Curbing Excessive Pornography Consumption Using Traditional, Relationship, and Religious
Identity-Based Extended Parallel Process Model Messages
A dissertation submitted to the College of Communication and Information of Kent State
University in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
by
Krishnamurti Murniadi
July, 2018 Dissertation written by
Krishnamurti Murniadi
B.A., University of Wisconsin-Eau Claire, 2002
M.A., Western Kentucky University, 2008
Ph.D., Kent State University, 2018
Approved by
______, Chair, Doctoral Dissertation Committee Dr. Nichole Egbert
______, Member, Doctoral Dissertation Committee Dr. Mei-Chen Lin
______, Member, Doctoral Dissertation Committee Dr. Xueying Zhang
______, Member, Doctoral Dissertation Committee Dr. Susan Roxburgh
Accepted by
______, Chair, School of Communication Studies Dr. Elizabeth Graham
______, Dean, College of Communication and Information Dr. Amy Reynolds
Table of Contents
Page
TABLE OF CONTENTS………………………………………………………………… iii
LIST OF FIGURES………………………………………………………………………. v
LIST OF TABLES………………………………………………………………………... vi
ACKNOWLEDGEMENTS………………………………………………………………. viii
CHAPTERS
I. BACKGROUND…………………………………………………………. 1 Statement of Problem……………………………………………... 2 Statement of Purpose……………………………………………… 4 Theoretical Framework……………………………………………. 4
II. LITERATURE REVIEW…………………………………………………. 11 The Extended Parallel Process Model…………………………….. 20 Social Identity Theory…………………………………………….. 30 Social Categorization Theory……………………………………… 32 Identity Theory……………………………………………………. 33 Identity Importance, Salience, and Commitment…………………. 36 Social Identity and Behaviors …………………………………….. 38 Health EPPM and Identity-Based EPPM…………………………. 52 Research Questions and Hypotheses……………………………… 55
III. METHODOLOGY...... 65 A. Pretest…………………………………………………………. 65 B. Main Experiment……………………………………………… 74
IV. RESULTS…………………………………………………………………. 82 Research Questions and Hypotheses Testing……………………... 93
V. DISCUSSION S…………………………………………………………… 110
DEFINITION OF TERMS………………………………………………………………... 127
APPENDICES A. Health EPPM message…………………………………………………………. 130 B. Relationship EPPM message…………………………………………………… 131 (being a husband/boyfriend as a social identity)
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C. Faith EPPM message…………………………………………………………… 132 (being a Christian as a social identity) D. Meyer (1998) and West (1994) Channel Credibility Index……………………. 133 E. Social Identity Stimulus Check………………………………………………… 134 F. Social Identity Stimulus Check for the Control Group………………………… 138 G. Demographic Questions………………………………………………………... 141 H. Pornography Use……………………………………………………………….. 142 I. Witte, et al. (1996) Risk Behaviors Diagnosis Scale……………………………. 143 J. Adjusted Sellers et al. (1997) Multidimensional Inventory…………………….. 145 of Black Identity (MIBI) centrality dimension scale for being a boyfriend/husband as a social identity K. Adjusted Sellers et al. (1997) Multidimensional Inventory…………………… 146 of Black Identity (MIBI) centrality dimension scale for being a Christian as a social identity L. Rise, Kovac, Kraft, & Moan (2008) Behavioral Intention Scale………………. 147
REFERENCES……………………………………………………………………………. 148
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List of Figures
Figure Page
1. Diagram of Witte’s (1992) health EPPM…………………………………………. 26
2. Presenting threat in identity-based EPPM………………………………………… 46
3. Presenting efficacy in identity-based EPPM……………………………………… 52
4. Diagram of identity-based EPPM…………………………………………………. 54
5. Social identity and fear……………………………………………………………. 57
6. Diagram of social identity and threat……………………………………………... 59
7. Diagram of social identity and efficacy………………………………………….... 61
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List of Tables
Table Page
1. Descriptive Statistics and Reliability for All Scales Used In the Study……………….. 79
2. Description of Key Analytic Variables across Three Groups………………………….. 83
3. Description of Key Analytic Variables in Health EPPM Condition…………………… 84
4. Description of Key Analytic Variables in Relationship EPPM Condition …………….. 85
5. Description of Key Analytic Variables in Faith EPPM Condition……………………... 87
6. Factor Analysis for Relationship Identity Scale………………………………………... 90
7. Final Exploratory Factor Analysis Factor Solution for Relationship
Identity Scale……………………………………………………………………… 91
8. Factor Analysis for Faith Identity Scale………………………………………………... 92
9. Exploratory Factor Analysis Factor Solution for Faith Identity Scale…………………. 93
10. Relationships between Perceived Threat/Efficacy and Behavioral Intention
Among Individuals Receiving Health EPPM Message…………………………… 95
11. Relationships between Perceived Threat/Efficacy and Behavioral Intention
Among Individuals Receiving Relationship EPPM Message …………………….. 97
12. Relationships between Perceived Threat/Efficacy and Behavioral Intention
.Among Individuals Receiving Faith EPPM Message……………………………………. 100
13. Relationships between Perceived Threat/Identity and Behavioral Intention
Among Individuals Receiving Relationship EPPM Message …………………….. 101
14. Relationships between Perceived Efficacy/Identity and Behavioral Intention
Among Individuals Receiving Relationship EPPM Message …………………….. 103
15. Relationships between Perceived Threat/Efficacy and Behavioral Intention
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Among Individuals Receiving Faith EPPM Message …………………………….. 105
16. Relationships between Perceived Threat/Efficacy and Behavioral Intention
Among Individuals Receiving Health EPPM Message…………………………… 107
17. Correlations matrix among participants who received the health EPPM
Message…………………………………………………………………………… 108
18. Correlations matrix among participants who received the relationship
EPPM message…………………………………………………………………….. 108
19. Correlations matrix among participants who received the faith EPPM message……... 108
20. Summary of Research Questions and Hypotheses…………………………………….. 109
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Acknowledgements
This dissertation is for my wife, my son, my parents, my brother, my sister-in-law, my aunts, my
American mother Annis Hickman, and the rest of my adoptive family in Northeast Oklahoma.
Without your love and prayers, this paper would not exist.
I would also like to thank first to my advisor, Dr. Nichole Egbert, and my committee members - Dr. Mei-Chen Lin, Dr. Catherine Goodall, Dr. Maria Zhang, and Dr. Susan Roxburgh
- for your time, assistance, constant support, valuable advices and insightful criticism.
Thank you to Kristin Yeager from the Statistical Consulting at Kent State University
Library, thank you to Dr. Setyo Hari Wijanto from the School of Business Administration and
Sofyan Cholid from the Faculty of Social Welfare, both of the University of Indonesia, for helping me with the statistical analyses. Thank you to Portugal National Football Team for their performance in Euro 2016, which very much inspired me to succeed, as I always see myself as an underdog during my college experience. Thank you to the staffs at Tree City Coffee and
Pastry in Kent, Ohio; Metronome Coffee in Tacoma, Washington; Thump Coffee in Denver,
Colorado; Café Jen in Prague, Czech Republic; and Mata Kopi in Tangerang, Indonesia, who allowed me to use your comfortable space and Wi-Fi all day for the price of one cup of coffee.
Finally, thank you to every single person who helped me to be where I am today in terms of my academic endeavor. This includes but not limited to the current and previous faculty, staff, and fellow graduate students at the College of Communication and Information, my friends and colleagues in Kent, and my former advisors and professors at Western Kentucky University.
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1
Chapter I
Background
The advent of Internet technology has opened avenues for communication activities that traditionally take place offline to move online (Walther, Gay, & Hancock, 2005). These activities range from communicating with the loved ones, playing games, to conducting a meeting. One controversial communication activity that is becoming more popular online is media-related sexual activity (Cooper, 1998; Cooper, Galbreath, & Becker, 2004; Goodson, McCormick, &
Evans, 2000). The most popular form of media-related sexual activity is Internet pornography, which refers to “written or pictorial matter intended to arouse sexual feelings” (Boyer et al.,
1983, p. 534; Fisher & Barack, 2001).
Internet pornography is widely consumed by the general population, particularly males.
The Huffington Post reported that 70% of men surveyed admitted that they spent a significant amount of their time visiting pornographic sites, with the average amount of 12 minutes spent on one site (“Porn Sites”, 2013). In 2008, 86% of male college students aged 18 to 26 reported that they used Internet pornography at some level in the past year. Among those pornography users,
16% reported using pornography three to five days a week and 5% admitted using pornography every day (Carroll et al., 2008). Bartlein (2004) reported that people are more likely to visit an
Internet pornography website than to visit any of the top three search engines (Google, Yahoo!, and MSN). In addition, when using search engines, people listed pornographic-related words in one out of four inputs, with approximate hits of 68 million (Carroll et al., 2008). Pornography is the number one entry in Bing and, the second most popular search engine after Google (Dickson,
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2014; O’Neill, 2015). Pornography is so popular that there is a search engine created solely for searching these adult materials called Boodigo (Moore, 2014).
Statement of Problem
Sexual compulsive and at-risk consumption of pornography can lead to negative effects on individuals’ health and social well-being (Braun-Courville & Rojas, 2009; Bridges, Bergner,
& Hesson-McInnis, 2003; Cooper, Delmonico, & Burg, 2000; Cooper et al., 2004; Owens et al.,
2012; Wingood et al., 2001; Zillman & Bryant, 1988). In terms of mental health, a study by
Braun-Courville and Rojas (2009) involving young adults in New York suggested that those who visited pornography websites in the last one month are 1.8 times more likely to have multiple sexual partners than those who did not visit pornography website in the previous month. In addition, Wingood et al. (2001) found that pornography viewers were 1.5 times less likely to have used contraception last time they were having sex. As for social well-being, frequent viewing of pornography correlated with lower marital satisfaction, and distorted views on sexual assaults cases (Zillman & Bryant, 1988).
The effects are particularly bad for sexual compulsive and at-risk users. In their study involving 9,177 Internet users, Cooper et al. (1999) categorized users into: (a) recreational users, or those who search for Internet pornography out of curiosity, spend one hour or less per week online for this purpose, and make up 46.6% of the Internet users, (b) sexual compulsive users, or those who go online as one way to fulfill their sexual needs, spend more than one hour per week for Internet pornography, and make up 44.9% of the Internet users, and (c) at-risk users, or those who develop online sexually compulsive behavior due to the availability of sexual materials on the Internet, and make up 8.5% of the Internet users.
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In their study, Cooper et al (1999) found that participants who spent 11 hours or more per week in consuming pornography had significantly more negative consequences than the average users. These results prompted Cooper et al (1999) to classify some pornography users as at-risk users and sexual compulsive users. The negative consequences for at-risk users include feeling the urge to engage in a sexual act and difficulty controlling their sexual arousal. Among at-risk users, the urge to have sex and the difficulty in controlling their urge were nearly two standard deviations above the average users. In addition, negative consequences for sexual compulsive users were one standard deviation above the average users.
Schneider (1994) suggested that having negative effects two standard deviations above the average pornography users shows the threshold at which a behavior is clinically atypical, especially if the behavior continues despite negative consequences. As for sexual compulsive users, the negative effects of consuming pornography for more than one hour per week also resonated with previous experiment by Zillman and Bryant (1988). In their experiment, participants who viewed one hour per week of pornography reported more acceptance of sexual promiscuity, such as extramarital affairs and having multiple sexual partners than those in the control group.
Researchers who study pornography effects regularly use Cooper et al.’s (1999) classifications of Internet pornography users (Boies, Knudson, & Young, 2004; Manning, 2006).
Some of their findings include how both sexual compulsive and at-risk consumption of Internet pornography were more likely to experience pornography addiction (Hilton & Watts, 2011), commit sexual deviancy, such as masturbation in public (Oddone-Paolucci, Genuis, & Violato,
2000), conduct risky behaviors, such as having multiple sexual partners (Carroll et al., 2008), alter perceptions of sexuality and relationships, such as acceptance of extramarital sex (Zillman
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& Bryant, 1988), marital dissatisfaction (Bergner & Bridges, 2006), sexual dissatisfaction in monogamous relationships (Schneider, 2000), and unintentionally showing one’s partner or children pornographic materials (Bridges et al., 2003; Schneider, 2000).
Statement of Purpose
This present study addresses the health issue of sexual compulsive and at-risk pornography consumption from a communication perspective. Specifically, this study investigates what kind of persuasive messages would deter Internet users from viewing pornography for more than one hour per week. To date, there has not been any study on the effects of health persuasive messages on sexual compulsive and at-risk pornography consumption.
When it comes to pornography users, men and women differ in their motivations and frequency of use. Although males are likely to feel entertained or sexually aroused while viewing pornography, females are likely to feel angry or disgusted (Goodson et al., 2000). Male pornography viewers also outnumber female pornography viewers by 85% to 15% (Cooper et al., 2004). In addition, male users are twice more likely than female users to forward the pornographic materials to friends (Boies, 2002). As this study focuses on compulsive and at-risk consumption of pornography and aims to customize health messages to a specific demographic, the population of the study consists of only males.
Theoretical Frameworks
Fear appeals are popular tools to use in persuasive health messages. This type of appeal refers to a persuasive element that scares individuals through descriptions of negative effects that may happen if they do not comply with the recommendation within the message (Rogers, 1985;
Witte, 1992). Fear appeals are often used to modify a broad range of health behaviors, from
5 curbing risky behaviors such as having unprotected sex (Casey, Timmerman, Allen, Krahn, &
Turkiewicz, 2009), smoking (Thompson, Barnett, & Pearce, 2009), drinking and driving (Lewis,
Watson, & Tay, 2007), to promoting healthy behaviors, such as eating healthy among children
(Chan, Prendergast, Grønhøj, & Bech-Larsen, 2011) and exercising regularly (Jones, Sinclair, &
Courneya, 2003). Due to the popular use of fear appeals, persuasive messages using fear appeal models developed over time, starting from Janis and Feshbach’s (1953) drive explanation to
Rimal and Real’s (2003) risk perception attitude framework.
Of all the fear appeal models, Witte’s (1992, 1998) EPPM is widely used within the health context in the past decade (Maloney, Lapinski, & Witte, 2011). Its central tenet argues that when an individual accepts persuasive messages that are high in threat and efficacy, he or she is likely to comply with the recommended behaviors presented within the message. Threat refers to the danger that exists within the environment. Threat is different from fear, which is the emotional reaction when a person perceives threats. Efficacy refers to an individual’s own perception about one’s ability to perform the recommended behaviors (self-efficacy), and the belief regarding whether the behavior is effective in containing the fear (response efficacy).
Many communication scholars have supported the use of the EPPM as an effective tool in delivering recommendations for health and pro social behaviors to diverse populations. Studies that use EPPM as their theoretical framework include health messages that promote: the use of condoms to prevent HIV infection (Casey et al., 2009), the intention to quit smoking among heavy smokers (Wong & Cappella, 2009), hand washing behavior among college students
(Botta, Dunker, Fenson-Hood, Maltarich, & McDonald, 2008), testing patients’ level of kidney functioning or kidney disease among physicians (Roberto, Goodall, West & Mahan, 2010), saving children from asthma attack among school workers (Goei et al., 2010), and intervening on
6 behalf of friends and family members who suffer from depression (Egbert, Miraldi, & Murniadi,
2014), among many health issues.
However, the EPPM has its limitations. Health messages using the EPPM at times fail to create adequate levels of fear and/or efficacy. These failures are primarily due to: (a) presenting the wrong threat and (b) message failure in building self-efficacy among audience.
One way to mitigate these limitations is by presenting identity threat or social threat as a replacement for health threat. Message designers can induce both identity and social threat is by making a particular social identity or identity more salient (Berger & Rand, 2008). Social identity itself refers to an individual’s understanding that he or she belongs to certain social groups or categories (Hoggs & Abrams, 1988; Tajfel, 1974). Meanwhile, identity refers to how an individual categorize himself or herself as an occupant of a role, and how he or she incorporate the self and society’s expectations and performances that come with the role (Burke
& Tully, 1977). Individuals choose the available categorizations as their basis for both social identity and identity, such as culture, nationality, religion, etc. (Turner, 1985). Once individuals find their social categories - such as being an American - they seek to maintain positive distinctiveness compared to other social groups - such as Russians or Mexicans – or to fulfil their role expectations as an American to build their self-esteem.
This study incorporates both role identity and social identity in its theoretical framework, and uses the concept of role identity threat in designing the EPPM messages pertaining to curbing excessive pornography consumption. This study also involves two elements of identity, which are: (a) the importance (or prominence, as some identity scholars refer to) of the social identity and (b) the salience of identity (McCall & Simmons, 1978). Throughout this paper, I distinguish between identity importance and identity salience.
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The importance or prominence of identity among individuals refers to the sense of belonging and commitment to a group membership role that a person internalizes as part of his or her self-concept, regardless of the situations (Tajfel & Turner, 1979). Identity importance is hierarchical. An identity is highly important when the individual views the identity role as being desirable from his or her point of view (Stryker & Serpe, 1994). Stryker and Sterpe (1994) suggested that an individual cognitively assigns which identities are more important than other identities to himself or herself, hence, resulting an overall order of identities from high to low importance.
Meanwhile, identity salience refers to the likelihood that a particular identity will activate across various circumstances (Stryker, 1968). Identity salience is also hierarchical. The higher the salience of an identity of an individual, the higher the probability that the particular identity will be brought in the different situations through verbal or non-verbal behaviors because the individual actively seeks an opportunity to perform that identity (Stets & Serpe, 2013).
The hierarchy of identity importance and salience becomes apparent when a person comes across a conflicting task. Whereas identity importance plays parts in one’s cognitive self, identity salience manifests in his or her behaviors. For instance, a student athlete may see herself as both a Communication major and a basketball player. If given the situation, she assesses her task as a student to be more important than her duty as an athlete, the student identity importance places higher than an athlete identity importance. If she later devotes more time studying for midterm exam in the following week and spends less time practicing basketball for the game on the weekend, then the Communication major identity places high in the salience hierarchy than a basketball player identity.
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In addition, from the social identity perspective, scholars contend that individuals do not normally wish to be marginal members of their social groups (Berger & Rand, 2008; White &
Dahl, 2006; White & Dahl, 2007). This is also called intragroup threat. In general, group members generally dislike and distrust marginal group members. Marginal members also have less influence than central members. Therefore, making one’s social group more salient along with inserting the threat of exclusion from one’s social group (or being marginalized within an individual’s social group) may be the basis of threat in a modified EPPM.
Other than the threat of being marginal in one’s own social group, individuals are also afraid of any affiliations with dissociative groups. This is also called intergroup threat. Turner
(1991) classified three types of social groups that serve as reference groups for individual behaviors: (a) membership groups, (b) aspirational groups, and (c) dissociative groups.
Membership groups refer to the group to which an individual voluntarily or involuntarily belongs, such as men and women or college students and high school students. Aspirational groups refer to groups to which an individual wishes to belong, such as athletes, celebrities, national heroes, or high-status occupations. Dissociative groups refer to groups to which an individual avoids belonging, such as criminals, “freaks,” “weirdos,” or other social pariahs.
The use of identity threat should particularly work well with the issue of pornography because consuming pornography often falls under as a socially deviant behavior. For instance, although rare, there is a positive correlation between pornography consumption and committing rape or between pornography consumption and owning/distributing child pornography materials
(Allen, D’Alessio, & Emmers-Sommer, 1999; Carr & vanDeusen, 2004). The modified EPPM could show how a message might threaten the audience by presenting the severity and susceptibility of falling into dissociative memberships or marginal members of the society.
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This type of threat should mitigate one of the issues concerning failures in the EPPM, which is presenting the wrong threats to the audience. Social threats can be made relevant to any audience because every individual belongs to social groups and strives to maintain his or her membership through performing certain behaviors (Turner, et al., 1987), whereas individuals may perceive health threats differently (Cameron et al., 2009). Also, an individual’s social identity can be made salient through contextual cues, such as a communication professor’s professional identity becomes more salient when he or she is put among students. As each social group prescribes different behaviors for its members, the communication professor in the case above would want to perform behaviors that are typical of a professor and would fear doing behaviors that are typical of students. In regard to the identity-based EPPM, the efficacy has two functions: (a) to make the individual feel that he or she is able to perform the behavior, which aligns with his or her role expectations, and (b) to make the individual believe that performing the behavior would secure his or her role and also place within his or her social group (social identity based-response efficacy).
To date, there are few studies that linked social identity (in the forms of presentation of a message character or testimony by a fellow social group member) with efficacy (Hoeken &
Geurts, 2005; Moyer-Guse et al., 2011; Phua, 2013). Unfortunately, those studies only examine how social identity correlates with self-efficacy, which leaves a gap in understanding how social identity can also influence response efficacy. Hence, this study extends the EPPM by connecting social identity with response efficacy by measuring both degree of salience in social identity and level of perceived response efficacy among participants.
Consequently, when using this identity-based EPPM, it is important to identify the salience of the relevant social identities of the target audience. In addition, each individual also
10 belongs to multiple social group memberships (Tajfel, 1974). For instance, an individual can belong to a group of mothers, Christians, and communication professors. Among the most salient social identities or group memberships are: (a) gender, (b) age, (c) family, (d) profession, and (e) religion (Garza & Herringer, 2001; Stryker, 1980; Tajfel, 1974; Turner, 1987; Weaver, Peters,
Koch, & Wilson, 2011).
Therefore, I designed the messages within this modified EPPM to make one’s role and social group membership more salient than others. For instance, in the case of a female Christian communication professor with children, the message could emphasize one of her multiple social identities. If the message focuses on her being a mother (instead of being a Christian or a communication professor), then the message should give recommendations as to what to do or not to do as a mother. In doing so, the message builds the individual’s fear of rejection by a group of mothers and efficacy of being able to comply with the recommendations as other mothers would.
Hence, this study contributes to the health communication literature in two ways: (a) it extends the EPPM, a popular tool in health persuasive messages, by inserting social threat and identity-based efficacy, and (b) applying the EPPM to compulsive and at-risk pornography consumption among a male population.
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Chapter II
Literature Review
History of pornography
The word “pornography” comes from a Greek word “pornographos,” which means the
“writing about harlots” (Vaughn, 2006). More than 2,000 years ago, early pornography appeared on wall frescoes, paintings, and Greek and Roman sculptures depicting sexual activities, and male and female genitals. Pornography then became a profitable industry, leading to the publication of Bocaccio’s Decameron in 1438 and Chaucer’s Canterbury Tales in 1387, which were the earliest obscene material since the invention of printing press (Vaughn, 2006).
The concept of pornography has changed over time (Buzzell, 2005). The number of sexually-oriented photographs began mushrooming and became public consumption. The development of movie technology in 1890s led to the numerous adult theatres across the nation.
More than a half century later, the first pornography magazine, Playboy, was published in
December 1953. Thus, as early as 1950s, individuals were able to consume pornography in the comfort of their own homes. In the late 1970s, this privilege became even greater with the introduction of videocassette recorders (VCR) and mail-order delivery.
Pornography videos were soon followed by the introduction of Internet by the end of the
20th century. Holmes, Tewksbury, and Holmes (1998) suggested that Internet propelled the increase in sexually explicit materials. In addition, Waskul (2002) noted that Internet provides a cost benefit in accessing pornographic sites compared to VCR and pornographic magazines.
Using evidence above, Buzzell (2005) highlighted three periods of pornography in the media: (a) the films in the 1970s, (b) the VCR in the 1980s, and (c) the Internet since 1990s.
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Cooper (1998) suggested that Internet pornography is unique compared to other forms of pornography due to its anonymity, accessibility, and affordability features. These features of
Internet pornography are more likely to entice individuals toward pornography as compared to porn magazines and porn DVDs because: (a) the Internet allows individuals to acquire the pornographic images from the privacy of one’s home, (b) the Internet allows individuals to keep the images hidden, and (c) the Internet eliminates the need of a retailer or a middle person between porn producers and consumers, hence avoiding embarrassment among consumers
(Cooper et al., 2000). These characteristics of Internet pornography caused Internet viewing among adult males to increase from 16% in 1980 to 25% in 2002, then to 70.4% in 2013
(Buzzell, 2005; General Social Survey, 1972-2002). In the online world, pornographic material is listed in 1 out of 4 inputs among search engines with approximate hits of 68 million (Carroll et al., 2008).
Cooper et al. (1999) argued that this fixation on consuming Internet pornography could fit into the definition of paraphilia, or sexual disorder involving sexual fantasies with non-human object. The American Psychiatric Association (2000) considered sexual compulsive online pornography consumption under Sexual Disorders Not Otherwise Specified in DSM-IV. This category refers as “distress about a pattern of repeated sexual relationships involving a succession of lovers who are experienced by the individual only as things to be used” (p. 582).
Some examples of this diagnosis include compulsive masturbation and compulsive fixation on an unattainable partner. Symptoms for this disorder include repetitive and intense sexually arousing fantasies and urges. Stein, Black, and Pienaar (2000) added that these urges can lead to the suffering and humiliation of the pornography users or users’ partner, children, and other non- consenting individuals.
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Among those who consume pornography are sexual compulsive and at-risk users (Cooper et al., 1999). Sexual compulsive users are those who browse the Internet looking for pornographic material as one way to fulfill their sexual needs, spending between one to 11 hours per week, whereas at-risk users are those whose online pornographic consumption has caused problems in their lives. At-risk users are individuals who have a vulnerability and proclivity for sexual disorders. The users may never have had this problem had it not been for the Internet pornography. These people may spend more than eleven hours per week engaged with Internet pornography (Cooper et al., 1999).
