video games violence research

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• 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

553k Accesses

106 Citations

2335 Altmetric

Metrics details

• 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.

Similar content being viewed by others

The associations between autistic characteristics and microtransaction spending

No effect of short term exposure to gambling like reward systems on post game risk taking

Increasing prosocial behavior and decreasing selfishness in the lab and everyday life

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.

Anderson CA, Bushman BJ. Effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, and prosocial behavior: a meta-analytic review of the scientific literature. Psychol Sci. 2001;12:353–9.

Article   CAS   Google Scholar  

Anderson CA, Shibuya A, Ihori N, Swing EL, Bushman BJ, Sakamoto A, et al. Violent video game effects on aggression, empathy, and prosocial behavior in eastern and western countries: a meta-analytic review. Psychol Bull. 2010;136:151–73.

Article   Google Scholar  

Ferguson CJ. Do angry birds make for angry children? A meta-analysis of video game influences on children’s and adolescents’ aggression, mental health, prosocial behavior, and academic performance. Perspect Psychol Sci. 2015;10:646–66.

Ferguson CJ, Kilburn J. Much ado about nothing: the misestimation and overinterpretation of violent video game effects in eastern and western nations: comment on Anderson et al. (2010). Psychol Bull. 2010;136:174–8.

Greitemeyer T, Mugge DO. Video games do affect social outcomes: a meta-analytic review of the effects of violent and prosocial video game play. Pers Soc Psychol Bull. 2014;40:578–89.

Anderson CA, Carnagey NL, Eubanks J. Exposure to violent media: The effects of songs with violent lyrics on aggressive thoughts and feelings. J Pers Soc Psychol. 2003;84:960–71.

DeWall CN, Anderson CA, Bushman BJ. The general aggression model: theoretical extensions to violence. Psychol Violence. 2011;1:245–58.

Sestire MA, Bartholow BD. Violent and non-violent video games produce opposing effects on aggressive and prosocial outcomes. J Exp Soc Psychol. 2010;46:934–42.

Kneer J, Elson M, Knapp F. Fight fire with rainbows: The effects of displayed violence, difficulty, and performance in digital games on affect, aggression, and physiological arousal. Comput Hum Behav. 2016;54:142–8.

Kneer J, Glock S, Beskes S, Bente G. Are digital games perceived as fun or danger? Supporting and suppressing different game-related concepts. Cyber Beh Soc N. 2012;15:604–9.

Sauer JD, Drummond A, Nova N. Violent video games: the effects of narrative context and reward structure on in-game and postgame aggression. J Exp Psychol Appl. 2015;21:205–14.

Ballard M, Visser K, Jocoy K. Social context and video game play: impact on cardiovascular and affective responses. Mass Commun Soc. 2012;15:875–98.

Read GL, Ballard M, Emery LJ, Bazzini DG. Examining desensitization using facial electromyography: violent video games, gender, and affective responding. Comput Hum Behav. 2016;62:201–11.

Szycik GR, Mohammadi B, Hake M, Kneer J, Samii A, Munte TF, et al. Excessive users of violent video games do not show emotional desensitization: an fMRI study. Brain Imaging Behav. 2017;11:736–43.

Szycik GR, Mohammadi B, Munte TF, Te Wildt BT. Lack of evidence that neural empathic responses are blunted in excessive users of violent video games: an fMRI study. Front Psychol. 2017;8:174.

Tear MJ, Nielsen M. Failure to demonstrate that playing violent video games diminishes prosocial behavior. PLoS ONE. 2013;8:e68382.

Tear MJ, Nielsen M. Video games and prosocial behavior: a study of the effects of non-violent, violent and ultra-violent gameplay. Comput Hum Behav. 2014;41:8–13.

Kühn S, Gleich T, Lorenz RC, Lindenberger U, Gallinat J. Playing super Mario induces structural brain plasticity: gray matter changes resulting from training with a commercial video game. Mol Psychiatry. 2014;19:265–71.

Buss AH, Perry M. The aggression questionnaire. J Pers Soc Psychol. 1992;63:452.

Anderson CA, Deuser WE, DeNeve KM. Hot temperatures, hostile affect, hostile cognition, and arousal: Tests of a general model of affective aggression. Pers Soc Psychol Bull. 1995;21:434–48.

Payne DL, Lonsway KA, Fitzgerald LF. Rape myth acceptance: exploration of its structure and its measurement using the illinois rape myth acceptance scale. J Res Pers. 1999;33:27–68.

McMahon S, Farmer GL. An updated measure for assessing subtle rape myths. Social Work Res. 2011; 35:71–81.

Detert JR, Trevino LK, Sweitzer VL. Moral disengagement in ethical decision making: a study of antecedents and outcomes. J Appl Psychol. 2008;93:374–91.

Bandura A, Barbaranelli C, Caprara G, Pastorelli C. Mechanisms of moral disengagement in the exercise of moral agency. J Pers Soc Psychol. 1996;71:364–74.

Rosenzweig S. The picture-association method and its application in a study of reactions to frustration. J Pers. 1945;14:23.

Hörmann H, Moog W, Der Rosenzweig P-F. Test für Erwachsene deutsche Bearbeitung. Göttingen: Hogrefe; 1957.

Anderson CA, Dill KE. Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. J Pers Soc Psychol. 2000;78:772–90.

Przybylski AK, Deci EL, Rigby CS, Ryan RM. Competence-impeding electronic games and players’ aggressive feelings, thoughts, and behaviors. J Pers Soc Psychol. 2014;106:441.

Bitsakou P, Antrop I, Wiersema JR, Sonuga-Barke EJ. Probing the limits of delay intolerance: preliminary young adult data from the Delay Frustration Task (DeFT). J Neurosci Methods. 2006;151:38–44.

Hoyle RH, Stephenson MT, Palmgreen P, Lorch EP, Donohew RL. Reliability and validity of a brief measure of sensation seeking. Pers Individ Dif. 2002;32:401–14.

Farmer R, Sundberg ND. Boredom proneness: the development and correlates of a new scale. J Pers Assess. 1986;50:4–17.

Lejuez CW, Read JP, Kahler CW, Richards JB, Ramsey SE, Stuart GL, et al. Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task (BART). J Exp Psychol Appl. 2002;8:75–84.

Richards JB, Zhang L, Mitchell SH, de Wit H. Delay or probability discounting in a model of impulsive behavior: effect of alcohol. J Exp Anal Behav. 1999;71:121–43.

Davis MH. A multidimensional approach to individual differences in empathy. JSAS Cat Sel Doc Psychol. 1980;10:85.

Google Scholar  

Mehrabian A. Manual for the Balanced Emotional Empathy Scale (BEES). (Available from Albert Mehrabian, 1130 Alta Mesa Road, Monterey, CA, USA 93940); 1996.

Baron-Cohen S, Wheelwright S, Hill J, Raste Y, Plumb I. The “Reading the Mind in the Eyes” Test revised version: A study with normal adults, and adults with Asperger syndrome or high-functioning autism. J Child Psychol Psychiatry. 2001;42:241–51.

Buhrmester D, Furman W, Reis H, Wittenberg MT. Five domains of interpersonal competence in peer relations. J Pers Soc Psychol. 1988;55:991–1008.

Richardson DR, Green LR, Lago T. The relationship between perspective-taking and non-aggressive responding in the face of an attack. J Pers. 1998;66:235–56.

Maras D, Flament MF, Murray M, Buchholz A, Henderson KA, Obeid N, et al. Screen time is associated with depression and anxiety in Canadian youth. Prev Med. 2015;73:133–8.

Hautzinger M, Bailer M, Worall H, Keller F. Beck-Depressions-Inventar (BDI). Beck-Depressions-Inventar (BDI): Testhandbuch der deutschen Ausgabe. Bern: Huber; 1995.

Spielberger CD, Spielberger CD, Sydeman SJ, Sydeman SJ, Owen AE, Owen AE, et al. Measuring anxiety and anger with the State-Trait Anxiety Inventory (STAI) and the State-Trait Anger Expression Inventory (STAXI). Mahwah, NJ: Lawrence Erlbaum Associates Publishers; 1999.

Lorenz RC, Gleich T, Buchert R, Schlagenhauf F, Kuhn S, Gallinat J. Interactions between glutamate, dopamine, and the neuronal signature of response inhibition in the human striatum. Hum Brain Mapp. 2015;36:4031–40.

Bush G, Shin LM. The multi-source interference task: an fMRI task that reliably activates the cingulo-frontal-parietal cognitive/attention network. Nat Protoc. 2006;1:308–13.

King JA, Colla M, Brass M, Heuser I, von Cramon D. Inefficient cognitive control in adult ADHD: evidence from trial-by-trial Stroop test and cued task switching performance. Behav Brain Funct. 2007;3:42.

Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc. 1995;57:289–300.

Wagenmakers E-J. A practical solution to the pervasive problems of p values. Psychon Bull Rev. 2007;14:779–804.

Hay DF. The gradual emergence of sex differences in aggression: alternative hypotheses. Psychol Med. 2007;37:1527–37.

Jeffreys H. The Theory of Probability. Oxford: Clarendon Press; 1961.

Raftery AE, Newton MA, Satagopan YM, Krivitsky PN. Estimating the integrated likelihood via posterior simulation using the harmonic mean identity. In: Bernardo JM, Bayarri MJ, Berger JO, Dawid AP, Heckerman D, Smith AFM, et al., editors. Bayesian statistics. Oxford: University Press; 2007.

Faul F, Erdfelder E, Lang A-G, Buchner A. G*Power3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39:175–91.

Barlett C, Branch O, Rodeheffer C, Harris R. How long do the short-term violent video game effects last? Aggress Behav. 2009;35:225–36.

Williams D, Skoric M. Internet fantasy violence: a test of aggression in an online game. Commun Monogr. 2005;72:217–33.

Teng SK, Chong GY, Siew AS, Skoric MM. Grand theft auto IV comes to Singapore: effects of repeated exposure to violent video games on aggression. Cyber Behav Soc Netw. 2011;14:597–602.

van Rooij AJ, Kuss DJ, Griffiths MD, Shorter GW, Schoenmakers TM, Van, de Mheen D. The (co-)occurrence of problematic video gaming, substance use, and psychosocial problems in adolescents. J Behav Addict. 2014;3:157–65.

Brunborg GS, Mentzoni RA, Froyland LR. Is video gaming, or video game addiction, associated with depression, academic achievement, heavy episodic drinking, or conduct problems? J Behav Addict. 2014;3:27–32.

Green CS, Sugarman MA, Medford K, Klobusicky E, Bavelier D. The effect of action video game experience on task switching. Comput Hum Behav. 2012;28:984–94.

Strobach T, Frensch PA, Schubert T. Video game practice optimizes executive control skills in dual-task and task switching situations. Acta Psychol. 2012;140:13–24.

Colzato LS, van Leeuwen PJ, van den Wildenberg WP, Hommel B. DOOM’d to switch: superior cognitive flexibility in players of first person shooter games. Front Psychol. 2010;1:8.

PubMed   PubMed Central   Google Scholar  

Hutchinson CV, Barrett DJK, Nitka A, Raynes K. Action video game training reduces the Simon effect. Psychon B Rev. 2016;23:587–92.

Powers KL, Brooks PJ, Aldrich NJ, Palladino MA, Alfieri L. Effects of video-game play on information processing: a meta-analytic investigation. Psychon Bull Rev. 2013;20:1055–79.

Colzato LS, van den Wildenberg WP, Zmigrod S, Hommel B. Action video gaming and cognitive control: playing first person shooter games is associated with improvement in working memory but not action inhibition. Psychol Res. 2013;77:234–9.

Steenbergen L, Sellaro R, Stock AK, Beste C, Colzato LS. Action video gaming and cognitive control: playing first person shooter games is associated with improved action cascading but not inhibition. PLoS ONE. 2015;10:e0144364.

Download references

Acknowledgements

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).

Author information

Authors and affiliations.

Max Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195, Berlin, Germany

Simone Kühn, Katharina Schmalen, Markus Weichenberger & Charlotte Witt

Clinic and Policlinic for Psychiatry and Psychotherapy, University Clinic Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany

Simone Kühn, Dimitrij Tycho Kugler & Jürgen Gallinat

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Simone Kühn .

Ethics declarations

Conflict of interest.

The authors declare that they have no conflict of interest.

Electronic supplementary material

Supplementary material, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

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

Download citation

Received : 19 August 2017

Revised : 03 January 2018

Accepted : 15 January 2018

Published : 13 March 2018

Issue Date : August 2019

DOI : https://doi.org/10.1038/s41380-018-0031-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

The effect of competitive context in nonviolent video games on aggression: the mediating role of frustration and the moderating role of gender.

