Mäd- chen teilnehmen können, die die Fragebögen, die ich euch in den nächsten Tagen per Post zuschicken werde, ausgefüllt an mich zurücksenden.

Zu gewinnen sind wahlweise Gutscheine von Saturn oder H&M Hauptgewinn: Ein Gutschein im Wert von 30 Euro; Zweiter Preis: Ein Gutschein im Wert von 20 Euro; Dritte Preise: Fünf Gutscheine im Wert von 10 Euro.

Kommen wir nun zur Erläuterung der eigentlichen Studie!

Allgemeiner Ablauf

Ich werde Dir einige Fragebögen zum Ausfüllen geben. In ca. 8-10 Tagen wirst Du von mir Post bekommen, in diesem Umschlag findest Du dann weitere Fragebögen. Ich bitte Dich, diese innerhalb von 5 Tagen auszufüllen und mit dem frankierten Rückumschlag an mich zurückzusenden.

Antwortvorgaben

Es gibt unterschiedliche Antwortmöglichkeiten bei den Fragebögen. Bei manchen kreuzt man Kästchen an, bei anderen Zahlen, manchmal auch Sätze, oder Du schreibst Deine Antwort auf. Es folgen nun vier Beispiele für die verschiedenen Antwortmög- lichkeiten zum Thema „Schwangerschaftsverhütung“, um das Prinzip zu zeigen.

Bitte umblättern =>

1. Beispiel

Wie hast Du Dich bisher über „Schwangerschaftsverhütung“ informiert? (Mehrfachnennungen möglich):

 Berichte in Zeitungen und Illustrierten  Bücher  Schulunterricht  Fernsehsendungen  Radiosendungen  Broschüren  Freund/inn/e/n gefragt  Arzt  gar nicht

Falls Du Dich bisher z.B. im Schulunterrricht und durch Broschüren über „Schwanger- schaftsverhütung“ informiert hast, dann kreuze die entsprechenden Kästchen an.

2. Beispiel

Ich habe Angst vor einer ungewollten Schwangerschaft.

-3 -2 -1 +1 +2 +3

Stimme über- stimme nicht zu stimme eher stimme stimme zu stimme voll haupt nicht zu eher zu und ganz zu nicht zu

Falls Du beispielsweise Angst vor einer ungewollten Schwangerschaft hast, müsstest Du hier die +3 ankreuzen. Doch auch Abstufungen sind möglich. Falls Du z.B. nur eher wenig Angst vor einer ungewollten Schwangerschaft hast, dann kreuze bitte den für Dich passenden Wert dazwischen an.

3. Beispiel

Ich bin am Thema „Schwangerschaftsverhütung“ interessiert. trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig

Hier ist es so ähnlich wie im zweiten Beispiel, nur dass nicht alle Werte mit Worten beschrieben sind. Kreuze auch hier den passendsten Wert für Dich an.

4. Beispiel

Worüber hast Du mit Deiner Freundin zuletzt geredet, als es um Schwangerschaftsverhütung ging? Schreib nun bitte kurz in Stichpunkten auf, worüber Ihr genau gesprochen habt (z.B. die Pille, Abtreibung ...)

______

______

Hier geht es darum, dass Du selbst ein paar Stichworte zur Beantwortung der Frage auf- schreibst.

Jetzt geht´s los

Bitte fülle alle Fragebogenteile vollständig und in der vorgegebenen Reihenfolge aus und überspringe keine der Fragen bzw. Aussagen, auch wenn Dir manche Fragen sehr ähnlich erscheinen! (Übersprungene Fragen bereiten uns Psycholog/inn/en stets große Probleme...).

Ich bitte Dich darum, die ausgefüllten Fragebögen in den beiliegenden Umschlag zu stecken und dann an mich zurückzugeben.

Yvonne Thies-Brandner International University Bremen School of Humanities and Social Sciences P.O. Box 750561 28725 Bremen

Sämtliche Auskünfte über Deine Antworten und Deine Person werden selbstverständlich streng vertraulich behandelt!

Informationen zu den Ergebnissen dieser Studie schicke ich Dir gerne zu, sofern Du daran interessiert bist. Sende mir in diesem Fall bitte eine E-mail an die folgende Adres- se: [email protected]

Nun hoffe ich, dass Dir das Ausfüllen der vielen Fragen auch etwas Spaß macht. Ich danke Dir im Voraus ganz herzlich für Deine Teilnahme an dieser Studie und Deine Kooperation!

Mit feundlichen Grüßen

Dipl. Psych. Yvonne Thies-Brandner

Wissenschaftliche Mitarbeiterin International University Bremen School of Humanities and Social Sciences P.O. Box 750561 28725 Bremen

______

Geheimname

Damit ich die Ergebnisse von heute mit den neuen nächste Woche kombinieren kann, ist es wichtig, dass ich weiß, welche Teile zusammengehören. Da aber alles anonym bleibt, bitte ich Dich, Dir ein Codewort oder einen „Geheimnamen“ zu überlegen. Dies sollte aus einem Wort und einer Zahl bestehen, z.B. Schnecke25 oder 13Piraten.

Trage hier bitte nun Dein selbstausgedachtes Codewort ein, einmal für mich und einmal für Dich. Diesen Teil kannst Du dann abtrennen und im Portemonnaie aufheben. Du brauchst Dein Geheimwort wieder, wenn Du in ca. einer Woche Post von mir be- kommst.

Mein Codewort lautet: Bitte wiederhole hier Dein Co- dewort und nimm diese Ecke des Blatts mit:

______

Demographic Facts

Allgemeine Fragen

Ich habe nun einige Fragen zu Deiner Person. Trage die Antwort bitte entweder in die dafür vorgesehenen Felder ein oder kreuze die für Dich zutreffende Antwort bitte an.

1. Wie alt bist Du? ______Jahre

2. Hast Du gerade eine feste Beziehung? Was auf dieser Liste trifft auf Dich zu?

 Ich habe keinen festen Freund  Ich habe einen festen Freund, aber wir wohnen nicht zusammen  Ich habe einen festen Partner und lebe mit ihm zusammen  Sonstiges, und zwar:______

4. Falls Du Schülerin bist, welchen Schulabschluss strebst Du an?

 Hauptschulabschluss  Mittlere Reife, Realschulabschluss, Fachschulreife  Fachhochschulreife, Abschluss einer Fachoberschule  Abitur, allgemeine oder fachgebundene Hochschulreife  Einen anderen Schulabschluss, und zwar:______

Experience with Computer Game Playing

Computerspiele

Bei den folgenden Fragen geht es darum, ob und wie Du Computerspiele spielst. Mit Computer- und Videospielen meine ich alle Spiele, die man auf einem Computer, einer Spielekonsole, einer tragbaren Spielekonsole (z.B. Gameboy) oder einem Handy spielen kann.

1. Wie häufig spielst Du mit folgenden Geräten Computer- und Videospiele?

Ù Falls Du nie Computer- oder Videospiele spielst, dann kreuze unten „Ich spiele nie Computer- oder Videospiele“ an und mach mit dem nächsten Fragebogen weiter!

 Ich spiele nie Computer- oder Videospiele

nie einmal im mehrmals mehrmals jeden Monat oder im Monat in der Tag seltener Woche

Computer      Spielekonsole (z.B. Playstation, Gamecube, Xbox)      Tragbare Konsole (z.B. Gameboy, Nintendo DS)      Handy     

2. Schätz doch mal: Wie lange spielst Du pro Tag ungefähr Computer- und Videospiele mit all den in Frage 1 erwähnten Geräten?

An Schul-/Arbeitstagen: ca______Stunde(n) und ______Minuten pro Tag

An freien Tagen: ca______Stunde(n) und ______Minuten pro Tag

3. Wie heißen die drei Computer- und Videospiele, die Du zurzeit am meisten spielst?

1 ______

2 ______

3 ______

4. Wie häufig spielst Du folgende Arten von Computer- und Videospielen mit all den in Frage 1 erwähnten Geräten?

nie selten manch- oft sehr mal oft

Denk- und Geschicklichkeitsspiele (z.B. Tetris, Minesweeper)     

Strategie- und Simulationsspiele (z.B. Warcraft, Civilisation, The      Sims)

Adventures (z.B. Black Mirror, Diablo, Gothic)     

Ego-Shooter oder Third-Person-Shooter (z.B. Doom, Halflife,      Counterstrike, Manhunt oder Hitman)

Andere Kampfspiele (z.B. Streetfighter, Mortal Combat, Tekken)     

Andere Spiele, und zwar:______    

Sexual Behavior

Sexualverhalten

Als nächstes bitte ich Dich, einige Fragen zu Deinem Sexualverhalten zu beantworten. Kreuze bitte das jeweils zutreffende Kästchen an. Du kannst Dir absolut sicher sein, dass Deine Daten anonym sind, d.h. niemand kann wissen, welche Antworten Du hier gegeben hast.

1. Wie würdest Du Deine sexuelle Orientierung beschreiben?

 Ich bin heterosexuell, d.h. ich fühle mich zu Männern hingezogen  Ich bin homosexuell, d.h. ich fühle mich zu Frauen hingezogen  Ich bin bisexuell, d.h. ich fühle mich zu Frauen und Männern hingezogen  Ich weiß nicht

2. Hattest Du schon einmal Geschlechtsverkehr? Ich meine, ob Du schon einmal mit einem Mann oder einer Frau geschlafen hast.

 Ja, zum ersten Mal im Alter von ______Jahren  Nein, bisher noch nicht (hier bitte Alter eintragen)

3. Die Menschen sind ja in ihren sexuellen Gewohnheiten sehr verschieden. Manche sind aktiver, mache weniger aktiv, und alle haben in ihrem Leben auch Zeiten, in denen in sexueller Hinsicht gar nichts passiert. Wie ist das bei Dir: Bist Du in den letzten 12 Monaten mit jemandem intim gewesen, d.h. hattest Du mit jemandem Geschlechtsverkehr, Petting, Oralverkehr etc.?

 Ja  Nein (=> mach bitte mit Frage 6 weiter)

4. Innerhalb eines Jahres kann es ja durchaus möglich sein, dass man mehrere Partner hat, und viele Menschen haben gelegentlich auch einmal Zufallsbekanntschaften, mit denen sie intim werden. Hattest Du in den letzten 12 Monaten mehr als eine/n Part- ner/in, mit denen Du intim warst?

 Ja  Nein (=> mach bitte mit Frage 6 weiter)

5. Mit wie vielen Partner/inne/n warst Du in den letzten 12 Monaten intim?

Insgesamt mit ______Partnern (bitte hier Anzahl eintragen)

6. Wenn Du Beziehungen mit einer eher unbekannten Person eingehen würdest, würdest Du immer ein Kondom verwenden oder manchmal auch nicht?

 Ja, ich würde immer ein Kondom verwenden  Ja, aber manchmal würde ich es vielleicht vergessen  Nein  Ich gehe keine Beziehungen mit unbekannten Partnern ein

7. Wenn man zu Beginn einer neuen Beziehung ein Kondom verwendet, taucht die Fra- ge auf, ab wann man denn auf das Kondom verzichtet, wenn die Beziehung andauert. Wann würdest Du auf das Kondom verzichten?

 Eigentlich von Beginn an, denn ich gehe intime Beziehungen nur mit Personen ein, die ich richtig einschätzen kann  Sobald ich die Person einige Zeit kenne  Wenn ich mehr über das sexuelle Vorleben der Person weiß und ihr vertraue  Erst nachdem wir beide einen AIDS-Test gemacht haben

Knowledge about HIV/AIDS and Condom Use

Kondome & HIV/AIDS

Bei den folgenden Aussagen geht es um Kondome und wie man diese anwendet bzw. um HIV-Ansteckungswege. Falls Du die Aussagen für richtig hältst, dann kreuze bitte „stimmt“ an, falls Du die Aussagen nicht für richtig hältst, kreuze bitte „stimmt nicht“ an, und falls Du die richti- ge Antwort nicht kennst, dann kreuze bitte „weiß nicht“ an.

1. Kondome schützen bei Oralverkehr vor einer Ansteckung mit HIV / AIDS.

 stimmt  stimmt nicht  weiß nicht

2. Wenn die Verpackung eines Kondoms beschädigt ist, sollte man es nicht mehr verwenden.

 stimmt  stimmt nicht  weiß nicht

3. Man kann ein Kondom mehrmals verwenden.

 stimmt  stimmt nicht  weiß nicht

4. Bevor ein Kondom benutzt wird, sollte es durch Ausrollen auf seine Dichte überprüft werden.

 stimmt  stimmt nicht  weiß nicht

5. Kondome können zusammen mit Cremes (z.B. Nivea) verwendet werden.

 stimmt  stimmt nicht  weiß nicht

6. Die „Pille“ schützt nicht vor einer HIV-Infektion.

 stimmt  stimmt nicht  weiß nicht

7. Naturdarmkondome schützen vor HIV / AIDS.

 stimmt  stimmt nicht  weiß nicht

8. Zwei Kondome übereinander zu ziehen ist noch sicherer.

 stimmt  stimmt nicht  weiß nicht

9. Durch Küssen kann man sich mit HIV anstecken.

 stimmt  stimmt nicht  weiß nicht

10. Die „Pille danach“ schützt vor einer HIV-Infektion.

 stimmt  stimmt nicht  weiß nicht

11. Markenkondome haben eine CE-Kennzeichnung mit einer Prüfnummer.

 stimmt  stimmt nicht  weiß nicht

12. Durch Umarmen einer anderen Person kann man sich mit HIV anstecken.

 stimmt  stimmt nicht  weiß nicht

13. Richtig ausgeführter Safer Sex schützt vor HIV.

 stimmt  stimmt nicht  weiß nicht

14. Druck (z.B. im Portemonnaie) schadet dem Kondom nicht.

 stimmt  stimmt nicht  weiß nicht

15. Trotz der Verwendung eines Scheidenzäpfchens kann man sich mit HIV anstecken.

 stimmt  stimmt nicht  weiß nicht

16. Während der Menstruation ist das Infektionsrisiko für beide Partner/innen höher als ohne Menstruation.

 stimmt  stimmt nicht  weiß nicht

17. Andere sexuell übertragbare Krankheiten (z.B. Tripper, Syphilis) erhöhen das Risi- ko einer HIV-Infektion.

 stimmt  stimmt nicht  weiß nicht

18. Kondome haben ein Haltbarkeitsdatum.

 stimmt  stimmt nicht  weiß nicht

19. Hitze (z.B. durch Heizkörper, pralle Sonne, Auto-Handschuhfach) kann das Kon- dom beschädigen.

 stimmt  stimmt nicht  weiß nicht

20. Scherzkondome (z.B. mit Tierköpfen oder Comicfiguren) schützen vor einer HIV- Infektion.

 stimmt  stimmt nicht  weiß nicht

Interest in HIV/AIDS and Condom Use

Dein Interesse am Thema HIV / AIDS

Die Interessen von Menschen können ja sehr unterschiedlich sein. Manche interessieren sich für viele Themen, mache eher für weniger Themen. Außerdem kann das Maß an Interesse an einem Thema auch sehr unterschiedlich sein.

Ich bitte Dich hier, ein paar Angaben zu Deinem persönlichen Interesse an den Themen HIV und AIDS zu machen. Hier gibt es keine „richtigen“ oder „falschen“ Antworten – wenn Du Dich also beispielsweise gar nicht für die Themen HIV oder AIDS interes- sierst und das so ankreuzt, dann hilft mir das auch sehr weiter! Kreuze bitte die Antwort an, die am ehesten auf Dich zutrifft. Bitte sei bei der Bearbeitung des Fragebogens so ehrlich wie möglich.