Consequently, communication and health scholars noted the importance of investigating this phenomenon (Bridges et al., 2003; Cooper et al., 2000; Cooper et al., 2004; Weaver et al.,
2011; Wright, 2013; Zillman & Bryant, 1988). The General Social Survey (GSS), a sociological survey conducted by the National Research Opinion Center of the University of Chicago, is responsible for measuring public consumption of pornography. Since 1973, the GSS has surveyed the American population regarding their demographic characteristics, such as race, marital status, or education, and their habits, such as church attendance, sexual behaviors, or the amount of pornographic materials they view every year (Patterson & Price, 2012). The extensive information that GSS gathers allows scholars to explore relationships between pornography consumption and its effects in the individuals.
Pornography as a health and social issue
Within the realm of health, pornography use correlates with mental health issues and risk- taking behaviors, including addictions (Ross, Mansson, & Daneback, 2011), greater depressive symptoms (Weaver et al., 2011), higher consumption of alcohol (Carroll et al., 2008; Svedin,
Akerman, & Priebe, 2011), sexual risk taking (Peter & Valkenburg, 2011), negative attitudes
14 toward condom use (Wingood et al., 2001; Traen, Sitgum, & Eskild, 2002), less sexual contentment (Stulhofer, Jelovica, & Ruzic, 2008), substance abuse (Carroll et al., 2008), and substance abuse during sexual encounters (Braun-Corville & Rojas, 2009). Using GSS data from
1973 to 2010, Wright (2013) concluded that sexual compulsive and at-risk consumption of pornography can lead men to: (a) have multiple sexual partners, (b) pay for sex, (c) view teenage sex in a positive light, and (d) engage in extramarital sex.
Millennials have vastly different experience compared to the older generations when it comes to pornography viewing. During the 1940s, less than 1% of men under 30 experienced erectile dysfunction. The number went up to 7% in early 1990s and in the 2000s, the number is as high as 30% for men under 30 (Bridges et al., 2010). Interestingly, in most cases their erectile dysfunction occurred when the men are with their partners but not when these men are viewing pornography (Voon et al., 2014).
Some scholars suggested that the detrimental effects of pornography on health are increasing partly because today’s pornography content of today is unlike those contents in the early years of pornography (Bridges et al., 2010). The depiction of violence, both physical and verbal, is all too common within pornographic video materials, ranging from 76% to 94% of the performers’ behaviors. Among the audience, 95% of them either favored the violence or had no objections.
Pornography correlates with having distorted views of family values and risky behaviors as well. In one noted experiment by Zillman and Bryant (1988) involving University of Alabama students, they divided 160 heterosexual participants into: a) a control group, who then regularly watched a comedy show, and b) an experiment group, who then regularly viewed non-violent pornography. The exposure occurred for one hour per week and lasted for six consecutive weeks.
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At the end of the six weeks, those who were in the experiment group reported higher acceptance of extramarital sex and nonexclusive sexual access to their intimate partners.
Of all the effects above, the addictive nature of Internet pornography is the most often discussed (Carnes, 2001; Carnes, Delmonico, & Griffin, 2001; Cooper et al., 2001; Cooper et al.,
2000; Cooper et al., 2004; Cooper et al., 1999; Cooper, Scherer, Boies, & Gordon, 1999;
Delmonico, Griffin, & Moriarty, 2001; Delmonico, 1997; Waskul, 2004). Many scholars refer to this type of addiction as compulsive pornography use (CPU). CPU is defined as the lack of ability to refrain from consuming more than an hour per week of pornography, which leads to negative effects on the quality of one’s life (Coleman, Miner, Ohlerking, & Raymond, 2001;
McBride, Reece, & Sanders, 2007). McBride et al. (2007) suggested that CPU leads to guilty feelings, personal distress, financial/productivity loss, poor performance at work/school, and damaged intimate relationships. Hence, consuming pornography for more than an hour per week is also positively related to one’s frequency of seeing mental health providers (Cooper et al.,
2001). Kuzma and Black (2008) estimated that 1.5% to 3% of U.S. adult population falls into the category of individuals with CPU.
Perhaps one of the most convincing arguments on the effects of pornography on health comes from Wilson (2014). In his book, Your Brain on Porn, he detailed studies by neurologists, which showed brain scans of heterosexual male pornography consumers. The brain scans results suggested that: (a) the brains reacted to women as if they were objects, rather than individuals,
(b) the brains were less able to wait for gratification, which suggested possibility of addiction, and (c) the slowing down of short-term memory. Voon et al. (2014) corroborated claims made by this book in their study by showing evidence that pornography triggered brain activity among heavy pornography viewers similar to that trigger by drugs among drug addicts.
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In terms of social issues, there are few meta-analyses examining pornography effects on the individuals consuming pornography. The latest meta-analysis comes from Wright, Tokunaga, and Kraus (2015) who compiled 22 studies from seven countries dated 1994 to 2011. They concluded that pornography effects in other countries were similar than those in the US. These effects include higher verbally coercive threatening communication in asking for sex and sexual harassment that correlated with higher consumption of pornography.
Oddone-Paolucci, Genuis, and Violato (2000) looked at 46 studies on the effects of pornography done in U.S., Canada, and Europe between 1962 and 1995 involving 12,323 samples of individuals. They concluded that pornography use correlated with: (a) experiencing problems in individuals’ intimate relationships, such as viewing intimate partners as objects, (b) committing sexual deviancy, such as masturbating in public places, (c) committing sexual offenses, such as rape, and (d) supporting belief that victims are to blame in rape cases.
Allen, D’Alessio, and Brezgel (1995) conducted another meta-analysis. Allen et al.
(1995) examined 30 studies conducted from 1971 to 1984. Because during the time of those studies the Internet was not available, the pornographic materials included in the analysis were in the form of pictures, videos, films, and written materials. This meta-analysis found that: (a) there is a strong correlation between viewing violent pornography and aggression, (b) there is a small correlation between viewing pornography and aggression, and (c) viewing non-violent pornography slightly increases aggressive behaviors.
The ubiquity of pornography on the Internet brings problems to the families and intimate partners (Manning, 2006; Marks, 2004). Pornography has negative effects on intimate/marital relationships and satisfaction (Bergner & Bridges, 2002; Bridges et al., 2003; Manning, 2006;
Schneider, 2000; Zillman & Bryant, 1988). Using 100 individuals who were in relationships,
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Bergner and Bridges (2002) concluded that married women were more distressed than women in dating relationships with their partner’s online pornography habit. The level of distress increases with the perceived amount of pornography consumption by one’s partner. In Schneider’s (2000) study among individuals who dated or were married to Internet addiction patients, it showed that
100% of the Internet addiction involved downloading pornographic material. In addition, more than half of divorces are due to a pornography habit (Manning, 2006). Manning (2006) used the data from 1,600 divorce and matrimonial law attorneys who specialize in divorce and legal separation. According to these lawyers, the Internet had a significant factor in the divorce cases that they handled in the previous year. Among these cases, 56% of them involved one person in the relationships having an obsessive interest in online pornography. Children can also fall victim to Internet pornography. Manning (2006) suggested that the average age when children started viewing pornography online is nine.
Sexual compulsive and at-risk consumption of pornography may lead individuals to anti- social behaviors, such as men’s negative views of women (Allen et al., 1995; Hald et al., 2010;
Oddone-Paolucci et al., 2000; Zillman & Bryant, 1988). In Zillman and Bryant’s (1988) experiment, the control group and experimental group who viewed non-sexual comedies and X- rated videos, respectively, for six consecutive weeks. During the seventh week, participants in the experimental group reported a higher acceptance of: (a) extramarital affairs, (b) male dominance and female servitude, and (c) allowing one’s romantic/sexual partner to have another sexual partner, as compared to those in the control group. Those who viewed pornographic materials also placed a lower value on: (a) the importance of marriage and (b) the desire to have children.
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In a study that investigated women’s responses to their male partners’ use of pornography, Bridges et al. (2003) gathered and examined 100 online posts written by female participants who were currently in a heterosexual relationship with a man addicted to online pornography. These online posts asked for solution and emotional support from others who share their experience. From reading the posts, Bridges et al. (2003) depicted how these women experience emotional distress. The three stages that these women experienced were: (a) reappraisal of the relationship, (b) negative views of themselves, and (c) negative views of partner. Many of the women in the online group felt betrayed by their partners, in that their addict partner preferred the pornographic models rather than the women in the study. These women also viewed themselves more negatively. Among the descriptions that these women labeled themselves included being physically unattractive, inadequate, or being a warm body to be used by the addict partner for sexual gratification after viewing pornographic materials.
Finally, these women came to conclusion that their addict partner is not the person they thought they knew, and their relationships began to deteriorate.
Negative emotions or unhappiness with the relationships was the common theme among individuals whose partners consume online pornography regularly (Schneider, 2000). In a qualitative study involving 91 women and 3 men who were involved in a (heterosexual or homosexual) romantic relationship with an online pornography addict, Schneider (2000) found that partners of sex addicts felt devastated, hurt, betrayed, and humiliated by their partners.
Participants also reported that they lost their trust toward the addict partner. Addict partners would often make excuses to avoid sex, appear distant and only concerned with their pleasure, and demand their partner to reenact the sexual activities that the addict partner found online. In most of the cases in the study, the negative effects of pornography also affected their children.
19
These children lost parental time, saw pornography themselves, or became witness to their parents’ arguments (Schneider, 2000).
Topic of objectification of women is also rampant on studies of pornography (Klaasen &
Peter, 2015; Orenstein, 2016). Objectification of women consists of two parts, which are: (a) instrumentality or using women as a tool for user’s own purpose, and (b) dehumanization or denying women’s thoughts and feelings (Loughnan et al., 2010). In their content analysis study,
Klaasen and Peter (2015) compiled 400 videos from Pornhub, RedTube, xHamster, and
YouPorn, with more than 300,000 views by February 2013. They suggested that instrumentality occurred more than 80% of the time, whereas dehumanization happened more than 90% of the time, ranging from any close-ups of body parts (instrumentality) to sex for own pleasure
(dehumanization). Whereas the cases for instrumentality and dehumanization applied for both sexes, the most often contents were from the male performers toward female performers.
Klaasen and Peter (2015) emphasized that pornography videos are “depicting women as
‘interchangeable’ objects who lack agency and whose feelings are unimportant” (p. 722).
Based on the above studies, pornography affects both the users and the romantic partners of the users. In most cases, the users are males (Boies, 2002; Cooper et al., 2004; Wright &
Randall, 2012), whereas the partners affected are usually female (Bridges et al., 2003; Schneider,
2000). However, it is also common for women to regularly view pornography (Carroll et al.,
2008; Cooper, 2002), or for men in homosexual relationships and children to be negatively affected by their partners’ or parents’ sexual compulsive and at-risk consumption of pornography respectively (Bridges et al., 2008; Schneider, 2000).
Gender differences in using pornography
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In terms of the demographics of the viewers, there are significant differences when it comes to gender. Malemuth (1996) suggested that pornography was originally produced to cater to the male audiences. Since its inception, Internet pornography male users consistently outnumber female users in surveys (Boies, 2002; Cooper et al., 2004; Goodson et al., 2000).
Males are also more likely to distribute pornographic materials. They are twice more likely than females to forward the pornographic materials to their friends (Boies, 2002).
In a study by Goodson et al. (2000), the findings suggested that women were significantly less likely to feel entertained or sexually aroused when viewing Internet pornography. In addition, women were more likely than men to report feeling embarrassed, angry, and disgusted with what they saw. Based on this reason, Wright (2010) found that many feminists who are concerned about pornography’s adverse effects on women spearheaded anti-pornography movements.
Because sexual compulsive and at risk pornography consumption is problematic, the goal of this study is to reduce pornography consumption to minimum, at the very least it becomes recreational pornography consumption, which is less than one hour per week. As seen in the previous studies, sexual compulsive and at risk pornography consumption correlate with an array of health and social issues. These health issues included having multiple sexual partners (Wright,
2013), engaging in unsafe sex (Wingood et al., 2001), substance abuse during sex (Braun-
Corville & Rojas, 2009), whereas the social issues included divorce (Manning, 2006), acceptance toward extramarital affairs (Bryant & Zillman, 2006), and blaming victims in rape cases
(Oddone-Paolucci et al., 2000).
The Extended Parallel Process Model
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Due to the detrimental effects that Internet pornography consumption has on sexual compulsive and at risk users, it is necessary to consider designing a health communication campaign to curb sexual compulsive and at-risk consumption of Internet pornography. Such campaigns commonly use fear appeals messages. Fear appeals refer to a persuasive element that scares individuals through descriptions of unwanted consequences that may occur if the individuals do not follow the message recommendation (Rogers, 1985; Witte, 1992). Nabi
(2002) suggested that fear is a gripping persuasive tool, which is capable of organizing and directing perceptual cognitive processes. In general, fear or threatening information can motivate people to avoid the effects of the fear.
There has been a number of meta-analyses on the effectiveness of fear-appeals in campaigns or persuasive messages (Boster & Mongeau, 1984; Floyd, Prentice-Dunn, & Rogers,
2000; Hale & Dillard, 1995; Rogers, 1983; Witte & Allen, 2000). Those meta-analyses show how fear-appeal based theories developed over time and built one upon another. These fear- appeals theories include: (a) Janis and Feshbach’s (1953) drive explanation, (b) Leventhal’s
(1970) parallel response model, (c) Rogers (1975, 1983) protection motivation theory, (d)
Witte’s (1992, 1998) extended parallel process model (EPPM), and (e) Rimal and Real’s (2003) risk perception attitude (RPA) framework.
Of all the theories using fear appeals message, I chose the EPPM as the framework in curbing sexual compulsive and at-risk use of Internet pornography because it is the most theoretically extensive and the most widely used in the past decade (Maloney, Lapinski, & Witte,
2011). The EPPM is an expansion of the previous fear appeals theoretical approaches (Janis,
1967; Leventhal, 1970; Rogers, 1975, 1983; Witte, 1992, 1998). A search on the EBSCOhost and PubMed at 7.00 – 7.20 am EST on January 14, 2018 using “EPPM” as a keyword gathered
22 most scholarly journal articles at 133 in EBSCOHost and 55 in PubMed. This is more than other fear appeal models, which included “drive theory of motivation” related to fear appeals messages
(119 and 51), “protection motivation theory” related to fear appeals messages (99 and 29), “risk perception attitude” related to fear appeals messages (62 and 22), and “parallel response model” related to fear appeals messages (16 and 11).
The development of the EPPM
Janis and Feshbach (1953) were the first to conduct an experiment testing the effectiveness of fear in conforming to the message recommendation. In their study, 200
Connecticut high-school students watched movies depicting consequences of poor dental hygiene. They were placed into three conditions: (a) high-fear, (b) medium-fear, and (c) low- fear. The fears displayed ranged from tooth decay, gum disease, to cancer. Initially, students in high-fear condition were impressed with the depiction, whereas students in low-fear condition thought the movie was boring. After a week, however, only 28% of students in high-fear condition reported a change in their tooth-brushing behavior, whereas 50% of students in low- fear condition changed their tooth-brushing behavior. Janis and Feshbach (1953) suggested that whereas high fear is more useful in attracting audience’s attention than low fear, minimal fear is more effective than maximum fear in promoting a behavior change.
Following Janis and Feshbach’s (1953) study, subsequent studies on the effectiveness of fear in persuasive messages promoting health behaviors gathered mixed results. Several studies supported Janis and Feshbach’s (1953) finding by suggesting that low-fear is more effective than high fear (De Wolfe & Governale, 1964; Insko, Arkoff, & lnsko, 1965). Others suggested that low-fear is less effective than high-fear (Dabbs & Leventhal, 1966; Hewgill & Miller, 1965;
Powell, 1965; Kornzweig, 1967; Leventhal, Jones, & Trembly, 1966). One study did not show
23 any significant difference between high-fear and low-fear (Radelfinger, 1963). In addition to dental hygiene (Goldstein, 1956; Haefner, 1959), topics of persuasion included the danger of smoking (Insko, Arkoff, & lnsko, 1965), the risks of getting tuberculosis (De Wolfe &
Governale, 1964), the risks of getting tetanus (Dabbs & Leventhal, 1966), and auto safety
(Berkowitz & Cottingham, 1960; Leventhal & Niles, 1964).
These contrasting results led health scholars to propose a drive theories approach (Witte
& Allen, 2000). Drive theories come with several names, including: (a) Hovland, Janis, and
Kelley’s (1953) fear-as-acquired model, (b) Janis’s (1967) family of curves, and (c) McGuire’s
(1968) nonmonotonic model. Hovland et al. (1953) suggested that for a persuasive message to work, the audience first need to feel the threat presented within the message. Individuals then comply with the message to reduce the fear or the drive. The behaviors to reduce the fear then become rewarding to the individuals and lead the individuals to adopt the behaviors.
Janis’s (1967) family of curves elaborated the model by suggesting an inverse U-shape model representing the effectiveness of fear. Janis (1967) proposed that initially, the increase of fear will increase persuasiveness of the message until it hits the optimal level of the fear-aroused persuasion. An addition of fear after this point will decrease the persuasive effects of the message due to overwhelming emotional tension, which paralyzes the audience.
McGuire (1968) proposed nonmonotonic model, which shows the inverse U model of correlation between the level of attitude change and the level of fear. This is similar to Janis’s
(1967) family of curves. McGuire’s (1968) model shows a nonmonotonic relationship between fear/awareness and attitude change. Attitude change is at its maximum level when the level of fear/awareness is moderate. Hence, there are two effects of fear: (a) too much fear, which will
24 interfere with message acceptance and lead to boomerang effect in term of behavior change, and
(b) the right amount of fear, which will motivate individuals to comply with the message.
However, McGuire (1968) also noted how several individual traits – self-esteem, intelligence, freedom from anxiety – play significant roles on how the individuals perceive the fear or the threat presented within the message. In this case, what an individual perceives as being high in fear may not be the same for other individuals. Due to these individual differences, it would be difficult to create a message that caters to all individuals. These limitations of drive theories unfortunately persist within the current studies of fear appeal messages.
Leventhal (1970) later proposed parallel response model, which explains the functions of fear in fear appeals message. The model suggested that individuals’ motivation to comply with the message can be categorized into: (a) danger control process, or cognitive reactions, and (b) fear control process, or emotional reactions. In a danger control process, an individual will comply with the message to control the dangers or consequences of the threat presented in the message. This leads to attitude or behavior changes. Meanwhile, in fear control process, individuals focus on their fear and try to control their fear. This leads to denial toward the dangers or consequences posed by the threat.
Next, Rogers (1975) introduced the concept of efficacy to the fear appeal literature.
According to Rogers, inconsistent findings pertaining to fear appeals are due to three crucial components that moderate the effects of fear appeal messages: (a) the severity of the consequences, also known as severity (b) the probability of the individuals to experience the consequences, also known as susceptibility, and (c) the efficacy of the coping response. Maddux and Rogers (1983) later classified the efficacy of the coping response as: (a) self-efficacy, or
25 individual’s belief in himself or herself being able in controlling the threat, and (b) response efficacy, or individual’s belief that the environment is conducive in controlling the threat.
Rogers (1983) found that many individuals choose to regulate the effects of fear and overlook the severity of the fear, which Leventhal (1970) referred to as the fear control process.
This tendency to neglect the feeling of fear without addressing it refers to a maladaptive coping response. Some of the examples of maladaptive coping responses include “If it’s time for me to die, then I cannot do anything about it” (avoidance), “It can happen to other people, but not me”
(lack of perceived susceptibility) or “Just pray and everything will be alright” (lack of perceived self-efficacy).
Rogers (1983) also suggested that maladaptive coping responses occur due to the lack of perceived susceptibility and efficacy. In his theory, known as protection motivation, Rogers
(1983) proposed that the interaction between severity, susceptibility, and efficacy is necessary to create positive message acceptance, which leads to attitude and behavior change. Again, similar to Leventhal (1970), empirical evidence did not fully support this notion (Rogers, 1985). Studies testing this theory found that either severity or probability will interact with either self or response efficacy, but failed to explain when and how fear appeals will work or not (Kleinot &
Rogers, 1982; Maddux & Rogers, 1983; Mulilis & Lippa, 1990; Wurtele & Maddux, 1987).
Witte (1992) then proposed the extended parallel process model (EPPM). The EPPM examines the outcome variable of fear appeals message based on the four components from
Rogers’ (1975, 1983) protection motivation theory: (a) severity, (b) susceptibility, (c) self- efficacy, and (d) response efficacy.
The ideal outcome variable in fear appeal message is message acceptance, which refers to audience’s attitude, intention, or behavior change after viewing the message. With low severity
26 and/or susceptibility, individuals are not motivated to process the message further. Meanwhile, with high severity and susceptibility, individuals are motivated to continue to the next stage, which is efficacy. Next, when the degree of self-efficacy and/or response efficacy is low, individuals will cater to their fear and deny the legitimacy of their fear – also called fear control process. With low efficacy, individuals control their fear through emotion by rejecting the message. On the other hand, when both self-efficacy and response efficacy are high, individuals will respond to the danger or the consequences of the threat – also called the danger control process. With high efficacy, individuals control the danger through their cognitive process and adjust their attitude and behavior to deter the threat by accepting the message recommendations.
In short, Witte (1992) suggested that maximum behavioral intention to follow message recommendations will be attained when both threat and efficacy are high (HTHE), and not when only threat is high (HTLE) or when only efficacy is high (LTHE). Yet, having one element, either threat or efficacy being high, is still more effective than both threat and efficacy being low.
Using her reviews of EPPM, it can be concluded that HTHE > HTLE = LTHE > LTLE (Witte,
1992, 1996).
Figure 1. Diagram of Witte’s (1992) Health EPPM
Message Perceived Protection Message acceptance components: Efficacy Motivation (Self-Efficacy & Severity Response Susceptibility Efficacy) Self-efficacy FEAR Response Perceived Threat efficacy (Severity & Susceptibility) Defensive Message rejection Motivation
No Threat Perceived Message ignored
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Knowing the precise meanings of the variables involved above is important in applying this model to persuasive health messages (Figure 1). Fear is the audience’s emotion (Witte,
1992). O’Keefe (1990) contended that fear is measured by the level of physiological and psychological arousal experienced by the audience. Threat is the environmental danger perceived by the audience, which then activates the emotion, fear. Efficacy consists of two parts: (a) response efficacy, or the effectiveness of the message recommendations, and (b) self-efficacy, or the audience’s perceived abilities in doing the message recommendations. The mechanism of the variables then works as follows: threats evoke fear, which prompts the audience to react based on the perceived response efficacy and self-efficacy.
Current trends in the EPPM research
For the most part, studies on the relationships between message acceptance and the components of fear and efficacy in the EPPM have gained significant empirical support. Since its inception in 1992, the EPPM has made its presence in different health promotion contexts.
Recent research that supports the credence of the EPPM includes promoting the use of condoms among general population to prevent HIV infection (Casey et al., 2009), the intention to quit smoking among heavy smokers (Wong & Cappella, 2009), hand washing behavior among college students (Botta, Dunker, Fenson-Hood, Maltarich, & McDonald, 2008), testing patients’ level of kidney functioning or kidney disease among physicians (Roberto, Goodall, West &
Mahan, 2010), and saving children from asthma attack among school workers (Goei et al., 2010).
Like all persuasive models, the EPPM has its limitations. Health messages designed to test the validity of the EPPM oftentimes fail to create fear and/or efficacy. These failures are primarily due to: (a) presenting the wrong threat toward the audience, (b) message failure in building self-efficacy among audience, and (c) the additive model of the EPPM.
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Presenting the wrong threat to the audience. Many times health messages using fear appeals fail to evoke relevant fear in the audience. One of the reasons why this happens is that those individuals responsible for designing message could not identify the kind of threat that is compatible for the audience that the message is targeting (Botta et al., 2008; Timmers, 2004;
Timmers & van der Wijst, 2007). Timmers (2004) found at least four different categories of fear of smoking that are prevalent among Dutch teenagers: (a) health, such as getting lung cancer, (b) sexuality, such as having bad breath, (c) being social, such as harming others, or (d) looks, such as having ugly teeth. This distinction becomes important when a health practitioner designs a campaign. A message showing how smoking causes lung cancer would be ineffective for a target audience concerned more about their looks than their physical health.
Health campaigners need to know which particular kind of fear to pick from to create an effective message. For instance, Botta et al. (2008) found that in addressing the importance of washing hands among college students, health threats may not be effective in evoking fear.
Instead, the study suggested that messages emphasizing the squalor of dirty hands were more effective. Messages containing words such as “you just peed, wash your hands” or “poo on you, wash your hands,” along with vivid pictures, resulted in an increase in hand-washing behaviors among students.
Message failure to build self-efficacy. A basic rule of the EPPM states that when there is a threat, there should be efficacy. However, numerous fear appeal messages present threat without building audience’s self-efficacy (Witte & Allen, 2000). Similar to individual differences in perceiving threat, there are many factors that influence individuals in perceiving self and response efficacy. Some of the factors include individuals’ social skills, social support, and family communication culture (Hecht, Warren, Wagstaff, & Elek, 2008; Koesten, Miller, &
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Hummer, 2001; Velu, Melkote, & Skinner, 2005). Presenting the right message that builds audience’s self and response efficacy remains a challenge for health communication scholars, as this area still merits further exploration.
From the evidence above, it is clear that EPPM is dependent on the individual differences in processing fear appeal message. High threat for one person may not necessarily be the same for another person. For instance, when addressing the college student population on the dangers of consuming Internet pornography for more than an hour per week, students may underestimate the threat presented within the message. This is because many students are high sensation- seekers, which is part of biosocial traits characterized by tendency to engage in risky behaviors that involve dangers or novel physical experience (Lee & Ferguson, 2002, Sheer, 1995;
Zuckerman, 1979). In this case, the same fear appeal message would only be effective for the students who are low sensation seekers, and students who are high in sensation seeking would ignore this type of fear appeal message.
