violence in video games research articles

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The contagious impact of playing violent video games on aggression: Longitudinal evidence

Tobias greitemeyer.

1 Department of Psychology, University of Innsbruck, Innsbruck Austria

Meta‐analyses have shown that violent video game play increases aggression in the player. The present research suggests that violent video game play also affects individuals with whom the player is connected. A longitudinal study ( N  = 980) asked participants to report on their amount of violent video game play and level of aggression as well as how they perceive their friends and examined the association between the participant's aggression and their friends’ amount of violent video game play. As hypothesized, friends’ amount of violent video game play at Time 1 was associated with the participant's aggression at Time 2 even when controlling for the impact of the participant's aggression at Time 1. Mediation analyses showed that friends’ aggression at Time 1 accounted for the impact of friends’ amount of violent video game play at Time 1 on the participant's aggression at Time 2. These findings suggest that increased aggression in video game players has an impact on the player's social network.

1. INTRODUCTION

Given its widespread use, the public and psychologists alike are concerned about the impact of violent video game play. In fact, a great number of studies have addressed the effects of exposure to violent video games (where the main goal is to harm other game characters) on aggression and aggression‐related variables. Meta‐analyses have shown that playing violent video games is associated with increased aggression in the player (Anderson et al., 2010 ; Greitemeyer & Mügge, 2014 ). The present longitudinal study examines the idea that violent video game play also affects the player's social network, suggesting that concern about the harmful effects of playing violent video games on a societal level is even more warranted.

1.1. Theoretical perspective

When explaining the effects of playing violent video games, researchers often refer to the General Aggression Model (GAM) proposed by Anderson & Bushman ( 2002 ). According to this theoretical model, person and situation variables (sometimes interactively) may affect a person's internal state, consisting of cognition, affect, and arousal. This internal state then affects how events are perceived and interpreted. Based on this decision process, the person behaves more or less aggressively in a social encounter. For example, playing violent video games is assumed to increase aggressive cognition and affect, which in turn results in behavioral aggression. An extension of this model further assumes that increased aggression due to previous violent video game play may instigate an aggression escalation cycle in that the victim also behaves aggressively (cf. Anderson & Bushman, 2018 , Figure 5). The present research tested key predictions derived from the GAM and its extension, that (a) violent video game play is associated with increased aggression in the player and that (b) individuals who are connected to the player will also become more aggressive.

1.2. Effects of violent video game play on aggression

The relationship between violent video game play and aggression has been examined in studies employing cross‐sectional, longitudinal, and experimental designs. Cross‐sectional correlational studies typically show a positive relationship between the amount of violent video game play and aggression in real‐world contexts (e.g., Gentile, Lynch, Linder, & Walsh, 2004 ; Krahé & Möller, 2004 ). Several longitudinal studies have been conducted, showing that habitual violent video game play predicts later aggression even after controlling for initial aggressiveness (e.g., Anderson, Buckley, & Carnagey, 2008 ). That violent video game play has a causal impact on aggression and related information processing has been demonstrated by experimental work (e.g., Anderson & Carnagey, 2009 ; Gabbiadini & Riva, 2018 ). Finally, meta‐analyses corroborated that violent video game play significantly increases aggressive thoughts, hostile affect, and aggressive behavior (Anderson et al., 2010 ; Greitemeyer & Mügge, 2014 ). Some studies failed to find significant effects (e.g., McCarthy, Coley, Wagner, Zengel, & Basham, 2016 ). However, given that the typical effect of violent video games on aggression is not large, it is to be expected that not all studies reveal significant effects.

1.3. The contagious effects of aggression

Abundant evidence has been collected that aggression and violence can be contagious (Dishion, & Tipsord, 2011 ; Huesmann, 2012 ; Jung, Busching, & Krahé, 2019 ). Indeed, the best predictor of (retaliatory) aggression is arguably previous violent victimization (Anderson et al., 2008 ; Goldstein, Davis, & Herman, 1975 ). However, even the observation of violence can lead to increased violence in the future (Widom, 1989 ). Overall, it is a well‐known finding that aggression begets further aggression. Given that violent video game play increases aggression, it thus may well be that this increased aggression then has an impact on people with whom the player is connected.

Correlational research provides initial evidence for the idea that the level of people's aggression is indeed associated with how often their friends play violent video games (Greitemeyer, 2018 ). In particular, participants who did not play violent video games were more aggressive the more their friends played violent video games. However, due to the cross‐sectional design, no conclusions about the direction of the effect are possible. It may be that violent video game players influence their friends (social influence), but it is also conceivable that similar people attract each other (homophily) or that there is some shared environmental factor that influences the behavior of both the players and their friends (confounding). That is, it is unclear whether indeed aggression due to playing violent video games spreads or whether the effect is reversed, such that aggressive people are prone to befriend others who are attracted to violent video game play. Moreover, it is possible that some third variable affected both, participants’ reported aggression and their friends’ amount of violent video game play. There is also the possibility that people are unsure about the extent to which their friends play violent video games. In this case, they may perceive their friends as behaving aggressively and then (wrongly) infer that the friends play violent video games. To disentangle these possibilities and to show that the effect of violent video game play (i.e., increased aggression in the player) indeed has an impact on the player's social network, relationships among variables have to be assessed over time while covarying prior aggression (Bond & Bushman, 2017 ; Christakis & Fowler, 2013 ).

Verheijen, Burk, Stoltz, van den Berg, and Cillessen ( 2018 ) tested the idea that players of violent video games have a long‐term impact on their social network. These authors found that participants’ exposure to violent video games increased their friend's aggressive behavior 1 year later. However, given that the authors did not examine whether the violent video game player's increased aggression accounts for the impact on their friend's aggressive behavior, it is unknown whether violent video game play indeed instigates an aggression cycle. For example, players of violent video games may influence their friends so that these friends will also play violent video games. Any increases in aggression could then be an effect of the friends playing violent video games on their own.

1.4. The present research

The present study examines the longitudinal association between the participant's aggression and their friends’ amount of violent video game play, employing an egocentric networking approach (Stark & Krosnick, 2017 ). In egocentric networking analyses, participants provide self‐reports but also report on how they perceive their friends. In the following, and in line with Greitemeyer ( 2018 ), the friends were treated as the players and the participant was treated as their friends’ social network. Please note that ties between the participant's friends (i.e., whether friends also know each other) were not assessed (Greitemeyer, 2018 ; Mötteli & Dohle, 2019 ), because this information was not needed for testing the hypothesis that participants become more aggressive if their friends play violent video games. It was expected that friends’ amount of violent video game play at Time 1 would predict the participant's aggression at Time 2 even when controlling for the impact of the participant's aggression and amount of violent video game play at Time 1. It was further examined whether friends’ aggression at Time 1 would account for the impact of friends’ amount of violent video game play at Time 1 on the participant's aggression at Time 2. Such findings would provide suggestive evidence that violent video game play may instigate an aggression cycle. The study received ethical approval from the Internal Review Board for Ethical Questions by the Scientific Ethical Committee of the University of Innsbruck. The data and materials are openly accessible at https://osf.io/jp8ew/ .

2.1. Participants

Participants were citizens of the U.S. who took part on Amazon Mechanical Turk. Because it was unknown how many of the participants will complete both questionnaires, no power analyses were conducted a priori but a large number of participants was run. At Time 1, there were 2,502 participants (1,376 females, 1,126 males; mean age = 35.7 years, SD =  11.8). Of these, 980 participants (522 females, 458 males; mean age = 38.9 years, SD =  12.5) completed the questionnaire at Time 2. Time 1 and Time 2 were 6 months apart. There were no data exclusions, and all participants were run before any analyses were performed. The questionnaire included some further questions (e.g., participant's perceived deprivation) that are not relevant for the present purpose and are reported elsewhere (Greitemeyer & Sagioglou, 2018 ). 1 Given that the questionnaire was relatively short, no attention checks were employed.

2.2. Procedure and measures

Procedure and measures were very similar to Greitemeyer ( 2018 ), with the main difference that individuals participated at two time points (instead of one). After providing demographics, self‐reported aggressive behavior was assessed. As in previous research (e.g., Krahé & Möller, 2010 ), participants indicated for 10 items how often they had shown the respective behavior in the past 6 months. Sample items are: “I have pushed another person” and “I have spread gossip about people I don't like” (5 items each address physical aggression and relational aggression, respectively). All items were rated on a scale from 1 ( never ) to 5 ( very often ), and scores were averaged. Participants were then asked about their amount of violent video game play, employing one item: “How often do you play violent video games (where the goal is to harm other game characters)?” (1 =  never to 7 =  very often ).

Afterwards, participants learned that they will be asked questions about people they feel closest to. These may be friends, coworkers, neighbors, relatives. They should answer questions for three contacts with whom they talked about important matters in the last few months. For each friend, they reported the level of aggression (αs between = 0.90 and 0.91) and the amount of violent video game play, employing the same questions as for themselves. Responses to the three friends were then averaged. Finally, participants were thanked and asked what they thought this experiment was trying to study, but none noted the hypothesis that their friend's amount of violent video game play would affect their own level of aggression. At Time 2, the same questions were employed. Reliabilities for how participants perceived the level of aggression for each friend were between 0.89 and 0.90.

Descriptive statistics, intercorrelations, and internal consistencies of all measures are shown in Table ​ Table1 1 .

Means, standard deviations, and bivariate correlations

Note : For Time 1, N  = 2,502; for Time 2, N  = 980. All correlation coefficients: p  < .001. Where applicable, α reliabilities are presented along the diagonal.

3.1. Time 1 ( N  = 2,502)

The relationship between the amount of violent video game play and reported aggression was significant, both for the participant and the friends. That is, violent video game play was associated with increased aggression in the player and participants perceived their friends who play more violent video games to be more aggressive than their less‐playing friends. Participant's and friends’ amount of violent video game play as well as their level of reported aggression, respectively, were also positively associated, indicating that participants perceived their friends to be similar to them. Most importantly, participant's aggression was significantly associated with friends’ amount of violent video game play. 2

It was then examined whether friends’ amount of violent video game play is still associated with the participant's aggression when controlling for the participant's amount of violent video game play. Participant sex (coded 1 = male, 2 = female) and age were included as covariates. In fact, a bootstrapping analysis showed that the impact of friends’ amount of violent video game play remained significant (point estimate = 0.08, SE  = 0.02, t  = 4.72, p  < .001, 95% confidence interval [CI] = [0.05, 0.11]). Participant's amount of violent video game play (point estimate = 0.03, SE  = 0.01, t  = 2.18, p  = .029, 95% CI = [0.00, 0.05]) and the interaction were also significant (point estimate = −0.01, SE  = 0.00, t  = 2.41, p  = .016, 95% CI = [−0.02, −0.00]). At low levels of the participant's amount of violent video game play (− 1 SD, equals that the participant does not play violent video games in the present data set), friends’ amount of violent video game play was associated with the participant's aggression (point estimate = 0.07, SE  = 0.01, t  = 5.06, p  < .001, 95% CI = [0.04, 0.10]). At high levels of the participant's amount of violent video game play ( + 1 SD), friends’ amount of violent video game play was also associated with the participant's aggression (point estimate = 0.03, SE  = 0.01, t  = 3.14, p  = .002, 95% CI = [0.01, 0.06]), but the effect was less pronounced. Participants were thus most strongly affected by whether their social network plays violent video games when they do not play violent video games themselves (Figure ​ (Figure1). 1 ). Participant sex was not significantly associated with the participant's aggression (point estimate = −0.04, SE  = 0.02, t  = 1.95, p  = .052, 95% CI = [−0.09, 0.00]), whereas age was (point estimate = −0.01, SE  = 0.00, t  = 7.84, p  < .001, 95% CI = [−0.009, −0.005]).

Simple slopes of the interactive effect of friends’ amount of violent video game play and the participant's amount of violent video game play on the participant's aggression, controlling for participant sex and age (Time 1, N  = 2,502)

3.2. Time 1 and Time 2 ( N  = 980)

To examine the impact of friends’ amount of violent video game play on the participant's aggression over time, a cross‐lagged regression analysis was performed on the data. Participant's amount of violent video game play, friends’ amount of violent video game play, participant's aggression at Time 1, as well as participant sex and age were used as predictors for participant's aggression at Time 2. The overall regression was significant, F (5,974) = 68.92, R 2  = 0.26, p  < .001. Most importantly, friends’ amount of violent video game play at Time 1 significantly predicted participant's aggression at Time 2, t  = 2.60, β  = .09, 95% CI = (0.02, 0.16), p  = .009. Participant's aggression showed high stability, t  = 16.77, β  = .48, 95% CI = (0.42, 0.53), p  < .001, whereas the participant's amount of violent video game play at Time 1 did not significantly predict the participant's aggression at Time 2, t  = 1.77, β  = −.07, 95% CI = (− 0.14, 0.01), p  = .077 (Figure ​ (Figure2 2 ). 3 , 4 Participant sex also received a significant regression weight, t  = 2.08, β  = −.06, 95% CI = (−0.12, −0.00), p  = .038, whereas age did not, t  = 1.93, β  = −.06, 95% CI = (−0.12, 0.00), p  = .054. The reverse effect that the participant's aggression at Time 1 predicts their friends’ amount of violent video game play at Time 2 when controlling for the participant's amount of violent video game play and friends’ amount of violent video game play at Time 1, as well as participant sex and age, was not significant, t  = 0.67, β  = .02, 95% CI = (−0.03, 0.06), p  = .504.

Participant's aggression at Time 2 simultaneously predicted by friends’ amount of violent video game play, participant's aggression, and participant's amount of violent video game play at Time 1. Participant sex and age were controlled for, but were not included in the figure (see the main text for the impact of participant sex and age). * p  < .01, ** p  < .001 ( N  = 980)

Finally, it was examined whether the impact of friends’ amount of violent video game play at Time 1 on the participant's aggression at Time 2 would be mediated by friends’ level of aggression at Time 1 (while controlling for the participant's aggression and amount of violent video game play at Time 1 as well as participant sex and age). A bootstrapping analysis (with 5.000 iterations) showed that the impact of friends’ level of aggression at Time 1 on the participant's aggression at Time 2 was significant (point estimate = 0.16, SE  = 0.04, t  = 4.28, p  < .001, 95% CI = [0.09, 0.23]). Participant's aggression at Time 1 was also a significant predictor (point estimate = 0.34, SE  = 0.03, t  = 10.19, p  < .001, 95% CI = [0.27, 0.40]). Friends’ amount of violent video game play at Time 1 (point estimate = 0.03, SE  = 0.01, t  = 1.82, p  = .069, 95% CI = [−0.00, 0.05]) and participant's amount of violent video game play at Time 1 (point estimate = −0.01, SE  = 0.01, t  = 1.65, p  = .099, 95% CI = [−0.03, 0.00]) were not significant predictors. Participant sex significantly predicted the participant's aggression at Time 2 (point estimate = −0.06, SE  = 0.03, t  = 2.31, p  = .021, 95% CI = [−0.11, −0.01]), whereas age did not (point estimate = −0.00, SE  = 0.00, t  = 1.90, p  = .058, 95% CI = [−0.00, 0.00]). The indirect effect was significantly different from zero (point estimate = 0.01, 95% CI = [.00, 0.02]), suggesting that participants are more aggressive if their friends play violent video games for the reason that these friends are more aggressive. Figure ​ Figure3 3 displays a simplified version of this mediation effect, based on regression coefficients and without controlling for the participant's aggression at Time 1, the participant's amount of violent video game play at Time 1, participant sex, and age.

Mediation of the impact of friends’ violent video game exposure (VVE) at Time 1 on the participant's aggression at Time 2 by friends’ aggression at Time 1. All paths are significant. β * = the coefficient from friends’ VVE at Time 1 to the participant's aggression at Time 2 when controlling for friends’ aggression at Time 1 ( N  = 980)

4. DISCUSSION

Violent video games have an impact on the player's aggression (Anderson et al., 2010 ; Greitemeyer & Mügge, 2014 ), but—as the present study shows—they also increase aggression in the player's social network. In particular, participants who do not play violent video games reported to be more aggressive the more their friends play violent video games. Mediation analyses showed that the increased aggression in the friends accounted for the relationship between friends’ amount of violent video game play and the participant's aggression. Because changes in aggression over time were assessed, the present study provides evidence for the hypothesized effect that violent video game play is associated with increased aggression in the player, which then instigates aggression in their social network. Importantly, the impact of the participant's amount of violent video game play was controlled for, indicating that the relationship between friends’ amount of violent video game play and the participant's aggression is not due to the friends being similar to the participants. Moreover, the reverse effect that aggressive people will become attracted to others who play violent video games was not reliable. The present research thus documents the directional effects that violent video games is associated with increased aggression in the player and that this increased aggression then has an impact on people with whom the player is connected.

