overall frontal lobe activity (Matthews et al., 2005). Two groups of adolescents, a subset ..... Bell Adjustment Inventory (2002). Bartholow, Sestir, & Davis (2005).
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The Unintended Negative Consequences of Exposure to Violent Video Games Computer technology has revolutionized a wide variety of tasks from communication and scientific calculations to entertainment and education. However, any new tool or technology may be misused or may create unintended negative consequences. In the case of video games, technology has seen considerable success in entertaining users and teaching specific content However, what they teach depends upon their content, regardless of the intent of the game creators or the end users. In the case of violent video games, research has demonstrated conclusively that these games can have deleterious effects on the user. Regardless of the research design (e.g., crosssectional or experimental) and outcome measures used (e.g., anger, aggressive thoughts, or aggressive behavior), research consistently shows that violent video games can increase aggression. Children and young adults, males and females, high aggressive and low aggression people are all susceptible to increases in aggression, after even short exposures to violent video games. Key Terms: violence, video games, aggression, consequence
Over the past thirty-five years video games have become a pervasive social phenomenon of substantial importance to many people, both those who play them and those who are indirectly affected by them. The immense growth in the popularity of video games has made understanding their effects an increasingly important scientific goal. Perhaps the most obvious and intentional effect of these video games is entertaining their users. Thousands of video game titles are available, and in 2005 their sales (including directly related accessories) accounted for $10.5 billion in the United States alone (ESA, 2007a). This exceeds the $8.9 billion made by films in the US box office that same year (MP AA, 2007). A national survey conducted several years ago found that 87% of children regularly play video games (Walsh, Gentile, Gieske, Walsh, Chasco, 2003); the number must be higher by now. The use of video games is not limited to children; 69% of American heads of household play video games as well (ESA, 2007b). Video games have also proven to be highly effective teaching tools. It is this role that has captured the interests of many researchers, educators, parents, and a variety of business and government organizations. Effective Teaching Tools The first things video games do that makes them effective at teaching is capture and hold the attention of the player (Gentile & Gentile, 2005). They do this through the use of rapidly changing visual and auditory stimuli that produce an automatic orienting response. These stimuli often are quite vivid- a trait that makes them easier to learn and remember. Well-designed
video games provide the player with clear objectives that are adaptable to the learning pace of the viewer. This adaptable pace is a key to learning and motivation in many educational models. In some games, the objectives may be modified, depending on the preferences of the individual player. In the attempt to reach these objectives, not only do video games reinforce mastery of their material through immediate and constant feedback but they also provide extrinsic reinforcement (e.g., awarding points, impressive visual and sounds effects), which motivates players to continue playing. Eventually, players develop their skills to the point of overlearning. In other words, their performance becomes automatized so that they may focus on acquiring and utilizing new skills or applying recently acquired skills in new contexts. The application of skills in multiple contexts helps in the transfer of learning from the game to the real world. In the long term, the habits of video gamers seem to provide them with both massed practice (playing for a long period of time) and distributed practice (playing frequently), which further facilitates learning. Intended Uses and Consequences of Video Games These remarkable features that make video games such effective teaching tools have not gone unnoticed or unused. Video games are applied in a variety of educational contexts, with both children and adults. This includes the teaching of traditional school subjects to children and adolescents, such as algebra, geometry, and biology (Corbett, Koedinger, & Hadley, 2001; Ybarrondo, 1984). Video games have also proven
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effective at improving children's self-management of health problems, such as asthma and diabetes (McPherson, Glazebrook, Forster, James, & Smyth, 2006; Lieberman, 1997). Many businesses have made use of video games in order to teach job skills to employees. Cisco uses a computer game to teach employees basic aspects of network security, such as firewalls, intrusion detection systems, and anti-virus software. Volvo uses an online computer game to teach financial and regulatory information to car sales employees (Flood, 2007). Canon, which uses a video game to teach employees how to repair printers, has noted improvements in the performance of new employees trained with video games compared to older training methods (Business Week, 2007). The Mayo Clinic uses video games such as "Name That Congenital Abnormality" in order to teach medical knowledge or skills to residents (Yaman, 2004). One of the most enthusiastic users of video games as teaching tools is the US military. The US Army created the Program Executive Office for Simulation, Training, and Instrumentation (PEO STRI), which now operates with an annual budget of more than $2 billion (Blake, 2007). This office is responsible for creating simulators for training soldiers from several branches of the armed forces in a variety of combat related skills, such as flying helicopters, using weapons systems, and firefighting. Similarly, the US Marines used a version of the commercial video game Doom to train Marines in teamwork, communication, and coordination (Prensky, 2001). Unintended Consequences of Violent Video Games Clearly, video games can teach a variety of subjects. However, concern has emerged that the same principles that make video games effective at teaching such a broad range of subjects to students, employees, and soldiers also make them effective at teaching potentially undesirable things that were not intended by their creators or by players. One of the primary concerns is the potential of violent video games to make those who play them more aggressive. This concern is particularly strong for children and adolescents, though the research literature has demonstrated that video games are capable of exerting similar effects on many age groups, including young adults, that are exposed to them (Anderson, Gentile, & Buckley, 2007). General Aggression Model To understand how video game violence influences aggression, it is useful to relate it to a theoretical explanation of aggression. The General Aggression Model (GAM) is a useful framework for examining these effects (e.g., Anderson & Bushman, 2002; Anderson & Carnagey, 2004; Anderson, Gentile, & Buckley, 2007; Anderson & Huesmann, 2003). GAM incorporates mechanisms from a variety of previous psychological theories (e.g., Cognitive Neoassociationism, Script Theory, and Social Learning Theory) that have been applied to the explanation of aggression. It is also useful for its ability to explain 4
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the short term processes responsible for aggression as well as the cyclical processes by which long term changes in aggression occur (see Figure I). Note that slight modifications of this theory can produce a General Learning Model (GLM). This model describes all forms of learning from social encounters, including positive effects of video games (for a more detailed description of GLM, see Buckley & Anderson, 2006).