Although EPPM has addressed various health issues, the issue of excessive pornography consumption remains untouched by any fear appeal study. Using the fear and efficacy elements of the EPPM, health practitioners could design messages that correspond with pornography as a health issue. For instance, a message that highlights the severity of pornography could be sexual compulsive and at-risk pornography use leads to severe health consequences. In term of susceptibility, the message could be: “I am susceptible to fall into using pornography for more than an hour per week.” Self-efficacy could be inserted in a message saying: “I have the ability to cease my pornography use or limit my pornography use to less than an hour per week.”
Finally, message containing response efficacy would be: “Limit my pornography use to less than
30 an hour per week would prevent me from the health consequences due to sexual compulsive and at-risk pornography use.”
Additive Model of the EPPM. In the early stage of the conception of the EPPM, Witte and
Allen (2000) had pondered about the possibility of additive nature of the theory, or the additive model of EPPM. Additive model refers to the fact that threat alone or efficacy alone is more persuasive than the combination of high threat and high efficacy. Recent studies in the EPPM and fear appeals messages tend to support this notion (Duong & Bradshaw, 2013; Jasemzadeh et al., 2016; Roberto & Goodall, 2011; von Gottberg et al., 2016). Meta-analysis of previous fear appeal studies suggested that both multiplicative and additive model of the EPPM are highly correlated and thus, fit the data in eliciting the most persuasive health messages. In their meta- analysis, Witte and Allen (2000) suggested that although the EPPM and the additive model both fit the data, the patterns are more consistent with the additive model. Roberto and Goodall (2009) also suggested that the additive model works better in predicting the behavioral intentions compared to the multiplicative model.
This prompted Mongeau (2013) to conduct a review of the EPPM. In his analysis, he found that threat alone or efficacy alone is more persuasive than the multiplicative model of the
EPPM suggests. He concluded that the additive model should explain a better picture of the
EPPM than the multiplicative model. In short, whereas the studies prior to the EPPM suggest multiplicative model, studies after 2000 support the additive model.
Social Identity Theory
One of the limitations in the EPPM, which is presenting wrong threats to the audience, is due to individual differences in processing the health persuasive message. Because of this, social identity theory could be a helpful addition to the EPPM. Tajfel’s (1974) social identity theory
31 suggests that individuals classify themselves and others into different social categories. These categories are based on their personal self and their social self, such as “I am a woman,” “I am
American,” or “I am a teacher.” These social categories have two functions: (a) making sense of an individual’s social environment by providing a way to describe others, and (b) helping an individual to describe himself or herself in his or her social environment by associating the individual to certain characteristics (Tajfel & Turner, 1986). Social identity theory (SIT) is essentially a theory that highlights how individuals feel that there are particular groups where they belong (Ashforth & Mael, 1989).
Furthermore, SIT contends that each individual has two distinct yet related aspects of the self, which are: (a) our shared characteristics, such as race, sex, or nationality, and (b) our individual identity that stems from our idiosyncratic characteristics, which are personal in nature and parts of individual differences (Tajfel, 1978). The main tenet of this theory concerns with intergroup relationship, such as how individuals view themselves as part of the in-group as opposed with the out-group. When the feeling of shared characteristics is high, the individual then experiences depersonalization, which is the process of personal identity becoming irrelevant
(Stets & Burke, 2000).
The multiple levels of social identity argue that each individual has different selves that integrate to form a wider, cohesive self-concept. Brewer (2008) proposed that each individual has multiple needs of belongingness. The individual self needs to connect and bond to other individuals. The collective self needs to be included in larger social groups. For example, the author knew two working class Muslim Bosnians who lived in a predominantly white, Christian, affluent town in Kentucky1. These two would feel the need to connect with each other due to
1 Around 10% of the population of Bowling Green, Kentucky consists of Bosnian refugees (Celik, 2012).
32 their similarities in religious practices and ethnic background and (b) their need to belong in a larger social group, such as Muslims in Kentucky or Bosnians in Kentucky.
Whereas the early application of social identity theory focused on the demographics of individuals – such as gender, age, or socioeconomic status (Tajfel, et al., 1970; Turner, 1972), the subsequent studies using social identity theory extended the concept of social identity into “a complex integration of personality attributes, unique experiences, and personal choices” (Babad,
Birnbaum, & Benne, 1983, p. 37). These attributes, experiences, and choices of each individual include: physical attractiveness (Stevens, Owens, & Schaefer, 1990), personality traits
(Banikiotes & Neimeyer, 1981), attitudes (Byrne, Baskett, & Hodges, 1971), and hobbies
(Werner & Parmelee, 1979).
Therefore, not only do the groups to which we belong by fate have an influence on our social identity, but our personal attitudes, values, and to some extent, past history, also play some roles in shaping our identity. The variety of social identities may include those who are ethnically Bosnians (attributes), those who lived in Kentucky (unique experience), those who cheer for New Orleans Saints (attitude), those who own a Subaru (choice), or those who voted for Barack Obama (past history).
Social Categorization Theory
SIT provides the basis for self-categorization theory (Turner et al., 1987). This theory engages SIT by stating that individuals choose to “identify with groups, construe themselves and others in group terms, and manifest group behaviors” (Hogg & Reid, 2006, p. 9). The degree of individuals’ identification toward their groups becomes a factor in how much individuals will adopt group level behaviors. Identification refers to the extent to which an in-group member defines the self as a member of the particular social group (Rothgerber, 1997). When individuals
33 feel strongly that they belong to a group, they will behave more according to the group’s norms
(Hogg & Abrams, 1988). This is because behaving according to the group norms will give positive feelings toward the individuals with high social identity, especially when interacting with fellow group members (Levine & Moreland, 1998).
Furthermore, this theory concerns with the process of social identity formation (Stets &
Burke, 2000). This formation of social identity requires: (a) self-categorization and (b) social comparison.
In self-categorization, the individual feels “the accentuation of perceived similarities between the self and other in-group members and the accentuation of the perceived differences between the self and other out-group members” (Stets & Burke, 2000, p. 225). This happens when an individual compares oneself to similar others and those who are different from oneself.
The accentuation transpires into the individual’s values, beliefs, attitudes, norms, personal appearances, and other elements that highlight intergroup categorizations at different hierarchical levels, ranging from personal, such as being a male Republican from Kentucky, to something universal, such as being an American.
Next, the social comparison process would filter the accentuation of similarities and differences, resulting in the positive evaluation toward the in-group characteristics and negative evaluation toward out-group characteristics. An example would be biasedly viewing one’s political affiliation as something positive and judged other individuals from different parties as negative. This biased view reflects in the individual’s subsequent behavior such as only consuming media that strengthens their biased view (Lin, Haridakis, & Hanson, 2016).
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Identity Theory
Because the formation identity is such a constant and complex process, another theory emerges to explain identity formation, which is Identity Theory. This theory contends that as components of the self, each individual’s identity occupies a particular role, such as being a chef, or being a husband (Stets & Burke, 2000). Each individual’s identities come with roles and expectations from oneself and others to guide the individual’s behaviors (Gecas & Burke, 1995;
Stets & Burke, 2003). For instance, the society and an individual who identifies as a chef expect himself to be able to cook quality dishes and present the dishes aesthetically to a group of diners.
This notion of how individuals strive to fulfill their roles becomes the framework of Identity
Theory (Stets & Burke, 2000).
Whereas SIT focuses on the static nature of self as belonging to others, Stryker & Burke
(2000) highlights the dynamics of the self-identification process. According Identity Theory, identities and their associated expectations serve as a standard of reference for individual’s behaviors. Each individual consistently modifies his or her identity and behaviors to create congruency between his or her identity and his or her behaviors. For example, someone who identifies as a teacher would strive to perform behaviors that match with his or her roles as a teacher, such as teaching, nurturing, and caring for the students. Stets and Burke (2003) suggested that a mismatch between one’s identity and behaviors leads to negative emotions whereas matching one’s identity and behaviors creates positive emotions.
Thus, Identity Theory posits that individuals regulate their behavior in a manner that is consistent with their goal identity (Gecas & Burke, 2003). Individual self refers to the
“psychological apparatus that allows individuals to think consciously about themselves” and creates goal identity (Leary & Price Tangney, 2003, p.8). When an individual engage in actions
35 that align with his or her goal identity, Identity Theory refers to it as self-verification (Stets &
Burke, 2000).
Identity Theory has proven useful in predicting behaviors. Stryker and Serpe (1982) suggested that level of commitment to a religious identity predicted salience of that same identity and amount of time spent engaging in religious activities. In another study, individuals’ identification with “being blood donors” identity significantly predicted the number of donations
(Callero, 1985). In addition, strong identity as a mother predicted acceptance of the motherhood role and willingness to make sacrifices for one’s children among a sample of first time mothers
(Nuttbrock & Freudinger, 1991).
Similar to SIT, Identity theory also concerns the multiplicity of selves (McCall &
Simmons, 1978; Stryker, 1968). In short, identity theory states that individuals perform role- related behaviors as the products of reciprocal relationships between the self and society. These roles then developed into role-identities (Hogg, Terry, & White, 1995; Stryker, 1968).
The different “categories” or “social groups” mentioned by SIT above are the equivalent of the different “roles” in identity theory. In SIT, these categories are formed through using self- categorization process where individuals: (a) view themselves as part of those within the same category, (b) view others who are similar as in-groups and (c) view others who are different as outgroups. In Identity theory, these roles are the results of society’s expectations on one’s roles and performances. In SIT,
Having a certain role means: (a) taking action to achieve the expectations of that particular role, (b) interacting with the role partners, and (c) managing one’s surroundings to fit with the role’s tasks and responsibilities (Stets & Burke, 2000). For example, having the role of a parent means taking care of one’s child physically and emotionally, interacts with the child’s
36 caregivers, and works to provide for the child. Role is “what you would do” whereas category is
“what you feel you are”.
Identity Importance, Salience, and Commitment
Identity theory states that individuals have multiple role identities that respond to the social roles. Serpe (1987) suggested that individuals often face the dilemma of having role choices, or the situation where individuals have to choose one role over another. The decision in enacting certain role is not necessarily linear with our cognitive schemas of our identity (identity importance), but rather follows the hierarchy of identity salience.
Identity salience refers to how much likelihood that one’s particular identity will be active in various situations (Stryker, 1980). Identity salience influences how each individual acts in various situations. The level of salience of an individual’s identity corresponds to the expectations that come with the particular identity (Stryker & Burke, 2000).
Because the self is a product of social expectations and observations, identity salience changes constantly over time. For example, a person who migrated to the US from Bosnia as a child might have both Bosnian being an ethnic identity, and American as a national identity.
However, as he lives longer in the US and converses with people around him in English, rather than Bosnian, his identity salience as an American moves upward in the hierarchy, while his ethnic identity as a Bosnian, move lower in the hierarchy.
The mobility of identity salience is due to several factors, such as support, reward, and perceived opportunity structure (McCall & Simmons, 1978). Support refers to the people around him who directly or indirectly strengthen his identity salience. Rewards mean intrinsic and extrinsic prizes that he gets from enacting the American identity. Perceived opportunity structure is the difference between rewards and costs for behaving his role in social situations.
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For example, when he is watching a soccer match between Bosnia and USA teams, does he receive more reward by displaying an American flag from his social environment?
On the other hand, identity importance, or some scholars refer to it as identity prominence, is the identity’s “location in the self-concept structure, whether it is central or peripheral, a major or minor part of self” (Rosenberg, 1979, p. 18). The difference between identity importance and salience is that prominence places itself in an individual’s cognitive structure whereas salience’s position is in an individual’s behavioral action.
Identity importance is also hierarchical. There are several factors that influence importance, which are the individual’s imaginative view of himself or herself, how others validate the individual’s identity, and how committed the individual is to the particular identity.
Commitment here refers to the strength of connection between the self and the society, which allows the individual to enact his or her role and add meaning to his or her identity by performing certain behaviors.
Stryker and Serpe (1994) presented an example how identity importance could differ from identity salience. For example, two fathers have equally high identity importance as being a father and lower identity importance as being a researcher. However, the first father would take his child to the zoo on the weekends while the second father chose to work on his current research or study in his lab. In this case, the first father has being a parent as a salient social identity while the second father has being a researcher as a salient social identity. Here the first father has a higher commitment toward his children whereas the second father has a lower commitment. Morris (2013) suggested that while identity importance predicts identity salience, when given choices some individuals would enact their less important role identities – as seen in the example of the two fathers above.
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Social Identity and Behaviors
In line with the concept of “roles” in Identity Theory, social norms propose that when an individual strongly identifies with the reference group, he or she is more likely to adhere to the requisite norms or prototype (Terry, Hogg, and White, 1999). Terry, Hogg and White (1999) suggested that social norms could predict behavior. In addition to finding an independent effect of social identity on behavior, researchers also found an interaction effect for social identity with social norms.
The relationship between identity, group status, norms, and behaviors has resulted in several social norms marketing or campaigns (Berkowitz, 2005; Cialdini et al., 2006). New York
Times Magazine ranked social norms marketing or campaigns as one of the most significant ideas in 2001 (Frauenfelder, 2001). The idea is based on people’s tendency to behave according to what is “normal or “typical” in a social context, or as New York Times Magazine said, “the science of persuading people to go along with the crowd (Frauenfelder, 2001, p. 100).” Social norms serve as an effective tool to influence individuals’ attitudes, intentions, and behaviors.
Another example comes from the successful anti-smoking campaign, popularly known as truth™ campaign. This campaign depicts socially active adolescents demonstrating and exposing tobacco company lies (Farrelly, et al. 2002). This campaign has successfully decreased smoking behavior and increased anti-tobacco attitudes among adolescents due to its appeal to adolescents by showing the norms and typical behaviors of adolescents (Farrelly et al., 2002; Farrelly, Davis,
Haviland, Messeri & Healton, 2005). In addition, the adolescents appearing in the campaign also fit with the descriptions of a reference group among adolescents by being hip, vocal, and bold.
Using social norms approach, it can be implied that the truth™ campaign was successful because the campaign promotes refraining from smoking as the desirable behaviors among the
39 adolescents reference group, with the reference group appearing smart and edgy (Farrelly et al.,
2002). The truth™ campaign can be said to ascribe not smoking and rebelling against cigarette companies as prototypical behaviors for the cool adolescents. Health practitioners can then infer that health campaigns targeting particular social identities will see significant effects among audiences who identify with such identities, using the depictions of their reference groups.
The application of social identity theory in influencing human behaviors has gone through many developments (Garza & Herringer, 2001; Stets & Burke, 2000). Studies on the relationships between social identity, norms, and behaviors have garnered significant results within social science. Relevant theories that emerged from the effects of social identity in health persuasive messages include: (a) Sherif and Hovland’s (1961) social judgment theory, (b)
Fishbein and Ajzein (1975, 1980) theory of reasoned action, (c) Bandura’s (1986) social cognitive theory, (d) Gerbner, Gross, Morgan, and Signorielli’s (1994) cultivation theory, and (e)
Rimal and Real’s (2003) theory of normative social behavior. Each of the theories above has been prevalent when it comes to designing health persuasive messages.
Role identity and social identity in fear appeal messages and the EPPM
Considering the prevalence of role identities among individuals, when it comes to designing fear appeal messages, rather than customizing the fear variable based on the health threats, a number of fear appeals messages using identity-based threat could reach different social groups. This current study adopted both the importance and salience of identity from the identity theory perspective. When designing health messages, it is advantageous to measure and cater to the social group membership and role identities of the target audience.
For instance, using presentation of similar attitude and group appraisals technique, the fear appeal message to prevent drinking and driving targeted to those who voted for Obama can
40 be “Let’s listen to the latest message from our President, ’I do not respect those irresponsible individuals who drink and drive.’ – Barack Obama.” Obama voters are likely to have positive attitude toward Barack Obama. In the above case of reaching Obama voters, this approach of using social identity based threat might be more practical than to increase the amount of threat presented within the message because: (a) role identities are more visible than each individual’s level of sensation-seeking, (b) there is less likelihood of message ignorance due to the lack amount of threat presented, and (c) there is less likelihood of message rejection due to lack of efficacy, which was the case in the several studies involving fear-appeals messages.
Other than role identity, social identity can also fit to almost any type of health persuasive messages because every individual occupies multiple identities. An individual can be all “a woman,” “a teacher,” “a person who cheers for New Orleans Saints,” and “a person who lived in
Kentucky.” Rosenberg (1979) suggested that one’s multiplicity of selves is present in an almost infinite variety of social identities and infinite ways in which individuals can respond to themselves. Health practitioners could customize persuasive messages to fit in the individual’s social identity. For example, when persuading someone to cook healthy food, the message may focus on the individual’s social identity as a mother, whereas when persuading someone to check the reliability of information from health-related websites, the message will focus on the individual’s social identity as a teacher.
Using the above examples, the EPPM could benefit by infusing both role identity and social identity in building the fear and efficacy variables. Social identity elements in the EPPM provide an alternative to: (a) perceived severity and susceptibility of a health risk as the measure of the fear variable and (b) self and response efficacy as the measure of the efficacy variable within the EPPM framework. This alternative is necessary because messages using the principles
41 of the EPPM sometimes failed to reach certain individuals due to presenting health threats irrelevant to the individuals’ perception of threat. In addition, previous studies on persuasive messages using identity-based threat have not included identity-based efficacy, or any type of efficacy designed to respond to identity-based threat.
Identity and threat (SIT perspective)
Based on SIT, there are two types of identity threats. Those are: (a) intergroup threat and
(b) intragroup threat. Intergroup threat involves comparing an individual as part of the in-group members with out-group members. Intragroup threat involves comparing the individual with other fellow in-group members. In fear appeals messages and EPPM using identity-based threat, both fear of being associated with one’s out-group and fear of not fitting in one’s own social group can be referred to as “identity-based threat.”
Intergroup Threat
Turner (1999) discussed the importance of presenting a relevant out-group in creating intergroup threat. In previous studies, intergroup threats have been created by comparing
Canadians participants with Americans (Lalonde, 2002), men and women (White & Dahl, 2007), or undergraduate and graduate students (Berger & Rand, 2008). In those studies, the participants avoid being associated with the out-group members.
In addition to out-group members, intergroup threat can also involve dissociative groups.
Turner (1991) classified three types of social groups that serve as reference groups for individual behaviors: (a) membership groups, (b) aspirational groups, and (c) dissociative groups.
Membership groups refer to the group to which an individual voluntarily or involuntarily belongs, such as men and women or college students and high school students. Membership groups are part of an individual’s social groups. Aspirational groups refer to groups to which an individual wishes to join, such as sport players, celebrities, national heroes, or other occupations
42 that make them the in-crowd. Dissociative groups refer to groups of which an individual avoids being a member, such as “criminals,” “freaks,” “weirdos,” or other social pariahs.
Of these three groups, dissociative groups create the most threat among individuals. No individual wants to be labeled as part of his or her dissociative group. Using sports fandom as an example, a New Orleans Saints fan does not want to be identified as a fan of Atlanta Falcons (a rival team), which serves as a dissociative group.
The use of dissociative group could assist fear appeals message and EPPM in building identity threat. For example, Berger and Rand (2008) investigated how identity-based interventions work in improving the health behaviors of the individuals, which in this case is junk food consumption. They defined identity-based interventions as “associating risky behaviors with identities most individuals want to avoid signaling to others” (p. 510). After a series of pre-tests, Berger and Rand (2008) designed a persuasive message that associated online gamers, which serve as a dissociative group, with junk food consumption.
Intragroup Threat
In addition to fear of being associated with an out-group and a dissociative group, individuals do not normally wish to be marginal members of their social groups because marginal members are not well liked and trusted (Turner, 1991). Marginal members also have less influence than central members. For instance, among New Orleans Saints fans, those who do not regularly watch the game or own participate in discussions about their team, are less likely to have their opinions heard.
For individuals who affiliate strongly with their social groups, being marginalized in their own social group will evoke their fear easily. Meanwhile, for those individuals who are unattached to their social groups, the same social threat deems ineffective. For instance, Laroche
43 et al. (2001) presented male students in Canada with anti-smoking ads emphasizing the social rejection of smoking. Laroche et al. (2001) also suggested that the ad worked with Canadian students because the negative social effects of smoking are prevalent in the Canadian society. In fact, the perceived threat moderates the relationship between the level of social identity of the students/participants and the behavior intention. In another study that also used Canadian students, an intergroup threat came in the form of telling participants that they score lower on a standardized test, compared to other students in Canada. Upon knowing their lower than average grades, these participants then became motivated to increase their scores partly due to the more salient sense of nationalism (Lalonde, 2002).
For a social threat to evoke fear, the audience must perceive the threat to be personally relevant. For example, in Laroche et al.’s (2001) study, if an ad shows a smoker has trouble dating because of his or her smoking habit, then the audience should also be able to see: (a) not having a date is painful (severity) and (b) statistics show that most smokers cannot get a date
(susceptibility).
Among sports fans, Hirt, Zilman, Erickson, and Kennedy (1992) found that those who highly identified with their team often live vicariously through their team and view the team’s successes and failures as their personal successes and failures. Compared to those low in team identification, highly identified fans are more likely to attack the fans of opposing team and display favorable attitudes to those who share their love for their team (Wann & Branscombe,
1995). Hence, in responding to identity-based threat, individuals with high identification will perceive the threat to be higher than those with low identification.
SIT also explains the effects of group status and intergroup bias in individuals daily lives
(Caricati & Monacelli, 2012; Lin, Haridakis, & Hanson, 2016). Group status is how group
44 members evaluate their groups when compared to other groups, which can be positive or negative. It implies that the higher the group status the more likely that the particular member remains with his or her group. Intergroup bias is the favorable attitude toward one’s own group and unfavorable attitude toward the other groups (Tajfel & Turner, 1986). Lin et al. (2016) suggested that group status and intergroup bias influence individual’s perception of media content and whether the content is against one’s political party or not. Albeit its political context rather than health context, this finding is relevant when it comes to health promotion considering that media bias could influence how one receives health messages (Mita, Mhurchu, & Jull,
2016). In their meta-analysis, Mita et al. (2016) opined that those with hostile media bias toward social media perceived risk preventions distributed through social media to be untrustworthy and lacking in reputation and privacy. Hence, social identity has a potential in influencing the outcome of fear appeals messages.
Identity and threat (Identity Theory perspective)
Stemming from intragroup threat, identity-based threat is a relatively novel concept compared to health threat (Berger & Heath, 2007; Berger & Rand, 2008). Using the Identity
Theory, the threat should come from the possibilities that individuals failed to fulfil their ideal identity roles. This role identity threat would be at its highest efficient level when the identity is both important and salient. In the past, using identity-based threat to change individuals’ risky behaviors was limited to anti-smoking messages among adolescents or college students (Ho,
1998; Laroche et al., 2001). This leads to a challenge as to how to make social-identity based threat a universal tool for health promotion, similar to the use of physical or health consequences in the fear component of the EPPM.
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These studies suggest that health decisions and behaviors hinged on the importance and salience of identity. In those cases, social identity importance and salience moderates message viewing and behavioral intention. Identity associations are not static. In certain situations, social identity could become salient through manipulation. For instance, by labelling the steak as
“ladies cut” participants who identify as men will avoid the dish (Berger & Rand, 2008).
However, in order for the participants to modify their behaviors, they need to reach certain threshold in term of their salience of being a man as a social identity (Berger & Rand, 2008;
White & Dahl, 2006). Only by having a salient gender social identity, will the participants desire to avoid having others making undesired identity inferences about them.
Health choices constantly serve as signals of identity, social groups, and social class
(Berger & Heath, 2007; Holt, 1998; Thompson & Haytko, 1997). An example of identity-based health behaviors would be how individuals involved in detrimental health behaviors signal certain social identities to others, such as drinking beer to signal membership of masculine males, or how individuals avoid signaling unfavorable out-group membership, such as having one sexual partner to avoid any affiliation with a group of promiscuous individuals.
The identity-based EPPM proposed that there are individual differences in social identity based-fear. A person’s self-concept is comprised of a number of social identities, each varying along a continuum ranging from personal self at one end and social self at the other end (Hogg &
Abrams, 1988). In addition, Abrams and Hogg (1990) suggested that the salience of an individual’s personal and social selves vary according to the social context. A person will behave as a group member when the social self becomes salient and behave as an individual when the personal self is salient.
After building identity-based threat, the next challenge is to build self and response
46 efficacy that is compatible to the threat being presented. Similar to Witte’s (1992) EPPM, failure to build efficacy in the next stage will lead to fear control process, where the audience will deny the fact that they may become part of the dissociative groups. However, research connecting identity and efficacy are few compared with studies on the effects of identity on fear. Whereas studies involving other communication theories, such as uses and gratifications (Barker, 2009), theory of reasoned action (Linnehan et al., 2003), or elaboration likelihood model (Crano, 2000), provided empirical evidence on how social identity influences behaviors, the relationship between social identity and individuals’ perceived self and response efficacy is still largely unexplored.
Figure 2. How social threat is induced using the social identity.
Fear components: Importance and salience of I. Association with one’s dissociative identity group (Intergroup threat) A. Severity B. Susceptibility Message rejected II. Exclusion from one’s social membership OR group (Intragroup threat) Message accepted
A. Severity B. Susceptibility
Identity and efficacy
Social Cognitive Theory
One approach in linking identity and efficacy is by using social cognitive theory. Social cognitive theory suggests that individuals are active agents in shaping their surroundings and environments (Bandura, 1986, 1987). Social cognitive theory also suggests that individuals are capable in reflecting their experienced and regulating their behaviors using self-efficacy. Self- efficacy in social cognitive theory refers to individuals’ capacity in executing certain behaviors
47 to create specific outcomes. Maddux (2003) further noted that self-efficacy influences individuals’ choices of goals, attitudes toward achieving those goals, and responses toward the setbacks.