Overall, the present study provides comprehensive support for key hypotheses derived from the GAM and its extension (Anderson & Bushman, 2018 ). It shows that violent video game play is associated with increased aggression in the player and it documents that others who are connected to players might be also affected even when controlling for their own amount of violent video game play. To the best of my knowledge, this study is the first that shows that because violent video game players are more aggressive their friends will become aggressive, too. Previous research either employed a cross‐sectional design and thus could not address the direction of the effect (Greitemeyer, 2018 ) or did not examine whether the effect of violent video game play (i.e., increased aggression) indeed spreads (Verheijen et al., 2018 ). As proposed by the GAM and its extension (Anderson & Bushman, 2018 ), increased aggression in violent video game players appears to instigate an aggression escalation cycle (cf. Anderson et al., 2008 ).

It is noteworthy, however, that the longitudinal effect of the participant's amount of violent video game play at Time 1 on the participant's aggression at Time 2 was not reliable. Hence, although there were significant correlations between participants’ aggression and their violent video game use at both time points, the present study does not show that repeatedly playing violent video games leads to long‐term changes in aggression. However, a recent meta‐analysis of the long‐term effects of playing violent video games confirmed that violent video game play does increase physical aggression over time (Prescott, Sargent, & Hull, 2018 ), although the effect size was relatively small ( β  = 0.11) and thus single studies that produce nonsignificant results are to be expected. Importantly, in the present study, a single‐item measure of violent video game play was employed. In contrast, previous research on the relationship between violent video game play and the player's aggression has often employed multi‐item measurement scales that are typically more reliable and precise (for an overview, Busching et al., 2015 ). Hence, it may well be that due to the limitations of the single‐item measure of the participant's amount of violent video game play the relationship between participants’ violent game play and their aggressive behavior was artificially reduced.

Even though the longitudinal design allows ruling out a host of alternative explanations for the impact of violent video games on the player's social network, causality can only inferred by using an experimental design. Future research may thus randomly assign participants to play a violent or nonviolent video game (players) and assesses their aggression against new participants (partners). It can be expected that the partners suffer more aggression when the player had played a violent, compared to a nonviolent, video game. Afterwards, it could be tested whether the partner of a violent video game player is more aggressive than a partner of a nonviolent video game player. Given that the partner is not exposed to any video games, firm causal conclusions could be drawn that violent video game play affects aggression in people who are connected to violent video game players. It could be also tested whether the partner of a violent video game player would not only be more likely to retaliate against the player, but also against a third party. In fact, previous research into displaced aggression has shown that people may react aggressively against a target that is innocent of any wrongdoing after they have been provoked by another person (Marcus‐Newhall, Pedersen, Carlson, & Miller, 2000 ). It may thus well be that the effect of playing violent video games spreads in social networks and that even people who are only indirectly linked to violent video game players are affected.

An important limitation of the present egocentric network data is the reliance on the participant's perception of their social network, leaving the possibility that participants did not accurately perceive their friends. It is noteworthy that participants perceived their friends to be highly similar to them. In this regard, it is important to keep in mind that participants always provided self‐ratings first, followed by perceptions of their friends. It is thus conceivable that participants used their self‐ratings as anchors for the perceptions of their friends. Such a tendency, however, would reduce the unique effect of friends’ amount of violent video game play on the participant's aggression when controlling for the participant's amount of violent video game play. The finding that participants in particular who do not play violent video games reported to be more aggressive if their friends play violent video games also suggests that the impact of violent video games on the player's social network is not due to participants providing both self‐reports and how they perceive their friends. Finally, rather than by their friends’ objective qualities, people's behavior should be more likely to be affected by their subjective perceptions of their friends.

As noted in the introduction, participants may not be aware of the extent to which their friends play violent video games and hence used the perception of how aggressive their friends are as an anchor for estimating their friends’ amount of violent video game play. Importantly, however, the participant's aggression at Time 2 was significantly predicted by friends’ amount of violent video game play at Time 1 even when controlling for friends’ level of aggression at Time 1 (see Figure ​ Figure3). 3 ). Moreover, whereas aggression might be used for estimating violent video game exposure of the friends, participants should be well aware of the extent to which they play violent video games so that anchoring effects for participant's self‐reports are unlikely. However, given that it cannot be completely ruled out that the correlation between violent game play of friends at Time 1 and aggressive behavior of participants at Time 2 reflects a pseudocorrelation that is determined by the correlation between aggressive behavior of friends at Time 1 and aggressive behavior of the participant at Time 2, future research that employs sociocentric network analyses where information about the friends is provided by the friends themselves would be informative.

Another limitation is the employment of self‐report measures to assess aggressive behavior. Self‐report measures are quite transparent, so participants may have rated themselves more favorably than is actually warranted. In fact, mean scores of reported aggressive behavior were quite low. This reduced variance, however, typically diminishes associations with other constructs. In any case, observing how actual aggressive behavior is influenced by the social network's violent video game play would be an important endeavor for future work. It also has to be acknowledged that some participants may have reported on different friends at Time 1 and Time 2. Future research would be welcome that ensures that participants consider the same friends at different time points.

Future research may also shed some further light on the psychological processes. In the present study, the violent video game players’ higher levels of aggression accounted for the relationship between their amount of violent video game play and the participants’ reported aggression. It would be interesting to examine why the players’ aggression influences the aggression level of their social network. One possibility is that witnessing increased aggression by others (who play violent video games) leads to greater acceptance of norms condoning aggression, which are known to be an antecedent of aggressive behavior (Huesmann & Guerra, 1997 ). After all, if others behave aggressively, why should one refrain from engaging in the same behavior.

Another limitation of the present work is that it was not assessed how participants and their friends play violent video games. A recent survey (Lenhart, Smith, Anderson, Duggan, & Perrin, 2015 ) showed that many video game users play video games together with their friends, either cooperatively or competitively. This is insofar noteworthy as there might be some overlap between participants’ and their friends’ violent video game play. Moreover, cooperative video games have been shown to increase prosocial tendencies (Greitemeyer, 2013 ; Greitemeyer & Cox, 2013 ; but see Verheijen, Stoltz, van den Berg, & Cillessen, 2019 ) and decrease aggression (Velez, Greitemeyer, Whitaker, Ewoldsen, & Bushman, 2016 ). In contrast, competitive video game play increases aggressive affect and behavior (e.g., Adachi & Willoughby, 2016 ). Hence, future research should examine more closely whether participants play violent video games on their own, competitively, or cooperatively. The latter may show some positive effects of video game play, both on the player and the player's friends, whereas opposing effects should be found for competitive video games.

To obtain high statistical power and thus to increase the probability to detect significant effects, data were collected via an online survey. The current sample was drawn from the MTurk population (for a review of the trend to rely on MTurk samples in social and personality psychology, see Anderson et al., 2019 ). Samples drawn from MTurk are not demographically representative of the U.S. population as a whole. For example, MTurk samples are disproportionally young and female and they are better educated but tend to be unemployed (for a review, Keith, Tay, & Harms, 2017 ). On the other hand, MTurk samples are more representative of the U.S. population than are college student samples (Paolacci & Chandler, 2014 ) and the pool of participants is geographically diverse. Moreover, MTurk participants appear to be more attentive to survey instructions than are undergraduate students (Hauser & Schwarz, 2016 ). Nevertheless, future research on the impact of violent video game play on the player's social network that employs other samples would improve the generalizability of the present findings.

In conclusion, violent video game play is not only associated with increased aggression in the player but also in the player's social network. In fact, increased aggression due to violent video game play appears to instigate further aggression in the player's social network. This study thus provides suggestive evidence that not only players of violent video games are more aggressive, but also individuals become more aggressive who do not play violent video games themselves but are connected to others who do play.

Greitemeyer T. The contagious impact of playing violent video games on aggression: Longitudinal evidence . Aggressive Behavior . 2019; 45 :635–642. 10.1002/ab.21857 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

1 Participant's perceived deprivation was positively related to both violent video game exposure, r (2,502) = 0.08, p  < .001, and reported aggression, r (2,502) = 0.14, p  < .001. However, the relationship between violent video game exposure and reported aggression, r (2,502) = 0.15, p  < .001, was relatively unaffected when controlling for perceived deprivation, r (2,499) = 0.14, p  < .001.

2 Given that the measures of violent video game exposure and aggressive behavior violated the normal distribution, Spearman's ρ coefficients were also calculated. However, the pattern of finding was very similar (e.g., the crucial relationship between the participant's aggression and friends’ amount of violent video game play was 0.18 [Pearson] and 0.17 [Spearman]). All these analyses can be obtained from the author upon request.

3 When dropping friends’ amount of violent video game play from the analysis, the participant's amount of violent video game play at Time 1 still did not predict participant's aggression at Time 2, t  = 0.44, β  = −.01, 95% CI = (− 0.02, 0.01), p  = .657 (when controlling for participant's aggression at Time 1, participant sex, and age).

4 Given that violent video games primarily model physical aggression, violent video games should have a stronger effect on the player's physical aggression than on other types of aggression. In fact, the impact of the participant's amount of violent video game play at Time 1 on the participant's physical aggression at Time 2, t  = 1.49, β  = .04, 95% CI = (− 0.00, 0.02), p  = .136 (when controlling for the participant's physical aggression at Time 1), was more pronounced than the impact on the participant's relational aggression at Time 2, t  = 0.52, β  = .02, 95% CI = (− 0.01, 0.02), p  = .603 (when controlling for the participant's relational aggression at Time 1), but both effects were not significant.

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• Published: 13 March 2018

Does playing violent video games cause aggression? A longitudinal intervention study

• Simone Kühn 1 , 2 ,
• Dimitrij Tycho Kugler 2 ,
• Katharina Schmalen 1 ,
• Markus Weichenberger 1 ,
• Charlotte Witt 1 &
• Jürgen Gallinat 2  

Molecular Psychiatry volume  24 ,  pages 1220–1234 ( 2019 ) Cite this article

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• Neuroscience

It is a widespread concern that violent video games promote aggression, reduce pro-social behaviour, increase impulsivity and interfere with cognition as well as mood in its players. Previous experimental studies have focussed on short-term effects of violent video gameplay on aggression, yet there are reasons to believe that these effects are mostly the result of priming. In contrast, the present study is the first to investigate the effects of long-term violent video gameplay using a large battery of tests spanning questionnaires, behavioural measures of aggression, sexist attitudes, empathy and interpersonal competencies, impulsivity-related constructs (such as sensation seeking, boredom proneness, risk taking, delay discounting), mental health (depressivity, anxiety) as well as executive control functions, before and after 2 months of gameplay. Our participants played the violent video game Grand Theft Auto V, the non-violent video game The Sims 3 or no game at all for 2 months on a daily basis. No significant changes were observed, neither when comparing the group playing a violent video game to a group playing a non-violent game, nor to a passive control group. Also, no effects were observed between baseline and posttest directly after the intervention, nor between baseline and a follow-up assessment 2 months after the intervention period had ended. The present results thus provide strong evidence against the frequently debated negative effects of playing violent video games in adults and will therefore help to communicate a more realistic scientific perspective on the effects of violent video gaming.

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The concern that violent video games may promote aggression or reduce empathy in its players is pervasive and given the popularity of these games their psychological impact is an urgent issue for society at large. Contrary to the custom, this topic has also been passionately debated in the scientific literature. One research camp has strongly argued that violent video games increase aggression in its players [ 1 , 2 ], whereas the other camp [ 3 , 4 ] repeatedly concluded that the effects are minimal at best, if not absent. Importantly, it appears that these fundamental inconsistencies cannot be attributed to differences in research methodology since even meta-analyses, with the goal to integrate the results of all prior studies on the topic of aggression caused by video games led to disparate conclusions [ 2 , 3 ]. These meta-analyses had a strong focus on children, and one of them [ 2 ] reported a marginal age effect suggesting that children might be even more susceptible to violent video game effects.

To unravel this topic of research, we designed a randomised controlled trial on adults to draw causal conclusions on the influence of video games on aggression. At present, almost all experimental studies targeting the effects of violent video games on aggression and/or empathy focussed on the effects of short-term video gameplay. In these studies the duration for which participants were instructed to play the games ranged from 4 min to maximally 2 h (mean = 22 min, median = 15 min, when considering all experimental studies reviewed in two of the recent major meta-analyses in the field [ 3 , 5 ]) and most frequently the effects of video gaming have been tested directly after gameplay.

It has been suggested that the effects of studies focussing on consequences of short-term video gameplay (mostly conducted on college student populations) are mainly the result of priming effects, meaning that exposure to violent content increases the accessibility of aggressive thoughts and affect when participants are in the immediate situation [ 6 ]. However, above and beyond this the General Aggression Model (GAM, [ 7 ]) assumes that repeatedly primed thoughts and feelings influence the perception of ongoing events and therewith elicits aggressive behaviour as a long-term effect. We think that priming effects are interesting and worthwhile exploring, but in contrast to the notion of the GAM our reading of the literature is that priming effects are short-lived (suggested to only last for <5 min and may potentially reverse after that time [ 8 ]). Priming effects should therefore only play a role in very close temporal proximity to gameplay. Moreover, there are a multitude of studies on college students that have failed to replicate priming effects [ 9 , 10 , 11 ] and associated predictions of the so-called GAM such as a desensitisation against violent content [ 12 , 13 , 14 ] in adolescents and college students or a decrease of empathy [ 15 ] and pro-social behaviour [ 16 , 17 ] as a result of playing violent video games.

However, in our view the question that society is actually interested in is not: “Are people more aggressive after having played violent video games for a few minutes? And are these people more aggressive minutes after gameplay ended?”, but rather “What are the effects of frequent, habitual violent video game playing? And for how long do these effects persist (not in the range of minutes but rather weeks and months)?” For this reason studies are needed in which participants are trained over longer periods of time, tested after a longer delay after acute playing and tested with broader batteries assessing aggression but also other relevant domains such as empathy as well as mood and cognition. Moreover, long-term follow-up assessments are needed to demonstrate long-term effects of frequent violent video gameplay. To fill this gap, we set out to expose adult participants to two different types of video games for a period of 2 months and investigate changes in measures of various constructs of interest at least one day after the last gaming session and test them once more 2 months after the end of the gameplay intervention. In contrast to the GAM, we hypothesised no increases of aggression or decreases in pro-social behaviour even after long-term exposure to a violent video game due to our reasoning that priming effects of violent video games are short-lived and should therefore not influence measures of aggression if they are not measured directly after acute gaming. In the present study, we assessed potential changes in the following domains: behavioural as well as questionnaire measures of aggression, empathy and interpersonal competencies, impulsivity-related constructs (such as sensation seeking, boredom proneness, risk taking, delay discounting), and depressivity and anxiety as well as executive control functions. As the effects on aggression and pro-social behaviour were the core targets of the present study, we implemented multiple tests for these domains. This broad range of domains with its wide coverage and the longitudinal nature of the study design enabled us to draw more general conclusions regarding the causal effects of violent video games.

Materials and methods

Participants.

Ninety healthy participants (mean age = 28 years, SD = 7.3, range: 18–45, 48 females) were recruited by means of flyers and internet advertisements. The sample consisted of college students as well as of participants from the general community. The advertisement mentioned that we were recruiting for a longitudinal study on video gaming, but did not mention that we would offer an intervention or that we were expecting training effects. Participants were randomly assigned to the three groups ruling out self-selection effects. The sample size was based on estimates from a previous study with a similar design [ 18 ]. After complete description of the study, the participants’ informed written consent was obtained. The local ethics committee of the Charité University Clinic, Germany, approved of the study. We included participants that reported little, preferably no video game usage in the past 6 months (none of the participants ever played the game Grand Theft Auto V (GTA) or Sims 3 in any of its versions before). We excluded participants with psychological or neurological problems. The participants received financial compensation for the testing sessions (200 Euros) and performance-dependent additional payment for two behavioural tasks detailed below, but received no money for the training itself.

