THE RELATION BETWEEN PLAYING VIOLENT SINGLE AND MULTIPLAYER VIDEO GAMES AND ADOLESCENTS’ AGGRESSION, SOCIAL COMPETENCE, AND ACADEMIC ADJUSTMENT

Jason A. Drummond

A Thesis

Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of

MASTER OF ARTS

May 2009

Committee:

Eric F. Dubow, Advisor

Dara R. Musher-Eizenman

Jean M. Gerard

ii

ABSTRACT

Eric F. Dubow, Advisor

Over the past 20 years video games have grown in popularity and come to include

“modes” that allow players to play with others who are either present or connected by the internet. Although research has found links between solitary violent video game play and indices of maladjustment (e.g., increases in aggressive behavior, decreased GPA), little research has examined the correlates of playing violent video games with others. The present study examined not only the extent to which children and adolescents are playing violent video games with others in multiple contexts (i.e., alone, with others present, and with others online), but also the relation between play in these contexts and aggressive and prosocial behavior, social adjustment, and academic adjustment. Participants included 484 participants in the 7th, 9th, and 11th grades who completed surveys about their video game play habits, aggressive and prosocial behavior, social competence, and academic adjustment. The majority (60%) of participants indicated that they played violent video games, with 56%, 50%, and 30% indicating that they play alone, with others present, and with others online, respectively. Male participants played in each context more often than females, and younger participants generally spent greater amounts of time playing than older participants. Higher frequencies of violent video game play were found to be related to more aggressive and less prosocial behavior, lower ratings of social competence, and poorer academic adjustment. Participants’ primary context of play (i.e., primarily playing alone, with others present, or with others online) did not relate to outcomes. These relations generally held even when gender and grade level were accounted for, and these relations generally were not moderated by gender or grade level. In general, higher frequencies of violent video game iii play, rather than the context of game play, were related to negative adjustment. Limitations of the study included those generally accepted regarding self-report data such as reporter bias and possible errors in retrospective reporting, limited generalizability due to a sample with restricted age and ethnic diversity, and lack of longitudinal data. Finally, implications of the results and ideas for future research were discussed. iv

I dedicate this thesis to Sarah and Lily- without your love and support I never would have made

it through this process. A big “too” to both of you! v

ACKNOWLEDGMENTS

I would first like to acknowledge my advisor, Dr. Eric Dubow, whose support,

encouragement, and wealth of knowledge was invaluable throughout the thesis process. I would

also like to thank my committee members, Dr. Dara Musher-Eizenman and Dr. Jean Gerard, for

their contribution to each step of the thesis process and guidance in refining and completing this

study. Heartfelt thanks are also due to my compatriot in this undertaking, Kelly Lister. I will

always be thankful for the hours we spent together refining this project and bouncing ideas off

each other- having someone to laugh with throughout the project was also a special bonus. I

would like to say a special thanks to Paula Watson, Rich Rowlands, BGSU HSRB, and Sue

Thornton for their help and expertise during this project. Acknowledgement is further due to the parents, students, administrators, and teachers of the Bowling Green Junior High and High

School for participating in this study. Special thanks also go out to my good friend Jeremy Athy

who was not only supportive throughout this process but also provided invaluable help during

data collection. I would be remiss if I did not thank my fellow graduate students for providing an

environment of academic excellence and valuable peer support. Finally, I would like to thank

my family and friends for always supporting my curiosity and my academic dreams. Without

your support and love I never would have made it this far- I love you all! vi

TABLE OF CONTENTS

Page

INTRODUCTION ...... 1

Video Game Usage Among Adolescents...... 2

Theoretical Models to Explain the Hypothesized Effects of Playing Violent Video Games

on Aggression, Social Competence, and Academic Adjustment...... 6

Aggression ...... 6

Social competence ...... 9

Academic adjustment...... 11

Empirical Findings on the Relation of Violent Online and Multiplayer Video Game Play

to Aggression, Social Competence, and Academic Adjustment...... 12

Violent video game play and aggressive behavior ...... 12

Violent video game play and social competence...... 14

Video game play and academic adjustment...... 16

Multiplayer and online video games...... 17

Limitations of the current research on relations between violent video game

usage, aggression, social competence, and academic adjustment ...... 21

Present Study ...... 22

METHOD……………...... 25

Participants and Procedures...... 25

Overview of the Survey ...... 26

Measures Used in the Present Study ...... 27

Video game play items...... 27 vii

Assessing aggressive and prosocial behavior using the Direct and Indirect

Aggression Scales ...... 29

Perceived competence...... 31

Academic adjustment...... 33

RESULTS……………...... 34

Overview of Analyses...... 34

Preliminary Analyses...... 35

Hypothesis 1: Developmental Differences in Video Game Play…………………... 38

Hypothesis 2: Relation between the Frequency of Video Game Play and Aggressive and

Prosocial Behavior, Social Competence, and Academic Adjustment……………… 41

Video game play and behavioral adjustment...... 41

Video game play and social adjustment...... 42

Video game play and academic adjustment...... 44

Summary of results for Hypothesis 2...... 44

Hypothesis 3: Gender and Grade Level as Moderators of the Relation between Frequency

of Play and Adjustment...…………………………………………………………... 45

Results for aggressive and prosocial behavior, with gender included as an

independent variable ...... 46

Results for aggressive and prosocial behavior, with grade included as an

independent variable ...... 47

Summary of results for aggressive and prosocial behavior ...... 47

Results for social adjustment, with gender entered as an independent

variable...... 48 viii

Results for social adjustment, with grade entered as an independent

variable...... 49

Summary of results for social adjustment...... 50

Results for academic adjustment, with gender entered as an independent

variable...... 50

Results for academic adjustment, with grade entered as an independent

variable...... 51

Summary of results for academic adjustment...... 52

DISCUSSION...... 54

Hypothesis 1: Developmental and Gender Differences in Video Game Play ...... 54

Hypothesis 2 & 3: Relation between the Frequency of Violent Video Game Play and

Aggressive and Prosocial Behavior, Social Adjustment, and Academic Adjustment 56

Violent video game play and aggressive and prosocial behavior...... 56

Violent video game play and social adjustment ...... 59

Violent video game play and academic adjustment...... 61

Limitations ...... 62

Conclusions and Future Directions...... 64

REFERENCES……… ...... 66

APPENDIX A: LETTER SENT TO PARENTS DESCRIBING THE STUDY...... 74

APPENDIX B: ITEMS REGARDING DEMOGRAPHICS AND ACADEMIC

ACHIEVEMENT………...... 75

APPENDIX C: VIDEO GAME USAGE ITEMS ...... 76

APPENDIX D: AGGRESSIVE AND PROSOCIAL BEHAVIOR ITEMS ...... 77 ix

APPENDIX E: PERCEIVED COMPETENCE ITEMS...... 78

APPENDIX F: ACADEMIC ADJUSTMENT ITEMS...... 79

APPENDIX G: TABLES AND FIGURES ...... 80 x

LIST OF TABLES

Table Page

1 Description of the Sample...... 80

2 Number and Percentage of Participants of Each Gender Who Indicated Playing Violent

Video Games Overall, Alone, With Others Present, and With Others Online ...... 81

3 Number and Percentage of Participants in Each Grade Who Indicated Playing Violent

Video Games Overall, Alone, With Others Present, and With Others Online ...... 82

4 Multiple Analysis of Variance and Multiple Analysis of Covariance for Behavioral,

Social Adjustment, and Academic Adjustment Variables...... 83

5 Multiple Analysis of Variance and Multiple Analysis of Covariance for Behavioral,

Social Adjustment and Academic Adjustment Variables...... 84

6 Multiple Analysis of Variance and Multiple Analysis of Covariance F-Values for

Examining Gender Main Effects and Interactions with Video Game Variables in

Predicting Adjustment Variables ...... 85

7 Multiple Analysis of Variance and Multiple Analysis of Covariance F-Values for

Examining Gender Main Effects and Interactions with Video Game Variables in

Predicting Adjustment Variables ...... 87

xi

LIST OF FIGURES

Figure

1 Mean intimate competence scores for the gender x frequency of play with others present

interaction ...... 89

2 Mean cognitive competence ratings for the grade x primary context of play

interaction ...... 90

1

INTRODUCTION

Video games have been a part of American culture for over 20 years (Kent, 2001).

Concern regarding the content of video games has increased in recent years in response to several important factors. First, more children are playing video games now than ever before (Roberts, Foehr, & Rideout, 2005). This increase in video game usage by children has raised concerns that this activity is replacing other activities such as playing outside, reading, and schoolwork and that exposure to video game violence may be affecting social behaviors (Gentile, Lynch, Linder, & Walsh, 2004). A second factor that is raising public concern is the highly publicized school shootings by teens who were found to have high levels of violent video game use (Anderson & Dill, 2000; Kirsh, 2003). However, it should be noted that those who have committed school shootings are an incredibly small percent of violent video game consumers. Finally, there is concern that video games are becoming more graphically detailed. With this increased detail, violent behaviors can be portrayed with a higher degree of realism. Thus, in recent years there has been a growing concern over the relation between violent video game exposure and levels of aggressive behavior in children.

In the extant literature, very little attention has been given to the effects of playing violent video games with others. Recent developments in internet and video game technology have made it possible for people to jointly play video games from a distance

(e.g., playing with others online). Thus video game production companies have begun to place greater emphasis on producing games that can be played with multiple players.

Additionally, online video games which were previously restricted to “first-person shooter” (FPS) games now also include sports games, massive multiplayer online games 2

(MMOs) in which players take part in an online “world” with thousands of other players, and other types of games which attract a greater variety of game consumers (Ducheneaut,

Yee, Nickell, & Moore, 2006; Williams et al., 2006; Natkin, 2006). Overall, recent advances in technology have changed the face of how video games are played with others.

The present study was aimed at not only examining how much time children are spending playing violent multiplayer video games, but also examining gender and age differences in play. In addition, the present study examined the relation between time spent playing violent multiplayer video games and levels of aggressive and prosocial behavior, social competence, and academic adjustment.

The following discussion of the factors in question in this study begins with an examination of extant research on video game usage rates. Next, theoretical models pertaining to the effects of violent video game exposure on aggressive behavior, social competence, and academic adjustment will be discussed. Subsequently, the discussion will turn to an examination of empirical findings on the relation between video game exposure and the variables of interest. Finally, the author concludes with a description of the present study.

Video Game Usage Among Children and Adolescents

When examining the effects of playing video games on children, it is important to begin by reviewing basic data such as who is playing video games. In 2005, The Kaiser

Family Foundation released the results of a large-scale study, “Generation M: Media in the Lives of 8-18 Year-Olds,” which examined the amount of time children spend using electronic media (Roberts et al., 2005). These authors collected data through interviews 3 and media-use diaries from a nationally representative sample of 2,032 children between the ages of 8 and 18 years of age. This study served as a follow up to similar study conducted in 1999 with over 3, 000 children and represents one of the largest studies of its kind (Roberts, Foehr, Rideout, & Brodie, 1999, Roberts et al., 2005). It provides detailed information about the media habits of children in the United States.

According to Roberts et al. (2005), children today live in a world filled with electronic media. In fact, 99% of children have at least one television in the home, with

73% having three or more televisions in the home. Furthermore, 83% of children have at least one video game device in their home. Additionally, this study reported that even in homes at the lowest levels of socioeconomic status (SES), there is a high degree of media saturation. However, the results indicate that those who live in lower SES neighborhoods are less likely to have a computer, video game system, or internet access in their homes.

Despite this fact, 49% of lower SES homes have video game systems, 36% have computers with CD-Rom drives, and 23% have computers which are connected to the internet. Additionally, many children who do not have these types of media in their homes will be exposed to them either at public institutions such as libraries and schools, in the growing number of internet cafes, or in the homes of friends. Thus, regardless of

SES, many children in today’s culture have access to a wide array of electronic media.

According to Roberts et al. (2005), the amount of time children spend with video games each day decreases as children grow older, with the average amount of time spent playing games daily for 8-10 year-olds, 11-14 year-olds, and 15-18 year olds being 65 minutes, 52 minutes, and 33 minutes, respectively; this represents an increase in reported time spent with video games from the previous study (Roberts et al., 1999). Furthermore, 4 over half (52%) of the participants in the 2005 study indicated that they had played video games in the 24 hours prior to their data being collected, with 8-10 year olds being the most likely to have played video games in this time period (59%). These data indicate that many children spend a significant amount of time with video games each week which makes it important to understand the effects these games may be having on children.

A significant gender difference in video game play was also found by Roberts et al. (2005). Overall, males tend to spend more time playing video games than females, with males playing, on average, 54 more minutes per day than females. Additionally, males are more likely to spend long periods playing video games daily than females with

31% of males and only 11% of females reporting playing for more than an hour each day.

What is of greater concern to researchers about the increased time males spend with video games is that, compared to girls, some studies have provided evidence that boys tend to prefer games with more violence (e.g., Gentile et al., 2004).

Although past research has illuminated the general play patterns of children, little research has examined the amount of time children spend playing video games with others. That is, much of the extant research regarding video games has involved the study of solitary play experiences. However, several recent studies have begun to shed light on who is playing multiplayer games and what motivates players to engage in multiplayer games. In a study by Griffiths et al. (2004), researchers set out to determine the characteristics of gamers who played the “massively multiplayer online role-playing game” (MMORPG) Everquest. In this study researchers gathered information from a self- selected group of 540 (431 male; 99 female) Everquest players using an online survey 5 aimed at gathering demographic information as well as information on time spent playing and motivation for playing the MMORPG. Results of this study indicated that approximately 59% of the Everquest players were 12-17 years-old and that 93% of respondents in this age range were male. Additionally, it was found that many of these players placed greater emphasis on social factors, such as interacting with others and forming friendships, than on any combat or competition related factors. In a study by

Jansz and Tanis (2007), an online survey (N=754; 745 male) was utilized to gather information on who is playing first person shooter games (FPS) online and what motivates the players to play online with others. This study found that the mean age of

FPS players was 18.09 years of age (SD=3.92). Similar to the previously mentioned study, evidence was also found for greater social motivations for playing. However, as players began to view themselves as more serious or “professional” gamers, they tended to be more motivated by competition. In another study, a survey was given to 176 (6 female) participants at a Local Area Network (LAN) event at which game players gathered to play multiplayer video games on computers connected to one another via a

LAN (Jansz & Martens, 2005). Participants in this study ranged in age from 11 to 35 with a mean age of 19.5, indicating that adolescents were among the participants at the event in question. Again, participants at this event indicated that they were mostly motivated to attend for the social interaction aspects of the event, with aspects such as competition rated as less important.

These three studies provide some limited evidence that children and adolescents are, in fact, playing video games in which they participate with other players online or in person. They also provide some insight into the motivation behind playing multiplayer 6 games, with players generally indicating that they are drawn to this type of gaming for social interaction reasons rather than for competition. However, no studies have been published which survey random samples of participants to determine how popular online video games are with children and adolescents. Additionally, no research currently available has gathered information on the frequency with which children and adolescents play video games with other players who are actually in the room with them. Thus, it is important to gather information on how common it is for children to engage in video game play in a social manner and with what types of behaviors such play may be associated. With this in mind, the current study will attempt to gather information on the percentage of children across different stages of adolescence who are playing games in a multiplayer setting, either online or with others present in the room. Additionally, information on behavioral, academic, and social adjustment will be gathered to examine whether a relation exists between these variables and social video game play.

Theoretical Models to Explain the Hypothesized Effects of Playing Violent Video Games on Aggression, Social Competence, and Academic Adjustment

Aggression. The definition of aggression has been taken by different researchers to encompass a wide range of behaviors. In some cases aggression is defined as acts such as yelling or hurting another person in a relatively minor way such as by pushing someone or pulling his or her hair (Bjorkqvist, 1997). In other cases indirect methods of aggression, such as asking others to exclude a certain person, are also included in this definition (Lagerspetz & Bjorkqvist, 1994). Additionally, others have proposed that aggression encompasses a wide range of behavior ranging from verbal and minor physical altercations to extreme violence including aggravated assault and murder 7

(Berkowitz, 1997). Regardless of these distinctions, they all have a common thread; most social scientists define aggressive behaviors as those behaviors which have either the goal of causing some type of injury or loss to a target or further the aims of the aggressor and allow the aggressor access to a desired object or goal (Anderson & Bushman, 2002).