1. Wie groß ist Dein allgemeines Interesse an den Themen HIV und AIDS?

1------2------3------4------5 sehr groß groß teils, teils gering sehr gering

2. Wie groß ist Dein Interesse an Informationen über die verschiedenen Ansteckungs- wege einer HIV-Infektion?

1------2------3------4------5 sehr groß groß teils, teils gering sehr gering

3. Wie groß ist Dein allgemeines Interesse an dem Thema Kondombenutzung?

1------2------3------4------5 sehr groß groß teils, teils gering sehr gering

4. Wie hast Du Dich bisher über HIV/AIDS informiert? (Mehrfachnennungen möglich):

 Berichte in Zeitungen und Illustrierten  Bücher  AIDS-Fernsehspots  Fernsehsendungen über AIDS  Radiosendungen über AIDS  Broschüren über AIDS  Beim Gesundheitsamt  Arzt/Ärztin  Beratung bei Organisationen  Gespräche mit Bekannten  Gespräche mit Familienmitgliedern  Vorträge, Lehrveranstaltungen  Schule  Sonstiges, und zwar:______ Gar nicht

5. Über welche Themen bzgl. HIV und AIDS würdest Du Dich gern genauer informie- ren? (Mehrfachnennungen möglich)

 Ansteckungswege  Safer Sex  Richtige Kondombenutzung  Medikamentöse Behandlungsmöglichkeiten von HIV / AIDS  HIV-Test  andere, und zwar:______ Ich habe kein Interesse an dem Thema HIV / AIDS

6. Stell Dir vor, im Fernsehen würde eine Sendung darüber laufen, wie man Kondome richtig benutzt. Würdest Du diese Sendung anschauen?

     Ja, ich würde sie Ich würde sie Ich weiß nicht Ich würde sie Nein, ich würde sie auf alle Fälle an- wahrscheinlich wahrscheinlich auf keinen Fall schauen anschauen nicht anschauen anschauen

7. Stell Dir vor, in Deiner Lieblingszeitschrift würde ein Artikel über Kondombenut- zung stehen. Würdest Du diesen Artikel lesen?

     Ja, ich würde Ich würde ihn Ich weiß nicht Ich würde ihn Nein, ich würde ihn auf alle wahrscheinlich wahrscheinlich ihn auf keinen Fall Fälle lesen lesen nicht lesen lesen

8. Stell Dir vor, Du bekämst eine Broschüre zum Thema Kondombenutzung geschenkt. Würdest Du diese Broschüre lesen?

     Ja, ich würde Ich würde sie Ich weiß nicht Ich würde sie Nein, ich würde sie sie auf alle wahrscheinlich wahrscheinlich auf keinen Fall Fälle lesen lesen nicht lesen lesen

9. Stell Dir vor, Du würdest im Internet zufällig auf eine Seite zur Kondombenutzung stoßen. Würdest Du Dir diese Internetseite anschauen?

     Ja, ich würde Ich würde sie Ich weiß nicht Ich würde sie Nein, ich würde sie sie auf alle wahrscheinlich wahrscheinlich auf keinen Fall Fälle anschauen anschauen nicht anschauen anschauen

10. Stell Dir vor, in Deiner Nähe (Schule, Uni, Arzt) würde eine HIV-Infizierte einen Vortrag zum Thema HIV-Ansteckungswege halten. Würdest Du Dir diesen Vortrag an- hören?

     Ja, ich würde ihn Ich würde ihn Ich weiß nicht Ich würde ihn Nein, ich würde auf alle Fälle anhö- wahrscheinlich wahrscheinlich ihn auf keinen Fall ren anhören nicht anhören anhören

11. Stell Dir vor, in Deiner Lieblingssendung im Fernsehen würde das Thema HIV/AIDS thematisiert. Würdest Du die Sendung anschauen?

     Ja, ich würde sie Ich würde sie Ich weiß nicht Ich würde sie Nein, ich würde sie auf alle Fälle an- wahrscheinlich wahrscheinlich auf keinen Fall schauen anschauen nicht anschauen anschauen

Communication about HIV/AIDS and Condom Use – Pretest –

HIV / AIDS als Gesprächsthema

Über manche Themen unterhält man sich mehr, über manche eher weniger. Es folgen nun einige Fragen dazu, wie das bzgl. HIV / AIDS bei Dir ist. Bitte kreuze Deine Ant- worten an oder schreibe Deine Antwort in Stichpunkten in die dafür vorgesehenen Fel- der.

1. Wie oft unterhältst Du Dich in Deinem Freundes- und Bekanntenkreis über HIV / AIDS?

 häufig  gelegentlich  selten  nie => weiter  weiß nicht mit Frage 3

2. Falls Du Dich in Deinem Freundes- und Bekanntenkreis über HIV / AIDS unterhalten hast, schreib nun bitte kurz in Stichpunkten auf, worüber ihr genau gesprochen habt (z.B. Ansteckungswege, Krankheitsverlauf, Medikamente...).

______

3. Wie oft unterhältst Du Dich mit anderen Personen (Familie, Arzt) über HIV / AIDS?

 häufig  gelegentlich  selten  nie => weiter  weiß nicht mit Frage 6

4. Mit wem hast Du Dich über HIV /AIDS unterhalten (z.B. Schwester, Bruder, Frauen- ärztin etc.):______

5. Worüber hast Du mit dieser Person / diesen Personen geredet? Schreib nun bitte kurz in Stichpunkten auf, worüber ihr genau gesprochen habt (z.B. Ansteckungswege, Krankheitsverlauf, Medikamente...)

______

6. Bist Du schon einmal von jemanden um Rat gefragt worden, wie man sich vor AIDS schützen kann?

 ja  nein  weiß nicht

7. Hast Du selber schon einmal jemanden um Rat gefragt, wie man sich vor AIDS schützen kann?

 ja  nein  weiß nicht

8. Sprichst Du mit Deinen Freunden / Freundinnen oder anderen Personen über HIV und AIDS und wie man sich anstecken kann?

 gelegentlich  häufig  selten  nie  weiß nicht

9. Sprichst Du mit Deinen Freunden / Freundinnen oder anderen Personen über Kon- dome und wie man diese anwendet?

 gelegentlich  häufig  selten  nie  weiß nicht

Communication about HIV/AIDS and Condom Use – Posttest –

HIV / AIDS als Gesprächsthema

Über manche Themen unterhält man sich mehr, über manche eher weniger. Es folgen nun einige Fragen dazu, wie das bzgl. HIV / AIDS bei Dir ist. Bitte kreuze Deine Ant- worten an oder schreibe Deine Antwort in Stichpunkten in die dafür vorgesehenen Fel- der.

1. Wie oft hast Du Dich seit dem ersten Teil dieser Studie in Deinem Freundes- und Bekanntenkreis über HIV / AIDS unterhalten?

 häufig  gelegentlich  selten  nie  weiß nicht

2. Wie oft hast Du Dich seit dem ersten Teil dieser Studie mit anderen Personen (z.B. Familie, Arzt) über HIV / AIDS unterhalten?

 häufig  gelegentlich  selten  nie =>  weiß nicht (weiter mit dem nächsten Bogen)

3. Falls Du Dich seit dem ersten Teil dieser Studie mit Ihren Freunden- und Bekannten oder anderen Personen über HIV / AIDS unterhalten hast, wer hat das Thema HIV / AIDS als erstes erwähnt: Du oder Deine Gesprächspartnerin / Dein Gesprächspartner?

 ich  Gesprächspartner/in  weiß nicht

Self-Efficacy

Kondomgebrauch

Es gibt Situationen, in denen man anders handelt, als man sich es vorher vorgenommen hat. Dies kann auch bzgl. der Benutzung von Kondomen der Fall sein. In diesem Frage- bogen geht es darum, was Du glaubst, wie Du in verschiedenen Situationen reagieren würdest. Auch hier gilt wieder, dass ich im Nachhinein nichts darüber sagen kann, wer welche Antworten gegeben hat. Wenn Du zwar in bestimmten Situationen gerne Kondome be- nutzen wolltest, Dir aber nicht sicher bist, ob Du auch wirklich darauf bestehen würdest – oder wenn Du in manchen Situationen lieber keine Kondome benutzen würdest, dann hilfst Du mir am besten weiter, wenn Du das hier auch so ankreuzt. Bitte sei also auch bei der Bearbeitung dieses Fragebogens so ehrlich wie möglich und kreuze die Antwort an, die am besten auf Dich zutrifft.

1. Für wie wahrscheinlich hältst Du es, dass Du gegenwärtig in der Lage bist, bei neuen sexuellen Kontakten Kondome anzuwenden?

sehr unwahrscheinlich 1 – 2 – 3 – 4 – 5 – 6 – 7 sehr wahrscheinlich

2. Für wie schwierig hältst Du für Dich die Anwendung von Kondomen bei neuen sexu- ellen Kontakten?

für gar nicht schwierig 1 – 2 – 3 – 4 – 5 – 6 – 7 für sehr schwierig

3. Es gibt manchmal Hindernisse, die es einem schwer machen, Kondome zu benutzen. Es werden nun einige Situationen genannt, in denen es schwer sein kann, ein Kondom zu verwenden. Bitte kreuze an, wie sicher Du Dir bist, in den genannten Situationen ein Kondom zu verwenden, d.h. ob Du Dir „ganz sicher“ bist, in dieser Situation auf ein Kondom zu bestehen, „fast sicher“, „eher sicher“, oder ob Du Dir „sehr unsicher“ bist.

Wie sicher bist Du Dir, dass Du trotz der folgenden Hindernisse bei einer neuen Liebes- beziehung bzw. bei einem One-Night-Stand Kondome verwenden könntest?

Ich könnte auf Verwendung eines Kondoms auch dann noch bestehen,...

sehr eher fast ganz unsicher sicher sicher sicher

...wenn ich das Thema „Kondom“ als erste an-     sprechen muss.

... der Partner sagt, dass ich die einzige Frau bin,     die er kennt, die auf ein Kondom besteht.

sehr eher fast ganz unsicher sicher sicher sicher

...wenn ich vom Partner gebeten werde, auf ein     Kondom zu verzichten, weil er darauf allergisch reagiert.

...wenn es dadurch eine „Unterbrechung“ geben     würde.

...wenn der Partner dann auf den Geschlechtsver-     kehr ganz verzichten würde.

...wenn ein Kondom erst organisiert werden     müsste (z.B. kaufen oder Mitbewohner fragen).

... wenn der Partner mir versichert, dass er HIV-     negativ ist.

...wenn der Partner meine Bitte, Sex nur mit     Kondom zu haben, ignoriert.

...wenn der Partner es „uncool“ findet, mit Kon-     dom Sex zu haben.

Personal Risk Perception

Du und HIV / AIDS

Bei den nächsten Fragen geht es darum, wie Du hoch oder niedrig Du die Wahrschein- lichkeit einschätzt, dass Du selbst einmal in Deinem Leben mit HIV angesteckt werden könntest. Bitte kreuze wieder die für Dich zutreffendste Antwort an. Du kannst Dir ganz sicher sein, dass ich im Nachhinein nichts darüber sagen kann, wer welche Antworten gegeben hat. Wenn Du also meinst, dass es durchaus sein könnte, dass Du Dich mit AIDS ansteckst und das hier auch so ankreuzt, dann weiß niemand (auch nicht Deine Eltern oder Lehrerinnen und Lehrer), dass Du in diesem Fragebogen eine solche Antwort gegeben hast. Antworte also bitte auch hier so ehrlich wie möglich! Ich weiß, dass das gerade bei solchen persönlichen Fragen schwierig sein kann. Deine Antworten helfen mir bei meiner Studie aber nur dann weiter, wenn Du wirklich ehrlich bist! Dafür an dieser Stelle schon einmal herzlichen Dank!

1. Für wie wahrscheinlich hältst Du es, dass Du in den nächsten 10 Jahren durch sexuel- len Kontakt mit HIV / AIDS infiziert wirst?

Extrem unwahrscheinlich 1 – 2 – 3 – 4 – 5 – 6 – 7 Extrem wahrscheinlich

2. Für wie wahrscheinlich hältst Du es, dass andere Frauen in Deinem Alter und ähnli- cher Lebenssituation durch sexuellen Kontakt mit HIV / AIDS infiziert werden?

Extrem unwahrscheinlich 1 – 2 – 3 – 4 – 5 – 6 – 7 Extrem wahrscheinlich

3. Ich bin gefährdet, mich mit HIV anzustecken.

    

Ja, auf Ja, eher schon Ich weiß nicht Nein, eher nicht Nein, auf alle Fälle keinen Fall

4. Es besteht die Möglichkeit, dass ich HIV/AIDS habe.

    

Ja, auf Ja, eher schon Ich weiß nicht Nein, eher nicht Nein, auf alle Fälle keinen Fall

5. Es kann sein, dass ich Sex mit jemandem hatte, der gefährdet ist, sich mit HIV/AIDS anzustecken.

    

Ja, auf Ja, eher schon Ich weiß nicht Nein, eher nicht Nein, auf alle Fälle keinen Fall

6. Meine sexuellen Erfahrungen stellen ein Risiko für eine HIV/AIDS Ansteckung dar.

    

Ja, auf Ja, eher schon Ich weiß nicht Nein, eher nicht Nein, auf alle Fälle keinen Fall

Behavior Intention

Safer Sex

Sieh die nächsten drei Fragen bitte rein theoretisch, d.h. auch wenn Du Dir nicht vor- stellen kannst, dass die folgenden Situationen bei Dir im wirklichen Leben eintreffen könnten, antworte bitte so, als ob Du in dieser Situation wärst.

Es sind nun einige Situationen aufgelistet, die am Beginn einer neuen Beziehung oder bei einem One-Night-Stand vorkommen können.

1. Nehmen wir einmal an, in einer neuen Liebesbeziehung oder bei einem One-Night- Stand würde der Partner ohne Kondom mit Dir schlafen wollen. Würdest Du zustimmen oder nicht zustimmen?

 ich würde zustimmen  ich würde nicht zustimmen  weiß nicht

2. Wenn der Partner nur mit Kondom mit Dir schlafen wollte: Würdest Du zustimmen oder nicht zustimmen?

 ich würde zustimmen  ich würde nicht zustimmen  weiß nicht

3. Würdest Du in einer neuen Liebesbeziehung oder einem One-Night-Stand von Dir aus vorschlagen, Kondome zu benutzen?

 eher schon  eher nicht  weiß nicht

Involvement while Playing „Supergöre“

Fragen zum Computerspiel

Kreuze zunächst bitte an, welches Level Du im Spiel „Supergöre“ erreicht hast:

 Disco-Level  Ferienlager-Level  Unterwasserwelt-Level  Geister-Level  Dschungel-Level

Nun kommen einige Fragen dazu, wie Du Dich während des Computerspiels gefühlt hast. Manche Aussagen klingen sehr ähnlich, es ist aber wichtig, dass Du immer den für Dich zutreffendsten Wert ankreuzt.