• Jinqian Liao
• Yanling Liu

Current Psychology (2024)

Geeks versus climate change: understanding American video gamers’ engagement with global warming

• Jennifer P. Carman
• Marina Psaros
• Anthony Leiserowitz

Climatic Change (2024)

Exposure to hate speech deteriorates neurocognitive mechanisms of the ability to understand others’ pain

• Agnieszka Pluta
• Joanna Mazurek
• Michał Bilewicz

Scientific Reports (2023)

The effects of violent video games on reactive-proactive aggression and cyberbullying

• Yunus Emre Dönmez

Current Psychology (2023)

Machen Computerspiele aggressiv?

• Jan Dieris-Hirche

Die Psychotherapie (2023)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

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.

APS regularly opens certain online articles for discussion on our website. Effective February 2021, you must be a logged-in APS member to post comments. By posting a comment, you agree to our Community Guidelines and the display of your profile information, including your name and affiliation. Any opinions, findings, conclusions, or recommendations present in article comments are those of the writers and do not necessarily reflect the views of APS or the article’s author. For more information, please see our Community Guidelines .

Please login with your APS account to comment.

Vaccinating Against Bunk: Curbing Viral Misinformation

Online games and nudges aim to curb viral misinformation around vaccines and more.

Technology in Context: The Surprising Social Upsides of Constant Connectivity

The very same technologies that make social distancing bearable in the age of COVID-19 have also been cited among leading causes of social isolation and mental health issues. Psychological research suggests a more nuanced reality.

Games Can Be Good – When You Play for the Right Reasons

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

Privacy Overview

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.

Anderson, C. A. (2004). An update on the effects of playing violent video games. J. Adolesc. 27, 113–122. doi: 10.1016/j.adolescence.2003.10.009

PubMed Abstract | CrossRef Full Text | Google Scholar

Anderson, C. A., and Bushman, B. J. (2001). Effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, and prosocial behavior: a meta-analytic review of the scientific literature. Psychol. Sci. 12, 353–359. doi: 10.1111/1467-9280.00366

CrossRef Full Text | Google Scholar

Anderson, C. A., and Carnagey, N. L. (2014). “The role of theory in the study of media violence: the general aggression model” in Media violence and children. ed. Gentile, D. A. (Westport, CT: Praeger), 103–133.

Google Scholar

Anderson, C. A., Carnagey, N. L., Flanagan, M., Benjamin, A. J., Eubanks, J., and Valentine, J. C. (2004). Violent video games: specific effects of violent content on aggressive thoughts and behavior. Adv. Exp. Soc. Psychol. 36, 199–249. doi: 10.1016/S0065-2601(04)36004-1

Anderson, C. A., and Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. J. Pers. Soc. Psychol. 78, 772–790. doi: 10.1037/0022-3514.78.4.772

Anderson, C. A., Sakamoto, A., Gentile, D. A., Ihori, N., Shibuya, A., Yukawa, S., et al. (2008). Longitudinal effects of violent video games on aggression in Japan and the United States. Pediatrics 122, e1067–e1072. doi: 10.1542/peds.2008-1425

Anderson, C. A., Shibuya, A., Ihori, N., Swing, E. L., Bushman, B. J., Sakamoto, A., et al. (2010). Violent video game effects on aggression, empathy, and prosocial behavior in eastern and western countries: a meta-analytic review. Psychol. Bull. 136, 151–173. doi: 10.1037/a0018251

Anderson, C. A., Suzuki, K., Swing, E. L., Groves, C. L., Gentile, D. A., Prot, S., et al. (2017). Media violence and other aggression risk factors in seven nations. Pers. Soc. Psychol. Bull. 43, 986–998. doi: 10.1177/0146167217703064

Bailey, C. A., and Ostrov, J. M. (2008). Differentiating forms and functions of aggression in emerging adults: associations with hostile attribution biases and normative beliefs. J. Youth Adolesc. 37, 713–722. doi: 10.1007/s10964-007-9211-5

Bailey, K., West, R., and Anderson, C. A. (2011). The association between chronic exposure to video game violence and affective picture processing: an ERP study. Cogn. Affect. Behav. Neurosci. 11, 259–276. doi: 10.3758/s13415-011-0029-y

Bandura, A. (1989). “Social cognitive theory” in Annals of child development: Six theories of child development. ed. Vasta, R. (Greenwich, CT: JAI Press), 1–60.

Batanova, M., and Loukas, A. (2014). Unique and interactive effects of empathy, family, and school factors on early adolescents’ aggression. J. Youth Adolesc. 43, 1890–1902. doi: 10.1007/s10964-013-0051-1

Boxer, P., Groves, C. L., and Docherty, M. (2015). Video games do indeed influence children and adolescents’ aggression, prosocial behavior, and academic performance: a clearer reading of Ferguson (2015). Perspect. Psychol. Sci. 10, 671–673. doi: 10.1177/1745691615592239

Burton, K. A., Dan, F., and Wygant, D. B. (2013). The role of peer attachment and normative beliefs about aggression on traditional bullying and cyberbullying. Psychol. Schools 50, 103–115. doi: 10.1002/pits.21663

Bushman, B. J., and Anderson, C. A. (2002). Violent video games and hostile expectations: a test of the general aggression model. Pers. Soc. Psychol. Bull. 28, 1679–1686. doi: 10.1177/014616702237649

Buss, A. H., and Perry, M. (1992). The aggression questionnaire. J. Pers. Soc. Psychol. 63, 452–459. doi: 10.1037/0022-3514.63.3.452

Casas, J. F., Weigel, S. M., Crick, N. R., Ostrov, J. M., Woods, K. E., Jansen Yeh, E. A., et al. (2006). Early parenting and children’s relational and physical aggression in the preschool and home contexts. J. Appl. Dev. Psychol. 27, 209–227. doi: 10.1016/j.appdev.2006.02.003

Chen, H., Liu, Y., and Cui, W. (2012). The relationship between online violent video games and aggressive behavior: the mediating effect of college students’ attitudes towards violence. Chinese J. Special Educ. 8, 79–84.

DeLisi, M., Vaughn, M. G., Gentile, D. A., Anderson, C. A., and Shook, J. (2013). Violent video games, delinquency, and youth violence: new evidence. Youth Violence Juv. J. 11, 132–142. doi: 10.1177/1541204012460874

Duan, D., Zhang, X., Wei, L., Zhou, Y., and Liu, C. (2014). The impact of violent media on aggression: the role of normative belief and empathy. Psychol. Dev. Educ. 30, 185–192.

Fei, L., Shen, Q., Zheng, Y., Zhao, J., Jiang, S., Wang, L., and Wang, X. (1991). Preliminary evaluation of Chinese version of FACES and FES: comparison of normal families and families of schizophrenic patients. Chin. Ment. Health. J. 5, 198–202, 238.

Ferguson, C. J. (2007). Evidence for publication bias in video game violence effects literature: a meta-analytic review. Aggress. Violent Behav. 12, 470–482. doi: 10.1016/j.avb.2007.01.001

Ferguson, C. J. (2013). Adolescents, crime, and the media: A critical analysis. New York, NY: Springer.

Ferguson, C. J. (2015). Do angry birds make for angry children? A meta-analysis of video game influences on children’s and adolescents’ aggression, mental health, prosocial behavior, and academic performance. Perspect. Psychol. Sci. 10, 646–666. doi: 10.1177/1745691615592234

Ferguson, C. J., Rueda, S., Cruz, A., Ferguson, D., Fritz, S., and Smith, S. (2008). Violent video games and aggression: causal relationship or byproduct of family violence and intrinsic violence motivation? Crim. Justice Behav. 31, 2231–2237. doi: 10.1002/chin.200028107

Ferguson, C. J., San Miguel, C., Garza, A., and Jerabeck, J. M. (2012). A longitudinal test of video game violence influences on dating and aggression: a 3-year longitudinal study of adolescents. J. Psychiatr. Res. 46, 141–146. doi: 10.1016/j.jpsychires.2011.10.014

Ferguson, C. J., San Miguel, C., and Hartley, R. D. (2009). A multivariate analysis of youth violence and aggression: the influence of family, peers, depression, and media violence. J. Pediatr. 155, 904–908. e903. doi: 10.1016/j.jpeds.2009.06.021

Fikkers, K. M., Piotrowski, J. T., and Valkenburg, P. M. (2017). A matter of style? Exploring the effects of parental mediation styles on early adolescents’ media violence exposure and aggression. Comput. Hum. Behav. 70, 407–415. doi: 10.1016/j.chb.2017.01.029

Fikkers, K. M., Piotrowski, J. T., Weeda, W. D., Vossen, H. G. M., and Valkenburg, P. M. (2013). Double dose: high family conflict enhances the effect of media violence exposure on adolescents’ aggression. Societies 3, 280–292. doi: 10.3390/soc3030280

Furuya-Kanamori, L., and Doi, S. A. (2016). Angry birds, angry children, and angry meta-analysts: a reanalysis. Perspect. Psychol. Sci. 11, 408–414. doi: 10.1177/1745691616635599

Gentile, D. A. (2015). What is a good skeptic to do? the case for skepticism in the media violence discussion. Perspect. Psychol. Sci. 10, 674–676. doi: 10.1177/1745691615592238

Gentile, D. A., Li, D., Khoo, A., Prot, S., and Anderson, C. A. (2014). Mediators and moderators of long-term effects of violent video games on aggressive behavior: practice, thinking, and action. JAMA Pediatr. 168, 450–457. doi: 10.1001/jamapediatrics.2014.63

Greitemeyer, T. (2014). Intense acts of violence during video game play make daily life aggression appear innocuous: a new mechanism why violent video games increase aggression. J. Exp. Soc. Psychol. 50, 52–56. doi: 10.1016/j.jesp.2013.09.004

Greitemeyer, T., and Mugge, D. O. (2014). Video games do affect social outcomes: a meta-analytic review of the effects of violent and prosocial video game play. Pers. Soc. Psychol. Bull. 40, 578–589. doi: 10.1177/0146167213520459

Groves, C. L., Anderson, C. A., and DeLisi, M. (2014). A response to Ferguson: more red herring. PsycCRITIQUES 59, 9. doi: 10.1037/a0036266

Huesmann, L. R., Dubow, E. F., Boxer, P., Landau, S. F., Gvirsman, S. D., and Shikaki, K. (2017). Children’s exposure to violent political conflict stimulates aggression at peers by increasing emotional distress, aggressive script rehearsal, and normative beliefs favoring aggression. Dev. Psychopathol. 29, 39–50. doi: 10.1017/S0954579416001115

Huesmann, L. R., and Guerra, N. G. (1997). Children’s normative beliefs about aggression and aggressive behavior. J. Pers. Soc. Psychol. 72, 408–419. doi: 10.1037/0022-3514.72.2.408

Kawabata, Y., Alink, L. R. A., Tseng, W. L., Van Ijzendoorn, M. H., and Crick, N. R. (2011). Maternal and paternal parenting styles associated with relational aggression in children and adolescents: a conceptual analysis and meta-analytic review. Dev. Rev. 31, 240–278. doi: 10.1016/j.dr.2011.08.001

Kepes, S., Bushman, B. J., and Anderson, C. A. (2017). Violent video game effects remain a societal concern: reply to Hilgard, Engelhardt, and Rouder (2017). Psychol. Bull. 143, 775–782. doi: 10.1037/bul0000112

Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., and Lattanner, M. R. (2014). Bullying in the digital age: a critical review and meta-analysis of cyberbullying research among youth. Psychol. Bull. 140, 1073–1137. doi: 10.1037/a0035618

Krahe, B., and Busching, R. (2014). Interplay of normative beliefs and behavior in developmental patterns of physical and relational aggression in adolescence: a four-wave longitudinal study. Front. Psychol. 5:1146. doi: 10.3389/fpsyg.2014.01146

Li, J. B., Nie, Y. G., Boardley, I. D., Dou, K., and Situ, Q. M. (2015). When do normative beliefs about aggression predict aggressive behavior? an application of I3 theory. Aggress. Behav. 41, 544–555. doi: 10.1002/ab.21594

Lim, S. H., and Ang, R. P. (2009). Relationship between boys’ normative beliefs about aggression and their physical, verbal, and indirect aggressive behaviors. Adolescence 44, 635–650.

PubMed Abstract | Google Scholar

Linder, J., and Werner, N. E. (2012). Relationally aggressive media exposure and children’s normative beliefs: does parental mediation matter? Fam. Relat. 61, 488–500. doi: 10.1111/j.1741-3729.2012.00707.x

Liu, Y., Teng, Z., Lan, H., Zhang, X., and Yao, D. (2015). Short-term effects of prosocial video games on aggression: an event-related potential study. Front. Behav. Neurosci. 9:193. doi: 10.3389/fnbeh.2015.00193

Machackova, H., and Pfetsch, J. (2016). Bystanders’ responses to offline bullying and cyberbullying: the role of empathy and normative beliefs about aggression. Scand. J. Psychol. 57, 169–176. doi: 10.1111/sjop.12277

Markey, P. M. (2015). Finding the middle ground in violent video game research lessons from Ferguson (2015). Perspect. Psychol. Sci. 10, 667–670. doi: 10.1177/1745691615592236

Moos, R. H. (1990). Conceptual and empirical approaches to developing family-based assessment procedures: resolving the case of the Family Environment Scale. Fam. Process 29, 199–208; discussion 209-111. doi: 10.1111/j.1545-5300.1990.00199.x

Nathanson, A. I. (1999). Identifying and explaining the relationship between parental mediation and children’s aggression. Commun. Res. 26, 124–143.