As was previously noted, much of the research on video games has focused on the potentially harmful effects of exposure to graphic depictions of violence. Several theories have been advanced to explain how violent video games affect levels of aggression.

Some researchers have proposed that the effects of video games, and media in general, work through a social learning model (e.g., Chambers & Ascione, 1987; Irwin & Gross,

1995; Schutte, Malouff, Post-Gorden, & Rodasta, 1988). According to social learning theory (SLT), people learn new behaviors by observing others and copying those behaviors which they see are rewarded (Bandura, 1994). According to SLT, violent video games provide numerous instances to observe violent behavior which is rewarded by points, in-game money, or achievement of goals. Additionally, Bjorkqvist (1997, p. 71) proposed that there are four important factors that determine if another person’s behavior will be imitated:

1. the degree of similarity between the model situation and the actual situation, 2. identification with the model in question, 3. whether the model is successful or not, and 4. the amount of exposure to the model situation in question.

Therefore, if game players come to identify with the characters in a game, SLT posits that they will be more likely to imitate behaviors they have observed. Finally, these video games are said to allow game players to rehearse violent behaviors making them more available for use in future situations. Thus, SLT proposes that video games affect players 8 through social transmission and repeated trials of being exposed to and practicing aggressive behaviors.

Another model which has been proposed for how playing violent video games affect players is a neo-associative networks or priming model (e.g., Anderson & Ford,

1987; Anderson & Morrow, 1995). According to this model, priming occurs when violent media provides violent cues which prime networks within the brain that connect aggressive thoughts, feelings, and behaviors, thus increasing the possibility that aggressive behaviors will be chosen as solutions to problems (Berkowitz, 1990; Jo &

Berkowitz, 1994).

The most popular model currently being applied to video game effects on aggression is the General Aggression Model (GAM) (Anderson & Bushman, 2002;

Bushman & Anderson, 2002; Anderson & Dill, 2000; Bartholow et al., 2005; Carnagey

& Anderson, 2005). The GAM was designed to be an inclusive model, encompassing the previously discussed models and others, which proposes that aggressive behavior arises from interactions between personological traits (e.g., temperament, trait hostility) and situational factors which affect a person’s cognitions, arousal, and emotional state

(Anderson et al., 2004). According to this model, violent video games affect players in several ways. The immediate consequence of playing violent video games is that they increase a person’s general arousal and activate aggressive behavior scripts which are described by Eron (1994, p.7) as “guides for behavior and social problem solving.” These scripts have been learned over time in a manner similar to how SLT proposes all behaviors are learned. Recalling a script does not necessarily mean that the behaviors encoded in the script will be enacted; the decision to actually engage in the behaviors is 9 influenced by a host of mediating individual and situational factors, including but not limited to noxious stimuli, beliefs either supporting or opposing aggressive behavior, hostile thoughts, mood, and arousal levels (Anderson & Bushman, 2002; Berkowitz,

1997; Eron, 1994). Activation of aggressive scripts is said to lead to increases in aggressive behaviors shortly after exposure to video game violence.

Long-term exposure, on the other hand, is posited in the GAM to teach players violent behaviors through imitation of characters in the games and repeated opportunities to learn violent solutions to problems. This model also proposes that long-term exposure to violent video game content leads to desensitization to violence which makes committing aggressive behaviors seem less aversive. Thus, this model proposes that video games not only affect game players through several different modes, but also that video games may have potential for greater harm than other media on account of video games immersing the player in an active rather than passive (e.g., through simply viewing violent content as in television viewing) experience. The GAM will be used as the primary model for how violent video game usage affects aggression levels as well as social competence throughout this study.

Social competence. All of the theoretical models discussed above have been used to predict how violent video game exposure may lead to an increase in aggressive behavior. An area that has not been extensively examined in the literature is the effect playing video games may have on social interactions with others. Furthermore, no published research to-date has examined the effect of playing video games in a social context (i.e., with others in the same room or with others online). With these issues in 10 mind, the current study is aimed at gathering data to determine if a relation exists between social video game play and levels of aggression and social competence.

Previous studies have found that socially competent children differ from socially incompetent ones in several ways including differences in the encoding of social information, in assessing the motives behind behaviors, in deciding how to resolve problems, and in estimating the consequences of behavior (Lenhart & Rabiner, 1995).

Although several studies have examined the manner in which competent social skills can be learned and the differences between socially competent and incompetent children and adolescents, few studies have directly examined the relation between video game exposure, and more specifically social video game play, and competent social behavior.

When playing violent video games, children often learn to use violent methods to solve problems rather than using prosocial solutions. Additionally, evidence suggests that children exposed to violent video games have higher levels of aggressive behavior and thoughts. As these aggressive behaviors increase, it is likely that prosocial behaviors will decrease. The GAM would suggest that, during social video game play, it is likely that children will see others receive rewards for aggressive behavior while prosocial behavior is either ignored or punished. The fact that these rewards and punishments are being experienced by a real person, as opposed to a character in a game, may result in even greater increases in aggressive behavior and greater decreases in prosocial behavior.

Alternatively, playing video games with others may give a child more opportunities to interact with others in a supportive manner. This may be the case if children who are playing together encourage one another to reach goals or congratulate each other for successes. If this is the case, it may be that children learn and use prosocial 11 skills as they play games with others. It is also possible for players of online video games to form relationships with other players online. Many games that are played online often see the formation of groups of players who routinely play together and organize into

“guilds” or “clans” (Williams et al., 2006). Through the formation of these relationships, it may be possible for someone to increase his or her social support network and engage in more social interactions with others. These factors may result in higher self ratings of social competence in those who play video games socially compared to those who mainly play alone. Thus, it is important to consider the effects of video games on children’s social skills and ability to use prosocial behaviors in addition to examining effects on aggression.

Academic adjustment. With the amount of time children are now spending playing video games, some concern has arisen regarding how this lost time affects academic adjustment. Some have proposed that the time spent playing video games will “displace” time spent towards academic activities (Huston et al., 1992). This displacement hypothesis also proposes that time spent playing video games would take away time from reading and time spent engaged in extracurricular activities at school. Taking this theory one step further, if a child or adolescent places a large emphasis on spending time playing video games, it is likely that he or she will place less importance on spending time engaged in school activities.

Several studies have found negative relations between video game play and academic achievement (Gentile et al., 2004). Furthermore, it has been proposed that time spent in media usage displaces activities with a similar “function” (Comstock & Paik,

1991). In other words, rather than replacing social activities, television viewing and video 12 game play tend to replace time spent on activities such as reading or studying. Thus it is possible that excessive video game play may lead to a displacement of time spent engaged in activities related to academic adjustment. If this is the case, then it is likely that decreases in academic adjustment will be seen as time spent with video games increases.

Empirical Findings on the Relation of Violent Online and Multiplayer Video Game Play to Aggression, Social Competence, and Academic Adjustment

Violent video game play and aggressive behavior. Much of the research on video games has focused on the negative effects of playing video games. That research has mainly focused on the effects violent video games have on aggressive behaviors, empathy, anxiety, and sensitivity to violence.

The area of video game research that has been the focus of the most empirical literature is that pertaining to the effects of playing violent video games on aggression.

Some studies have provided support for a relation between exposure to video game violence and increased levels of aggression (for example, Anderson & Dill, 2000;

Bartholow et al., 2005). Alternatively other studies have shown little or no relation between violent video game exposure and aggressive behavior (for example, Colwell &

Kato, 2003; Williams & Skoric, 2005). Even separate meta-analyses of the video game research literature have reached different conclusions. On the one hand, in a meta- analysis by Anderson and Bushman (2001), it was concluded that there was a definite link between violent video games and aggression which was so strong that it “…poses a public-health threat to children and youths, including college age individuals” (p. 358).

In this study, effect sizes for violent video game play on outcomes such as aggressive 13 behavior and physiological arousal were computed as Pearson’s r and ranged from .18 to

.26. On the other hand, in a meta-analysis published the same year by Sherry (2001), the results suggested that there was an overall relation between playing violent video games and increased levels of aggression but that this “…relationship is smaller than that found for television” (p.424). Effect sizes for violent video game exposure in this study were also computed as Pearson’s r and ranged from .13 to .16. Some researchers have accused others of only citing studies which support their conclusions and not those which contradict evidence that may support the aggression/violent video game link and discounting theories which may explain some of the contradictory findings (i.e., catharsis theory which proposes that video games may provide a socially acceptable release for aggressive behavior) (Griffiths, 2000).

While examining results of meta-analyses is important in understanding the overall trends being found in research on the relation between aggression and violent video game exposure, it is also important to examine the results of specific studies that are frequently cited in the extant research. In 2000, Anderson and Dill published a report regarding two studies examining the effects of violent video games on emotions, aggressive thought, and behavior. In the first study, 227 (149 female) undergraduates were asked to complete self report surveys on their video game usage as well as scales measuring irritability (impulsive reactions to provocation), trait aggression (likelihood a person will favor an aggressive solution to a problem), delinquency (e.g., hitting or threatening others, destruction of property, drug use), and academic achievement

(cumulative GPA). This study found a positive association between exposure to video game violence, trait aggressiveness, and rates of delinquency. Furthermore, it was found 14 that exposure to video game violence was a stronger predictor of aggressive outcomes than was total video game usage. In the second study reported by Anderson and Dill

(2000), 210 (104 female) undergraduates from the previous study were selected and split into a group with low irritability scores and another with high irritability scores. The participants were then asked to play either a violent or nonviolent game three times followed by tests of reaction time designed to measure aggressive cognition as well as ratings of state hostility. Results revealed that the type of video game played did not have a significant effect on state hostility above the effect of trait hostility and gender (females generally had higher ratings). On the other hand, video game type was found to significantly relate to the accessibility of aggressive cognitions and aggressive behaviors.

The authors proposed that their findings offer some support for a connection between long-term exposure to video game violence and hostile and delinquent behaviors in addition to short-term increases in aggressive behavior and cognition after playing violent video games. On the other hand, a study by Wiegman and van Schie (1998), in which 278

10-14 year olds were interviewed regarding their video game usage and preferences, found no relation between violent video game exposure and aggressive behavior.

However evidence was found that more aggressive children preferred to play violent games, suggesting that perhaps persons with aggressive personalities naturally gravitate towards violent media. Thus, although there is some mixed evidence in some studies for the relation between violent video game exposure and aggressive behavior, the meta- analyses do show at least a modest effect size.

Violent video game play and social competence. A second set of variables often studied in relation to violent video game play is socially competent behaviors (i.e., 15 empathy and prosocial behavior). One concern is that exposure to video game violence results in decreased levels of empathy (perhaps through desensitization) and, on account of this, lower levels of socially competent behavior. One study, in which survey data were gathered from two hundred male undergraduates ranging in age from 18 to 22, found that persons with higher levels of violent video game exposure exhibited lower levels of empathy and higher levels of aggressive responding (Bartholow et al., 2005).

However, this study was correlational in nature so it is impossible to determine whether lower empathy leads a person to seek out violent media or violent media is leading to decreased levels of empathy. Funk et al. (2003) conducted an experimental study in which thirty-five children aged 8- to 12 years old (M=10.14, 10 females) were asked to play either a “relatively” violent or nonviolent game and then responded to vignettes and survey measures designed to rate levels of empathy. The researchers found that children exposed to the violent video game were less able to provide empathic responses to the vignettes.

Several studies have also examined the relation between violent video game play and prosocial (socially competent) behavior. In one study, after playing a violent video game undergraduate students (N=48; 6 female) were presented with a “prisoner’s dilemma” test (Sheese & Graziano, 2005). In order to test prosocial behavior, the prisoner’s dilemma test gave each participant the choice of either cooperating with a partner or working against (defecting from) a partner. Participants were told that if both partners chose to cooperate, the reward they were to receive was increased slightly. On the other hand if they both defected, the reward amount was decreased. Finally, if one cooperated while the other defected, the defecting partner’s reward increased while the 16 cooperating partner’s reward decreased. Participants who played the violent game were less likely to respond in a cooperative manner with their partner, an indication of lower prosocial behavior. In a similar study using a group of 8 to 15 year-old children (N=160;

80 female), those who had played a violent video game were found to be less likely to donate money than children who had played a prosocial game (Chambers & Ascione,

1987). However in this study there was no difference between the two conditions in children’s willingness to help the experimenter with a task, so the results related to prosocial behavior were mixed. In another study with 278 10-14 year-old adolescent participants, there was a negative correlation between violent video game exposure and prosocial behavior, even though no relation was found between aggressive behavior and violent video game exposure (Wiegman & van Schie, 1998).

Video game play and academic adjustment. A third area that has been examined in video game research is the effect of playing video games on academic adjustment.

Researchers examining the effect of video game usage often predict that time spent playing video games in general, rather than violent video games specifically, will effect academic adjustment by displacing time previously spent on academic activities (Huston et al., 1992). In the study mentioned earlier by Anderson and Dill (2000), a modest negative relation was found between total video game usage and academic achievement as measured by total GPA. In a separate study, the results of surveys completed by 245 college students found a negative correlation between video game usage, GPA, and SAT scores (Anand, 2007). Although these two studies provide some evidence for the relation between video game play and poorer academic outcomes, they use college students as their samples, and thus do not shed light on the relation between video game play and 17 academic adjustment among children. In addition, being correlational studies, the direction of effect is not clear. It is possible that lower-achieving students gravitate toward video games. Gentile et al. (2004) conducted a study with 8th and 9th graders

(N=607; 291 female) that examined, among other variables, the relation between video

game play and academic adjustment. In this study, total time spent with video games was negatively related to grades earned. Additionally, it was found that children who played more violent video games also reported that they argued with their teachers more frequently. However, this second finding was limited by the fact that trait hostility was found to vary with both violent video game exposure and arguments with teachers. Taken as a whole, the results of these studies provide some evidence for a relation between time spent playing video games and poorer academic adjustment, but the direction of the effect is unclear.

Multiplayer and online video games. As noted earlier, video game producers are now creating games with a greater potential for multiplayer functionality. Much of the extant research on violent video game play has been conducted using “old generation” video games that do not emphasize social game play. With this increase in multiplayer game popularity and availability, it is important to determine whether playing with another person, whether that person is in the room or across the world, may have an affect on those playing. Whether this be an increase or decrease in learned aggression or an increase or decrease in social competence, it is important to gather information first on whether a relation exists.

The majority of studies about online game play have focused on identifying who is playing these games and examining the virtual communities which develop within 18 these online environments. These studies might suggest that playing these games is related to the development of socially competent behavior. In a study by Whang and

Chang (2004), the online “lives” of 4,786 players of the MMORPG Lineage were studied via an online survey to determine what types of activities players engaged in while playing. It was found that in this MMORPG, there were diverse personalities which ranged from socially oriented players who preferred to join virtual groups within the game to those who preferred to explore the virtual environments alone. It was also found that players of Lineage tend to favor factors in people which are seen as favorable in the real world such as sincerity and manners. These findings are interesting as the authors contend that some have called Lineage a violent video game, which may lead one expect players to find factors which may promote in-game violence more favorable such as strength and aggressive personality factors. Studies such as this are important as they allow us to gain a greater understanding of how the use of online games can draw people together into communities of people with common interests and how these virtual communities are similar to real communities.