Distal Causes & Processes
Biological Modifiers
Environmental Modifiers
Personality
Situation
Person Proximate Causes & Processes
Present Internal State
Social Encounter
Cognition Affect
Arousal
Appraisal Decision Behavior
Figure 1. The General Aggression Model (GAM) The short term, episodic model of aggression begins with two broad categories of input factors: person factors and situation factors. Person factors relevant to aggression include a variety of knowledge structures (e.g., belie~s, values, and attitudes) and other characteristics, such as sex, while situational factors could include having just played a violent video game or encountering a specific provocation. These person and situational factors lead to behavior through an individual's present internal state, consisting of cognition, affect, and arousal. For example, playing a violent video game could activate an existing aggressive script (a sequence of aggression related events so strongly associated through rehearsal that they become simultaneously activated, as though they were a single concept) making aggression in a subsequent situation more likely. These three components are highly interconnected, and may interact to produce behavioral outcomes. An individual's internal state leads to some type of decision process. Like most dual-process models of decision making and behavior (e.g., Strack & Deutsch, 2004) the initial internal reaction to an event is based on an immediate and automatic (relatively effortless) appraisal of the situation. If no further processing takes place, the resulting behavior is said to be impulsive. Thoughtful action results when an individual has sufficient resources (e.g., time, cognitive capacity) and desire (the outcome domain must be sufficiently
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UNINTENDED NEGATIVE CONSEQUENCES important and the immediate appraisal must be unsatisfying). The outcome o f the decision process determines whether an aggressive action i s taken, producing subsequent changes in the social situation, and potentially making further aggression mo likely to occur. According to CAM, repeated enco aggression may produce long term changes in an individual through processes such as observational learning, imitation, the rehearsal and reinforcement o f aggressive knowledge structures, and the extinction o f initially negative emotional reactions to the sights (e.g., blood and gore) and sounds (e.g., screams o f pain) o f violence. Repeated exposure to violent video games, for example, may lead to more aggressive attitudes, beliefs, scripts, perceptual and expectation schemata, and desensitization to aggression or violence. i n more global terms, repeated exposure to violent video games may increase cognitive and emotional factors known to increase the likelihood o f aggression and decrease factors known to inhibit aggression. Collectively, these relatively permanent cognitive and emotional changes increase the preparedness o f the individual to aggress against others. In other words, the person becomes more aggressive in general, 'an increase in trait aggressiveness. Such long term changes also can influence later situational context variables, as well. A boy who becomes more aggressive over time w i l l find himself in different (more conflict-filled) situations with teachers, parents, and peers. Research shows that aggressive children are likely to be rejected by less aggressive peers, leading to them spending more time with other highly aggressive children. Review o f Violent Video Game Effects Best Practices As with any research topic, results vary to some extent from one study to another. In some cases this i s due to different operationalizations o f variables, different populations sampled, or simply chance, but i t can also be due to methodological flaws present in some studies. A recent meta-analysis o f violent video game effects on aggression separated studies on the basis o f such methodological flaws i n order to compare the effects emerging from the studies with and without those flaws (Anderson, 2004; Anderson et al., 2004; see Appendix A for a list o f the flaws). This meta-analysis revealed that the average effect sizes were larger for studies without any o f the methodological flaws than for those studies which had at least one o f the methodological flaws (though the average effects were significantly larger than zero and were i n the same direction in both cases). The 'best practices' studies demonstrated a stronger effect o f video game violence than the 'not best practices' studies whether the dependent measure was aggressive behavior (r = .27 vs. r = .16), aggressive cognition (r = 2 7 vs. r = .20), or aggressive affect (r = .19 vs. r = .09; Anderson et al., 2004). This suggests that poorer methodology i n this domain leads to underestimates o f the effect size o f video game violence. Because the goal o f the current review i s to explicate the general
findings within the video game violence effects literature, we focus on those studies that meet the best practices standards set forth by Anderson et al. (2004). We do not mean to imply that studies with one o f more o f these methodological flaws make no important contributions to the overall research literature (some do, some do not), merely that the best practices studies better represent the true underlying relationships. The studies summarized in the following section were selected from the "best practices" studies to represent a broad range o f aggression related outcome measures (e.g., aggressive behavior, aggressive cognition) and different study design types (experimental, cross-sectional, or longitudinal). For a complete listing o f the best practices studies o f all o f these types, see Tables 1,2, and 3. Aggressive Behavior Experimental example. Carnagey and Anderson (2005, study 3) conducted an experimental study to test the hypothesis that rewarding (rather than punishing) video game players for in-game violence would result in a larger increase aggressive behavior. This study also served as an opportunity to conceptually replicate the findings o f previous researchers that violent video games increase aggression, relative to nonviolent video games. Undergraduate participants were randomly assigned to play one o f three versions o f a racing game, Cannageddon 2. I n the "reward" violent condition, participants were given points for running over pedestrians with their car. I n the "punish" violent condition, participants lost points for running over pedestrians in their car. I n the nonviolent condition, there were no pedestrians, making violence impossible. Before playing the game, participants wrote a brief essay on the topic o f abortion. They then completed an evaluation o f another essay supposedly written by another participant. Participants then played the assigned game for 20 minutes. After playing the game, participants received feedback on their essay supposedly written by the other participant. Actually, all participants rated the same essay and received the same highly insulting feedback as a provocation. Next, participants completed a modified version o f the Taylor Competitive Reaction-time Task (CRT) in which they competed against a fictitious opponent (they were told it was the same person who had rated their essay) to click a button faster i n a series o f competition trials. The participants were told that whoever was slowerto respond on each trial would receive a noise blast through their headphones, the duration and intensity o f which was to be set by their opponent before each trial. I n fact, there was no opponent and the participants won and lost in a predetermined pattern o f trials, receiving an ambiguous pattern o f noise blast intensities and durations on the trials they lost. The duration and intensity o f the noise blasts selected by the participant were combined to create the dependent measure o f aggression. Participants then completed a short questionnaire rating various aspects o f the game they had played before being probed for suspicion, debriefed, and dismissed. As hypothesized, those