Padilla-Walker, L. M., Coyne, S. M., and Collier, K. M. (2016). Longitudinal relations between parental media monitoring and adolescent aggression, prosocial behavior, and externalizing problems. J. Adolesc. 46, 86–97. doi: 10.1016/j.adolescence.2015.11.002

Piotrowski, J. T., and Valkenburg, P. M. (2015). Finding orchids in a field of dandelions: understanding children’s differential susceptibility to media effects. Am. Behav. Sci. 59, 1776–1789. doi: 10.1177/0002764215596552

Rasmussen, E. E. (2014). Proactive vs. retroactive mediation: effects of mediation’s timing on children’s reactions to popular cartoon violence. Hum. Commun. Res. 40, 396–413. doi: 10.1111/hcre.12030

Rosenthal, R., and Rosnow, R. (1991). Essentials of behavioral research: Methods and data analysis. New York, NY: McGraw Hill.

Rothstein, H. R., and Bushman, B. J. (2015). Methodological and reporting errors in meta-analytic reviews make other meta-analysts angry: a commentary on Ferguson (2015). Perspect. Psychol. Sci. 10, 677–679. doi: 10.1177/1745691615592235

Sandstrom, M. J. (2007). A link between mothers’ disciplinary strategies and children’s relational aggression. Brit. J. Dev. Psychol. 25, 399–407. doi: 10.1348/026151006X158753

Shao, R., and Wang, Y. (2017). Reliability and validity of normative beliefs about aggression scale among middle school students. Chin. J. Clin. Psychol. 25, 1035–1038.

Sherry, J. L. (2001). The effects of violent video games on aggression. Hum. Commun. Res. 27, 409–431. doi: 10.1093/hcr/27.3.409

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.

Violent Video Games and Aggression

A discussion based on the main theoretical frameworks

• Living reference work entry
• First Online: 23 November 2022
• Cite this living reference work entry

• H. Andaç Demirtaş-Madran 4  

195 Accesses

Whether or not exposure to violent media is a risk factor for aggressive behavior has been the subject of numerous studies over many years. Research, which was mostly focused on the effects of television during the first decades, started to shift its focus in the 1980s to video games. The interactive and rewarding nature of video gaming and the active role it imposes on players not only facilitates the comprehension of educational content, but also accelerates the modeling and reinforcement of negative orientations. Studies have generally shown that violent video games can trigger harmful effects in physical, cognitive, emotional, and behavioral terms. This chapter presents an overview of current findings from experiments, longitudinal and cross-sectional studies, meta-analyses, and conclusions based on the main theoretical frameworks. Initially, a comparison of the effects of violent video games and violent television is presented. Then, research findings concerning the effects of violent video game and theoretical explanations of the underlying processes are reviewed in detail. This is followed by a summary of research findings concerning the effect of violent video games on aggressive tendencies in accordance with the main theoretical frameworks and ongoing academic conflicts based on disagreements in method, tool, sampling, and statistical dimensions. Finally, a comprehensive discussion is presented along with various recommendations.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Abbreviations

Violent video games

Adachi T, Willoughby T (2011) The effect of violent video games on aggression. Is it more than just the violence? Aggress Violent Behav 16:55–62

Article   Google Scholar  

Addo PC, Fang J, Kulbo NB et al (2021) Violent video games and aggression among young adults: the moderating effects of adverse environmental factors. Cyberpsychol Behav Soc Netw 24(1):17–23. https://doi.org/10.1089/cyber.2020.0018

Article   PubMed   Google Scholar  

Anderson CA, Berkowitz L, Donnerstein E (2003) The influence of media violence on youth. Psychol Sci Public Interest 4(3):81–110. https://doi.org/10.1111/j.1529-1006.2003.pspi_1433.x

Anderson CA (2002) Violent video games and aggressive thoughts, feelings, and behaviors. In: Calvert SL, Jordan AB, Cocking RR (eds) Children in the digital age. Praeger, Westport, pp 101–119

Google Scholar  

Anderson CA, Bushman BJ (2001) Effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, and prosocial behavior: a meta-analytic review of the scientific literature. Psychol Sci 12:353–359

Anderson CA, Bushman BJ (2002) The effects of media violence on society. Science 295(5564):2377–2379. https://doi.org/10.1126/science.1070765

Anderson CA, Carnagey NL (2004) Violent evil and the general aggression model. In: Miller A (ed) The social psychology of good and evil. Guilford, New York, pp 168–192

Anderson CA, Carnagey NL (2009) Causal effects of violent sports video games on aggression: is it competitiveness or violent content? J Exp Soc Psychol 45:731–739

Anderson CA, Dill KE (2000) Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. J Pers Soc Psychol 78:772–790

Anderson CA, Carnagey NL, Flanagan M et al (2004) Violent video games: specific effects of violent content on aggressive thoughts and behavior. In: Zanna MP (ed) Advances in experimental social psychology, vol 36. Elsevier Academic Press, pp 199–249. https://doi.org/10.1016/S0065-2601(04)36004-1

Chapter   Google Scholar  

Anderson CA, Gentile DA, Buckley KE (2007) Violent video game effects on children and adolescents: theory, research, and public policy. Oxford University Press, New York

Book   Google Scholar  

Anderson CA, Shibuya A, Ihori N et al (2010) Violent video game effects on aggression, empathy, and prosocial behavior in eastern and western countries: a meta-analytic review. Psychol Bull 136(2):151–173. https://doi.org/10.1037/a0018251

Anderson CA, Suzuki K, Swing EL et al (2017) Media violence and other aggression risk factors in seven nations. Personal Soc Psychol Bull 43(7):986–998. https://doi.org/10.1177/0146167217703064

Ballard ME, Lineberger R (1999) Video game violence and confederate gender: effects on reward and punishment given by college males. Sex Roles 41:541–558

Ballard ME, Wiest JR (1996) Mortal Kombat (TM): the effects of violent video game play on males’ hostility and cardiovascular responding. J Appl Soc Psychol 26:717–730

Bandura A (1986) Social foundations of thought and action: a social cognitive theory. Prentice Hall

Bandura A (2001) Social cognitive theory: an agentic perspective. Annu Rev Psychol 52:1–26. https://doi.org/10.1146/annurev.psych.52.1.1

Barlett CP, Harris RJ, Baldassaro R (2007) Longer you play, the more hostile you feel: examination of first person shooter video games and aggression during video game play. Aggress Behav 33(6):486–497. https://doi.org/10.1002/ab.20227

Barlett CP, Branch O, Rodeheffer C et al (2009) How long do the short-term violent video game effects last? Aggress Behav 35(3):225–236. https://doi.org/10.1002/ab.20301

Bartholow BD, Bushman BJ, Sestir MA (2006) Chronic violent video game exposure and desensitization to violence: behavioral and event-related brain potential data. J Exp Soc Psychol 42(4):532–539. https://doi.org/10.1016/j.jesp.2005.08.006

Bender PK, Plante C, Gentile DA (2018) The effects of violent media content on aggression. Curr Opin Psychol 19:104–108. https://doi.org/10.1016/j.copsyc.2017.04.003

Bensley L, Van Eenwyk J (2001) Video games and real-life aggression: review of the literature. J Adolesc Health 29(4):244–257. https://doi.org/10.1016/s1054-139x(01)00239-7

Bleakley A, Vaala S, Jordan AB et al (2017) The Annenberg media environment survey: media access and use in US homes with children and adolescents. In: Jordan AB, Romer D (eds) Media and the well-being of children and adolescents. Oxford University Press, New York, pp 1–19

Bond RM, Bushman BJ (2017) The contagious spread of violence among US adolescents through social networks. Am J Public Health 107(2):288–294. https://doi.org/10.2105/AJPH.2016.303550

Article   PubMed   PubMed Central   Google Scholar  

Bryant J, Zillmann D, Oliver MB (eds) (2002) Media effects, advances in theory and research, 2nd edn. Routledge, New York. https://doi.org/10.4324/9781410602428

Bushman BJ (1998) Effects of television violence on memory for commercial messages. J Exp Psychol Appl 4(4):291–307. https://doi.org/10.1037/1076-898X.4.4.291

Bushman BJ, Huesmann LR (2001) Effects of televised violence on aggression. In: Singer DG, Singer JL (eds) Handbook of children and the media. Sage, Thousand Oaks, pp 223–254

Bushman BJ, Newman K, Calvert SL et al (2016) Youth violence: what we know and what we need to know. Am Psychol 71:17–39. https://doi.org/10.1037/a0039687

Carnagey NL, Anderson CA (2004) Violent video game exposure and aggression: a literature review. Minerva Psichiatr 45(1):1–18

Carnagey NL, Anderson CA (2005) The effects of reward and punishment in violent video games on aggressive affect, cognition, and behavior. Psychol Sci 16(11):882–889. https://doi.org/10.1111/j.1467-9280.2005.01632.x

Crick NR (1995) Relational aggression: the role of intent attributions, feelings of distress, and provocation type. Dev Psychopathol 7(2):313–322. https://doi.org/10.1017/S0954579400006520

Delhove M, Greitemeyer T (2021) Violent media use and aggression: two longitudinal network studies. J Soc Psychol 161(6):697–713. https://doi.org/10.1080/00224545.2021.1896465

Donnerstein E, Slaby RG, Eron LD (1994) The mass media and youth aggression. In: Eron LD, Gentry JH, Schlegel P (eds) Reason to hope: a psychosocial perspective on violence & youth. American Psychological Association, Washington, DC, pp 219–250. https://doi.org/10.1037/10164-010

Drew B, Waters J (1986) Video games: utilization of a novel strategy to improve perceptual motor skills and cognitive functioning in the non-institutionalized elderly. Cogn Rehab 4(2):26–31

Drummond A, Sauer JD, Garea SS (2018) The infamous relationship between violent video game use and aggression: uncharted moderators and small effects make it a far cry from certain. In: Ferguson CJ (ed) Video game influences on aggression, cognition, and attention. Springer, Cham, pp 23–40

Elson M, Mohseni MR, Breuer J et al (2014) Press CRTT to measure aggressive behavior: the unstandardized use of the competitive reaction time task in aggression research. Psychol Assess 26(2):419–432. https://doi.org/10.1037/a0035569

Evra JV (2004) Television and child development. Lawrence Erlbaum, Hillsdale

Ferguson CJ (2015) Do angry birds make for angry children? A meta-analysis of video game influences on children’s and adolescents’ aggression, mental health, prosocial behavior, and academic performance. Perspect Psychol Sci 10(5):646–666. https://doi.org/10.1177/1745691615592234

Ferguson CJ, Beresin E (2017) Social science’s curious war with pop culture and how it was lost: the media violence debate and the risks it holds for social science. Prev Med Int J Devot Pract Theory 99:69–76. https://doi.org/10.1016/j.ypmed.2017.02.009

Ferguson CJ, Colwell J (2017) Understanding why scholars hold different views on the influences of video games on public health. J Commun 67:305–327. https://doi.org/10.1111/jcom.12293

Ferguson CJ, Kilburn J (2010) Much ado about nothing: the misestimation and overinterpretation of violent video game effects in Eastern and Western nations: comment on Anderson et al. (2010). Psychol Bull 136(2):174–178. https://doi.org/10.1037/a0018566

Ferguson CJ, Wang JC (2019) Aggressive video games are not a risk factor for future aggression in youth: a longitudinal study. J Youth Adolesc 48(8):1439–1451

Ferguson CJ, Rueda S, Cruz A et al (2008) Violent video games and aggression: causal relationship or byproduct of family violence and intrinsic violence motivation? Crim Justice Behav 35:311–332

Ferguson CJ, Ivory JD, Beaver KM (2013) Genetic, maternal, school, intelligence and media use predictors of adult criminality: a longitudinal test of the catalyst model in adolescence through early adulthood. J Aggress Maltreat Trauma 22:447–460

Ferguson CJ, Copenhaver A, Markey P (2020) Reexamining the findings of the American Psychological Association’s 2015 task force on violent media: a meta-analysis. Perspect Psychol Sci 15(6):1423–1443. https://doi.org/10.1177/1745691620927666

Ferguson CJ, Gryshyna A, Kim JS et al (2022) Video games, frustration, violence, and virtual reality: two studies. Br J Soc Psychol 61(1):83–99. https://doi.org/10.1111/bjso.12471

Feshbach S (1955) The drive-reducing function of fantasy behavior. J Abnorm Soc Psychol 50(1):3–11. https://doi.org/10.1037/h0042214