Training procedure

The violent video game group (5 participants dropped out between pre- and posttest, resulting in a group of n  = 25, mean age = 26.6 years, SD = 6.0, 14 females) played the game Grand Theft Auto V on a Playstation 3 console over a period of 8 weeks. The active control group played the non-violent video game Sims 3 on the same console (6 participants dropped out, resulting in a group of n  = 24, mean age = 25.8 years, SD = 6.8, 12 females). The passive control group (2 participants dropped out, resulting in a group of n  = 28, mean age = 30.9 years, SD = 8.4, 12 females) was not given a gaming console and had no task but underwent the same testing procedure as the two other groups. The passive control group was not aware of the fact that they were part of a control group to prevent self-training attempts. The experimenters testing the participants were blind to group membership, but we were unable to prevent participants from talking about the game during testing, which in some cases lead to an unblinding of experimental condition. Both training groups were instructed to play the game for at least 30 min a day. Participants were only reimbursed for the sessions in which they came to the lab. Our previous research suggests that the perceived fun in gaming was positively associated with training outcome [ 18 ] and we speculated that enforcing training sessions through payment would impair motivation and thus diminish the potential effect of the intervention. Participants underwent a testing session before (baseline) and after the training period of 2 months (posttest 1) as well as a follow-up testing sessions 2 months after the training period (posttest 2).

Grand Theft Auto V (GTA)

GTA is an action-adventure video game situated in a fictional highly violent game world in which players are rewarded for their use of violence as a means to advance in the game. The single-player story follows three criminals and their efforts to commit heists while under pressure from a government agency. The gameplay focuses on an open world (sandbox game) where the player can choose between different behaviours. The game also allows the player to engage in various side activities, such as action-adventure, driving, third-person shooting, occasional role-playing, stealth and racing elements. The open world design lets players freely roam around the fictional world so that gamers could in principle decide not to commit violent acts.

The Sims 3 (Sims)

Sims is a life simulation game and also classified as a sandbox game because it lacks clearly defined goals. The player creates virtual individuals called “Sims”, and customises their appearance, their personalities and places them in a home, directs their moods, satisfies their desires and accompanies them in their daily activities and by becoming part of a social network. It offers opportunities, which the player may choose to pursue or to refuse, similar as GTA but is generally considered as a pro-social and clearly non-violent game.

Assessment battery

To assess aggression and associated constructs we used the following questionnaires: Buss–Perry Aggression Questionnaire [ 19 ], State Hostility Scale [ 20 ], Updated Illinois Rape Myth Acceptance Scale [ 21 , 22 ], Moral Disengagement Scale [ 23 , 24 ], the Rosenzweig Picture Frustration Test [ 25 , 26 ] and a so-called World View Measure [ 27 ]. All of these measures have previously been used in research investigating the effects of violent video gameplay, however, the first two most prominently. Additionally, behavioural measures of aggression were used: a Word Completion Task, a Lexical Decision Task [ 28 ] and the Delay frustration task [ 29 ] (an inter-correlation matrix is depicted in Supplementary Figure 1 1). From these behavioural measures, the first two were previously used in research on the effects of violent video gameplay. To assess variables that have been related to the construct of impulsivity, we used the Brief Sensation Seeking Scale [ 30 ] and the Boredom Propensity Scale [ 31 ] as well as tasks assessing risk taking and delay discounting behaviourally, namely the Balloon Analogue Risk Task [ 32 ] and a Delay-Discounting Task [ 33 ]. To quantify pro-social behaviour, we employed: Interpersonal Reactivity Index [ 34 ] (frequently used in research on the effects of violent video gameplay), Balanced Emotional Empathy Scale [ 35 ], Reading the Mind in the Eyes test [ 36 ], Interpersonal Competence Questionnaire [ 37 ] and Richardson Conflict Response Questionnaire [ 38 ]. To assess depressivity and anxiety, which has previously been associated with intense video game playing [ 39 ], we used Beck Depression Inventory [ 40 ] and State Trait Anxiety Inventory [ 41 ]. To characterise executive control function, we used a Stop Signal Task [ 42 ], a Multi-Source Interference Task [ 43 ] and a Task Switching Task [ 44 ] which have all been previously used to assess effects of video gameplay. More details on all instruments used can be found in the Supplementary Material.

Data analysis

On the basis of the research question whether violent video game playing enhances aggression and reduces empathy, the focus of the present analysis was on time by group interactions. We conducted these interaction analyses separately, comparing the violent video game group against the active control group (GTA vs. Sims) and separately against the passive control group (GTA vs. Controls) that did not receive any intervention and separately for the potential changes during the intervention period (baseline vs. posttest 1) and to test for potential long-term changes (baseline vs. posttest 2). We employed classical frequentist statistics running a repeated-measures ANOVA controlling for the covariates sex and age.

Since we collected 52 separate outcome variables and conduced four different tests with each (GTA vs. Sims, GTA vs. Controls, crossed with baseline vs. posttest 1, baseline vs. posttest 2), we had to conduct 52 × 4 = 208 frequentist statistical tests. Setting the alpha value to 0.05 means that by pure chance about 10.4 analyses should become significant. To account for this multiple testing problem and the associated alpha inflation, we conducted a Bonferroni correction. According to Bonferroni, the critical value for the entire set of n tests is set to an alpha value of 0.05 by taking alpha/ n  = 0.00024.

Since the Bonferroni correction has sometimes been criticised as overly conservative, we conducted false discovery rate (FDR) correction [ 45 ]. FDR correction also determines adjusted p -values for each test, however, it controls only for the number of false discoveries in those tests that result in a discovery (namely a significant result).

Moreover, we tested for group differences at the baseline assessment using independent t -tests, since those may hamper the interpretation of significant interactions between group and time that we were primarily interested in.

Since the frequentist framework does not enable to evaluate whether the observed null effect of the hypothesised interaction is indicative of the absence of a relation between violent video gaming and our dependent variables, the amount of evidence in favour of the null hypothesis has been tested using a Bayesian framework. Within the Bayesian framework both the evidence in favour of the null and the alternative hypothesis are directly computed based on the observed data, giving rise to the possibility of comparing the two. We conducted Bayesian repeated-measures ANOVAs comparing the model in favour of the null and the model in favour of the alternative hypothesis resulting in a Bayes factor (BF) using Bayesian Information criteria [ 46 ]. The BF 01 suggests how much more likely the data is to occur under the null hypothesis. All analyses were performed using the JASP software package ( https://jasp-stats.org ).

Sex distribution in the present study did not differ across the groups ( χ 2 p -value > 0.414). However, due to the fact that differences between males and females have been observed in terms of aggression and empathy [ 47 ], we present analyses controlling for sex. Since our random assignment to the three groups did result in significant age differences between groups, with the passive control group being significantly older than the GTA ( t (51) = −2.10, p  = 0.041) and the Sims group ( t (50) = −2.38, p  = 0.021), we also controlled for age.

The participants in the violent video game group played on average 35 h and the non-violent video game group 32 h spread out across the 8 weeks interval (with no significant group difference p  = 0.48).

To test whether participants assigned to the violent GTA game show emotional, cognitive and behavioural changes, we present the results of repeated-measure ANOVA time x group interaction analyses separately for GTA vs. Sims and GTA vs. Controls (Tables  1 – 3 ). Moreover, we split the analyses according to the time domain into effects from baseline assessment to posttest 1 (Table  2 ) and effects from baseline assessment to posttest 2 (Table  3 ) to capture more long-lasting or evolving effects. In addition to the statistical test values, we report partial omega squared ( ω 2 ) as an effect size measure. Next to the classical frequentist statistics, we report the results of a Bayesian statistical approach, namely BF 01 , the likelihood with which the data is to occur under the null hypothesis that there is no significant time × group interaction. In Table  2 , we report the presence of significant group differences at baseline in the right most column.

Since we conducted 208 separate frequentist tests we expected 10.4 significant effects simply by chance when setting the alpha value to 0.05. In fact we found only eight significant time × group interactions (these are marked with an asterisk in Tables  2 and 3 ).

When applying a conservative Bonferroni correction, none of those tests survive the corrected threshold of p  < 0.00024. Neither does any test survive the more lenient FDR correction. The arithmetic mean of the frequentist test statistics likewise shows that on average no significant effect was found (bottom rows in Tables  2 and 3 ).

In line with the findings from a frequentist approach, the harmonic mean of the Bayesian factor BF 01 is consistently above one but not very far from one. This likewise suggests that there is very likely no interaction between group × time and therewith no detrimental effects of the violent video game GTA in the domains tested. The evidence in favour of the null hypothesis based on the Bayes factor is not massive, but clearly above 1. Some of the harmonic means are above 1.6 and constitute substantial evidence [ 48 ]. However, the harmonic mean has been criticised as unstable. Owing to the fact that the sum is dominated by occasional small terms in the likelihood, one may underestimate the actual evidence in favour of the null hypothesis [ 49 ].

To test the sensitivity of the present study to detect relevant effects we computed the effect size that we would have been able to detect. The information we used consisted of alpha error probability = 0.05, power = 0.95, our sample size, number of groups and of measurement occasions and correlation between the repeated measures at posttest 1 and posttest 2 (average r  = 0.68). According to G*Power [ 50 ], we could detect small effect sizes of f  = 0.16 (equals η 2  = 0.025 and r  = 0.16) in each separate test. When accounting for the conservative Bonferroni-corrected p -value of 0.00024, still a medium effect size of f  = 0.23 (equals η 2  = 0.05 and r  = 0.22) would have been detectable. A meta-analysis by Anderson [ 2 ] reported an average effects size of r  = 0.18 for experimental studies testing for aggressive behaviour and another by Greitmeyer [ 5 ] reported average effect sizes of r  = 0.19, 0.25 and 0.17 for effects of violent games on aggressive behaviour, cognition and affect, all of which should have been detectable at least before multiple test correction.

Within the scope of the present study we tested the potential effects of playing the violent video game GTA V for 2 months against an active control group that played the non-violent, rather pro-social life simulation game The Sims 3 and a passive control group. Participants were tested before and after the long-term intervention and at a follow-up appointment 2 months later. Although we used a comprehensive test battery consisting of questionnaires and computerised behavioural tests assessing aggression, impulsivity-related constructs, mood, anxiety, empathy, interpersonal competencies and executive control functions, we did not find relevant negative effects in response to violent video game playing. In fact, only three tests of the 208 statistical tests performed showed a significant interaction pattern that would be in line with this hypothesis. Since at least ten significant effects would be expected purely by chance, we conclude that there were no detrimental effects of violent video gameplay.

This finding stands in contrast to some experimental studies, in which short-term effects of violent video game exposure have been investigated and where increases in aggressive thoughts and affect as well as decreases in helping behaviour have been observed [ 1 ]. However, these effects of violent video gaming on aggressiveness—if present at all (see above)—seem to be rather short-lived, potentially lasting <15 min [ 8 , 51 ]. In addition, these short-term effects of video gaming are far from consistent as multiple studies fail to demonstrate or replicate them [ 16 , 17 ]. This may in part be due to problems, that are very prominent in this field of research, namely that the outcome measures of aggression and pro-social behaviour, are poorly standardised, do not easily generalise to real-life behaviour and may have lead to selective reporting of the results [ 3 ]. We tried to address these concerns by including a large set of outcome measures that were mostly inspired by previous studies demonstrating effects of short-term violent video gameplay on aggressive behaviour and thoughts, that we report exhaustively.

Since effects observed only for a few minutes after short sessions of video gaming are not representative of what society at large is actually interested in, namely how habitual violent video gameplay affects behaviour on a more long-term basis, studies employing longer training intervals are highly relevant. Two previous studies have employed longer training intervals. In an online study, participants with a broad age range (14–68 years) have been trained in a violent video game for 4 weeks [ 52 ]. In comparison to a passive control group no changes were observed, neither in aggression-related beliefs, nor in aggressive social interactions assessed by means of two questions. In a more recent study, participants played a previous version of GTA for 12 h spread across 3 weeks [ 53 ]. Participants were compared to a passive control group using the Buss–Perry aggression questionnaire, a questionnaire assessing impulsive or reactive aggression, attitude towards violence, and empathy. The authors only report a limited increase in pro-violent attitude. Unfortunately, this study only assessed posttest measures, which precludes the assessment of actual changes caused by the game intervention.

The present study goes beyond these studies by showing that 2 months of violent video gameplay does neither lead to any significant negative effects in a broad assessment battery administered directly after the intervention nor at a follow-up assessment 2 months after the intervention. The fact that we assessed multiple domains, not finding an effect in any of them, makes the present study the most comprehensive in the field. Our battery included self-report instruments on aggression (Buss–Perry aggression questionnaire, State Hostility scale, Illinois Rape Myth Acceptance scale, Moral Disengagement scale, World View Measure and Rosenzweig Picture Frustration test) as well as computer-based tests measuring aggressive behaviour such as the delay frustration task and measuring the availability of aggressive words using the word completion test and a lexical decision task. Moreover, we assessed impulse-related concepts such as sensation seeking, boredom proneness and associated behavioural measures such as the computerised Balloon analogue risk task, and delay discounting. Four scales assessing empathy and interpersonal competence scales, including the reading the mind in the eyes test revealed no effects of violent video gameplay. Neither did we find any effects on depressivity (Becks depression inventory) nor anxiety measured as a state as well as a trait. This is an important point, since several studies reported higher rates of depressivity and anxiety in populations of habitual video gamers [ 54 , 55 ]. Last but not least, our results revealed also no substantial changes in executive control tasks performance, neither in the Stop signal task, the Multi-source interference task or a Task switching task. Previous studies have shown higher performance of habitual action video gamers in executive tasks such as task switching [ 56 , 57 , 58 ] and another study suggests that training with action video games improves task performance that relates to executive functions [ 59 ], however, these associations were not confirmed by a meta-analysis in the field [ 60 ]. The absence of changes in the stop signal task fits well with previous studies that likewise revealed no difference between in habitual action video gamers and controls in terms of action inhibition [ 61 , 62 ]. Although GTA does not qualify as a classical first-person shooter as most of the previously tested action video games, it is classified as an action-adventure game and shares multiple features with those action video games previously related to increases in executive function, including the need for hand–eye coordination and fast reaction times.

Taken together, the findings of the present study show that an extensive game intervention over the course of 2 months did not reveal any specific changes in aggression, empathy, interpersonal competencies, impulsivity-related constructs, depressivity, anxiety or executive control functions; neither in comparison to an active control group that played a non-violent video game nor to a passive control group. We observed no effects when comparing a baseline and a post-training assessment, nor when focussing on more long-term effects between baseline and a follow-up interval 2 months after the participants stopped training. To our knowledge, the present study employed the most comprehensive test battery spanning a multitude of domains in which changes due to violent video games may have been expected. Therefore the present results provide strong evidence against the frequently debated negative effects of playing violent video games. This debate has mostly been informed by studies showing short-term effects of violent video games when tests were administered immediately after a short playtime of a few minutes; effects that may in large be caused by short-lived priming effects that vanish after minutes. The presented results will therefore help to communicate a more realistic scientific perspective of the real-life effects of violent video gaming. However, future research is needed to demonstrate the absence of effects of violent video gameplay in children.

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SK has been funded by a Heisenberg grant from the German Science Foundation (DFG KU 3322/1-1, SFB 936/C7), the European Union (ERC-2016-StG-Self-Control-677804) and a Fellowship from the Jacobs Foundation (JRF 2016–2018).

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Kühn, S., Kugler, D., Schmalen, K. et al. Does playing violent video games cause aggression? A longitudinal intervention study. Mol Psychiatry 24 , 1220–1234 (2019). https://doi.org/10.1038/s41380-018-0031-7

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Stress and Violence in Video Games: Their Influence on Aggression

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• Published: 21 January 2022
• Volume 30 , pages 497–512, ( 2022 )

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This study investigated whether stress or violent content in video games plays a greater role in aggressiveness towards a cooperative partner while playing a video game. It was hypothesized that participants, when exposed to stress, would demonstrate greater aggressiveness toward an incompetent partner than a competent partner. Furthermore, it was hypothesized that participants, when exposed to a violent video game, would demonstrate greater aggression toward an incompetent partner than those exposed to a non-violent video game. Stress was provoked in half of the participants using the Paced Auditory Serial Addition Test (PASAT), while others took a simple math quiz. Participants were then assigned to a video game condition, violent or non-violent with a competent or incompetent confederate and completed a reaction time task to measure aggression. Results indicated that provoked stress and violent content are not linked to aggression in this context.

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Under stressful circumstances, individuals tend to resort to aggressiveness. Studies have highlighted that stressful situations which have developed earlier in life and are repeatedly imposed on an individual have underlying effects on aggression. However, many studies have also discussed the perception that immediate stress can also provoke and incite aggression (Verona & Kilmer, 2007 ). Despite this, it is important to understand whether acquired stress plays a role in the expression of human aggression.