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participants rewarded for violence behaved more aggressively than those punished for violence. Furthermore, participants assigned either of the violent game conditions were more aggressive than those assigned to the nonviolent game condition. Cross-sectional (correlational) example. One of Anderson et al.'s (2004) four new studies was a crosssectional study examining the effects of past violent video game exposure on aggressive behavior and cognition. The undergraduate participants completed the measures in a mass testing session in a large lecture hall. Violent video game exposure scores were computed for each participant based on participant ratings of the violence in their three favorite video games and multiplying by how often they had played each game (averaged across the three games). Participants also completed several personality questionnaires including measures of Goldberg's (1992) Big Five, narcissism, emotional susceptibility, and attitudes towards violence. Aggressive behavior was based on three
measures: the nine-item physical aggression subscale and the five-item verbal aggression subscale of the Buss Perry Aggression Questionnaire (described as "mild physical aggression" and "verbal aggression," respectively), and 10 violent behavior items from the National Youth Survey's delinquency items ("severe physical aggression). Analyses revealed video game violence scores to be related to all three measures of aggressive behavior even after controlling for sex and a host of personality variables. Longitudinal example. To date, the only longitudinal study of video game violence effects on aggression to meet the 'best practices' designation is Anderson, Gentile, and Buckley's (2007) study 3. This study examined the effects of video game violence exposure on a variety of factors such as verbal, physical, and relational aggression, prosocial behavior, peer rejection, and hostile attribution bias. Data were collected for the third-, fourth-, and fifthgrade participants at two times during the school year, approximately five months apart. Violent video game exposure scores were based on self-reported frequency and content of video game play. Participants completed additional self-report measures assessing hostile attribution bias, physical aggression, and parental involvement in media habits. Peer and teacher ratings of physical, verbal, and relational aggression, as well as prosocial behavior and grades were collected at both measurement times as well. The most important of the numerous findings was that video game violence exposure at Time I predicted physical aggression at Time 2 even when Time I physical aggression, total screen time, and parental involvement in media habits, as well as hostile attribution bias (as a mediating variable) and sex were statistically controlled. Collectively, these three studies illustrate many of the features common to the methodologically best studies of media violence effects. Regardless of the method or specific measures used, video game violence is found to increase aggressive behavior. The
converging operations show this effect to occur in both short term and long term contexts, and to represent a causal relationship. Aggressive Cognition Experimental example. Anderson and Dill (2000) study 2 examined the effect of video game violence on aggressive cognitions in an experimental context. Undergraduate participants came to the lab for two separate sessions. In the first session, they played either Wolfenstein 3D (violent) or Myst (nonviolent) for 15 minutes. These games were previously matched in pilot testing on various characteristics, such as difficulty, enjoyment, frustration, and action speed. Wolfenstein 3D is a first-person shooter game, whereas Myst is a nonviolent 3D walkthrough game. After playing the assigned game, participants complete the State Hostility Scale, video game ratings, and a World View Scale measuring beliefs about the likelihood of crime and feelings of safety. Participants then played their assigned video game for another 15 minutes. Next, the participant completed the reading reaction time task (RRT). For this task, 192 words are presented on the screen one at a time. These words are divided into four categories: 24 aggression words, 24 anxiety words, 24 escape words, and 24 control words (each word appearing twice). Participants must say the word aloud when it appears as quickly as possible. Faster reaction times suggest that a word is more cognitively accessible. The reaction time of aggressive words, as compared to the other three types of words, served as the measure of aggressive cognition. As hypothesized, participants who had played the violent video game demonstrated greater accessibility of aggressive cognitions than those who had played the nonviolent game, as measured by the reading reaction time. Cross-sectional (correlational) example. Anderson, Gentile, and Buckley, (2007) study 2 was a crosssectional study of violent media usage, attitudes towards violence, trait hostility, forgivingness, beliefs about aggression, and self-reported physically and verbally aggressive behaviors. High school students completed a series of questionnaires in their classrooms. Video game violence exposure was measured with the same scale used by Anderson et al. (2004). Participants also completed questionnaires measuring trait aggressiveness, forgivingness, and violent behavior. Aggressive cognitions were assessed with two different scales: the revised attitudes towards violence scale (reflecting a positive orientation towards aggression) and normative aggressive beliefs (reflecting beliefs that aggression is common). As expected, based on the fact that violent video games frequently involve fighting in a war context but seldom involve killing children, video game violence exposure was most strongly related to attitudes toward violence in war (r = .36) and only weakly (nonsignificantly) related to attitudes toward corporal punishment of children. Exposure also significantly predicted normative aggressive beliefs. Longitudinal example. The only longitudinal study measuring violent video game effects on aggressive cognition and meeting the best practices guidelines is