Gardner H (1991) The unschooled mind: how children think and how schools should teach. Basic Books, New York

Geen RG, Donnerstein E (eds) (1998) Human aggression: theories, research, and implications for social policy. Academic Press, Cambridge, MA

Gentile DA (ed) (2003) Media violence and children: a complete guide for parents and professionals. Praeger/Greenwood, Santa Barbara

Gentile DA, Anderson CA (2003) Violent video games: The newest media violence hazard. In: Gentile DA (ed) Media violence and children: A complete guide for parents and professionals. Praeger Publishers/Greenwood Publishing Group, pp 131–152

Gentile DA, Anderson CA (2006) Video games. In: Salkind NJ (ed) Encyclopedia of human development, vol 3. Sage, Thousand Oaks, pp 1303–1307

Gentile DA, Gentile RJ (2008) Violent video games as exemplary teachers: a conceptual analysis. J Youth Adolesc 37:127–141

Gentile DA, Lynch PJ, Linder JR et al (2004) The effects of violent video game habits on adolescent hostility, aggressive behaviors, and school performance. J Adolesc 27(1):5–22

Gentile DA, Li D, Khoo A et al (2014) Mediators and moderators of long-term effects of violent video games on aggressive behavior: practice, thinking, and action. JAMA Pediatr 168(5):450–457. https://doi.org/10.1001/jamapediatrics.2014.63

Gerbner G, Gross L, Morgan M et al (1994) Growing up with television: the cultivation perspective. In: Bryant J, Zillmann D (eds) Media effects: advances in theory and research. Lawrence Erlbaum Associates, Inc., pp 17–41

Graybill D, Kirsch JR, Esselman ED (eds) (1985) Effects of playing violent versus non-violent video games on the aggressive ideation of children. Child Study J 15:199–205

Greitemeyer T (2014) Intense acts of violence during video game play make daily life aggression appear innocuous: a new mechanism why violent video games increase aggression. J Exp Soc Psychol 50:52–56

Greitemeyer T (2018) The spreading impact of playing violent video games on aggression. Comput Hum Behav 80:216–219

Greitemeyer T (2019) The contagious impact of playing violent video games on aggression: longitudinal evidence. Aggress Behav 45(6):635–642. https://doi.org/10.1002/ab.21857

Greitemeyer T (2022) The dark and bright side of video game consumption: effects of violent and prosocial video games. Curr Opin Psychol 46:101326. https://doi.org/10.1016/j.copsyc.2022.101326

Greitemeyer T, McLatchie N (2011) Denying humanness to others: a newly discovered mechanism by which violent video games increase aggressive behavior. Psychol Sci 22(5):659–665. https://doi.org/10.1177/0956797611403320

Greitemeyer T, Mügge DO (2014) Video games do affect social outcomes: a meta-analytic review of the effects of violent and prosocial video game play. Personal Soc Psychol Bull 40(5):578–589. https://doi.org/10.1177/0146167213520459

Greitemeyer T, Osswald S (2010) Effects of prosocial video games on prosocial behavior. J Pers Soc Psychol 98(2):211–221. https://doi.org/10.1037/a0016997

Griffiths MD, Hunt N (1998) Dependence on computer games by adolescents. Psychol Rep 82(2):475–480. https://doi.org/10.2466/pr0.1998.82.2.475

Gunter B (2016) Does playing video games make players more violent? Springer, London

Harris RJ (2004) A cognitive psychology of mass communication. Lawrence Erlbaum, Mahwah

Hilgard J, Engelhardt CR, Rouder JN (2017) Overstated evidence for short-term effects of violent games on affect and behavior: a reanalysis of Anderson et al. (2010). Psychol Bull 143:757–774. https://doi.org/10.1037/bul0000074

Huesmann LR (1986) Psychological processes promoting the relation between exposure to media violence and aggressive behavior by the viewer. J Soc Issues 42(3):125–139

Huesmann LR (1988) An information processing model for the development of aggression. Aggress Behav 14:13–24

Huesmann LR (2010) Nailing the coffin shut on doubts that violent video games stimulate aggression: comment on Anderson et al. (2010). Psychol Bull 136(2):179–181. https://doi.org/10.1037/a0018567

Huesmann LR (2018) An integrative theoretical understanding of aggression: a brief exposition. Curr Opin Psychol 19:119–124. https://doi.org/10.1016/j.copsyc.2017.04.015

Huesmann LR, Miller LS. Long-term effects of repeated exposure to media violence in childhood. In Huesmann LR. Aggressive behavior: current perspectives. Plenum Press; 1994, p. 153–186 https://doi.org/10.1007/978-1-4757-9116-7_7

Ihori N, Sakamoto A, Kobayashi K et al (2003) Does video game use grow children’s aggressiveness?: results from a panel study. In: Arai K (ed) Social contributions and responsibilities of simulation and gaming. Japan Association of Simulation and Gaming, Tokyo, pp 221–230

Kestenbaum GI, Weinstein L (1985) Personality, psychopathology, and developmental issues in male adolescent video game use. J Am Acad Child Psychiatry 24(3):329–333. https://doi.org/10.1016/S0002-7138(09)61094-3

Király O, Griffiths MD, King DL et al (2018) Policy responses to problematic video game use: a systematic review of current measures and future possibilities. J Behav Addict 7(3):503–517. https://doi.org/10.1556/2006.6.2017.050

Kirsh SJ (1998) Seeing the world through mortal Kombat-colored glasses: violent video games and the development of a short-term hostile attribution bias. Childhood 5:177–184

Kirsh SJ, Olczak PV, Mounts JRW (2005) Violent video games induce an affect processing bias. J Media Psychol 7:239–250

Krahé B (2013) The social psychology of aggression, 2nd edn. Psychology Press, Hove. https://doi.org/10.4324/9781315804521

Kühn S, Kugler DT, Schmalen K et al (2019) Does playing violent video games cause aggression? A longitudinal intervention study. Mol Psychiatry 24(8):1220–1234

Lynch PJ (1994) Type A behavior, hostility, and cardiovascular function at rest and after playing video games in teenagers. Psychosom Med 56:152

Lynch PJ (1999) Hostility, type a behavior, and stress hormones at rest and after playing violent video games in teenagers. Psychosom Med 61:113

Lynch PJ, Gentile DA, Olson AA et al (2001) The effects of violent video game habits on adolescent aggressive attitudes and behaviors. Biennial Conference of the Society for Research in Child Development, Minneapolis. http://www.eric.ed.gov/PDFS/ED461420.pdf

Milani L, Camisasca E, Caravita SCS et al (2015) Violent video games and children’s aggressive behaviors: an Italian study. SAGE Open 5(3). https://doi.org/10.1177/2158244015599428

Mullin CR, Linz D (1995) Desensitization and resensitization to violence against women: effects of exposure to sexually violent films on judgments of domestic violence victims. J Pers Soc Psychol 69(3):449–459. https://doi.org/10.1037/0022-3514.69.3.449

Olson CK, Kutner LA, Warner DE (2008) The role of violent video game content in adolescent development: boys’ perspectives. J Adolesc Res 23(1):55–75. https://doi.org/10.1177/0743558407310713

Paik H, Comstock G (1994) The effects of television violence on antisocial behavior: a meta-Analysis1. Commun Res 21(4):516–546. https://doi.org/10.1177/009365094021004004

Palaus M, Marron EM, Viejo-Sobera R et al (2017) Neural basis of video gaming: a systematic review. Front Hum Neurosci 22(11):248. https://doi.org/10.3389/fnhum.2017.00248

Prot S, Anderson CA, Gentile DA et al (2014) The positive and negative effects of video game play. In: Jordan AB, Romer D (eds) Media and the well-being of children and adolescents. Oxford University Press, New York, pp 109–128

Sestir MA, Bartholow BD (2010) Violent and nonviolent video games produce opposing effects on aggressive and prosocial outcomes. J Exp Soc Psychol 46(6):934–942

Shao R, Wang Y (2019) The relation of violent video games to adolescent aggression: an examination of moderated mediation effect. Front Psychol 10:384. https://doi.org/10.3389/fpsyg.2019.00384

Sherry JL (2001) The effects of violent video games on aggression: a meta analysis. Hum Commun Res 27(3):409–431

Sherry JL (2004) Media effects theory and the nature/nurture debate: a historical overview and directions for future research. Media Psychol 6:83–109. https://doi.org/10.1207/s1532785xmep0601_4

Shibuya A, Sakamoto A, Ihori N et al (2008) The effects of the presence and contexts of video game violence on children: a longitudinal study in Japan. Simul Gaming 39(4):528–539. https://doi.org/10.1177/1046878107306670

Silvern SB, Williamson PA (1987) The effects of video game play on young children’s aggression, fantasy and prosocial behavior. J Appl Dev Psychol 8:453–462

Smith SL, Donnerstein E. Harmful effects of exposure to media violence: learning of aggression, emotional desensitization, and fear. In Geen RG, Donnerstein E, edıtors. Human aggression: Theories, research, and implications for social policy. Academic Press; 1998, p. 167–202. https://doi.org/10.1016/B978-012278805-5/50008-0

Statista (2022). https://www.statista.com/statistics/748044/number-video-gamers-world/ . Accessed April 2022

Tannenbaum PH, Zillmann D (1975) Emotional arousal in the facilitation of aggression through communication. In: Berkowitz L (ed) Advances in experimental social psychology, vol VIII. Academic Press, New York, pp 149–192

Tian Y, Gao M, Wang P et al (2020) The effects of violent video games and shyness on individuals’ aggressive behaviors. Aggress Behav 46(1):16–24. https://doi.org/10.1002/ab.21869

Unsworth G, Devilly GJ, Ward T (2007) The effect of playing violent video games on adolescents: should parents be quaking in their boots? Psychol Crime Law 13(4):383–394

Van Schie EG, Wiegman O (1997) Children and videogames: leisure activities, aggression, social integration, and school performance. J Appl Soc Psychol 27(13):1175–1194

Warburton WA, Anderson CA (2015) Social psychology of aggression. In: Wright J, Berry J (eds) International encyclopedia of social and behavioral sciences, vol 1, 2nd edn. Elsevier, Oxford, pp 373–380

Wiederhold BK (2021) Violent video games: harmful trigger or harmless diversion? Cyberpsychol Behav Soc Netw 24(1):1–2. https://doi.org/10.1089/cyber.2020.29203

Wiegman O, Van Schie EGM (1998) Video game playing and its relations with aggressive and prosocial behavior. Br J Soc Psychol 37:367–368

Winkel M, Novak DM, Hopson H (1987) Personality factors, subject gender, and the effects of aggressive video games on aggression in adolescents. J Res Pers 21(2):211–223

Zhang Q, Cao Y, Tian J (2021) Effects of violent video games on aggressive cognition and aggressive behavior. Cyberpsychol Behav Soc Netw 24(1):5–10. https://doi.org/10.1089/cyber.2019.0676

Zheng X, Chen H, Wang Z et al (2021) Online violent video games and online aggressive behavior among Chinese college students: the role of anger rumination and self-control. Aggress Behav 47(5):514–520. https://doi.org/10.1002/ab.21967

Zillmann D (2002) Exemplification theory of media influence. In: Bryant J, Zillmann D (eds) Media effects: advances in theory and research. Lawrence Erlbaum, Hillsdale, pp 19–41

Download references

Author information

Authors and affiliations.

Faculty of Comm, Başkent University, Ankara, Turkey

H. Andaç Demirtaş-Madran

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to H. Andaç Demirtaş-Madran .

Editor information

Editors and affiliations.

Institute for Clinical and Applied Health Research, University of Hull, Hull, UK

Colin Martin

King's College London, London, UK

Victor R. Preedy

University of Westminster, London, UK

Vinood B. Patel

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this entry

Cite this entry.

Demirtaş-Madran, H.A. (2022). Violent Video Games and Aggression. In: Martin, C., Preedy, V.R., Patel, V.B. (eds) Handbook of Anger, Aggression, and Violence. Springer, Cham. https://doi.org/10.1007/978-3-030-98711-4_21-1

Download citation

DOI : https://doi.org/10.1007/978-3-030-98711-4_21-1

Received : 26 May 2022

Accepted : 12 June 2022

Published : 23 November 2022

Publisher Name : Springer, Cham

Print ISBN : 978-3-030-98711-4

Online ISBN : 978-3-030-98711-4

eBook Packages : Springer Reference Behavioral Science and Psychology Reference Module Humanities and Social Sciences Reference Module Business, Economics and Social Sciences

• Publish with us

Policies and ethics

• Find a journal
• Track your research

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 .”

• Where We Work
• Publications
• Toolkits & Guides
• Data Collection Tools
• Fact Sheets
• All Resources

Do Video Games Influence Violent Behavior?

By:  Roanna Cooper, MA and Marc Zimmerman, PhD, MI-YVPC Director

An op-ed article appeared recently in the The New York Times  discussing the Supreme Court’s decision to strike down California’s law barring the sale or rental of violent video games to people under 18.  The author, Dr. Cheryl Olson,   describes how the proposed law was based on the erroneous assumption that such games influence violent behavior in real life.