Although these games may bring together large groups of people who would otherwise not interact with one another, there is also some preliminary information about possible negative side effects these games have on the players such as the possibility for addictive play behavior and social deficits. Grüsser, Thalemann, and Griffiths (2007) conducted an online survey with 7,069 “gamers” to examine the possibility of video game addiction. Results indicated that 11.9% of the study’s sample met diagnostic criteria for addiction (e.g., “craving” video games). Additionally, this study found that those who met the criteria for an addiction showed symptoms of cognitive biases and 19 cravings seen in those with substance addiction problems. Furthermore, another independent study indicated that players of the MMORPG Everquest spend a great deal of time involved in the game with adolescent players playing an average of 26.25 hours per week with 14.7% of adolescents playing over 31 hours per week (Griffiths et al.,

2004). Additionally, a survey of 174 college-age online game players in Taiwan found that increases in time spent playing online games had a significant relation to lower self- reported levels of social functioning and higher levels of social anxiety (Lo, Wang, &

Fang, 2005). However, the correlational nature of this study made it impossible to determine whether socially impaired individuals spent more time playing online games or if playing online games leads to social impairment. It should also be noted that another study showed no decrease in the number of friends or increase in social isolation related to spending more time playing computer games (Colwell & Kato, 2003). Overall, there is some preliminary evidence that there may be negative relations to real-world social functioning and the possibility of addiction when too much time is spent in online game play.

Although some studies have suggested that there may be negative effects from playing online video games, there is some evidence that playing games with others also may have a buffering effect on increases in aggression typically evidenced in research into violent video games. In one study, researchers set out to determine whether there was a difference in aggressive behavior after playing a computer or playing another human

(Williams & Clippinger, 2002). This study had college age students (N=54; 26 female) play the non-violent computer game Monopoly against both a computer and another participant of the same sex in separate testing sessions. After playing the game against a 20 computer there were greater increases in self-reported levels of aggressive behavior and frustration than after playing against the human opponent. This study provides limited evidence that the presence of other human players may act to moderate the effects of competitive play on aggressive behavior. In a second study, participants (N=213; 45 female, 1 unstated) who had no MMORPG experience were recruited from video game and general interest online message boards and were asked to play the MMORPG

Asheron’s Call 2 (AC2) for a month (Williams & Skoric, 2005). Participants in this study ranged from age 14 to 68 with a mean age of 27.7 years. The game AC2 was chosen for this study because of its relative simplicity and because it is considered the most violent

MMORPG on the market with high degrees of detailed blood and gore. At the end of the exposure period, all of the participants had experienced many exposures to AC2, many on a daily basis. It was found that participants who had played AC2 did not experience increases in aggressive cognitions or behaviors related to being exposed to the violent video game. Thus, the results of this study seem to contradict the GAM model of how video games affect players over extended periods. It is unknown whether this lack of increase in aggression was related to playing the game with other participants or reflected a general lack of overall effect for the simulated violence on aggressive behavior.

Additionally, when looking at the effects of violent media on aggression, it is important to consider developmental characteristics of participants. Many researchers believe that violent media exposure has greater effects on aggression in younger children. The participants in this study were mainly adults who may not be affected as greatly by media violence exposure, as their behavior and cognitions may already be well established and more resistant to change. However, the results of these two studies taken together provide 21 interesting information related to how playing games in a social setting may affect the outcomes experienced by players.

Limitations of the current research on relations between violent video game usage, aggression, social competence, and academic adjustment. Although there has been a great deal of research on the effects of violent video games, there are several limitations to the research. To date, no longitudinal work has been done examining the relation between violent video game exposure and aggression. Therefore, it is difficult to determine if violent video game exposure leads to higher levels of aggression, if more aggressive individuals seek out violent content, if the effect is bidirectional, or if there is some third variable such as parental supervision which better accounts for the relations found in some studies.

Some researchers contend that short-term increases in aggression after playing violent video games in laboratory experiments coupled with correlations between violent video game exposure and aggressiveness found in survey studies indicate that there is, in fact, a causal relation between violent video game exposure and aggression (Anderson &

Bushman, 2001; Anderson & Dill, 2000). However, others propose that some of the effects seen in experimental research may be an artifact of another weakness of many of the studies in the current literature, i.e., short violent video game exposure periods

(Sherry, 2001). That is, many of the experimental studies on violent video game effects only allow participants to play the video game for short periods of time, usually 20 minutes or less (for example, Bushman & Anderson, 2002; Bartholow, et al., 2005;

Schneider et al., 2004). In a meta-analysis by Sherry (2001), it was found that as play times increased there came a point where aggression levels actually decreased. Thus, it 22 has been proposed that these studies may be finding evidence for a general arousal caused by the games which fades after the games are no longer novel and interesting and that limited exposure time is a consistent limitation in the research literature.

Present Study

In summary, much research has focused on the relation between playing violent video games and aggressive behavior, but less has focused on social competence and academic adjustment. This research has arisen from the concern that exposure to violence in video games negatively effects children. One area that has not been examined is the relation of social video game play to children’s adjustment. It is likely that this is an important area to study as children are engaging in social video game play now more than ever in the past with recent advances in technology.

The first aim of the present study was to gather information on developmental and gender differences regarding social video game play of violent video games. Therefore, this study examined the differing rates of playing violent video games alone, with others present, and with others online across age and gender. It is was hypothesized that developmental trends would be similar to those found in studies of video game usage in general, with older children engaging in less video game play in each area than younger children. However, with the increased desire for social interaction in adolescence, it is possible that older children may engage in more social video game play than younger children. Additionally, consistent with previous research, I hypothesize that males will engage in more of each type of video game play than females, regardless of age.

The second aim of the present study was to examine the relation between violent video game play (alone and with others in-person or online), and aggression, social 23 competence, and academic adjustment. Based on previous research and the GAM, it was hypothesized that there would be a positive relation between time spent playing violent video games, both alone and with others, and levels of aggression. Regarding the relation between violent video game play, either alone or with others, and social competence, the lack of previous research into this area made it difficult to formulate a specific hypothesis as to what results would be found. On the one hand, it is possible that children who engage in high levels of violent video game play, in general, would have lower levels of social competence as violent video games reinforce children for engaging in socially incompetent behaviors (e.g., aggression) and they may have been more inclined to enact those behaviors. On the other hand, it is possible that the social interaction that occurs while playing violent video games with others helps children learn socially competent behaviors such as complimenting others for their success, despite the violent content of the video games. If this is the case, it would be likely that lower levels of social competence would be seen in children who play primarily alone rather than with others present. Regarding academic adjustment, it was hypothesized that, as in prior studies, a negative relation would exist between total time spent playing video games and levels of academic adjustment.

The final aim of the present study was to examine if gender and age moderated the relations between social video game play and the other variables of interest. Based on previous research, it was hypothesized that the relation between playing violent video games and adjustment would be stronger for younger than for older children. This is likely to be the case as children’s personality characteristics, such as aggressiveness and social competence, might become more resistant to change with age. Additionally, it was 24 hypothesized that exposure to video game violence would show a weaker relation to the adjustment variables for females as is found in most previous studies regarding violent video game content. Previous research has demonstrated that females, in general, show lower levels of aggression-related cognitions and behavior, possibly due to factors such as socialization or biological tendencies. 25

METHOD

Participants and Procedures

Five hundred and seven participants were recruited from 7th, 9th, and 11th grade

classrooms in a semi-rural, middle class community in Wood County, Ohio. One

participant’s data were excluded from the study due to patterned responses. Further, four

participants’ parents returned forms declining permission for their children to participate in the present study. In addition, 18 participants indicated being in the 10th grade which

placed them outside the original grade level parameters of the study. In order to maintain

the desired grouping, the data from these students were excluded as well. The final sample included 484 students, or approximately 95% of the intended sample. Table 1

shows data regarding the characteristics of the participants in each grade level. Each

grade produced data for 90-223 students. Participant age ranged from 12 to 17 years-old.

The majority of the participants were male (53.8%), Caucasian (79.3%), and indicated

that two parental figures lived in their home (70.6%).

In order to recruit participants, letters were sent to the parents of adolescents in

the selected classes of the schools where the data were gathered. The letter described the survey as being completed anonymously by the adolescents, indicated that the survey would be administered in a classroom setting, and discussed why the information being collected is important to teachers, parents, and researchers (see Appendix A). Because of the anonymity of respondents and the innocuous content of the survey, approval was granted by Bowling Green State University Human Subjects Review Board to have parents return a form to the school by a pre-determined date if they did not want their child to participate in the present study. At the time the survey was administered, 26 adolescent participants were presented with material describing the current study and were asked to complete forms providing their assent to participate. The information presented to the students informed them that completion of the survey was voluntary and that their responses were anonymous. Participants then completed the survey, which required approximately 45 minutes to one hour.

Overview of the Survey

The survey used in this study was part of a larger study of children’s media usage, and consisted of several sections. The first section consisted of three pages that were adapted from the Henry J. Kaiser Family Foundation study (Roberts et al., 2005).

Questions on these pages were aimed at collecting data regarding demographic characteristics of the participants and academic achievement self-report data.

Respondents were asked questions regarding their age, gender, grade level, racial or ethnic background, and average grades earned at school (see Appendix B). Participants also responded to questions regarding who resides in their home.

The next section of the survey was aimed at collecting data on participants’ aggressive and prosocial behavior. The subsequent section of the survey was aimed at collecting data regarding total video game play, social video game play, and playing specific types of games (i.e., first person shooters, sports games, strategy games, massive multiplayer online (MMO) games, or internet-based games) alone or with others in addition to data on the usage of online communication technologies while playing video games (i.e., chatting through typing or chatting via headset). The next scale participants completed was a measure of perceived social competence. The final section of the survey 27 was aimed at gathering data on participants’ perceptions of school (school bonding) and participation in school activities (school involvement).

Measures Used in the Present Study

Video game play items. Items regarding video game usage (see Appendix C) were modeled after the general format of the survey used by Roberts et al (2005). This scale prompted participants to, “Please tell us how many days each week you do the following things while playing video games.” Items on this scale were rated on a 5-point scale including the responses: never, once a week, a few times a week, most days, and every day. This section of the survey consisted of eight items which asked raters to indicate how often they play different types of video games in three different contexts: “by yourself,” “with another person who is in the room with you,” or “with someone online who is not in the room with you.” This section included three items regarding how often respondents play “First-Person Shooters” (games in which a player controls one character and engages in battles from a first-person perspective) in each context, three items regarding how often respondents play “strategy games” (games in which players control computer simulated armies or societies) in each context, and two items regarding how often respondents play “Massively Multiplayer Online Games” (MMO; games in which players interact with an online virtual world along with other players) either with “none of the other players in the room” or “at least one other player in the room.” (Only two items concerning MMO games were created as it is not possible to play this type of game completely alone.)

Responses to these items were used to create several measures of frequency of violent video game play in each context. Participants’ responses were examined to 28 determine the frequency with which they play the various violent video game types (first- person shooter, strategy, or MMO) alone, with others present, or with others online.

Participants’ responses to each of the eight items were coded into three groups (never, once a week/a few times a week, most days/every day). In order to create the scales that were used to examine violent video game play in each context a two-step process was followed. First, all items rating playing alone, across violent content (i.e., first-person shooter and strategy), were combined; all items rating playing with others present across violent content (i.e., first-person shooter, strategy, and MMO) were combined; and all items rating playing with others online across violent content (i.e., first-person shooter, strategy, and MMO) were combined. Next, the frequency of playing violent games in each context (i.e., never, once a week/a few times a week, most days/every day) was determined. This was done by finding the item with the highest frequency of play indicated and using this as the frequency rating for each context of play. For example, if a participant indicated that he or she never plays MMO games or strategy games with others present, but indicated that he or she plays first-person shooter games with others present most days/every day, the participant was coded into the most day/every day category with regard to frequency of playing violent video games alone. Thus, three scales were created: 1) frequency of playing violent video games alone; 2) frequency of playing violent video games with others present; and 3) frequency of playing violent video games with others online.

In addition to the above measures, a measure was created in order to examine participants’ total exposure to violent video games. This scale was created by first combining all items rating playing violent video games regardless of content (FPS, 29

MMO, or strategy. Next, the process described above was used to determine the highest frequency of play, regardless of content or context, which determined the overall frequency of playing violent video games. This process resulted in a scale rating participants’ overall frequency of violent video game play.

Internal consistencies were examined among the items on the video game play frequency subscales described above (e.g., how often respondents play strategy, FPS, and

MMO games with others present) to ensure that combining the items into the subscales described above reflecting context of play (i.e., alone, with others present, with others online) was advisable. Items regarding overall frequency of violent video game play were found to have an internal consistency of .88. Items regarding playing video games alone, with others present, and with others online were found to have internal consistencies of

.62, .68, and .78, respectively. Thus, it was decided that it would be appropriate to combine these items as discussed previously.

Assessing aggressive and prosocial behavior using the Direct and Indirect

Aggression Scales (DIAS; Bjorkqvist et al., 1992). How often a participant uses aggressive and prosocial behaviors was assessed using a modified version of the DIAS.

The DIAS was originally developed as a peer-nomination scale to rate both direct and indirect aggressive behaviors (Bjorqvist et al., 1992). The original form of the DIAS was found, across several samples, to have consistently strong internal consistencies ranging from .78 to .96 (Kaukiainen et al., 1999; Österman et al., 1999). Furthermore, the DIAS has been found to be similar to other self-report measures of aggression (Osterman et al.,

2004). The form of the scale in the present study was adapted from a self-report adaptation of the DIAS (Musher-Eizenman et al., 2004). Musher-Eizerman et al.’s 30 version of the measure included fewer items than the original DIAS but was found to have internal consistencies of .76 and .61 for direct and indirect forms of aggression, respectively. In the present study, aggressive behavior items showed an internal consistency alpha of .88 while prosocial behavior items showed an internal consistency alpha of .88. For the purpose of this study, the scale was adapted to a 5-point scale ranging from “never” to “very often.” On the original DIAS, children were shown pictures of their classmates and asked for each one, “What does he/she do when angry with another boy/girl in the class?” followed by several options such as, “call others names.” For each aggressive response, children were given five choices (0=never to

4=very often; Bjorkqvist et al., 1992). For the present study, this was modified to read

“Please tell us how often you do the following things when you are face-to-face with others…You call another person names face-to-face.” (The “face-to-face” instructions were included to distinguish between aggressive and prosocial behaviors engaged in when the respondent is with another person “face-to-face” versus the same behaviors engaged in while online via internet communication, which is the focus of a separate study). Response choices to these items were never, seldom, sometimes, quite often, and very often as on the DIAS. This scale included 20 items used to assess participants’ aggressive and prosocial behaviors (see Appendix D). Ten of the items on this scale assessed aggressive behaviors, with five items concerning direct aggression (e.g., “You yell at or argue with another person face-to face,” “You insult another person face-to- face) while the other five concerned indirect aggression (e.g., “When talking to someone face-to-face, you gossip about someone else you are angry at,” “When talking to someone face-to-face, you say bad things about someone else you have problems with”). 31

The remaining ten items assessed prosocial behaviors with five direct items (e.g., “You congratulate another person face-to-face,” “You cheer someone up face-to-face”) and five indirect items (e.g., “When talking to someone face-to-face, you say something nice about someone else,” “When talking to someone face-to-face, you compliment someone else”). It should be noted that items assessing physical aggression were removed as items on other scales within the survey were aimed at collecting data regarding aggression while using CMC, so it was decided the scales regarding CMC and in-person behavior should be similar.

Two subscales were created from the 20 items. The ten items regarding aggressive behavior were averaged to compute a subscale reflecting the degree to which respondents endorsed engaging in aggressive behaviors. And, the ten items regarding prosocial behavior were averaged to compute a subscale reflecting prosocial behavior.

Perceived competence. Items assessing domains of perceived competence were adapted from Harter’s Self Perception Profile for Children (SPPC; 1985). The specific domains of perceived competence include social competence, intimate relations competence, cognitive competence, and global self-worth. On the original SPPC, respondents were asked to rate how similar they are to a person being described. Original items consisted of a stem containing two opposed descriptions of children such as, “Some children find it hard to make friends but for other children it’s quite easy.” Respondents were given two choices on either side of each question allowing them to respond whether each description was “really true of me” or “sort of true of me.” Some have contended that this response pattern can be confusing for children completing the scale (Shelvin,

Adamson, & Collins, 2003). Thus the scale was redesigned (see Appendix E) providing 32 participants with the initial instruction, “Please tell us how you feel about the following statements.” Participants were then asked to respond to 14 statements such as, “Some kids feel that they are just as smart as others their age, but other kids don’t. Do you feel that you are as smart as other kids your age?” Four of these items addressed social competence (e.g., “Some kids have a lot of friends, but others don’t. Do you have a lot of friends?”), three items addressed intimate relations competence (e.g., “Some kids have a close friend they can share secrets with, but others don’t. Do you have a close friend you can share secrets with?”), and three items addressed cognitive competence (e.g., “Some kids do very well at their classwork, but others don’t. Do you do well at your classwork?). Response options were in the form of a 5-point scale from “always” to

“never.