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Anderson, Gentile, and Buckley (2007) study 3, described earlier. A key aggressive cognition measure assessed hostile attribution bias. This measure requires participants to interpret ambiguous stories depicting acts which can potentially be interpreted as physical or relational aggression. Video game violence at Time 1 significantly predicted hostile attributional bias at Time 2, even after controlling for Time 1 hostile attribution bias and a host of other variables. Aggressive cognition (as assessed by hostile attribution bias) also proved to be a partial mediator o f the Time 1 video game violence effect on later aggressive behavior. Across a range o f studies, research designs, and measures, exposure to video game violence consistently leads to aggressive cognitions (Table 2). This i s a causal relationship that operates through both immediate short term and cumulative long term processes. Aggressive Affect Experimental example. Carnagey and Anderson (2005) study 1 measured the effects o f a violent video game on aggressive affect i n an experimental design with a college student population. This study was designed to test the effects o f video game violence (either rewarded or punished) on aggressive affect. Participants played one o f three versions o f the video game Cannageddon 2. The original version is a racing game in which points are awarded for running over pedestrians (the reward condition). Another condition in which points are subtracted for running over pedestrians (the punishment condition) was also used, as well as a version i n which there were no pedestrians (nonviolent). Aggressive affect was measured with the State Hostility Scale, on which participants rated their present feelings on a variety o f hostility related dimensions (e.g., I feel furious, I feel aggravated) on a five-point Likert-type scale ("strongly disagree" to "strongly agree"). Participants who had just played a violent video game (violence rewarded or punished) were more hostile than nonviolent game participants. Cross-sectional (correlational) example. Gentile, Lynch, Linder, and Walsh (2004) conducted a crosssectional study o f the relations between video game violence exposure, aggressive affect and several other variables in 8th- and 9th-grade students. Questionnaire measures were completed in a single session i n the classroom. Video game violence was based on ratings o f the level o f violence and frequency o f play for the participants' three favorite video games (as used by Anderson & Dill, 2000). Aggressive affect (trait hostility) was measured with the Cook & Medley Hostility Scale. Video game violence exposure was significantly positively correlated with trait hostility. N o longitudinal studies o f video game effects on aggressive affect have been conducted. The results from experimental and cross-sectional studies show that violent video games increase aggressive affect. The existing research suggests that the positive relation between video game violence exposure and aggressive affect i s causal. Longitudinal tests o f this relation would be useful, particularly to further test the hypothesis that repeated exposure to violent video
games increases trait hostility, though current crosssectional studies are suggestive o f long term effects, Desensitization to Violence Another potential unintended negative effect o f exposure to violent video games i s emotionall physiological desensitization to violence. Humans' normal physiological reactions to the sights (e.g., blood, severed body parts), sounds (screams o f anger, pain) and smells o f violence tend to be negative. This appears to be true whether witnessing actual violence, viewing images o f violence, or even thinking about real violence. This negative reaction serves as an inhibition to violence, affecting decision-making processes and behavioral choices. These automatic negative reactions also play a role in instigating helping behavior towards victims o f violence. Thus, the normal negative emotional and physiological reaction to violence decreases the likelihood o f aggressive behavior and increases the likelihood o f prosocial behavior towards violence victims. However, just as people can be desensitized to other fearful things, such as spiders, snakes, and the sights, sounds, and smells o f surgery, it i s also possible that violent media exposure can desensitize an individual to violence. When this desensitization occurs, the inhibitory effect on aggression and the facilitatory effects on prosocial behavior are diminished. Experimental example. One study that tested this prediction is Camagey, Anderson, and Bushman (2007). For this study, participants reported their general media habits and completed the Buss-Perry Aggression Questionnaire while baseline heart rate (HR) and galvanic skin response (GSR) measurements were taken. Participants were randomly assigned so that half played one o f four violent video games (Duke Nukem, Carmageddon, Mortal Kombat, or Future Cop), whereas the other half played a nonviolent game (Glider Pro, 3D Pinball, 3D Munch Man, or Tetra Madness). A l l participants played the assigned game for 20 minutes. After the game play period, additional H R and GSR measurements were taken. Finally, HR and GSR measurements were taken while the participants watched a 10 minute video clip o f real life violence. Participants who had played a violent video game showed decreases i n H R and GSR while observing real life violence, i n stark contrast to the increases by those who had played a nonviolent game. Cross-sectional (correlational) example. Further evidence for the potential o f violent video games to desensitize players to violence comes from a study by Bartholow, Bushman, and Sestir (2005). I n this study, participants varying in past history o f violent video game exposure were presented with a series o f negative photos, half violent and half nonviolent, interspersed among a set o f more numerous neutral photos, while event-related potentials (ERPs) were recorded. ERPs are scalp-recorded voltage fluctuations that represent neural activity associated with various information-processing operations. The P300 component-a positive voltage deflection occurring approximately 300 ms after stimulus onset-has been demonstrated to be positively related to
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UNINTENDED NEGATIVE CONSEQUENCES activation of the aversive motivational system (e.g., [to, aggressive and nonaggressive actions so that neural Larsen, Smith, & Cacioppo, 1998). Results demonstrated activations could be time-locked to those actions. that participants with a history of violent video game Engaging in virtual violent actions was related to exposure were significantly less physiologically suppressed activity in the anterior cingulate cortex and responsive to the violent images, compared to participants amygdala, structures known to play a key role in selfwith low prior violent game exposure. The specificity of regulation of behavior and emotional responses. Cross-sectional (correlational) example. There this emotional desensitization to violence was are no correlational studies that specifically focus on demonstrated by the lack of any relation between past video game effects. However, one recent study used a violent video game exposure and physiological composite measure of exposure to television and video responsiveness to the control or the negative nonviolent game violence, and related it to different patterns of images. Furthermore, this violent video game effect on overall frontal lobe activity (Matthews et al., 2005). desensitization remained significant after controlling for Two groups of adolescents, a subset with Disruptive individual differences in trait aggression. Interestingly, the Behavior Disorder with aggressive features (DBD) and high violent video game exposure participants also were a clinically normal subset, provided self-report data on more aggressive on a subsequent standardized laboratory violent television and video game exposure and then aggression task, and their P300 responses to violent