Dr. Olson suggests that the deliberately outrageous nature of violent games, though disturbing, makes them easily discernible from real life and suggests that the interactivity could potentially make such games less harmful.

She raises the question of how these two behaviors can be linked if youth violence has declined over the last several years while violent video game playing has increased significantly during the same period.

This analysis ignores the fact that such variation may be explained by factors other than the link between the two. A spurious variable–a third variable that explains the relationship between two other variables—may explain the negative correlation of video game playing and violent behavior. As one example, socioeconomic status may explain both a decline in violent behavior and an increase in video game playing. More affluent youth have the means and time to buy and play video games, which keeps them safely inside while avoiding potentially violent interactions on the street.  Dr. Olsen also cites several studies that have failed to show a connection between violent video game playing and violent behavior among youth.

This conclusion, however, may not be as clear cut as it appears.

Youth violence remains a significant public health issue

The decline of youth violence notwithstanding, it remains a significant public health issue that requires attention.Youth homicide remains the number one cause of death for African-American youth between 14 and 24 years old, and the number two cause for all children in this age group. Furthermore, the proportion of youth admitting to having committed various violent acts within the previous 12 months has remained steady or even increased somewhat in recent years ( http://pediatrics.aappublications.org/content/108/5/1222.full.pdf+html ).  Although the Columbine tragedy and others like it make the headlines, youth are killed everyday by the hands of another.  A more critical analysis of the link between video game playing and violence is necessary for fully understanding a complex problem like youth violent behavior that has many causes and correlates.

Studies support a link between violent video games and aggressive behavior

Researchers have reported experimental evidence linking violent video games to more aggressive behavior, particularly as it relates to children who are at more sensitive stages in their socialization.  These effects have been found to be particularly profound in the case of child-initiated virtual violence.

• In one study, 161 9- to 12-year olds and 354 college students were randomly assigned to play either a violent or nonviolent video game.  The participants subsequently played another computer game in which they set punishment levels to be delivered to another person participating in the study (they were not actually administered).  Information was also gathered on each participant’s recent history of violent behavior; habitual video game, television, and move habits, and several other control variables.  The authors reported three main findings: 1) participants who played one of violent video games would choose to punish their opponents with significantly more high-noise blasts than those who played the nonviolent games; 2) habitual exposure to violent media was associated with higher levels of recent violent behavior; and 3) interactive forms of media violence were more strongly related to violent behavior than exposure to non-interactive media violence.
• The second study was a cross-sectional correlational study of media habits, aggression-related individual difference variables, and aggressive behaviors of an adolescent population.  High school students (N=189) completed surveys about their violent TV, movie, and video game exposure, attitudes towards violence, and perceived norms about violent behavior and personality traits.  After statistically controlling for sex, total screen time and aggressive beliefs and attitudes, the authors found that playing violent video games predicted heightened physically aggressive behavior and violent behavior in the real world in a long-term context.
• In a third study, Anderson et al. conducted a longitudinal study of elementary school students to examine if violent video game exposure resulted in increases in aggressive behavior over time.  Surveys were given to 430 third, fourth, and fifth graders, their peers, and their teachers at two times during a school year.  The survey assessed both media habits and their attitudes about violence.  Results indicated that children who played more violent video games early in a school year changed to see the world in a more aggressive way and also changed to become more verbally and physically aggressive later in the school year.  Changes in attitude were noticed by both peers and teachers.
• Bushman and Huesmann, in a 2006 Pediatrics and Adolescent Medicine article , examined effect size estimates using meta-analysis to look at the short- and long-term effects of violent media on aggression in children and adults.  They reported a positive relationship between exposure to media violence and subsequent aggressive behavior, aggressive ideas, arousal, and anger across the studies they examined.  Consistent with the theory that long-term effects require the learning of beliefs and that young minds can easier encode new scripts via observational learning, they found that the long-term effects were greater for children.
• In a more recent review, Anderson et al. (2010) also analyzed 136 studies representing 130,296 participants from several countries.  These included experimental laboratory work, cross-sectional surveys and longitudinal studies.  Overall, they found consistent associations between playing violent video games and many measures of aggression, including self, teacher and parent reports of aggressive behavior.  Although the correlations were not high (r=0.17-0.20), they are typical for psychological studies in general and comparable with other risk factors for youth violence suggested in the 2001 Surgeon General’s Report on youth violence .

Violent video games may increase precursors to violent behavior, such as bullying

Although playing violent video games may not necessarily determine violent or aggressive behavior, it may increase precursors to violent behavior.  In fact, Dr. Olson points out that violent video games may be related to bullying, which researchers have found to be a risk factor for more serious violent behavior. Therefore, video game playing may have an indirect effect on violent behavior by increasing risk factors for it.  Doug Gentile notes that the only way for violent video games to affect serious criminal violence statistics is if they were the primary predictor of crime, which they may not be.  Rather, they represent one risk factor among many for aggression ( http://www.apa.org/monitor/2010/12/virtual-violence.aspx ).

Should video games be regulated?

L. Rowell Huesmann (2010) points out that violent video game playing may be similar to other public health threats such as exposure to cigarette smoke and led based paint .  Despite not being guaranteed, the probability of lung cancer from smoking or intelligence deficits from lead exposure is increased.  Nevertheless, we have laws controlling cigarette sales to minors and the use of lead-based paint (and other lead-based products such as gasoline) because it is a risk factor for negative health outcomes.  Huesmann argues the same analysis could be applied to video game exposure.  Although exposure to violent video games is not the sole factor contributing to aggression and violence among children and adolescents, it is a contributing risk factor that is modifiable.

Violent behavior is determined by many factors

Finally, most researchers would agree that violent behavior is determined by many factors which may combine in different ways for different youth. These factors involve neighborhoods, families, peers, and individual traits and behaviors. Researchers, for example, have found that living in a violent neighborhood and experiencing violence as a victim or witness is associated with an increased risk for violent behavior among youth. Yet, this factor alone may not cause one to be violent and most people living in such a neighborhood do not become violent perpetrators. Similarly, researchers have found consistently that exposure to family violence (e.g., spousal and child abuse, fighting and conflict) increases the risk for youth violent behavior, but does not necessarily result in violent children. Likewise, researchers have found that first person killing video game playing is associated with increased risk for violent behavior, but not all the time. Yet, constant exposure to violence from multiple sources, including first person violent video games, in the absence of positive factors that help to buffer these negative exposures is likely to increase the probability that youth will engage in violent behavior.

Despite disagreements on the exact nature of the relationship between violent video game playing and violent or aggressive behavior, significant evidence exists linking video game playing with violent behavior and its correlates.  Although we are somewhat agnostic about the role of social controls like laws banning the sale of violent video games to minors, an argument against such social controls based on the conclusion  that the video games have no effect seems to oversimplify the issue. A more in-depth and critical analysis of the issue from multiple perspectives may both help more completely understand the causes and correlates of youth violence, and provide us with some direction for creative solutions to this persistent social problem.

Share this:

You must be logged in to post a comment.

• Mental Health
• Expert Content
• Ambassadors
• Industry Consulting & Workshops
• Talks and Panels
• Recent Press

State of the Research: Violent Video Games

In this all new State of the Research, we tackle the big kahuna: Violent video games. Specifically, we tackle the three broad issues associated with claims of violent video game effects on players: 

• Does playing violent video games make someone more aggressive?
• Does playing violent video games make someone more violent?
• Does playing violent video games desensitize players to violence?

Violence in the media: Psychologists study potential harmful effects

Early research on the effects of viewing violence on television—especially among children—found a desensitizing effect and the potential for aggression. Is the same true for those who play violent video games?

• Video Games

Television and video violence

Virtually since the dawn of television, parents, teachers, legislators, and mental health professionals have wanted to understand the impact of television programs, particularly on children. Of special concern has been the portrayal of violence, particularly given psychologist Albert Bandura’s work in the 1970s on social learning and the tendency of children to imitate what they see.

As a result of 15 years of “consistently disturbing” findings about the violent content of children’s programs, the Surgeon General’s Scientific Advisory Committee on Television and Social Behavior was formed in 1969 to assess the impact of violence on the attitudes, values, and behavior of viewers. The resulting report and a follow-up report in 1982 by the National Institute of Mental Health identified these major effects of seeing violence on television:

• Children may become less sensitive to the pain and suffering of others.
• Children may be more fearful of the world around them.
• Children may be more likely to behave in aggressive or harmful ways toward others.

Research by psychologists L. Rowell Huesmann, Leonard Eron, and others starting in the 1980s found that children who watched many hours of violence on television when they were in elementary school tended to show higher levels of aggressive behavior when they became teenagers. By observing these participants into adulthood, Huesmann and Eron found that the ones who’d watched a lot of TV violence when they were 8 years old were more likely to be arrested and prosecuted for criminal acts as adults.

Interestingly, being aggressive as a child did not predict watching more violent TV as a teenager, suggesting that TV watching could be a cause rather than a consequence of aggressive behavior. However, later research by psychologists Douglas Gentile and Brad Bushman, among others, suggested that exposure to media violence is just one of several factors that can contribute to aggressive behavior.

Other research has found that exposure to media violence can desensitize people to violence in the real world and that, for some people, watching violence in the media becomes enjoyable and does not result in the anxious arousal that would be expected from seeing such imagery.

Video game violence

The advent of video games raised new questions about the potential impact of media violence, since the video game player is an active participant rather than merely a viewer. 97% of adolescents age 12–17 play video games—on a computer, on consoles such as the Wii, Playstation, and Xbox, or on portable devices such as Gameboys, smartphones, and tablets. A Pew Research Center survey in 2008 found that half of all teens reported playing a video game “yesterday,” and those who played every day typically did so for an hour or more.

Many of the most popular video games, such as “Call of Duty” and “Grand Theft Auto,” are violent; however, as video game technology is relatively new, there are fewer empirical studies of video game violence than other forms of media violence. Still, several meta-analytic reviews have reported negative effects of exposure to violence in video games.

A 2010 review by psychologist Craig A. Anderson and others concluded that “the evidence strongly suggests that exposure to violent video games is a causal risk factor for increased aggressive behavior, aggressive cognition, and aggressive affect and for decreased empathy and prosocial behavior.” Anderson’s earlier research showed that playing violent video games can increase a person’s aggressive thoughts, feelings, and behavior both in laboratory settings and in daily life. “One major conclusion from this and other research on violent entertainment media is that content matters,” says Anderson.

Other researchers, including psychologist Christopher J. Ferguson, have challenged the position that video game violence harms children . While his own 2009 meta-analytic review reported results similar to Anderson’s, Ferguson contends that laboratory results have not translated into real world, meaningful effects. He also claims that much of the research into video game violence has failed to control for other variables such as mental health and family life, which may have impacted the results. His work has found that children who are already at risk may be more likely to choose to play violent video games. According to Ferguson, these other risk factors, as opposed to the games, cause aggressive and violent behavior.

APA launched an analysis in 2013 of peer-reviewed research on the impact of media violence and is reviewing its policy statements in the area.

Anderson, C.A., Ihori, Nobuko, Bushman, B.J., Rothstein, H.R., Shibuya, A., Swing, E.L., Sakamoto, A., & Saleem, M. (2010). Violent video game effects on aggression, empathy, and prosocial behavior in Eastern and Western countries: A Meta-analytic review.  Psychological Bulletin , Vol. 126, No. 2.

Anderson, C. A., Carnagey, N. L. & Eubanks, J. (2003). Exposure to violent media: The effects of songs with violent lyrics on aggressive thoughts and feelings.  Journal of Personality and Social Psycholog y, Vol. 84, No. 5.

Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life.  Journal of Personality and Social Psychology , Vol. 78, No. 4.

Ferguson, C.J. (2011). Video games and youth violence: A Prospective analysis in adolescents.  Journal of Youth and Adolescence , Vol. 40, No. 4.

Gentile, D.A., & Bushman, B.J. (2012). Reassessing media violence effects using a risk and resilience approach to understanding aggression.  Psychology of Popular Media Culture , Vol. 1, No. 3.

Huesmann, L. R., & Eron, L. D. (1986). Television and the aggressive child: A cross-national comparison. Hillsdale, NJ: Erlbaum.

Huesmann, L. R., Moise-Titus, J., Podolski, C. L., & Eron, L. D. (2003). Longitudinal relations between children’s exposure to TV violence and their aggressive and violent behavior in young adulthood: 1977–1992.  Developmental Psychology , Vol. 39, No. 2, 201–221.

Huston, A. C., Donnerstein, E., Fairchild, H., Feshbach, N. D., Katz, P. A., Murray, J. P., Rubinstein, E. A., Wilcox, B. & Zuckerman, D. (1992). Big world, small screen: The role of television in American society. Lincoln, NE: University of Nebraska Press.