Animals, Stress, and Aggression

One means of examining how stress impacts aggression is through the study of animal models. In one study conducted with male adult mice, acute stressors were the primary causes of a marked increase in aggressiveness (Nosjean et al., 2015 ). During this study, the researchers’ aim was to determine the immediate effect acute stress would have on social interaction in adult male mice. In order to conduct their study, the researchers used 70 adult male mice purchased from a laboratory and separated them into isolated host (IH) mice and social visitor (SV) mice. During the study, each isolated host mice either received or did not receive acute stress while the social visitor mice remained unstressed throughout the environment. After being placed under duress, the IH mice were allowed to explore their cage before being exposed to an SV mouse for social interaction. This interaction was videotaped and analyzed by researchers. The researchers concluded that stress depleted the mice’s social repertoire, accelerated their dominance behaviors, and furthered aggressive behaviors. Due to their findings, they concluded that social interactions can be influenced by a single stressful event.

Kohl et al. ( 2013 ) utilized a similar procedure, wherein mice were exposed to a resident intruder to measure and evaluate the resident’s aggressive behaviors. In their study, they primarily focused on whether there was an interaction of conditional neural cell adhesion molecule knockout (NCAM-KO) and the extent to which exposure to repeated stress influenced aggression. Through the utilization of a gene by environment experiment, researchers attempted to determine whether the lack of forebrain in NCAM-KO mice would facilitate the development of an aggressive phenotype following exposure to either subchronic stress and chronic stress or one stressful condition when compared to wild-type variations of the mice. During their procedure, the researchers first measured the animals’ baseline anxiety-like behavior through the use of an elevated plus-maze; they also conducted a bedding preference test to determine social behavior, an open field test to observe exploratory behavior, and the resident-intruder test for aggression. After running statistical analyses on their data, they found that NCAM-KO mice exhibited no differences in aggressive behavior prior to subchronic stress exposure and while under basal conditions. However, following chronic exposure to stress, the NCAM-KO mice showed increased aggressive behavior toward their intruder. These findings led to the conclusion that chronic stress-induced differences in aggressive behavior rather than subchronic stress. Furthermore, the researchers outlined that due to the age of their mice, there could be age differences in the vulnerability to stress and thus a differing impact of stress on aggression.

Studies such as these provide some useful hints as to how stress can influence animals. However, mice are not humans, and it is to human research that we next turn.

Humans, Stress, and Aggression

It has been long suggested as part of the Frustration-Aggression Hypothesis that certain types of stress may provoke aggression. Other scholars have suggested that stress more generally, not merely frustration, could lead to aggression. Hinsberger et al. ( 2016 ) aimed to determine whether individuals were more aggressive when exposed to continuous traumatic stress. Researchers had trained mental health experts and counselors to conduct diagnostic interviews of 290 South African participants. The researchers discovered that there was a significant correlation between self and witnessed traumatic events, PTSD symptom severity, and engagement in violent behavior. Researchers found that attraction to violence was predicted by witnessed traumatic events as well as victimization, and perpetrated acts of violence were directly predicted by the witnessing of violence and that PTSD symptom severity was directly predicted by victimization. They also found that exposure to violence did not directly influence PTSD severity or perpetrated violence by means of appetitive aggression. Instead, they determined that appetitive aggression predicted the severity of PTSD and aggressive behavior. This study primarily focused on the act of resorting to violence when under continually stressful circumstances and concluded that aggression exhibited in stressful environments would aid in survival.

In a study conducted by Verona and Kilmer ( 2007 ), acute stress was examined as a determinant of aggressive behaviors in 120 volunteers. The researchers used the Positive and Negative Affect Schedule before and after a stress manipulation. Participants were exposed to either low- and high-stress conditions after which they interacted with a confederate who they could inflict with shocks during judgment task. In their study, the researchers primarily found gender differences in the influence of acute stressors on aggressive behaviors. They concluded that women displayed less aggression whereas men displayed increased aggression after being exposed to the high-stress condition.

Meta-analyses likewise have examined the relationship between stress and aggression. Evidence suggests that stress and trauma can increase the propensity to engage in aggression in both men and women (Augsburger, & Maercker, 2020 ; Orth, & Wieland, 2006 ). Such effects appear fairly consistent in the literature with moderate to large effects for hostile feelings and small to moderate effects for aggressive behavior.

Violence in Video Games

Prior studies outlined observed aggression in relation to stress; however, in this study, it is important to understand whether the task the participant engaged in also influences aggression, especially under stressful circumstances. Therefore, it is important to also understand the relationship between video games and aggression. The issue of whether violence in video games can impact aggression has been controversial. Despite several decades of research, no consensus has emerged. Though the American Psychological Association (APA) has taken a stance that violent games promote aggression (but not violent crime), reanalysis of their work has suggested that this claim is not supported by the extant literature and the APA may be misinforming the public (Ferguson et al., 2020 ). Below, we consider just a few studies in this realm.

In a unique study designed by Weber et al. ( 2006 ), researchers analyzed brain activity in relation to game play to understand and distinguish between virtual violence and non-virtual violence. The researchers conducted their experiment using 13 volunteers who chose to play a mature-rated first-person shooter game while under fMRI scanning. They recorded brain activity, physiological responses throughout game play, audio data from the game, and video display of the game play. They also included a questionnaire measure meant to control for arousal and subjective experiences throughout the experiment. After analyzing their data, they found that virtual violence produces similar brain activity when compared to the experience of aggressive thoughts and actions.

Despite the previous findings, several studies have found no relationship between violent video games and aggression (e.g., Przybylski et al., 2014 ; Toniutti et al., 2013 ). For example, in a longitudinal experiment, Kuhn and colleagues found no evidence that repeated exposure to a violent video game had any impact on aggressive behavior (Kühn et al., 2019 ). One issue that appears to emerge is that preregistered studies, wherein scholars post their analyses plans in advance so as to reduce questionable researcher practices, are particularly unlikely to find significant results (e.g., Hilgard et al., 2019 ; McCarthy et al., 2016 ). As such, more preregistered studies in this realm would be welcome.

Although individual studies may naturally differ in results , it is possible that meta-analyses may provide some illumination regarding larger trends in the field. However, there are disagreements in the conclusions of meta-analyses here too. For instance, Anderson and colleagues ( 2010 ) concluded that there are meaningful relationships between violent game playing and aggression in players. However, a reanalysis of this data concluded that effects, particularly for experimental studies, were largely driven by publication bias (Hilgard et al., 2017 ). Likewise, Prescott et al. ( 2018 ) found that there are very, very small longitudinal relationships between violent gameplay and later aggression. However, in reanalyzing this data, Drummond et al. ( 2020 ) concluded the effect sizes ( r  = 0.06) were trivial and driven by methodological noise, not true effects. Best practice studies demonstrated effect sizes that were no different from zero.

The Current Study

The purpose of this study was to determine whether violent content or acute stress plays a greater role in aggressiveness towards a cooperative partner while playing a video game. This study not only focused on investigating the role of stress in aggression but also its influence under varying conditions. The hypotheses being tested are as follows:

H1: Participants when exposed to acute stress will demonstrate greater aggressiveness toward an incompetent partner than a competent partner.

H2: Acute stress will play a greater role in causing aggressiveness towards an incompetent partner than chronic stress.

H3: Participants when exposed to stress and a violent video game will depict greater aggression toward an incompetent partner than those exposed to a non-violent video game.

We note that these hypotheses are expressed as main effects. However, it is possible that stress may moderate any relationship between violent game play and aggression (Shao & Wang, 2019 ). As such, we will also be alert for interaction effects between the independent variables.

Data Availability Statement

A preregistration of this study can be found at https://aspredicted.org/37ie4.pdf . Original data files can be found at https://osf.io/8w7mz/ .

Conflict of Interest

The authors declare no competing interests.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Participants

This study involved 73 participants who were compensated with two extra credit points for psychology courses registered in the undergraduate research portal. About twenty percent of the participants were male (20.5%, n  = 15), while the others were female (79.5%, n  = 58). Participants’ age ranged from 18 to 50 years old ( M  = 20.55, SD  = 4.98). Frequencies were also gathered for participants in each condition. In the stress condition, there were 37 participants (50.7%) in the acute stress condition and 49.3% in the control condition ( n  = 36). For the video game condition, about half of the participants were in the violent condition (52.1%, n  = 38) while 35 were in the nonviolent condition (47.9%). Additionally, the incompetent confederate condition included 38 participants (52.1%) while the competent condition consisted of 47.9% participants ( n  = 35). For a further two participants, a technical glitch resulted in the loss of their aggression data. In our preregistration document, we had planned to reach 100 participants. However, due to COVID-19 shutting down in-person research and the graduation of the lead author, participant recruitment was discontinued. This was done prior to examining any data.

State-Trait Anxiety Inventory (STAI)

The State-Trait Anxiety Inventory (STAI) is a self-report anxiety measure (Spielberger et al., 1983 ). The inventory consists of a form Y-1, which measures current anxiety levels, and Y-2, which measures anxiety levels for the past 6 months. This measure contains 40 items, 20 state anxiety and 20 trait anxiety. For our purposes, we administered the Y2 trait form. Questions range from “I feel upset” to “I feel that difficulties are piling up so that I cannot overcome them.” These questions were rated on a 4-point Likert scale ranging from almost never to almost always. For the trait anxiety form with the current sample, the coefficient alpha was 0.90. The range of scores was from 22 to 70 from a possible range of 20–80. The mean score was 71.49 with a standard deviation of 10.63 indicating good variability in scores.

Crossword Puzzle

Participants took a simple crossword puzzle based on school classes, to act as a distractor task (see Appendix).

Stress Conditions

In this study, participants were randomly assigned to one of two stress conditions: The Paced Auditory Serial Addition Task (PASAT) or a control math quiz (see Appendix). The PASAT was originally used as a means of assessing short-term memory loss; however, for this study, it was used as a measure of inducing stress in participants . In this study, the computerized version (PASAT-C) of the PASAT was used (Lejuez et al., 2003 ). Participants mentally calculated addition problems during a set time frame. The PASAT requires sustained and specific attention. Participants are given simple math problems, but these are done with intervening numbers that are distractors, thus setting up high frustration. Participants must add each number to the number before it, keying in the response. However, each response serves as a distractor. For instance, a respondent may be given the numbers, in sequence, 3, 9, and 5. For the first two numbers, they key in the correct response “12”; however, then, they are supposed to add 5 to the 9. Yet, having “12” in working memory sets up a distractor and increases frustration, particularly as the task speeds up. Previous evidence has supported that the PASAT is effective in inducing stress, including for college students specifically ( Holdwick, & Wingenfeld, 1999 ; Starcke et al., 2016 ). Participants not assigned to the PASAT took a 10-min math quiz meant to represent the no-stress condition. This quiz was not difficult. Examples of questions are finding the sum of 2 plus 2 and what is 5 multiplied by 5.

Video Game Conditions

For this study, participants played either a “violent” or “non-violent” video game on the XBOX One. Participants assigned to the violent game condition played Battlefront. Battlefront is an action-packed video game wherein the player was in control of a Star Wars character who wields a lightsaber or gun throughout gameplay. Those assigned to the “non-violent” condition played portal 2. Portal 2 is an action-adventure game rated E10 + . This is a strategy video game wherein the player masqueraded as a first-person shooter wielding a portal gun which creates shortcuts throughout the game and does not cause harm to another character. Thus, the games are similar in gameplay and the use of a gun, but without violence of any kind in the portal 2 game.

Aggressive Behavior

This study utilized a modified version of the Taylor competitive reaction time task (TCRTT). This is a newer version utilizing noise blasts instead of the electric shocks, used in the original study (Taylor, 1967 ). In Taylor’s version, the participant had electrodes hooked up to their bodies and to convince the participant that they were playing against an individual they distributed a shock when the participant lost. He also had the wins and losses predetermined wherein the participant lost fifty percent of the trials. In this version, participants were asked to set the level and duration of a white noise blast acting as a punishment for their previous confederate partner. This game lasts for a total of 15 min and has 25 different trials. In the task, the wins and losses are preset as participants are not playing against a human opponent. The blast is not harmful and causes no discomfort; it is just annoying. As per the standardization suggested by Ferguson et al. ( 2008 ), aggressive behavior was measured as the averaged of the 25 intensity scores.

Data collection began following Institutional Review Board approval. Participants who signed up under the undergraduate research portal were told that the researcher was conducting a study on the effect of several tests on an individual’s ability to play games. To participate in this study, participants were asked to sign an informed consent form and to complete the STAI – Y2. Upon completion, they were asked to take a simple crossword puzzle, a distractor task to reduce hypothesis guessing. Participants were then randomly assigned to a stress condition, wherein they either took the PASAT-C or take a simple math quiz, both of which lasted 10 min. After completing the stress condition activity, participants were then randomly assigned to a video game condition, wherein they either played Battlefront, a “violent” video game, or portal 2, a “non-violent” video game. Furthermore, they were randomly assigned to play the game for 30 min with either a competent or incompetent confederate partner. Once they entered the room, they were given instructions on how to operate an XBOX One controller and how to play the game they are assigned. After the game play, participants engaged with the TCRTT task. Participants were asked to play a reaction time game which lasted around 15 min. For this game, they were informed that they were playing against their previous confederate, who is now in a separate room, and was competing against them on a separate computer. They were told that for every trial they can set the intensity and duration of white noise for their confederate as a form of punishment. Participants were also informed that they would hear the noise if they lost, while their partners would hear the noise if they won. They were told that they can set the noise level from 0 to 10 and that they can set the blast from 0 to 5 s. Post gameplay, participants were debriefed, and the true nature of the study was revealed; all hypotheses were discussed, and they were asked if they held any suspicion of the topic’s true hypotheses.

Research Design

To assess the effects of stress and video games on aggression, this study utilized a 2 × 2 × 2 (stress × game condition × competence) factorial analysis of variance. The dependent variable was the noise blast intensity (aggression). To assure that randomization worked, and conditions were not confounded by demographic factors, chi-square analyses were run for gender, and bivariate correlations for age with a group assignment. No outcomes were statistically significant, suggesting randomization was effective. As such, age and gender will not be included as covariates.

Screening, Cleaning, and Descriptive Statistics

Once data collection was completed, data were entered and analyzed using IBM SPSS Version 26. A total of 73 participants partook in the study and received credit for their participation. Demographic data for the participants are presented in Table 1 .

Descriptive statistics data are presented in Table 2 .

Hypotheses Tests

A factorial ANOVA was conducted to evaluate the study hypotheses (Table 3 ). Firstly, there was no significant effect for the stress condition on the intensity setting by participants, F (1,65) = 0.04, p  = 0.85, \({\eta }_{p}^{2}\) = 0.001. Similarly, there was also no significant effect for the video game condition on the intensity level setting, F (1,65 = 0.09, p  = 0.77, \({\eta }_{p}^{2}\) = 0.001. The confederate condition also did not have a significant effect with the intensity setting, F (1,65) = 0.05, p  = 0.828, \({\eta }_{p}^{2}\) = 0.001. Hypothesis one stated that participants when exposed to acute stress will depict greater aggressiveness toward an incompetent partner than a competent partner. There was no significant finding for this hypothesis, as the stress condition and the confederate condition showed no significant interaction with the intensity level settings, F (1,65) = 2.05, p  = 0.16, \({\eta }_{p}^{2}\) = 0.03. Related to hypothesis 3, there was no significant impact of video game condition and stress condition F (1,65) = 0.002, p  = 0.97, \({\eta }_{p}^{2}\) = 0.03. As such, hypothesis 3 was not supported.

Exploratory Analysis (H2)

We also examined the issue of whether acute stress played a greater role in causing aggressiveness towards an incompetent partner than chronic stress. For this, we conducted an OLS regression with pairwise deletion. Gender, STAI score (chronic stress), and stress condition (acute stress) were included as predictors. Although this was our H2 we note, as an oversight, we had not included the specifics of this analysis in our preregistration; thus, it should be considered exploratory. Ultimately, the regression model was non-significant F (3, 69) = 0.017, p  = 0.997.

Given null results can be difficult to interpret all three major contrasts (game condition, stress condition, and confederate competence) were reassessed using Bayesian contrasts. In each case, Bayes factors indicated support for the null for game condition (BF = 5.401), stress condition (BF = 5.550), and confederate competence (BF = 5.502). Thus, we are confident in interpreting results as supportive of the null.