The self-efficacy in social cognitive theory and social identity share some assumptions about the individuals. Those assumptions include: (a) individuals are active agents in their behaviors, (b) the presence of others, especially those who are similar, influence individuals’ behaviors, (c) individuals develop own behaviors through observing the behaviors of others.
When it comes to Witte’s (1992) EPPM, self-efficacy refers to an individual’s ability to perform the particular behavior. An individual whose level of self-efficacy is high would feel capable to follow the recommended behaviors of the health-related message. For instance, if a health message tells a man that wearing a condom would prevent him from getting sexually transmitted disease (STD), the man’s level of self-efficacy will determine if he thinks he is able to obtain and wear condom next time he is having sex.
Meanwhile, response efficacy refers to the individual’s perception that performing the particular behavior is an effective solution toward the problem or the fear. An individual whose level of response efficacy is high would strongly believe that the recommended behaviors of the health-related message are the ultimate solutions. Using the example above, here the man’s level of response efficacy will determine if he thinks wearing condom is an effective measure to prevent getting STDs.
With regard to the social identity based-EPPM, one could build efficacious message by presenting others who are part of the in-group being able to perform the recommended behaviors. According to the EPPM, the social identity-based message should then have two functions: (a) the individual should feel that he or she is able to perform the behavior to avoid
48 being excluded from his or her social groups (social identity based-self efficacy), and (b) the individual should believe that performing the behavior would secure his or her place within his or her social group (social identity based-response efficacy).
Research on the influence of identity on self-efficacy has generated mixed results. In addition, none of those studies involved social identity based-fear. Egbert and Parrott (2001) reported that among rural women in Georgia, perceived self-efficacy in performing regular detection practices for breast and cervical cancer is positively correlated with perceived social norms. On the other hand, Busse et al. (2010) found that among male and female adolescents, the self-efficacy to initiate or to refrain from having sex does not correlate with normative pressures.
Normative pressures among adolescents correlated with intention to have sex, whereas self- efficacy correlated inversely with intention to have sex. However, there was no significant correlation between their normative pressure and their self-efficacy. Cho, So, and Lee (2009) suggested that perceived norms lead to mixed results in building self-efficacy among South
Korean smokers. Descriptive norms, or the perceived smoking behaviors of social reference groups, correlated with self-efficacy to quit smoking, whereas injunctive norms, or the perceived attitude toward smoking among social reference groups, did not predict smokers’ self-efficacy to quit smoking.
Using testimonies and exemplars in presenting efficacy elements in the EPPM
The use of exemplars offer promises in increasing individual’s level of self-efficacy.
There are three studies supporting use of exemplars and message characters in building self- efficacy. First, Hoeken and Geurts (2005) designed a fear appeal message describing the detrimental effects of excessive use of Internet. The message, which targeted Dutch college students, contained two different exemplars. In the first exemplar, a Dutch student gave a
49 testimony of not to being able to perform the recommended behaviors to limit the use of Internet and paid the consequences of dropping out the university. Meanwhile, the second exemplar featured a Dutch student who gave a testimony about how he or she successfully used the
Internet sparingly, and therefore did well socially and academically. After conducting
MANOVA test, the study’s results suggested that those who read the second exemplar had greater general self-efficacy moderated by the level of identification with the message character.
Second, Moyer-Guse, Chung, and Jain (2011) conducted a study to determine the effects of television characters on viewers’ ability to discuss taboo topics, such as sexually transmitted infections. The study used the clips from the television show Sex and the City as stimulus materials. In one of their hypotheses, Moyer-Guse et al. (2011) stated that “identification with the characters who model sexual discussion in a television narrative will be associated with greater self-efficacy” (p. 391). Some of the variables measured included: (a) self-efficacy, (b) level of identification, which included items such as “at key moments in the show, I felt I knew exactly what Miranda (the name of the character) was going through” (p. 395), (c) counterarguing, which refers to critical reception toward the information being presented in the program, and (d) behavioral intentions. The results showed a significant correlation between participants’ level of identification with the show characters and: (a) participants’ level of self- efficacy in initiating conversations regarding sexually transmitted infections (p < .05), (b) counterarguing (p < .05), and (c) behavioral intentions (p <.05) (Table 7). In their findings, not only level of identification directly correlated with self-efficacy, but identification also correlated with behavioral intention (where self-efficacy serves as a moderator in that correlation). The result of this study suggests that one of the reasons many identity-based health persuasive
50 messages did not use self-efficacy as a variable is because identification alone may affect behavioral intention, which is the ultimate goal of the message, making self-efficacy irrelevant.
Further investigation on how social identity affects response efficacy is crucial. In previous studies linking social identity and efficacy variables, the survey questions only concern individuals’ ability to perform the recommended messages, without examining individuals’ belief on how the recommended messages are effective in containing the threat (Hoeken &
Geurts, 2005; Moyer-Guse et al., 2011; Phua, 2013).
Third, Phua (2013) examined the dynamics and self-efficacy building in health-related social networking sites (SNS) designed to help individuals to quit smoking. In the study involving SNS participants, Phua (2013) found that exchanging testimonies (bridging and bonding social capital) with fellow SNS members and social identification in the SNS are related to smoking cessation self-efficacy. Some of the statements that are part of the social identification include “My attitudes and beliefs are strongly similar to other members,” whereas bridging and bonding social capital items include “There are people on the site I turn for important advice.”
The Hoeken and Geurts (2005), Moyer-Guse et al.’s (2011), and Phua (2013) studies all offered two variables that can be inserted within the fear appeals efficacy building message: (a) the presence of a character/model with whom the target audience can identify and (b) the testimony/exemplar on how the character/model was successful in modeling the recommended behaviors. Therefore, the identity-based EPPM proposes a social identity based-efficacy building message which include the two variables above. This identity-based efficacy building message may also be the answer to one of the ways messages can fail, according to EPPM, which is failure to build message efficacy.
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The social identity perspective can explain how the presence of characters and their testimonies may activate audience’s self-efficacy. These variables pair with fear appeals message and cue audience’s identity more than the fear inducing messages alone. When stories and situations cue an identity - such as a college student or a female - the cued identity brings traits that highlight the social identity (Oyserman, 2009). Being a college student may mean being sociable, whereas being a female may mean being warm. These traits create awareness in the audience as to how to make sense of the world.
This awareness concept is dependent on the particular context. For instance, being an international college instructor is likely to mean something different when teaching public speaking where “non-native speaker” identity is salient, than when teaching a class in intercultural communication, when other aspect of being an international college instructor, such as being “cultured,” is salient. This distinction could be relevant in terms of audience’s acceptance toward health messages. The salient identity could influence self-efficacy and behavioral intentions. An example would be how college students tend to consume more alcohol than the general population. However, by priming the aspect of “being attractive” among a 18-24 year old population, college students may develop the self-efficacy to avoid too much drinking in order to keep themselves healthy and not have a beer belly.
Hence, a identity-based efficacy building messages should activate aspects of the individual’s identity that trigger appropriate behavioral responses. Using results from previous studies, it can be implied that: (a) higher identification with the model/character leads to higher self-efficacy and (b) positive testimony from the model/character leads to higher self-efficacy than negative testimony.
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Figure 3. Presenting efficacy in identity-based EPPM.
High identification with the model/character, and Efficacy present exemplar/testimony of success
Insertion of a model/character providing an exemplar or giving a testimony for the audience Low identification with the Efficacy not model/character, and/or present exemplar/testimony of failure
Absence of response efficacy
The limitation of the identity-based efficacy is that it does not include response efficacy.
Witte et al. (1996) defined response efficacy as, “beliefs about the effectiveness of the recommended response in deterring the threat.” (p. 320). As previously noted, Hoeken and
Geurts (2005), Moyer–Guse et al. (2011), and Phua’s (2013) studies linking identity to efficacy did not ask how participants felt about the effectiveness of the recommendations in containing their problems. Rather, the three studies only measured how much the participants believe that they have the capacity to perform message recommendations or self-efficacy, which is the
“beliefs about one’s ability to perform the recommended response to avert the threat” (Witte et al., 1996, p. 332). Therefore, this study aims to extend previous results in the study of social identity and efficacy by including response efficacy.
Health EPPM and Identity-Based EPPM
When it comes to curbing sexual compulsive and at-risk consumption of Internet pornography, any study involving the health EPPM or the identity-based EPPM is worth pursuing. This is because: (a) to date, there has not been any fear appeal study involving sexual compulsive and at-risk pornography use, and (b) the area of pornography as a health and social
53 issue is rampant with health threat and identity-based threat that can be used in developing both health and identity-based EPPM.
Research has shown that much of the fear of consuming pornography is due to the threat of being embarrassed or shamed, which is a social threat (Garlick, 2012; Gililland, South,
Carpenter, & Hardy, 2011; Laqueur, 2003). Because of this particular reason, consumption of pornography increases when pornography shifts into the online world, where pornography users can maintain their anonymity through the Internet (Cooper, 1998; Cooper et al., 2000).
The concept of social threat itself is common among individuals with addiction (Cook,
1998; Gililland et al., 2011; Meehan et al., 1996; Potter-Effron, 2002). Two elements of social threat that are generated by a pattern of addiction are shame and guilt. One study showed a positive correlation between the tendency to feel shame and alcohol/substance abuse (Dearing,
Stuewig, & Tangney, 2005). A subsequent study that focused on compulsive sexual behaviors showed a significant positive correlation between hypersexuality, which includes item such as
“doing something sexual helps me cope with stress” (p.17), and shame (Gililland et al., 2011).
Gililland and colleagues also found significant positive correlations between the guilt induced from compulsive sexual behaviors and: (a) motivation to change and (b) proactive behavior change.
Using all of the facts in this literature review, the EPPM messages in both health and identity-based EPPM should build self-efficacy in the message audience. In the health EPPM, the fear message will emphasize the health threats relevant in consuming sexual compulsive and at-risk Internet pornography, such as depression and dissatisfaction with one’s intimate relationship, whereas the efficacy message will emphasize the available outlets to limit the sexual compulsive and at-risk use of Internet pornography.
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Figure 4. Diagram of identity-based EPPM.
Paired with high identity Message accepted Message based self-efficacy AND components: response efficacy
Fear of association High level of identity- with one’s based severity AND Paired with low identity Message dissociative group susceptibility based self and/or rejected OR Fear of rejection response efficacy
or marginalization by one’s social group Low level of identity- Efficacy built by a based severity and/or Message ignored model/character/ susceptibility fellow social identity group member(s)
Salient and relevant social identities
Previous studies on identity-based health interventions suggest that gender, age and nationality as social identities were effective in influencing individuals’ behavior (Berger &
Heath, 2007; Berger & Rand, 2008; White & Dahl, 2006; White & Dahl, 2007). Two factors were important in including social identities in identity-based health message, which are: (a) the position of the chosen social identities within the importance and salience hierarchy and (b) the relevance of the social identity within the particular health context (Berger & Heath, 2007;
Berger & Rand, 2008; White & Dahl, 2006; White & Dahl, 2007).
Different situations or intergroup contexts can make certain social identity more salient
(Abrams & Hogg, 1990). Past studies in social identity suggest that when a social identity is salient, individuals engage in group-based appraisal (Doosje et al., 1998; Iyer & Leach, 2008;
Koopens & Yzerbyt, 2012). In a research on creating salient social identity, Doosje et al. (1998) presented participants with the information on Dutch wrongdoings and colonialism in Indonesia.
The participants who were Dutch then reported salient social identity and group-based guilt.
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Salient social identity also positively correlated with food consumption behaviors. For example, in White and Dahl’s (2006) study, male participants avoided being associated with female participants and therefore, refused to eat steak labeled as “ladies’ cut.” They made this choice because gender or sex is among the most salient social identities for many people in different social situations as compared to other social identities, such as occupations or hobbies
(Garza & Herringer, 2006; White & Dahl, 2008). For men in general, the identification of being a man is usually more vital than the identification of being a civil engineer or as a coin collector
(White & Dahl, 2008). Therefore, the identification of being a woman is less desirable for men and signaling anything associated with being a woman is likely for men to avoid.
These studies above suggest that health decisions and behaviors intersect with the communication of identity. Research shows that health choices constantly serve as signals of identity, social groups, and social class (Berger & Heath, 2007; Holt, 1998; Thompson &
Haytko, 1997). An example of this would be how individuals involved in detrimental health behaviors signal certain social identities to others, such as drinking beer to signal membership of masculine males, or how individuals avoid signaling unfavorable out-group membership, such as having one sexual partner to avoid any affiliation with a promiscuous group of people.
Research Questions and Hypotheses
The first research questions examine both the tenets of EPPM and the mechanism of identity-based EPPM. There has not been any fear appeal or EPPM studies within the context of sexual compulsive and at-risk pornography use. Although EPPM states that messages must be high in both threat and efficacy to be effective in creating behavioral intention (multiplicative model), the theory opens a possibility for potential modification called the additive model (Witte
& Allen, 2000).
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The EPPM proposed that individuals assess threat and efficacy, each consisting of two components. Threat consists of perceived severity (the seriousness of the threat) and perceived susceptibility (the likelihood that the individual is prone to getting the threat). Efficacy consists of self-efficacy (the belief that the individual is able to follow the recommendations) and response efficacy (the belief that the recommendations are effective in averting the threat).
EPPM suggests an interaction between threat and efficacy will create the highest behavioral intention, also called the multiplicative or interactive model (Witte, 1992). When the threat is high but efficacy is low, individuals would engage in fear control process, which is a response that suppresses the fear by discounting the threat of the message. When the efficacy is high but the threat is low, individuals lack sufficient motivation to follow the recommendations.
Only when both fear and efficacy are high, individuals are more likely to engage in danger control process, or following the message recommendations to reduce the threat.
However, several meta-analyses and reviews on EPPM studies indicated that the data showed a different model (Mongeau, 2013; Muter et al., 2013; Roberto & Goodall, 2009; So,
2013; Witte & Allen, 2000). In fact, Mongeau (2013) found that high threat and high efficacy alone were more persuasive than when both threat and efficacy are high. Data from the above meta-analyses suggested that threat and efficacy do not interact, but rather each has positive main effects that combine additively to create danger control responses. This refers to the additive model.
Research questions 1A, 1B and 1C investigate if EPPM works as multiplicative model or additive model (in the particular issue of high consumption of pornography). Whereas most of the EPPM studies suggest a multiplicative model, an alternative explanation would be the
57 additive model, where either threat, or efficacy, or both, would correlate with behavioral intention without any effects from the interaction of threat and efficacy.
Figure 5. Diagram of Research Questions 1A, 1B, and 1C
Perceived Efficacy
Behavioral Perceived Threat Intention
RQ1A: Among individuals receiving the health EPPM message, is the effect of perceived threat on behavioral intention moderated by perceived efficacy?
RQ1B: Among individuals receiving the relationship EPPM message, is the effect of perceived threat on behavioral intention moderated by perceived efficacy?
RQ1C: Among individuals receiving the faith EPPM message, is the effect of perceived threat on behavioral intention moderated by perceived efficacy?
Identity and Threat
This study introduces the concept of the identity-based EPPM. According to SIT, social identity makes up each individual’s self-concept stemming from the individual’s membership in his or her social group with “value and emotional significance attached to that membership”
(Tajfel, 1978, p. 63). Furthermore, the theory also implies that individuals are motivated to maintain a positive value self. This includes restoring any threatened image of identity.
Based on the SIT and identity theory, there are two individual difference perspectives, which are: (a) the perspective that an individual’s identity assumes a stable self-structure, and (b) an individual’s identity is discontinuous and an individual could act either as an individual or as part of group members (Turner, 1999). By focusing on the discontinuous nature of identity, the
58 importance of one’s identity should be more predictive of one’s behaviors in a situation where social identity has been made salient compared with a situation where social identity is less salient (Turner, 1999).
When social identity is both important and salient, individuals are motivated to behave in ways that maintain a positive image of the group (Tajfel & Turner, 1987). Thus, this study aims to examine how to best customize and personalize EPPM toward individuals from particular social groups. Therefore, participants receive questionnaires measuring their social identity importance prior to viewing the EPPM message to categorize the participants into those with high importance of identity and those with low importance of identity (or those who fit into the target audience and those who do not fit into the target audience). The analyses could answer whether the individual’s social identity level or the identity-based EPPM message is the better predictor in creating behavioral intention.
In this particular study, I chose intragroup threat over intergroup threat. The reason is that it is difficult to determine accurately each individual’s out-group or dissociative group to create intergroup threat. For instance, a Christian man’s idea of an out-group can be Atheists, individuals from other religions, or individuals whose life purposes contradict Christian values.
For the next hypotheses, messages containing intragroup threat present the severity and susceptibility of not living up according to general Christian values. The fear elements for these hypotheses should make social identity as a boyfriend/husband and social identity as a Christian more salient among self-claimed Christian male partners, which then prompts the individuals to engage in behaviors that promote their social group in a positive way.
In terms of identity intragroup threat and health behaviors, Oyserman, Fryberg, and
Yoder (2007) found that White and upper class participants were likely to adopt health-
59 promoting behaviors, such as eating healthy, because ill-health behaviors were negative images to their identity. In In one study of bullying prevention among students aged 10-13, group identification interacts with social norms to result in rejecting bullying behaviors (Tarrant &
Butler, 2011). In addition, Mussweiler et al. (2000) suggested that group identification interacts with threat to one’s identity in predicting behavioral responses.
This current study uses role identity element of social identity and identity theory. Role identities are self-conceptions of an individual’s position in the social structure. These conceptions are based on enduring, normative, and reciprocal relationships with others, such as individual’s relationships with one’s romantic partner (e.g. I am a boyfriend, I am a husband) or the individual’s relationship with the higher being and people of different faiths (e. g. I am a believer, I am a Christian).
As previously mentioned, whereas the framework applies combining EPPM with both identity theory and SIT, the message designs in building threat and efficacy of the identity based-
EPPM use more elements from past studies on identity theory rather than SIT.
Figure 6. Diagram of Social Identity and Threat
Social identity importance
Perceived Threat (Severity Behavioral and Susceptibility) After Intention Identity Made Salient
Identity and Efficacy
The relationship between identity and efficacy is not as established as the relationship between identity and fear within the Communication literature. In few studies, both identity and
60 self-efficacy served as predictors of behaviors, such as how identity and self-efficacy predicted intentions to use condoms (Fekadu & Kraft, 2001) or how individuals who categorized themselves as healthy eaters have more intentions to eat more fiber and less total fat compared to those who categorized as non-healthy eaters (Kendzierski & Costello, 2004).
Previous studies suggest that presenting identity-based efficacy could be done through (a) presenting a member of one’s social group in a health message narrative (Hoeken & Geurts,
2005), (b) inserting testimonies by the characters in an entertainment TV show (Moyer-Guse et al., 2011), and (c) identification with other members in an online social support group (Phua,
2013). In this study, the presentation of a member of one’s social group, along with his testimony, is present in social identity-based messages.
Furthermore, the health EPPM and the identity-based EPPM differ in their presentation of health messages. The health EPPM message should build the individuals’ efficacy using the health message alone, whereas the identity-based EPPM features a character from the audience’s social group.
Past studies suggested that the strength of identification with the characters moderates the relationship between viewing the message and behavioral intention. The efficacy elements for the next hypotheses will make social identity as a boyfriend/husband and social identity as a
Christian more salient among self-claimed Christian male partners, which then prompts the individuals to engage in behaviors that promote their social group in a positive way.
Similar to Hypotheses 2A and 2B, a set of questionnaires measured participants’ social identity importance prior to viewing the EPPM message to categorize the participants into those with high importance of identity and those with low importance of identity. The result would then answer if the identity-based EPPM would build message acceptance or behavioral intention
61 among individuals who identify highly with their social groups. Hence, it will help health practitioners in customizing and personalizing this type of EPPM message.
Figure 7. Diagram of Social Identity and Efficacy
Social Identity Importance
Perceived Efficacy (Self Efficacy and Response Behavioral Efficacy) After Identity Made Intention Salient
Relationship role as a role identity
One social identity that is relevant in discussing the issue of sexual compulsive and at- risk consumption of online pornography is the social identity of being a marital or romantic relationship partner (Manning, 2006; White & Kimball, 2009). Manning (2006) suggested that pornography causes harm to marriages and families among Christian individuals. White and
Kimball (2009) found that compulsive Internet pornography use is problematic among Christians in romantic relationships. In their study, Christian men in romantic relationships lost sexual interest and needed to keep their pornography consumption a secret. This made the women in relationships with those men feel isolated and alone in their problems, as exposing their partner’s pornography habit risks may cause the women to have negative images in their community and their social circles.
These results aligned the negative effects of pornography on female partners in heterosexual romantic relationships suggested by Bridges et al. (2003). According to their study, women whose male partners engages in excessive pornography consumption felt betrayed by their partners. These women’s feelings lead to the deterioration of the romantic relationships. In
62 a related study, Zillman and Bryant (1998) also concluded that viewing pornography correlated with acceptance of extramarital affair.
Going back to the current study, family roles are important social identity (Kiang, Yip, &
Fuligni, 2008; Moen, Erickson, & Dempster-McClain, 2000; Stryker, 1968; Stryker & Serpe,
1994). Hence, in designing the identity-based EPPM toward Christian males in a relationship, the fear messages will emphasize relationship identity or social identity of being a boyfriend/husband. The efficacy message in the identity-based EPPM will use a husband, which corresponds to the social identity based-fear in the message. This representative serves as a model/exemplar and shares successful testimonies regarding how to curb sexual compulsive and at-risk consumption of Internet pornography use.
Hence, this study will examine both Witte’s (1992) health EPPM and the social identity based-EPPM. Unlike the health EPPM messages that feature health threats, self, and response efficacy, the presentation of a character from one’s social group dealing with the pornography issue aims to make one’s social identity more salient. As previously mentioned, several studies suggested several elements within health messages that could contribute to individuals’ increase in self-efficacy (Hoeken & Geurts, 2005; Moyer-Guse et al., 2011; Phua, 2013). Those elements include: (a) presenting a member of one’s social group in a health message narrative (Hoeken &
Geurts, 2005), (b) inserting testimonies by the characters in an entertainment TV show (Moyer-
Guse et al., 2011), and (c) identification with other members in an online social support group
(Phua, 2013). In this study, the presentation of a member of one’s social group along with his testimony will be used in social identity-based messages.
H2A: Among individuals receiving relationship-based EPPM, the effect of perceived threat on behavioral intention is moderated by relationship identity.
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H2B: Among individuals receiving relationship-based EPPM, the effect of perceived efficacy on behavioral intention is moderated by relationship identity.
Religious membership as a social and role identity
In addition to being a male romantic partner, another important social identity is the identity of being a Christian (Abell, Steenbergh, & Boivin, 2006; Balthazar et al., 2010; Earle &
Laaser, 2002). Evidence for this phenomenon is that Christian groups have long been opposing pornography within the community and the nation (Earle & Laaser, 2002). Manning (2006) suggested that the reason those religious groups fight pornography is due to the harm to marriages and families, which are two of the several foundations of a religious congregation.
Greenfield and Marks’ (2006) reported significant correlation between religion as social identity and behaviors associated with Christian religion, such as church service attendance, in a study involving 3,000 participants. In that study, participants’ religious identity significantly correlated with their behaviors than their gender or level of income.
Similar to relationship or family roles, religion is also an important role identity
(Greenfield & Marks, 2006; Kiang, Yip, & Fuligni, 2008; Stryker, 1968; Stryker & Serpe, 1994).
For the next hypotheses, the fear messages will emphasize relationship identity or social identity of being a Christian. Additional element of the fear message includes biblical verses. The efficacy message in the identity-based EPPM will use a Christian man, which corresponds to the social identity based-fear in the message. Just like the previous hypothesis, this representative serves as a model/exemplar and shares successful testimonies regarding how to curb sexual compulsive and at-risk consumption of Internet pornography use.
H3A: Among individuals receiving faith-based EPPM, the effect of perceived threat on behavioral intention is moderated by faith identity.
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H3B: Among individuals receiving faith-based EPPM, the effect of perceived efficacy on behavioral intention is moderated by faith identity.
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Chapter IIIA
Methodology (Pretest)
Purpose
I pre-tested both health and identity-based EPPM messages before administering them for the main experiment. The pre-tests included three different EPPM messages: (a) relationship status as a social identity message (b) religion as a social identity message, and (c) a health message. The purpose of the pre-test was to: (a) verify statistically that all of the three designs of
EPPM messages are legitimate and credible and (b) verify statistically that each EPPM message actually serves its purpose, which is making a particular social identity more salient.
Stimulus materials
Three different EPPM messages would induce: (a) fear, which consists of severity and susceptibility, and (b) efficacy, which consists of response efficacy and self-efficacy. Whereas health practitioners design the health EPPM message to elicit health threat and efficacy, I designed two social identity-based messages using Christianity and husband/boyfriend identity to activate participants’ level of social identity of being a Christian or a husband/boyfriend respectively.
I designed the EPPM messages by following the recommendations by Cho (2011),
Monahan (1995), and Slater (1995). Cho (2011) stated that optimal number of messages should range between two to three versions, each containing a balanced amount of severity of the threat and the audience susceptibility of the threat. Stories and visuals were used to convey the four elements of EPPM, which are severity, susceptibility, self-efficacy, and response efficacy and also to build salience in terms of being a husband/boyfriend as social identity and being a
Christian (Cho, 2011; Berger & Rand, 2008; White & Dahl, 2006). Cho (2011) and Slater (1995)
66 suggested that health practitioners and researchers should pre-test messages before delivering them to the audience (Cho, 2011; Slater, 1995). Messages should contain straightforward presentation of facts, which are the results garnered from past studies (Monahan, 1995). I created the following messages after interviewing members of target audience, which is a group of
Christian males who are currently in a romantic relationship (Slater, 1995).