Krahe, B., Moller, I., Kirwil, L., Huesmann, L.R., Felber, J., & Berger, A. (2011). Desensitization to media violence: Links with habitual media violence exposure, aggressive cognitions, and aggressive behavior.  Journal of Personality and Social Psychology , Vol. 100, No. 4.

Murray, J. P. (1973). Television and violence: Implications of the Surgeon General’s research program.  American Psychologist , Vol. 28, 472–478.

National Institute of Mental Health (1982). Television and behavior: Ten years of scientific progress and implications for the eighties, Vol. 1. Rockville, MD: U.S. Department of Health and Human Services.

Recommended Reading

You may also like.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Int J Environ Res Public Health

Violent Video Game Exposure and Problem Behaviors among Children and Adolescents: The Mediating Role of Deviant Peer Affiliation for Gender and Grade Differences

Associated data.

Data are available from the corresponding author upon reasonable request.

Based on problem behavior theory, a mediation model for gender and grade differences is explored in this study. The study examined gender and grade differences in the effects of violent video games and deviant peer affiliation on problem behaviors among children and adolescents. A total of 2118 children and adolescents from four primary and middle schools in China (M age = 13.08, SD = 2.17) were surveyed using an anonymous questionnaire on basic information, exposure to violent video games, deviant peer affiliation, and problem behaviors. The results showed that exposure to violent video games significantly positively predicted problem behaviors, and deviant peer affiliation played a mediating role. Significant gender and grade differences were found in the mediating effect. This finding helps understand the individual differences in the influencing factors of problem behaviors. Further, it has important implications for interventions to reduce problem behaviors among children and adolescents.

1. Introduction

Problem behavior (PB) is one of the most prevalent and persistent forms of maladjustment among children and adolescents [ 1 ]. It refers to abnormal behaviors that occur in individuals that hinder their social adjustment, involving both their own emotional abnormalities and behaviors that negatively affect others and society [ 2 ]. Further, it can be divided into internalizing and externalizing problems. Research has shown that PBs among children and adolescents are often strongly associated with lower academic performance [ 3 ], substance addiction [ 4 ], adjustment difficulties [ 5 ], and even lead to delinquent behavior [ 6 ]. Moreover, this adverse effect often persists into adulthood [ 7 ]. Therefore, it is necessary to study the factors influencing children and adolescents’ PBs to reduce the occurrence of their PBs and promote the healthy development of primary and middle school students.

Problem behavior theory (PBT) suggests that PBs do not occur randomly among children and adolescents but result from a combination of risk and protective factors. Protective factors reduce the likelihood of PBs by providing prosocial behavior patterns and individual or social regulation of PBs. Contrastingly, risk factors increase the likelihood of PBs by providing PB patterns, greater exposure or involvement in PBs, and increased individual susceptibility to PBs [ 8 , 9 , 10 ].

Since the beginning of the 21st century, with the rapid development of the Internet, video games have been an important leisure and entertainment tool for children and adolescents. Violent video games, as a popular game genre, are vital for the development of children and adolescents. Based on PBT, violent video games serve as a virtual external environment that can influence the production and dissolution of PBs among children and adolescents. Scholars have investigated the effects of violent video games on children and adolescents. Through multiple meta-analyses, they established that violent video games significantly adversely affected aggressive behavior, aggressive affect, violent desensitization, and mental health [ 11 ]. Moreover, few studies have found that deviant peer affiliation (DPA) may mediate the relationship between risk factors and PBs. For example, Bao et al. (2015) found that school climate indirectly predicts juvenile criminal behavior through adverse peer interactions [ 12 ]. Sun and Sun (2021) suggested that peer influence may mediate the relationship between violent video games and PBs [ 13 ]. Violent video games and peers are critical environmental factors that affect children’s and adolescents’ PBs.

Notably, in addition to risk and protective factors, PBT emphasizes the possible differences in PB by gender and age [ 14 ]. Previous studies have found that boys have more PBs than girls [ 15 ], and adolescent PBs increase with age. Further, Moffitt (2003) argues that adolescent antisocial behavior peaks at approximately 17 years of age [ 16 ].

Through literature review, we found that research on how violent video games affect PBs is limited, with inadequate discussion of social context and participants who are middle school or college students. Simultaneously, fewer studies involve middle and elementary school students. Therefore, based on a literature review and PBT, this study investigated the effects of violent video game exposure (VVGE) on children and adolescents’ PBs, including the mediating effect of DPA, with Chinese middle and elementary school students as participants. Moreover, we focused on the differences in the relationship between VVGE, DPA, and PB among children and adolescents of different genders and grades.

1.1. Violent Video Game Exposure and Problem Behavior

Most studies show that violent video games significantly increase PB in players. Regarding violent content, some meta-analyses have found that violent video games increase players’ aggressive cognition, emotion, and behavior and decrease players’ empathy, which negatively impacts players’ social behavior [ 17 , 18 ]. Concerning game frequency, studies have found that long-term video game exposure has adverse effects on adolescents’ emotions and social relations and increases the risk of anxiety, mood disorders, and social adjustment difficulties [ 19 , 20 ]. Further, attention difficulties and hyperactivity disorder are significantly related to game exposure [ 21 ]. Some empirical studies have also shown that VVGE is associated substantially with PBs such as aggressive behavior [ 22 ] and emotional problems, including anxiety and depression [ 23 , 24 ], and even criminal behavior [ 25 ]. Based on the literature reviewed above, we propose the following hypothesis:

VVGE positively correlates with PBs among children and adolescents .

1.2. Deviant Peer Affiliation as a Mediator

DPA refers to associating with peers who violate school rules and regulations, social ethics, and legal behaviors [ 26 ]. Evidence shows that DPA is significantly associated with individual PBs [ 27 , 28 ]. The General Aggression Model is often used to explain and predict the paths and ways in which violent video games lead to increased aggression. Recent revisions to the General Aggression Model theory have highlighted the role of peer groups in the association between violent video games and their adverse effects [ 29 ]. This suggests that DPA may be an important mediating variable between VVGE and PBs among children and adolescents. As children and adolescents join the school and adopt it as their main life scene, they rely more on their peers (classmates). At this stage, children and adolescents have a strong need for a sense of belonging to the group, and peers are vital in the adolescent development stage, especially in the transition to middle school. According to the “interpersonal similarity principle”, children and adolescents seek peers with the same or similar behaviors to establish friendships based on their own characteristics. Children and adolescents who play violent games are more likely to choose peers with similar behavioral characteristics to develop friendships with them [ 30 ]. Studies have found that VVGE affects the social behavior of players and those associated with them, such as increased aggression by players and their peers [ 31 , 32 ]. Some studies on actual violence have also found that exposure to community violence may increase the likelihood of adolescents becoming friends with immoral peers [ 33 ]. To avoid deviating from the social context of peer norms or peer group roles, adolescents may conform to their peers’ interests, hobbies, and behaviors based on adverse peer pressure [ 34 ] and then develop more problematic behaviors.

Similarly, DPA also affects individual behavior; it is one of the common risk factors for externalization problems (EP) [ 35 ]. Studies have found that children or adolescents with aggressive friends are more likely to have social adjustment problems [ 30 ] and that DPA is also commonly associated with skipping class, smoking, violence, or aggression [ 36 , 37 ]. Regarding internalization problems (IP), some researchers believe that the quality of friendships adolescents establish in DPA is low, and the relationship between groups is chaotic. The effort and return between them is inadequate; therefore, it is difficult to obtain necessary emotional support, which is more likely to lead to IPs, such as emotional disorders [ 38 , 39 ]. Based on the literature reviewed above, we propose the following hypothesis:

Deviant peer affiliation significantly mediates the relationship between exposure to violent games and PBs among children and adolescents .

1.3. Gender and Grade Differences

Although gender and grade differences in PBs have been widely acknowledged and discussed, few studies explore the factors influencing PBs among children and adolescents of different genders and grades. Based on PBT, as external environmental factors, VVGE and DPA may have significant gender and grade differences in their relationship with PB.

First, concerning gender, previous studies have shown that boys indulge in violent video games more than girls do. They have a lower level of guilt when exposed to violent video games [ 40 ]. Most researchers also believe that boys are more likely to be influenced by immoral peers and that they have various internal and external problems [ 41 , 42 ]. However, some research results show that girls are more likely to be influenced by immoral peers in drinking behavior [ 43 ] and depression or anxiety [ 44 ]. Second, at grade level, studies have found that playing time decreases with age [ 45 ], and that game preferences change. The susceptibility or resistance of individuals to peer influence also presents different characteristics at various ages. For example, studies have found that the tendency of individual behavior to be susceptible to peer influence seems to appear in early adolescence and reaches its peak at approximately 14 years of age [ 46 ]. This study focuses on the mediating effect of adverse peer interactions between VVGE and problem behavior. Based on this, we propose the following hypothesis:

Significant gender and grade differences exist in the relationships between VVGE, DPA, and PBs among children and adolescents .

1.4. Research Purpose

In summary, this study intends to use Chinese middle and elementary schools as the research object and propose a mediating model ( Figure 1 ) to explore the mediating effect on the relationship between VVGE and PBs among children and adolescents. Based on PBT, the differences in gender and grade were investigated.

Hypothesized model of violent video games affecting problem behavior.

2. Materials and Methods

2.1. participants.

This study used the cluster sampling method to randomly select 2191 students from the fourth grade of elementary school to the first grade of senior high school from four elementary and secondary schools in a city in southwest China. The questionnaire was screened according to the principles, whether the answer was complete, whether there was a regular answer, and whether there was a contradiction. After screening questionnaires, 2118 valid questionnaires were obtained, with an effective rate of 96.67%. The participants were aged between 9 and 17 years, with an average age of 13.08 ± 2.17 years.

Monte Carlo power analysis for indirect effects was adopted. Based on the effect sizes of previous research [ 47 , 48 ], the effects size was set for a (r = 0.10), b (r externalization problem = 0.20, r internalization problem = 0.10), and c (r externalization problem = 0.20, r internalization problem = 0.10) path. Consequently, recruiting a total of 1100 (externalization problem) and 1300 (internalization problem) participants would lead to the power of 90 percent for the indirect effects (i.e., a · b) at the p < 0.05 level with 20,000 Monte Carlo replications. Thus, the sample recruited for this study (n = 2118) was more than sufficient to provide adequate statistical power (>95 percent) to detect small indirect effects.

2.2. Measures

2.2.1. violent video game exposure questionnaire.

This questionnaire was compiled by [ 49 ] and revised by Chinese scholars, and is widely used [ 50 , 51 ]. It asked the participants to list three violent video games they had most recently encountered and to rate the frequency and violence of each game. Using a 5-point score, the degree of exposure to violent video games = amount of exposure = ∑ [violent content × frequency of using games]/3; the higher the score, the more exposure to violent video games. The violent video game exposure questionnaire has been shown to be both reliable and valid [ 52 ]. In this study, Cronbach’s α was 0.87.

2.2.2. Deviant Peer Affiliation Questionnaire

The deviant peer affiliation questionnaire [ 53 , 54 ] contained eight questions that involved destructive behaviors, such as smoking, drinking, theft, Internet addiction, truancy, or misbehavior. A 5-point score from 1 “none” to 5 “all” indicated the number of friends who showed one of the eight destructive behaviors in the recent year. Considering the average score, the higher the score, the more undesirable the peer behavior. The questionnaire has been shown to be reliable and valid [ 55 , 56 ]. In this study, Cronbach’s α was 0.78.

2.2.3. Strengths and Difficulties Questionnaire (Student Version)

This scale was developed by Goodman R. [ 57 , 58 ] and revised by Du [ 59 ]. The scale comprises five factors; because this study focused on PBs, the difficult part of the questionnaire was used. This comprised four factors: emotional symptoms, conduct problems, hyperactivity and attention disorders, and peer relationships, and was divided into internalization (emotional symptoms, peer relationships) and externalization problems (conduct problems, hyperactivity, and attention disorders) using Goodman’s suggestion. A “0–2” scale was used, ranging from “does not meet” to “fully meets”. In previous studies, this questionnaire showed good reliability [ 60 , 61 ]. In this study, Cronbach’s α coefficient for the difficult part of the questionnaire was 0.76.

2.3. Procedure and Data Analysis

Participants voluntarily completed the questionnaire survey while at school during a specified class period lasting 20 min. SPSS 26.0 was applied to obtain descriptive statistics, Pearson correlations, and difference test. Data may be missing on some variables because participants left an answer blank for 0.28% to 0.94% of the items across the total sample. We used participants’ average scores to replace such information. Then, Amos 24 was applied to test the mediating effect of deviant peer affiliation using the structural equation model, and the differences in gender and grade in the mediating effect of deviant peer affiliation utilizing the method of group analysis.