The purpose of this study was to determine whether stress or violent content played a role in aggressiveness towards a cooperative partner who is incompetent when playing a video game. Although there have been several studies on the influence of stress on aggression, there is still a lack of experimental studies discussing the influence of the different types of stress on aggression especially towards another individual, and whether that individual’s actions play a role in increasing aggression. Moreover, this study attempted to examine the role of video games in aggression and whether they also influenced aggression towards another individual as this is important to several current concerns.

After conducting this study, there was no support for any of the study hypotheses. The results showed that the stress condition, whether it be acute (as primed by the PASAT) or chronic (as measured by the STAI), had no effect on the intensity setting participants gave their confederate partner. This finding illustrated that despite the participants’ exposure to stress, there was no significant impact on their aggression, which means that the form of stress the individual is experiencing does not particularly influence their decision at least in this context. Furthermore, the stress condition and confederate competence condition in interaction had no significant impact on the aggression exhibited towards participants.

The video game condition also had no effect on the intensity of the noise burst participants administered to the confederate. The findings of this study were similar to those of previously mentioned studies (e.g., Hilgard et al., 2019 ; McCarthy et al., 2016 ). There was no significant difference in intensity level setting between participants in the violent or nonviolent group, thus illustrating that the type of video game experienced had no real effect on aggression towards another individual. Additionally, the confederate competence condition, interacting with the video game condition also had no significant effect on aggression towards the confederate, thus signifying that confederate competency and an individual’s ability to further frustrate someone may not necessarily impact or increase their aggression towards them in this context. The absence of interaction effects was unable to support that stress may moderate links between violent games and aggressive behavior. Of course, it is possible that other moderators may function in other ways, but that was not evident from the current data.

Participants were also assigned to varying confederate conditions which exhibited two levels of competency, incompetent or competent, and these conditions had no significant effect on aggression. In studies like Hinsberger et al.’s ( 2016 ), it was found that participants administered shocks when individuals did not complete the judgment tasks correctly. This study’s findings differ greatly and exhibit that competency itself does not necessarily impact aggression and other factors could play a role in the intensity level setting. For example, several participants described being competitive and disliked losing, while others exhibited far more passive feelings towards their confederate. As such, many participants may not have worried greatly about the competence of the confederate.

Limitations

As with all studies, ours has limitations. Our use of the STAI, in capturing anxiety, may have only considered a portion of chronic stress. It is possible that this measure may tap into personality characteristics as much as it does chronic stress. However, prior studies have used the STAI as a measure of chronic stress (e.g., al Abdi et al., 2018 ; Valsamakis et al., 2020 ). Our sample size was not as large as we had initially intended which naturally reduces the power of our analyses. Furthermore, generalizations from experiments on aggression that take place in the lab to real-life aggression should be done only with great care.

Conclusions

Future studies should look at other factors that may also influence aggression, especially when playing a game. For instance, competition would be a great variable to observe, especially as the aggression measure was viewed as a form of competitive task. The current study is a small one and, as noted, data collection was interrupted by COVID-19. However, in combination with other studies, it appears that violent content in video games has little impact on aggressive behavior, even in combination with acute stress.

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Barrington, G., Ferguson, C.J. Stress and Violence in Video Games: Their Influence on Aggression. Trends in Psychol. 30 , 497–512 (2022). https://doi.org/10.1007/s43076-022-00141-2

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ORIGINAL RESEARCH article

The relation of violent video games to adolescent aggression: an examination of moderated mediation effect.

• 1 Research Institute of Moral Education, College of Psychology, Nanjing Normal University, Nanjing, China
• 2 The Lab of Mental Health and Social Adaptation, Faculty of Psychology, Research Center for Mental Health Education, Southwest University, Chongqing, China

To assess the moderated mediation effect of normative beliefs about aggression and family environment on exposure to violent video games and adolescent aggression, the subjects self-reported their exposure to violent video games, family environment, normative beliefs about aggression, and aggressive behavior. The results showed that there was a significant positive correlation between exposure to violent video games and adolescent aggression; normative beliefs about aggression had a mediation effect on exposure to violent video games and adolescent aggression, while family environment moderated the first part of the mediation process. For individuals with a good family environment, exposure to violent video games had only a direct effect on aggression; however, for those with poor family environment, it had both direct and indirect effects mediated by normative beliefs about aggression. This moderated mediation model includes some notions of General Aggression Model (GAM) and Catalyst Model (CM), which helps shed light on the complex mechanism of violent video games influencing adolescent aggression.

Introduction

Violent video games and aggression.

The relationship between violent video games and adolescent aggression has become a hot issue in psychological research ( Wiegman and Schie, 1998 ; Anderson and Bushman, 2001 ; Anderson et al., 2010 ; Ferguson et al., 2012 ; Greitemeyer, 2014 ; Yang et al., 2014 ; Boxer et al., 2015 ). Based on the General Aggression Model (GAM), Anderson et al. suggested that violent video games constitute an antecedent variable of aggressive behavior, i.e., the degree of exposure to violent video games directly leads to an increase of aggression ( Anderson and Bushman, 2001 ; Bushman and Anderson, 2002 ; Anderson, 2004 ; Anderson et al., 2004 ). Related longitudinal studies ( Anderson et al., 2008 ), meta-analyses ( Anderson et al., 2010 ; Greitemeyer and Mugge, 2014 ), event-related potential studies ( Bailey et al., 2011 ; Liu et al., 2015 ), and trials about juvenile delinquents ( DeLisi et al., 2013 ) showed that exposure to violent video games significantly predicts adolescent aggression.

Although Anderson et al. insisted on using the GAM to explain the effect of violent video games on aggression, other researchers have proposed alternative points of view. For example, a meta-analysis by Sherry (2001) suggested that violent video games have minor influence on adolescent aggression. Meanwhile, Ferguson (2007) proposed that publication bias (or file drawer effect) may have implications in the effect of violent video games on adolescent aggression. Publication bias means that compared with articles with negative results, those presenting positive results (such as statistical significance) are more likely to be published ( Rosenthal and Rosnow, 1991 ). A meta-analysis by Ferguson (2007) found that after publication bias adjustment, the related studies cannot support the hypothesis that violent video games are highly correlated with aggression. Then, Ferguson et al. proposed a Catalyst Model (CM), which is opposite to the GAM. According to this model, genetic predisposition can lead to an aggressive child temperament and aggressive adult personality. Individuals who have an aggressive temperament or an aggressive personality are more likely to produce violent behavior during times of environmental strain. Environmental factors act as catalysts for violent acts for an individual who have a violence-prone personality. This means that although the environment does not cause violent behavior, but it can moderate the causal influence of biology on violence. The CM model suggested that exposure to violent video games is not an antecedent variable of aggressive behavior, but only acts as a catalyst influencing its form ( Ferguson et al., 2008 ). Much of studies ( Ferguson et al., 2009 , 2012 ; Ferguson, 2013 , 2015 ; Furuya-Kanamori and Doi, 2016 ; Huesmann et al., 2017 ) found that adolescent aggression cannot be predicted by the exposure to violent video games, but it is closely related to antisocial personality traits, peer influence, and family violence.

Anderson and his collaborators ( Groves et al., 2014 ; Kepes et al., 2017 ) suggested there were major methodological shortcomings in the studies of Ferguson et al. and redeclared the validity of their own researches. Some researchers supported Anderson et al. and criticized Ferguson’s view ( Gentile, 2015 ; Rothstein and Bushman, 2015 ). However, Markey (2015) held a neutral position that extreme views should not be taken in the relationship between violent video games and aggression.

In fact, the relation of violent video games to aggression is complicated. Besides the controversy between the above two models about whether there is an influence, other studies explored the role of internal factors such as normative belief about aggression and external factors such as family environment in the relationship between violent video games and aggression.

Normative Beliefs About Aggression, Violence Video Games, and Aggression

Normative beliefs about aggression are one of the most important cognitive factors influencing adolescent aggression; they refer to an assessment of aggression acceptability by an individual ( Huesmann and Guerra, 1997 ). They can be divided into two types: general beliefs and retaliatory beliefs. The former means a general view about aggression, while the latter reflects aggressive beliefs in provocative situations. Normative beliefs about aggression reflect the degree acceptance of aggression, which affects the choice of aggressive behavior.

Studies found that normative beliefs about aggression are directly related to aggression. First, self-reported aggression is significantly correlated to normative beliefs about aggression ( Bailey and Ostrov, 2008 ; Li et al., 2015 ). General normative beliefs about aggression can predict young people’s physical, verbal, and indirect aggression ( Lim and Ang, 2009 ); retaliatory normative beliefs about aggression can anticipate adolescent retaliation behavior after 1 year ( Werner and Hill, 2010 ; Krahe and Busching, 2014 ). There is a longitudinal temporal association of normative beliefs about aggression with aggression ( Krahe and Busching, 2014 ). Normative beliefs about aggression are significantly positively related to online aggressive behavior ( Wright and Li, 2013 ), which is the most important determining factor of adolescent cyberbullying ( Kowalski et al., 2014 ). Teenagers with high normative beliefs about aggression are more likely to become bullies and victims of traditional bullying and cyberbullying ( Burton et al., 2013 ). Finally, normative beliefs about aggression can significantly predict the support and reinforcement of bystanders in offline bullying and cyberbullying ( Machackova and Pfetsch, 2016 ).

According to Bandura’s social cognitive theory ( Bandura, 1989 ), violent video games can initiate adolescents’ observational learning. In this situation, not only can they imitate the aggressive behavior of the model but also their understanding and acceptability about aggression may change. Therefore, normative beliefs about aggression can also be a mediator between violent video games and adolescent aggression ( Duan et al., 2014 ; Anderson et al., 2017 ; Huesmann et al., 2017 ). Studies have shown that the mediating role of normative beliefs about aggression is not influenced by factors such as gender, prior aggression, and parental monitoring ( Gentile et al., 2014 ).

Family Environment, Violence Video Games, and Aggression

Family violence, parenting style, and other family factors have major effects on adolescent aggression. On the one hand, family environment can influence directly on aggression by shaping adolescents’ cognition and setting up behavioral models. Many studies have found that family violence and other negative factors are positively related to adolescent aggression ( Ferguson et al., 2009 , 2012 ; Ferguson, 2013 ), while active family environment can reduce the aggressive behavior ( Batanova and Loukas, 2014 ).

On the other hand, family environment can act on adolescent aggression together with other factors, such as exposure to violent video games. Analysis of the interaction between family conflict and media violence (including violence on TV and in video games) to adolescent aggression showed that teenagers living in higher conflict families with more media violence exposure show more aggressive behavior ( Fikkers et al., 2013 ). Parental monitoring is significantly correlated with reduced media violence exposure and a reduction in aggressive behavior 6 months later ( Gentile et al., 2014 ). Parental mediation can moderate the relationship between media violence exposure and normative beliefs about aggression, i.e., for children with less parental mediation, predictability of violent media exposure on normative beliefs about aggression is stronger ( Linder and Werner, 2012 ). Parental mediation is closely linked to decreased aggression caused by violent media ( Nathanson, 1999 ; Rasmussen, 2014 ; Padilla-Walker et al., 2016 ). Further studies have shown that the autonomy-supportive restrictive mediation of parents is related to a reduction in current aggressive behavior by decreasing media violence exposure; conversely, inconsistent restrictive mediation is associated with an increase of current aggressive behavior by enhancing media violence exposure ( Fikkers et al., 2017 ).

The Current Study

Despite GAM and CM hold opposite views on the relationship between violent video games and aggression, both of the two models imply the same idea that aggression cannot be separated from internal and external factors. While emphasizing on negative effects of violent video games on adolescents’ behavior, the GAM uses internal factors to explain the influencing mechanism, including aggressive beliefs, aggressive behavior scripts, and aggressive personality ( Bushman and Anderson, 2002 ; Anderson and Carnagey, 2014 ). Although the CM considers that there is no significant relation between violent video games and aggression, it also acknowledges the role of external factors such as violent video games and family violence. Thus, these two models seem to be contradictory, but in fact, they reveal the mechanism of aggression from different points of view. It will be more helpful to explore the effect of violent video games on aggression from the perspective of combination of internal and external factors.

Although previous studies have investigated the roles of normative beliefs about aggression and family factors in the relationship between violent video games and adolescent aggression separately, the combined effect of these two factors remains unstudied. The purpose of this study was to analyze the combined effect of normative beliefs about aggression and family environment. This can not only confirm the effects of violent video games on adolescent aggression further but also can clarify the influencing mechanism from the integration of GAM and CM to a certain extent. Based on the above, the following three hypotheses were proposed:

Hypothesis 1: There is a significant positive correlation between exposure to violent video games and adolescent aggression.

Hypothesis 2: Normative beliefs about aggression are the mediator of exposure to violent video games and adolescent aggression.

Hypothesis 3: The family environment can moderate the mediation effects of normative beliefs about aggression in exposure to violent video games and adolescent aggression; exposure to violent video games, family environment, normative beliefs about aggression, and aggression constitute a moderated mediation model.

Materials and Methods

Participants.

All subjects gave informed written consent for participation in this investigation, and their parents signed parental written informed consent. The study was reviewed and approved by the Professor Committee of School of Psychology, Nanjing Normal University, which is the committee responsible for providing ethics approvals. A total of 648 Chinese middle school students participated in this study, including 339 boys and 309 girls; 419 students were from cities and towns, and 229 from the countryside. There were 277 and 371 junior and high school students, respectively. Ages ranged from 12 to 19 years, averaging 14.73 ( SD  = 1.60).

Video Game Questionnaire (VGQ)

The Video Game Questionnaire ( Anderson and Dill, 2000) required participants to list their favorite five video games and assess their use frequencies, the degree of violent content, and the degree of violent images on a 7-point scale (1, participants seldom play video games, with no violent content or image; 7, participants often play video games with many violent contents and images). Methods for calculating the score of exposure to violent video games: (score of violent content in the game + score of violent images in the game) × use frequency/5. Chen et al. (2012) found that the Chinese version of this questionnaire had high internal consistency reliability and good content validity. The Chinese version was used in this study, and the Cronbach’s α coefficient of the questionnaire was 0.88.

Aggression Questionnaire (AQ)

There were 29 items in AQ ( Buss and Perry, 1992 ), including four dimensions: physical aggression, verbal aggression, anger, and hostility. The scale used 5-point scoring criteria (1, very incongruent with my features; 5, very congruent with my features). Scores for each item were added to obtain the dimension score, and dimension scores were summed to obtain the total score. The Chinese version of AQ had good internal consistency reliability and construct validity ( Ying and Dai, 2008 ). In this study, the Chinese version was used and its Cronbach’s α coefficient was 0.83.

Family Environment Scale (FES)

The FES ( Moos, 1990 ) includes 90 true-false questions and is divided into 10 subscales, including cohesion, expressiveness, conflict, independence, achievement-orientation, intellectual-cultural orientation, active-recreational orientation, moral-religious emphasis, organization, and control. The Chinese version of FES was revised by Fei et al. (1991) and used in this study. Three subscales closely related to aggression were selected, including cohesion, conflict, and moral-religious emphasis, with 27 items in total. The family environment score was the sum of scores of these three subscales (the conflict subscale was first inverted). The Cronbach’s α coefficient of the questionnaire was 0.75.

Normative Beliefs About Aggression Scale (NOBAGS)

There are 20 items in the NOBAGS ( Huesmann and Guerra, 1997 ), which includes retaliation (12 items) and general (8 items) aggression belief. A 4-point Likert scale is used (1, absolutely wrong; 4, absolutely right). The subjects were asked to assess the accuracy of the behavior described in each item. High score means high level of normative beliefs about aggression. The revised Chinese version of NOBAGS consists of two factors: retaliation (nine items) and general (six items) aggression belief. Its internal consistency coefficient and test-retest reliability are 0.81 and 0.79. Confirmative factor analysis showed that this version has good construct validity: χ 2  = 280.09, df  = 89, χ 2 / df  = 3.15, RMSEA = 0.07, SRMR = 0.04, NFI = 0.95, NNFI = 0.96, and CFI = 0.96 ( Shao and Wang, 2017 ). In this study, the Cronbach’s α coefficient of the Chinese version was 0.88.

Group testing was performed in randomly selected classes of six middle schools. All subjects completed the above four questionnaires.

Data Analysis

IBM SPSS Statistics 22 was used to analysis the correlations among study variables, the mediating effect of normative beliefs about aggression on the relationship between exposure to violent video games and aggression, and the moderating role of family environment in the relationship between exposure to violent video games and normative beliefs about aggression. In order to validate the moderated mediation model, Mplus 7 was also used.