Those messages were as follows:
(a) identity-based EPPM (being a husband/boyfriend as social identity)
Pornography harms your relationship. Using pornography could lead to seeking multiple sexual partners. Partners of sex addicts reported that they felt devastated, humiliated, and betrayed by their partners. When viewing pornography, men are likely to feel entertained whereas women are likely to feel disgusted. The danger of pornography: Consumption of pornography for more than an hour per week relates to dissatisfaction in intimate relationships. In fact, half of divorces are related to online pornography habit. Pornography hurts women in relationships. Women reported that they feel their boyfriends use them as “warm bodies” to achieve sexual gratification after watching pornography. Most men agree that a good boyfriend or husband should refrain from watching online pornography. “A good boyfriend would rather spend a quality time with his partner rather than watching pornography,” said one of the men being interviewed. Say no to pornography: Matt Seago, a married man, admitted that he used to spend more than 11 hours a week viewing pornography online. Now he is a changed man. “The key is to change routines and environments that lead to pornography usage,” Seago said. “Avoid high risk situations. Make a list of the positive and negative consequences of using pornography. Spend more time with your spouse, so you can quit your pornography use.”
(b) identity-based EPPM message (being a Christian as social identity)
Pornography harms your spirituality. Pornography is a concern for Christian men. People who view pornography reported a higher acceptance of extramarital affairs. Men who view pornography are less likely to attend church. The danger of pornography: The Ten Commandments say, “You shall not commit adultery” and “You shall not covet … your neighbor’s wife.” Pornography is anti-Christian. God abhors all that is immoral, sexually perverted, and lustful. Jesus even said, “anyone who looks at a woman lustfully has already committed adultery with her in his heart. If your right eye causes you to sin, gouge it out and throw it away.“ Most of the Christians agree that Christians should refrain from viewing pornography online. “We should treat our body as the way God intended it to be,” said one of them. “He wants us to live up to a higher standard’s than the world.” Say no to pornography: Matt Seago, a Christian man, admitted that the idea of consuming pornography can be tempting.“The key is to change routines and environments that lead to
67 pornography usage,“ Seago said. “Avoid high risk situations. Make a list of the positive and negative consequences of using versus not using pornography. Spend more time with other strong Christian men, so you can quit your pornography use.”
(c) health EPPM message
Pornography harms your health. One of four Internet searches is related to pornography. Every second, 28,000 people view Internet pornography. In 2006, pornography revenues in the U.S. exceeded 13 billion dollars. The danger of pornography: The American Psychiatric Association considers excessive viewing of online pornography to be a mental health disorder. Symptoms of this disorder include compulsive masturbation and fixation on an unattainable partner. Other symptoms include intense sexual fantasies and urges. Internet pornography can lead to negative effects on individuals’ sexual and mental health. Internet pornography has been shown to correlate with depression and drug abuse. Say no to pornography: The University Counseling Centre provides some suggestions for excessive viewers of pornography. “Change your routines and environments that lead to pornography usage, and avoid high risk situations,” the website states. “Make a list of the positive and negative consequences of using pornography.” “It is also important to spend less time alone, so you can quit your pornography use.”
Participants
Due to the preponderance of male viewers of pornography over female viewers, the study population consisted only of male individuals. Male pornography users outnumber female users by 85% to 15%, and the rate of pornography usage among men has quadrupled since 1980
(Cooper et al., 2004). In term of effects, the General Social Survey (GSS) suggested that pornography is more detrimental among male users than female users (GSS, 2010).
In addition, because the study aims to examine and compare the mechanism of religion and relationship-based identity in EPPM among individuals who fall under above categories, the participants were also only self-identified Christians who were in relationships.
Pre-test participants included a convenience sample of 97 Christian male college students who were in relationships enrolled in a large Midwestern university. Basic course lecturers recruited them in an introductory Communication course in exchange for research participation
68 and 47 men who were in relationships, who were also members of two church congregations in the Southwest. Two youth pastors recruited them for a chance to win five Amazon.com gift cards. There were 144 participants. Their ages ranged from 18 to 62 years-old (M = 22.94, SD =
8.76), with 77.7% participants between 18 to 24 years-old. The three most common ethnicities were Whites/Caucasians (80.5%), Blacks/African Americans (8.3%), and Hispanic/Latinos
(4.1%). The average participant had been in a relationship for almost a year (M = 11.62, SD =
75.12).
Procedure
I randomly divided the participants into four groups using Qualtrics: (a) a control group, which did not receive any message, (b) a group receiving health EPPM mentioning the negative effects of pornography on one’s health, (c) a group receiving faith identity-based EPPM focusing on the negative effects of pornography on one’s spirituality, and (d) a group receiving relationship identity-based EPPM focusing on the negative effects of pornography on one’s romantic relationship/marriage. I first presented the participants with one of the three EPPM messages before filing out the survey questions which measured the credibility of the scale and their salience of social identity, whereas the participants who were in the control group simply filled out the identity-related scales that are presented to the other three groups.
Measurements
All groups received modified Sellers et al. (1998) Multidimensional Inventory for Black
Identity (MIBI) to measure the effects of the message to their social identity salience. Next, all groups receiving the three different types of EPPM messages (groups “b”, “c”, and “d”) received
Meyer (1998) and West’s (1994) Channel Credibility Index to assess the perceived legitimacy of the message. Those scales are as follows:
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Adjusted Sellers et al. (1998) Multidimensional Inventory for Black Identity (MIBI). This is an 8- items self-report questionnaire using 7-point Likert scale. This scale stems from the centrality scale of Sellers et al. (1998) Multidimensional Inventory for Black Identity (MIBI). The centrality scale of identity was chosen because: (a) it is the most stable element of identity, meaning that the scale measures part of individuals’ identity that emerges among their multiple identities regardless of the different situations (Sellers et al., 1998) and (b) the similarities of the scale with other scales measuring social identity, such as Cameron’s (2001) Three-Factor Model of Identity and Nario-Redmond et al.’s (2001) Social and Personal Identity Scale.
I adjusted the scale and then used it to measure the salience of participants’ social identity by: (a) comparing participants (who are Christian males in a relationship) scores across their social identities of being a Christian, a husband/boyfriend, and a health-oriented person after viewing the message and (b) adding the words “this message makes me … “ prior to the statements measuring participants’ social identity (eg. This message is effective in strengthening my identity as a Christian).
The centrality scale itself refers to “the extent to which an individual normatively emphasizes group membership as part of their overall self-concept” (Scottham et al., 2008, p. 2).
Scholars have previously used this dimension of the scale in measuring different roles as a social identity, such as religion (Kiang et al., 2005) or parental identity (Simon, 1992). I adjusted the particular dimension of the scale to measure degree of faith and relationship identities. This is an
8-item self-report questionnaire using a 7-point Likert-type scale.
Because there were two types of identity-based EPPM messages presented, the groups exposed to identity-based EPPM messages received two different measures of social identity pertaining to their feelings after viewing the identity-based EPPM messages. For the practicality
70 purpose, these measures were named Message Identity Scale for Religion and Message Identity
Scale for Relationship. There are two types of questions, which are: (a) questions that measure one’s identity as a Christian (e.g. “This message is significant to my role as a Christian”), and (b) questions that measure one’s identity as a boyfriend/husband (e.g. “This message makes me think about my responsibility as a husband/boyfriend”).
Meanwhile, the control group received the adjusted MIBI Scales. This version asks the participants’ stance on the salience of both their Christian identity and being a husband/boyfriend as social identity (e.g. “My role as a Christian is significant”, “I have a strong sense of belonging to a group of husbands/boyfriends”, “I strongly relate to other Christians”, “Being a husband/boyfriend is an important reflection of who I am.”).
In order for the religion-based and relationship-based messages to be eligible in creating identity salience, the scores on Message Identity Scale that corresponded with the messages participants received should be significantly higher than the scores for the other two adjusted
MIBI Scales. Total there are three MIBI Scales, which measured each participant’s: (a) identity as a health-oriented individual, (b) identity as a Christian, and (c) identity as a husband/boyfriend.
Meyer (1998) and West’s (1994) Channel Credibility Index. This is a 5-item self-report questionnaire using 7-point semantic differential scale and consist of: “The scenario is realistic –
The scenario is unrealistic,” “The message is believable – The message is unbelievable,” “Matt
Seago’s statements are well founded – Matt Seago’s statement is not well founded,” “The information given would be verifiable if examined – The information given would not be verifiable if examined,” “Statements are usually true/correct – Statements are usually not true/correct.”
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In order for the three messages to be deemed credible, each item in the scale should score above 5 in 7-point semantic differential scale. Otherwise, the messages would be refined and reworded.
I compared the two groups receiving faith and relationship identity-based EPPM messages with the control group, which did not receive any message in term of their social identity salience. The salience of participants’ social identities were measured using adjusted
Sellers et al. (1998) Multidimensional Inventory for Black Identity (MIBI), which was renamed as Message Identity Scale for Religion and Message Identity Scale for Relationship.
Results
In terms of reliability, I tested the four scales. The first two were MIBI scale for relationship and faith identity, which I administered among the participants in the control group.
The next two were the Message Identity Scale for Relationship and Message Identity Scale for
Religion, which I presented toward participants receiving relationship identity-based EPPM and participants receiving religion identity-based EPPM respectively. MIBI scale for relationship identity had a good Cronbach Alpha (α = .89). As for the adjusted MIBI scale for religion identity, the Cronbach’s Alpha was also good with α = .93. Next, for the Message Identity Scale in the relationship version, the Cronbach’s Alpha stood at α = .82. The Message Identity Scale in the religion version was slightly higher at α = .89. Finally, I presented all of the participants with the Channel Credibility Index for the three different EPPM messages: (a) relationship, (b) religion, and (c) health. The reliability for each was α = .86, α = .85, and α = .84, respectively.
The next pre-test concern was the social identity effects of each message. To verify that the messages could make relationship identity more salient, I conducted two independent sample t-tests conducted. The first independent sample t-test compared the control group (n = 37) and
72 the group who received relationship identity-based EPPM message (n = 36). The result suggested that there was a significant difference in term of individuals’ relationship identity salience between the control group (M = 37.54, SD = 8.91) and those who received relationship identity- based EPPM message (M = 46.22, SD = 5.18) with t(58.15) = -5.1 at p < .001. The result suggested that who saw the message had more salient relationship identity compared to those who did not see the message.
The second independent sample t-test compared the control group (n = 37) and the group who received faith identity-based EPPM message (n = 35). The result suggested that there was a significant difference in terms of individuals’ faith identity salience between the control group
(M = 34.59, SD = 10.51) and those who received faith identity-based EPPM message (M = 45.8,
SD = 6.78) with t(70) = -5.33 at p < .001. The result supported the assumption that those who saw the message had more salient faith identity as compared to those who did not see the message.
With regard to the believability of the three messages, I tested each message with different groups of participants. First, 36 participants were assigned to the group receiving health
EPPM message. The participants took Channel Credibility Index to measure the perceived credibility of the message. The items were high in terms of perceived credibility (M = 30.42, SD
= 4.21) using 5-items 7-point semantic differential scale (where 1 is the least credible and 7 is the most credible).
Second, I administered the relationship identity-based EPPM message and the Meyer and West Chanel Credibility Index to 36 participants. The items were moderately high in term of the perceived credibility (M = 28.86, SD = 4.09) using 5-items 7-point semantic differential scale
(where 1 is the least credible and 7 is the most credible).
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Last, in response to the faith identity-based EPPM message, 35 participants took Channel
Credibility Index. The items were moderately high in term of the perceived credibility (M =
29.57, SD = 4.37) using 5-items 7-point semantic differential scale (where 1 is the least credible and 7 is the most credible).
These results suggested that all of the three different versions of EPPM messages functioned as designed and therefore were usable for the hypotheses testing in the main experiment.
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Chapter IIIB
Methodology (Main Experiment)
Research Design
The purpose of this study was to test the health EPPM and the identity-based EPPM in the development of persuasive messages targeting sexual compulsive and at-risk pornography use. The study randomly assigned participants to one of the three conditions: (a) those who received health EPPM message, (b) those who received faith EPPM message, and (c) those who received relationship EPPM message.
In the current study, the independent variables were: (a) level of relationship as social identity, (b) level of faith as social identity, (c) perceived severity, (d) perceived susceptibility,
(e) perceived self-efficacy, and (f) perceived response efficacy. The dependent variable was behavioral intention.
Participants
Similar to the pre-test, the participants were Christian males who were in romantic relationship. The participants consisted of 234 students enrolled in an introductory course in
Communication Studies. Basic course instructors recruited the participants in exchange for the required research credit. Those who chose not to take part in the study could opt for alternative assignments.
Procedure
After agreeing to participate, participants received an e-mail containing a link to a
Qualtrics online survey and proceeded to fill out scales, view one of the three EPPM messages, and respond to the rest of the questionnaires online. Using Qualtrics online survey, the software randomly divided the participants into these three conditions. Each condition required
75 participants to fill out the corresponding scales and view the corresponding health messages in the following sequences:
(a) Health EPPM Condition: (EPPM) – Fear – Efficacy – Health Behavioral Intention (HBI)
(b) Relationship EPPM Condition: Relationship Identity – (Relationship EPPM) – Fear –
Efficacy – Health Behavioral Intention (HBI)
(c) Faith EPPM Condition: Faith Identity – (Religion EPPM) – Fear – Efficacy – Health
Behavioral Intention (HBI)
Demographics. Several items recorded participants’ demographic information, including age, race/ethnicity, level of income, level of education, occupation, relationship/marital status and the length of relationship/marital status (see Appendix G).
Pornography Use. Three items measured pornography use, including: “How many hours per week do you spend looking at pornographic material?” “How many hours in the past week did you spend looking at pornographic material?” and ”How many times did you look at pornographic material in the past year?” These questions are taken from Carroll et al. (2008), which is the most cited study on the negative effects of sexual compulsive and at-risk pornography consumption from 2008 until 2014 (see Appendix H).
Messages. Messages consisted of three different types of EPPM health message (see
Appendix A, B, and C). The messages varied according to the type of the stimulus presented that would make participants’ social identity more salient. For instance, the health EPPM message includes harmful effects on one’s body, whereas the relationship-based EPPM message includes the negative effects on one’s partner.
Perceived Threat. This scale is used in RQ1A, RQ1B, RQ1C, H2A, H2B, H3A, and
H3B. Threat was used to assess all of the hypotheses in this study. Threat is a second-order
76 unidimensional construct composed of severity (SEV) and susceptibility (SUS) (see Appendix I).
SEV and SUS were each measured with a 3-item self-report questionnaire using 7-point Likert scale, which is part of the Witte et al. (1996) Risk Behavior Diagnosis scale.
Because this study of EPPM concerns pornography, social threat and efficacy, an area that has not been tested using Risk Behavior Diagnosis scale, an exploratory factor analysis
(EFA) was conducted for the scale across the three different conditions to statistically verify that the scale is loaded in one factor for SEV and SUS (Henson & Roberts, 2006). All of the items loaded in one factor with: (a) .88 for SEV and .75 for SUS in the health EPPM condition, (b) .93 for SEV and .73 for SUS in the relationship EPPM condition, and (c) .93 in SEV and .77 for
SUS in the faith EPPM condition. The alpha coefficients stood at: (a) .92 for SEV and .84 for
SUS in the health EPPM condition, (b) .93 for SEV and .85 for SUS in the relationship EPPM condition, and (c) .94 for SEV and .83 for SUS in the faith EPPM condition.
Perceived Efficacy. I used this scale for RQ1A, RQ1B, RQ1C, H2A, H2B, H3A, and
H3B. Efficacy was assessed in all of the hypotheses in this study. Efficacy is a second-order unidimensional construct composed of self-efficacy (SE) and response efficacy (RE) (see
Appendix I). SE and RE were each measured with a 3-item self-report scale using 7-point Likert scale, which is part of the Witte et al. (1995) RBD scale.
Because this study of EPPM concerns pornography, social threat and efficacy, an area that has not been tested using Risk Behavior Diagnosis scale, an EFA was conducted for the scale across the three different conditions to statistically verify that the items in the scale loaded in one factor for SE and RE (Henson & Roberts, 2006). All of the items loaded in one factor with
(a) .87 for SE and .81 for RE in the health EPPM condition, (b) .89 for SE and .89 for RE in the relationship EPPM condition, and (c) .85 for SE and .90 for RE in the faith EPPM condition. The
77 alpha coefficients stood at: (a) .88 for SE and .78 for RE in health EPPM condition, (b) .89 for
SE and .88 for RE in the relationship EPPM, and (c) .86 for SE and .90 for RE in the faith
EPPM.
Importance of Being a Boyfriend/Husband as a Social Identity. I used this scale for
RQ1B, H2A, and H3A. The degree of importance of being a boyfriend/husband as a social identity was used to assess the importance of the social identity of being a boyfriend/husband among participants receiving relationship-based EPPM (individuals’ level of social identity is positively correlated to individuals’ level of perceived SEV and perceived SUS in the identity- based EPPM) for those who received the boyfriend/husband as social identity in identity-based
EPPM. This variable was measured using the adapted centrality scale of Sellers et al. (1998)
Multidimensional Inventory for Black Identity (MIBI) for relationship and faith identity (see
Appendix J).
I chose the centrality scale of identity because it is the most stable element of identity, meaning that the scale measures part of individuals’ identity that emerges among their multiple identities regardless of the different situations (Sellers et al., 1998). In this case, the individuals’ activated social identity is vital in determining their reception toward the social identity-based message at any given time. The statements from the scale seem to fit with the definition of identity importance, and those statements aptly measure the hierarchical position of an individual’s identity within his or her cognitive self.
Rosenberg (1979) regarded identity importance - or prominence as he called it - as psychological centrality, and he also explained the term as the components of self that are important to the individual. The centrality scale itself refers to “the extent to which an individual normatively emphasizes group membership as part of their overall self-concept” (Scottham et al.,
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2008, p. 2). Scholars have previously used this dimension of the scale in measuring different roles as a social identity, such as religion (Kiang et al., 2005) or parental identity (Simon, 1992).
I adjusted this dimension to measure the boyfriend/husband identity and became an 8-item self- report questionnaire using a 7-point Likert-type scale. Some of the items include: “I have a strong sense of belonging to a group of husbands/boyfriends,” “I strongly relate to other husbands/boyfriends,” and “Being a husband/boyfriend is an important reflection of who I am.”
In the present study, the alpha coefficient stood at .797.
Importance of Being a Christian as a Social Identity. This scale is used in RQ1C, H2B and H3B. The degree of importance of being a Christian as a social identity was used to assess the importance of the social identity of being a Christian among participants who received faith- based EPPM message (individuals’ level of social identity is positively correlated to individuals’ level of perceived SEV and perceived SUS in the identity-based EPPM) for those who received the Christianity as social identity in identity-based EPPM.
Again, this variable was measured using adjusted centrality scale of Sellers et al. (1998)
MIBI. I adjusted the particular dimension to measure degree of faith identity. This is an 8-item self-report questionnaire using a 7-point Likert-type scale. Some of the items included: “I have a strong sense of belonging to a group of Christians,” “I have a strong attachment to other
Christians,” and “Being a Christian is an important reflection of who I am.” In the present study, the alpha coefficient stood at .906.
Behavioral Intention. I used this scale in RQ1A, RQ1B, RQ1C, H2A, H2B, H3A, and
H3B. Behavioral intention is the dependent variable in all of the research questions and hypotheses. I measured this variable using Rise, Kovac, Kraft, and Moan’s (2008) Behavioral
Intention Scale.
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Because this study of EPPM concerns pornography, social threat and efficacy, an area that has not been tested using Behavioral Intention Scale, an EFA was conducted for the scale across the three different conditions to statistically verify that the scale is loaded in one factor
(Henson & Roberts, 2006). All of the items loaded in one factor with .92 in the health EPPM condition, .91 in the relationship EPPM condition, and .98 in the faith EPPM condition. The alpha coefficients stood at: (a) .92 in the health EPPM condition, (b) .93 in the relationship
EPPM condition, and (c) .98 in the faith EPPM condition.
Table 1. Descriptive Statistics and Reliabilies for All Scales
Conditions Scales M SD α
Health Severity of RBD Scale 9.98 4.67 .92
(n = 67) Susceptibility of RBD Scale 10.74 5.4 .84
Self-Efficacy of RBD Scale 14.82 4.96 .88
Response Efficacy of RBD Scale 15.32 4.03 .78
Behavioral Intention Scale 12.11 5.88 .92
Relationship Husband/Boyfriend as Social Identity Scale 20.07 5.31 .79
(n = 70) Severity of RBD Scale 10.17 5.03 .93
Susceptibility of RBD Scale 10.97 5.3 .73
Self-Efficacy of RBD Scale 15.1 4.75 .89
Response Efficacy of RBD Scale 15.61 4.51 .88
Behavioral Intention Scale 11.71 5.98 .93
Faith Being a Christian as Social Identity Scale 20.88 5.9 .90
(n = 72) Severity of RBD Scale 10.59 4.97 .94
Susceptibility of RBD Scale 10.19 4.94 .83
Self-Efficacy of RBD Scale 14.5 4.52 .86
Response Efficacy of RBD Scale 14.51 4.58 .90
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Behavioral Intention Scale 11.41 6.02 .98
Statistical Analysis
Hierarchical multiple regression is appropriate for use in studies based on existing theoretical frameworks, such as this current study. This method is one of three main variants of the basic multiple regression procedure, together with standard multiple regression and stepwise regression. The difference between hierarchical multiple regression and standard multiple regression, or stepwise regression, is that it enables the researcher to insert independent variables cumulatively based on the theoretical framework and the logic of the research.
For all research questions and hypotheses, ordinary least squares (OLS) hierarchical regression analysis is used to investigate if a set of independent variables consisting of interval and ratio variables influence the dependent variable, and if the covariates are significant in affecting the dependent variable. This technique estimates Y value (Y’) = (Y-intercept) + slope
(given value of X). In all of the hypotheses, Y refers to the behavioral intention. The model for this hypothesis is then given as: Y = β0 + β1X1 + β2X2 + … + βkXk, where β values serve as the regression coefficient for each independent variable. The least-squares principle includes minimizing the sum of the squared vertical difference between the actual Y values (Y) and the predicted Y values (Y’) and thus, minimizes the distances between the best-fit line (Y’) and the actual values of Y (Grimm & Yarnold, 1995).
Prior to using OLS hierarchical regression analysis, I created z-scores from the perceived threat, perceived efficacy, relationship identity, and faith identity data sets. Z-scores measure the distance of a data point from the mean in terms of the standard deviation. I used the SPSS in creating z-scores. The process normally involves subtracting the mean of all data points from each individual data, and dividing the points by the standard deviation of all points.
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Using OLS hierarchical regression analysis, a set of independent variables are entered in the specified order to determine how much additional variance after each additions. This model is generated with every subsequent model displaying more independent variables than the previous one (Grimm & Yarnold, 1995).
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Chapter IV
Results
Sample
Participants’ ages ranged from 18 to 75 years old, with 18 year-olds making up 34% of the sample, followed by 19 year-olds at 33% and 20 year-olds at 16%. Their ethnicities were
82.3% White, 4.3% Black, 1.9% Hispanic, 8.1% Asian or Pacific Islanders, and 3.3% classified themselves as Other. Their incomes were mostly below $20,000 (87.6%), followed by income ranging from $20,000 to $40,000 (3.8%). As for the relationship status, 89.5% were dating, 2.9% were married, while engaged, separated, and divorced were 1.9% each. In terms of their length of relationship, most of them had been in their current relationship for 3 months (16%), followed by
2 months; 4 months; and 2 years and 2 months; each came second at 14%. When it comes to their consumption of pornographic material, the majority (30%) viewed pornography for 1 hour per week, 20.5% did not watch pornography at all, 9.5% watched porn for 30 minutes per week, and 6% or 12 individuals did not report their pornography viewing habit. The rest of them (34%) gave a variety of results ranging from 5 minutes to 40 hours per week. Nine individuals (4.5%) fall under at-risk pornography consumers, whereas 50 individuals (25%) were sexual compulsive pornography consumers.
Data cleaning
I performed data cleaning to: (a) find errors during data entry and eliminate them, (b) examine missing data and statistically account for it, and (c) prepare the data for the analysis.
First, I performed descriptive analyses to measure: (a) time spent completing the survey and (b) age. Qualtrics estimated15 to 20 minutes to complete the survey, and the time spent completing the survey reflects the estimation (M = 16.29, SD = 5.12). I deleted participants who spent less
83 than five minutes or more than half an hour (beyond two standard deviations from the average of
16.29 minutes). Next, I also eliminated individuals who were below the age of 18 from the sample pool for ethical purpose.
After that, I examined the data to fix variables and value labels, such as correcting the typos (one year instead of 1 when filling out the relationship length in year) for those who filled out the demographic variables and making sure that the variables are of the appropriate type
(changing variables into numeric scores for future computation). I took a conservative approach by eliminating participants’ entries that had missing data. The whole data cleaning process narrowed down 234 participants into 209 participants. These participants occupied three different conditions: (a) health, (b) relationship, and (c) faith. Each condition has 67, 70, and 72 samples, respectively. Due to the small sample size for each condition, the level of significance is set at p
< .10 (Kim, 2015).