1. Während des Computerspielens verging die Zeit wie im Flug.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

2. Ich musste mich zwingen, meine Gedanken nur auf das Computerspiel zu richten.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

3. Ich war so gefesselt, dass ich mich gar nicht mehr von dem Spiel losreißen konnte.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

4. Die Spielfiguren und die dargestellte Welt waren beim Computerspielen meine Welt.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

5. Ich war beim Spielen ganz in das Spielgeschehen versunken.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

6. Ich bin so richtig in meiner Rolle als Heldin aufgegangen.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

7. Meine Gedanken sind beim Computerspielen immer wieder abgeschweift.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

8. Beim Computerspielen habe ich mich ganz in die im Spiel dargestellte Welt versetzt gefühlt.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

9. Während des Computerspielens war ich abgelenkt.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

10. Beim Computerspielen war die beschriebene Welt realer für mich als die ‚wirkliche Wirklichkeit‘.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

11. Ich habe die Welt um mich herum beim Computerspielen vergessen.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

12. Ich habe mich voll auf das Computerspiel konzentriert.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

13. Das Spielen des Computerspiels hat mir Spaß gemacht.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

14. Beim Computerspielen ist mir aufgefallen, dass ich an etwas anderes denke.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

15. Beim Computerspielen hatte ich das Gefühl, mich an einem anderen Ort zu befin- den.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

16. Gut, dass das Computerspiel nicht noch länger gedauert hat.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

17. Beim Computerspielen bin ich ganz in die Welt des Spiels eingetaucht.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

18. Ich hatte das Gefühl, mich in der Computerspiel-Welt zu befinden.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

19. Ich habe das Computerspiel mit Freude gespielt.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

20. Das Computerspiel war unterhaltsam.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

21. Das Computerspielen war wie eine Reise an einen anderen Ort.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

22. Das Computerspiel hat mir gefallen.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

23. Mein Körper war hier in diesem Raum, aber ich selber war in dem Computerspiel.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

24. Ich würde das Computerspiel „Supergöre“ auch zuhause spielen.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

25. Ich würde das Computerspiel „Supergöre“ meinen Freundinnen empfehlen.

trifft gar nicht zu 1 – 2 – 3 – 4 – 5 – 6 trifft völlig zu

Appendix E

– Statistical Analyses –

Data Preparation

Box Plots

Age of first sexual intercourse

16

14

39 12

altergv

Computer playing time during typical week day and typical weekend day

600

48

500 25

59 400 39

48 300 43

200

100

0

KonsumSchultag KonsumWE

Comparison of Partial Samples (Bremen/Cologne)

t-tests

Group Statistics

Town N Mean Std. Deviation Std. Error Mean Age BREMEN 50 14,84 ,370 ,052

COLOGNE 25 14,80 1,118 ,224 Age of first sexual BREMEN 15 13,93 ,961 ,248 intercousre COLOGNE 6 15,00 ,894 ,365 Number of partners BREMEN 49 ,63 ,972 ,139

COLOGNE 25 ,56 ,712 ,142 Computer BREMEN 41 3,51 1,186 ,185

COLOGNE 21 3,43 1,248 ,272 Consoles BREMEN 42 2,05 ,882 ,136

COLOGNE 21 2,24 ,995 ,217 Portable BREMEN 42 1,71 ,995 ,153

COLOGNE 21 1,95 1,203 ,263 Cell Phone BREMEN 42 3,36 1,206 ,186

COLOGNE 21 3,57 1,502 ,328 Minutes during week BREMEN 42 106,07 76,553 11,812

COLOGNE 21 87,14 72,052 15,723 Minutes during weekend BREMEN 41 178,29 121,689 19,005

COLOGNE 21 157,86 125,942 27,483 Skill BREMEN 42 3,33 1,183 ,182

COLOGNE 21 2,71 1,271 ,277 Strategy/Simulation BREMEN 42 2,98 1,137 ,175

COLOGNE 21 3,24 1,513 ,330 Adventures BREMEN 42 1,88 1,109 ,171

COLOGNE 21 1,76 ,944 ,206 EgoShooter BREMEN 42 1,62 1,103 ,170

COLOGNE 21 1,76 1,091 ,238 Fight BREMEN 42 1,79 1,001 ,154

COLOGNE 21 1,67 1,111 ,242 Computer game time added BREMEN 41 142,38 94,325 14,731

COLOGNE 21 122,50 96,125 20,976 Overall_playtime_tripartite BREMEN 41 2,10 ,800 ,125 COLOGNE 21 1,86 ,854 ,186 Overall_hardware_tripartite BREMEN 41 2,02 ,821 ,128 COLOGNE 21 2,29 ,717 ,156 Sum variable game intensity BREMEN 40 4,13 1,202 ,190

COLOGNE 21 4,14 1,236 ,270 Sum variable risk perception BREMEN 50 -1,4000 ,55328 ,07825

COLOGNE 25 -1,3800 ,55958 ,11192 Sum variable general interest BREMEN 49 3,6667 ,65969 ,09424 (pre-test) COLOGNE 25 3,8267 ,46268 ,09254 Sum variable general interest BREMEN 24 3,6528 ,67730 ,13825 (post-test I) COLOGNE 11 3,8182 ,47990 ,14469 Sum variable general interest BREMEN 31 3,5914 ,80143 ,14394 (post-test II) COLOGNE 20 3,6000 ,74614 ,16684 sum_int_5er_pre BREMEN 50 2,60 1,107 ,156 COLOGNE 25 3,24 1,393 ,279 sum_int_5er_post_I BREMEN 24 2,88 1,154 ,236 COLOGNE 11 3,09 1,375 ,415 Sum variable interest media BREMEN 26 ,7179 ,73298 ,14375 products (post-test II) COLOGNE 18 ,9815 ,61007 ,14379 Sum variable interest in BREMEN media products about 50 ,9633 ,69276 ,09797 HIV/AIDS(pre-test) COLOGNE 25 1,1667 ,52042 ,10408 Communication sum (pre- BREMEN 49 2,1122 ,77906 ,11129 test) COLOGNE 24 2,3750 ,59436 ,12132 Communication sum (post- BREMEN 31 2,2581 ,98210 ,17639 test) COLOGNE 20 2,1000 ,86754 ,19399 Knowledge (information BREMEN included in game) sum (pre- 50 ,569091 ,2350685 ,0332437 test) COLOGNE 25 ,592727 ,2165978 ,0433196 Knowledge (information BREMEN included in game) sum (post- 23 ,588933 ,2207656 ,0460328 test) COLOGNE 11 ,702479 ,1353960 ,0408234 Knowledge (information not BREMEN included in game) sum (pre- 50 ,384444 ,1997857 ,0282540 test) COLOGNE 25 ,386667 ,1954208 ,0390842 Knowledge (information not BREMEN included in game) sum (post- 23 ,386473 ,1703946 ,0355297 test) COLOGNE 11 ,404040 ,2124096 ,0640439 Self-efficacy sum item 3-11 BREMEN 48 3,331019 ,7300412 ,1053724 (pre-test) COLOGNE 25 3,253333 ,7539471 ,1507894 Self-efficacy sum item 3-11 BREMEN 24 3,268519 ,8864197 ,1809397 (post-test) COLOGNE 11 3,353535 ,7450548 ,2246425 Intention sum (pre-test) BREMEN 50 ,8267 ,27962 ,03954 COLOGNE 24 ,8194 ,34021 ,06944 Intention sum (post-test) BREMEN 22 ,8636 ,24471 ,05217 COLOGNE 11 ,8182 ,27340 ,08243

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper Age Equal variances assumed 20,068 ,000 ,230 73 ,819 ,040 ,174 -,306 ,386 Equal variances not assumed ,174 26,666 ,863 ,040 ,230 -,431 ,511 Age first sexual intercousre Equal variances assumed ,113 ,741 -2,339 19 ,030 -1,067 ,456 -2,021 -,112 Equal variances not assumed -2,416 9,929 ,036 -1,067 ,441 -2,051 -,082 Number of partners Equal variances assumed 1,416 ,238 ,331 72 ,742 ,073 ,220 -,365 ,511 Equal variances not assumed ,365 62,934 ,716 ,073 ,199 -,325 ,470 Computer Equal variances assumed ,159 ,692 ,258 60 ,797 ,084 ,324 -,564 ,731 Equal variances not assumed ,254 38,645 ,801 ,084 ,329 -,583 ,750 Consoles Equal variances assumed ,538 ,466 -,774 61 ,442 -,190 ,246 -,683 ,302 Equal variances not assumed -,743 36,083 ,462 -,190 ,256 -,710 ,329 Portable Equal variances assumed ,500 ,482 -,834 61 ,407 -,238 ,285 -,809 ,332 Equal variances not assumed -,783 34,066 ,439 -,238 ,304 -,856 ,380 Cell Phone Equal variances assumed 2,368 ,129 -,612 61 ,543 -,214 ,350 -,915 ,486 Equal variances not assumed -,568 33,281 ,574 -,214 ,377 -,981 ,552 Computer game playing Equal variances time week day assumed ,063 ,803 ,943 61 ,349 18,929 20,073 -21,210 59,067 Equal variances not assumed ,963 42,365 ,341 18,929 19,666 -20,749 58,606 Computer game playing Equal variances time weekend day assumed ,325 ,571 ,619 60 ,539 20,436 33,040 -45,653 86,524 Equal variances not assumed ,612 39,217 ,544 20,436 33,414 -47,138 88,009 Skill Equal variances assumed ,080 ,778 1,911 61 ,061 ,619 ,324 -,029 1,267 Equal variances not assumed 1,865 37,633 ,070 ,619 ,332 -,053 1,291 Strategy/Simulation Equal variances assumed 7,053 ,010 -,770 61 ,444 -,262 ,340 -,942 ,418 Equal variances not assumed -,700 31,645 ,489 -,262 ,374 -1,024 ,500 Adventures Equal variances assumed ,263 ,610 ,421 61 ,675 ,119 ,283 -,446 ,684 Equal variances not assumed ,445 46,365 ,659 ,119 ,268 -,420 ,658 EgoShooter Equal variances assumed ,274 ,602 -,486 61 ,629 -,143 ,294 -,730 ,445 Equal variances not assumed -,488 40,511 ,628 -,143 ,293 -,734 ,448 Fight Equal variances assumed ,392 ,534 ,429 61 ,669 ,119 ,277 -,436 ,674 Equal variances not assumed ,414 36,599 ,681 ,119 ,287 -,463 ,702 Spielzeit_gesamt Equal variances assumed ,001 ,969 ,780 60 ,438 19,878 25,474 -31,077 70,833 Equal variances not assumed ,776 39,757 ,443 19,878 25,632 -31,936 71,692 Overall_playtime_tripartite Equal variances assumed ,420 ,519 1,095 60 ,278 ,240 ,220 -,199 ,680 Equal variances not assumed 1,072 38,188 ,291 ,240 ,224 -,214 ,694 Overall_hardware_tripartite Equal variances assumed ,217 ,643 -1,236 60 ,221 -,261 ,211 -,684 ,162 Equal variances not assumed -1,292 45,602 ,203 -,261 ,202 -,669 ,146 Computer game intensity Equal variances assumed ,176 ,676 -,055 59 ,957 -,018 ,327 -,672 ,637 Equal variances not assumed -,054 39,763 ,957 -,018 ,330 -,685 ,649 Sum variable risk Equal variances perception assumed ,658 ,420 -,147 73 ,884 -,02000 ,13603 -,29112 ,25112 Equal variances not assumed -,146 47,624 ,884 -,02000 ,13656 -,29462 ,25462 Pre_overall_interest_sum Equal variances assumed 3,146 ,080 -1,083 72 ,283 -,16000 ,14777 -,45458 ,13458 Equal variances not assumed -1,211 64,766 ,230 -,16000 ,13208 -,42379 ,10379 Post_I_overall_interest Equal variances _sum assumed 2,179 ,149 -,728 33 ,472 -,16540 ,22724 -,62774 ,29693 Equal variances not assumed -,826 26,860 ,416 -,16540 ,20013 -,57613 ,24532 Post_II_overall_interest Equal variances _sum assumed ,729 ,397 -,038 49 ,970 -,00860 ,22384 -,45843 ,44122 Equal variances not assumed -,039 42,795 ,969 -,00860 ,22035 -,45305 ,43584 sum_int_5er_pre Equal variances assumed 2,188 ,143 -2,163 73 ,034 -,640 ,296 -1,230 -,050 Equal variances not assumed -2,003 39,607 ,052 -,640 ,320 -1,286 ,006 sum_int_5er_post_I Equal variances assumed ,222 ,641 -,484 33 ,632 -,216 ,446 -1,123 ,692 Equal variances not assumed -,453 16,738 ,657 -,216 ,477 -1,223 ,791 interest_6bis11_post_II Equal variances assumed 1,453 ,235 -1,253 42 ,217 -,26353 ,21031 -,68795 ,16089 Equal variances not assumed -1,296 40,471 ,202 -,26353 ,20332 -,67432 ,14725 interest_6bis11_pre Equal variances assumed 1,897 ,173 -1,295 73 ,200 -,20333 ,15707 -,51637 ,10971 Equal variances not assumed -1,423 61,660 ,160 -,20333 ,14294 -,48910 ,08243 communication_pre Equal variances assumed 2,061 ,156 -1,456 71 ,150 -,26276 ,18048 -,62263 ,09712 Equal variances not assumed -1,596 58,236 ,116 -,26276 ,16464 -,59228 ,06677 communication_post Equal variances assumed ,771 ,384 ,587 49 ,560 ,15806 ,26941 -,38333 ,69946 Equal variances not assumed ,603 44,249 ,550 ,15806 ,26219 -,37027 ,68640 info_game_sum_pre Equal variances assumed ,110 ,741 -,421 73 ,675 -,0236364 ,0561326 -,1355084 ,0882357 Equal variances not assumed -,433 51,793 ,667 -,0236364 ,0546052 -,1332201 ,0859474 info_game_sum_post Equal variances assumed 3,446 ,073 -1,564 32 ,128 -,1135465 ,0726140 -,2614564 ,0343633 Equal variances not assumed -1,845 29,741 ,075 -,1135465 ,0615270 -,2392473 ,0121543 info_not in game_sum_pre Equal variances assumed ,869 ,354 -,046 73 ,964 -,0022222 ,0485884 -,0990588 ,0946143 Equal variances not assumed -,046 49,074 ,963 -,0022222 ,0482272 -,0991346 ,0946902 info_not in game_sum_post Equal variances assumed 1,108 ,300 -,260 32 ,797 -,0175670 ,0676557 -,1553770 ,1202431 Equal variances not assumed -,240 16,397 ,813 -,0175670 ,0732392 -,1725225 ,1373885 pre_selfefficacy_3b- Equal variances 11_sum assumed ,486 ,488 ,427 71 ,671 ,0776852 ,1820748 -,2853617 ,4407321 Equal variances not assumed ,422 47,392 ,675 ,0776852 ,1839586 -,2923111 ,4476815 post_selfefficacy_3bis11_s Equal variances um assumed ,451 ,507 -,276 33 ,784 -,0850168 ,3080657 -,7117813 ,5417476 Equal variances not assumed -,295 22,979 ,771 -,0850168 ,2884500 -,6817512 ,5117176 pre_intention_sum Equal variances assumed ,369 ,546 ,097 72 ,923 ,00722 ,07457 -,14144 ,15588 Equal variances not assumed ,090 38,437 ,928 ,00722 ,07991 -,15449 ,16894 post_intention_sum Equal variances assumed ,451 ,507 ,484 31 ,632 ,04545 ,09391 -,14608 ,23699 Equal variances not assumed ,466 18,224 ,647 ,04545 ,09756 -,15932 ,25023

Chi-squared tests

At which point in a relationship would you start using condoms?