2.4. Common Method Deviation

In this study, variable data collection adopted a self-report method. Based on Zhou and Long’s (2004) suggestion, the Harman single-factor test was adopted to test the common method deviation [ 62 ]. The results showed nine factors with eigenvalues > 1, and the variance explained by the first principal factor was 17.35%, which was less than the critical standard of 40%. It can be concluded that there were no common methodological deviations in this study.

3.1. Descriptive Statistics

Table 1 contains the basic information on all subjects. Table 2 contains the correlation, mean, and standard deviation for study variables. Table 3 contains the differences in the research variables in gender and grade.

Basic information.

Correlation.

Note: ** p < 0.01, *** p < 0.001.

Difference test.

Note: * p < 0.05, *** p < 0.001.

The results in Table 2 show that there is a significant positive correlation between VVGE and IP and EP, indicating that the more VVGE, the higher the IPs and EPs levels among children and adolescents. Further, there is a significant positive correlation between VVGE and DPA, indicating that the more VVGE, the more DPA among children and adolescents. DPA positively correlates with the IP and EP of children and adolescents, indicating that the more DPA children and adolescents have, the higher their IPs and EPs levels are.

Difference test showed significant differences in VVGE and DPA by gender and grade level—boys had higher levels of VVGE and DPA than girls did. There were substantial differences in IP by gender and non-significant differences by grade level, and girls had higher levels of IPs than boys did. Significant differences existed in EP by grade level and non-significant differences by gender. Children and adolescents in higher grades had more EPs ( Table 3 ).

3.2. Mediating Effect of Deviant Peer Affiliation between Violent Video Game Exposure and Problem Behaviors

A structural equation model was constructed using Amos24 to examine the mediating effect of DPA between VVGE and PB. According to the different test results, gender and grade were included in the mediation effect test as control variables.

Based on the mediation effect test process suggested by [ 63 ], an unmediated model with VVGE as the independent variable and IP and EP as the dependent variables is constructed. The results showed that the unmediated model fit well (χ 2 / df = 11.15, RMSEA = 0.07, CFI = 0.96, TLI = 0.93, GFI = 0.98, IFI = 0.96, SRMR = 0.04), and VVGE positively predicted IPs ( β = 0.15, p < 0.001) and EPs ( β = 0.24, p < 0.001).

A mediating model was constructed using DPA as the mediating variable. The results showed that the mediation model fit well (χ 2 / df = 10.33, RMSEA = 0.07, CFI = 0.95, TLI = 0.92, GFI = 0.97, IFI = 0.95, and SRMR = 0.05). The test results for each coefficient showed that VVGE significantly positively predicted DPA ( β = 0.24, p < 0.001), and DPA significantly positively predicted IP. After adding DPA as a mediating variable, the predictive effect of VVGE on IP weakened ( β = 0.10, p < 0.001). DPA positively predicted EP ( β = 0.38, p < 0.001), while the predictive effect of VVGE on EP was weakened ( β = 0.17, p < 0.001), indicating that DPA partially mediated the relationship between VVGE and IP and EP. Bootstrap (sampling times: 5000) was used further to test DPA’s mediating effect ( Table 4 ). The results showed that the mediating effect of DPA between VVGE and IP was 0.06, and 0.09 between VVGE and EP.

Breakdown table of the total effect, direct effect, and mediating effect.

3.3. Cross-Group Comparison of Mediating Effects of Deviant Peer Affiliation between Violent Game Exposure and Problem Behavior

3.3.1. gender difference analysis.

A structural equation model was used to investigate gender differences in the mediating effect of DPA between VVGE and PB, and the model included grade as a control variable. First, a model test was conducted on male and female students, and the results showed that the model fit was good in the two samples, which could be compared across groups ( Table 5 ). Next, the unconstrained Model M 0 was constructed on this basis (the male and female students had the same shape, and the path coefficient was freely estimated). The measurement weights Model M 1 was constructed based on model M 0 (the factor loading of latent variables in the two groups of models was restricted to remain unchanged across the groups). The two models fit well. The model comparison showed a significant difference between M 0 and M 1 [Δχ 2 = 20.55, p < 0.001], indicating that the model measurement coefficients of the male and female groups had cross-group inequalities. Further tests found cross-group differences in the loading coefficients of factors 1 and 2 on VVGE and the loading coefficients of peer barriers on IP. Therefore, the above coefficients were freely estimated to establish Model M 2 with equal measurement weights across groups. Finally, the structural weights Model M 3 is constructed based on M 2 (the path coefficients in the two groups of models are restricted to remain unchanged across groups). The results showed that both M 2 and M 3 models fit well, and the model comparison revealed a significant difference between M 2 and M 3 [Δχ 2 = 57.14, p < 0.001]. Further tests revealed that the path coefficients of DPA on IP and EP differed across the groups ( Table 5 , Figure 2 ). The predictive effect of DPA on IP in boys ( β = 0.31, p < 0.001) was significantly higher than that in girls ( β = 0.28, p < 0.001). However, the predictive effect of DPA on EP was significantly lower in boys ( β = 0.37, p < 0.001) than in girls ( β = 0.41, p < 0.001).

Gender differences in mediating role of deviant peer affiliation. Note: The path coefficient is male outside the brackets and female inside the brackets; the load coefficient between each latent variable and its index, the residual error and error of all variables, and the control variable coefficient are omitted to simplify the model. * p < 0.05, *** p < 0.001.

Fitting index of multi-cohort model for multi-cohort analysis of gender difference.

Note: M male and M female were male and female models.

3.3.2. Grade Difference Test

This study investigated the grade difference of the mediating role of DPA in VVGE and PB used for the cross-group comparison of the structural equation model and considered gender as a control variable in the model. The participants were divided into elementary school, junior high school, and senior high school according to their grades, and the grade differences in the intermediary model were investigated. First, the samples were divided into school sections for the model test. The results showed that the models of the three samples fit well and could be compared across groups ( Table 6 ). Next, the unconstrained model M 4 (three groups of models have the same shape, and the path coefficient can be estimated freely) was built. Further, the measurement coefficient Model M 5 (limiting the factor load of latent variables in three groups of models to be constant across groups) was built. Both models fit well, and the comparison of the models showed a significant difference between Models M 4 and M 5 [Δχ 2 = 45.66, p < 0.001], indicating that the measurement coefficients of the three groups of models were unequal across groups. Further tests showed cross-group differences in the load coefficient of factor 1 and factor 2 on VVGE, the load coefficient of factor 2 on DPA, and the load coefficient of peer obstacles on IP. Therefore, the above coefficients were estimated freely, and Model M 6 with equal measurement weights s across groups was established. Finally, a structural weights Model M 7 was built based on M 6 (the path coefficient among the three models is limited to be unchanged across groups). The results showed that the M 6 and M 7 models fit well, and the comparison indicated that M 6 and M 7 had significant differences [Δχ 2 = 110.07, p < 0.001]. Further examination showed that cross-group differences existed between the path coefficients of DPA on IP and EP and VVGE on EP ( Table 6 , Figure 3 ). For instance, the predictive effect of DPA on IP was significantly higher at the elementary school level ( β = 0.39, p < 0.001) than at the senior high school level ( β = 0.31, p < 0.001), and significantly higher at the senior high school level than at the junior high school level ( β = 0.22, p < 0.001). Further, the predictive effect of DPA on EP was significantly higher at the elementary level ( β = 0.41, p < 0.001) than at the junior high school level ( β = 0.33, p < 0.001), but considerably lower than that at the senior high school level ( β = 0.47, p < 0.001). The direct effect of VVGE on EP was significantly lower at the senior high school level ( β = 0.06, p = 0.217) than at the elementary school level ( β = 0.21, p < 0.001) and junior high school ( β = 0.24, p < 0.001).

Grade differences in mediating role of deviant peer affiliation. Note: Path coefficients outside parentheses are for elementary school, inside parentheses are for junior high school, and inside square brackets are for senior high school. The load coefficient between each latent variable and its index, the residual error and error of all variables, and the control variable coefficient are omitted to simplify the model. * p < 0.05, ** p < 0.01, *** p < 0.001.

Fitting index of multi-cohort model for multi-cohort analysis of grade difference.

Note: M elementary school , M junior high school , and M senior high school are models with different school sections.

4. Discussion

Childhood and adolescence are crucial periods of rapid individual development and tremendous change. This study was conducted with elementary, junior high, and senior high school students, focusing on the mechanisms of VVGE and DPA on PBs of children and adolescents and examining the differences by gender and grade.

First, the findings showed that VVGE positively and significantly predicted PB in children and adolescents, validating Research Hypothesis 1, which is consistent with previous research [ 19 , 20 , 21 ]. Regarding IPs, Kuss and Griffiths (2012) argue that the emergence of IPs may result from escapism and that players are attracted to games to escape from real-world problems [ 64 ]. Nonetheless, too much exposure is unhelpful and may exacerbate players’ emotional problems, such as anxiety and depression. Concerning EPs, violent video games are often fast-paced and offer frequent rewards or novel and enjoyable stimuli, which may contribute to the attention problems of child/adolescent players. According to the social learning theory, individuals can acquire undesirable behaviors in two ways: first, through observational learning, in which individuals receive unwanted behaviors by observing or imitating others’ undesirable behaviors. The other way is direct learning, in which individuals acquire undesirable behaviors through personal participation. During the game, child and adolescent players can develop unwanted behaviors by observing and imitating game non-player characters or directly manipulating game characters, which may lead to more EPs being exhibited by children and adolescents in real life.

Second, DPA mediated the relationship between VVGE and IP and EP, validating research Hypothesis 2 that VVGE affects PB by increasing children’s adolescents’ DPA. Games have a significant impact on children’s and adolescents’ peer interaction as a way of maintaining friendship. According to social network theory [ 65 ], individuals who are chronically exposed to violent games may be increasingly exposed to undesirable peers through a process of “selection”. The “selection” process refers to children and adolescents actively choosing peers with similar behaviors as their peers. Children and adolescents chronically exposed to violent video games tend to have more IPs or EPs. They may voluntarily join peers identical to them through a selection process based on similarity. The influence of undesirable peers on children and adolescents’ PB results from the interaction between children and adolescents and undesirable peers. This interaction is two-way, including the “socialization” process and the “selection” process. The process of “socialization” refers to children and adolescents making friends with peers who exhibit PB; they may develop similar behaviors under the influence of peer pressure and other factors. These two processes interact; children and adolescents who play games select peers with behavioral problems, and interactions with undesirable peers increase their own problem behaviors [ 66 ]. Simultaneously, friendships with undesirable peers tend to be unstable, and interactions with them tend to increase traditional peer rejection, which also increases the risk of IPs and EPs in children and adolescents.

Finally, the study’s results found that the effects of DPA on IP and EP showed significant gender and grade differences, partially validating research Hypothesis 3. Regarding gender, boys’ IPs were more likely to be influenced by DPA. Generally, boys are less flexible and lack cognitive and emotional coping skills and regulation when dealing with interpersonal relationships than girls [ 34 ], which may lead to more psychological distress in boys when dealing with DPA. Girls’ EPs are more likely to be influenced by DPA. On the one hand, girls are typically more precocious than boys. They are more likely to be exposed to older mixed-sex groups. Further, adolescent girls are more sensitive to social appraisal concerns and more dependent on intimate relationships as a source of self-evaluation and self-worth [ 67 ]. A qualitative study found that college girls’ drinking behavior is more often driven by pressure to impress their male peers [ 68 ], suggesting that girls are more likely to engage in more EPs out of the need for approval and influence from undesirable peers. On the other hand, boys have a greater tendency toward EPs than girls, and their EPs are more likely to be influenced by a combination of other factors, such as hormones and personality [ 69 ]. Concerning grade differences, elementary school students’ IPs were affected more by DPA. Early adolescence is a critical transition period for individual development, during which essential changes in the individual are often accompanied by changes in the social environment. Simultaneously, individuals become more independent in the face of their parents, where dependence on parents is replaced by reliance on peers, and they are more susceptible to peer influence [ 70 , 71 ]. Additionally, children in elementary school tend to show a one-off imbalance in their psychological development due to their young age. Simultaneously, they have low self-centeredness and self-control; they are more susceptible to peer pressure and more likely to develop IPs. The EPs of senior high school students are affected more by DPA. It has been found that undesirable peer influences play an important role in developing PB in middle and late adolescence [ 27 ]. In senior high school, peer interaction has become an important way for senior high school students to meet their social needs and plays an important role in learning and life. Simultaneously, the character and hobbies of peers are gradually becoming essential criteria for choosing friends, and individuals who interact with undesirable peers often tend to misbehave. Aggression and popularity are often intertwined during interactions with undesirable peers [ 72 ]. Therefore, senior high school students in unwanted peer groups may adopt destructive behaviors to maintain friendships.