Table 2. Description of Key Analytic Variables across Three Groups
Construct Variables Description Mean (Standard Deviation)
Age 18-75 20.77 (6.82) n = 209
Ethnicity White = 1, Black = 2, Hispanic = 3, Asian/ 1=172 (82.2%), 2=9 (4.3%) Pacific Islanders = 4, Other = 5 3=4 (1.9%), 4=17 (8.1%) 5=7 (3.3%)
Education Middle School = 1, High School = 2, Some 1=1 (.4%), 2=20 (9.5%), College = 3, Bachelor = 4, Master = 5, 3=156 (74.6%), 4=30 Doctorate = 6 (14.3%), 5=1 (.4%), 6=1 (.4%)
Status Married = 1, Engaged = 2, Dating = 3, 1=6 (2.8%), 2=4 (1.9%) Separated = 4, Divorced = 5, Other = 6 3=187 (89.4%), 4=4 (1.9%) 5=4 (1.9%), 6=3 (1.4%)
Relationship The number of months the person has been in 15.78 (19.34) Length the current romantic relationship.
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Pornography The number of minutes the person spends on 93.21 (179.37) Use pornographic material in a week.
Table 3. Description of Key Analytic Variables in Health EPPM Group
Construct Variables Description Mean (Standard Deviation)
Age 18-75 20.43 (7.27) n = 67
Ethnicity White = 1, Black = 2, Hispanic = 3, Asian/ 1=53 (79.1%), 2=2 (3%), Pacific Islanders = 4, Other = 5 3=2 (3%), 4=5 (7.5%), 5=5 (7.5%)
Education High School = 2, Some College = 3, 2=7 (10.4%), 3=50 (74.6%), Bachelor = 4 4=10 (14.9%)
Status Married = 2, Dating = 3, Separated = 4, 2=2 (3%), 3=62 (92.5%), Divorced = 5, Other = 6 4=1 (1.5%), 5=1 (1.5%), 6=1 (1.5%)
Relationship The number of months the person has been in 11.7 (11.89) Length the current romantic relationship.
Pornography The number of minutes the person spends on 59.24 (52.15) Use pornographic material in a week.
Severity 3-item scale. 7-point Likert scale, summed. 9.98 (4.67) 1. Consuming pornography for more than one hour per week is serious threat 2. Consuming pornography for more than one hour per week is harmful 3. Consuming pornography for more than one hour per week is severe threat (7 = Strongly Agree, 1 = Strongly Disagree)
Susceptibility 3-item scale. 7-point Likert scale, summed. 10.74 (5.4) 1. I am at risk for using pornography for more than one hour per week 2. It is possible that I will use pornography for more than one hour per week 3. I am susceptible to using pornography for more than one hour per week. (7 = Strongly Agree, 1 = Strongly Disagree)
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Self-Efficacy 3-item scale. 7-point Likert scale, summed. 14.82 (4.96) 1. I am able to quit/limit pornography use to prevent more than one hour per week use of pornography 2. It is easy to quit/limit pornography use to prevent more than an hour per week use of pornography 3. I can quit/limit pornography use to prevent more than an hour per week use of pornography (7 = Strongly Agree, 1 = Strongly Disagree)
Response 3-item scale. 7-point Likert scale, summed. 15.32 (4.03) Efficacy 1. Quitting/limiting pornography use prevents more than an hour per week use of pornography. 2. I can quit/limit pornography use to prevent more than an hour per week use of pornography. 3. Quitting/limiting pornography use is effective in getting rid of more than an hour per week use of pornography. (7 = Strongly Agree, 1 = Strongly Disagree)
Behavioral 3-item scale. 7-point Likert scale, summed. 12.11 (5.88) Intention 1. During the next 3 months, I plan to quit/limit pornography use. 2. During the next 3 months, I plan to quit/limit pornography use. 3. During the next 3 months, I expect to quit/limit pornography use. (7 = Strongly Agree, 1 = Strongly Disagree)
Table 4. Description of Key Analytic Variables in Relationship EPPM Group
Construct Variables Description Mean (Standard Deviation)
Age 18-75 21.14 (7.13) n = 70
Ethnicity White = 1, Black = 2, Hispanic = 3, Asian/ 1=54 (77.1%), 2=4 (5.7%), Pacific Islanders = 4, Other = 5 3=1 (1.4%), 4=9 (12.9%), 5=2 (2.9%)
Education High School = 2, Some College = 3, 2=3 (4.3%), 3=54 (77.1%)
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Bachelor = 4, Doctorate = 6 4=12 (17.1%), 6=1 (1.4%)
Status Married = 1, Engaged = 2, Dating = 3, 1=1 (1.4%), 2=1 (1.4%). Separated = 4, Divorced = 5 3=64 (91.4%), 4=1 (1.4%), 5=2 (2.9%)
Relationship The number of months the person has been in 16.42 (19.3) Length the current romantic relationship.
Pornography The number of minutes the person spends on 115.93 (206.81) Use pornographic material in a week.
Relationship 5-item scale, 7-point Likert scale, summed. 20.07 (5.31) Identity e.g. I strongly relate to other boyfriends/husbands. (7 = Strongly Agree, 1 = Strongly Disagree)
Severity 3-item scale. 7-point Likert scale, summed. 10.17 (5.03) 1. Consuming pornography for more than one hour per week is serious threat 2. Consuming pornography for more than one hour per week is harmful 3. Consuming pornography for more than one hour per week is severe threat (7 = Strongly Agree, 1 = Strongly Disagree)
Susceptibility 3-item scale. 7-point Likert scale, summed. 10.97 (5.3) 1. I am at risk for using pornography for more than one hour per week 2. It is possible that I will use pornography for more than one hour per week 3. I am susceptible to using pornography for more than one hour per week. (7 = Strongly Agree, 1 = Strongly Disagree)
Self-Efficacy 3-item scale. 7-point Likert scale, summed. 15.1 (4.75) 1. I am able to quit/limit pornography use to prevent more than one hour per week use of pornography 2. It is easy to quit/limit pornography use to prevent more than an hour per week use of pornography 3. I can quit/limit pornography use to prevent more than an hour per week use of pornography (7 = Strongly Agree, 1 = Strongly Disagree)
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Response 3-item scale. 7-point Likert scale, summed. 15.61 (4.51) Efficacy 1. Quitting/limiting pornography use prevents more than an hour per week use of pornography. 2. I can quit/limit pornography use to prevent more than an hour per week use of pornography. 3. Quitting/limiting pornography use is effective in getting rid of more than an hour per week use of pornography. (7 = Strongly Agree, 1 = Strongly Disagree)
Behavioral 3-item scale. 7-point Likert scale, summed. 11.71 (5.98) Intention 1. During the next 3 months, I plan to quit/limit pornography use. 2. During the next 3 months, I plan to quit/limit pornography use. 3. During the next 3 months, I expect to quit/limit pornography use. (7 = Strongly Agree, 1 = Strongly Disagree)
Table 5. Description of Key Analytic Variables in Faith EPPM Group
Construct Variables Description Mean (Standard Deviation)
Age 18-75 20.71 (6.13) n=72
Ethnicity White = 1, Black = 2, Hispanic = 3, Asian/ 1=65 (90.3%), 2=3 (4.2%), Pacific Islanders = 4 3=1 (1.4%), 4=3 (4.2%)
Education Middle School = 1, High School = 2, Some 1=1 (1.4%), 2=10 (13.9%), College = 3, Bachelor = 4, Master = 5 3=52 (72.2%), 4=8 (11.1%), 5=1 (1.4%)
Status Married = 1, Engaged = 2, Dating = 3, 1=3 (4.2%), 2=3 (4.2%), Separated = 4, Divorced = 5 3=61 (84.7%), 4=2 (2.8%), 5=1 (1.4%)
Relationship The number of months the person has been in 18.95 (24) Length the current romantic relationship.
Pornography The number of minutes the person spends on 102.74 (220.16) Use pornographic material in a week.
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Faith 5-item scale, 7-point Likert scale, summed. 20.88 (5.9) Identity e.g. I strongly relate to other Christians. (7 = Strongly Agree, 1 = Strongly Disagree)
Severity 3-item scale. 7-point Likert scale, summed. 10.59 (4.97) 1. Consuming pornography for more than one hour per week is serious threat 2. Consuming pornography for more than one hour per week is harmful 3. Consuming pornography for more than one hour per week is severe threat (7 = Strongly Agree, 1 = Strongly Disagree)
Susceptibility 3-item scale. 7-point Likert scale, summed. 10.19 (4.94) 1. I am at risk for using pornography for more than one hour per week 2. It is possible that I will use pornography for more than one hour per week 3. I am susceptible to using pornography for more than one hour per week. (7 = Strongly Agree, 1 = Strongly Disagree)
Self-Efficacy 3-item scale. 7-point Likert scale, summed. 14.5 (4.52) 1. I am able to quit/limit pornography use to prevent more than one hour per week use of pornography 2. It is easy to quit/limit pornography use to prevent more than an hour per week use of pornography 3. I can quit/limit pornography use to prevent more than an hour per week use of pornography (7 = Strongly Agree, 1 = Strongly Disagree)
Response 3-item scale. 7-point Likert scale, summed. 14.51 (4.58) Efficacy 1. Quitting/limiting pornography use prevents more than an hour per week use of pornography. 2. I can quit/limit pornography use to prevent more than an hour per week use of pornography. 3. Quitting/limiting pornography use is effective in getting rid of more than an hour per week use of pornography. (7 = Strongly Agree, 1 = Strongly Disagree)
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Behavioral 3-item scale. 7-point Likert scale, summed. 11.41 (6.02) Intention 1. During the next 3 months, I plan to quit/limit pornography use. 2. During the next 3 months, I plan to quit/limit pornography use. 3. During the next 3 months, I expect to quit/limit pornography use. (7 = Strongly Agree, 1 = Strongly Disagree)
Factor analyses
I conducted factor analysis to measure the structure of two scales: (a) faith identity scale, and (b) relationship identity scale to measure how well each item within those three scales aligned with the constructs being tested. This process is especially important for the faith and relationship identity scales, as I used the two scales for the first time after adjusting the items from MIBI scale.
First, I conducted principle component analysis (PCA) for Lennox and Wolf’s (1984) self-monitoring measure using SPSS. Brown (2006) suggested that in the EFA model items should have no a priory restrictions. The purpose of EFA is to verify the dimensionality of items from the questionnaire (Brown, 2006).
I applied goodness-of-fit statistics test to determine the number of items to retain. The basis of the test is as follows: (a) size of the factor loadings (items that loaded at least 0.5 were retained), (b) at least two items present in each factor, (c) the eigenvalue is set at greater than 1
(the eigenvalue rule [Kaiser, 1960]), and (d) the absence of cross-loading of items onto multiple factors. Eigenvalues indicate the amount of variance explained by each factor or dimension.
Relationship identity scale
I conducted an exploratory factor analyses (EFA) for adapted Sellers et al. (1998)
Multidimensional Inventory for Black Identity (MIBI) for relationship identity using SPSS
90 version 24 (Table 5). Although the scale is supposed to have only one dimension, EFA was still performed to verify the number of dimensions (Henson & Roberts, 2006).
The results revealed that two factors initially emerged from the EFA, which were the significance of the individual’s relationship in the society and the negatively-worded individual’s relationship importance to himself. Three items were problematic, falling under the second factor with loadings above .50 (Overall, being a boyfriend/husband has very little to do with how I feel about myself) at .718 and (Being a boyfriend/husband is unimportant to my sense of what kind a person I am at .512), with the third item (Being a boyfriend/husband is not a major factor in my social relationships) cross-loading (the first factor as .639 and the second factor as .497) (Table
5). All of these items are also items that require reverse coding. The extraction sums of squared loadings presented that the first factor explained 41.61% of the variance and the second factor explained 22.37% of the variance.
Table 6. Factor Analysis for Relationship identity Scale
Item Factor 1 Factor 2
Overall, being a boyfriend/husband has very little to do with how I feel about myself* .147 .718
In general, being a boyfriend/husband is an important part of my self-image .507 - .592
My destiny is tied to the destiny of other boyfriends/husbands .649 .340
Being a boyfriend/husband is unimportant to my sense of what kind of person I am* .650 .512
I have a strong sense of belonging to a group of boyfriends/husbands. .830 -.213
I strongly relate to other boyfriends/husbands .780 -.229
Being a boyfriend/husband is an important reflection of who I am .711 -.450
Being a boyfriend/husband is not a major factor in my social relationships* .639 .497
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* denotes reverse coding
Three items above (Overall, being a boyfriend/husband has very little to do with how I feel about myself, Being a boyfriend/husband is unimportant to my sense of what kind a person I am, and Being a boyfriend/husband is not a major factor in my social relationships) were then omitted from the scale because they cross loaded into both factors, leaving the first item the lone item in the second factor, which was then omitted. An EFA analysis was run for the second time with eigenvalues set greater than 1. One factor then emerged. This factor explained 56.24% of the variance.
Table 7. Final Exploratory Factor Analysis Factor Solution for Relationship identity Scale
Item Factor 1
My destiny is tied to the destiny of other boyfriends/husbands .691
Being a boyfriend/husband is an important part of my self-image .529
I have a strong sense of belonging to a group of boyfriends/husbands .849
I strongly relate to other boyfriends/husbands .809
Being a boyfriend/husband is an important reflection of who I am .825
Looking at the face validity of the items in the sole factor, the factor seemed to represent being part of a relationship and a sense of identity with other men who are also in relationships.
This factor aligns with the importance of relationship identity. In addition, the nature of male partners as a social identity is different than other social identities where each intimate relationship is unique and privately governed. The final scale then has only five items with a
Cronbach’s Alpha of .797, whereas the previous scale using eight items had a Cronbach’s Alpha of .776.
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Faith identity scale
I conducted an EFA for the adapted Sellers et al. (1998) Multidimensional Inventory for
Black Identity (MIBI) for religion identity using SPSS version 24. Although MIBI for religion identity is a scale that is supposed to have only one dimension, EFA was necessary to verify the number of dimensions in the adapted version (Henson & Roberts, 2006).
Table 8. Factor Analysis for Faith Identity Scale
Item Factor 1 Factor 2
Overall, being a Christian has very little to do with how I feel about myself* .097 .815
In general, being a Christian is an important part of my self-image .816 - .027
My destiny is tied to the destiny of other Christians .800 .078
Being a Christian is unimportant to my sense of what kind of person I am* .167 .802
I have a strong sense of belonging to a group of Christians . .871 -.107
I strongly relate to other Christians .897 -.240
Being a Christian is an important reflection of who I am .863 -.077
Being a Christian is not a major factor in my social relationships* .162 .750
* denotes reverse coding
The results revealed two factors. The first factor reflects the importance of Christian identity as MIBI scale suggests. The second factor, however, did not reflect a clear construct when it comes to the importance of Christian identity other than being the items that require reverse coding. I then concluded that this factor does not fit theoretically and conceptually, especially since this scale is supposed to have one factor.
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Three items above (Overall, being a Christian has very little to do with how I feel about myself, Being a Christian is unimportant to my sense of what kind a person I am, and Being a
Christian is not a major factor in my social relationships) were then omitted from the scale. The second and third items were omitted because they cross-loaded into both factors, leaving the first item the lone item in the second factor, which was then omitted. An EFA analysis was run for the second time with eigenvalues set greater than 1. One factor then emerged. This factor explained
72.91% of the variance. The original 8-items scale has a Cronbach’s Alpha of .791, whereas the
5-items scale consisting one factor has a Cronbach’s Alpha of .906.
Table 9. Exploratory Factor Analysis Factor Solution for Faith Identity Scale
Item Factor 1
In general, being a Christian is an important part of my self-image .818
My destiny is tied to the destiny of other Christian individuals .790
I have a strong sense of belonging to a group of Christians. .875
I have a strong attachment to other Christians .914
Being a Christian is an important reflection of who I am .866
Research Questions and Hypotheses Testing
RQ1A: Among individuals receiving health EPPM message, is the effect of perceived threat on behavioral intention moderated by perceived efficacy?
According to the EPPM tenets, efficacy moderates threat in producing health behavioral intention. Research Question 1A follows other studies in EPPM that examine how threat and efficacy influence health behavioral intention.
Throughout all of the research questions and hypotheses, a set of demographic variables was controlled. For Research Question 1A, Model 1 independent variables consisted of age,
94 relationship length, and pornography use. This model was followed by Model 2, which included perceived threat and perceived efficacy as the independent variables. Model 3 contained the interaction of perceived threat and efficacy as the final independent variable.
All predictor variables were not highly correlated, supporting the assumption of no multicollinearity. The no autocorrelation assumption is not violated (Durbin-Watson test = 2.30), and multicollinearity was not an issue according to Variance Inflation Factor, or VIF ( the largest
VIF among any of the predictor variable was 1.17). Autocorrelation assumption is violated when
Durbin-Watson test is < 1, whereas VIF shows multicollinearity, or an indication where independent variables are highly correlated, when the VIF value is > 10 (Curto, 2010).
With the level of significance set at p < .10, the overall model was significant at Model 1 with F (3,63) = 2.25 at p = .09, Model 2 with F (5,61) = 4.06 at p = .001, and Model 3 with F
(6,60) = 4.06 at p = .002. Model 1, or the covariates accounted for 9.7% of the variance in behavioral intention. Model 2 accounted for 19.2% of the variance. Model 3 accounted for 1% of the variance. The total model accounted 28.9% of the variance.
Among covariates, pornography use was a significant, negative predictor of behavioral intention with β = -.29 at p = .02, β = -.24 at p = .04, and β = -.29 at p = .04 in Model 1, Model 2, and Model 3, respectively. It means that the higher amount of pornography that an individual views each week, the less likely he is to adopt the message recommendations. In details, for every 1 unit of pornography consumed, there is .29 or .24 unit less of behavioral intention produced depending on the model.
Perceived efficacy was significant, positive predictor after controlling for demographic variables β = .44 at p < .001, β = .44 at p < .001 in Model 2 and Model 3, respectively. Perceived threat did not make significant contributions to the model. Because the interaction between
95 perceived threat and perceived efficacy was not significant at p = .80, perceived threat was not moderated by perceived efficacy in creating behavioral intention.
This result suggests the additive model of EPPM with efficacy being the lone predictor of the behavioral intention. In details, for every 1 unit increase in efficacy there is .44 unit increase in behavioral intention.
The multiplicative model suggests that condition with high threat and high efficacy
(HTHE) would make the biggest impact, followed the conditions with high threat and low efficacy (HTLE) or low threat and high efficacy (LTHE) next, and then the condition with low threat and low efficacy (LTLE) making the least impact. In an equation, it would look as HTHE
> HTLE = LTHE > LTLE. This particular result, however, found that HTHE and LTHE are equally significant condition in creating behavioral intention, followed by both HTLE and LTLE
(HTHE = LTHE > HTLE = LTLE).
Table 10. Relationships between Perceived Threat/Efficacy and Behavioral Intention among Individuals Receiving Health EPPM Message
Independent Variables b(SE) β p Model 1 Constant 14.45 (2.28) Age -.02 (.10) -.02 .82 Relationship Length .01 (.06) .02 .83
Pornography Use -.03 (.01) -.29 .02* R2 .097 Model 2 Constant 13.84 (.20) Age .00 (.09) .00 .95 Relationship Length .00 (.05) .00 .96 Pornography Use -.02 (.01) -.24 .04** Perceived Threat .06 (.64) .10 .35 Perceived Efficacy 2.62 (.65) .44 .00***** ΔR2 .192 Model 3 Constant 13.79 (2.09) Age .00 (.09) .00 .95 Relationship Length .00 (.05) .01 .92
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Pornography Use -.02 (.01) -.24 .04** Perceived Threat .62 (.65) .10 .34 Perceived Efficacy 2.61 (.65) .44 .00***** Perceived Threat * Perceived Efficacy .00 (.01) -.13 .80 ΔR2 .001 Total R2 .289 Adjusted R2 .218 p < .10 = *, p < .05 = **, p < .01 = ***, p < .005 = ****, p <.001=*****
RQ1B: Among individuals receiving relationship EPPM message, is the effect of perceived threat on behavioral intention moderated by perceived efficacy?
Research Question 1B aims to investigate whether EPPM tenet where efficacy moderates threat in creating health behavioral intention persists in relationship-based EPPM. I again applied hierarchical multiple regression in this hypothesis.
For Research Question 1B, Model 1 independent variables consisted of age, relationship length, and pornography use. Model 2 followed, which included perceived threat and perceived efficacy as the independent variables. Finally, Model 3 contained the interaction of perceived threat and efficacy as the final independent variable.
All predictor variables were not highly correlated, supporting the assumption of no multicollinearity. The no autocorrelation assumption is not violated (Durbin-Watson test = 2.03), and multicollinearity was not an issue according to Variance Inflation Factor, or VIF (the largest
VIF among any other predictor variables was 1.21).
With the level of significance set at p < .10, none of the models were significant with
Model 1 at F(3,66) = .35, p = .78, Model 2 at F(5,64) = 1.03 p = .40, and Model 3 at F (1,63) =
1.03 p = .41. Model 1 or the covariates accounted for 1.6% of the variance in behavioral intention. Model 2 accounted for 5.9% of the variance. Model 3 accounted for 1.5% of the variance. The total model accounted 9% of the variance.
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Perceived efficacy was significant, positive predictor after controlling for demographic variables β = .21 at p < .10, β = .22 at p < .10 in Model 2 and Model 3, respectively. Perceived threat did not make significant contributions to the model. Because the interaction between perceived threat and perceived efficacy was not significant at p = .31, perceived threat was not moderated by perceived efficacy in creating behavioral intention.
Similar to the previous research question, this result supports the additive model of
EPPM, as efficacy was the lone predictor of the behavioral intention. In detail, for every 1 unit increase in efficacy there is .21 or .22 unit increase in behavioral intention depending on the model.
Again, the multiplicative model of EPPM proposes that condition with high threat and high efficacy (HTHE) would make the biggest impact, followed the conditions with high threat and low efficacy (HTLE) or low threat and high efficacy (LTHE) next, and then the condition with low threat and low efficacy (LTLE) making the least impact (HTHE > HTLE = LTHE >
LTLE). This particular result supported additive model of EPPM over multiplicative model of
EPPM with HTHE and LTHE being equally significant condition in creating behavioral intention, followed by both HTLE and LTLE (HTHE = LTHE > HTLE = LTLE).
Table 11. Relationships between Perceived Threat/Efficacy and Behavioral Intention among Individuals Receiving Relationship EPPM Message
Independent Variables b(SE) β p Model 1 Constant 12.41 (2.48) Age -.02 (.10) -.03 .80 Relationship Length .01 (.03) .05 .68
Pornography Use .00 (.00) -.12 .33 R2 .016 Model 2 Constant 13.08 (2.61) Age -.06 (.10) -.07 .58 Relationship Length .01 (.03) .05 .65
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Pornography Use .00 (.00) -.11 .35 Perceived Threat .78 (.78) .13 .32 Perceived Efficacy .15 (.08) .21 .08* ΔR2 .059 Model 3 Constant 13.72 (2.69) Age -.08 (.11) -.10 .44 Relationship Length .01 (.03) .04 .74 Pornography Use .00 (.00) -.10 .40 Perceived Threat .72 (.78) .12 .36 Perceived Efficacy 1.35 (.73) .22 .06* Perceived Threat * Perceived Efficacy .73 (.72) .12 .31 ΔR2 .015 Total R2 .090 Adjusted R2 .003 p < .10 = *, p < .05 = **, p < .01 = ***, p < .005 = ****, p <.001=*****
RQ1C: Among individuals receiving faith EPPM message, is the effect of perceived threat on behavioral intention moderated by perceived efficacy?
Similar to the previous research questions, Research Question 1C intends to verify whether faith-based EPPM falls under multiplicative/interactive model, additive model, or none of those models.
For Research Question 1C, Model 1 independent variables consisted of age, relationship length, and pornography use as the covariates. Model 2 included perceived threat and perceived efficacy as the independent variables. Finally, Model 3 contained the interactions of: perceived threat and perceived efficacy as the final independent variable.
All predictor variables are not highly correlated, supporting the assumption of no multicollinearity. The no autocorrelation assumption is not violated (Durbin-Watson test = 1.87) and multicollinearity is not an issue according to VIF (< 1.6).
With the level of significance set at p < .10, the overall model was significant at Model 2 with F (5,66) = 4.48 at p = .001, and Model 3 with F (6,65) = 3.72 at p = .003. Model 1, or the
99 covariates accounted for 4% of the variance in behavioral intention. Model 2 accounted for 30% of the variance. Model 3 accounted for 1.6% of the variance. The total model accounted 35.6% of the variance.
Among covariates, pornography use was a significant, negative predictor of behavioral intention with β = -.20 at p = .09 in Model 2. It means that the higher amount of pornography that an individual views each week, the less likely he is to adopt the message recommendations.
It means that for every 1 unit of pornography consumed, there is .20 unit less of behavioral intention produced.
Perceived threat and perceived efficacy were significant, positive predictors after controlling for demographic variables.
Perceived threat was significant, positive predictor after controlling for demographic variables β = .45 at p = .000, β = .48 at p = .000 in Model 2 and Model 3, respectively. For every
1 unit increase in threat there is .45 or .48 unit increase in behavioral intention depending on the model.
Perceived efficacy was significant, positive predictor after controlling for demographic variables β = .30 at p = .004, β = .35 at p = .002 in Model 2 and Model 3, respectively. For every
1 unit increase in efficacy there is .30 or .35 unit increase in behavioral intention depending on the model.
Although both threat and efficacy were significant predictors of behavior intention, there was no interaction between perceived threat and perceived efficacy with p = .21. This means that a condition where both perceived threat and perceived efficacy are high is not required to produce maximum behavior intention, further debunking the multiplicative model of EPPM. An effective faith EPPM message needs either: (a) high perceived threat only (HTLE) or (b) high
100 perceived efficacy only (LTHE) to create behavior intention and it will have the same impact as a message that is high in both perceived threat and efficacy (HTHE), or to put it in an equation, it will be HTHE = HTLE = LTHE > LTLE.