Participants’ responses to these items were used to create three subscales.

Responses to the four items regarding social competence were averaged to create a perceived social competence subscale. Responses to the three items regarding intimate relations competence were averaged to create a perceived intimate relations subscale.

Responses to the three items regarding cognitive competence were averaged to create a perceived cognitive competence scale.

Previous research has reported alpha coefficients for internal reliability ranging from .72 to .88 across the subscales in the SPPC (Harter, 1985). In the present study, the alpha coefficients for social competence, intimate relations competence, and cognitive competence items were .73, .61, and .73 respectively. With regard to validity, Harter

(1982, 1985) has reported correlations with other ratings of competence ranging from .46 to .62 for each subscale. 33

Academic adjustment. There were four measures of academic adjustment. First, as described in the previous paragraph, we included the perceived cognitive competence subscale of perceived competence. Second, respondents were asked to indicate, “What grades do you usually get?” followed by nine responses from 1 = “mostly A’s” to 9 =

“mostly F’s” (see Appendix B). Third, students were presented with two scales: academic involvement and negative attitudes toward school (Appendix F). The first scale, assessing academic involvement, provided students with the prompt, “Have you done any of the following in the past year.” Respondents then indicated “yes” or “no” on nine items such as “been a member of a school sports team.” Responses are summed to create a scale score. This scale was adapted from Dubow, Kausch, Blum, Reed, and Bush’s (1989) revision of the Health and Daily Living Form (Moos, Cronkite, Billings, & Finney,

1986). The second scale, assessing negative attitudes toward school, provided students with the prompt, “Which of the following is most true for you in school?” followed by three items with stems such as, “I care how I do in school.” These items were rated on a

5-point scale ranging from “always” to “never,” and are averaged to create a scale score.

This scale was derived from Hawkins, Guo, Hill, Battin-Pearson, and Abbot’s (1996) scale rating negative attitudes towards school, which was found to have an internal consistency alpha of .68. In the present study, items regarding negative attitudes towards school were found to have an internal consistency alpha of .67. 34

RESULTS

Overview of Analyses

Preliminary analyses were computed to determine if demographic variables needed to be controlled throughout later analyses. A series of chi-square tests were computed to examine the relation between participant race and family structure and the major study variables pertaining to video game play habits. MANOVAs were conducted to examine the relation between participant race and family status and the study variables pertaining to aggressive and prosocial behavior, social competence, and academic adjustment. As will be discussed later, it was found that family status was significantly related to aggressive and prosocial behavior and academic adjustment. Thus, family status was included as a covariate in analyses involving these dependent measures.

Hypothesis one examines whether developmental differences exist in video game play behavior. In order to examine this hypothesis, frequencies, means and standard deviations of self-reported video game play were examined. Chi-square tests were computed to determine if there were differences in play behaviors based on gender or age.

Hypothesis two examines possible relations between frequency of video game play in the various contexts (i.e., alone, with others present, with others online), total violent video game play, or primary context of video game play and aggressive and prosocial behavior, social competence, or academic adjustment. To examine this hypothesis, a series of MANOVAs and MANCOVAs were computed. MANOVAs examined the relation between the independent variables regarding video game usage and the dependent variables regarding social competence. MANCOVAs were computed with 35 the independent variables regarding video game usage and the dependent variables of aggressive and prosocial behavior and academic adjustment, with family status entered as a covariate.

Hypothesis three examines gender and grade level differences in the relations examined in hypothesis two. To examine this hypothesis, the MANOVAs and

MANCOVAs computed in hypothesis two were computed again first with gender or grade level and the play variable x gender, or grade level, entered as independent variables. The key issue of interest was the interactions of frequency of play x gender and frequency of play x grade. I was specifically interested in determining if the frequency of play variables showed relations to the major study variables (e.g., aggressive behavior) after the relations to gender and grade level were accounted for. In order to do this, each

MANCOVA and MANOVA was computed using a hierarchical method first accounting for the total parents covariate (if necessary), followed by the gender or grade variable, followed by the violent video game play variable, and finally the gender/grade level x violent video game play interaction was entered. This method was used in order to determine if any effects of violent video game play on adjustment found in hypothesis two remain after first accounting for the main effects of gender or grade, and then examining whether any main effects of violent video game play are further moderated by gender or grade.

Preliminary Analyses

A series of analyses were computed to determine if there were race and family structure differences in the major study variables. Chi-square tests were computed to examine the relation between the dependent variables of violent video game play (in 36 three contexts: alone, with others present, with others online) or overall frequency of violent video game play and the independent variables of race (Caucasian vs. Non-

Caucasian) and family structure (one parent vs. two parents in the home). For this study, family status was determined by examining the two demographic items asking students whether their father and mother were currently living in the home. It should be noted that this measure cannot specify what the relation of the “father” or “mother” indicated is to the participant. For example, it is possible that participants have adults living in their home that are not biologically related to them but are seen by the participant as a parental figure, so it is understood that this variable is a crude index of parents in the home. No significant relations were found between total parents in the home and violent video game play in each context or total violent video game play.

Next, a MANOVA was computed to examine the relation between the dependent variables of aggressive behavior and prosocial behavior and the independent variables of race and family structure. No significant effects were found for race. But, a significant multivariate effect was found for number of parents in the home, F (2, 467) =6.00, p <

.01. Univariate ANOVAs revealed a significant effect for parents in the home on aggressive behavior, F (1, 468) = 10.886, p < .01. Specifically, participants who indicated living in a home with one parent showed higher levels of aggressive behavior compared to participants with two parents in the home. A second MANOVA was computed to examine the relation between the dependent variables of social competence and intimate relations competence and the independent variables of race and family structure. No significant effects were found for family structure. There was a significant multivariate effect for race, F (2, 466) = 5.103, p < .01. Univariate ANOVAs revealed a significant 37 effect for race on intimate relations competence, F (1, 467) = 5.02, p < .01. Specifically, non-Caucasian participants were found to have lower self-ratings of intimate relations competence than Caucasian participants. A third MANOVA was computed to examine the relation between the dependent variables of cognitive competence, GPA, academic involvement, and negative attitudes towards school and the independent variables of race and family structure. No significant effects were found for race. A significant multivariate effect was found for family structure, F (4, 461) = 6.47, p <.01. Univariate

ANOVAs revealed significant effects for family structure on cognitive competence, F

(1,464) = 5.659, p < .05, GPA, F (1,464) = 22.29, p < .01, and negative attitudes about school, F (1, 464) = 12.25, p <.01. Specifically, participants with one parent in the home showed lower levels of cognitive competence, more negative attitudes about school, and lower GPA than participants with two parents in the home.

In summary, although significant relations were found between race and intimate relations competence and frequency of playing with others present, no consistent pattern of relations was found. This being the case, I decided not to include race as a covariate.

Family structure, on the other hand, was found to be significantly related to aggressive behavior, GPA, and negative attitudes about school with a consistent pattern of relations.

Specifically, having one parent in the home was related to poorer outcomes. Due to this pattern, family structure was included as a covariate for analyses involving aggressive behavior and academic adjustment.

Finally, analyses were computed to determine if participants could be separated into groups based on the context in which they primarily play violent video games (i.e., primarily playing alone, primarily playing with others present, or primarily playing with 38 others online). A participant was determined to have a primary context of play if he or she indicated a higher level or play in one context than both of the other contexts.

Therefore, if a participant indicated playing alone most days/every day and playing with others who are present or online once a week/a few times a week, the participant would be coded as primarily playing alone. On the other hand if a participant indicated playing violent video games once a week/a few time a week in all contexts, he or she was not coded into any primary group. Using this process, 94 participants (approximately 19% of the sample) were able to be coded into a primary context of play. Of this group, 61

(approximately 12% of the sample) indicated primarily playing alone, 25 (approximately

5% of the sample) indicated primarily playing with others who were present, and eight

(approximately 2% of the sample) indicated primarily playing with others online.

Furthermore, 68% of these participants were male while 32% were female. Based on the fact that I was able to divide some participants into primary context of play groups; this variable was examined in later analyses.

Hypothesis 1: Developmental Differences in Video Game Play

Frequencies, means, and standard deviations of video game play, specifically total violent video game play and playing violent video games, regardless of content, in the contexts of being alone, with others present, or with others online, were examined (See

Table 2.) Approximately 38% of participants indicated that they never play violent video games; 39.8% indicated that they play once a week/a few times a week; and 21.9% indicated that they play most days/every day. Responses further indicated that 44.5% of participants never play violent video games alone, 38.0% play alone once a week/a few times a week, and 17.5% play alone most days/everyday. Regarding playing violent 39 video games with others present, 50.3% of respondents indicated that they never play with others who are present; 38.4% indicated that they play with others who are present once a week/a few times a week; and 11.3% indicated that they play with others present most days/everyday. Finally, the majority (71%) of respondents indicated that they never play violent video games with others who are online; 18.2% indicated that they play with others online once a week/a few times a week; and 10.8% indicated that they play with others online most days/every day.

Next, a series of chi-square tests were computed to examine the relation between the frequency of violent video game play in each context and gender, and the relation between the frequency of violent video game play in each context and grade level. A significant relation was found between gender and total amount of violent video game play, χ2 (2, N=479) = 153.05, p < .01. Specifically, male participants were more likely to

indicate playing violent video games most days/every day than female participants (36%

and 5%, respectively; see Table 2 for descriptive statistics). A significant relation was

also found between gender and time spent playing video games alone, χ2 (2, N=478) =

143.31, p < .01. Again, males were more likely than females to indicate playing violent

video games alone most days/every day (28% and 5%, respectively; see Table 2 for

descriptive statistics). When examining gender and amount of video game play with

others who were present, a significant relation was found, χ2 (2, N=478) = 129.08, p <

.01. Specifically, males were more likely than females to indicate playing violent video games with others who were present most days/every day, 19% compared to 2% (see

Table 2 for descriptive statistics). Finally, a significant relation was also found between gender and amount of video game play with others online, χ2 (2, N=478) = 80.19, p <.01. 40

Specifically, males were more likely than females to indicate playing video games online with others most days/every day, 19% compared to 2% (see Table 2 for descriptive statistics).

In terms of grade level differences in video game play behaviors (see Table 3), a significant relation was found between grade level and total amount of violent video game play, χ2 (4, N = 480) = 10.36, p < .05. Results indicated that 7th grade (32%)

participants were most likely to indicate playing most days/every day, with 9th and 11th graders (23% and 16%, respectively) less likely to indicate this frequency of play (see

Table 3 for descriptive statistics). A significant relation was also found between grade level and frequency of playing violent video games alone, χ2 (4, N=479) = 10.35, p < .05.

Specifically, 7th graders (26%) were more likely to indicate playing alone most

days/every day than 9th graders (19%) who were more likely to indicate playing alone

than 11th graders (11%; see Table 3 for descriptive statistics). A significant relation was

also found for the relation between grade level and playing violent video games with

another person who was present, χ2 (4, N = 479) = 10.04, p < .05. Specifically, 7th and 9th

graders (16% and 14%, respectively) were more likely to indicate playing with others

who were present most days/every day more than 11th graders (5%) (see Table 3 for descriptive statistics). Finally, no significant relation was found between grade level and playing video games with others online (see Table 3 for descriptive statistics).

As mentioned previously, I was able to code 94 participants into categories based on their primary context of play. Chi-square tests were computed to determine if a relation exists between gender or grade and primary context of play for these participants. 41

No significant relations were found between gender or grade level and primary context of play.

Hypothesis 2: Relation between the Frequency of Video Game Play and Aggressive and

Prosocial Behavior, Social Competence, and Academic Adjustment

Video game play and behavioral adjustment. Five MANCOVAs were computed to examine the relation between the dependent variables of aggressive behavior and prosocial behavior and the independent variables of: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play. For these analyses, family status was entered as a covariate. Results for the MANOVAs and MANCOVAS computed in hypothesis two are presented in Tables 4 (frequency of playing alone, with others present, and with others online) and 5 (total violent video game play and primary context of play).

There was a significant multivariate effect for the overall frequency of violent video game play, F (4, 948) = 8.87, p < .01. Follow-up univariate ANCOVAs revealed a significant effect for overall frequency of violent video game play for aggressive behavior, F (2, 474) = 5.73, p < .01, and prosocial behavior, F (2, 474) = 10.41, p < .01.

Specifically, participants who indicated higher amounts of violent video game play showed higher levels of aggressive behavior and lower levels of prosocial behavior. The second MANCOVA revealed a significant multivariate effect for frequency of playing violent video games alone, F (4, 946) = 7.99, p < .01. Univariate ANCOVAs revealed significant effects for frequency of playing alone for aggressive behavior, F (2, 473) =

6.21, p < .01, and for prosocial behavior, F (2, 473) = 8.49, p < .01. Again, participants 42 who indicated higher frequency of playing violent video games alone showed higher levels of aggressive behavior and lower levels of prosocial behavior. The third

MANCOVA resulted in a significant multivariate effect for playing violent video games with another person who was present, F (4, 946) = 6.49, p < .01. Follow-up univariate

ANCOVAs revealed a significant effect for frequency of playing with others present for aggressive behavior, F (2, 473) = 5.25, p < .01, and for prosocial behavior, F (2, 473) =

6.58, p < .01. As before, higher frequency of playing violent video games with others who are present was related to higher levels of aggressive behavior and lower levels of prosocial behavior. The fourth MANCOVA resulted in a significant multivariate effect for playing violent video games with others online, F (4, 948) = 6.21, p < .01. Follow-up univariate ANCOVAs revealed a significant main effect of playing with others online for prosocial behavior, F (2, 474) = 11.11, p < .01. Specifically, participants who played video games with others online more frequently showed lower levels of prosocial behavior. No significant effects were found for primary context of play.

Video game play and social adjustment. Next, five MANOVAs (see Tables 4 and

5) were computed to examine the relation between the dependent variables of social competence and intimate relations competence and the independent variables of: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play. There was a significant multivariate effect for overall frequency of violent video game play, F (4,

952) = 2.43, p < .05. Follow-up univariate ANOVAs revealed a significant effect of total violent video game play for social competence, F (2,476) = 3.80, p < .05, and intimate 43 relations competence, F (2, 476) = 3.93, p < .05. Specifically, participants who indicated higher amounts of violent video game play displayed lower levels of social competence and intimate relations competence. No significant multivariate effects were revealed by

MANOVAs computed regarding frequency of playing violent video games alone, with others who were present, with others online, or for primary context of play.

Video game play and academic adjustment. Finally, five MANCOVAs (see

Tables 4 and 5) were computed to examine the relation between the dependent variables of cognitive competence, school involvement, negative attitudes towards school, and general academic achievement and the independent variables of: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play. There was a significant multivariate effect for overall frequency of violent video game play, F (8, 938) = 5.61, p < .01.

Follow-up univariate ANCOVAs revealed a significant effect of overall frequency of violent video game play for GPA, F (2, 471) = 8.16, p < .01, school involvement, F (2,

471) = 8.48, p < .01, and negative attitudes towards school, F (2, 471) = 11.52, p < .01.