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * 72 96,0% 3 4,0% 75 100,0% whenstopusingcondoms

Place* whenstopusingcondoms Crosstabulation

whenstopusingcondoms Total Only After relationships When I know hiv- with good After a about his sexual screeni friends while experiences ng test Place BREMEN Count 1 2 25 20 48 Expected 1,3 2,7 24,7 19,3 48,0 Count Std. Residual -,3 -,4 ,1 ,2 COLOGNE Count 1 2 12 9 24 Expected ,7 1,3 12,3 9,7 24,0 Count Std. Residual ,4 ,6 -,1 -,2 Total Count 2 4 37 29 72 Expected 2,0 4,0 37,0 29,0 72,0 Count

Chi-Square Tests

Asymp. Sig. Value df (2-sided) Pearson Chi-Square ,832(a) 3 ,842 Likelihood Ratio ,790 3 ,852 N of Valid Cases 72 a 4 cells (50,0%) have expected count less than 5. The minimum expected count is ,67.

Relationship status

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Ort * beziehung 75 100,0% 0 ,0% 75 100,0%

Place * relationship Crosstabulation

relationshio Total Not dating anyone Boyfriend, other Place BREMEN Count 30 19 1 50 Expected Count 31,3 17,3 1,3 50,0 Std. Residual -,2 ,4 -,3 COLOGNE Count 17 7 1 25 Expected Count 15,7 8,7 ,7 25,0 Std. Residual ,3 -,6 ,4 Total Count 47 26 2 75 Expected Count 47,0 26,0 2,0 75,0

Chi-Square Tests

Asymp. Sig. Value df (2-sided) Pearson Chi-Square ,901(a) 2 ,637 Likelihood Ratio ,902 2 ,637 N of Valid Cases 75 a 2 cells (33,3%) have expected count less than 5. The minimum expected count is ,67.

Playing digital games – yes/no

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * playing? 75 100,0% 0 ,0% 75 100,0%

Place * playing? Crosstabulation

Do you play digital games? Total ja nein Place BREMEN Count 43 7 50 Expected Count 42,7 7,3 50,0 Std. Residual ,1 -,1 COLOGNE Count 21 4 25 Expected Count 21,3 3,7 25,0 Std. Residual -,1 ,2 Total Count 64 11 75 Expected Count 64,0 11,0 75,0

Chi-Square Tests

Asymp. Sig. Exact Sig. Value df (2-sided) (2-sided) Exact Sig. (1-sided) Pearson Chi-Square ,053(b) 1 ,817 Continuity Correction(a) ,000 1 1,000 Likelihood Ratio ,053 1 ,819 Fisher's Exact Test 1,000 ,534 N of Valid Cases 75 a Computed only for a 2x2 table b 1 cells (25,0%) have expected count less than 5. The minimum expected count is 3,67. Sum variable computer game playing intensity

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * playing intensity_tripartite 61 81,3% 14 18,7% 75 100,0%

Place * playing intensity_tripartite Crosstabulation

playing intensity_tripartite Total 1 2 3 Place BREMEN Count 12 13 15 40

Expected Count 13,1 11,8 15,1 40,0 Std. Residual -,3 ,3 ,0 COLOGNE Count 8 5 8 21 Expected Count 6,9 6,2 7,9 21,0 Std. Residual ,4 -,5 ,0 Total Count 20 18 23 61 Expected Count 20,0 18,0 23,0 61,0

Chi-Square Tests

Asymp. Sig. Value df (2-sided) Pearson Chi-Square ,629(a) 2 ,730 Likelihood Ratio ,635 2 ,728 N of Valid Cases 61 a 0 cells (,0%) have expected count less than 5. The minimum expected count is 6,20. Bremen/Cologne – Solomon-Four-Group Design

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * group 75 100,0% 0 ,0% 75 100,0%

Place * group Crosstabulation

Group Total Experimental Kontroll- Kontroll- Kontroll- Gruppe gruppe 1 gruppe 2 gruppe 3 Place BREMEN Count 12 12 13 13 50 Expected 11,3 12,0 11,3 15,3 50,0 Count Std. Residual ,2 ,0 ,5 -,6 COLOGNE Count 5 6 4 10 25 Expected 5,7 6,0 5,7 7,7 25,0 Count Std. Residual -,3 ,0 -,7 ,8 Total Count 17 18 17 23 75 Expected 17,0 18,0 17,0 23,0 75,0 Count

Chi-Square Tests

Asymp. Sig. Value df (2-sided) Pearson Chi-Square 1,918(a) 3 ,590 Likelihood Ratio 1,923 3 ,589 N of Valid Cases 75 a 0 cells (,0%) have expected count less than 5. The minimum expected count is 5,67. Sexual intercourse experience (dichotomous)

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * 74 98,7% 1 1,3% 75 100,0% intercourse

Place * intercourse Crosstabulation

intercourse Total ja nein Place BREMEN Count 15 34 49 Expected Count 13,9 35,1 49,0 Std. Residual ,3 -,2 COLOGNE Count 6 19 25 Expected Count 7,1 17,9 25,0 Std. Residual -,4 ,3 Total Count 21 53 74 Expected Count 21,0 53,0 74,0

Chi-Square Tests

Asymp. Sig. Exact Sig. Exact Sig. Value df (2-sided) (2-sided) (1-sided) Pearson Chi-Square ,356(b) 1 ,551 Continuity Correction(a) ,105 1 ,746 Likelihood Ratio ,362 1 ,547 Fisher's Exact Test ,598 ,378 N of Valid Cases 74 a Computed only for a 2x2 table b 0 cells (,0%) have expected count less than 5. The minimum expected count is 7,09. Would you use condoms?

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place* condom use 73 97,3% 2 2,7% 75 100,0%

Place * condom use Crosstabulation

Condom use Total Yes, but Yes, sometimes No realationships always not with foreigners Place BREMEN Count 33 4 12 49 Expected 36,2 3,4 9,4 49,0 Count Std. Residual -,5 ,4 ,8 COLOGNE Count 21 1 2 24 Expected 17,8 1,6 4,6 24,0 Count Std. Residual ,8 -,5 -1,2 Total Count 54 5 14 73 Expected 54,0 5,0 14,0 73,0 Count

Chi-Square Tests

Asymp. Sig. Value df (2-sided) Pearson Chi-Square 3,453(a) 2 ,178 Likelihood Ratio 3,804 2 ,149 N of Valid Cases 73 a 3 cells (50,0%) have expected count less than 5. The minimum expected count is 1,64. More than one partner within the last year?

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * more than 74 98,7% 1 1,3% 75 100,0% one partner

Place * more than one partner Crosstabulation

more than one partner Total yes no Place BREMEN Count 8 41 49 Expected Count 7,9 41,1 49,0 Std. Residual ,0 ,0 COLOGNE Count 4 21 25 Expected Count 4,1 20,9 25,0 Std. Residual ,0 ,0 Total Count 12 62 74 Expected Count 12,0 62,0 74,0

Chi-Square Tests

Asymp. Sig. Exact Sig. Exact Sig. Value df (2-sided) (2-sided) (1-sided) Pearson Chi-Square ,001(b) 1 ,971 Continuity Correction(a) ,000 1 1,000 Likelihood Ratio ,001 1 ,971 Fisher's Exact Test 1,000 ,625 N of Valid Cases 74 a Computed only for a 2x2 table b 1 cells (25,0%) have expected count less than 5. The minimum expected count is 4,05. Level of school education aimed for

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * school 75 100,0% 0 ,0% 75 100,0%

Place * school Crosstabulation

School Total Fachhochs Hauptschule Realschule chule Abitur Place BREMEN Count 2 27 2 19 50 Expected 4,7 24,7 1,3 19,3 50,0 Count Std. -1,2 ,5 ,6 -,1 Residual COLOGNE Count 5 10 0 10 25 Expected 2,3 12,3 ,7 9,7 25,0 Count Std. 1,7 -,7 -,8 ,1 Residual Total Count 7 37 2 29 75 Expected 7,0 37,0 2,0 29,0 75,0 Count

Chi-Square Tests

Asymp. Sig. Value df (2-sided) Pearson Chi-Square 6,251(a) 3 ,100 Likelihood Ratio 6,558 3 ,087 N of Valid Cases 75 a 4 cells (50,0%) have expected count less than 5. The minimum expected count is ,67. Have you been sexually active within the last 12 months?

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * sexual active 12 74 98,7% 1 1,3% 75 100,0% months

Place * sexual active 12 months Crosstabulation

sexual active 12 months Total yes no Place BREMEN Count 19 30 49 Expected Count 19,2 29,8 49,0 Std. Residual ,0 ,0 COLOGNE Count 10 15 25 Expected Count 9,8 15,2 25,0 Std. Residual ,1 -,1 Total Count 29 45 74 Expected Count 29,0 45,0 74,0

Chi-Square Tests

Asymp. Sig. Exact Sig. Exact Sig. ( Value df (2-sided) (2-sided) 1-sided) Pearson Chi-Square ,010(b) 1 ,919 Continuity Correction(a) ,000 1 1,000 Likelihood Ratio ,010 1 ,919 Fisher's Exact Test 1,000 ,557 N of Valid Cases 74 a Computed only for a 2x2 table b 0 cells (,0%) have expected count less than 5. The minimum expected count is 9,80. Sexual orientation

Case Processing Summary

Cases Valid Missing Total N Percent N Percent N Percent Place * sexual 74 98,7% 1 1,3% 75 100,0% orientation

Place * sexual orientation Crosstabulation

Sexual orientation Total Do not heterosexual homosexual bisexual know Place BREMEN Count 46 0 3 0 49 Expected Count 45,7 ,7 2,0 ,7 49,0 Std. Residual ,0 -,8 ,7 -,8 COLOGNE Count 23 1 0 1 25 Expected Count 23,3 ,3 1,0 ,3 25,0 Std. Residual -,1 1,1 -1,0 1,1 Total Count 69 1 3 1 74 Expected Count 69,0 1,0 3,0 1,0 74,0

Chi-Square Tests

Asymp. Sig. Value df (2-sided) Pearson Chi-Square 5,457(a) 3 ,141 Likelihood Ratio 6,820 3 ,078 N of Valid Cases 74 a 6 cells (75,0%) have expected count less than 5. The minimum expected count is ,34. Bremen/Cologne difference between age of first sexual intercourse – additional analyses

Mann-Whitney-Test – with variable “How much time went by since a girl had her first sexual intercourse”

Ränge

Summe der Place H Mittlerer Rang Ränge Für GV-Erfahrene wie Bremen 49 38,50 1886,50 B1/Alle GV-Unerfahrenen Köln 25 35,54 888,50 erhalten den arbiträren Wert Gesamtsumme 74 -.01

Teststatistikena Für GV- Erfahrene wie B1/Alle GV- Unerfahrenen erhalten den arbiträren Wert - .01 Mann-Whitney-U-Test 563,500 Wilcoxon-W 888,500 U -,705 Asymp. Sig. (2-seitig) ,481 a. Gruppierungsvariable: Stadt

Mann-Whitney-Test – with variable “Difference between the mean age of girls with sexual intercourse experience and the current age of girls without sexual intercourse experience”

Ränge

Summe der Stadt H Mittlerer Rang Ränge Für GV-Erfahrene Differenz Bremen 49 36,56 1791,50 zwischen Alter und erstem Köln 25 39,34 983,50 GV/Für GV-Unerfahrene Gesamtsumme Differenz zwischen eigenem 74 Alter und Durchschnittsalter der Erfahrenen

Teststatistikena Für GV- Erfahrene Differenz zwischen Alter und erstem GV/Für GV- Unerfahrene Differenz zwischen eigenem Alter und Durchschnittsalte r der Erfahrenen Mann-Whitney-U-Test 566,500 Wilcoxon-W 1791,500 U -,559 Asymp. Sig. (2-seitig) ,576 a. Gruppierungsvariable: Stadt

Data Reduction

Factor Analysis

Un-rotated factor analysis for all items of the involvement questionnaire.

Total Variance Explained

Component Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % 1 10,861 43,444 43,444 10,861 43,444 43,444 2 3,174 12,695 56,139 3,174 12,695 56,139 3 2,365 9,461 65,600 2,365 9,461 65,600 4 1,570 6,280 71,880 1,570 6,280 71,880 5 1,058 4,232 76,112 1,058 4,232 76,112 6 1,039 4,157 80,269 1,039 4,157 80,269 7 ,770 3,082 83,350 8 ,690 2,760 86,110 9 ,553 2,211 88,322 10 ,486 1,944 90,266 11 ,446 1,783 92,049 12 ,371 1,483 93,533 13 ,342 1,368 94,901 14 ,294 1,174 96,075 15 ,197 ,788 96,863 16 ,192 ,769 97,632 17 ,170 ,682 98,314 18 ,109 ,437 98,751 19 ,085 ,341 99,091 20 ,071 ,284 99,375 21 ,059 ,237 99,611 22 ,050 ,201 99,813 23 ,030 ,119 99,931 24 ,011 ,043 99,974 25 ,006 ,026 100,000 Extraction Method: Principal Component Analysis.

Scree Plot

12

10

8

6 Eigenvalue 4

2

0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Component Number

Component Matrix(a)

Component 1 2 3 4 5 6 RFU_2_Zeit_im_Flug ,643 ,207 ,092 -,050 -,406 -,158 Gefesselt_vom_Spiel_Klimmt ,546 ,186 ,218 -,106 ,366 ,458

RFU_2_meine_Welt ,680 ,003 ,126 -,281 -,250 ,391 Spielgeschehen_Versunken_Kl immt ,910 ,194 -,188 -,078 -,049 -,008 Rolle_als_Heldin_Klimmt ,791 -,166 -,328 ,098 ,224 -,033 RFU_4_in_Welt_versetzt ,721 -,218 -,355 -,120 ,048 ,173 RFU_2_realer_als_Welt ,466 ,309 ,113 -,660 -,071 -,386 RFU_2_Welt_vergessen ,687 -,282 -,376 -,069 -,146 ,045 RFU_1_konzentriert ,788 ,307 -,198 -,060 -,066 -,143 RFU_8_Spass_gemacht ,807 -,006 ,234 ,299 -,304 ,035 RFU_4_anderer_Ort ,403 -,609 -,294 ,027 -,181 ,184 RFU_2_in_Welt_eingetaucht ,776 -,159 -,197 -,354 ,021 -,206

RFU_4_in_computerwelt ,776 -,335 -,330 ,034 ,071 -,036 RFU_8_Freude ,643 -,144 ,266 ,536 ,234 -,071 RFU_8_unterhaltsam ,587 -,125 ,506 ,321 ,105 -,342 zuhause_spielen_YT ,558 -,001 ,625 -,298 ,039 ,255 Freundinnen_Empfehlen_YT ,680 -,103 ,552 -,168 ,244 ,099

RFU_4_Reise_anderer_Ort ,686 -,582 -,019 ,112 ,100 -,112

RFU_8_gefallen ,764 -,080 ,418 -,032 -,079 -,271 RFU_4_selbst_im_Computers piel ,716 -,378 -,209 ,045 ,185 -,021 RFU_1_nicht_Gedanken_auf_ Spiel_Zwingen ,541 ,544 -,314 -,012 ,265 -,021

RFU_1_Gedanken_nicht_abge schweift ,385 ,538 -,257 ,402 -,179 -,009 RFU_1_nicht_abgelenkt ,550 ,661 -,199 ,141 -,070 ,217 RFU_1_nicht_an_anderes_ged acht ,318 ,760 -,116 ,017 ,340 -,111 RFU_8_länger_dauern ,665 ,266 ,286 ,287 -,284 ,162 Extraction Method: Principal Component Analysis. a 6 components extracted.