Table 12. Relationships between Perceived Threat/Efficacy and Behavioral Intention among Individuals Receiving Faith EPPM Message
Independent Variables b(SE) β p Model 1 Constant 12.74 (2.53) Age -.07 (.11) -.07 .54 Relationship Length .04 (.03) .16 .25
Pornography Use .00 (.00) -.22 .11 R2 .040 Model 2 Constant 13.18 (2.21) Age -.08 (.10) -.08 .42 Relationship Length .02 (.03) .11 .36 Pornography Use .00 (.00) -.20 .09* Perceived Threat 2.74 (.62) .45 .00***** Perceived Efficacy 1.85 (.62) .30 .00**** ΔR2 .300 Model 3 Constant 12.95 (2.20) Age -.07 (.10) -.07 .49 Relationship Length .02 (.03) .09 .45 Pornography Use .00 (.00) -.18 .13 Perceived Threat 2.89 (.63) .48 .00***** Perceived Efficacy 2.14 (.65) .35 .00**** Perceived Threat * Perceived Efficacy .61 (.48) .46 .21 ΔR2 .016 Total R2 .356 Adjusted R2 .296 p < .10 = *, p < .05 = **, p < .01 = ***, p < .005 = ****, p <.001=*****
H2A: Among individuals receiving relationship-based EPPM message, the effect of perceived threat on behavioral intention is moderated by relationship identity.
For Hypothesis 2A, Model 1 independent variables consisted of age, relationship length, and pornography use as the covariates. Model 2 also included perceived threat and relationship
101 identity as the independent variables. Model 3 contained the interaction of perceived threat and relationship identity as the final independent variable.
All predictor variables are not highly correlated, supporting the assumption of no multicollinearity. The no autocorrelation assumption is not violated (Durbin-Watson test = 2.08) and multicollinearity is not an issue according to VIF (< 1.8). Although the level of significance is set at p < .10, none of the models were significant with Model 1 at F(3,66) = .35, p = .78,
Model 2 at F(5,64) = .42, p = .83 and Model 3 at F(6,63) = .94, p = .46. Model 1 or the covariates accounted for 1.6% of the variance in behavioral intention. Model 2 accounted for
1.6% of the variance. Model 3 or the total model accounted for 5.1% of the variance. The total model accounted for 8.3% of the variance.
Neither perceived threat nor relationship identity was a significant predictor of behavior intention. Perceived threat was not significant at p = .34 and p = .23 in Model 2 and Model 3, respectively, whereas relationship identity was not significant at p = .70 and p = .65 in Model 2 and Model 3, respectively.
However, there was an interaction between perceived threat and relationship identity at p
= .06, thus supporting Hypothesis 2A. This result suggests that in order to create maximum behavior intention using relationship EPPM message, both elements of perceived threat and relationship identity must be high (High Threat High Relationship, or HTHR). High threat and high relationship identity condition has more impact compared to high threat low relationship identity condition (HTLR) or low threat high relationship identity (LTHR) condition (HTHR >
HTLR = LTHR = LTLR).
Table 13. Relationships between Perceived Threat/Relationship Identity and Behavioral Intention Among Individuals Receiving Relationship EPPM Message
Independent Variables b(SE) β p
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Model 1 Constant 12.41 (2.48) Age -.02 (.10) -.03 .80 Relationship Length .01 (.03) .05 .68
Pornography Use .00 (.01) -.12 .33 R2 .016 Model 2 Constant 12.94 (2.83) Age -.04 (.11) -.05 .70 Relationship Length .01 (.03) .04 .72 Pornography Use .00 (.00) -.14 .26 Perceived Threat .76 (.80) .12 .34 Relationship Identity -.30 (.79) -.05 .70 ΔR2 .016 Model 3 Constant 15.35 (3.06) Age -.16 (.13) -.19 .21 Relationship Length .01 (.03) .03 .79 Pornography Use .00 (.00) -.14 .27 Perceived Threat .96 (.79) .16 .23 Relationship Identity -.35 (.78) -.05 .65 Perceived Threat * Relationship Identity 1.58 (.84) .26 .06* ΔR2 .051 Total R2 .083 Adjusted R2 -.005 p < .10 = *, p < .05 = **, p < .01 = ***, p < .005 = ****, p <.001=*****
H2B: Among individuals receiving relationship-based EPPM message, the effect of perceived efficacy on behavioral intention is moderated by relationship identity.
For Hypothesis 2B, Model 1 independent variables consisted of age, relationship length, and pornography use as the covariates. Model 2 also included perceived efficacy and relationship identity as the independent variables. Model 3 contained the interaction of perceived efficacy and relationship identity as the final independent variable.
All predictor variables are not highly correlated, supporting the assumption of no multicollinearity. The no autocorrelation assumption is not violated (Durbin-Watson test = 2.06) and multicollinearity is not an issue according to VIF (< 1.2). Although the level of significance
103 is set at p < .10, none of the models were significant with Model 1 at F(3,66) = .35, p = .78,
Model 2 at F(5,64) = .83, p = .52 and Model 3 at F(6,63) = .68, p = .66. Model 1 or the covariates accounted for 1.6% of the variance in behavioral intention. Model 2 accounted for
4.5% of the variance. Model 3 accounted for 0% of the variance. The total model accounted for
6.1% of the variance.
Perceived efficacy was a significant predictor of behavior intention. Perceived efficacy was significant with β = .21 at p = .09 in both Model 2 and Model 3. It means that for every 1 unit increase in efficacy there is .21 unit increase in behavior intention.
There was no interaction between perceived efficacy and relationship identity at p = .98, meaning that Hypothesis 2B was not supported. This result suggests that in order to create maximum behavior intention using relationship EPPM message, only perceived efficacy is necessary. High efficacy condition, regardless of the relationship identity, has more impact toward behavior intention compared to low efficacy condition. This additive model of perceived efficacy and relationship identity is similar to the additive model of EPPM in RQ1.
Table 14. Relationships between Perceived Efficacy/Relationship Identity and Behavioral Intention among Individuals Receiving Relationship EPPM Message
Independent Variables b(SE) β p Model 1 Constant 12.41 (2.48) Age -.02 (.10) -.03 .80 Relationship Length .01 (.03) .05 .68
Pornography Use .00 (.01) -.12 .33 R2 .016 Model 2 Constant 11.91 (2.62) Age .01 (.11) -.01 .91 Relationship Length .02 (.03) .06 .59 Pornography Use .02 (.03) -.08 .48 Perceived Efficacy 1.26 (.73) .21 .09* Relationship Identity -.21 (.78) -.03 .78 ΔR2 .045
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Model 3 Constant 11.91 (2.65) Age -.01 (.11) -.01 .21 Relationship Length .01 (.03) .06 .60 Pornography Use .00 (.00) -.08 .49 Perceived Efficacy 1.26 (.75) .21 .09* Relationship Identity -.21 (.79) -.03 .79 Perceived Efficacy * Relationship Identity .01 (.71) .00 .98 ΔR2 .000 Total R2 .061 Adjusted R2 -.028 p < .10 = *, p < .05 = **, p < .01 = ***, p < .005 = ****, p <.001=*****
H3A: Among individuals receiving faith-based EPPM message, the effect of perceived threat on behavioral intention is moderated by faith identity.
For Hypothesis 3A, Model 1 independent variables consisted of age, relationship length, and pornography use as the covariates. Model 2 also included perceived threat and faith identity as the independent variables. Finally, Model 3 contained the interaction of perceived threat and faith identity as the final independent variable.
All predictor variables are not highly correlated, supporting the assumption of no multicollinearity. The no autocorrelation assumption is not violated (Durbin-Watson test = 2.06) and multicollinearity is not an issue according to VIF (< 1.1).
The overall model was significant at Model 2 with F(5,66) = 4.48 at p = .001 and Model
3 with F(6,65) = 3.72 at p = .003. Model 1 was not significant with F(3,68) = .94 at p = .42.
Model 1 or the covariates accounted for 4% of the variance in behavioral intention. Model 2 accounted for 21.3% of the variance. Model 3 accounted for 2% of the variance. The total model accounted for 25.6% of the variance.
Perceived threat was a significant, positive predictor after controlling for demographic variables with β = .45 at p = .000 in Model 2, and β = .43 at p = .001 in Model 3. For every 1 unit
105 increase in perceived threat, there is .45 or .43 unit increase in behavior intention depending on the model.
The interaction between perceived threat and faith identity was not significant at p = .66, meaning that perceived threat was not moderated by faith identity in creating behavioral intention. This result suggests that in order to create maximum behavior intention using faith
EPPM message, only perceived threat is necessary. High threat condition, regardless of the faith identity, has more impact toward behavior intention compared to low threat condition. This additive model of perceived threat and faith identity is similar to the additive model of EPPM.
Table 15. Relationships between Perceived Threat/Faith Identity and Behavioral Intention among Individuals Receiving Faith EPPM Message
Independent Variables b(SE) β p Model 1 Constant 12.74 (2.53) Age -.07 (.11) -.07 .54 Relationship Length .04 (.03) .16 .25
Pornography Use .00 (.00) -.22 .11 R2 .040 Model 2 Constant 3.46 (4.17) Age -.13 (.10) -.13 .22 Relationship Length .02 (.03) .08 .52 Pornography Use .00 (.00) -.23 .07 Perceived Threat 2.71 (.71) .45 .00***** Faith Identity .34 (.70) .05 .62 ΔR2 .213 Model 3 Constant 14.32 (2.33) Age -.13 (.10) -.13 .22 Relationship Length .02 (.03) .08 .54 Pornography Use .00 (.00) -.22 .08 Perceived Threat 2.62 (.74) .43 .00**** Faith Identity .38 (.71) .06 .59 Perceived Threat * Faith Identity .24 (.55) .05 .66 ΔR2 .002 Total R2 .256 Adjusted R2 .187
106 p < .10 = *, p < .05 = **, p < .01 = ***, p < .005 = ****, p <.001=*****
H3B: Among individuals receiving faith-based EPPM message, the effect of perceived efficacy on behavioral intention is moderated by faith identity.
For Hypothesis 3B, Model 1 independent variables consisted of age, relationship length, and pornography use as the covariates. Model 2 also included perceived efficacy and faith identity as the independent variables. Finally, Model 3 contained the interaction of perceived efficacy and faith identity as the final independent variable.
All predictor variables are not highly correlated (r < 0.66), supporting the assumption of no multicollinearity. The no autocorrelation assumption is not violated (Durbin-Watson test =
1.66) and multicollinearity is not an issue according to VIF (< 1.1).
The overall model was significant at Model 2 with F (5,66) = 3.26 at p = .01 and Model 3 with F (6,65) = 3.19 at p = .008. Model 1 was not significant with F(3,68) = .94 at p = .42.
Model 1 or the covariates accounted for 4% of the variance in behavioral intention. Model 2 accounted for 15.8% of the variance. Model 3 accounted for 2.9% of the variance. The total model accounted for 22.7% of the variance.
Perceived efficacy and faith identity were significant, positive predictors after controlling for demographic variables in Model 2 and Model 3.
Perceived efficacy was significant at β = .34 at p = .000 in Model 2, and β = .33 at p =
.004 in Model 3. For every 1 unit increase in perceived efficacy there is .34 or .33 unit increase in behavior intention depending on the model.
Faith identity was significant at β = .23 at p = .04 in Model 2, and β = .23 at p = .03 in
Model 3. For every 1 unit increase in perceived efficacy there is .23 unit increase in behavior intention.
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Although both efficacy and faith identity were significant predictors of behavior intention, there was no interaction between perceived efficacy and faith identity with p = .12.
This means that a condition where both perceived efficacy and faith identity are high is not required to produce maximum behavior intention. An effective faith EPPM message needs either: (a) high perceived efficacy only (High Efficacy Low Faith, or HELF) or (b) high faith identity only (Low Efficacy High Faith, or LEHF) to create behavior intention and it will have the same impact as a message that is high in both perceived efficacy and faith identity (HEHF), or to put it in an equation, it will be HEHF = HELF = LEHF > LELF.
Table 16. Relationships between Perceived Efficacy/Faith Identity and Behavioral Intention among Individuals Receiving Faith EPPM Message
Independent Variables b(SE) β p Model 1 Constant 12.74 (2.53) Age -.07 (.11) -.07 .54 Relationship Length .04 (.03) .16 .25
Pornography Use .00 (.00) -.22 .11 R2 .040 Model 2 Constant 11.25 (2.39) Age .00 (.11) .00 .98 Relationship Length .03 (.03) .13 .32 Pornography Use .00 (.00) -.15 .24 Perceived Efficacy 2.05 (.68) .34 .00**** Faith Identity 1.40 (.67) .23 .04* ΔR2 .158 Model 3 Constant 11.28 (2.36) Age .00 (.11) .00 .99 Relationship Length .03 (.03) .12 .34 Pornography Use .00 (.00) -.16 .20 Perceived Efficacy 1.99 (.67) .33 .00**** Faith Identity 1.43 (.66) .23 .03* Perceived Efficacy * Faith Identity .87 (.56) .17 .12 ΔR2 .029 Total R2 .227 Adjusted R2 .156
108 p < .10 = *, p < .05 = **, p < .01 = ***, p < .005 = ****, p <.001=***** Table 17. Correlation matrix among participants who received the health EPPM ______1 2 3 4 5 M SD
1. SEV 9.98 4.67
2. SUS -.11 10.74 5.40
3. SE -.03 -.29* 14.82 4.96
4. REF .25* -.14 .28* 15.32 4.03
5. HBI .48** -.41** .31** .45** 12.11 5.88
Note. SEV = Severity, SUS = Susceptibility, SE = Self-Efficacy, REF = Response Efficacy, HBI = Health Behavioral Intention, ** = p < .01, * = p < .05
Table 18. Correlation matrix among participants who received the relationship EPPM message ______1 2 3 4 5 6 M SD
1. RI 20.07 5.31
2. SEV .00 10.17 5.03
3. SUS .16 -.12 10.97 5.30
4. SE -.10 .08 -.25* 15.10 4.75
5. REF -.05 .20 -.13 .58** 15.61 4.51
6. HBI -.06 .55** -.43** . .16 .23 11.71 5.98
Note. RI = Relationship Identity, SEV = Severity, SUS = Susceptibility, SE = Self-Efficacy, REF = Response Efficacy, HBI = Health Behavioral Intention, ** = p < .01, * = p < .05
Table 19. Correlations matrix among participants who received the faith EPPM message ______1 2 3 4 5 6 M SD
1. FI 32.08 6.31
2. SEV .37** 10.54 5.03
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3. SUS .06 -.31** 9.97 4.90
4. SE -.11 .24* -.33** 14.70 4.51
5. REF .06 .33** -.24* .76** 14.67 4.62
6. HBI .24* .74** -.23* .32** .31** 11.44 6.14
Note. FI = Faith Identity, SEV = Severity, SUS = Susceptibility, SE = Self-Efficacy, REF = Response Efficacy, HBI = Health Behavioral Intention, ** = p < .001, * = p < .005
Table 20. Summary of Research Questions and Hypotheses ______Hypotheses Results
RQ1A (threat and efficacy in health EPPM) Additive model (Efficacy only)
RQ1B (threat and efficacy in the relationship EPPM) Additive model (Efficacy only)
RQ1C (threat and efficacy in the faith EPPM) Additive model (Threat and efficacy)
H2A (social identity and threat [the relationship EPPM]) Supported
H2B (social identity x efficacy [relationship EPPM]) Not supported (Efficacy only)
H3A (social identity and threat [the faith EPPM]) Not supported (Threat only)
H3B (social identity x efficacy [the faith EPPM]) Not supported (Efficacy and identity)
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Chapter V
Discussion
This study had two main objectives. The first objective was to examine excessive pornography use as a health and social issue that demands attention and potentially, a series of focused health campaign messages. The second objective was to examine social identity as an additional source to the health-related threat and efficacy often presented in EPPM messages.
EPPM messages and identity salience (Pre-Test)
For the first objective, using Christian men who are currently in a romantic relationship for the study population, this study proposed that the issue of pornography together with health, relationship, and religion EPPM messages could trigger the salience of both relationship and religion as social identities. The pre-test showed that participants who were exposed to: (a) relationship EPPM message and (b) religion EPPM message had higher levels of salience of relationship and religious social identity respectively, as compared to those who were not exposed to such message (the control group).
As previously mentioned in the literature review, according to Stryker (1968), social identity salience is situation based, referring to which individual social identity is active in different situations. Based on the pre-test results, the EPPM social identity-based messages could activate participants’ particular identity of relationship status and religious membership while addressing the issue of excessive pornography consumption.
There are few explanations as to how the issue of pornography creates salience of social identity. First, churches have frequently addressed men’s pornography consumption in religious contexts (Abbell et al., 2006; Gardner, 2001). Carnes (1991) suggested that interventions for
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Christian men struggling with their sexuality consist of counseling in church settings and bible- based men’s groups in addition to professional counseling. Second, in terms of relationship status identity, the particular population of Christian men is: (a) familiar with the importance of being faithful to one’s spouse or partner and (b) using other Christian couples as points of reference in guiding their sexual behaviors (Cochran & Beeghley, 1991).
These explanations further support Stryker’s (1980) concept of identity salience. The salience hierarchy of identity should affect how individuals behave in various circumstances.
The greater the salience of identity that an individual has, the more likely that he or she will behave according to the expectations that come with the particular identity. This tendency stems from the positive feelings that he or she gains when his or her behaviors align with his or her identity. On the other hand, when the individual’s behaviors do not align with his or her identity, negative feelings emerge, and the individual will attempt to modify his or her behaviors to create synergy between his or her behaviors and his or her identity (Stryker & Burke, 2000).
Additive model of EPPM
The results of RQ1A, RQ1B, and RQ1C contributed to our theoretical understanding of the EPPM. In their review of EPPM, Maloney et al. (2011) suggested that one of the characteristics of a good theory is openness. In this case, EPPM as a theory should be “open to other possibilities beyond what it proposes” (Maloney et al., 2014, p. 214). This criterion includes falsifiability where the data analyses and results may deviate from what the theory predicts.
The current study showed that within the context of pornography, using health (RQ1A), relationship (RQ1B), and faith (RQ1C) EPPM messages, the threat and efficacy effects were additive, rather than interactive in influencing behavioral intention. The results of RQ1A and
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RQ1B added to the list of previous studies that suggest that efficacy alone correlated with behavioral intention change (Casey et al., 2009; Duong & Bradshaw, 2013; Jasemzadeh et al.,
2016, von Gottberg et al., 2016). Two reasons on why efficacy plays stronger role than fear in behavioral intention is the lack of familiarity with one’s environment and the lack of experience with the social issue being presented in the message (Duong & Bradshaw, 2013; Jasemzadeh et al. 2016). For instance, among less experienced teachers, only perceived efficacy correlated with the likelihood to intervene in bullying incidents in school environment, whereas for more experienced teachers both fear and efficacy correlated with their intervention tendency (Duong &
Bradshaw, 2013). Perceived efficacy was also the only predictor among first time expectant mothers in their self-care against air pollution (Jasemzadeh et al., 2016).
As for R1C, the result echoed Mongeau’s (2013) sentiment, which stated that high perceived threat alone (HTLE) or high perceived efficacy alone (LTHE) works as efficiently as high threat high efficacy (HTHE). Krieger and Sage (2013) noted the additive model of threat and efficacy, and mentioned that some axioms of EPPM garnered inconsistent findings. Those axioms were: (a) the idea that the amount of risk presented should not exceed the amount of efficacy that is present among individuals and (b) the concept of “magic cell” or the condition where both threat and efficacy are high (HTHE) is the absolute condition needed to incite behavior intention.
In short, the result of RQ1C corresponded more with Rogers’ (1970) Protection
Motivation Theory, where a certain amount of threat, paired with sufficient amount of efficacy, predicts behavior intention. Overall, the outcomes of RQ1A, RQ1B, and RQ1C suggested the additive model of EPPM. This model proposes that persuasive effects of creating both threat and efficacy perceptions are equal to adding threat with efficacy perceptions (HTHE > HTLE =
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LTHE > LTLE). The multiplicative model of EPPM, on the other hand, proposes that high threat high efficacy (HTHE) or the “magic cell” is the absolute requirement for behavior intention
(HTHE > HTLE = LTHE = LTLE).
Threat, efficacy, and social identity
The result of H2A, that supported the hypothesis, suggested that in creating severity and susceptibility elements of fear in relationship EPPM message, the importance of social identity affects behavior intention only if it comes with sufficient amount of perceived threat resulting from the message. Whereas EPPM message developed salience, social identity importance refers to the internal part of the self-concept and social group membership of the participants, regardless of the situation (Tajfel & Turner, 1979).
In previous literature, the threat to identity itself alone does not always lead to behavior
(Mussweiler, Gabriel, & Bodenhausen, 2000). Oftentimes, upon receiving identity threat, individuals could increase or decrease behaviors that correspond to their identity. Oher times, individuals could simply experience changes in mood or remain passive. This might be the reason why in order for behavior intention to take place, the individuals need to place high importance in their relationship role identity as well.
Individuals with high relationship identity importance felt more susceptible in consuming pornography than those with low relationship identity importance. Meanwhile, those with high religious identity importance did not feel more susceptible as compared with those with low religious identity importance. The items within the relationship identity scale pertain to the individuals’ commitment to their romantic partnership. The audience viewed these items as a reminder to protect the individuals’ partners’ feeling and thus, led the individuals who viewed the message to feel susceptible. In contrast, those with high religious identity importance may
114 perceive themselves as less susceptible to such temptations because their ways of life correspond with the religious messages displayed in the religion EPPM.
Next, H2B was not supported because efficacy appeared to be lone predictor of behavior intention in relationship EPPM condition. This result suggested that the role of efficacy as the most important predictor in behavior intention in previous health EPPM studies is applicable in relationship EPPM study. As mentioned above, efficacy could serve as the main predictor of behavior intention when the individuals lack familiarity and experience with the particular health or social issue. For most participants in relationship EPPM condition, taking part in this study could very well be their first time learning about the harmful effects of excessive pornography consumption on their marriage or romantic relationship.
As for faith EPPM message, H3A suggested that threat alone, without importance of identity, predicts behavior intention. However, a closer look at the data reveals that severity, without susceptibility, served as a single factor in predicting intent to avoid excessive consumption of pornography r = .37, p < .001. In fact, susceptibility alone was inversely correlated with behavioral intention. A possible explanation would be the nature of the faith
EPPM message that highlighted the severity of pornography consumption from the biblical standpoint. As for the susceptibility, perhaps a significant number of participants did not consume pornography to begin with. Hence, they do not feel that they were susceptible in consuming pornographic materials for over 11 hours per week and consequently, the behavior intention scale does not apply to them.
Finally, H3B, while not supported, supported the additive model of efficacy and faith identity in predicting behavior intention. Scholars can infer that creating both high efficacy and
115 high faith identity (HEHF) is unnecessary, and yet the sum of the high efficacy and high faith identity will result in behavior intention.
Among all of the research questions and hypotheses, this particular hypothesis is the most likely to be further developed in the near future due to the growing amount of research connecting self-efficacy and spiritual, or faith, identity. Previous studies connected spiritual identity with efficacy concerned efficacy in coping skills (Targ & Levine, 2002), efficacy in dealing with spiritual guilt (Klenck, 2004) and building self and response efficacy through social norms (Egbert & Parrott, 2001; Cho et al., 2009).
Next, among the three messages, the health EPPM message and faith EPPM message concerning excessive consumption of pornography show the most promise for administration in a hypothetical anti-pornography campaign. Because I want to focus solely on the message without taking the sample uniqueness (individual differences of identity trait), I would look at
RQ1A, RQ1B, and RQ1C results only. Here the R-squared for the health EPPM message and faith EPPM message were higher than relationship EPPM message. R-squared explains how good the model is using the baseline model (the model that uses the mean of Y to substitute for all of the X values) as a comparison. This value of R-squared refers to how much the independent variables influence the dependent variable (which in this case is behavioral intention). The health EPPM message (R2 = 28.9%) and faith EPPM message (R2 = 35.6%) were much better models than relationship EPPM (R2 = 9%). This result suggested that only health and faith messages elicited threat and built efficacy. Then, both threat and efficacy stemming from those messages prompted the behavioral intention actions.
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Relationship status identity and religion identity comparison
The two social identities (or identity roles) used in this particular study - relationship status and religious membership – have similar mechanisms in inciting fear and efficacy among participants. As mentioned in the literature review, those with high importance of religious membership identity might be more familiar with religious messages or sermons that deal with the severity of lust than those with low importance of religion membership identity. Relationship identity importance may not be as influential as religion membership identity when it comes to severity of pornography due to the uniqueness of different participants’ partners and their personally governed relationship rules. For instance, consuming pornography may have higher detrimental effects to one’s partner but not another man’s partner.
One significant difference in terms of messages between relationship EPPM and religious
EPPM is the novelty of the message. In relationship EPPM, the message contains relatively new information for the participants, such as “Pornography hurts women in heterosexual relationships. Women reported that they feel their boyfriends use them as ‘warm bodies’ to achieve sexual gratification after watching pornography.” Whereas in religious EPPM, most of the message mentioned statements that Christian men are familiar with, such as the biblical verses from the Book of Matthew: “Jesus even said, ‘anyone who looks at a woman lustfully has already committed adultery with her in his heart.’” The different effects that these two messages have on building fear suggest that in fear appeals message, there are many elements within the message itself that influence the effects of the threat being presented.
These different message elements were apparent in a previous study by Goodall and Reed
(2013) that manipulated the fear and efficacy elements within EPPM message to contain high and low amounts of uncertainty. Their study suggested that fear and efficacy messages that are
117 high in uncertainty lead the audience to seek more information about the issue. This result can be applied to the current study where the information regarding the detrimental effects of pornography are not as readily available as the more publicized health threats such as smoking or substance abuse.