Specifically, higher levels of total violent video game play were related to lower GPA, lower levels of school involvement, and more negative attitudes towards school. The second MANCOVA revealed a significant multivariate effect for frequency of violent video game play alone, F (8, 936) = 4.94, p < .01. Follow-up univariate ANCOVAs revealed significant effects of frequency of violent video game play alone for GPA, F (2,

470) = 7.15, p < .01, school involvement, F (2, 470) = 7.54, p < .01, and negative attitudes towards school, F (2, 470) = 8.49, p < .01. Similar to the previous pattern, 44 higher frequencies of violent video game play alone were related to lower GPAs, lower levels of school involvement, and more negative attitudes towards school. The third

MANCOVA resulted in a significant multivariate effect for frequency of playing violent video games with others present, F (8, 936) = 5.52, p < .01. Follow-up univariate

ANCOVAs revealed significant effects of frequency of violent video game play with others present for GPA, F (2, 470) = 11.92, p < .01, school involvement, F (2,470) =

6.63, p < .01, and negative attitudes towards school, F (2, 470) = 11.73, p < .01. Again, higher frequencies of violent video game play with others who were present was related to lower GPAs, lower levels of school involvement, and more negative attitudes towards school. The fourth MANCOVA revealed a significant multivariate effect for frequency of playing violent video games with others online, F (8, 936) = 3.51, p < .01. Follow-up univariate ANCOVAs revealed a significant effect of frequency of playing violent video games with others online for negative attitudes towards school, F (2, 470) = 8.50, p < .01.

In this case, higher frequencies of violent video game play with others online was only related to more negative attitudes towards school. Finally, there was no significant multivariate effect was found for primary context of play.

Summary of results for Hypothesis 2. In summary, violent video game exposure in general and exposure in the three contexts (alone, with others present, with others online) were related to negative adjustment in multiple areas. Regarding aggressive and prosocial behavior, higher amounts of overall video game play and game play alone or with others present were related to higher levels of aggression. In addition, higher amounts of overall video game play and video game play in all three contexts were related to lower levels of prosocial behavior. Regarding social adjustment, higher frequencies of overall violent 45 video game play and video game play alone were related to lower levels of social competence and intimate relations competence. However, playing with others present was not related to social adjustment while playing with others online was only related to ratings of social competence. Regarding academic adjustment, higher frequencies of overall violent video game play and play in all three contexts were related to less school involvement, more negative attitudes about school, and lower GPAs. Only playing with others present was related to cognitive competence, in this case higher frequencies of playing with others present was related to lower ratings of cognitive competence. Finally, it was notable that students’ levels of adjustment were not related to the primary context in which they played.

Hypothesis 3: Gender and Grade Level as Moderators of the Relation between

Frequency of Play and Adjustment

To determine if gender and grade level moderated the relation between frequency of play and adjustment, MANCOVAs and MANOVAs were computed as described in the Overview of Analyses section. Recall that variables were entered in the following hierarchical steps: 1) covariates; 2) main effect of gender or grade; 3) video game play variable; and 4) the interaction of video game play frequency with gender or grade. This order of entry examines whether video game play is related to adjustment after having accounted for the covariates and gender or grade, and then whether gender or grade moderates the relation between video game play and adjustment. Results for these analyses are summarized in Table 6, containing information regarding the MANOVAs and MANCOVAs examining gender as a moderator; and Table 7, containing information regarding the MANOVAs and MANCOVAs examining grade as a moderator. Due to the 46 conservative nature of the analyses (i.e., controlling for covariates, if necessary, gender, and/or grade before examining the contributions of video game play and the interaction of video game play with gender/grade), I decided to include findings that indicated a trend toward significance (p < .10).

Results for aggressive and prosocial behavior, with gender included as an independent variable. Five MANCOVAs were computed to examine the relation between aggressive and prosocial behavior and the independent variables (covariate, gender, one of the five video game usage variables, and the interaction of gender x video game usage). Recall that the five video game frequency variables were: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play. For three of the five video game usage analyses, Table 6 shows that, after controlling for the covariate and gender, frequency of play had significant multivariate effects. Specifically, higher levels of playing violent video games overall, alone, and with others present were related to higher levels of aggressive behavior. Additionally, playing violent video games with others online was marginally related to aggressive behavior. It is notable that, in most cases where a significant multivariate effect was found, the univariate effect was only significant for aggressive behavior but not for prosocial behavior as in prior analyses. However, higher frequencies of playing with others online were related to lower levels of prosocial behavior. In addition, frequency of playing alone showed a similar trend toward significance. In addition, Table 6 shows that gender did not moderate the main effects when it was entered in the final step of the MANCOVA. 47

Results for aggressive and prosocial behavior, with grade included as an independent variable. Next, five MANCOVAs were computed to examine the relation between aggressive and prosocial behavior and the independent variables (covariate, grade, one of the five video game usage variables, and the interaction of grade x video game usage). Recall that the five video game usage variables were: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play. For four of the five video game usage analyses, Table 7 shows that, after controlling for the covariate and grade, frequency of play showed significant multivariate effects. Specifically, overall violent video game play, game play alone, and game play with others present was significantly related to both aggressive and prosocial behavior. In addition, violent video game play with others online was significant only for prosocial behavior. Table 7 also shows that grade only moderated the main effects when it was entered in the final step of the MANCOVA regarding playing with others present. Further examination of the results revealed that 9th graders who reported playing violent video games with others present most days/every day had higher levels of aggressive behavior than 7th and 11th graders who reported the

same frequency of playing with others.

Summary of results for aggressive and prosocial behavior. Results regarding

aggressive and prosocial behavior computed in Hypothesis 3 were similar to those in

Hypothesis 2 when gender and grade main effects and interactions were not examined.

However, two differences were found. When gender was entered into the MANCOVAs,

it was found that the video game usage variables no longer showed as strong relations to 48 prosocial behavior. The other difference was found when grade was included in the

MANCOVA regarding playing with others present. In this case, the relation between playing with others present and aggressive behavior was no longer significant. It is also notable that only one significant multivariate effect was found for the interaction terms in the MANCOVAs; i.e., gender and grade did not moderate the relation between video game play and behavioral adjustment in most cases.

Results for social adjustment with gender entered as an independent variable.

Five MANOVAs were next computed to examine the relation between the dependent variables of social competence and intimate relations competence and the independent variables (covariate, gender, one of the five video game usage variables, and the interaction of gender x video game usage). Recall that the five video game usage variables were: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play.

As can be seen in Table 6, after accounting for gender differences in behavior, no significant multivariate effects were found for the frequency of play variables or primary context variable in any of these five MANOVAs. However, the effects for playing video games were marginally significant for the relation between violent video game play overall, alone, and with others online and social competence. In addition, a multivariate effect was found for the interaction term of gender x frequency of play with others present. Specifically, the interaction term was found to be significantly related to intimate relations competence, F (2, 477) = 4.52, p < .05. Figure 1 shows only small differences in intimate relations competence were reported for males based on frequency of violent 49 video game play with others. Females on the other hand reported lower levels of intimate relations competence only if they also reported playing violent video games with others present most days/every day. No other gender x frequency of play interaction terms had significant multivariate effects.

Results for social adjustment, with grade included as an independent variable.

Next, five MANOVAs were computed to examine the relation between the dependent variables of social competence and intimate relations competence and the independent variables (covariate, grade, one of the five video game usage variables, and the interaction of grade x video game usage). Recall that the five video game usage variables were: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play.

As can be seen in Table 7, only overall frequency of violent video game play showed a significant multivariate effect for the social adjustment variables. Specifically, overall frequency of violent video game play was significantly related to both social competence and intimate relations competence. Additionally, playing with others present was significantly related to intimate relations competence and playing with others online was significantly related to social competence. In these relations, higher frequencies of overall violent video game play were related to lower levels of social competence and intimate relations competence. In addition, frequency of playing violent video games alone was related to both social and intimate relations competence. Table 7 also shows that grade did not moderate the main effects when it was entered in the final step of the

MANOVAs. 50

Summary of results for social adjustment. Adding the gender and grade terms to the MANOVAs generally eliminated the significant effects found in Hypothesis 2.

However, the relation between overall frequency of violent video game play remained significant for both social competence and intimate relations competence. Additionally, there were trends toward significance that were consistent with the findings for video game play found in Hypothesis 2. Only the gender x frequency of play with others present interaction term was found to be significant. In this case, it was found that female participants who played with others present most days/every day reported lower levels of intimate relations competence.

Results for academic adjustment, with gender included as an independent variable. Five MANCOVAs were then computed to examine the relation between the dependent variables of cognitive competence, school involvement, negative attitudes towards school, and general academic achievement (GPA) and the independent variables

(covariate, gender, one of the video game usage variables, and the interaction of gender x video game usage). Recall that the video game usage variables were: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play. As shown in Table 6, only frequency of violent video game play with others present showed a significant multivariate effect.

Specifically, higher frequencies of violent video game play with others present was related to more negative attitudes towards school and lower GPAs. Marginally significant relations were found between overall frequency of violent video game play and frequency of violent video game play alone and negative attitudes towards school and GPA and 51 between violent video game play with others present and cognitive competence. Higher frequency of play, in these cases, was related to poorer adjustment in the target areas. In addition, Table 6 also shows that gender did not moderate the main effects when it was entered in the final step of the MANCOVAs.

Results for academic adjustment, with grade included as an independent variable.

Finally, Five MANCOVAs were computed to examine the relation between the dependent variables of cognitive competence, school involvement, negative attitudes towards school, and general academic achievement (GPA) and the independent variables

(covariate, grade, one of the video game usage variables, and the interaction of grade x video game usage). Recall that the five video game usage variables were: 1) overall frequency of violent video game play; 2) frequency of violent video game play alone; 3) frequency of violent video game play with others present; 4) frequency of violent video game play with others online; and 5) primary context of play. For four of the five video game usage analyses, Table 7 shows that even after the covariate and grade were entered in the first two steps, video game usage showed significant multivariate effects.

Specifically, higher frequencies of overall violent video game play, game play alone, and game play with others present were related to lower school involvement, more negative attitudes towards school, and lower GPAs. In addition, higher frequencies of violent video game play with others online was related to more negative attitudes towards school.

Marginally significant relations were found between frequency of play with others present and cognitive competence and frequency of play online and school involvement and GPA. In these cases, higher frequencies of play were related to poorer adjustment.

As can also be seen in Table 7, grade did not moderate the main effects when it was 52 entered in the final step for four of the five MANCOVAs. However, a significant grade x primary context of play interaction was found. Specifically, this interaction term was significantly related to ratings of cognitive competence, F (4, 93) =3.02, p < .01. Figure 2 shows that 7th graders who played primarily with others present, 9th graders who played

primarily with others present or others online, and 11th graders who primarily played alone tended to provide lower ratings of cognitive competence.

Summary of results for academic adjustment. When gender was included in the

MANCOVAs to examine Hypothesis 3, overall frequency of violent video game play, frequency of violent video game play alone, and frequency of violent video game play online were no longer significant at the .01 and .05 levels. On the other hand, frequency of play with others remained significant for negative attitudes towards school and GPA but was no longer significant for school involvement or cognitive competence. There were trends toward significance for some of the relations for overall frequency of violent video game play, frequency of play alone, and frequency of play with others. No significant relations were found for the gender x frequency of play or gender x primary context of play interactions. When grade was included in the MANCOVAs, the relations were relatively similar to those found in Hypothesis 2. However, it was only at the .10 significance level that frequency of play with others present was significantly related to cognitive competence and frequency of play online was related to school involvement and GPA. A significant effect was only found for the grade x primary context of play interaction but no other interaction terms. Further analysis indicated that lower ratings of cognitive competence were found for 7th graders who played primarily with others 53 present, 9th graders who played primarily with others present or others online, and 11th

graders who primarily played alone. 54

DISCUSSION

The present study was conducted to examine how often children play video games alone, with others present, or with others online and how these play behaviors may relate to aggressive and prosocial behavior, social competence, and academic adjustment. Self report data were gathered from 7th, 9th, and 11th graders regarding their weekly video

game play frequency alone, with others present, and with others online.

Hypothesis 1: Developmental and Gender Differences in Video Game Play

As hypothesized, the results of the present study indicate that the majority (over

60%) of children in the sample play violent video games. These results are similar to those of Roberts et al. (2005), who reported that the majority of their sample played violent video games, with 52% reporting they had played within 24 hours of the data collection. It was also found that 56% of the children in the sample played alone, 50% of

the children played with others who were present, and less than 30% played with others

online at least once per week. These findings provide new information to this field of

study. Although prior studies have examined how often children play video games in

general (e.g., Roberts et al., 2005) or examined the demographic characteristics of

persons who play a specific game (e.g., Griffiths et al., 2004), no prior research has

gathered data on the context (i.e., alone, with others present, with others online) in which

children play video games. The current study reveals that children are most likely to play

violent video games alone, followed by playing with others present, while they play with

others online much less than in the other two contexts. It is possible that children play

violent video game s online much less than the other two contexts because it is simply less popular. Another possibility is that access to the necessary equipment and internet 55 service to play games online serves as a barrier to playing in this context. A third possibility is that parents are wary of their children playing video games online and therefore restrict access to this context.

As hypothesized, there were gender differences in violent video game play habits.

Specifically, males were much more likely than females to play violent video games most days/every day. Males were also more likely than females to indicate playing alone, with others present, or with others online most days/every day. These results are similar to those found in prior research. For example, Roberts et al. (2005) found that males were more likely to spend extended periods of time playing video games and that they were more likely to play violent video games than females. Additionally, the results support prior findings that males tend to be disproportionately represented when sampling the population of players for a particular game or gaming event. For example, Jansz and

Tanis (2007) found that 98% of the players of an online FPS game were males. Similarly,

Jansz and Martens (2005) found that 95% of the attendees at a LAN event were male.

Overall, these results further support previous research indicating that males are more likely to play violent video games than females, regardless of context. Thus, if there are negative outcomes related to violent video game play, males might be more likely to experience these negative outcomes as they have more exposure to the video game violence.

Grade level was also found to be significantly related to several violent video game play variables, as hypothesized. Results of the present study showed that 7th graders

were more likely to play violent video games most days/every day than 9th and 11th

graders. In addition, 7th graders were significantly more likely to report playing violent 56 video games alone most days/every day than 9th graders, who were significantly more

likely to do so than 11th graders. It was also found that 7th and 9th graders were both more

likely to play violent video games with others present most days/every day than 11th graders. Contrary my hypothesis, there was no significant relation between grade and violent video game play online. In general, the patterns of play found in the present study are similar to those found by Roberts et al (2005). Specifically, younger children tend to spend more time playing violent video games than older children and children’s time playing violent video games as they get older decreases. Interestingly, children in each grade were equally likely to play violent video games online. First, note that the frequency of playing games online is lower than playing games in other contexts. Thus, it is possible that this pattern of results has to do with the need for an internet connection and necessary equipment (e.g., a video game system that can connect to the internet) restricting who has access to this context of play. The lack of grade differences in playing video games online might also reflect that there is some characteristic of online play, such as excitement, that makes it less likely for time spent playing in this context to decrease. Another possibility is that there is some characteristic of those who enjoy playing online that makes it more likely that they will maintain the amount of time spent playing games online. It is also notable that no relation was found between age or gender and primary context of play.

Hypotheses 2 & 3: Relation between the Frequency of Violent Video Game Play and

Aggressive and Prosocial Behavior, Social Adjustment, and Academic Adjustment

Violent video game play and aggressive and prosocial behavior. Analyses conducted regarding hypothesis two revealed, as predicted, a significant relation between 57 frequency of violent video game play overall, violent video game play alone, and violent video game play with others present, and aggressive and prosocial behavior. Higher frequencies of play in each of these contexts was found to be significantly related to higher levels of aggressive behavior and lower levels of prosocial behavior. Frequency of violent video game play with others online was significantly related to lower levels of prosocial behavior but was not significantly related to aggressive behavior. Overall, these results are similar to what would be expected based on the GAM and previous research.