completed a Stroop task while fMRI data were images predicted their aggressive behavior on this task. collected. Consistent with past research, it was Brain Activity and Imaging In recent years, social neuroscientists have predicted that the high-aggressive participants would determined that activity of certain brain structures is show diminished frontal lobe activity during the task related to aggressive thoughts, aggressive behavior, and relative to the control participants. Results supported impulse control. For example, suppression of the this prediction, demonstrating that the DBD anterior cingulate cortex, located in the medial frontal participants show reduced executive function compared lobe, has been linked to aggressive and anti-social to control participants. Of more relevance to the present behavior (e.g., Sterzer, Stadler, Krebs, Kleinschmidt, & article, a similar pattern was observed within the Poustka, 2003). Specifically, the anterior cingulate normal subset among participants high in self-reported cortex appears important various executive functions, media violence exposure. That is, control participants with high violent media exposure showed reduced including inhibition, performance monitoring, and possibly error correction. It is also involved in the frontal lobe activity during the performance of an evaluation of pain and distress (Luu, Collins, & Tucker, executive control task compared with participants low 2000). in violent media exposure. This included a reduction of activity in the anterior cingulate cortex, which was Media violence exposure may be linked to consistent with similar experimental studies (e.g., decreases in the activity of brain structures important for regulation of aggressive behavior and to increases Weber, Ritterfeld, & Mathiak, 2006). DBD participants with high violent media exposure also performed more in activity of structures linked to impulsive and poorly on the Stroop task than DBD participants with aggressive behavior (Carnagey, Anderson, & Bartholow, in press). For example, recent evidence low violent media .exposure, demonstrating that the from the movie domain has suggested that exposure to high media violence DBD participants had even lower violent scenes is associated with activation in different levels of executive functioning than DBD participants neural regions than exposure to nonviolent scenes with low media violence histories. (Murray et al., 2006). Children were shown violent and Conclusions nonviolent scenes from commercially-released movies A clear picture has emerged of the effects of while functional magnetic resonance images of the violent video games on aggressive affect, behavior, and brain (fMRI) were collected. Results demonstrated that cognition. Consistent with GAM, short term exposure violence viewing activated a network of brain regions to violent video games produces immediate increases in aggressive behavior, aggressive cognition, and (including precuneus, posterior cingulate, amygdala, aggressive affect; repeated exposure leads to the inferior parietal, and prefrontal and premotor cortex) involved in the regulation of emotion, arousal and development of stable individual differences in attention, memory encoding and retrieval, and motor aggressiveness. As Tables I, 2, and 3 and the summarized studies illustrate, a variety of methods programming. This network of activations may be converge to reveal detrimental effects of video game inked to increases in aggressive behavior associated with violent media exposure reported in many studies. violence on all of these outcomes. These effects are Experimental example. In the video game observed in children, adolescents, and young adults. domain, recent studies have provided evidence that Some aspects of violent video game effects warrant different parts of the brain' are activated when game increased future research attention. Despite the players engage in virtual violence compared with relatively important role ascribed to physiological virtual nonviolent actions (Weber, Ritterfeld, & desensitization as a mechanism for long term increases Mathiak, 2006). Male participants played a violent in aggressiveness, this area has received little research video game while fMRI data were collected. Gameplay attention. What research exists in this area (e.g., was recorded and analyzed frame-by-frame to Camagey, Anderson, & Bushman, 2007; Bartholow, determine when participants were engaging in Bushman, and Sestir, 2005) is supportive of the COGNITIVETECHNOLOGY
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predictions of G A M regarding desensitization. Similarly, even though recent research using functional brain imaging and violent media has been illuminating, more research in this area would undoubtedly be useful for clarifying the role o f specific neural structures and activities in contributing to or inhibiting aggression. Research identifying the neural substrates of the well documented violent video game effects will have an important impact on the scientific and public understanding of aggression References Anderson, C. A. (2004). An update on the effects of playing violent video games. Journal ofAdolescence,27, 1 13-122. Anderson, C. A,, & Bushman, B. J. (2002). Human aggression. Annual Review of Psychology, 53,27-51. Anderson, C. A., & Carnagey, N. L. (2004). Violent evil and the general aggression model. Chapter in A. Miller (Ed.) The Social Psychology of Good and Evil (pp. 168-192). New York: Guilford Publications. Anderson, C. A,, Carnagey, N. L., Flanagan, M., Benjamin, A. J., Eubanks, J., & Valentine, J. C. (2004). Violent video games: Specific effects of violent content on aggressive thoughts and behavior. Advances in Experimental Social Psychology, 36, 199-249. 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, 78,772-790. Anderson, C.A., & Ford, C.M. (1986). Affect of the game player: Short term effects of highly and mildly aggressive video games. Personality and Social Psychology Bulletin, 12, 390-402. Anderson, C.A., Gentile, D.A., & Buckley, K.E. (2007). Violent Video Game Effects on Children and Adolescents: Theory, Research, and Public Policy. New York: Oxford University Press. Anderson, C.A., & Huesmann, L.R. (2003). Human aggression: A social-cognitive view. In M.A. Hogg & J. Cooper (Eds.), Handbook of Social Psychology (pp. 296323). London: Sage Publications. Anderson, C.A., & Murphy, C.R. (2003). Violent videogames and aggressive behavior in young women. Aggressive Behavior, 29,423-429. Arriaga, P., Esteves, F., Carneiro, P., & Monteiro, M. B. (2006). Violent computer games and their effects on state hostility and physiological arousal. Aggressive Behavior, 32, 146- 158. Ballard, M. E., & Lineberger, R. (1999). Video game violence and confederate gender: Effects on reward and punishment given by college males. Sex Roles, 41, 541- 558. Ballard, M. E., & Wiest, J . R. (1996). Mortal Kombat (tm): The effects of violent videogame play on males' hostility and cardiovascular responding. Journal of Applied Social Psychology, 26, 7 17-730. Bartholow, B.D., Bushman, B.J., & Sestir, M.A. (2006). Chronic violent video game exposure and desensitization to violence: Behavioral and event-related brain potential data. Journal of Experimental Social Psychology, 42, 532-539. Bartholow, B.D., Sestir, M.A., & Davis, E.B. (2005) Correlates and consequences of exposure to videogame violence: Hostile personality, empathy and aggressive behavior. Personality and SocialPsychology Bulletin, 31, 1573-1586.