Next, numerous studies on identity distinguish between the importance (others also call it prominence) and salience of social identity (Garza & Herringer, 2001; Stryker & Serpe, 1994). I measured the ability of the message to activate the salience of social identity during the pre-test upon receiving the identity-based EPPM message. During the main experiment, I measured the importance of social identity prior to exposing participants to the message. The results showed that the importance of relationship status and the importance of religious membership identity affected behavioral intention differently.
In examining freely listed social identities among undergraduate students, Garza and
Herringer (2001) noted that both religion and family roles rank moderately high in terms of positive emotion, importance, and stability as compared to other social identities, such as hobbies, employment, geographical origin, club membership, and age. However, the family roles in Garza and Herringer’s (2001) study did not pertain to being a spouse or a partner, but a family member. Thoits (1991) provided the most extensive explanation on the social roles of being a husband or a boyfriend. These role identities appear to be unstable due to the different stress and burden of nurturing and caring for the other person that each husband or boyfriend has. For instance, stay-at-home husbands have different concepts of spouse identity than breadwinning husbands.
Finally, scholars and churches have consistently brought the topic of pornography using the context of religion and Christianity, rather than its effects toward one’s spouse or partner
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(Abbell et al., 2006; Carnes, 1991; Gardner, 2001). A good chunk of the literature on the consumption of pornography in the context of partnership focuses on its effects toward the female partner (Bridges et al., 2003; Bergner & Bridges, 2002; Schneider, 2000). These studies became the basis of relationship EPPM message, which emphasizes on the partner’s detrimental effects rather than the participant’s detrimental effects shown in the health EPPM message and religion EPPM message. Similar EPPM research has also existed where the behavioral intention involves acting on behalf of others rather than oneself (Egbert, Miraldi, & Murniadi, 2014).
Theoretical implications
As previously mentioned, the first purpose of this study is to address the danger of excessive pornography consumption in being a health and social issue. Looking at the findings it is useful for health practitioners to involve the element of identity in designing fear appeals messages. Both: (a) identity threat of hurting one’s partner and not following the Biblical verses as a Christian, or (b) social identity threat of not fitting in with husbands/boyfriends group and
Christian group, worked as effectively as the health threats.
These results lend an explanation to the Identity theory, that identity importance plays a significant role in influencing behavioral intention, as evidenced in this study. For example, among participants who received relationship EPPM message, their relationship identity importance moderated perceived threat in creating behavioral intention. Those who received faith EPPM message, their faith identity importance directly correlated with behavioral intention.
While this particular study pertained to the application of EPPM within the context of pornography consumption, scholars may relate the above study design to future EPPM messages in different contexts, such as gambling or drinking and driving. It is plausible that upon receiving health messages in non-pornography context, different individuals with different levels of
119 identity importance process the health message differently. Another possibility is that perhaps any health message would invoke an individual’s identity salience, and thus, prompt the individual to perform the message recommendations due to identity salience rather than risk behavior diagnosis.
Identity is an important factor to examine in subsequent studies involving EPPM or other fear appeals messages. Other elements of identity that could serve as mediators include the source of identity importance and identity salience (McCall & Simmons, 1978). Health and social identity scholars could measure support, reward, and perceived opportunity situation, in determining predictors of behavioral intention. Other elements of identity to observe could be group status or perceived group stigma, for members of minority groups, such as transgender or
Muslims. The next realm of health promotional message should include identity salience- building messages in addition to fear and efficacy building messages.
If there should be one take away message with this study, it is that these results extend
Identity theory, and to some extent Social Cognitive Theory, in a way that our identity role is capable of empowering us to experience, perceive, feel about ourselves, evaluate ourselves, and finally, regulate ourselves. These assumptions are significant because identity could be the keys to successful interventions in a plethora of health problems. As a side note, future research should also examine the role of emotions that occurred among individuals while and after viewing identity-based EPPM messages.
In terms of SIT, the results provided evidence to Hogg and Reid’s (2006) statement on the function of identity. According to Hogg and Reid, individuals’ group memberships create group prototypes that allow individuals to enact who they are, and by doing that, individuals strengthen their identity. By acting in alignment with their identity, the individuals reaffirm and
120 communicate their social identity to others and inform others who they are. The fact that religious identity correlated with behavioral intention suggested the notion above. The statement
“I am a Christian” manifested in the behavioral intentions that fit with the biblical verses. By applying SIT, this study provides an insight to understand pornography consumption as identity- based behaviors.
However, scholars should not overlook additional factors in pornography consumption behavioral intention regarding pornography consumption, such as: (a) negative emotions
(Averbeck et al., 2011) and (b) positive emotions (Nabi, 2010). Regret and guilt may play important roles in health issues affecting others, such as this context of excessive pornography consumption (Averbeck et al., 2011, Nabi, 2002). Some important appraisals of regret and guilt include negative self-perceptions and self-accountability. In this case, engaging in corrective behaviors may function as a suppression for the guilty feeling toward one’s partner, one’s higher power, or one’s fellow social group members (group of male partners or group of Christians).
Another theory where these results or this study design could be beneficial would be
Brehm and Brehm’s (1981) Psychological Reactance Theory. The theory suggests that individuals love to be free to experience an array of activities, and reactance happens when the activities encounter some threats. In this case, it would be the health or identity threats from consuming excessive pornography. Meanwhile, resistance is an element of counteractive behaviors triggered by the perceived threat to freedom. In this case, it is the freedom to view pornographic materials. Further, this theory argues that individuals differ on their trait reactance, or the tendency to reject recommendations from others (Pavey & Sparks, 2009). This is where the identity or social identity factor could offer some explanations on how to solve the trait reactance issues or to strengthen message recommendations.
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Practical implications
The findings of this study should benefit the professional world, particularly when it comes to message design. As identity is crucial in processing health promotional messages, health practitioners should pay more attention to individual differences in terms of their identity.
The use of social media might allow message designers to customize health messages to fit with one’s social group. Identity-based health messages could appear on YouTube, Instagram, or
Facebook.
One area that I also noticed is the fact that pornography use inversely correlated with behavioral intention among participants receiving the EPPM health message. This finding brought me to consider Prochaska and DiClemente’s (1983) stages of change to consider for future research. For some people, pornography addiction is not something that is feasible to stop within the next three months. The stages of change framework describe the individuals’ process in commencing and continuing preventative behaviors. Its tenet states that individuals in the early stages of change lack any motivation and intention to adopt the preventive behaviors, but as the individuals pay more attention to the health consequences, they move to the later stage, the preventive behaviors become habitual and the individuals would not slip backward to doing the risky behaviors.
For health practitioners, social identity importance (the significance of the particular identity in our cognitive self) and salience (the likelihood of the particular identity becomes active across different situations) have two implications. Those are: (a) health message campaigners could customize the message based on the social identity importance of the population of the study, and (b) health message campaigners could create relevant contexts or scenarios to the underlying health issue – when presenting the message – that would invoke the
122 particular identity of the population. Previous research in EPPM deals with an array of different populations ranging from rural women (Egbert & Parrot, 2001) to wildlife managers (Muter et al., 2013), along with a variety of topics, such as bed bug prevention (Goodall & Reed, 2014) to intention to save school children from asthma attack (Goei et al., 2010).
Consequently, health practitioners can design the EPPM messages to cater to these specific populations. The designs could include keywords that differentiate them from the general population and make them associate with other individuals from their population, or contain cases that are common in their daily lives. An excellent example comes from the
Tobacco Truth campaign.
Limitations
The main limitation of this study is the difficulties in infusing social identity into EPPM theoretical framework. The first difficulty comes from the message design. It is challenging to create health messages that present a health threat while simultaneously the containing an identity threat. Studies in EPPM have always been about informing the audience regarding the severity and susceptibility of health threats and the urgency and efficacy to take actions. In identity-based EPPM, the message should also manipulate the audience’s salience of identity, which can be counterproductive to the purpose of a health message.
The second difficulty comes from choosing the appropriate scales to measure identity importance, identity salience, perceived threat, and perceived efficacy. This study simply used
Witte et al.’s (1996) Risk Behavior Diagnosis Scale, which is more fitting to answer perceived health threat and not perceived identity threat. In addition, the questions addressing the duality of importance and salience of identity can be problematic because the available scales concerned more with cognitive processing, which is part of identity importance, rather than behaviors,
123 which is the element of identity salience. Hopefully, future research could lend some ideas on how to employ the right methodology tactics in the studies in the areas of identity and fear appeals messages.
Other limitations of this study come from the study rationale and the ethical considerations. While a number of studies provide the correlation between pornography consumption and aggression or marital dissatisfaction, the old adage of chicken-or-egg argument applies. As the saying goes, correlation does not prove causation. Marital dissatisfaction could as well lead individuals to escape their sexual frustration through the consumption of pornography.
Highly aggressive individuals are perhaps more likely to view pornography than average individuals. If those are the cases, inserting excessive consumption of pornography into the list of public health issues may not be the most astute step to take as a health scholar.
Presenting facts from other than peer-reviewed articles or citing the bible to frighten the participants also poses an ethical dilemma. Participants might perceive the facts, or arguable facts, regarding pornography as more serious than what I intended them to be. Next, while there are biblical verses that forbid humans to practice deviant behaviors, Jesus’ teachings are mostly about kindness and compassion. To use the verses literally might lead to some negative repercussions among practicing Christians.
In terms of method, the study sample posed a significant limitation. While the literature review addresses the prevalence of pornography use among men and the social identities of relationship status and religious memberships, male college students were the sole sample population for the main experiment due to convenience purpose. On one hand, this choice resulted in a homogeneous sample but on the other hand, the results of this study cannot generalize the population of Christian men who are currently in an intimate relationship.
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The next limitation is the use of single topic of pornography in examining the effects of social identity on fear appeal messages. In addition to this limitation, there are other important and potentially salient social identities besides religious membership and relationship status in bringing up the detrimental effects of deviant sexual behaviors. This study is simply an initial attempt to connect the dots of social identity importance, salience, fear, efficacy, and behavioral intention in fear appeals message.
The following limitation pertains to the measurements of social identity. In the pre-test, it is somewhat problematic to measure salience by re-wording identity importance measurement scaling items. The concept of salience should refer to behaviors rather than cognitive processing.
By presenting the participants with questionnaires, I automatically elicited the participants’ cognitive self. An ideal measurement of salience would be asking participants about their past behaviors in different circumstances (Stryker & Serpe, 1994).
For the main experiment, this study only measured religion identity prior to the exposure to religion EPPM message and only relationship identity prior to the exposure of the relationship
EPPM message. In addition to that, participants receiving health EPPM message did not receive social identity importance measurement. There are two reasons for this choice: (a) this study is a preliminary study within the area of social identity and EPPM, and (b) it is important to keep the survey lean considering the samples consist of undergraduate students who participated in this study for a credit. The fact that participants took this survey for college credits is also an important variable to consider when studying pornography.
The final limitation is that the study collected participants’ data through self-report measurements rather than other forms of measurement. Because pornography use is highly stigmatized, the results may not necessarily reflect the actual behaviors of the participants.
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Scholars in this field need to explore some better ways to measure attitudes toward pornography and pornography habits, such as by applying Uses and Gratifications Theory together with
EPPM or other health communication theories to pornography consumption (Blumler & Katz,
1974; Rubin, 1994).
Uses and Gratifications Theory could lend an analysis as to whether a person views pornography out of sexual compulsive needs, peer pressure, loneliness, curiosity, or even educational purpose. In the past, Ebersole (2000) examined how students in ten different public schools navigate the Internet and found that a handful of them cited their reason to browse material online was to find sexually explicit sites. However, the study did not divulge what motivated those students to visit the sexually explicit sites, which could be the next step in studying pornography consumption.
This theory could alter studies on excessive pornography consumption as for example, someone who views pornography for educational purpose, does not fit under sexual compulsive or at-risk users described in the literature despite the amount of hours spent viewing pornography. Previously, Uses and Gratifications Theory had explained that among men, the number of hours watching televised violence is a less significant predictor of aggressive behaviors when compared with experience with crime and locus of control (Haridakis, 2006).
Future directions
Future directions within the area of pornography, social identity, and fear appeals message should address all of the limitations above. As a public health and social issue, pornography affects individuals from different sexes, age groups, occupations, and other demographic variables (Owens et al., 2012). Hence, the use of Christian men who are currently in an intimate relationship is simply an experiment on the effects of social identity on fear
126 appeals message and the beginning of a more holistic approach in curbing excessive pornography use.
Health communication and identity scholars need diverse samples for future study to test the health messages pertaining to identity-based threat appeal and pornography use. This is due to the facts that: (a) in terms of pornography use, Christian males who are in a romantic relationship do not reflect the results of the GSS survey, and (b) there are other relevant social identities when addressing the sexual compulsive and at-risk pornography consumers.
As well, health scholars should continue to examine if identity facilitates, or in some cases, detracts from individual’s health behavioral intention. For instance, scholars could look at the emotional processes that take place during the health messages consumptions and behavioral intention changes. While identity serves as an important marker health behavior adoptions and the prior or subsequent cognitive processes, it is the responsibility of health scholars to effectively use identity in health contexts in the most beneficial and effective manner.
In closing, the script outlined for future research within the intersections of health, media, and identity is challenging. However, this current study might assist health communication scholars to unravel the connections between social identity and fear appeals message and to identify different aspects and elements within various health messages in general. The results obtained in this study could potentially improve future health campaigns against excessive consumption of pornography.
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Definition of terms
At-risk: the term used for individuals who consume pornography for more than 11
hours per week
Efficacy: the effectiveness, feasibility, and ease with which a recommended
response impedes or averts a threat
EPPM: a fear appeal model which proposes that in order for individuals to
perform message recommendations, the message needs to incite high level
of fear and efficacy
Fear: an internal emotional reaction comprising psychological and physiological
dimensions that may be aroused when a serious and personally relevant
threat is perceived
Identification: the extent to which an in-group member defines the self as a member of
the particular social group
Mediation: the generative mechanism where the independent causes the mediator
which then causes the independent variable
Mediator: the qualitative or quantitative variable that occurs in a causal pathway
between an independent and dependent variable
Moderation: the generative mechanism where the relationship between an independent
and dependent variable is dependent upon a moderator
Moderator: the qualitative or quantitative variable that affects the direction and/or
strength of the relation between an independent and dependent variable
Pornography: written or pictorial matter intended to arouse sexual feelings
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Response efficacy: beliefs about the effectiveness of the recommended response in deterring
the threat
Self-efficacy: beliefs about one’s ability to perform the recommended response to avert
the threat
Severity: beliefs about the significance or magnitude of the threat
Sexual compulsive: the term used for individuals who consume pornography between one hour
to 11 hour per week
Social categorization: how individuals choose to identify with groups, construe themselves and
others in group terms, and manifest group behaviors
Social identity: how individuals classify themselves and others into different social
categories
Social identity importance: the location of one’s identity in the self-concept structure, whether it is
central or peripheral, a major or minor part of self
Social identity salience: how much likelihood that one’s particular identity will be active in various
situations
Social-identity based efficacy: a proposed element in identity-based EPPM where beliefs about
the effectiveness of the recommended response in deterring the threat
stemmed from social identity-based message.
Social-identity based threat: a proposed element in identity-based EPPM where perceived
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serious and personally relevant threat stemmed from social identity-based
message.
Susceptibility: beliefs about one’s risk in experiencing the threat
Threat: a danger or harm that exists in the environment whether we know it or not
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Appendix A
Health EPPM message
Pornography harms your health.
One of four Internet searches is related to pornography. Every second, 28,000 people view Internet pornography. In 2006, pornography revenues in the U.S. exceeded 13 billion dollars.
The danger of pornography.
The American Psychiatric Association considers excessive viewing of online pornography to be a mental health disorder. Symptoms of this disorder include compulsive masturbation and fixation on an unattainable partner. Other symptoms include intense sexual fantasies and urges. Internet pornography has been shown to correlate with pornography addiction, depression, and drug abuse.
Say no to pornography.
The University Counseling Centre provides suggestions for excessive viewers of pornography. “Change your routines and environments that lead to pornography usage, and avoid high risk situations,” the website states. “Make a list of the positive and negative consequences of using pornography.” “It is also important to spend less time alone, so you can quit your pornography use.”
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Appendix B
Relationship EPPM message (being a husband/boyfriend as a social identity) Pornography harms your relationship.
Using pornography could lead to seeking multiple sexual partners. Partners of sex addicts reported that they felt devastated, humiliated, and betrayed by their partners. When viewing porn, men are likely to feel entertained whereas women are likely to feel disgusted.
The danger of pornography.
Consumption of pornography for more than an hour per week relates to dissatisfaction in intimate relationships. In fact, half of divorces are related to online pornography habit. Pornography hurts women in heterosexual relationships. Women reported that they feel their boyfriends use them as “warm bodies” to achieve sexual gratification after watching pornography. Most men agree that a good boyfriend or husband should refrain from watching online pornography. “A good boyfriend would rather spend a quality time with his partner rather than watching pornography,” said one of the men being interviewed.
Say no to pornography.
Matt Seago, a married man, admitted that he used to spend more than 11 hours a week viewing pornography online. Now he is a changed man. “The key is to change routines and environments that lead to pornography usage,” Seago said. “Avoid high risk situations. Make a list of the positive and negative consequences of using pornography. Spend more time with your spouse, so you can quit your pornography use.”
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Appendix C
Faith EPPM message (being a Christian as a social identity) Pornography harms your spirituality.
Pornography is a concern for Christian men. People who view pornography reported higher acceptance of extramarital affairs. Men who view pornography are less likely to attend church.
The danger of pornography.
Pornography is anti-Christian. God abhors all that is immoral, sexually perverted, and lustful. The Ten Commandments say, “You shall not commit adultery” and “You shall not covet … your neighbor’s wife.” Jesus even said, “anyone who looks at a woman lustfully has already committed adultery with her in his heart. If your right eye causes you to sin, gouge it out and throw it away.“ Most of the Christians being interviewed said that Christians should refrain from viewing pornography online. “We should treat our body as the way God intended it to be,” said one of them. “God wants us to live up to a higher standard’s than the world.”
Say no to pornography.
Matt Seago, a Christian man, admitted that the idea of consuming pornography can be tempting. “The key is to change routines and environments that lead to pornography usage,” Seago said. “Avoid high risk situations. Make a list of the positive and negative consequences of using versus not using pornography. Spend more time with other strong Christian men, so you can quit your pornography use.”
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Appendix D
Meyer (1998) and West (1994) Channel Credibility Index
1. The scenario is:
realistic 1 2 3 4 5 6 7 unrealistic.
2. The message is:
believable 1 2 3 4 5 6 7 unbelievable.
3. Matt Seago’s testimony is:
well-founded 1 2 3 4 5 6 7 not well-founded.
4. The information given would: be verifiable if examined 1 2 3 4 5 6 7 not be verifiable
if examined.
5. Statements are mostly:
true/correct 1 2 3 4 5 6 7 not true/correct.
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Appendix E
Social Identity Stimulus Check
Be sure to read every part of the message. Answer these questions by circling the number that best indicates how you feel.
1. A. This message reminds me of the importance of maintaining a healthy body and mind.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. This message reminds me of the importance of being a Christian.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. This message reminds me of the importance of being a husband/boyfriend.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
2. A. This message is significant to my role as a person with healthy body and mind.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. This message is significant to my role as a Christian.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. This message is significant to my role as a husband/boyfriend.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. A. This message makes me feel a strong identification with people who are physically
and mentally healthy.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
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B. This message makes me feel a strong identification with other Christians.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. This message makes me feel a strong identification with other husbands/boyfriends
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
4. A. This message makes me realize that being physically and mentally healthy is
important to my sense of self.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. This message makes me realize that being a Christian is important to my sense of self.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. This message makes me realize that being a husband/boyfriend is important to my
sense of self.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
5. A. This message makes me think about my responsibility to maintain a healthy body and
mind.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. This message makes me think about my responsibility as a Christian.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. This message makes me think about my responsibility as a husband/boyfriend.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
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6. A. This message increases my sense of belongingness with other physically and mentally
healthy individuals.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. This message increases my sense of belongingness with other Christians.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. This message increases my sense of belongingness with other boyfriends/husbands.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
7. A. This message is effective in strengthening my identity as a physically and mentally
healthy individual.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. This message is effective in strengthening my identity as a Christian.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. This message is effective in strengthening my identity as a husband/boyfriend.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
8. A. This message reminds me that being physically and mentally healthy is an important
part of my self-image.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. This message reminds me that being a Christian is an important part of my self-image.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
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C. This message reminds me that being a husband/boyfriend is an important part of my
self-image.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
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Appendix F
Social Identity Stimulus Check for the Control Group
Be sure to read every part of the message. Answer these questions by circling the number that best indicates how you feel.
1. A. It is important to maintain a healthy body and mind.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. It is important to be a Christian.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. It is important to be a husband/boyfriend.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
2. A. My role as a person with healthy body and mind is significant.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. My role as a Christian is significant.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. My role as a husband/boyfriend is significant.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. A. I feel a strong identification with people who are physically and mentally healthy.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. I feel a strong identification with other Christians.
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Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. I feel a strong identification with other husbands/boyfriends
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
4. A. I realize that being physically and mentally healthy is important to my sense of self.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. I realize that being a Christian is important to my sense of self.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. I realize that being a husband/boyfriend is important to my sense of self.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
5. A. I think about my responsibility to maintain a healthy body and mind.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. I think about my responsibility as a Christian.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. I think about my responsibility as a husband/boyfriend.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
6. A. I have a high sense of belongingness with other physically and mentally healthy
individuals.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. I have a high sense of belongingness with other Christians.
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Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. I have a high sense of belongingness with other boyfriends/husbands.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
7. A. I have strong identity as a physically and mentally healthy individual.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. I have strong identity as a Christian.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. I have strong identity as a husband/boyfriend.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
8. A. Being physically and mentally healthy is an important part of my self-image.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
B. Being a Christian is an important part of my self-image.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
C. Being a husband/boyfriend is an important part of my self-image.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
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Appendix G
Demographic Questions
Please indicate your age on your last birthday: 18 – 24 25 – 35 36 – 50
51 and above
Please indicate your annual income: less than $ 20,000 $20,000 – < $40,000
$40,000 – < 60,000 $ 60,000 – <$80,000
$80,000 – <$100,000 $100,000 and above
Please indicate your ethnicity: White Black or African American
Hispanic Native American or Alaskan
Asian or Pacific Islanders Other
Please indicate your education: Middle school High school Some college
Bachelor degree Master’s degree Doctorate degree
Please indicate your occupation:
Please indicate your relationship status: Married Engaged Dating
Separated Divorced
How long have you been in your current relationship? _____ years and _____ months
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Appendix H
Pornography Use
Did you look at pornographic material in the past year?
How many times in the past year did you look at pornographic material?
1 – 5 6 – 10 11 – 20 More than 20 times
How many hours per week do you spend looking at pornographic material?
How many hours in the past week did you spend looking at pornographic material?
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Appendix I
Witte, et al. (1996) Risk Behaviors Diagnosis Scale
Please read each statement and circle a number that indicates your opinion.
Severity.
1. Consuming pornography for more than an hour per week is a serious threat.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
2. Consuming pornography for more than an hour per week is harmful.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. Consuming pornography for more than an hour per week is a severe threat.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
Susceptibility.
1. I am at risk for consuming pornography for more than an hour per week.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
2. It is possible that I will use pornography for more than an hour per week.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. I am susceptible to using pornography for more than an hour per week.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
Self-Efficacy.
1. I am able to quit/limit pornography use to prevent more than an hour per week use of
pornography.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
144
2. It is easy to quit/limit pornography use to prevent more than an hour per week use of
pornography.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. I can quit/limit pornography use to prevent more than an hour per week use of
pornography.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
Response Efficacy.
1. Quitting/limiting pornography use prevents more than an hour per week use of
pornography.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
2. Quitting/limiting pornography use works in deterring more than an hour per week use of
pornography.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. Quitting/limiting pornography use is effective in getting rid of more than an hour per
week use of pornography.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
145
Appendix J
Adjusted Sellers et al. (1997) Multidimensional Inventory of Black Identity (MIBI)
centrality dimension scale for being a boyfriend/husband as a social identity
Please read each statement and circle a number that indicates your opinion.
1. Overall, being a boyfriend/husband has very little to do with how I feel about myself.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
2. In general, being a boyfriend/husband is an important part of my self-image.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. My destiny is tied to the destiny of other boyfriends/husbands.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
4. Being a boyfriend/husband is unimportant to my sense of what kind of person I am.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
5. I have a strong sense of belonging to a group of other boyfriends/husbands.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
6. I strongly relate to other boyfriends/husbands.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
7. Being a boyfriend/husband is an important reflection of who I am.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
8. Being a boyfriend/husband is not a major factor in my social relationships.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
146
Appendix K
Adjusted Sellers et al. (1997) Multidimensional Inventory of Black Identity (MIBI)
centrality dimension scale for Christianity as a social identity
Please read each statement and circle a number that indicates your opinion.
1. Overall, being a Christian has very little to do with how I feel about myself.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
2. In general, being a Christian is an important part of my self-image.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. My destiny is tied to the destiny of other Christian individuals.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
4. Being a Christian is unimportant to my sense of what kind of person I am.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
5. I have a strong sense of belonging to a group of Christians.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
6. I have a strong attachment to other Christians.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
7. Being a Christian is an important reflection of who I am.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
8. Being a Christian is not a major factor in my social relationships.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
147
Appendix L
Rise, Kovac, Kraft, and Moan (2008) Behavior Intention Scale.
Please read each statement and circle a number that indicates your opinion.
1. During the next 3 months, I intend to quit/limit pornography use.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
2. During the next 3 months, I plan to quit/limit pornography use
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
3. During the next 3 months, I expect to quit/limit pornography use
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
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