For example, multiple studies have found relations between increases in violent video game play, higher levels of aggressive behavior, and lower levels of prosocial behavior

(Anderson & Bushman, 2001; Anderson & Dill, 2001; Funk et al., 2003). Specifically, it appears that time spent playing violent video games, rather than time spent playing in a specific context, is related to higher levels of aggressive behavior and lower levels of prosocial behavior. The GAM proposes that this relation exists because children with higher frequencies of violent video game play are exposed to violent and antisocial behaviors in the video games they are playing. This exposure would theoretically provide the children with repeated chances to learn aggressive behaviors and antisocial solutions to problems. The GAM also proposes that exposure to violent video game content reinforces aggressive cognitions and aggressive beliefs (e.g., “any behavior that is bothersome to me must have been done to bother me and not on accident,” “If someone wrongs me I should retaliate with aggression”). Furthermore, exposure to violent video game content may lead to desensitization to violence through viewing scenes of violent behavior repeatedly. Additionally, as aggressive behavior increases, it is less likely that children will enact prosocial behaviors or prosocial solutions to problems. 58

It is interesting that only decreased levels of prosocial behavior were found to be related to violent video game play online with no significant increases in aggressive behavior. Although this result is somewhat contrary to what one would expect to find based on the GAM, it is supported by some previous research. For example, Williams and Skoric (2005) found no increases in aggressive behavior after having participants plays Asheron’s Call 2 for a month. The results are also consistent with previous research by Lo, Wang, and Fang (2005), who found decreased levels of social functioning and increased levels of social anxiety as time spent playing online video games increased. It is possible that violent video game play online is not as detrimental with regard to aggressive behavior. Rather, violent video game play online may result in difficulties using prosocial behaviors. It is also possible that there is some factor in playing with others online (e.g., that social contact is mediated by a computer interface) that feels like social interaction to players but does not reinforce prosocial behaviors that are useful in face-to-face interactions.

In general, these results provide support for a relation between increased frequency of violent video game play and problematic behavior. They also seem to support the idea that it is total exposure to video game violence that is related to poor behavioral adjustment rather than the context in which the exposure occurs. This is further supported by the fact that no relation was found between primary context of play and aggressive or prosocial behavior.

In hypothesis three, further examination of the data was conducted to determine if the relation between violent video game play and aggressive and prosocial video game play was moderated by grade level or gender. In general, gender did not act as a 59 moderator. That is, frequency of violent video game play, overall and in each context, remained significantly, or marginally, related to aggressive behavior. However, only playing with others online and playing alone were significantly, or marginally, related to prosocial behavior. Grade, on the other hand, was found to moderate the relation between playing with others present and aggressive and prosocial behavior, with higher levels of aggressive behavior found for 9th graders who reported playing in this context most

days/every day compared to the other grades. Overall, gender and grade generally did not

act as moderators of the relation between violent video game play and aggressive and

prosocial behavior in most cases. In other words, playing violent video games appears to

be related to negative outcomes for participants of any age or either gender.

Violent video game play and social adjustment. Analyses conducted in hypothesis two revealed a significant relation between frequency of violent video game play overall and lower levels of social and intimate relations competence, as predicted. However, contrary to what was expected violent video game play alone, with others present, with others online, and primary context of play were not found to be significantly related to social adjustment. These findings are consistent with previous research which found relations between violent video game play and difficulties with social competence

(Barthalow et al., 2005; Funk et al., 2003; Lo, Wang, & Fang, 2005; Wiegman & van

Schie, 1998). Therefore, the evidence gathered in this study provides some support for the assertion that playing violent video games is related to poorer social functioning.

In hypothesis three, gender and grade level were added to the analyses conducted in hypothesis two to determine if they moderated the relations found. In general, when gender was added to the analyses, frequency of violent video game play retained a similar 60 pattern of marginal significance. Gender was found to significantly moderate the relation between playing violent video games with others and intimate relations competence.

Specifically, females, but not males, who indicated that they played violent video games with others present showed lower levels of intimate relations competence. Grade level was not found to moderate the relation between violent video game play and social competence as the same pattern of significance from hypothesis two was maintained.

Overall, these results indicate that the relation between violent video game play and decreases in social adjustment are not, in general, moderated by grade level or gender.

The GAM suggests that these decreases in social adjustment are related to children learning poor solutions to social problems and observing models of poor social interaction. Another possibility is that children are learning antisocial or hostile ways to engage in social interactions by observing this type of interaction in a video game. It may also be that children learn to mistrust others in video games, as there is often a high level of intrigue and social conflict in video games, and this mistrust of others transfers to face- to-face interactions. Children who play violent video games frequently may also learn to pay more attention to social signals that indicate hostility or misinterpret social cues as more hostile than they really are. If this is the case, it could lead to children being more reserved or confrontational in social situations. It is also possible that children who spend more time playing video games spend less time interacting with peers, resulting in fewer chances to learn and apply positive social skills. In any case, children who spend a great deal of time playing violent video games may have learned that they are not as adept at social interactions and report lower feelings of social competence. 61

Violent video game play and academic adjustment. Analyses in hypothesis two revealed a significant relation between violent video game play overall, alone, with others present, and with others online and academic adjustment. Specifically, higher levels of overall play, play alone, and play with others present were significantly related to lower

GPA and school involvement and more negative attitudes toward school. Higher frequencies of violent video game play online were only related to more negative attitudes towards school. As in prior analyses, no relation was found between primary context of play and adjustment. Also no relations were found between frequency of violent video game play, or game play in specific contexts, and cognitive competence.

Consistent with the predicted results, frequency of violent video game play seems to be related to negative school adjustment. These results are consistent with prior research that has found negative relations between violent video game play and GPA and

SAT scores (Anand, 2007; Anderson & Dill, 2001; Gentile et al., 2004). The findings regarding negative attitudes towards school are also consistent with research by Gentile et al. (2004) which showed increases in conflict with teachers as violent video game play increased. Overall, these results suggest that frequency of violent video game play has a relation to poorer performance in school and more negative attitudes. It is possible that increased time spent playing violent video games decreases time spent working on school activities and that decreased importance is placed on academic activities. However, despite these decreases in academic adjustment, participants in the study did not seem to view themselves as any less competent when it comes to cognitive abilities.

In hypothesis three, the analyses from hypothesis two were re-examined to determine if grade level or gender moderated the relations found. When gender was 62 entered in the analyses, the same general pattern of relations was found so gender was not found to act as a moderator. In addition, in general grade was not found to moderate the results. However, grade level did moderate the relation between primary context of play and academic adjustment. Specifically, 7th graders who played primarily with others

present, 9th graders who played primarily with others present or others online, and 11th

graders who primarily played alone reported lower levels of cognitive competence.

Overall, these results suggest that all participants, regardless of age or gender, are likely

to experience the relation between violent video game play and decreased academic

adjustment. However, at 7th, 9th, and 11th grades, different primary contexts of play were

related to lower levels of cognitive competence. It is unclear why this relation exists, but

it may be related to developmental differences in participants. Another possibility is that

this group actually represents the least cognitively competent students and that these

students gravitate to a specific context of play at different grades.

Limitations

The present study has several limitations that should be discussed. First,

limitations of the survey format should be noted. In the present study, ratings of

aggressive and prosocial behavior, social adjustment, and academic adjustment were

gathered via self-report data. It is possible that these data may be subject to reporter bias,

as participants may not want to appear to engage in overly negative behaviors and thus

underreport signs of negative adjustment (e.g., poor grades, high levels of aggression).

However, it is possible that the anonymous nature of the survey allowed participants to

feel comfortable reporting accurate information. Another limitation of self-report data is

that it is possible that participants may over or underestimate the amount of time spent 63 playing video games. It would be helpful to have other data to support the play frequencies reported, such as daily play diaries. However, prior studies have found frequencies of play reports based on self-report data to generally be close to information gathered via other means, such as play diaries (e.g., Anderson & Dill, 2001; Roberts et al., 2005).

A second limitation of the present study lies in the characteristics of the sample.

As mentioned previously, the majority of the participants in the present study were of

Caucasian descent and all participants lived in a semi-rural, middle class community in northwest Ohio. Thus, the data from this sample cannot necessarily be generalized to larger populations (e.g., adolescents living in the United States). However, the data gathered revealed that these participants’ responses followed similar patterns to those found in prior studies. Additionally, data from these participants represents a good

“starting point” for gathering data that has not previously been examined. Specifically, this may be a good sample for beginning an inquiry into whether children engage in social video game play and how that compares to playing video games alone with regard to adjustment.

A third limitation of the current study is the cross-sectional nature of the data gathered. When data are gathered at only one time point, it is difficulty to determine if relations found are the result of selection or socialization. In other words, it is hard to determine if significant results indicate that children who play violent video games subsequently experience problems with social, behavioral, and academic adjustment. An alternate possibility is that children who experience difficulties in these areas of adjustment prefer to spend their time playing violent video games. 64

A final limitation of the present study is that the measures used did not specifically assess the level of violent content in the video games played by participants.

Instead, the survey asked about types of video games (e.g., “first person shooter games,”

“strategy games”) as a proxy for video game violence. However, prior research has found that the majority of the games in the classifications use contain violent content.

Despite these limitations, it is notable that violent video games, played across all contexts, were found to be significantly related to the various adjustment variables. The areas studied (academic, social, and behavioral adjustment) are likely the outcomes of multiple sources of influence (e.g., family of origin, culture of origin). The fact that relations were found between levels of video game violence exposure and adjustment provide support for the possibility that violent video game play has an influence on these outcomes.

Conclusions and Future Directions

Results from the present study provide support for the assertion that children and adolescents who play violent video games may experience problems with behavioral, social, and academic adjustment. Further research is warranted to determine the extent and direction of the relation between frequency of violent video game play and adjustment.

It is likely that the information gathered by the current study could be replicated with a larger, more nationally representative sample. Refinements to the survey, including the possible addition of physical aggression items and having more accurate measures of violent content in video games may be helpful were the study to be replicated. Furthermore, the addition of other measures of violent video game play, such 65 as video game diaries, would be helpful to further refine the results. Regardless of what refinements were made, there still exists a paucity of data regarding the amount of time children spend playing violent video games with others present. At the present time, it is difficult to determine if the stereotype of children playing violent video games by themselves is accurate. Based on the present study, it is likely that playing video games with others present is more common than previously thought.

This field would also benefit from longitudinal studies examining the relation between violent video game play and behavioral, social, and academic adjustment. To date, the vast majority of studies into the possible effects of video game violence exposure on adjustment have examined cross-sectional or laboratory data gathered at one point. Without longitudinal studies, it will be hard to ever determine which came first, the video game or the adjustment?

A final direction that would be helpful in expanding the information gathered in the present study would be to conduct laboratory experiments aimed at determining if there are differences between playing alone, playing with others present, and playing with others online. It would be useful to collect ratings of psychological phenomenon (e.g., aggressive cognition and behavior, frustration) from participants after playing in each context. It would also be valuable to gather biometric data (e.g., changes in blood pressure and heart rate) during and following video game play in each context. These data would help us further determine if there are differences in the way we react to violent video game content, physically and psychologically, based on the context in which the exposure occurs. 66

REFERENCES

Anand, V. (2007). A study of time management: The correlation between video game

usage and academic performance markers. Cyberpsychology and Behavior, 10(4),

552-559.

Anderson, C. A., & Bushman, B. J. (2001). Effects of violent video games on aggressive

behavior, aggressive cognition, aggressive affect, physiological arousal, and

prosocial behavior: A meta-analytic review of the scientific literature.

Psychological Science, 12(5), 353-359.

Anderson, C. A., & Bushman, B. J. (2002). Human aggression. Annual Review of

Psychology, 53(1), 27-51.

Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings,

and behavior in the laboratory and in life. Journal of Personality and Social

Psychology, 78 (4), 772-790.

Anderson, C. A., & Ford, C. M., (1987). Affect of the game player: Short-term effects of

highly and mildly aggressive video games. 12(4), 390-402.

Anderson, C. A., & Morrow, M. (1995). Competitive aggression without interaction:

Effects of competitive versus cooperative instructions on aggressive behavior in

video games. Personality and Social Psychology Bulletin, 21(10), 1020-1030.

Baldaro, B., Tuozzi, G., Codispoti, M., Montebarocci, O., Barbagli, F., Trombini, E., &

Rossi, N. (2004). Aggressive and non-violent videogames: Short-term

psychological and cardiovascular effects on habitual players. Stress and Health,

20, 203-208. 67

Bandura, A. (1973). Aggression: A social learning analysis. Englewood Cliffs, NJ:

Prentice-Hall.

Bartholow, B. D., Sestir, M. A., & Davis, E. B. (2005). Correlates and consequences of

exposure to video game violence: Hostile personality, empathy, and aggressive

behavior. Personality and Social Psychology Bulletin, 31(11), 1573-1586.

Berkowitz, L. (1990). On the formation and regulation of anger and aggression a

cognitive-neoassocionistic analysis. American Psychologist, 45(4), 494-503.

Berkowitz, L. (1997). On the determinants and regulation of impulsive aggression. In S.

Feshbach & J. Zagrodzka (Eds.), Aggression: biological, developmental, and

social perspectives (pp. 187-211). New York, NY: Plenum Press.

Bjorkqvist, K. (1997). Learning aggression from models: From a social learning toward a

cognitive theory of modeling. In S. Feshbach & J. Zagrodzka (Eds.), Aggression:

biological, developmental, and social perspectives (pp. 69-81). New York, NY:

Plenum Press.

Bjorkqvist, K., Lagerspetz, K. M. J., Osterman, K. (1992). “The Direct & Indirect

Aggression Scales.” Âbo Akademi University, Department of Social Sciences,

Vasa, Finland.

Bushman, B. J., & Anderson, C. A. (2002). Violent video games and hostile expectations:

A test of the general aggression model. Personality and Social Psychology

Bulletin, 28(12), 1679-1686.

Carnagey, N. L., & Anderson, C. A. (2005). The effects of reward and punishment in

violent video games on aggressive affect, cognition, and behavior. Psychological

Science, 16(11), 882-889. 68

Chambers, J. H., & Ascione, F. R. (1987). The effects of prosocial and aggressive video

games on children’s donating and helping. Journal of Genetic Psychology,

148(4), 499-505.

Colwell, J., & Kato, M. (2003). Short note investigation of the relationship between

social isolation, self-esteem, aggression, and computer game play in Japanese

adolescents. Asian Journal of Social Psychology, 6, 149-158.

Comstock, G. A., & Paik, H. (1991). Television and the American child. San Diego, CA:

Academic Press.

Dubow, E. F., Kausch, D. F., Blum, M. C., Reed, J., & Bush, E. (1989). Correlates of

suicidal ideation and attempts in a community sample of junior high and high

school students. Journal of Clinical Child Psychology, 18, 158-166.

Ducheneaut, N., Yee, N., Nickell, E., & Moore, R. J. (2006). Building an MMO with

mass appeal: A look at gameplay in World of Warcraft. Games and Culture, 1,

281-317.

Eron, L. D. (1994). Theories of aggression from drives to cognitions. In L. R. Huesmann

(Ed.), Aggressive behavior: Current perspectives (pp. 3-11). New York, NY:

Plenum Press.

Funk, J. B., Buchman, D. B., Jenks, J., & Bechtoldt, H. (2003). Playing violent video

games, desensitization, and moral evaluation in children. Applied Developmental

Psychology, 24, 413-436.

Gentile, D. A., Lynch, P. J., Linder, J. R., & Walsh, D. A. (2004). The effects of violent

video game habits on adolescent hostility, aggressive behaviors, and school

performance. Journal of Adolescence, 27, 5-22. 69

Griffiths, M. D. (2000). Video game violence and aggression: Comments on ‘Video game

playing and its relations with aggressive and prosocial behaviour’ by O. Wiegman

and E. G. M. van Schie. British Journal of Social Psychology, 39, 147-149.

Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2004). Demographic factors and

playing variables in online computer gaming. Cyberpsychology & Behavior, 7(4),

479-487.

Grüsser, S. M., Thalemann, R., and Griffiths, M.D. (2007). Excessive computer game

playing: Evidence for addiction and aggression? Cyberpsychology & Behavior,

10(2), 290-292.

Harter, S. (1982). The perceived competence scale for children. Child Development, 53,

87-97.

Harter, S. (1985). Manual for the self-perception profile for children. Denver, CO;

University of Denver.

Hawkins, J,D,, Guo, J., Hill, K.G., Battin-Pearson-S., Abbott, R.D. (1996). Long-term

effects of the Seattle Social Development intervention on school bonding

trajectories. Applied Developmental Science, 5, 225-236.