Blake, J.T. (2007). State of the PEO. Retrieved February 28th. 2007 from: http://www.peostri.army.mil/ABOUT US/ FILES/StateOfThePEO.pdf Brady, S. S., & Mathew K. A. (2006). Effects ofmedia violence on health-related outcomes among young men. Archives of Pediatric & Adolescent Medicine, 160,34 1-347. Buckley, K E., & Anderson, C.A. (2006). A Theoretical Model of the Effects and Consequences of Playing Video Games. Chapter in P. Vorderer & J. Bryant (Eds.), Playing Video Games - Motives, Responses, and Consequences (pp. 363-378). Mahwah, NJ: LEA. Business Week (Business Week Online.) (2007). On-the-job video gaming. Retrieved February 28th, 2007 from http://www.businessweek.com/magazine/content/0613/
b3977062.htm Carnagey, N. L., & Anderson, C. A. (2005). The effects of reward and punishment in violent video games on aggressive affect, cognition, and behavior. PsychologicalScience. 16, 882-889. Camagey, N. L., Anderson, C.A., & Bartholow, B.D. (in press). Media violence and social neuroscience: New questions and new opportunities. Current Directions in Psychological Science. Carnagey, N. L., & Anderson, C.A., Bushman, B.J. (2007). The effect of video game violence on physiological desensitization to real-life violence. Journal of Experimental Social Psychology, 43,489-496. Cicchirillo, V., & Chory-Assad, R.M. (2006). Effects of affective orientation and video game play on aggressive thoughts and behaviors. Journal of Broadcasting & Electronic Media, 49,435-449. Colwell, J., & Payne, J. (2000). Negative correlates of computer game play in adolescents. British Journal of Psychalogy, 91,295-3 10. Corbett, A.T., Koedinger, K.R., & Hadley W. (2001). Cognitive tutors: From the research classroom to all classrooms. In P.S. Goodman (Ed.), Technology Enhanced Learning (235263). Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Eastin, MS., & Griffiths, R.P. (2006). Beyond the shooter game: Examining presence and hostile outcomes among male game players. Communication Research, 33,448-466. ESA (Entertainment Software Association) (2007a). Retrieved February 25, 2007, from http://www.theesa. ~om/files/VideoGames-Final-pdf
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Eyal, K., Metzger, M. J., Lingsweiler, R. W., Mahood, C., & Yao, M. 2. (2006). Aggressive political opinions and exposure to violent media. Mass Communication & Society, 9, 399-27. Fleming, M.J., & Rickwood, D.J, (2001). Effects of violent versus nonviolent video games on children's arousal, aggressive mood, and positive mood. Journal ofApplied Social Psychology, 31,2047-2071. Flood, S. (2007). All play and more work. Retrieved February 28, 20407 from http://www.vnunet.com/ comuutin~/analvsis/2152597lplay-work Funk, J. B., Baldacci, H. B., Pasold, T., & Baumgardner, J. (2004) Violence exposure in real-life, video games, television, movies and the internet: is there desensitization? Journal ofAdolescence, 27,23-39.
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UNINTENDEDNEGATIVECONSEQUENCES Funk, J.B., Buchman, D.D., Jenks, J., & Bechtoldt, H. (2003). Playing violent video games, desensitization, Applied and moral evaluation in children. Developmental Psychology, 24,4 13-436. Funk, J. B., Hagan, J., Schimming, J., Bullock, W. A,, Buchman, D.D., & Myers, M. (2002). Aggression and psychopatholog in adolescents with a preference violent electronic games. Aggressive Behavior, 28, 134- 144. Gentile, D.A. & Gentile, J.R. (2005, April). Violent video games as exemplary teachers. Paper presented at the 2005 Society for Research in Child Development Biennial Conference, Atlanta, GA. 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 ofAdolescence, 27, 5-22. Goldberg, L. R. (1992). The development of markers for the Big-Five factor structure. Psychological Assessment, 4, 26-42. Graybill, D., Kirsch, J.R., & Esselman, E.D. (1985). Effects of playing violent versus nonviolent video games on the aggressive ideation of aggressive and nonaggressive children. Childstudy Journal, 15, 199-205. Hagell, A., & Newbum, T. (1994). Young offenders and the London: Policy media: Viewing habits and .preferences. . Studies institute. Hemphill, J.F. (2003). Interpreting the magnitudes of correlation coefficients. American Psychologist. 58,78-79. Hind. P.A. (1995). A study of reported satisfaction with differentially aggressive computer games amongst incarcerated young offenders. Issues in Criminological & LegalPsychology, 22, 28-36. Irwin, A.R., & Gross, A.M. (1995). Cognitive tempo, violent video games, and aggressive behavior in young boys. Journal of Family Violence, 70,337-350. 110, T.A., Larsen, J.T., Smith, N.K., & Cacioppo, J.T. (1998). Negative information weighs more heavily on the brain: The negativity bias in evaluative categorizations. Journal of Personality andSocialPsychology, 75,887-900 Kirsh, S.J. (1998). Seeing the world through Mortal Kombatcolored glasses: Violent video games and the development of a short-term hostile attribution bias. Childhood: A Global Journal of Child Research. 5, 177- 183. Kirsh, S.J., & Mounts, J.R. (in press). Violent video game play impacts facial emotion recognition. Aggressive Behavior. Kirsh, S. J., Olczak, P. V., & Mounts, J. R. (2005). Violent video games induce an affect processing- bias. Media Psycho& 7,239-250. Konijn, E. A,, Bijnank, M. N., & Bushman, B. J. (in press). 1 wish 1 were a warrior: The role of wishful identification in the effects of violent video sames on aeeression in adolescent boys. ~evelopmental>sychology~Krahe, B., & Moller, I. (2004). Playing violent electronic games, hostile attributional style, and aggression relatednorms in German adolescents. Journal of Adolescence, 27,53-69. Lieberman, D.A. (1997). Interactive video games for health promotion: Effects on knowledge, self-efficacy, social support, and health. In R.L. Street Jr., & W.R. Gold, (Eds) Health promotion and interactive technology: Theoretical applications and future directions. LEA'S communication series (pp. 103-120). Mahwah, NJ: Lawrence Erlbaum Associates, Publishers.