Factor analysis was with the adjustment to create one factor only

Total Variance Explained

Component Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % 1 10,861 43,444 43,444 10,861 43,444 43,444 2 3,174 12,695 56,139 3 2,365 9,461 65,600 4 1,570 6,280 71,880 5 1,058 4,232 76,112 6 1,039 4,157 80,269 7 ,770 3,082 83,350 8 ,690 2,760 86,110 9 ,553 2,211 88,322 10 ,486 1,944 90,266 11 ,446 1,783 92,049 12 ,371 1,483 93,533 13 ,342 1,368 94,901 14 ,294 1,174 96,075 15 ,197 ,788 96,863 16 ,192 ,769 97,632 17 ,170 ,682 98,314 18 ,109 ,437 98,751 19 ,085 ,341 99,091 20 ,071 ,284 99,375 21 ,059 ,237 99,611 22 ,050 ,201 99,813 23 ,030 ,119 99,931 24 ,011 ,043 99,974 25 ,006 ,026 100,000 Extraction Method: Principal Component Analysis.

Scree Plot

12

10

8

6 Eigenvalue 4

2

0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Component Number

Component Matrix(a)

Component

1 RFU_2_Zeit_im_Flug ,643 Gefesselt_vom_Spiel_Klimmt ,546

RFU_2_meine_Welt ,680 Spielgeschehen_Versunken_ Klimmt ,910 Rolle_als_Heldin_Klimmt ,791 RFU_4_in_Welt_versetzt ,721 RFU_2_realer_als_Welt ,466 RFU_2_Welt_vergessen ,687 RFU_1_konzentriert ,788 RFU_8_Spass_gemacht ,807 RFU_4_anderer_Ort ,403 RFU_2_in_Welt_eingetaucht ,776

RFU_4_in_computerwelt ,776 RFU_8_Freude ,643 RFU_8_unterhaltsam ,587 zuhause_spielen_YT ,558 Freundinnen_Empfehlen_YT ,680

RFU_4_Reise_anderer_Ort ,686

RFU_8_gefallen ,764 RFU_4_selbst_im_Computer spiel ,716 RFU_1_nicht_Gedanken_auf _Spiel_Zwingen ,541

RFU_1_Gedanken_nicht_ab geschweift ,385 RFU_1_nicht_abgelenkt ,550 RFU_1_nicht_an_anderes_g edacht ,318 RFU_8_länger_dauern ,665 Extraction Method: Principal Component Analysis. a 1 components extracted.

Descriptive Statistics

Sexual behavior

Status of Relationship Frequency Percent Valid Cumulative Percent Percent

No boyfriend 47 62,7 62,7 62,7 Boyfriend 26 34,7 34,7 97,3 Miscellaneous 2 2,7 2,7 100,0 (e.g., “I have a girlfriend”)

Sexual orientation

Valid Cumulative Frequency Percent Percent Percent

Valid Heterosexual 69 92,0 93,2 93,2 Homosexual 1 1,3 1,4 94,6 Bisexual 3 4,0 4,1 98,6 I don’t know 1 1,3 1,4 100,0 Total 74 98,7 100,0 Missing Missing 1 1,3 Total 75 100,0

Sexual intercourse

Do you have had sexual intercourse?

Frequency Percent Valid Cumulative Percent Percent Valid Yes 21 28,0 28,4 28,4 No 53 70,7 71,6 100,0 Total 74 98,7 100,0 Missing 1 1,3 Total 75 100,0

Age of first sexual intercourse

Age Frequency Percent Valid Cumulative Percent Percent Valid 12 1 1,3 4,8 4,8 13 4 5,3 19,0 23,8 14 7 9,3 33,3 57,1 15 7 9,3 33,3 90,5 16 2 2,7 9,5 100,0 Total 21 28,0 100,0 Missing No sexual intercourse 54 72,0 Total 75 100,0

Would you use condoms?

Frequency Percent Valid Cumulative Percent Percent Valid Yes, always 54 72,0 74,0 74,0 Yes, but sometimes I might 5 6,7 6,8 80,8 forget No relationships with 14 18,7 19,2 100,0 unknown persons Total 73 97,3 100,0 Missing Missing 2 2,7 Total 75 100,0

At which point would you stop using condoms?

Frequency Percent Valid Cumulative Percent Percent Valid From the beginning, because 2 2,7 2,8 2,8 I would only have sexual relationships with someone I know very well

After a while 4 5,3 5,6 8,3

When I know more about his 37 49,3 51,4 59,7 sexual past life and trust him

After negative HIV-test 29 38,7 40,3 100,0

Total 72 96,0 100,0 Missing Missing 3 4,0 Total 75 100,0

Computer game playing

Do you play digital games?

Valid Cumulative Frequency Percent Percent Percent Valid Yes 64 85,3 85,3 85,3 No 11 14,7 14,7 100,0 Total 75 100,0 100,0

How often do you play digital games with…

… a Computer?

Valid Cumulative Frequency Percent Percent Percent Valid Never 3 4,0 4,8 4,8 at least once a month 12 16,0 19,4 24,2 several times per month 14 18,7 22,6 46,8 several times per week 18 24,0 29,0 75,8 Daily 15 20,0 24,2 100,0 Total 62 82,7 100,0 Missing Missing 13 17,3 Total 75 100,0

... a game console?

Valid Cumulative Frequency Percent Percent Percent Valid Never 18 24,0 28,6 28,6 At least once a month 25 33,3 39,7 68,3 Several times per month 15 20,0 23,8 92,1 Several times per week 5 6,7 7,9 100,0 Total 63 84,0 100,0 Missing Missing 12 16,0 Total 75 100,0

...with portable game consoles?

Valid Cumulative Frequency Percent Percent Percent Valid Never 33 44,0 52,4 52,4 at least once a month 18 24,0 28,6 81,0 several times per month 6 8,0 9,5 90,5 several times per week 4 5,3 6,3 96,8 Daily 2 2,7 3,2 100,0 Total 63 84,0 100,0 Missing Missing 12 16,0 Total 75 100,0

…on a cellular phone?

Valid Cumulative Frequency Percent Percent Percent Valid Never 5 6,7 7,9 7,9 at least once a month 12 16,0 19,0 27,0 several times per month 15 20,0 23,8 50,8 several times per week 13 17,3 20,6 71,4 Daily 18 24,0 28,6 100,0 Total 63 84,0 100,0 Missing Missing 12 16,0 Total 75 100,0

How long do you play digital games during a normal weekday / weekend day?

N Minimum Maximum Mean Std. Deviation Minutes during weekdays 63 10 360 99,76 75,040

Minutes at weekends 62 10 540 171,37 122,498

How often do you play…

…games of (mental) skills

Valid Cumulative Frequency Percent Percent Percent Valid Never 6 8,0 9,5 9,5

Seldom 15 20,0 23,8 33,3 Sometimes 18 24,0 28,6 61,9 Often 13 17,3 20,6 82,5 very often 11 14,7 17,5 100,0 Total 63 84,0 100,0 Missing Missing 12 16,0 Total 75 100,0

...Strategy and simulation games?

Valid Cumulative Frequency Percent Percent Percent Valid Never 8 10,7 12,7 12,7

Seldom 14 18,7 22,2 34,9 Sometimes 17 22,7 27,0 61,9 Often 14 18,7 22,2 84,1 very often 10 13,3 15,9 100,0 Total 63 84,0 100,0 Missing Missing 12 16,0 Total 75 100,0

... Adventure games?

Valid Cumulative Frequency Percent Percent Percent Valid Never 32 42,7 50,8 50,8

Seldom 16 21,3 25,4 76,2 Sometimes 9 12,0 14,3 90,5 Often 5 6,7 7,9 98,4 very often 1 1,3 1,6 100,0 Total 63 84,0 100,0 Missing Missing 12 16,0 Total 75 100,0

... First-person ego shooter games?

Valid Cumulative Frequency Percent Percent Percent Valid Never 42 56,0 66,7 66,7

Seldom 7 9,3 11,1 77,8 Sometimes 9 12,0 14,3 92,1 Often 3 4,0 4,8 96,8 very often 2 2,7 3,2 100,0 Total 63 84,0 100,0 Missing Missing 12 16,0 Total 75 100,0

... fighting games?

Valid Cumulative Frequency Percent Percent Percent Valid Never 35 46,7 55,6 55,6

Seldom 16 21,3 25,4 81,0 Sometimes 6 8,0 9,5 90,5 Often 5 6,7 7,9 98,4 very often 1 1,3 1,6 100,0 Total 63 84,0 100,0 Missing Missing 12 16,0 Total 75 100,0

Which games do you play? (Multiple answers possible)

Valid Cumulative Frequency Percent Percent Percent Valid 3 Engel für Charlie 1 ,7 ,7 ,7 Autorennen 1 ,7 ,7 1,3 Backgammon 1 ,7 ,7 2,0 Billard 1 ,7 ,7 2,6 Black & White 2 1,3 1,3 3,9 Buzz 1 ,7 ,7 4,6 Cars 1 ,7 ,7 5,2 Chatten 2 1,3 1,3 6,5 Counterstrike 3 2,0 2,0 8,5 Deutschland Superst 1 ,7 ,7 9,2 FiFa 2 1,3 1,3 10,5 Final Fantasy 2 1,3 1,3 11,8 Fluch der Karibik 1 ,7 ,7 12,4 Freecell 2 1,3 1,3 13,7 GTA 3 2,0 2,0 15,7 Happy tree friends 1 ,7 ,7 16,3 Harry Potter 2 1,3 1,3 17,6 ICQ 2 1,3 1,3 19,0 Internet 1 ,7 ,7 19,6 Ju-Gi-Oh Nightmares 1 ,7 ,7 20,3 Karten 1 ,7 ,7 20,9 Kingdom Hearts 2 1 ,7 ,7 21,6 Luma 1 ,7 ,7 22,2 Mafia 1 ,7 ,7 22,9 Mahjong 1 ,7 ,7 23,5 Maxi und Mini 1 ,7 ,7 24,2 Mind Quiz 1 ,7 ,7 24,8 Minesweeper 1 ,7 ,7 25,5 Moorhuhn 1 ,7 ,7 26,1 Motorraver Trial 1 ,7 ,7 26,8 MSN 1 ,7 ,7 27,5 Musikspiel 1 ,7 ,7 28,1 My Boyfriend 1 ,7 ,7 28,8 Need4Speed 3 2,0 2,0 30,7 Nintendogs 1 ,7 ,7 31,4 No one lives foreve 1 ,7 ,7 32,0 Noten (Handyspiel) 1 ,7 ,7 32,7 Online Games 1 ,7 ,7 33,3 Pinball 1 ,7 ,7 34,0 Rebels 1 ,7 ,7 34,6 Rollenspiele 1 ,7 ,7 35,3 Shanghai 1 ,7 ,7 35,9 Simpsons 1 ,7 ,7 36,6 Sims 30 19,6 19,6 56,2 Sing Star 10 6,5 6,5 62,7 Singles 2 1,3 1,3 64,1 Ski-Langlauf 1 ,7 ,7 64,7 Slide-a-Lama 1 ,7 ,7 65,4 Snake 5 3,3 3,3 68,6 Solitär 4 2,6 2,6 71,2 Spellforce 1 ,7 ,7 71,9 Spieleaffe 1 ,7 ,7 72,5 Spiro 1 ,7 ,7 73,2 Spongebob 1 ,7 ,7 73,9 Sudoku 1 ,7 ,7 74,5 Super Mario 11 7,2 7,2 81,7 Sven das Schaf 1 ,7 ,7 82,4 Tekken 2 1,3 1,3 83,7 Tetris 10 6,5 6,5 90,2 Tombraider 4 2,6 2,6 92,8 Tony Hawks 1 ,7 ,7 93,5 Under the knife 1 ,7 ,7 94,1 Vier gewinnt 1 ,7 ,7 94,8 Warcraft 1 ,7 ,7 95,4 Wer wird Millionär 1 ,7 ,7 96,1 Wiggles 2 1,3 1,3 97,4 Zooplaoola 2 1,3 1,3 98,7 Zootycoon 1 ,7 ,7 99,3 Zuma 1 ,7 ,7 100,0 Total 153 100,0 100,0

Involvement

Playing “Supergöre” was fun.

Percent Valid Cumulative Percent Percent Valid I strongly disagree 1,3 2,9 2,9

I disagree 4,0 8,8 11,8 I somewhat disagree 2,7 5,9 17,6

I somewhat agree 10,7 23,5 41,2

I agree 20,0 44,1 85,3 I strongly agree 6,7 14,7 100,0

Total 45,3 100,0 Missing System 54,7 Total 100,0

Would play “Supergöre“ at home

Percent Valid Cumulative Percent Percent Valid I strongly disagree 9,3 21,2 21,2

I disagree 6,7 15,2 36,4

I somewhat disagree 2,7 6,1 42,4

I somewhat agree 9,3 21,2 63,6

I agree 12,0 27,3 90,9

I strongly disagree 4,0 9,1 100,0

Total 44,0 100,0 Missing Missing 1,3 System 54,7 Total 56,0 Total 100,0

I would recommend “Supergöre“ to friends

Percent Valid Cumulative Percent Percent Valid I strongly disagree 8,0 18,8 18,8

I disagree 9,3 21,9 40,6

I somewhat disagree 8,0 18,8 59,4

I somewhat agree 6,7 15,6 75,0

I agree 6,7 15,6 90,6

I strongly agree 4,0 9,4 100,0

Total 42,7 100,0 Missing Missing 1,3 System 56,0 Total 57,3 Total 100,0

Risk perception

What do you think: How likely is it that you will be infected with HIV through sexual activities within the next 10 years?

Valid Cumulative Percent Percent Percent Valid Extremely unlikely 18,7 18,7 18,7 Very unlikely 26,7 26,7 45,3 Quite unlikely 21,3 21,3 66,7 Neither 24,0 24,0 90,7 Quite likely 9,3 9,3 100,0 Total 100,0 100,0

What do you think: How likely is it that other girls at them same age and life situation will be infected with HIV through sexual activities within the next 10 years?

Valid Cumulative Percent Percent Percent Valid Extremely unlikely 1,3 1,3 1,3 Very unlikely 9,3 9,3 10,7 Quite unlikely 16,0 16,0 26,7 Neither 28,0 28,0 54,7 Quite likely 20,0 20,0 74,7 Very likely 18,7 18,7 93,3 Extremely likely 6,7 6,7 100,0 Total 100,0 100,0

I am at risk to be infected with HIV

Valid Cumulative Percent Percent Percent Valid Strongly disagree 22,7 22,7 22,7 Inclined to disagree 41,3 41,3 64,0 I don’t know 22,7 22,7 86,7 Inclined to agree 8,0 8,0 94,7 Strongly agree 5,3 5,3 100,0 Total 100,0 100,0

It might be that I am infected with HIV/AIDS

Valid Cumulative Percent Percent Percent Valid Strongly disagree 73,3 73,3 73,3 Inclined to disagree 17,3 17,3 90,7 I don’t know 6,7 6,7 97,3 Inclined to agree 2,7 2,7 100,0 Total 100,0 100,0

It might be that I had sex with somebody who is at risk of being infected with HIV/AIDS

Valid Cumulative Percent Percent Percent Valid Strongly disagree 81,3 81,3 81,3 Inclined to disagree 9,3 9,3 90,7 I don’t know 8,0 8,0 98,7 Inclined to agree 1,3 1,3 100,0 Total 100,0 100,0

My sexual experiences are risky concerning HIV/AIDS

Valid Cumulative Percent Percent Percent Valid Strongly disagree 72,0 72,0 72,0 Inclined to disagree 16,0 16,0 88,0 I don’t know 9,3 9,3 97,3 Inclined to agree 2,7 2,7 100,0 Total 100,0 100,0

Self-efficacy

Able to use condoms?