Correlation Analysis Among Study Variables

In this study, self-reported questionnaires were used to collect data, and results might be influenced by common method bias. Therefore, the Harman’s single-factor test was used to assess common method bias before data analysis. The results showed that eigenvalues of 34 unrotated factors were greater than 1, and the amount of variation explained by the first factor was 10.01%, which is much less than 40% of the critical value. Accordingly, common method bias was not significant in this study.

As described in Table 1 , the degree of exposure to violent video games showed significant positive correlations to normative beliefs about aggression and aggression; family environment was negatively correlated to normative beliefs about aggression and aggression; normative beliefs about aggression were significantly and positively related to aggression. The gender difference of exposure to violent video games ( t  = 7.93, p  < 0.001) and normative beliefs about aggression ( t  = 2.74, p  < 0.01) were significant, which boys scored significantly higher than girls.

Table 1 . Means, standard deviations, and Pearson correlations among study variables.

Mediating Effect Analysis

To examine the mediation effect of normative beliefs about aggression on the relationship between exposure to violent video games and aggression, gender factor was controlled firstly. Stepwise regression analysis showed that the regression of aggression to violent video games ( c  = 0.28, t  = 6.96, p  < 0.001), the regression of normative beliefs about aggression to violent video games ( a  = 0.19, t  = 4.69, p  < 0.001), and the regression of aggression to violent video games ( c ′ = 0.22, t  = 5.69, p  < 0.001) and normative beliefs about aggression ( b  = 0.31, t  = 8.25, p  < 0.001) were all significant. Thus, normative beliefs about aggression played a partial mediating role in exposure to violent video games and aggression. The mediation effect value was 0.06, accounting for 21.43% (0.06/0.28) of the total effect.

Moderated Mediation Effect Analysis

After standardizing scores of exposure to violent videogames, normative beliefs about aggression, family environment, and aggression, two interaction terms were calculated, including family environment × exposure to violent video games and family environment × normative beliefs about aggression. Regression analysis was carried out after controlling gender factor ( Table 2 ).

Table 2 . Moderated mediation effect analysis of the relationship between violent video exposure and aggression.

In the first step, a simple moderated model (Model 1) between exposure to violent video games and aggression was established. The result showed that exposure to violent video games had a significant effect on aggression ( c 1  = 0.24, t  = 6.13, p  < 0.001), while the effect of family environment × exposure to violent video games on aggression was not significant ( c 3  = 0.05, t  = −1.31, p  = 0.19), indicating that the relationship between exposure to violent video games and aggression was not moderated by family environment.

Next, a moderated model (Model 2) between exposure to violent video games and normative beliefs about aggression was established. The results showed that exposure to violent video games had a significant effect on normative beliefs about aggression ( a 1  = 0.13, t  = 3.42, p  < 0.001), and the effect of family environment × exposure to violent video games on normative beliefs about aggression was significant ( a 3  = −0.13, t  = −3.63, p  < 0.01).

In the third step, a moderated mediation model (Model 3) between exposure to violent video games and aggression was established. As shown in Table 2 , the effect of normative beliefs about aggression on aggression was significant ( b 1  = 0.24, t  = 6.15, p  < 0.001), and the effect of family environment × exposure to violent video games on normative beliefs about aggression was not significant ( b 2  = 0.02, t  = 0.40, p  = 0.69). Because both a 3 and b 1 were significant, exposure to violent video games, family environment, normative beliefs about aggression, and aggression constituted a moderated mediation model. Normative beliefs about aggression played a mediating role between exposure to violent video games and aggression, while family environment was a moderator between exposure to violent video games and normative beliefs about aggression. Mplus analysis proved that the moderated mediation model had good model fitting (χ 2 / df  = 1.54, CFI = 0.99, TLI = 0.98, RMSEA = 0.03, and SRMR = 0.01).

To further analyze the moderating effect of the family environment and exposure to violent video games on normative beliefs about aggression, the family environment was divided into the high and low groups, according to the principle of standard deviation, and a simple slope test was performed ( Figure 1 ). The results found that for individuals with high score of family environment, prediction of exposure to violent video games to normative beliefs about aggression was not significant ( b  = 0.08, SE  = 0.08, p  = 0.37). For individuals with low score of family environment, exposure to violent video games could significantly predict normative beliefs about aggression ( b  = 0.34, SE  = 0.09, p  < 0.001). Based on the overall findings, individuals with high scores of family environment showed a nonsignificant mediating effect of normative beliefs about aggression on the relation of exposure to violent video games and aggression; however, for individuals with low scores of family environment, normative beliefs about aggression played a partial mediating role in the effect of exposure to violent video games on aggression.

Figure 1 . The moderating effect of the family environment on the relationship between violent video game exposure and normative beliefs about aggression.

Main Findings and Implications

This study found a significantly positive correlation between exposure to violent video games and adolescent aggression, corroborating existing studies ( Anderson, 2004 ; Anderson et al., 2010 ; DeLisi et al., 2013 ; Greitemeyer and Mugge, 2014 ). Anderson et al. (2017) assessed teenagers in Australia, China, Germany, the United States, and other three countries and found that exposure to violent media, including television, movies, and video games, is positively related to adolescent aggression, demonstrating cross-cultural consistency; 8% of variance in aggression could be independently explained by exposure to violent media. In this study, after controlling for gender and family environment, R 2 for exposure to violent video games in predicting adolescent aggression was 0.05, indicating that 5% of variation in adolescent aggression could be explained by exposure to violent media. These consistent findings confirm the effect of exposure to violent video games on adolescent aggression and can be explained by the GAM. According to the GAM ( Bushman and Anderson, 2002 ; Anderson and Carnagey, 2014 ), violent video games can make teenagers acquire, repeat, and reinforce aggression-related knowledge structures, including aggressive beliefs and attitude, aggressive perceptual schemata, aggressive expectation schemata, aggressive behavior scripts, and aggression desensitization. Therefore, aggressive personality is promoted, increasing the possibility of aggressive behavior. The Hypothesis 1 of this study was validated and provided evidence for the GAM.

As shown above, normative beliefs about aggression had a partial mediation effect on the relationship between exposure to violent video games and aggression. Exposure to violent video games, on the one hand, can predict adolescent aggression directly; on the other hand, it had an indirect effect on adolescent aggression via normative beliefs about aggression. According to the above results, when exposure to violent video games changes by 1 standard deviation, adolescent aggression varies by 0.28 standard deviation, with 0.22 standard deviation being a direct effect of exposure to violent video games on adolescent aggression and 0.06 standard deviation representing the effect through normative beliefs about aggression. Too much violence in video games makes it easy for individuals to become accustomed to violence and emotionally apathetic towards the harmful consequences of violence. Moreover, it can make individuals accept the idea that violence is a good way of problem solving, leading to an increase in normative beliefs about aggression; under certain situational cues, it is more likely to become violent or aggressive. This conclusion is supported by other studies ( Gentile et al., 2014 ; Anderson et al., 2017 ; Huesmann et al., 2017 ). Like Hypothesis 1, Hypothesis 2 was validated the GAM.

One of the main findings of this study was the validation of Hypothesis 3: a moderated mediation model was constructed involving exposure to violent video games, family environment, normative beliefs about aggression, and aggression. Family environment moderated the first half of the mediation process of violent video games, normative beliefs about aggression, and aggression. In this study, family environment encompassed three factors, including (1) cohesion reflecting the degree of mutual commitment, assistance, and support among family members; (2) conflict reflecting the extent of anger, aggression, and conflict among family members; and (3) moral-religious emphasis reflecting the degree of emphasis on ethics, religion, and values. Individuals with high scores of family environment often help each other; seldom show anger, attack, and contradiction openly; and pay more attention to morality and values. These positive aspects would help them understand violence in video games from the right perspective, reduce recognition and acceptance of violence or aggression, and diminish the effect of violent video games on normative beliefs about aggression. Hence, exposure to violent video games could not predict normative beliefs about aggression of these individuals. By contrast, individuals with low scores of family environment are less likely to help each other; they often openly show anger, attack, and contradiction and do not pay much attention to morality and values. These negative aspects would not decrease but increase their acceptance of violence and aggression. For these individuals, because of the lack of mitigation mechanisms, exposure to violent video games could predict normative beliefs about aggression significantly.

The moderated mediation model of the relationship between exposure to violent video games and aggression could not only help reveal that exposure to violent video games can affect aggression but also provide an elaboration of the influencing mechanism. According to this model, for individuals with high scores of family environment, exposure to violent video games had only direct effect on aggression. However, for those with low scores of family environment, there was not only a direct effect of exposure to violent video games on aggression but also an indirect effect mediated by normative beliefs about aggression. In short, exposure to violence video games affecting aggression through normative beliefs about aggression is more likely to happen to adolescents with poor family environment than those with good family environment. That is, generation of adolescent aggression is not only related to internal cognitive factors but also to external situations. As Piotrowski and Valkenburg ( Piotrowski and Valkenburg, 2015 ; Valkenburg, 2015 ) pointed out, the effect of violent video games/media on adolescents is a complex interaction of dispositional, developmental, and social factors, and individual differences in susceptibility to these three factors determine the nature and the extent of this influence. The proposed model incorporated some perspectives of GAM and CM: while confirming the effect of exposure to violent video games on aggression occurrence, the combined effect of individual and environmental factors was verified.

Compared with the simple mediation or moderation model, the present moderated mediation model provided deeper insights into the internal mechanism of the effect of violent video games on aggression, providing inspirations for preventing adolescent aggression. First, in view of the close relationship between exposure to violent video games and adolescent aggression, relevant government departments should continue to improve the grading system of video games; meanwhile, parents should appropriately monitor the types of video games used by teenagers as well as the time spent and reduce the degree of exposure to violent video games. Second, by allowing teenagers to objectively distinguish between violence in games and reality, the mediating role of normative beliefs about aggression could inspire people to identify rational ways to solve violence problems and to experience the hurtful consequences of aggression. This would help adolescents change normative beliefs about aggression, establish a correct view of right and wrong, and reduce the occurrence of aggression. Finally, the moderating effect of family environment on the mediation process suggests that more attention should be paid to the important role of family environment. On the one hand, family education is closely related to adolescent aggression. Then, parents should create a good family atmosphere, publicly show anger and aggression as little as possible, and advocate and practice positive moral values. Parents should adopt authoritative styles, abandoning autocratic and indulgent parenting styles ( Casas et al., 2006 ; Sandstrom, 2007 ; Underwood et al., 2009 ; Kawabata et al., 2011 ) to minimize the negative effect of exposure to violent video games. On the other hand, for teenagers with poor family environment, while reducing exposure to violent video games, it is particularly important to change their normative beliefs about aggression, no longer viewing aggression as an alternative way to solve problems.

Limitations

Limitations of the current study should be mentioned. First, only Chinese school students were assessed, in a relatively small number, which could affect sample representativeness. A large sample of teenagers from different countries and in different ages, also including juvenile offenders, would be more accurate in revealing the effect of violent video games on adolescent aggression. Second, this study only focused on violent video games, not involving violent media such as internet and television, daily life events, wars, and other major social events. Indeed, these factors also have important effects on adolescent aggression, and their influencing mechanisms and combined effect are worth investigating further. Third, this study mainly adopted the self-report method. Use of peer, parent, or teacher reports to assess exposure to violent video games and aggression would help improve the effectiveness of the study. Fourth, there might be other mediators, moderating variables and relational models. In addition to normative beliefs about aggression and family environment, individual emotions, personality characteristics, school climate, and companions may play mediating or moderating roles in the relationship between violent video games and aggression. This study developed a moderated mediation model between family environment and normative beliefs about aggression, but the possibility of multiple mediation and mediated moderation models cannot be ruled out.

The current study showed that exposure to violent video games is positively related to adolescent aggression; normative beliefs about aggression have a mediating effect on exposure to violent video games and adolescent aggression, while the family environment regulates the first part of the mediation process. For individuals with good family environment, exposure to violent video games only has a direct effect on aggression; however, for those with poor family environment, there is an indirect effect mediated by normative beliefs about aggression alongside a direct effect. This moderated mediation model incorporates some perspectives of GAM and CM, enriching studies of generative mechanism of adolescent aggression.

Author Contributions

YW and RS conceived the idea of the study. RS analyzed the data. YW and RS interpreted the results and wrote the paper. YW discussed the results and revised the manuscript.

This study was supported by a grant from the National Social Science Foundation of China (14CSH017) to YW.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Underwood, M. K., Beron, K. J., and Rosen, L. H. (2009). Continuity and change in social and physical aggression from middle childhood through early adolescence. Aggress. Behav. 35, 357–375. doi: 10.1002/ab.20313

Valkenburg, P. M. (2015). The limited informativeness of meta-analyses of media effects. Perspect. Psychol. Sci. 10, 680–682. doi: 10.1177/1745691615592237

Werner, N. E., and Hill, L. G. (2010). Individual and peer group normative beliefs about relational aggression. Child Dev. 81, 826–836. doi: 10.1111/j.1467-8624.2010.01436.x

Wiegman, O., and Schie, E. G. (1998). Video game playing and its relations with aggressive and prosocial behaviour. Brit. J. Soc. Psychol. 37, 367–378. doi: 10.1111/j.2044-8309.1998.tb01177.x

Wright, M. F., and Li, Y. (2013). Normative beliefs about aggression and cyber aggression among young adults: a longitudinal investigation. Aggress. Behav. 39, 161–170. doi: 10.1002/ab.21470

Yang, G. S., Huesmann, L. R., and Bushman, B. J. (2014). Effects of playing a violent video game as male versus female avatar on subsequent aggression in male and female players. Aggress. Behav. 40, 537–541. doi: 10.1002/ab.21551

Ying, X., and Dai, C. (2008). Empathy and aggressive behavior of middle school students: the mediating effect of the anger-hostility action. Psychol. Dev. Educ. 24, 73–78.

Keywords: violence video games, aggression, family environment, normative beliefs about aggression, moderated mediation effect

Citation: Shao R and Wang Y (2019) The Relation of Violent Video Games to Adolescent Aggression: An Examination of Moderated Mediation Effect. Front. Psychol . 10:384. doi: 10.3389/fpsyg.2019.00384

Received: 25 September 2017; Accepted: 07 February 2019; Published: 21 February 2019.

Reviewed by:

Copyright © 2019 Shao and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yunqiang Wang, [email protected] ; [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

The evidence that video game violence leads to real-world aggression

A 2018 meta-analysis found that there is a small increase in real-world physical aggression among adolescents and pre-teens who play violent video games. Led by Jay Hull, a social psychologist at Dartmouth College, the study team pooled data from 24 previous studies in an attempt to avoid some of the problems that have made the question of a connection between gaming and aggression controversial.

Many previous studies, according to a story in Scientific American, have been criticized by “a small but vocal cadre of researchers [who] have argued much of the work implicating video games has serious flaws in that, among other things, it measures the frequency of aggressive thoughts or language rather than physically aggressive behaviors like hitting or pushing, which have more real-world relevance.”

Hull and team limited their analysis to studies that “measured the relationship between violent video game use and overt physical aggression,” according to the Scientific American article .

The Dartmouth analysis drew on 24 studies involving more than 17,000 participants and found that “playing violent video games is associated with increases in physical aggression over time in children and teens,” according to a Dartmouth press release describing the study , which was published Oct. 1, 2018, in the Proceedings of the National Academy of Sciences .

The studies the Dartmouth team analyzed “tracked physical aggression among users of violent video games for periods ranging from three months to four years. Examples of physical aggression included incidents such as hitting someone or being sent to the school principal’s office for fighting, and were based on reports from children, parents, teachers, and peers,” according to the press release.

The study was almost immediately called in to question. In an editorial in Psychology Today , a pair of professors claim the results of the meta-analysis are not statistically significant. Hull and team wrote in the PNAS paper that, while small, the results are indeed significant. The Psychology Today editorial makes an appeal to a 2017 statement by the American Psychological Association’s media psychology and technology division “cautioning policy makers and news media to stop linking violent games to serious real-world aggression as the data is just not there to support such beliefs.”

It should be noted, however, that the 2017 statement questions the connection between “serious” aggression while the APA Resolution of 2015 , based on a review of its 2005 resolution by its own experts, found that “the link between violent video game exposure and aggressive behavior is one of the most studied and best established. Since the earlier meta-analyses, this link continues to be a reliable finding and shows good multi-method consistency across various representations of both violent video game exposure and aggressive behavior.”

While the effect sizes are small, they’ve been similar across many studies, according to the APA resolution. The problem has been the interpretation of aggression, with some writers claiming an unfounded connection between homicides, mass shootings, and other extremes of violence. The violence the APA resolution documents is more mundane and involves the kind of bullying that, while often having dire long-term consequences, is less immediately dangerous: “insults, threats, hitting, pushing, hair pulling, biting and other forms of verbal and physical aggression.”