Luu, P., Collins, P., & Tucker, D.M. (2000). Mood, personality, and self-monitoring: Negative affect and emotionality in relation to frontal lobe mechanisms of error monitoring. Journal of Experimental Psychology: General. 129,4340. Matthews, V . P., Kronenberger, W.G., Want, Y., Lurito, J. T., Lowe, M.J., & Dunn, D.W. (2005). Media violence exposure and frontal lobe activation measure by functional magnetic resonance imaging in aggressive and nonaggressive adolescents. Journal of Computer Assisted Tomography, 29, 287-292. McPherson, A.C., Glazebrook, C., Forster, D., James, C., & Srnyth, A. (2006). A randomized, controlled trial of an interactive educational computer package for children with asthma. Pediatrics, 117. 1046-1054. MPAA (Motion Picture Association of America) (2007). Retrieved February 25, 2007, from http://www.mpaa. org/researchStatistics.asp Murray, J. P., Liotti, M., Mayberg, H. S., Pu, Y., Zamarripa, F., Liu, Y., Woldorff, M. G., Gao, J.H., & Fox, P.T. (2006). Children's brain activations while viewing televised violence revealed by fMRI. Media Psychology, 8. 25-37. Panee, C.D., & Ballard, M.E. (2002). High versus low aggressive priming during video game training: Effects on violent action during same play. hostility. heart rate. and blood pressure. Journal of .. Social Psychology, 32,2458-2474. Prensky, M. (2001). Digital Game-Based Learning. New York: McGraw Hill. Schutte, N. S., Malouff, J.M., Post-Gorden, J C., & Rodasta, A.L. (1988). Effects of playing video games on children's aggressive and other behaviors. Journal of Applied Social Psychology, 18, 454-460. Sheese, B.E., & Graziano, W.G. (2005) Deciding to defect: The effects of video-game violence on cooperative behavior. PsychologicalScience, 16,354-357. Sterzer, P., Stadler, C., Krebs, A,, Kleinschmidt, A,, & Poustka, F. (2003).'Reduced anterior cingulated activity in adolescents with antisocial conduct disorder confronted with affective pictures. Neurolmage, 19,23. Strack, F., & Deutsch, R. (2004). Reflective and Impulsive Determinants of Social Behavior, Personality and Social Psychology Review, 8, 220-247. Uhlmann, E., & Swanson, J. (2004). Exposure to violent video games increases automatic aggressiveness. Journal ofAdolescence, 27,4 1-52. Walsh, D., Gentile, D., Gieske, J., Walsh, M., & Chasco, E. (2003, December). Eighth Annual Video Game Report Card. National Institute on Media and the Family. Weber, R., Ritterfeld, U., & Mathiak, K. (2006). Does playing violent video games induce aggression? Empirical evidence of a functional magnetic resonance imaging study. Media Psychology, 8, 39-60. Wiegman, O., & van Schie, E. M. G. (1998). Video game playing and its relations with aggressive and prosocial behavior. British Journal ojSocial PsychoIogy,37, 367378. Yaman, D. (2004). Why games work. Retrieved May 2,2004 from http://leamingware.com/clients/gameswork.html Ybarrondo, B.A. (1984). A Study of the Effectiveness of Computer-Assisted Instruction in the High School Biology Classroom. Idaho. (ERIC Document Reproduction Service No. ED265015).
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Table 1. Best practices studies of violent video game effects on aggressive behavior, broken down by study design.
A~gressiveBehavior: Cross-sectional Studies BPAQ- Physical Aggression
Anderson et al (2004) Anderson et al. (2004)
] ~ ~ ~ - ~ i obehavior lent
Anderson & Dill (2000)
Large College students 1college students
~edium Positive
College students
Large
I ~ a r $ ePositive
I
1
1
NYS-Violent behavior
IBPAO- Physical
Large Postttve [Large
~.