Percent Valid Cumulative Percent Percent Valid Quite unlikely 5,3 5,4 5,4

Somewhat unlikely 4,0 4,1 9,5

Do not know 16,0 16,2 25,7

Somewhat likely 5,3 5,4 31,1

Quite likely 21,3 21,6 52,7

In all probability 46,7 47,3 100,0

Total 98,7 100,0 Missing Missing 1,3 Total 100,0

Is condom use difficult or easy?

Percent Valid Cumulative Percent Percent Valid Very easy 21,3 21,3 21,3

Quite easy 18,7 18,7 40,0

Somewhat easy 18,7 18,7 58,7

Do not know 16,0 16,0 74,7

Somewhat difficult 18,7 18,7 93,3

Quite difficult 2,7 2,7 96,0

Very difficult 4,0 4,0 100,0

Total 100,0 100,0

Knowledge about HIV/AIDS and condom use (pre-tests)

Item No. 1: “Condoms protect against an HIV infection when they are used during oral sex”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 7 9,3 9,3 9,3 I don’t know 16 21,3 21,3 30,7 That’s right 52 69,3 69,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 1

Valid Cumulative Frequency Percent Percent Percent Valid False answer 7 9,3 9,3 9,3 Don’t know 16 21,3 21,3 30,7 Right answer 52 69,3 69,3 100,0 Total 75 100,0 100,0

Item No. 2: “If a condoms’ packing is broken the condom should not be used anymore”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 2 2,7 2,7 2,7 I don’t know 2 2,7 2,7 5,3 That’s right 71 94,7 94,7 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 2

Valid Cumulative Frequency Percent Percent Percent Valid False answer 2 2,7 2,7 2,7 Don’t know 2 2,7 2,7 5,3 Right answer 71 94,7 94,7 100,0 Total 75 100,0 100,0

Item No. 3: “A condom can be used more than once”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 74 98,7 98,7 98,7 Don’t know 1 1,3 1,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 3

Valid Cumulative Frequency Percent Percent Percent Valid Don’t know 1 1,3 1,3 1,3 Right answer 74 98,7 98,7 100,0 Total 75 100,0 100,0

Item No. 4: “Before using a condom its intactness should be tested by rolling it out”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 26 34,7 34,7 34,7 I don’t know 19 25,3 25,3 60,0 That’s right 30 40,0 40,0 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 4

Valid Cumulative Frequency Percent Percent Percent Valid False answer 30 40,0 40,0 40,0 Don’t know 19 25,3 25,3 65,3 Right answer 26 34,7 34,7 100,0 Total 75 100,0 100,0

Item No. 5: “Condoms can be used together with cream (e.g., Nivea)”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 40 53,3 53,3 53,3 I don’t know 26 34,7 34,7 88,0 That’s right 9 12,0 12,0 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 5

Valid Cumulative Frequency Percent Percent Percent Valid False answer 9 12,0 12,0 12,0 Don’t know 26 34,7 34,7 46,7 Right answer 40 53,3 53,3 100,0 Total 75 100,0 100,0

Item No. 6: “The Pill does not protect against an HIV infection”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 15 20,0 20,0 20,0 I don’t know 4 5,3 5,3 25,3 That’s right 56 74,7 74,7 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 6

Valid Cumulative Frequency Percent Percent Percent Valid False answer 15 20,0 20,0 20,0 Don’t know 4 5,3 5,3 25,3 Right answer 56 74,7 74,7 100,0 Total 75 100,0 100,0

Item No. 7: “Natural gut condoms protect against an HIV infection”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 12 16,0 16,0 16,0 I don’t know 53 70,7 70,7 86,7 That’s right 10 13,3 13,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 7

Valid Cumulative Frequency Percent Percent Percent Valid False answer 10 13,3 13,3 13,3 Don’t know 53 70,7 70,7 84,0 Right answer 12 16,0 16,0 100,0 Total 75 100,0 100,0

Item No. 8: “To use two condoms at the same time is much safer”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 45 60,0 60,0 60,0 I don’t know 17 22,7 22,7 82,7 That’s right 13 17,3 17,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 8

Valid Cumulative Frequency Percent Percent Percent Valid False answer 13 17,3 17,3 17,3 Don’t know 17 22,7 22,7 40,0 Right answer 45 60,0 60,0 100,0 Total 75 100,0 100,0

Item No. 9 “By kissing you can be infected with HIV”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 65 86,7 86,7 86,7 I don’t know 6 8,0 8,0 94,7 That’s right 4 5,3 5,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 9

Valid Cumulative Frequency Percent Percent Percent Valid False answer 4 5,3 5,3 5,3 Don’t know 6 8,0 8,0 13,3 Right answer 65 86,7 86,7 100,0 Total 75 100,0 100,0

Item No. 10: “The morning-after pill protects against an HIV infection”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 70 93,3 93,3 93,3 Don’t know 5 6,7 6,7 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 10

Valid Cumulative Frequency Percent Percent Percent Valid False answer 5 6,7 6,7 6,7 Don’t know 70 93,3 93,3 100,0 Right answer 75 100,0 100,0

Item No. 11: “Branded condoms have a CE-label and a testing number”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 1 1,3 1,3 1,3 I don’t know 46 61,3 61,3 62,7 That’s right 28 37,3 37,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 11

Valid Cumulative Frequency Percent Percent Percent Valid False answer 1 1,3 1,3 1,3 Don’t know 46 61,3 61,3 62,7 Right answer 28 37,3 37,3 100,0 Total 75 100,0 100,0

Item No. 12. “You can be infected with HIV by hugging another person”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 72 96,0 96,0 96,0 I don’t know 1 1,3 1,3 97,3 That’s right 2 2,7 2,7 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 12

Valid Cumulative Frequency Percent Percent Percent Valid falsch 2 2,7 2,7 2,7 weiss nicht 1 1,3 1,3 4,0 richtig 72 96,0 96,0 100,0 Total 75 100,0 100,0

Item No. 13: “When correctly performed, safe sex protects against HIV”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 17 22,7 22,7 22,7 I don’t know 23 30,7 30,7 53,3 That’s right 35 46,7 46,7 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 13

Valid Cumulative Frequency Percent Percent Percent Valid falsch 17 22,7 22,7 22,7 weiss nicht 23 30,7 30,7 53,3 richtig 35 46,7 46,7 100,0 Total 75 100,0 100,0

Item No. 14: “Pressure (e.g., from being in a wallet) does not harm condoms”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 28 37,3 37,3 37,3 I don’t know 28 37,3 37,3 74,7 That’s right 19 25,3 25,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 14

Valid Cumulative Frequency Percent Percent Percent Valid False answer 19 25,3 25,3 25,3 Don’t know 28 37,3 37,3 62,7 Right answer 28 37,3 37,3 100,0 Total 75 100,0 100,0

Item No. 15: “An HIV infection may occur even while using a vaginal suppository”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 1 1,3 1,3 1,3 I don’t know 26 34,7 34,7 36,0 That’s right 48 64,0 64,0 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 15

Valid Cumulative Frequency Percent Percent Percent Valid False answer 1 1,3 1,3 1,3 Don’t know 26 34,7 34,7 36,0 Right answer 48 64,0 64,0 100,0 Total 75 100,0 100,0

Item No. 16: “While menstruation the risk of being infected with HIV is increased for both partners”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 19 25,3 25,3 25,3 I don’t know 40 53,3 53,3 78,7 That’s right 16 21,3 21,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 16

Valid Cumulative Frequency Percent Percent Percent Valid False answer 19 25,3 25,3 25,3 Don’t know 40 53,3 53,3 78,7 Right answer 16 21,3 21,3 100,0 Total 75 100,0 100,0

Item No. 17: “Other sexually transmitted diseases (e.g., gonorrhea, syphilis) increase the risk for an HIV infection”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 17 22,7 22,7 22,7 I don’t know 45 60,0 60,0 82,7 That’s right 13 17,3 17,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 17

Valid Cumulative Frequency Percent Percent Percent Valid False answer 17 22,7 22,7 22,7 Don’t know 45 60,0 60,0 82,7 Right answer 13 17,3 17,3 100,0 Total 75 100,0 100,0

Item No. 18: “Condoms do have a date of expiry”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 2 2,7 2,7 2,7 I don’t know 3 4,0 4,0 6,7 That’s right 70 93,3 93,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 18

Valid Cumulative Frequency Percent Percent Percent Valid False answer 2 2,7 2,7 2,7 Don’t know 3 4,0 4,0 6,7 Right answer 70 93,3 93,3 100,0 Total 75 100,0 100,0

Item No. 19: “Heat (e.g., because of a radiator, blazing sun, glove box) can harm condoms”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 2 2,7 2,7 2,7 I don’t know 17 22,7 22,7 25,3 That’s right 56 74,7 74,7 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 19

Valid Cumulative Frequency Percent Percent Percent Valid False answer 2 2,7 2,7 2,7 Don’t know 17 22,7 22,7 25,3 Right answer 56 74,7 74,7 100,0 Total 75 100,0 100,0

Item No. 20: “Joke condoms (e.g., with animal heads or comic figures) protect against HIV”

Participants’ answers

Valid Cumulative Frequency Percent Percent Percent Valid That’s wrong 39 52,0 52,0 52,0 I don’t know 26 34,7 34,7 86,7 That’s right 10 13,3 13,3 100,0 Total 75 100,0 100,0

Right and wrong answers concerning item 20

Valid Cumulative Frequency Percent Percent Percent Valid False answer 10 13,3 13,3 13,3 Don’t know 26 34,7 34,7 48,0 Right answer 39 52,0 52,0 100,0 Total 75 100,0 100,0

Interest in HIV/AIDS and condom use

Descriptive Statistics

N Minimum Maximum M SD Pre_general interest 1 74 2 5 3,58 ,662

Pre_general interest 2 75 2 5 3,79 ,793

Pre_general interest 3 75 2 5 3,80 ,870

Pre_Interest6 TV program 75 -2 2 ,89 1,085

Pre_Interest7 Favorite magazine 75 -2 2 1,44 ,793

Pre_Interest8 Leaflet 75 -1 2 1,12 ,915

Pre_Interest9 Internet page found 75 -2 2 ,29 1,148 by chance

Pre_Interest10 Presentation 75 -2 2 ,96 1,006

Pre_Interest11 Favorite TV 75 -2 2 1,48 ,723 program

Valid N (listwise) 74

Communication about HIV/AIDS and condom use

How often do you talk with friends about HIV/AIDS?

Valid Cumulative Percent Percent Percent Valid I don’t know 2,7 2,7 2,7 never 17,3 17,3 20,0 seldom 34,7 34,7 54,7 sometimes 41,3 41,3 96,0 often 2,7 2,7 98,7 missing 1,3 1,3 100,0 Total 100,0 100,0

How often do you talk with other people about HIV/AIDS?

Valid Cumulative Percent Percent Percent Valid never 22,7 22,7 22,7 seldom 40,0 40,0 62,7 sometimes 33,3 33,3 96,0 often 1,3 1,3 97,3 missing 2,7 2,7 100,0 Total 100,0 100,0

Did somebody ever asked you for an advice concerning HIV/AIDS?

Valid Cumulative Percent Percent Percent Valid I don’t know 2,7 2,7 2,7 yes 28,0 28,0 30,7 no 68,0 68,0 98,7 missing 1,3 1,3 100,0 Total 100,0 100,0

Did you ever asked somebody for an advice concerning HIV/AIDS?

Valid Cumulative Percent Percent Percent Valid I don’t know 6,7 6,7 6,7 yes 32,0 32,0 38,7 no 60,0 60,0 98,7 missing 1,3 1,3 100,0 Total 100,0 100,0

Do you talk with friends or other people about HIV/AIDS and how infection occurs?

Valid Cumulative Percent Percent Percent Valid I don’t know 2,7 2,7 2,7 never 10,7 10,7 13,3 seldom 40,0 40,0 53,3 sometimes 34,7 34,7 88,0 often 10,7 10,7 98,7 missing 1,3 1,3 100,0 Total 100,0 100,0

Do you talk with friends or other people about condoms and how to use them?

Valid Cumulative Percent Percent Percent Valid never 13,3 13,3 13,3 seldom 38,7 38,7 52,0 sometimes 28,0 28,0 80,0 often 18,7 18,7 98,7 missing 1,3 1,3 100,0 Total 100,0 100,0

With whom do you talk about HIV/AIDS? (multiple answers possible)

Valid Cumulative Frequency Percent Percent Percent Valid Physician 2 1,8 1,8 1,8 Brother 1 ,9 ,9 2,7 Ex-boyfriend 1 ,9 ,9 3,6 Family 2 1,8 1,8 5,4 Gynecologist (male) 1 ,9 ,9 6,3 Gynecologist (female) 7 6,3 6,3 12,5 Boyfriend 5 4,5 4,5 17,0 Friends 13 11,6 11,6 28,6 Best female friend 12 10,7 10,7 39,3 Siblings 1 ,9 ,9 40,2 Teacher 7 6,3 6,3 46,4 Teacher (female) 2 1,8 1,8 48,2 Mother 33 29,5 29,5 77,7 Grandmother 1 ,9 ,9 78,6 Sister 11 9,8 9,8 88,4 Aunt 1 ,9 ,9 89,3 School 1 ,9 ,9 90,2 Father 11 9,8 9,8 100,0 Total 112 100,0 100,0

About which topics concerning HIV/AIDS did you talk? (Multiple answers possible)

Valid Cumulative Frequency Percent Percent Percent Valid 3. World 1 ,7 ,7 ,7 AIDS in other counties 1 ,7 ,7 1,5 Children with AIDS 1 ,7 ,7 2,2 Fear of HIV 1 ,7 ,7 2,9 Infection risks 7 5,1 5,1 8,0 Infection ways 45 32,8 32,8 40,9 Treatment 3 2,2 2,2 43,1 Fight against HIV 1 ,7 ,7 43,8 Consequences of infection 2 1,5 1,5 45,3 Dangerousness 2 1,5 1,5 46,7 Healing possibilities 3 2,2 2,2 48,9 HIV-Testing 3 2,2 2,2 51,1 Condoms 5 3,6 3,6 54,7 Life of infected persons 3 2,2 2,2 56,9

General carelessness 2 1,5 1,5 58,4 Carelessness concerning HIV 1 ,7 ,7 59,1 Medicine 8 5,8 5,8 65,0 Characteristics of infection 3 2,2 2,2 67,2 Female participant and boyfriend waiting for testing results 1 ,7 ,7 67,9

Cannot be healed 3 2,2 2,2 70,1 If HIV can be detected by looking at somebody 1 ,7 ,7 70,8 Birth control pill 1 ,7 ,7 71,5 Situation in Africa 1 ,7 ,7 72,3 Contraception 6 4,4 4,4 76,6 Course of disease 14 10,2 10,2 86,9 What to do in case of infection 1 ,7 ,7 87,6 What is HIV 1 ,7 ,7 88,3 Which other diseases appear when infected with HIV 1 ,7 ,7 89,1 How life would be with an HIV infection 1 ,7 ,7 89,8 If I would tell my parents in case of infection 1 ,7 ,7 90,5 How to protect 11 8,0 8,0 98,5 How many people are infected with HIV/AIDS 1 ,7 ,7 99,3 Where to go for a HIV testing 1 ,7 ,7 100,0 Total 137 100,0 100,0

Behavior intention

If a partner in a new relationship or one-night stand would like to have sex without condom would you agree or disagree?”