Huesmann, L. R. (1988). An information model for the development of aggression.

Aggressive Behavior, 14, 13-24.

Huesmann, L. R. (1998). The role of social information processing and cognitive schema

in the acquisition and maintenance of habitual aggressive behavior. In R. G. Geen

& E. Donnerstein (Eds.), Human aggression: Theories, research, and

implications for social policy (pp.73-109). San Diego, CA: Academic Press. 70

Huston, A. C., Donnerstein, E., Fairchild, H., Feshbach, N. D., Katz, P. A., Murray, J. P.,

Rubinstein, E. A., Wilcox, B. L., & Zuckerman, D. M. (1992). Big world, small

screen: The role of television in American society. Lincoln, NE: University of

Nebraska Press.

Irwin, R. A., & Gross, A. M. (1995). Cognitive tempo, violent video games, and

aggressive behavior in young boys. Journal of Family Violence, 10(3), 337-350.

Jo, E., Berkowitz, L. (1994). A priming effect analysis on media influence: An update. In

J. Bryant & D. Zillman (Eds.), Media effects: Advances in theory and research

(pp. 43-60). Hillsdale, NJ: Lawrence Erlbaum Associates.

Jansz, J., & Martens, L. (2005). Gaming at a LAN event: The social context of playing

video games. New Media & Society, 7(3), 333-355.

Jansz, J., & Tanis, M. (2007). Appeal of playing online first person shooter games.

Cyberpsychology and Behavior, 10, 133-136.

Kaukiainen, A., Bjorkqvist, K., Lagerspetz, K., Osterman, K., Salmivalli, C., Rothberg,

S., & Ahlbom, A. (1999). The relationships between social intelligence, empathy,

and three types of aggression. Aggressive Behavior, 25(2), 81-89.

Kent, S. L. (2001). The ultimate history of video games: from Pong to Pokémon and

beyond—the story behind the craze that touched our lives. Roseville: Prima.

Kirsh, S. J. (2003). The effects of violent video games on adolescents the overlooked

influence of development. Aggression and Violent Behavior, 8, 377-389.

Lagerspetz, K. M. J., & Bjorkqvist, K. (1994). Indirect aggression in boys and girls. In L.

R. Huesmann (Ed.), Aggressive behavior: Current perspectives (pp. 131-150).

New York, NY: Plenum Press. 71

Lenhart, L. A., & Rabiner, D. L. (1995). An integrative approach to the study of social

competence in adolescence. Development and Psychopathology, 7, 543-561.

Lo, S., Wang, C., & Fang, W. (2005). Physical interpersonal relationships and social

anxiety among online game players. Cyberpsychology & Behavior, 8(1), 15-20.

Musher-Eizenman, D. R., Boxer, P., Danner, S., Dubow, E. F., Goldstein, S. E.,

& Heretick, D. M. L. (2004). Social-Cognitive Mediators of the Relation of

Environmental and Emotion Regulation Factors to Children's Aggression.

Aggressive Behavior, 30(5), 389-408.

Natkin, S. (2006). Video games and interactive media: A glimpse at new digital

entertainment. Wellesley: A K Peters.

Olson, C. K. (2004). Media violence research and youth violence data: Why do they

conflict? Academic Psychiatry, 28(2), 144-150.

Osterman, K., Bjorkqvist, K., Lagerspetz, K. M. J., Charpentier, S., Caprara, G. V.,

& Pastorelli, C. (1999). Locus of control and three types of aggression.

Aggressive Behavior, 25(1), 61-65.

Osterman, K., Bjorkqvist, K., Lagerspetz, K. M., Kaukiainen, A., Huesmann, L. R.,

Frącedil, A. (1994). Peer and self-estimated aggression and victimization in 8

year-old children from five ethnic groups. Aggressive Behavior, 20(6), 411-428.

Jansz, J., & Martens, L. (2005). Gaming at a LAN event: The social context of playing

video games. New Media & Society, 7(3), 333-355.

Roberts, D. F., Foehr, U. G., & Rideout, V. J.. (2005). Generation M: Media in the lives

of 8-18 year-olds. Menlo Park, CA: Henry J. Kaiser Family Foundation. 72

Roberts, D. F., Foehr, U. G., Rideout, V. J., Brodie, M. (1999). Kids & Media @ the New

Millennium

Schneider, E. F., Lang, A., Shin, M., & Bradley, S. D. (2004). Death with a story: How

story impacts emotional, motivational, and physiological responses to first-person

shooter video games. Human Communications Research, 30(3), 361-375.

Schutte, N. S., Malouff, J. M., Post-Gorden, J. C., & Rodasta, A. L. (1988). Effects of

playing videogames on children’s aggressive and other behaviors. Journal of

Applied Social Psychology, 18(5), 454-460.

Sheese, B. E., & Graziano, W. G. (2005). Deciding to defect the effects of video game

violence on cooperative behavior. Psychological Science, 16(5), 354-357.

Sherry, J. L. (2001). The effects of violent video games on aggression a meta-analysis.

Human Communications Research, 27(3), 409-431.

Uhlmann, E., & Swanson, J. (2004). Exposure to violent video games increases automatic

aggressiveness. Journal of Adolescence, 27, 41-52.

Whang, L. S., & Chang, G. (2004). Lifestyles of virtual world residents: Living in the on-

line game “Lineage.” Cyberpsychology & Behavior, 7(5), 592-600.

Wiegman, O., & van Schie, E. G. M. (1998). Video game playing and its relations with

aggressive and prosocial behaviour. British Journal of Social Psychology, 37(3),

367-378.

Wiliams, D., Ducheneaut, N., Xiong, L., Zhang, Y., Yee, N., Nickell, E. (2006). From

tree house to barracks: The social life of guilds in World of Warcraft. Games and

Culture, 1, 338-361. 73

Williams, R. B., & Clippinger, C. A. (2002). Aggression, competition and computer

games: computer and human opponents. Computers in Human Behavior, 18, 495-

506.

Williams, D., & Skoric, M. (2005). Internet fantasy violence: A test of aggression in an

online game. Communication Monographs, 72(2), 217-233. 74

APPENDIX A: LETTER SENT TO PARENTS DESCRIBING THE STUDY

Hi, our names are Jason Drummond and Kelly Lister, and we’re graduate students from Bowling Green State University. Teenagers today are using computers more than ever before. We are doing a research project that is a survey about how much teenagers of different ages use computers for social reasons, especially to talk to other people on instant messenger (IM), play multiplayer games, and use blogs. We want to see what kinds of things you do on IM, how much you play games on the internet, and how often you look at blogs. We also want to see how your behaviors toward other people when you are online are similar to and different from your behaviors offline. We also want to know how other people treat you when you are online and not online. This survey will help us learn more about how teenagers today are using the internet. Your honest opinions are very important to us. We would like you to fill out a survey so you can share your thoughts and opinions. This survey will take about 45 minutes to complete. We will not single out any one teenager’s answers because we are interested in how teenagers as a group respond to these questions.

You DO NOT have to fill out this survey if you do not want to. If you start, and then change your mind, you can stop at any time. If you do fill it out, your responses will be PRIVATE and ANONYMOUS. This means that no one will be able to know what you wrote. You will not write your name anywhere on the survey. If you agree to participate, just tear off this cover sheet and keep it for yourself.

If you have any questions for us, please feel free to ask!

Also feel free to contact us at:

Jason Drummond Kelly Lister Eric Dubow, Professor Psychology Department Bowling Green State University Bowling Green, OH 43403 (419) 372-4501

75

APPENDIX B: ITEMS REGARDING DEMOGRAPHICS AND ACADEMIC

ACHIEVEMENT

I’m going to read some questions, and I would like you to choose the answer that is most true for you. Please put an “X” by the answer that is most true for you.

*1. Are you a ______? (PUT AN “X” IN THE BOX THAT IS TRUE FOR YOU): □ Boy □ Girl

*2. How old are you? (PUT AN “X” IN THE BOX THAT IS TRUE FOR YOU): □ 11 years old □ 16 years old □ 12 years old □ 17 years old □ 13 years old □ 18 years old □ 14 years old □ 19 years old □ 15 years old

*3. What grade are you in? (PUT AN “X” IN THE BOX THAT IS TRUE FOR YOU): □ 7th grade □ 10th grade □ 8th grade □ 11th grade □ 9th grade □ 12th grade

*4. What is your race or ethnic background (PUT AN “X” IN THE BOX THAT IS TRUE FOR YOU): □ Caucasian □ African American □ Hispanic/Latino □ Asian/Asian Indian/Pacific Islander □ Native American □ Biracial/Multiracial (please specify: ______) □ Other (please specify: ______)

*Who lives in your home with you? (PUT AN “X” IN THE BOX THAT IS TRUE FOR YOU): Yes (1) No (2) 5. My mother lives with me 6. My father lives with me

*7. How many other adults (people over the age of 18), not including your mother and father, live in your home? (WRITE THE NUMBER HERE): ______

*8. How many kids (people under the age of 18), including you, live in your home? (WRITE THE NUMBER HERE): ______

**9. What grades do you usually get? (PUT AN “X” IN THE BOX THAT IS TRUE FOR YOU): □ Mostly A’s □ Mostly C’s and D’s □ Mostly A’s and B’s □ Mostly D’s □ Mostly B’s □ Mostly D’s and F’s □ Mostly B’s and C’s □ Mostly F’s □ Mostly C’s *Demographic question

**Academic achievement question 76

APPENDIX C: VIDEO GAME USAGE ITEMS

*Multiplayer games are those games that you play with either: 1) other people who are sitting in the room in front of the game unit with you, or 2) other people over the internet (such as X-box live and computer or Playstation 2 online games)*

Please tell us how many days each week you do the following things while playing video games (PUT AN “X” IN THE BOX THAT IS MOST TRUE FOR YOU. CHOOSE ONLY ONE ANSWER PER QUESTION): Never (1) Once a A few times Most days Everyday week a week (4) (5) (2) (3) 130. Play First Person Shooters by yourself (Halo 2, Half-life 2, Battlefield 1942, etc.) *First Person Shooters are games where the player engages in battle from a first person point of view* 131. Play First Person Shooters with another person who is in the room with you (Halo 2, Half-life 2, Battlefield 1942, etc.) *First Person Shooters are games where the player engages in battle from a first person point of view* 132. Play First Person Shooters with someone online who is not in the room with you (Halo 2, Half-life 2, Battlefield 1942, etc.) *First Person Shooters are games where the player engages in battle from a first person point of view* 136. Play strategy games by yourself (Warcraft 3, Starcraft, Civilization 3, Rome Total War, etc.) 137. Play strategy games with another person who is in the room with you (Warcraft 3, Starcraft, Civilization 3, Rome Total War, etc.)

138. Play strategy games with someone online who is not in the room with you (Warcraft 3, Starcraft, Civilization 3, Rome Total War, etc.)

139. Play Massively Multiplayer Online Games with at least one other player in the room with you (Star Wars Galaxies, World of Warcraft, Everquest II, Planetside, etc.) *massive multiplayer online games are games where there are worlds created online where players can log on and play with many other players* 140. Play Massively Multiplayer Online Games with none of the other players in the room with you (Star Wars Galaxies, World of Warcraft, Everquest II, Planetside, etc.) *massive multiplayer online games are games where there are worlds created online where players can log on and play with many other players*

77

APPENDIX D: AGGRESSIVE AND PROSOCIAL BEHAVIOR ITEMS

Please tell us how often YOU DO the following things when you are face-to-face with others (PUT AN “X” IN THE BOX THAT IS MOST TRUE FOR YOU. CHOOSE ONLY ONE ANSWER PER QUESTION): Never Seldom Sometimes Quite Very (1) (2) (3) often (4) often (5) 87. You yell at or argue with another person face-to-face. 88. You ask someone to play a game with you face-to-face. 89. You insult another person face-to-face. 90. When talking to someone face-to-face, you compliment someone else. 91. You tease someone face-to-face. 92. You plan secretly to bother someone face-to-face. 93. You share something with someone face- to-face. 94. When talking to someone face-to-face, you gossip about someone else you are angry at. 95. You call another person names face-to- face. 96. You compliment someone face-to-face.

97. You ignore someone when they talk to you face-to-face. 98. You say something nice about someone face-to-face. 99. You hand-write notes to someone that criticize someone else. 100. You congratulate someone face-to-face.

101. When talking to someone face-to-face, you say bad things about someone else you have problems with. 102. You cheer someone up face-to-face. 103. When talking to someone face-to-face, you say something nice about someone else. 104. You say you are going to hurt someone face-to-face. 105. When talking to someone face-to-face, you invite him/her to do something with you. 106. You help someone with his/her homework face-to-face.

78

APPENDIX E: PERCEIVED COMPETENCE ITEMS

Please tell us how you feel about the following statements (PUT AN “X” IN THE BOX THAT IS MOST TRUE FOR YOU. CHOOSE ONLY ONE ANSWER PER QUESTION): Always Most of Sometimes Hardly Never (5) (1) the time (3) ever (4) (2) 146. Some kids feel that they are just as smart as others their age, but other kids don’t. Do you feel that you are as smart as other kids your age? 147. Some kids find it hard to make friends, but others don’t. Do you find it hard to make friends? 148. Some kids have a close friend they can share secrets with, but others don’t. Do you have a close friend you can share secrets with? 149. Some kids like the way they are leading their life, but others don’t. Do you like the way you are leading your life? 150. Some kids are pretty slow in finishing their school work, but other kids aren’t. Are you pretty slow in finishing your school work? 151. Some kids are very hard to like, but others are easy to like. Do you think you are very hard to like?

152. Some kids find it hard to make friends they can really trust, but others don’t. Do you find it hard to make friends you can really trust?

153. Some kids are happy with themselves most of the time, but others aren’t. Are you happy with yourself most of the time? 154. Some kids do very well at their classwork, but others don’t. Do you do well at your classwork?

155. Some kids have a lot of friends, but others don’t. Do you have a lot of friends? 156. Some kids are able to make really close friends, but others aren’t. Are you able to make really close friends? 157. Some kids feel really good about the way they act, but others don’t. Do you feel really good about the way you act? 158. Some kids are popular with others their age, but others aren’t. Are you popular with others your age? 159. Some kids are very happy being the way they are, but others aren’t. Are you very happy being the way you are?

79

APPENDIX F: ACADEMIC ADJUSTMENT ITEMS

Have you done any of the following in the past year? (PUT AN “X” IN THE BOX THAT IS TRUE FOR YOU. CHOOSE ONLY ONE ANSWER PER QUESTION): No (1) Yes (2) 160. Been a member of a school sports team 161. Took part in a school play or show 162. Went to a school dance 163. Helped a teacher after school 164. Went to a meeting of a school club or group 165. Worked on a school project outside of class 166. Elected to some club or office 167. Tutored other students 168. Gone to a school sports event

Which of the following is most true for you in school? (PUT AN “X” IN THE BOX THAT IS TRUE FOR YOU. CHOOSE ONLY ONE ANSWER PER QUESTION): Always (1) Usually (2) Sometimes Hardly Ever Never (5) (3) (4) 169. At school, I try as hard as I can to do my best work.

170. I care how I do in school.

171. I feel bored at school.

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APPENDIX G: TABLES AND FIGURES

Table 1

Description of the Sample

Frequencies N Percent of Sample Total Participants 484 100 Grade Level 7th 90 (52% male) 18.6 9th 223 (49% male) 46.1 11th 171 (60% male) 35.3 Gender Male 260 53.8 Female 223 46.2 Race Caucasian 376 20.7 Non-Caucasian 98 79.3 Number of Parents in the Home Two parents 341 70.6 Less than two parents 142 29.4

Note. Due to missing items, the ns of various subsamples differ from one another and do

not always sum to equal the total N.