Eyal et al. (2006) Funk, Hagan, Schimming, Bullock, Buchman, & Myers (2002)
Aggression Self-repon aggressive behavior
I ~ o t l e s estudents
I
I
Children
~ a r x ePositive Very small
Medium Positive
Large
Large Positive
Aggressive Behavior: Longitudinal Studies Anderson. Gentile, & Buckley (2007)
Physical aggression (self, peer, and teacher reported) Children
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Table 2. Best p r a c t i c e s s t u d i e s o f v i o l e n t video game e f f e c t s on aggressive cognition, b r o k e n down by s t u d y d e s i g n . Aggressive Cognition: Experimental Studies stud\ Anderson et al (2004)
~utcome measure Word completion task
~ o [sample ~ size [VCV ~ ~ e s u~l t s [college students [Medium Positive
I
I
College students Large
Large Positive
College students Large College students Small College students Small
Small Positive Medium Positive Very Small Positive
ast tin & Griffiths (2006)
Reading Reaction-time Task (RRT) Story completion task Hostile Attribution Bias Word completion task Word completion task Stow . w m ~. l e t i o ntask Hostile [~xpectationBias
[~htldren
l~ar~e
~edium Positive
Gra\ hill Kirsch, & Esselman (1985)
Rosenzweig Picture-Frustration Study
Children
Medium
Large Positive
Kirsh (1998)
Ambiguous provocation story responses Children
Small
Medium Positive
Kirsh. Olczak. & Mounts (2005)
Genov Modified Stroop Task (GMST) Dynamic Emotion Identification Task (DEIT) Implicit Association Test
Anderson & Dill (2000)
-
Bushman & Anderson (2002) Camagey & Anderson (2005) Cicchinllo & Chory-Assad (2006)
-
Kirsh & Mounts (in press) Uhlmann & Swanson (2004)
I
I
~
mall
College students Medium
Medium Positive
College students Large College studenis Medium
Small Positive Medium Positive
t
1
Aggressive Cognition: Cross-sectional Studies Anderson el al. (2004)
Attitudes towards Violence scale (ATVS) College students Large Adolescent Attitudes towards Violence Anderson el al. (2004) Scale (AATVS) College students Large Revised Attitudes towards Violence Scale (RATVS) and Normative Aggressive High school Anderson, Gentile. & Buckley (2007) Beliefs Large students
Medium Positive Large Positive
Small Positive
Baumgardner (2004) Funk- Buchman, Jenks, & Bechtoldt (2003) Gentile. Lynch. Lmder & Walsh
Children)
Children
Medium
Large Positive
Aggressive responses to vignettes
Children
Small
Very Small Positive
Krahe & Moller (2004) Uhlmann & Swanson (2004)
attrihutional style) implicit Association Test
--
18th graders ILarge' [college students [Medium
~ m a lPositive l [ ~ a r g ePositive
Aggressive Cognition: Longitudinal Studies Sample size Study
Outcome measure l ~ t o winteroretations (Hostile ~al ~nderson,Gentile, & Buckley (2007) ~ n r ~ h u t i oBias)
Appendix A Nine methodological flaws taken from (Anderson et at., 2004, p. 238) I) Nonviolent video game condition contained violence, and there was no suitable nonviolent control condition. 2) Violent video game condition contained little orno violence, study, the measure of "ideo game exposure 3) a was not specifically tied to violent video games (e.g., the amount of time spent on any kind ofvideo game was measured instead oftime spent on violent video games). 4) Evidence that the violent and nonviolent conditions differed significantly in ways that could contaminate the conditions, such as the nonviolent condition being more difficult, boring, or frustrating than the violent condition. 5 ) A pre-post d e s i e was used, but only the of the and postmanipulation measures was reported. 6) E ~ & session inwived both a video fame piaver and an &ver,&on~~ava%eof~player
Outcome measure
ropulation
Anderson & Ford (1986)
State hosttlity (MAACL)
College students
san'p'e Small
Anderson & Murphy (20031 m i , Esteves, Carneiro, & Monteiro (20061
Revenge motivation (Self-reported)
Female college students
Small
Small Positive
State hostility (State Hostility Scale)
College students
Small
Small Positive
Vey small
'Ize
Results
Large Positive
Ballard& Wiest (1996)
State Hostility (Adjective Checklist)
Male college students
Brady & Malhews (2006)
l~educedProfile o f Mood Stales
Male college students
Camagey & Anderson (2005)
College students
Small
Medium Positive
Fleming & RicLnood (20011
State hostility (State Hostility Scale) State anger (State-Trait Anger Expression Inventory)
Children
Small
Medium Positive
Pance & Ballard (2002)
Bell Adjustment Inventory (2002)
Male college students
Very small
Large Positive
Large Positive Medium Positive
Aggressive Affect: Cross-sectional Studies
Bartholow. Sestir, & Davis (2005)
'
Bartholow, Sestir, & Davis (2005) Gentile. Lynch. tinder. & Walsh (2004)
ale college students lL^'
IBPAQ- Hostility
BPAQ- Anger l ~ a l college e students Trait hostility (Cook & Medley Hostility Scale) 8th & 9th graders
Phvsioloeical Desensitization: Experimental Studies Heart Rate (HR) and Galvanic Skin Camagey, Anderson, & Bushman (2007) Response (GSR)
lLage
Small Positive
Lar$e
Medium Positive
Large
Small Positive
~ o l l e g estudents
Ivery Small
ILarge Positive
Young adult males
Very Small
Positive
Adolescents
Very Small
Positive
College students
Physiological Desensitization: Cross-sectional Studies l ~ v e nrelated t brain potentials (ERPs - 1 1
bart tho low, Bushman, & Scstir (2006)
1~3001
Brain Activity and Imaging; Experimental Studies N R l : Anterior cingulate cortex (ACC) Weber, Ritterfeld. & Mathiak (2006) and Amygdala
/very Small Positive
1
1
1
Brain Activib and [maginx: Cross-sectional
Mathews et al. (2005)
tMRl: Anterior cingulate cortex (ACC) and left inferior frontal gyms (IFG)
The results of the studies reported in Tables 1, 2, and 3 with respect to video game violence (VGV) indicate both the direction of the findings (positive or negative) and their magnitude (very small, small, medium, or large). A positive finding indicates that exposure to violent video games was shown to increase the outcome measure for the relevant aggression variable (e.g., aggressive cognition), whereas a negative finding indicates that exposure decreased the aggression related variable. The descriptive report of the effect sizes is based on Hemphill's (2003) review of 380 psychological meta-analyses. Absolute effect sizes (in r+ terms) of .30 or larger are labeled "large." lr+l .2 to .29 = "medium." lr+l .I to . I 9 = "small." lr+l < .I = "very small." Because of the way data are analyzed in
fMR1 studies, effect sizes could not be estimated. Sample size 2 175 = "large." Sample size 100 to 174 = "medium." Sample size 50 to 99 = "small." Sample size < 50 = "very small." A substantial proportion of the studies included in Tables 1, 2, and 3 (41.8%) were conducted by Craig Anderson, Douglas Gentile, Brad Bushman, and several others, who have all conducted research at Iowa State University. However, as the studies in these tables demonstrate, the direction of the violent video game and aggression relationship found in the studies of these researchers (positive) is consistent with the best practices studies conducted by researchers not affiliated with Iowa State University.
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