Valid Cumulative Frequency Percent Percent Percent Valid I would disagree 60 80,0 81,1 81,1

I don’t know 13 17,3 17,6 98,6 I would agree 1 1,3 1,4 100,0 Total 74 98,7 100,0 Missing missing 1 1,3 Total 75 100,0

Would you agree or disagree if your partner would like to have sex only with a condom?

Valid Cumulative Frequency Percent Percent Percent Valid I would disagree 5 6,7 6,8 6,8

I don’t know 2 2,7 2,7 9,5

I would agree 67 89,3 90,5 100,0 Total 74 98,7 100,0 Missing missing 1 1,3 Total 75 100,0

Would you ask of your own accord for a condom in a new relationship or one-night stand?

Valid Cumulative Frequency Percent Percent Percent Valid Probably won’t 2 2,7 2,7 2,7

I don’t know 8 10,7 10,8 13,5

Probably will 64 85,3 86,5 100,0 Total 74 98,7 100,0 Missing missing 1 1,3 Total 75 100,0

Results

Hypothesis 1

Hypothesis 1 – Test A and D

Dependent Variable: knowledge post-test scores Type III Sum Partial Eta Source of Squares df Mean Square F Sig. Squared Corrected Model ,338(a) 3 ,113 2,213 ,094 ,087 Intercept 26,665 1 26,665 523,693 ,000 ,882 Pre-test ,030 1 ,030 ,585 ,447 ,008 Treatment ,199 1 ,199 3,910 ,052 ,053 Test D Pre-test * ,070 1 ,070 1,366 ,246 ,019 Test A treatment Error 3,564 70 ,051 Total 30,281 74 Corrected Total 3,902 73 Note: a R Squared = ,087 (Adjusted R Squared = ,047)

Hypothesis 1 – Test E

Type III Sum of Source Squares df Mean Square F Sig. . Corrected Model ,265(a) 2 ,132 3,779 ,034 Intercept 12,20 ,428 1 ,428 ,001 4 Knowledge pre-test scores ,249 1 ,249 7,114 ,012 Intervention ,071 1 ,071 2,035 ,164 Test E Error 1,087 31 ,035 Total 14,661 34 Corrected Total 1,351 33 Dependent Variable: knowledge post-test scores

Hypothesis 1 – Test H

Levene's Test

for Equality of Variances t-test for Equality of Means Sig. (2- Mean Std. Error 95% Confidence Interval of F Sig. t Df tailed) Difference Difference the Difference

Lower Upper Know Equal - variances ledge assumed ,134 ,716 2,149 38 ,038 ,16647 ,07745 ,009678 ,323266 post- test Equal variances not 2,095 31,081 ,044 ,16647 ,07945 ,004441 ,328504 assumed

Std. Error Treatment N Mean Std. Deviation Mean Knowledge post-test Yes 17 ,668449 ,2649286 ,0642546 scores No 23 ,501976 ,2241430 ,0467371 Hypothesis 2

Hypothesis 2a

Test A & D – Hypothesis 2a

Dependent Variable: general interest post-tests Type III Sum Partial Eta Source of Squares df Mean Square F Sig. Squared Corrected Model ,436(a) 3 ,145 ,232 ,874 ,015 Intercept 613,728 1 613,728 980,737 ,000 ,954 Premeasuremen ,079 1 ,079 ,126 ,724 ,003 t Intervention ,409 1 ,409 ,653 ,423 ,014 Test D premeasurement * Intervention ,005 1 ,005 ,008 ,930 ,000 Test A Error 29,412 47 ,626 Total 688,889 51 Corrected Total 29,847 50 a R Squared = ,015 (Adjusted R Squared = -,048)

Test E – Hypothesis 2a

Dependent Variable: general interest post-tests Type III Sum Partial Eta Source of Squares df Mean Square F Sig. Squared Corrected Model 10,249(a) 2 5,124 22,848 ,000 ,706 Intercept ,037 1 ,037 ,167 ,688 ,009 General interest 10,018 1 10,018 44,668 ,000 ,702 pre-test scores Intervention ,168 1 ,168 ,748 ,398 ,038 Test E Error 4,261 19 ,224 Total 303,000 22

Corrected Total 14,510 21 a R Squared = ,706 (Adjusted R Squared = ,675)

Test H – Hypothesis 2a

Levene's Test for Equality of Variances t-test for Equality of Means Sig. 95% Confidence (2- Mean Std. Error Interval of the F Sig. t df tailed) Difference Difference Difference

Lower Upper General Equal interest variances ,133 ,719 -,564 27 ,578 -,16491 ,29248 -,76502 ,43520 post- assumed test Equal variances 19,2 -,573 ,573 -,16491 ,28778 -,76668 ,43686 not 6 assumed

Group Statistics

Std. Error Intervention N Mean Std. Deviation Mean Post_II_allg_Intere Yes 10 3,4667 ,72350 ,22879 sse_sum No 19 3,6316 ,76089 ,17456

Hypothesis 2b

Hypothesis 2 b – Test A and D (ANOVA)

Dependent Variable: Interest concerning concrete media offer about HIV/Aids post-tests Type III Partial Sum of Mean Eta Source Squares df Square F Sig. Squared Corrected Model 1,984(a) 3 ,661 1,429 ,248 ,097 Intercept 28,733 1 28,733 62,082 ,000 ,608 Pre-measurement ,396 1 ,396 ,855 ,361 ,021 Intervention 1,779 1 1,779 3,845 ,057 ,088 Test D Pre-measurement * intervention 3,84E-005 1 3,84E-005 ,000 ,993 ,000 Test A Error 18,513 40 ,463 Total 50,500 44 Corrected Total 20,497 43 a R Squared = ,097 (Adjusted R Squared = ,029)

Hypothesis 2 b – Test E (ANCOVA)

Dependent Variable: concrete interest concerning media offer Type III Partial Sum of Mean Eta Source Squares df Square F Sig. Squared Corrected Model 5,437(a) 2 2,718 13,343 ,000 ,584 Intercept 3,13E-006 1 3,13E-006 ,000 ,997 ,000 Concrete interest 4,527 1 4,527 22,221 ,000 ,539 pre-test Intervention ,000 1 ,000 ,002 ,964 ,000 Test E Error 3,871 19 ,204 Total 26,889 22 Corrected Total 9,308 21 a R Squared = ,584 (Adjusted R Squared = ,540)

Hypothesis 2 b – Test H (t-test)

Levene's Test for Equality of Variances t-test for Equality of Means Sig. 95% Confidence (2- Mean Std. Error Interval of the F Sig. t df tailed) Difference Difference Difference

Lower Upper Interest Equal concrete variances ,056 ,815 -1,312 20 ,204 -,40456 ,30837 -1,04781 ,23869 media assumed products Equal variances -1,293 16,5 ,214 -,40456 ,31280 -1,06611 ,25699 not assumed

Means

Intervention N Mean Std. Deviation Std. Error Mean

Concrete interest yes 9 ,5185 ,74276 ,24759 post-test no 13 ,9231 ,68925 ,19116

Hypothesis 3

Hypothesis 3 – Test A and Test D (ANOVA)

Dependent Variable: communication post-test scores Type III Sum Partial Eta Source of Squares df Mean Square F Sig. Squared Corrected Model 2,869(a) 3 ,956 1,105 ,356 ,066 Intercept 228,643 1 228,643 264,227 ,000 ,849 Pre-measurement ,022 1 ,022 ,025 ,875 ,001 Intervention 2,489 1 2,489 2,877 ,096 ,058 Test D Pre-measurement * Intervention ,565 1 ,565 ,652 ,423 ,014 Test A Error 40,670 47 ,865 Total 289,500 51 Corrected Total 43,539 50 a R Squared = ,066 (Adjusted R Squared = ,006)

Hypothesis 3 – Test E (ANCOVA)

Dependent Variable: communication post-test scores Type III Sum Partial Eta Source of Squares df Mean Square F Sig. Squared Corrected Model 13,040(a) 2 6,520 15,151 ,000 ,627 Intercept ,025 1 ,025 ,058 ,812 ,003 Communication 10,888 1 10,888 25,301 ,000 ,584 pre-test scores Intervention 2,554 1 2,554 5,935 ,025 ,248 Test E Error 7,746 18 ,430 Total 123,750 21 Corrected Total 20,786 20 a R Squared = ,627 (Adjusted R Squared = ,586)

Dependent Variable: communication post-test scores

95% Confidence Interval Intervention Mean Std. Error Lower Bound Upper Bound yes 1,882(a) ,198 1,466 2,297 no 2,580(a) ,208 2,144 3,016 a Covariates appearing in the model are evaluated at the following values: communication pre-test = 2,3333.

Hypothesis 4

Hypothesis 4 – t-tests (general interest) general interest – significant group differences

Group Statistics

Median Std. Error Involvement N Mean Std. Deviation Mean General interest marginal involved 9 3,1852 ,68943 ,22981 post-test scores highly involved 11 3,8788 ,54309 ,16375

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Sig. (2- Mean Std. Error F Sig. t df tailed) Difference Difference Lower Upper General Equal interest variances ,697 ,415 -2,520 18 ,021 -,69360 ,27528 -1,27195 -,11526 post- assumed test scores Equal variances not -2,458 15,077 ,027 -,69360 ,28218 -1,29479 -,09242 assumed Hypothesis 4 – t-tests (knowledge)

Group Statistics

Std. Error MedianFaktorw N Mean Std. Deviation Mean info_spiel_sum_post marginal involviert 15 ,715152 ,1569585 ,0405265 hoch involviert 16 ,625000 ,2985271 ,0746318

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper Knowledge post- Equal variances test scores assumed 7,031 ,013 1,042 29 ,306 ,0901515 ,0865462 -,086855 ,267158

Equal variances not assumed 1,062 23,007 ,299 ,0901515 ,0849253 -,085526 ,265829

Hypothesis 4 – t-tests (concrete interest)

Group Statistics

Std. Error MedianFaktorw N Mean Std. Deviation Mean interest_6-11_post_II marginal involviert 8 ,5417 ,67700 ,23936 hoch involviert 11 ,7727 ,57866 ,17447

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Mean Std. Error Interval of the F Sig. t df Sig. (2-tailed) Difference Difference Difference

Lower Upper interest_6b- Equal variances 11_post_II assumed ,279 ,604 -,801 17 ,434 -,23106 ,28857 -,83990 ,37778 Equal variances not assumed -,780 13,706 ,449 -,23106 ,29620 -,86762 ,40550

Hypothesis 4 – t-tests (follow-up communication)

Group Statistics

Std. Error MedianFaktorw N Mean Std. Deviation Mean communication_post marginal involviert 9 1,5556 ,72648 ,24216 hoch involviert 11 2,2273 ,84746 ,25552

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means Sig. (2- Mean Std. Error 95% Confidence Interval of F Sig. T df tailed) Difference Difference the Difference

Lower Upper communication Equal _post variances ,322 ,577 -1,878 18 ,077 -,67172 ,35776 -1,42334 ,07991 assumed Equal variances not -1,908 17,940 ,073 -,67172 ,35204 -1,41150 ,06807 assumed Hypothesis 5

Hypothesis 5 – ANOVA (knowledge)

Knowledge post-test scores as dependent variables

Tests of Between-Subjects Effects

Dependent Variable: Info_game_sum_post Type III Sum of Partial Eta Source Squares df Mean Square F Sig. Squared Corrected Model ,360(a) 3 ,120 2,369 ,078 ,092 Intercept 25,195 1 25,195 497,866 ,000 ,877 Intervention ,287 1 ,287 5,669 ,020 ,075 MedianRisk ,072 1 ,072 1,422 ,237 ,020 intervention * MedianRisk ,050 1 ,050 ,984 ,325 ,014

Error 3,542 70 ,051 Total 30,281 74 Corrected Total 3,902 73 a R Squared = ,092 (Adjusted R Squared = ,053)

Hypothesis 5 – ANOVA (general interest)

General interest post-test scores

Tests of Between-Subjects Effects

Dependent Variable: Post_II_general interest _sum Type III Sum of Partial Eta Source Squares df Mean Square F Sig. Squared Corrected Model 3,343(a) 3 1,114 1,976 ,130 ,112 Intercept 631,474 1 631,474 1119,774 ,000 ,960 Intervention ,520 1 ,520 ,922 ,342 ,019 MedianRisk 1,271 1 1,271 2,253 ,140 ,046 intervention * MedianRisk 2,115 1 2,115 3,751 ,059 ,074

Error 26,505 47 ,564 Total 688,889 51 Corrected Total 29,847 50 a R Squared = ,112 (Adjusted R Squared = ,055)

Hypothesis 5 – ANOVA (concrete interest in media products) interest in media products

Tests of Between-Subjects Effects

Dependent Variable: Interest_6-11_post_II Type III Sum of Partial Eta Source Squares df Mean Square F Sig. Squared Corrected Model 2,902(a) 3 ,967 2,199 ,103 ,142 Intercept 30,142 1 30,142 68,520 ,000 ,631 intervention 2,014 1 2,014 4,578 ,039 ,103 MedianRisk ,146 1 ,146 ,333 ,567 ,008 intervention * MedianRisk 1,149 1 1,149 2,612 ,114 ,061

Error 17,596 40 ,440 Total 50,500 44 Corrected Total 20,497 43 a R Squared = ,142 (Adjusted R Squared = ,077)

Hypothesis 5 – ANOVA (follow-up communication) follow-up communication

Tests of Between-Subjects Effects

Dependent Variable: communication_post Type III Sum of Partial Eta Source Squares df Mean Square F Sig. Squared Corrected Model 4,233(a) 3 1,411 1,687 ,183 ,097 Intercept 234,606 1 234,606 280,531 ,000 ,857 intervention 2,613 1 2,613 3,125 ,084 ,062 MedianRisk ,290 1 ,290 ,347 ,559 ,007 intervention * MedianRisk 1,472 1 1,472 1,760 ,191 ,036

Error 39,306 47 ,836 Total 289,500 51 Corrected Total 43,539 50 a R Squared = ,097 (Adjusted R Squared = ,040)

Exploratory Questions

Exploratory question 1: Does playing the computer game “Supergöre” affect behavior intention concerning condom use?

Test A & D – ANOVA (Exploratory Question 1)

Tests of Between-Subjects Effects

Dependent Variable: post_intention_sum Type III Sum of Mean Partial Eta Source Squares df Square F Sig. Squared Corrected Model ,009(a) 3 ,003 ,040 ,989 ,002 Intercept 51,680 1 51,680 725,830 ,000 ,914 premeasurement ,005 1 ,005 ,066 ,798 ,001 intervention ,004 1 ,004 ,059 ,808 ,001 Test D premeasurement * intervention ,000 1 ,000 ,005 ,944 ,000 Test A

Error 4,842 68 ,071 Total 57,667 72 Corrected Total 4,850 71 a R Squared = ,002 (Adjusted R Squared = -,042)

Test E – ANCOVA (Exploratory Question 1)

Tests of Between-Subjects Effects

Dependent Variable: post_intention_sum Type III Sum Mean Partial Eta Source of Squares df Square F Sig. Squared Corrected Model ,337(a) 2 ,168 2,999 ,065 ,167 Intercept 1,815 1 1,815 32,346 ,000 ,519 pre_intention_sum ,336 1 ,336 5,980 ,021 ,166 intervention ,010 1 ,010 ,173 ,681 ,006 Error 1,684 30 ,056 Total 25,778 33 Corrected Total 2,020 32 a R Squared = ,167 (Adjusted R Squared = ,111)

Test H (Exploratory Question 1)

Group Statistics

Std. Error intervention N Mean Std. Deviation Mean post_intention_sum intervention 16 ,8750 ,23960 ,05990 no intervention 23 ,8551 ,29858 ,06226

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper post_intention_sum Equal variances assumed ,207 ,652 ,222 37 ,826 ,01993 ,08991 -,16225 ,20211 Equal variances not assumed ,231 36,150 ,819 ,01993 ,08640 -,15527 ,19512

Exploratory question 2: Does playing the computer game “Supergöre” affect girls’ self-efficacy?