Minor and micro-aggressions, though, do have significant health risks, especially for mental health. People of color, LGBTQ people , and women everywhere experience higher levels of depression and anger, as well as stress-related disorders, including heart disease, asthma, obesity, accelerated aging, and premature death. The costs of even minor aggression are laid at the feet of the individuals who suffer, their friends and families, and society at large as the cost of healthcare skyrockets.

Finally, it should be noted that studies looking for a connection between game violence and physical aggression are not looking at the wider context of the way we enculturate children, especially boys. As WSU’s Stacey Hust and Kathleen Rodgers have shown, you don’t have to prove a causative effect to know that immersing kids in games filled with violence and sexist tropes leads to undesirable consequences, particularly the perpetuation of interpersonal violence in intimate relationships.

No wonder, then, that when feminist media critic Anita Saarkesian launched her YouTube series, “ Tropes vs. Women in Video Games ,” she was the target of vitriol and violence. Years later she’d joke about “her first bomb threat,” but that was only after her life had been upended by the boys club that didn’t like “this woman” showing them the “grim evidence of industry-wide sexism.”

Read more about WSU research and study on video games in “ What’s missing in video games .”

Violent Video Games and Aggression: The Connection Is Dubious, at Best

• Childhood Development
• Perspectives on Psychological Science
• Video Games

Summary: If you are worried about violent video games triggering aggressive behavior in children, new research may help to alleviate your concerns.

The coronavirus pandemic put a damper on many traditional summertime activities for kids, like trips to the pool and youth camps. This gave more opportunity for children to socialize with friends virtually through online gaming. But many hours of extra screen time may have worried parents, especially in light of a highly publicized 2015 report by the American Psychological Association (APA) linking violent video games with aggressive behavior in children.

However, a recent reanalysis of these findings published in the journal Perspectives on Psychological Science came to a very different conclusion, finding no clear link between video game violence and aggression in children. Both the 2015 and the 2020 studies were meta-analyses, statistical methods of finding significant patterns in a large group of independent studies.

“Our new meta-analysis found that the evidence base was not sufficient to make the conclusions outlined in the 2015 report,” said Christopher J. Ferguson, lead author on the new paper and a professor of psychology at Stetson University. “We found that violent video games do not appear to be linked to aggression.”

When Ferguson and his colleagues reexamined the data used in the earlier meta-analysis, they found that it did not include most of the existing studies of video games and violence and failed to take quality issues into consideration.

“Studies that are well designed, such as those using standardized and well-validated aggression measures, almost never find evidence for negative, violent effects,” said Ferguson. “Our new meta-analysis also illustrates the need to focus on well-designed studies when researching the impact of violent media.”

“Games are now more important than ever for socialization, feeling autonomy and control during an uncertain time, and just de-stressing,” said Ferguson.

Additional research on the potential connection between video games and violent behavior is featured in the APS Research Topic Video Games and Violence .

Reference : Ferguson, C. J., Coperhaver, A., & Marley, P. (2020). Reexamining the Findings of the American Psychological Association’s 2015 Task Force on Violent Media: A meta-analysis. Perspectives on Psychological Science . Advance online publication. https://doi.org/10.1177/1745691620927666

Perspectives on Psychological Science  is a bimonthly journal publishing an eclectic mix of provocative reports and articles, including broad integrative reviews, overviews of research programs, meta-analyses, theoretical statements, and articles on topics such as the philosophy of science, opinion pieces about major issues in the field, autobiographical reflections of senior members of the field, and even occasional humorous essays and sketches.

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The effects of playing video games on well-being seem to depend largely on why and how an individual chooses to partake.

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Violent Video Games and Aggression

After mass shootings, the media and public officials often question the role of the shooter’s video game habits.

The American Psychological Association (APA) considers violent video games a risk factor for aggression . [1] In 2017, the APA Task Force on Violent Media concluded that violent video game exposure was linked to increased aggressive behaviors, thoughts, and emotions, as well as decreased empathy. However, it is not clear whether violent video game exposure was linked to criminality or delinquency.

Do Violent Video Games Increase Aggression?

Studies have shown that playing violent video games can increase aggressive thoughts, behaviors, and feelings in both the short-term and long-term. [2] Violent video games can also desensitize people to seeing aggressive behavior and decrease prosocial behaviors such as helping another person and feeling empathy (the ability to understand others). The longer that individuals are exposed to violent video games, the more likely they are to have aggressive behaviors, thoughts, and feelings. These effects have been seen in studies in both Eastern and Western countries. Although males spend more time than females playing violent video games, violent video game exposure can increase aggressive thoughts, behaviors, and feelings in both sexes.

Aggressive behavior is measured by scientists in a number of ways. Some studies looked at self-reports of hitting or pushing, and some looked at peer or teacher ratings on aggressive behaviors. Other studies looked at how likely an individual was to subject others to an unpleasant exposure to hot sauce or a loud noise after playing violent video games.

Unfortunately, few studies have been completed on violent video game exposure and aggression in children under age 10. There is also little information about the impact of violent video game exposure on minority children.

There have not been many studies on the effects of different characteristics of video games, such as perspective or plot. However, some studies have found that competition among players in video games is a better predictor of aggressive behavior than is the level of violence. [3] 

Do Violent Video Games Increase Violence?

Violence is a form of aggression, but not all aggressive behaviors are violent. Very few studies have looked at whether playing violent video games increases the chances of later delinquency, criminal behavior, or lethal violence. Such studies are difficult to conduct, and require very large numbers of children. It makes sense that since playing violent video games tends to increase the level of aggressive behavior it would also results in more lethal violence or other criminal behaviors, but there is no clear evidence to support that assumption.

In the aftermath of the Parkland shooting in Florida in 2018, policymakers are again questioning the influence of violent video games. The Entertainment Software Rating Board (ESRB) affirms that their rating system is effective, but the APA Task Force on Violent Media recommends that the ESRB revise their rating system to make the level of violence clearer. The Task Force also recommends that further research must be done using delinquency, violence, and criminal behavior as outcomes to determine whether or not violent video games are linked to violence.

Bottom Line

It is important to keep in mind that violent video game exposure is only one risk factor of aggressive behavior. For example, mental illness, adverse environments, and access to guns are all risk factors of aggression and violence.

All articles are reviewed and approved by  Dr. Diana Zuckerman and other senior staff.

The  National Center for Health Research  is a nonprofit, nonpartisan research, education and advocacy organization that analyzes and explains the latest medical research and speaks out on policies and programs. We do not accept funding from pharmaceutical companies or medical device manufacturers.  Find out how you can support us here .

References :

• The American Psychological Association Task Force on Violent Media. (2017). The American Psychological Association Task Force Assessment of Violent Video Games: Science in the Service of Public Interest. American Psychologist . 72(2): 126-143. Retrieved from http://dx.doi.org/10.1037/a0040413 . Accessed on March 9, 2018.
• Anderson CA, Shibuya A, Ihori N, Swing EL, Bushman BJ, Sakamoto A, Rothstein HR, Muniba. Violent Video Game Effects on Aggression, Empathy, and Prosocial Behavior in Eastern and Western Countries: A Meta-Analytic Review. Psychological Bulletin . 2010.
• Adachi, PJ and Willoughby, T. (2013). Demolishing the Competition: The Longitudinal Link Between Competitive Video Games, Competitive Gambling, and Aggression. Journal of Youth Adolescence. 42(7): 1090-104. doi: 10.1007/s10964-013-9952-2.
• Sanstock, JW. A Topical Approach to Life Span Development 4th Ed. New York: McGraw-Hill, 2007. Ch 15. 489-491
• Lemmens JS, Valkenburg PM, Peter J. The Effects of Pathological Gaming on Aggressive Behavior. Journal of Youth Adolescence . 2010.
• Huesmann LR, Moise J, Podolski CP, Eron LD. (2003). Longitudinal relations between childhood exposure to media violence and adult aggression and violence. Developmental Psychology . 35:201-221.

PSY 327: Abnormal Psychology: Empirical Research/PsycINFO

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Articles on empirical research can be accessed by completing a search in the library databases , such as PsycINFO & PsyArticles (see link below).

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• The effect of video game competition and violence on aggressive behavior: Which characteristic has the greatest influence?
• Irritability and behavioral symptom dimensions of oppositional defiant disorder in young adults Johnston, O. G., Cruess, D. G., & Burke, J. D. (2020). Irritability and behavioral symptom dimensions of oppositional defiant disorder in young adults: Associations with DSM-5 pathological personality traits. Journal of Psychopathology and Behavioral Assessment, 42(3), 424–435.

Video Games & Violence: Empirical Research Examples

• Violent video games and physical aggression: Evidence for a selection effect among adolescents.
• A 'dry eye' for victims of violence: Effects of playing a violent video game on pupillary dilation to victims and on aggressive behavior.
• Intense acts of violence during video game play make daily life aggression appear innocuous: A new mechanism why violent video games increase aggression.
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Helldivers 2 player uses 840 hours of research to determine the most popular Stratagems

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Helldivers 2 is a game that you can play however you want to due to its very versatile load-outs and enemy types. Whether you prefer to carry Assault Rifles, Shotguns, or SMGs, go in guns blazing, or be more stealth-focused, and whether you prefer to fight Automatons or Terminids, you can tailor your experience to suit you.

U/Bigenemy000 took to the Helldivers 2 sub-Reddit to share data collected through 840 hours of gameplay, which the player has used to track what Stratagems were being used the most and least by players. This could help determine what to carry yourself so you can maximize your destruction capabilities.

Here is the full list in text format, since it can be difficult to identify them by icon alone.

81-100 times:

• Shield Generator Pack
• LAS-99 Quasar Cannon
• Eagle 500KG Bomb
• Eagle Cluster Bomb
• Orbital Railcannon Strike
• Orbital Laser

61-80 Times:

• Eagle Airstrike
• Orbital Walking Barrage
• Orbital 120mm Barrage
• AC-8 Autocannon
• FLAM-40 Flamethrower

41-60 Times:

• APW-1 Anti-Materiel Rifle
• A/AC-8 Autocannon Sentry
• A/M-12 Mortar Sentry
• Orbital 380mm HE Barrage

21-40 Times:

• AX/AR-23 Guard Dog
• EAT-17 Expendable Anti-Tank
• ARC-3 ArcThrower
• Eagle110mm Rocket Pods

11-20 Times:

• M-105 Stalwart
• GL-21 Grenade Launcher
• FAF-14 Spear
• GR-8 Recoilless Rifle
• Eagle Napalm Airstrike
• Orbital Airburst Strike

1-10 Times:

• EXO-45 Patriot Exosuit
• AX/LAS-5 Guard Dog Rover
• B-1 Supply Pack
• LIFT-850 Jump Pack
• RS-422 Railgun
• LAS-98 Laser Cannon
• MG-206 Heavy Machine Gun
• FX-12 Shield Generator Relay
• A/M-23 EMS Mortar Sentry
• A/G-16 Gatling Sentry
• MD-14 Incendiary Mines
• Orbital Gatling Barrage
• Eagle Smoke Strike

Never Saw It Being Brought:

• RL-77 Airburst Rocket Launcher
• SH-20 Ballistic Shield Backpack
• A/MLS-4X Rocket Sentry
• MD-6 Anti-Personnel Minefield
• A/ARC-3 TeslaTower
• E/MG-101 HMG Emplacement
• Orbital EMS Strike
• Orbital Gas Strike
• Eagle Strafing Run
• Orbital Smoke Strike

Only Saw Being Brought By New Players Level 5 Or Under

• A/MG-43 Machine Gun Sentry
• Orbital Precision Strike
• MG-43 Machine Gun

Of course, this isn’t a definitive list of what is worth using and what isn’t in Helldivers 2, as everyone’s play style is different. For example, I always carry the Recoilless Rifle due to its multiple reloads that are fairly quick, despite it not being as popular as the Quasar Cannon or Expendable Anti-Tank.

With the new Major Order going live, which calls for an Automaton planet to be successfully liberated, this could be a good opportunity to see what other players are using and try out some new Stratagems. If you want to tweak the rest of your loadout, we highly recommend checking out our Helldivers 2 best weapons guide and best armor guide .

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• About Adverse Childhood Experiences
• Risk and Protective Factors
• Program: Essentials for Childhood: Preventing Adverse Childhood Experiences through Data to Action
• Adverse childhood experiences can have long-term impacts on health, opportunity and well-being.
• Adverse childhood experiences are common and some groups experience them more than others.

What are adverse childhood experiences?

Adverse childhood experiences, or ACEs, are potentially traumatic events that occur in childhood (0-17 years). Examples include: 1

• Experiencing violence, abuse, or neglect.
• Witnessing violence in the home or community.
• Having a family member attempt or die by suicide.

Also included are aspects of the child’s environment that can undermine their sense of safety, stability, and bonding. Examples can include growing up in a household with: 1

• Substance use problems.
• Mental health problems.
• Instability due to parental separation.
• Instability due to household members being in jail or prison.

The examples above are not a complete list of adverse experiences. Many other traumatic experiences could impact health and well-being. This can include not having enough food to eat, experiencing homelessness or unstable housing, or experiencing discrimination. 2 3 4 5 6

Quick facts and stats

ACEs are common. About 64% of adults in the United States reported they had experienced at least one type of ACE before age 18. Nearly one in six (17.3%) adults reported they had experienced four or more types of ACEs. 7

Preventing ACEs could potentially reduce many health conditions. Estimates show up to 1.9 million heart disease cases and 21 million depression cases potentially could have been avoided by preventing ACEs. 1

Some people are at greater risk of experiencing one or more ACEs than others. While all children are at risk of ACEs, numerous studies show inequities in such experiences. These inequalities are linked to the historical, social, and economic environments in which some families live. 5 6 ACEs were highest among females, non-Hispanic American Indian or Alaska Native adults, and adults who are unemployed or unable to work. 7

ACEs are costly. ACEs-related health consequences cost an estimated economic burden of $748 billion annually in Bermuda, Canada, and the United States. 8

ACEs can have lasting effects on health and well-being in childhood and life opportunities well into adulthood. 9 Life opportunities include things like education and job potential. These experiences can increase the risks of injury, sexually transmitted infections, and involvement in sex trafficking. They can also increase risks for maternal and child health problems including teen pregnancy, pregnancy complications, and fetal death. Also included are a range of chronic diseases and leading causes of death, such as cancer, diabetes, heart disease, and suicide. 1 10 11 12 13 14 15 16 17

ACEs and associated social determinants of health, such as living in under-resourced or racially segregated neighborhoods, can cause toxic stress. Toxic stress, or extended or prolonged stress, from ACEs can negatively affect children’s brain development, immune systems, and stress-response systems. These changes can affect children’s attention, decision-making, and learning. 18

Children growing up with toxic stress may have difficulty forming healthy and stable relationships. They may also have unstable work histories as adults and struggle with finances, jobs, and depression throughout life. 18 These effects can also be passed on to their own children. 19 20 21 Some children may face further exposure to toxic stress from historical and ongoing traumas. These historical and ongoing traumas refer to experiences of racial discrimination or the impacts of poverty resulting from limited educational and economic opportunities. 1 6

Adverse childhood experiences can be prevented. Certain factors may increase or decrease the risk of experiencing adverse childhood experiences.

Preventing adverse childhood experiences requires understanding and addressing the factors that put people at risk for or protect them from violence.

Creating safe, stable, nurturing relationships and environments for all children can prevent ACEs and help all children reach their full potential. We all have a role to play.