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Table 2

Number and Percentage of Participants of Each Gender Who Indicated Playing Violent

Video Games Overall, Alone, With Others Present, and With Others Online

Male Female Total n (%) n (%) n (%) Frequency of violent video game play overall Never 36(14%) 148 (67%) 184(38.4%) Once a week/few times a week 129(50%) 61(27.6%) 190(39.7%) Most days/every day 93(36%) 12(5.4%) 105(21.9%) Total 258(53.9%) 221(46.1%) 479(100%) Frequency of violent video game play alone Never 51 (19.8%) 162 (73.6%) 213 (44.6%) Once a week/few times a week 134 (51.9%) 47 (21.4%) 181 (37.9%) Most days/every day 73 (28.3%) 11 (5%) 84 (17.6%) Total 258 (54%) 220 (46%) 478 (100%) Frequency of violent video game with others present Never 69 (26.7%) 172 (78.2%) 241 (50.4%) Once a week/ few times a week 140 (54.3%) 43 (19.5%) 183 (38.3%) Most days/Every Day 49 (19%) 5 (2.3%) 54 (11.3%) Total 258 (54%) 220 (46%) 478 (100%) Frequency of violent video game play with others online Never 139 (54.1%) 201 (91%) 340 (71.1%) Once a week/few times a week 70 (27.2%) 16 (7.2%) 86 (18%) Most days/every day 48 (18.7%) 4 (1.8%) 52 (10.9%) Total 257 (53.8%) 221 (46.2%) 478 (100%)

Note. Due to missing items, the ns of various subsamples differ from one another and do

not always sum to equal the total N.

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Table 3

Number and Percentage of Participants in Each Grade Who Indicated Playing Violent

Video Games Overall, Alone, With Others Present, and With Others Online

7th grade 9th Grade 11th Grade Total n (%) n (%) n (%) n (%) Frequency of violent video game play overall Never 25 (28.4%) 89(40.1%) 80 (41.2%) 184 (38.3%) Once a week/few times a week 35 (39.8%) 83 (37.4%) 73 (42.9%) 191 (39.8%) Most days/every day 28 (31.8%) 50 (22.5%) 27 (15.9%) 105 (21.9%) Total 88 (18.3%) 222 (46.3%) 170 (35.4%) 480 (100%) Frequency of violent video game play alone Never 35 (40.2%) 100 (45%) 78 (45.9%) 213 (44.5%) Once a week/few times a week 29 (33.3%) 80 (36%) 73 (42.9%) 182 (38%) Most days/every day 23 (26.4%) 42 (18.9%) 19 (11.2%) 84 (17.5%) Total 87 (18.2%) 222 (46.3%) 170 (35.5%) 479 (100%) Frequency of violent video game play with others present Never 40 (45.5%) 112 (50.5%) 89 (52.7%) 241 (50.3%) Once a week/few times a week 34 (38.6%) 79 (35.6%) 71 (42%) 184 (38.4%) Most days/every day 14 (15.9%) 31 (14%) 9 (5.3%) 54 (11.3%) Total 88 (18.4%) 222 (46.3%) 169 (35.3%) 479 (100%) Frequency of violent video game play with others online Never 58 (66.7%) 154 (69.4%) 128 (75.3%) 340 (71%) Once a week/few times a week 18 (20.7%) 44 (19.8%) 85 (14.7%) 147 (18.1%) Most days/every day 11 (12.6%) 24 (10.8%) 17 (10%) 52 (10.9%) Total 87 (18.2%) 222 (46.3%) 170 (35.5%) 479 (100%) Note Due to missing items, the ns of various subsamples differ from one another and do

not always sum to equal the total N. 83

Table 4 Multiple Analysis of Variance and Multiple Analysis of Covariance for Behavioral, Social Adjustment, and Academic Adjustment Variables

Alone Others Other Present Online Mean (sd) Mean (sd) Mean (sd) Never Once/Few Most/Every F(df) Never Once/Few Most/Every F(df) Never Once/Few Most/Every F(df) Aggression Variables a Multivariate 7.99 6.49 6.21 (4,946)** (4,946)** (4,948)** Aggression 2.07a 2.14a 2.36b 6.21 2.09a 2.15a 2.41b 5.25 2.13a 2.24a 2.16a .97 (.61) (.58) (.80) (2,473)** (.60) (.59) (.88) (2,473)** (.62) (.70) (.66) (2,474) Prosocial 3.69a 3.45b 3.42b 8.49 3.65a 3.47b 3.33b 6.58 3.63a 3.43b 3.21b 11.11 (.68) (.64) (.73) (2,473)** (.68) (.61) (.83) (2,473)** (.67) (.66) (.71) (2,474)** Social Adjustment Multivariate 2.19 1.742 2.06 (4, 950)* (4,950) (4,950)* Social 4.00a 3.88ab 3.77b 3.56 3.95 3.90 3.76 __ 3.96a 3.85ab 3.69b 3.86 Competence (.66) (.64) (.87) (2,475)** (.68) (.67) (.83) (.65) (.77) (.81) (2,475)** Intimate 3.99a 3.88ab 3.68b 3.39 3.97 3.88 (.74) 3.68 3.95a 3.82a 3.68a 2.07 Relations (.74) (.74) (.77) (2,475)** (.74) (.77) __ (.73) (.78) (.77) (2,475) Competence Academic Adjustment a Multivariate 4.94 5.52 3.51 (8,936)** (8,936)** (8,936)** Cognitive 3.78a 3.82a 3.74a .35 3.80a 3.82a 3.58a 2.40 3.79a 3.76a 3.84a .149 Competence (.75) (.67) (.77) (2,470) (.72) (.68) (.86) (2,470)* (.70) (.75) (.81) (2,470) School 5.48a 5.08ab 4.66b 7.54 5.44a 5.04ab 4.56b 6.63 5.31a 5.00a 4.75a 2.94 Involvement (1.70) (1.72) (1.83) (2,470)** (1.71) (1.68) (2.03) (2,470)** (1.69) (1.94) (1.82) (2,470)* Negative 2.28a 2.41a 2.62b 8.49 2.28a 2.42a 2.76b 11.73 2.32a 2.46ab 2.71b 8.50 Attitudes (.66) (.65 (.71) (2,470)** (.65) (.64) (.78) (2,470)** (.65) (.65) (.78) (2,470)** GPA 2.39a 2.61a 3.12b 7.15 2.41a 2.56a 3.54b 11.92 2.50a 2.79a 2.94a 2.94 (1.45) (1.57) (1.77) (2,470)** (1.43) (1.57) (1.83) (2,470)** (1.49) (1.72) (1.78) (2,470)* Note: Aggressive and prosocial behavior items were rated on a 5-point scale and scored such that higher numbers indicate more incidences of the target behavior. Social adjustment and cognitive competence items were rated one a 5-point scale and scored such that higher numbers indicate greater feelings of competence. School involvement means are based on participants' indication whether or not each of 8 items applies to them; higher scores indicate greater school involvement. Negative attitudes towards school items were rated on a 5-point scale and scored such that higher numbers indicate more negative attitudes towards school. GPA was based on an answer to an item asking students to rate their GPA on a 9-point scale; lower numbers indicate higher GPA. Means with the same subscript are not significantly from one another based on Bonferroni comparisons. a MANCOVA which included total number of parents in the home was entered as a covariate in these analyses ** p < .01; * p < .05

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Table 5 Multiple Analysis of Variance and Multiple Analysis of Covariance for Behavioral, Social Adjustment, and Academic Adjustment Variables Total Violent Video Game Play Primary Context of Play Mean (sd) (sd)Mean Never Once/Few Most/Every F(df) Alone With With F(df) Others Others Present Online Aggression Variables a Multivariate 8.87 .36 (4,180) (4,948)** Aggression 2.07a 2.14a 2.32b 5.73 2.22 2.24 2.01 __ (.60) (.58) (.78) (2,474)** (.63) (.58) (.67) Prosocial 3.71a 3.50b 3.36b 10.41 3.50 3.51 3.26 __ (.68) (.63) (.73) (2,474)** (.62) (.62) (.76) Social Adjustment Multivariate 2.43 .855 (4,182) (4,952)** Social Competence 3.99a 3.92ab 3.76b 3.80 3.84 3.91 3.69 __ (.67) (.61) (.86) (2,476)** (.71) (.73) (.96) Intimate Relations Competence 3.98a 3.92ab 3.73b 3.93 3.76 3.96 4.04 __ (.76) (.67) (.84) (2,476)** (.84) (.77) (.84) Academic Adjustment a Multivariate 5.61 .67 (8,174) (8,938)** Cognitive Competence 3.79a 3.82a 3.72a .72 3.75 3.68 3.83 __ (.73) (.68) (.80) (2,471) (.77) (.75) (.44) School Involvement 5.55a 5.12ab 4.70b 8.48 5.08 5.16 4.00 __ (1.67) (1.75) (1.82) (2,471)** (1.73) (1.70) (2.00) Negative Attitudes 2.25a 2.39a 2.63b 11.52 2.38 2.52 2.46 __ (.67) (.64) (.70) (2,471)** (.63) (.71) (.43) GPA 2.33a 2.60a 3.06b 8.16 2.58 2.88 2.38 __ (1.38) (1.59) (1.75) (2,471)** (1.60) (1.74) (1.60) Note: Aggressive and prosocial behavior items were rated on a 5-point scale and scored such that higher numbers indicate more incidences of the target behavior. Social adjustment and cognitive competence items were rated one a 5-point scale and scored such that higher numbers indicate greater feelings of competence. School involvement means are based on participants' indication whether or not each of 8 items applies to them; higher scores indicate greater school involvement. Negative attitudes towards school items were rated on a 5-point scale and scored such that higher numbers indicate more negative attitudes towards school. GPA was based on an answer to an item asking students to rate their GPA on a 9 point scale; lower numbers indicate higher GPA. Means with the same subscript are not significantly from one another based on Bonferroni comparisons. a MANCOVA which included total number of parents in the home was entered as a covariate in these analyses ** p < .01; * p < .05

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Table 6

Multiple Analysis of Variance and Multiple Analysis of Covariance F-Values for Examining Gender Main Effects and Interactions with Video Game Frequency

Variables in Predicting Adjustment Measures

Aggressive and Prosocial Behavior a Social Adjustment Academic Adjustment a STEPS MANCOVA Aggressive Prosocial MANOVA Social Intimate MANCOVA Cognitive School Negative GPA Behavior Behavior Competence Relations Competence Involvement Attitudes Competence For Total Violent Video Game Play Covariate 3.37 * 4.30* 1.58 - - - 5.48 ** 6.61 ** 2.20 8.62 ** 20.29*** Gender 20.62 ** 3.12 34.48 ** 5.01 ** 1.95 9.78** 13.02 ** .09 19.73 ** 23.68 ** 8.46 ** Violent Video 3.12 * 4.23* 1.34 1.69 2.81+ 1.49 1.91 2.21 .92 3.93* 4.54* Game Play Gender x 1.54 1.41 1.86 .64 .48 1.20 1.57 2.16 .70 .60 2.71 Video Game Play

For Game Play Alone Covariate 3.22 * 3.99* 1.65 - - - 5.58 ** 3.33 * 2.75+ 8.41 ** 20.49*** Gender 20.57 ** 3.31 34.29 ** 5.09 ** 2.08 9.97 ** 12.76** .08 18.99 ** 23.62** 8.21 ** Game Play 2.83 * 4.67 ** .69 1.42 2.49+ .87 1.74 .38 2.08 2.55+ 4.04* Alone Gender x 2.20+ 1.65 2.93+ .43 .73 .05 1.92 1.39 3.39* .22 1.66 Game Play Alone

For Game Play with Others Present Covariate 3.27 * 3.92 * 1.78 - - - 5.46 ** 6.81 ** 2.57 8.54 ** 19.97 ** Gender 20.26 ** 3.32+ 33.64 ** 4.99 ** 1.93 9.74 ** 13.00** .11 18.96 ** 23.98 ** 8.74 ** Game Play 2.44 * 3.88 * .55 .78 .97 1.30 2.69 ** 2.73+ 1.75 5.25 ** 8.848** 86

with Others Present Gender x .95 .795 1.18 3.07* 2.60+ 4.52* .91 1.42 1.28 1.05 .70 Game Play with Others Present

For Game Play with Others Online Covariate 3.29* 4.22* 1.58 - - - 5.36 ** 3.52 ** 2.13 8.69 ** 19.92 ** Gender 20.50 ** 3.04+ 34.63** 5.13 ** 2.16 10.09 ** 13.10 ** .12 19.65 ** 23.47** 8.19 ** Game Play 2.02 .311 3.71* 1.55 2.86+ .32 1.34 .16 .35 3.46+ .89 with Others Online Gender x .497 .64 .46 1.38 1.90 2.42+ 1.35 1.41 1.09 1.11 1.37 Game Play with Others Online a MANCOVAs included total number of parents in the home was entered as a covariate in the analyses ** p < .01; * p < .05; + p < .10

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Table 7

Multiple Analysis of Variance and Multiple Analysis of Covariance F-Values for Examining Grade Main Effects and Interactions with Video Game Frequency

Variables in Predicting Adjustment Measures

Aggressive and Prosocial Behavior a Social Adjustment Academic Adjustment a STEPS MANCOVA Aggressive Prosocial MANOVA Social Intimate MANCOVA Cognitive School Negative GPA Behavior Behavior Competence Relations Competence Involvement Attitudes Competence For Total Violent Video Game Play Covariate 3.75 * 4.81 * 1.79 - - - 5.74 ** 6.65 ** 2.20 8.91 ** 21.49 ** Grade 2.48 * 3.42 * 1.36 1.20 .61 .50 3.88 ** 1.97 4.89 ** 6.23 ** 2.19 Violent Video 8.64 ** 5.99 ** 9.67** 2.52* 4.30 * 3.70* 5.94** .82 7.28 ** 14.74** 8.82** Game Play Grade x Video .436 .66 .30 .58 .34 .84 .80 .29 .52 .47 69 Game Play

For Game Play Alone Covariate 8.43 ** 4.47 * 1.85 - - - 5.80 ** 6.52 * 2.74+ 8.60 ** 21.63** Grade 2.57 * 3.60 * 1.41 1.23 .71 .44 4.07 ** 2.07 5.39 ** 6.21 ** 2.07 Game Play 7.83 ** 6.26 ** 8.17 ** 2.25+ 3.91+ 3.23+ 5.10 ** .41 6.56 ** 10.72** 7.40 ** Alone Grade x Game .271 .38 .21 .36 .26 .33 1.14 1.22 1.75 .23 .23 Play Alone

For Game Play with Others Present Covariate 3.64 * 4.48 * 1.99 - - - 5.67 ** 6.84 ** 2.57 8.76 ** 21.15** Grade 2.49 * 3.60* 1.24 1.19 .61 .50 3.83 ** 1.96 4.57 * 6.19 ** 2.25 Game Play 6.07 ** 4.95 ** 6.15 ** 1.74 1.94 3.35* 5.72 ** 2.37+ 5.63 ** 14.51** 11.86** with Others Present Grade x Game 1.57 2.51* .79 .434 .17 .29 .62 .35 .85 .52 .25 Play with 88

Others Present

For Game Play with Others Online Covariate 3.62 * 4.73 * 1.79 - - - 5.64 ** 6.84 ** 2.11 8.89 ** 21.29** Grade 2.43 * 3.36 * 1.36 1.15 .48 .61 4.03 ** 2.17 4.88 ** 6.35 ** 2.23 Game Play 5.90 ** .87 10.60** 2.11+ 4.00* 2.01 3.65 ** .13 2.51+ 9.68** 2.99+ with Others Online Grade x Game .61 1.04 .24 .83 .66 1.18 1.24 .57 .53 1.59 2.10+ Play with Others Online a MANCOVAs included total number of parents in the home was entered as a covariate in the analyses ** p < .01; * p < .05; +p < .10

89

Figure 1. Mean intimate competence scores for the gender x frequency of play with others present interaction

4.5 4 3.5 3 Never 2.5 Once a week/A few times a 2 week 1.5 Most days/Every Day 1 0.5 0 Male Female

90

Figure 2. Mean cognitive competence ratings for the grade x primary context of play interaction

4.5 4 3.5 3 2.5 Alone 2 With others present 1.5 With others online 1 0.5 0 7th grade 9th grade 11th grade