Test A & D – ANOVA (Exploratory Question 2)

Tests of Between-Subjects Effects

Dependent Variable: post_self-efficacy_3-11_sum Partial Type III Sum Mean Eta Source of Squares df Square F Sig. Squared Corrected Model ,074(a) 3 ,025 ,040 ,989 ,002 Intercept 781,370 1 781,370 1275,672 ,000 ,949 intervention ,021 1 ,021 ,034 ,853 ,000 premeasurement ,021 1 ,021 ,034 ,853 ,000 Test D intervention * premeasurement ,035 1 ,035 ,056 ,813 ,001 Test A Error 42,264 69 ,613 Total 843,111 73 Corrected Total 42,337 72 a R Squared = ,002 (Adjusted R Squared = -,042)

Test E – ANCOVA (Exploratory Question 2)

Tests of Between-Subjects Effects

Dependent Variable: post_self-efficacy_3-11_sum Type III Sum Partial Eta Source of Squares df Mean Square F Sig. Squared Corrected Model 20,277(a) 2 10,138 95,392 ,000 ,856 Intercept 6,18E-006 1 6,18E-006 ,000 ,994 ,000 pre_self-efficacy_3-11_sum 20,223 1 20,223 190,278 ,000 ,856

intervention ,010 1 ,010 ,091 ,765 ,003 Test E Error 3,401 32 ,106 Total 403,728 35 Corrected Total 23,678 34 a R Squared = ,856 (Adjusted R Squared = ,847)

Test H

Group Statistics

Std. Error intervention N Mean Std. Deviation Mean post_self-efficacy_3- intervention 15 3,333333 ,6706232 ,1731542 11_sum no intervention 23 3,323671 ,7490458 ,1561868

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper post_self-efficacy_3- Equal variances 11_sum assumed ,928 ,342 ,040 36 ,968 ,0096618 ,2388097 -,4746667 ,4939903 Equal variances not assumed ,041 32,400 ,967 ,0096618 ,2331881 -,4650968 ,4844205

Exploratory question 3: Does self-efficacy mediate the results on knowledge, interest and communication about HIV/AIDS and condom use?

Independent t-tests (Exploratory Question 3)

Group Statistics

Median Self-efficacy Std. Error pre-test N Mean Std. Deviation Mean General interest post-test Low 24 3,5278 ,67328 ,13743 High 25 3,6400 ,89194 ,17839 Concrete interest post-test Low 22 ,6894 ,67514 ,14394 High 20 ,9583 ,72118 ,16126 Follow-up communication Low 24 1,9583 ,84592 ,17267 High 25 2,4000 1,01036 ,20207 Knowledge post-test Low 39 ,596737 ,2124802 ,0340241 High 33 ,617080 ,2381028 ,0414484

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper General interest post-test Equal variances assumed 1,240 ,271 -,496 47 ,623 -,11222 ,22648 -,56784 ,34339 Equal variances not assumed -,498 44,563 ,621 -,11222 ,22519 -,56590 ,34145 Concrete interest post-test Equal variances assumed ,024 ,877 -1,248 40 ,219 -,26894 ,21546 -,70441 ,16653 Equal variances not assumed -1,244 38,960 ,221 -,26894 ,21616 -,70617 ,16829 Follow-up communication Equal variances assumed 1,556 ,218 -1,656 47 ,104 -,44167 ,26677 -,97835 ,09501 Equal variances not assumed -1,662 46,162 ,103 -,44167 ,26580 -,97664 ,09331 Knowledge post-test Equal variances assumed ,295 ,589 -,383 70 ,703 -,0203433 ,0531132 -,1262742 ,0855877 Equal variances not assumed -,379 64,857 ,706 -,0203433 ,0536247 -,1274436 ,0867571

Over all participants:

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t Df Sig. (2-tailed) Difference Difference Lower Upper General interest Equal variances assumed 1,163 ,286 1,138 49 ,260 ,24564 ,21578 -,18799 ,67927 Equal variances not assumed 1,144 46,558 ,258 ,24564 ,21463 -,18625 ,67753 Follow-up communication Equal variances assumed ,047 ,829 ,178 49 ,860 ,04692 ,26396 -,48352 ,57736 Equal variances not assumed ,178 48,737 ,860 ,04692 ,26413 -,48394 ,57779 Concrete interest Equal variances assumed ,022 ,882 -,436 42 ,665 -,09179 ,21038 -,51634 ,33277 Equal variances not assumed -,438 41,963 ,664 -,09179 ,20976 -,51511 ,33153 Knowledge Equal variances assumed 1,966 ,165 ,064 72 ,949 ,0034759 ,0543026 -,1047743 ,1117262 Equal variances not assumed ,063 60,992 ,950 ,0034759 ,0555050 -,1075134 ,1144653

Exploratory question 4: Does previous experience with digital games moderate the results on knowledge, interest and communication about HIV/AIDS and condom use?

Knowledge (Exploratory Question 4)

Group Statistics

Percentile Group Std. Error of Spielintensität N Mean Std. Deviation Mean Post_II_general_interest_sum Niedrig 25 3,7200 ,65744 ,13149 Hoch 26 3,4744 ,86499 ,16964 communication_post Niedrig 25 2,2200 ,95830 ,19166 Hoch 26 2,1731 ,92674 ,18175 interest_6-11_post_II Niedrig 21 ,7778 ,67358 ,14699 Hoch 23 ,8696 ,71766 ,14964 info_game_sum_post Niedrig 34 ,598930 ,2649182 ,0454331 Hoch 40 ,595455 ,2016566 ,0318847

Same t-test, but this time without participants who report never playing any digital games

Group Statistics

Std. Error MedianSpielintensität N Mean Std. Deviation Mean Post_II_general_ Niedrig 26 3,7949 ,71229 ,13969 Interest_sum Hoch 14 3,1905 ,85449 ,22837

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper Post_II_general_ Equal variances Interest_sum assumed ,597 ,445 2,387 38 ,022 ,60440 ,25324 ,09174 1,11705 Equal variances not assumed 2,258 22,882 ,034 ,60440 ,26771 ,05044 1,15835

Exploratory question 5: Is there a relation between previous experience with digital games and involvement while playing the computer game “Supergöre”?

Correlations

Previous experience with Involvement digital games Involvement Pearson Correlation 1 -,520(**) Sig. (2-tailed) ,006 N 31 26 Previous experience with Pearson Correlation -,520(**) 1 digital games Sig. (2-tailed) ,006 N 26 61 ** Correlation is significant at the 0.01 level (2-tailed).

ANOVA – Test A and D (Exploratory question 6)

Tests of Between-Subjects Effects

Dependent Variable: Info_game_sum_post Type III Sum Partial Eta Source of Squares Df Mean Square F Sig. Squared Corrected Model ,200(a) 3 ,067 1,537 ,220 ,106 Intercept 12,087 1 12,087 278,545 ,000 ,877 intervention ,000 1 ,000 ,008 ,927 ,000 premeasurement ,015 1 ,015 ,352 ,557 ,009 intervention * premeasurement ,162 1 ,162 3,737 ,060 ,087

Error 1,692 39 ,043 Total 14,785 43 Corrected Total 1,892 42 a R Squared = ,106 (Adjusted R Squared = ,037)

ANCOVA – Test E (Exploratory question 6)

Between-Subjects Factors

Value Label N intervention 1,00 intervention 7 2,00 no 10 intervention

Tests of Between-Subjects Effects

Dependent Variable: Info_spiel_sum_post Type III Sum of Partial Eta Source Squares df Mean Square F Sig. Squared Corrected Model ,208(a) 2 ,104 5,081 ,022 ,421 Intercept ,124 1 ,124 6,036 ,028 ,301 info_game_sum_pre ,148 1 ,148 7,229 ,018 ,341 intervention ,001 1 ,001 ,066 ,801 ,005 Error ,287 14 ,020 Total 6,165 17 Corrected Total ,495 16 a R Squared = ,421 (Adjusted R Squared = ,338)

Test H

Group Statistics

Std. Error intervention N Mean Std. Deviation Mean info_game_sum_post intervention 13 ,594406 ,2560975 ,0710287 no intervention 13 ,461538 ,1979980 ,0549148

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper info_game_sum_post Equal variances assumed ,800 ,380 1,480 24 ,152 ,1328671 ,0897814 -,0524326 ,3181669 Equal variances not assumed 1,480 22,569 ,153 ,1328671 ,0897814 -,0530562 ,3187904

Exploratory question 7: Does age affect the results on knowledge, interest and communication about HIV/AIDS and condom use?

ANCOVA Knowledge

Tests of Between-Subjects Effects

Dependent Variable: Info_game_sum_post Type III Sum of Partial Eta Source Squares Df Mean Square F Sig. Squared Corrected Model ,348(a) 4 ,087 1,687 ,163 ,089 Intercept ,017 1 ,017 ,321 ,573 ,005 Age ,010 1 ,010 ,186 ,667 ,003 intervention ,208 1 ,208 4,040 ,048 ,055 premeasurement ,024 1 ,024 ,473 ,494 ,007 intervention * premeasurement ,045 1 ,045 ,876 ,353 ,013

Error 3,555 69 ,052 Total 30,281 74 Corrected Total 3,902 73 a R Squared = ,089 (Adjusted R Squared = ,036)

ANCOVA General interest

Tests of Between-Subjects Effects

Dependent Variable: Post_II_general_Interest_sum Type III Sum of Partial Eta Source Squares Df Mean Square F Sig. Squared Corrected Model 1,265(a) 4 ,316 ,509 ,729 ,042 Intercept 4,425 1 4,425 7,122 ,010 ,134 Age ,829 1 ,829 1,334 ,254 ,028 intervention ,545 1 ,545 ,878 ,354 ,019 premeasurement ,134 1 ,134 ,216 ,644 ,005 intervention * premeasurement ,149 1 ,149 ,240 ,626 ,005

Error 28,583 46 ,621 Total 688,889 51 Corrected Total 29,847 50 a R Squared = ,042 (Adjusted R Squared = -,041)

ANCOVA interest in media products about HIV/AIDS

Tests of Between-Subjects Effects

Dependent Variable: Interest_6-11_post_II Type III Sum of Partial Eta Source Squares Df Mean Square F Sig. Squared Corrected Model 2,229(a) 4 ,557 1,190 ,331 ,109 Intercept ,056 1 ,056 ,119 ,732 ,003 Age ,245 1 ,245 ,523 ,474 ,013 intervention 1,700 1 1,700 3,629 ,064 ,085 premeasurement ,343 1 ,343 ,732 ,397 ,018 intervention * premeasurement ,037 1 ,037 ,078 ,781 ,002

Error 18,268 39 ,468 Total 50,500 44 Corrected Total 20,497 43 a R Squared = ,109 (Adjusted R Squared = ,017)

ANCOVA Follow-up communication

Tests of Between-Subjects Effects

Dependent Variable: communication_post Type III Sum of Partial Eta Source Squares Df Mean Square F Sig. Squared Corrected Model 2,987(a) 4 ,747 ,847 ,503 ,069 Intercept 1,151 1 1,151 1,305 ,259 ,028 Age ,119 1 ,119 ,134 ,716 ,003 intervention 2,581 1 2,581 2,928 ,094 ,060 premeasurement ,032 1 ,032 ,037 ,849 ,001 intervention * premeasurement ,680 1 ,680 ,771 ,384 ,016

Error 40,552 46 ,882 Total 289,500 51 Corrected Total 43,539 50 a R Squared = ,069 (Adjusted R Squared = -,012)

Exploratory question 8: Is there a relation between self-efficacy and own risk perception?

Correlations

pre_selbstwirk_ 3bis11_sum Risk_sum pre_self-efficacy_3-11_sum Pearson Correlation 1 -,133 Sig. (2-tailed) ,260 N 73 73 Risk_sum Pearson Correlation -,133 1 Sig. (2-tailed) ,260 N 73 75

Exploratory question 9: Is there a relation between self-efficacy and communication about HIV/AIDS and condom use?

Group Statistics

Std. Error Median_Pre_Selbst N Mean Std. Deviation Mean communication_pre niedrig 38 1,9342 ,67954 ,11024 hoch 33 2,4697 ,69529 ,12103

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference Mean Std. Error F Sig. t df Sig. (2-tailed) Difference Difference Lower Upper communication_pre Equal variances assumed ,618 ,434 -3,276 69 ,002 -,53549 ,16344 -,86155 -,20943 Equal variances not assumed -3,271 67,148 ,002 -,53549 ,16371 -,86224 -,20873

Exploratory question 10: Is there a relation between sexual activity and self-efficacy?

Correlations

pre_self-efficacy_3- Sexual activity 11_sum Sexual activity Pearson Correlation 1 -,112 Sig. (2-tailed) ,348 N 74 72 pre_self-efficacy_3-11_sum Pearson Correlation -,112 1 Sig. (2-tailed) ,348 N 72 73

Exploratory question 11: Is there a relation between sexual activity and own risk perception?

Correlations

Sexual activity Risk_sum Sexual activity Pearson Correlation 1 ,359(**) Sig. (2-tailed) ,002 N 74 74 Risk_sum Pearson Correlation ,359(**) 1 Sig. (2-tailed) ,002 N 74 75 ** Correlation is significant at the 0.01 level (2-tailed).

Exploratory question 12: Is there a relation between self-efficacy and dating somebody?

Correlations

pre_self- efficacy_3- Sexual activity 11_sum Spearman's rho Sexual activity Correlation Coefficient 1,000 -,102 Sig. (2-tailed) . ,395 N 74 72 pre_self- Correlation Coefficient -,102 1,000 efficacy_3-11_sum Sig. (2-tailed) ,395 . N 72 73

Exploratory question 13: Is there a relation between own risk perception and dating somebody?

Correlations

relationship_ dichotomous Risk_sum Spearman's rho relationship_dichotom Correlation Coefficient 1,000 ,254(*) ous Sig. (2-tailed) . ,028 N 75 75 Risk_sum Correlation Coefficient ,254(*) 1,000 Sig. (2-tailed) ,028 . N 75 75 * Correlation is significant at the 0.05 level (2-tailed).

Exploratory question 14: Is there a relation between pretest knowledge about HIV/AIDS and condom use and sexual activity?

Correlations

Sexual info_game_sum_p activity re Spearman's rho Sexual activity Correlation Coefficient 1,000 ,304(**) Sig. (2-tailed) . ,008 N 74 74 info_game_sum_pre Correlation Coefficient ,304(**) 1,000 Sig. (2-tailed) ,008 . N 74 75 ** Correlation is significant at the 0.01 level (2-tailed).