• Merrick MT, Ford DC, Ports KA, et al. Vital Signs: Estimated Proportion of Adult Health Problems Attributable to Adverse Childhood Experiences and Implications for Prevention — 25 States, 2015–2017. MMWR Morb Mortal Wkly Rep 2019;68:999-1005. DOI: http://dx.doi.org/10.15585/mmwr.mm6844e1 .
• Cain KS, Meyer SC, Cummer E, Patel KK, Casacchia NJ, Montez K, Palakshappa D, Brown CL. Association of Food Insecurity with Mental Health Outcomes in Parents and Children. Science Direct. 2022; 22:7; 1105-1114. DOI: https://doi.org/10.1016/j.acap.2022.04.010 .
• Smith-Grant J, Kilmer G, Brener N, Robin L, Underwood M. Risk Behaviors and Experiences Among Youth Experiencing Homelessness—Youth Risk Behavior Survey, 23 U.S. States and 11 Local School Districts. Journal of Community Health. 2022; 47: 324-333.
• Experiencing discrimination: Early Childhood Adversity, Toxic Stress, and the Impacts of Racism on the Foundations of Health | Annual Review of Public Health https://doi.org/10.1146/annurev-publhealth-090419-101940 .
• Sedlak A, Mettenburg J, Basena M, et al. Fourth national incidence study of child abuse and neglect (NIS-4): Report to Congress. Executive Summary. Washington, DC: U.S. Department of Health an Human Services, Administration for Children and Families.; 2010.
• Font S, Maguire-Jack K. Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse Negl. 2016;51:390-399.
• Swedo EA, Aslam MV, Dahlberg LL, et al. Prevalence of Adverse Childhood Experiences Among U.S. Adults — Behavioral Risk Factor Surveillance System, 2011–2020. MMWR Morb Mortal Wkly Rep 2023;72:707–715. DOI: http://dx.doi.org/10.15585/mmwr.mm7226a2 .
• Bellis, MA, et al. Life Course Health Consequences and Associated Annual Costs of Adverse Childhood Experiences Across Europe and North America: A Systematic Review and Meta-Analysis. Lancet Public Health 2019.
• Adverse Childhood Experiences During the COVID-19 Pandemic and Associations with Poor Mental Health and Suicidal Behaviors Among High School Students — Adolescent Behaviors and Experiences Survey, United States, January–June 2021 | MMWR
• Hillis SD, Anda RF, Dube SR, Felitti VJ, Marchbanks PA, Marks JS. The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial consequences, and fetal death. Pediatrics. 2004 Feb;113(2):320-7.
• Miller ES, Fleming O, Ekpe EE, Grobman WA, Heard-Garris N. Association Between Adverse Childhood Experiences and Adverse Pregnancy Outcomes. Obstetrics & Gynecology . 2021;138(5):770-776. https://doi.org/10.1097/AOG.0000000000004570 .
• Sulaiman S, Premji SS, Tavangar F, et al. Total Adverse Childhood Experiences and Preterm Birth: A Systematic Review. Matern Child Health J . 2021;25(10):1581-1594. https://doi.org/10.1007/s10995-021-03176-6 .
• Ciciolla L, Shreffler KM, Tiemeyer S. Maternal Childhood Adversity as a Risk for Perinatal Complications and NICU Hospitalization. Journal of Pediatric Psychology . 2021;46(7):801-813. https://doi.org/10.1093/jpepsy/jsab027 .
• Mersky JP, Lee CP. Adverse childhood experiences and poor birth outcomes in a diverse, low-income sample. BMC pregnancy and childbirth. 2019;19(1). https://doi.org/10.1186/s12884-019-2560-8 .
• Reid JA, Baglivio MT, Piquero AR, Greenwald MA, Epps N. No youth left behind to human trafficking: Exploring profiles of risk. American journal of orthopsychiatry. 2019;89(6):704.
• Diamond-Welch B, Kosloski AE. Adverse childhood experiences and propensity to participate in the commercialized sex market. Child Abuse & Neglect. 2020 Jun 1;104:104468.
• Shonkoff, J. P., Garner, A. S., Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care, & Section on Developmental and Behavioral Pediatrics (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246. https://doi.org/10.1542/peds.2011-2663
• Narayan AJ, Kalstabakken AW, Labella MH, Nerenberg LS, Monn AR, Masten AS. Intergenerational continuity of adverse childhood experiences in homeless families: unpacking exposure to maltreatment versus family dysfunction. Am J Orthopsych. 2017;87(1):3. https://doi.org/10.1037/ort0000133 .
• Schofield TJ, Donnellan MB, Merrick MT, Ports KA, Klevens J, Leeb R. Intergenerational continuity in adverse childhood experiences and rural community environments. Am J Public Health. 2018;108(9):1148-1152. https://doi.org/10.2105/AJPH.2018.304598 .
• Schofield TJ, Lee RD, Merrick MT. Safe, stable, nurturing relationships as a moderator of intergenerational continuity of child maltreatment: a meta-analysis. J Adolesc Health. 2013;53(4 Suppl):S32-38. https://doi.org/10.1016/j.jadohealth.2013.05.004 .

Adverse Childhood Experiences (ACEs)

ACEs can have a tremendous impact on lifelong health and opportunity. CDC works to understand ACEs and prevent them.

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Despite warnings of violence at UCLA, police didn’t step in for over 3 hours

Faculty had raised alarms in the days before the attack on pro-Palestinian protesters. That night, one witness called emergency services 11 times before police intervened.

Late on April 30, Sean Tabibian called 911 to say police were needed urgently at the University of California at Los Angeles. “All hell had broken loose,” Tabibian recalled in an interview. Masked agitators were attacking pro-Palestinian protesters on a campus quad, video footage shows, and a team of hired security guards had retreated.

The call at 11:09 p.m. was the first of 11 that Tabibian made to police that night as the violence escalated, according to his cellphone’s call log. Other witnesses called 911 as well, records show.

“They said they were responding,” said Tabibian, a local business executive and UCLA alumnus who was near campus around the time commotion erupted at the encampment, and who said he was concerned that protesters had been discriminating against Jewish students. “They kept saying they’re responding, they’re responding.”

While a small UCLA patrol could be seen in footage briefly early on, law enforcement agencies did not move in to stop the violence until 3 hours and 34 minutes after Tabibian’s first 911 call, a Washington Post examination has found — a delay that prolonged one of the most violent altercations since pro-Palestinian protesters began setting up encampments on college campuses across the country this spring.

The examination — based on evidence including more than 200 videos, emergency radio transmissions, text messages and interviews with more than a dozen witnesses — illuminates the stakes for university and local officials as they decide if and when to call police to deal with pro-Palestinian encampments. Elsewhere police have been accused of using heavy-handed tactics, but at UCLA, where university policy discourages calling police preemptively, campus police as well as the Los Angeles Police Department and California Highway Patrol are facing scrutiny for their hands-off approach that night.

It’s not clear why police waited so long to respond. But in the hours before they took action, at least 16 people were visibly injured, the majority of them pro-Palestinian, including two protesters who could be seen with blood streaking across their faces and soaking into their clothes, videos and images show. The counterprotesters ignited at least six fireworks; struck protesters at least 20 times with wooden planks, metal poles and other objects; and punched or kicked at least eight protesters.

The protesters occasionally fought back. People on both sides sprayed their opponents with chemical irritants at least 48 times — in some instances in the face, at close range. Unconfirmed reports of a gunshot on campus and a man armed with a knife were relayed to officers over radio, recordings show.

As the violence raged, some police remained stationed at a hastily convened command post near the encampment, while others assembled in formation closer to the violence but held back for an hour, video shows. Authorities did not report making any arrests and a review by The Post of video footage found no indication attackers were detained.

Powell Library

Pro-Palestinian

Counterprotesters attack

Source: Planet Labs

The Washington Post

Law enforcement’s tepid response on April 30 contrasts starkly with their aggressive maneuvers the following night, when officers in riot gear, some firing projectiles, swiftly dismantled the UCLA camp and arrested 210 people for refusing to leave.

The Post’s examination also found that faculty had raised concerns for days about harassment of pro-Palestinian activists and physical violence directed at people in the protest encampment, raising questions about whether the school should have had more police on hand to prevent an altercation.

College protests over Gaza war

The college is typically policed by its own small force, and university officials must ask outside departments for extra help when they determine it’s needed. UCLA follows a systemwide University of California policy “not to request law enforcement involvement preemptively, and only if absolutely necessary to protect the physical safety of our campus community,” a spokeswoman said in a statement last month after protesters established their encampment.

While LAPD would not answer questions about when they were summoned, a senior UCLA official told a colleague that the college had asked LAPD for assistance by around 11:30 p.m. on the night of the attack, according to text messages obtained by The Post. The California Highway Patrol has said UCLA requested its help an hour later, at 12:30 a.m.

UCLA police chief John Thomas told the Los Angeles Times that when he got to campus shortly before midnight, he saw 19 officers from campus police, the LAPD and three other local police departments, but an LAPD lieutenant told him the force was too small to step in.

It was not until about 1:30 a.m. that officers began staging with campus police in a parking lot near the encampment, video shows.

CHP confirmed the time UCLA requested its help, but did not respond to further questions.

In an unsigned email, LAPD told The Post, “The department is looking into its involvement on campus along with other law enforcement agencies and a detailed report is being completed.”

Campus police referred questions to UCLA. A spokesperson for UCLA did not respond to requests for comment.

UCLA and LAPD have said they are now jointly investigating perpetrators of the April 30 attack, and that they have asked the FBI for help. Michael V. Drake, the president of the University of California system, has requested an external investigation of the university’s response that night.

Mounting concerns

On April 25, as protests emerged at universities nationwide over Israel’s war in Gaza , students at UCLA’s Westwood campus began building a tent encampment on Dickson Plaza, an open, tree-lined quad in front of the college’s Royce Hall theater. Their demands to college leaders included calling for a cease-fire, divesting from companies tied to Israel’s war effort and boycotting Israeli universities.

Over the next several days, videos show, counterprotesters faced off with pro-Palestinian demonstrators. According to protesters, they repeatedly tried to enter the encampment.

UCLA asked for assistance in policing the demonstrations from the wider University of California police system on April 25 and April 26 but then canceled those requests, Wade Stern, the president of the University of California’s police union, told The Post. The cancellations, first reported by the Los Angeles Times , were frustrating, Stern said. “Every cop wants to go and help,” he said. “We all want to be there.”

Concerns about students’ safety mounted among some faculty ahead of a pro-Israeli counterprotest planned for April 28 and permitted by university officials. In a phone call on April 27, Administrative Vice Chancellor Michael Beck assured Randall Kuhn, a public health professor, that counterprotesters did not want to “pick a fight” and that UCLA was stationing dozens of hired security guards around the encampment, including 30 ready “to help address any provocations or potential attacks,” according to an email Kuhn sent to colleagues summarizing Beck’s remarks. Beck referred questions to a UCLA spokesman.

On April 28, counterprotesters erected a massive TV screen to blast footage of the Oct. 7 attack on Israel by Hamas at the protesters. UCLA’s police force was bolstered that day by additional officers from other University of California campuses. Still, when an assault occurred, they were outmanned and sought additional help from several local police departments, according to a timeline compiled by police union officials.

By the next night, tensions were rising again. Videos show a small group of agitators taunting people in the pro-Palestinian encampment. Police later separated fights between the two sides, protesters said in interviews.

Hours later, UCLA again asked for help from other UC police departments. But none was able to send reinforcements, as they were monitoring protests on their own campuses, according to the union timeline.

Agitators gathered outside the encampment the following day. Recordings posted on social media showed protesters refusing entry to a Jewish student who identified as a Zionist and a mother complaining to UCLA that Jewish students were being blocked from accessing a library.

At 2:35 p.m., Danielle Carr, an assistant professor at UCLA’s Institute for Society and Genetics, wrote an email seeking to sound an alarm about “truly unbelievable” aggression against protesters during the pro-Israeli counterprotest two days earlier. “I know that many faculty are wondering what the administration plans to do to protect our students,” Carr wrote to an office responsible for handling complaints of sexual violence and harassment.

By the evening, a large crowd had gathered outside the protest camp. One man was draped in an Israeli flag and others wore hoodies with slogans demanding the return of Israeli hostages kidnapped by Hamas. At 10:48 p.m., counterprotesters moved closer to the encampment’s southern barricades and blared “Harbu Darbu” — an Israeli wartime anthem calling for retribution for Oct. 7. Suddenly, they rushed forward and started pulling metal fences away from security guards stationed at the perimeter of the encampment.

The guards were from Contemporary Services Corporation (CSC), which contracts with UCLA and specializes in crowd control at sporting events and concerts, and a subsidiary. While some CSC guards attempted to push back attackers, others stood aside.

“There are too many!” one of the security guards said, recordings show. Another shouted “CSC, pack it up!” as fellow guards walked away. CSC did not respond to questions from The Post.

The agitators pushed past the fencing and started ripping down plywood barriers on the perimeter of the camp’s south and north sides. Pro-Palestinian protesters attempted to hold their line.

Calls for help

When Tabibian, the business executive, placed his first 911 call at 11:09 p.m., he connected with a dispatcher and they spoke for 21 seconds. “I believe I told him that people were getting hurt — they needed to get over here and shut this down,” Tabibian told The Post, noting that it was difficult to differentiate between each of his 11 calls. Tabibian blamed pro-Palestinian protesters for provoking the chaos.

At 11:13 p.m., two UCLA patrol cars and an ambulance arrived near a UCLA campus police car that an observer said had been there all day. A third arrives shortly after. At least four officers stepped out of their cars and were soon surrounded by counterprotesters, some shouting “Shut it down!” in an apparent reference to the encampment. One man was ushered to the ambulance, and at 11:19 p.m., the three police cars and ambulance pulled away.

Reports of injuries rolled in. At 11:31 p.m., a fire department dispatcher asked an ambulance stationed nearby to respond to an injury at the college.

Kuhn, the public health professor, texted Beck, the vice chancellor, about his growing concern. Beck assured him that LAPD had been summoned.

April 30 11:26 p.m.

Michael, what’s going on?

Michael Beck

Yes. I have been watching. Been

talking with the Chief

They’ve been subjected to five

days of torture

And now this?

Where are you?

I am at home.

LAPD has been summoned

What did you request?

LAPD assistance

Oh whom? Did you ask for

People are being pepper sprayed

by counter protestors

Rocket attack

A colleague was just pepper

Counter protestors crowd is just

growing. They’re coming from

Violence continues

Moments later, a counterprotester lit a firework and lobbed it over the encampment perimeter. It exploded inside the encampment to terrified screams.

The lack of police intervention frustrated witnesses. Jeremy López, who supported the protest, called 911 at 12:28 a.m. to report that students were being beaten. “The operator said ‘Yes, we know already,’ and hung up,” López later told The Post.

Carr, the assistant professor who had warned of potential violence, arrived at the plaza a few minutes later and encountered what looked to her like a war zone. Students were sprawled on the ground, some bleeding from their faces. Others were reeling from eye pain caused by irritants.

The violence continued “for hours and hours, with nobody stepping in,” said Bharat Venkat, an associate professor. “I thought a student would be killed.”

A mob surrounded two pro-Palestinian demonstrators who had stepped outside of the encampment. While one was hit with a wooden stick, the crowd rained punches on the other. He was later recorded receiving treatment from volunteer medics, his face covered in blood.

At 12:32 a.m., a man on LAPD radio said they “ might want to launch a UCLA unit,” according to a review of radio communications archived by the platform Broadcastify . Seconds later, an officer said he was at UCLA’s Murphy Hall — close to the violence — along with four other units. But no LAPD personnel were seen taking action in available video footage of the area.

After 1 a.m., police reported over radio that an “MFF” — mobile field force — and a helicopter had been requested at the college, and officers were told that the incident was “code three,” meaning they should use lights and sirens.

But over the subsequent hour, the address of the temporary command post was misstated over radio, confusing some officers.

People calling police continued to receive dismissive responses. “Didn’t you already call?” an operator said when a woman called UCLA police at 1:33 a.m., video shows. “I already told you, we’re handling the situation. You can’t continue calling unless you have an emergency.”

Police emerge

Throughout the evening, police vehicles had gathered on the outskirts of campus, but the first mass of police visible in footage reviewed by The Post was a line of about 30 CHP officers that began to form at 1:43 a.m. Another row of officers in black lined up behind them. They did not advance.

At 2:17 a.m., counterprotesters rushed the encampment barricade, physically assaulting protesters, including slamming a plank of wood on someone’s head and spraying an irritant. Officers stood about 200 feet away. None moved to stop the violence, the video shows.

Nearly an hour after they assembled in line, and nearly four hours after the attack began, officers from CHP and LAPD began slowly moving in formation toward Dickson Plaza at 2:43 a.m.

By 3:10 a.m., police had separated the majority of attackers from the pro-Palestinian protesters. But law enforcement did not arrest or appear to question the attackers, instead granting them an exit route away from the camp, according to video.

“There have only been a couple times in my life where I’ve had trouble understanding what’s real and what’s maybe a nightmare, and this was definitely one of them,” Nicholas Shapiro, an assistant professor and a former EMT who helped treat injured students, later told The Post.

Shapiro arrived home with dark stains on his fingers and palms.

“Surreal,” he texted a group of professor friends at 3:47 a.m., “to be ending the night cleaning a student’s blood off my hands.”

Samuel Oakford and Jarrett Ley in New York contributed to this report.