This study is an effort to explore the role of DPA between VVGE and PB, as well as gender and grade differences in a large sample (more than 2000 people), covering children and adolescents from different grades in elementary school, junior high school, and senior high school. In the term of theoretical aspect, this study explores the role of social factors in the relationship between VVGE and children and adolescents’ PBs and made clear the differences in both gender and grade, which deepens our understanding of the impact of VVGE on children and adolescents’ PBs and helps to explain its potential impact mechanism. In practice, this can also bring some thinking for the education of children and adolescents. As one of the common entertainment tools for children and adolescents, violent video games have a certain negative impact on children and adolescents’ social interaction and PBs. At the same time, the DPA of children and adolescents significantly affects their IPs and EPs. Therefore, in terms of family, parents should supervise children’s network use, cultivate children’s healthy network use habits, and avoid excessive addiction to video games. At the same time, they should also pay attention to children’s social interaction, guide children to establish healthy and positive peer groups, and reduce communication with bad peers. In school, first of all, teachers and mental health experts should pay attention to network security, to educate and guide children and adolescents to correctly understand the violent factors in video games. Secondly, we should pay attention to the harm of students’ bad companions and help students to establish a healthy and positive circle of friends. In addition, parents and schools should pay attention to the differences among primary, middle, and high school students in educating and guiding children and adolescents. In the social aspect, we can create a healthy network environment for children and adolescents by improving the game classification system and combating the illegal dissemination of harmful information.

Although the current study yielded important and practical findings on the targeted intervention and guidance, several limitations should be noted. First, this study is a cross-sectional study, which is not plausible to make a causal inference. In the future, longitudinal studies can be applied to clarify the causal relationship between variables. Second, all variables in the study are self-reported and may be affected by common method bias. Therefore, a more comprehensive data collection method should be adopted. Thirdly, video games are one of the common entertainment tools for children and adolescents and are regarded as an important factor affecting the psychosocial development of children and adolescents. This study only focuses on the impact of VVGE on children and adolescents’ PBs. Future research can further discuss the differences between different video game content. Finally, future researchers should consider more potential impact factors. In this study, we found that there are significant gender and age differences in the mediating role of DPA between violent video game exposure and problem behaviors, and the development of peer relationships in children and adolescents is affected by the individual growth environment (such as parent–child relationship, school atmosphere) [ 12 , 73 ]. Therefore, examining environmental factors such as family and school helps us understand the role of deviant peer affiliation.

5. Conclusions

In sum, this study found that VVGE can affect the social interaction of children and adolescents, thereby increasing their PBs, and this effect has gender and age differences. In terms of gender, although boys generally show more EPs in their daily lives, their IPs are more susceptible to peer influence, while girls are the opposite. In terms of age, the influence of peers presents different characteristics in different age groups. The IP of primary school students is more susceptible to DPA, while the EP of high school students is more susceptible to DPA.

Acknowledgments

The authors would like to thank all the students who participated in this study. The authors would like to thank all the researchers who helped with data collection.

Funding Statement

This work was supported by the Chongqing Federation of Social Science [grant numbers 2020SZ29].

Author Contributions

Conceptualization M.W., Y.L. and S.C.; data curation, M.W., Y.L. and S.C.; formal analysis, M.W. and S.C.; funding acquisition, Y.L.; investigation, M.W., Y.L. and S.C.; methodology, M.W., Y.L. and S.C.; project administration, Y.L.; resources, Y.L.; supervision, Y.L.; writing—original draft preparation, M.W.; writing—review and editing, M.W. and Y.L. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved Research Project Ethical Review Application Form, Faculty of Psychology, Southwest University of China ( {"type":"entrez-nucleotide","attrs":{"text":"H22074","term_id":"890769"}} H22074 , 4 July 2022).

Informed Consent Statement

Informed consent was obtained from all subjects and their parents involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

• Publications
• Our Methods
• Short Reads
• Tools & Resources

Read Our Research On:

Teens and Video Games Today

85% of u.s. teens say they play video games, and about four-in-ten do so daily. teens see both positive and negative sides of video games – from problem-solving and making friends to harassment and sleep loss, table of contents.

• Who plays video games?
• How often do teens play video games?
• What devices do teens play video games on?
• Social media use among gamers
• Teen views on how much they play video games and efforts to cut back
• Are teens social with others through video games?
• Do teens think video games positively or negatively impact their lives?
• Why do teens play video games?
• Bullying and violence in video games
• Appendix A: Detailed charts
• Acknowledgments
• Methodology

Pew Research Center conducted this analysis to better understand teens’ use of and experiences with video games.

The Center conducted an online survey of 1,453 U.S. teens from Sept. 26 to Oct. 23, 2023, through Ipsos. Ipsos recruited the teens via their parents, who were part of its KnowledgePanel . The KnowledgePanel is a probability-based web panel recruited primarily through national, random sampling of residential addresses. The survey was weighted to be representative of U.S. teens ages 13 to 17 who live with their parents by age, gender, race and ethnicity, household income, and other categories.

This research was reviewed and approved by an external institutional review board (IRB), Advarra, an independent committee of experts specializing in helping to protect the rights of research participants.

Here are the questions used for this analysis , along with responses, and  its methodology .

There are long-standing debates about the impact of video games on youth. Some credit them for helping young people form friendships and teaching them about teamwork and problem-solving . Others say video games expose teenagers to violent content, negatively impact their sleep and can even lead to addiction.

With this in mind, Pew Research Center surveyed 1,423 U.S. teens ages 13 to 17 about their own video game habits – from how often they play to the friends they’ve made and whether it gets in the way of them doing well in school or getting a good night’s sleep. 1

Key findings from the survey

• Video games as a part of daily teen life: 85% of U.S. teens report playing video games, and 41% say they play them at least once a day. Four-in-ten identify as a gamer.
• Gaming as a social experience: 72% of teens who play video games say that a reason why they play them is to spend time with others. And some have even made a friend online from playing them – 47% of teen video game players say they’ve done this.
• Helpful with problem-solving, less so for sleep: Over half of teens who play video games say it has helped their problem-solving skills, but 41% also say it has hurt their sleep.
• Bullying is a problem: 80% of all teens think harassment over video games is a problem for people their age. And 41% of those who play them say they’ve been called an offensive name when playing.
• Boys’ and girls’ experiences differ: Most teen boys and girls play video games, but larger shares of boys identify as gamers (62% vs. 17%) and play every day (61% vs. 22%). Boys who play them are also more likely to experience positive things from it, like making friends, and more troubling things like harassment.

Jump to read about: Who plays video games | Socializing over video games | Views about video games’ impact | Harassment and violence in video games      

Playing video games is widespread among teens. The vast majority of U.S. teens (85%) say they play them. Just 15% say they never do, according to the survey conducted Sept. 26-Oct. 23, 2023.

In addition to asking whether teens play video games, we also wanted to learn whether they consider themselves gamers. Overall, four-in-ten U.S. teens think of themselves as gamers. Just under half of teens (45%) play video games but do not think of themselves as gamers.

Nearly all boys (97%) say they play video games, compared with about three-quarters of teen girls. There is a substantial gap by gender in whether teens identify as gamers: 62% of teen boys do, compared with 17% of girls. 2

By gender and age

Younger teen girls are more likely than older girls to say they play video games: 81% of girls ages 13 to 14 compared with 67% of those ages 15 to 17. But among boys, nearly all play video games regardless of age. 

Similar shares of teens play video games across different racial and ethnic groups and among those who live in households with different annual incomes. Go to Appendix A for more detail on which teens play video games and which teens identify as gamers.

We also asked teens how often they play video games. About four-in-ten U.S. teens say they play video games daily, including 23% who do so several times a day.

Another 22% say they play several times a week, while 21% play them about once a week or less.

Teen boys are far more likely than girls to say they play video games daily (61% vs. 22%). They are also much more likely to say they play them several times a day (36% vs. 11%).

By whether someone identifies as a gamer

About seven-in-ten teens who identify as gamers (71%) say they play video games daily. This drops to 30% among those who play them but aren’t gamers.

By household income

Roughly half of teens living in households with an annual income of less than $30,000 (53%) say they play video games at least daily. This is higher than those in households with an annual income of $30,000 to $74,999 (42%) and $75,000 or more (39%).

Go to Appendix A to see more details about who plays video games and identifies as a gamer by gender, age, race and ethnicity, and household income.

Most teens play video games on a gaming console or a smartphone. When asked about five devices, most teens report playing video games on a gaming console (73%), such as PlayStation, Switch or Xbox. And 70% do so on a smartphone. Fewer – though still sizable shares – play them on each of the following:

• 49% say they play them on a desktop or laptop computer
• 33% do so on a tablet  
• 24% play them on a virtual reality (VR) headset such as Oculus, Meta Quest or PlayStation VR

Many teens play video games on multiple devices. About a quarter of teens (27%) do so on at least four of the five devices asked about, and about half (49%) play on two or three of them. Just 8% play video games on one device.

Teen boys are more likely than girls to play video games on four of the five devices asked about – all expect tablets. For instance, roughly nine-in-ten teen boys say they ever play video games on a gaming console, compared with 57% of girls. Equal shares of teen boys and girls play them on tablets.  

Teens who consider themselves gamers are more likely than those who play video games but aren’t gamers to play on a gaming console (95% vs. 78%), desktop or laptop computer (72% vs. 45%) or a virtual reality (VR) headset (39% vs. 19%). Similar shares of both groups play them on smartphones and tablets.

One way that teens engage with others about video games is through online platforms. And our survey findings show that teen gamers stand out for their use of two online platforms that are known for their gaming communities – Discord and Twitch :

• 44% of teen gamers say they use Discord, far higher than video game players who don’t identify as gamers or those who use the platform but do not play video games at all. About three-in-ten teens overall (28%) use Discord.
• 30% of teens gamers say they use Twitch. About one-in-ten other teens or fewer say the same; 17% of teens overall use the platform.

Previous Center research shows that U.S. teens use online platforms at high rates .

Teens largely say they spend the right amount of time playing video games. When asked about how much time they spend playing them, the largest share of teens (58%) say they spend the right amount of time. Far fewer feel they spend too much (14%) or too little (13%) time playing them.

Teen boys are more likely than girls to say they spend too much time playing video games (22% vs. 6%).

By race and ethnicity

Black (17%) and Hispanic (18%) teens are about twice as likely than White teens (8%) to say they spend too little time playing video games. 3

A quarter of teens who consider themselves gamers say they spend too much time playing video games, compared with 9% of those who play video games but don’t identify as gamers. Teen gamers are also less likely to think they spend too little time playing them (19% vs. 10%).

Fewer than half of teens have reduced how much they play video games. About four-in-ten (38%) say they have ever chosen to cut back on the amount of time they spend playing them. A majority (61%) report that they have not cut back at all.

This share is on par with findings about whether teenagers have cut back with their screen time – on social media or their smartphone.

Although boys are more likely to say they play video games too much, boys and girls are on par for whether they have ever cut back. About four-in-ten teen boys (39%) and girls (38%) say that they have ever cut back.

And gamers are as likely to say they have cut back as those who play video games but don’t identify as gamers (39% and 41%).

A main goal of our survey was to ask teens about their own experiences playing video games. For this section of the report, we focus on teens who say they play video games.

Socializing with others is a key part of the video game experience. Most teens who play video games do so with others, and some have developed friendships through them.

About nine-in-ten teen video game players (89%) say they play them with other people, in person or online. Far fewer (11%) play them only on their own.

Additionally, about half (47%) report that they have ever made a friend online because of a video game they both play. This equals 40% of all U.S. teens who have made a friend online because of a video game.

These experiences vary by:  

• Gender: Most teen boy and girl video game players play them with others, though it’s more common among boys (94% vs. 82%). Boys who play video games are much more likely to say they have made a friend online because of a video game (56% vs. 35%).
• Race and ethnicity: Black (55%) and Hispanic (53%) teen video game players are more likely than White teen video game players (43%) to say they have made a friend online because of them.
• Whether someone identifies as a gamer: Nearly all teen gamers report playing video games with others (98%). Fewer – though still most – of those who play video games but aren’t gamers (81%) also play them with others. And about seven-in-ten (68%) say they have made a friend online because of a video game, compared with 29% of those who play them but don’t identify as gamers.

Teens who play video games are particularly likely to say video games help their problem-solving skills. More than half of teens who play video games (56%) say this.

Additionally, more think that video games help, rather than hurt, three other parts of their lives that the survey asked about. Among teens who play video games:

• Roughly half (47%) say it has helped their friendships
• 41% say it has helped how they work with others
• 32% say it has helped their mental health

No more than 7% say playing video games has hurt any of these.

More teens who play video games say it hurts, rather than helps, their sleep. Among these teens, 41% say it has hurt how much sleep they get, while just 5% say it helps. And small shares say playing video games has impacted how well they do in school in either a positive or a negative way.

Still, many teens who play video games think playing them doesn’t have much an impact in any of these areas. For instance, at least six-in-ten teens who play video games say it has neither a positive nor a negative impact on their mental health (60%) or their school performance (72%). Fewer (41%) say this of their problem-solving skills.

Teen boys who play video games are more likely than girls to think playing them has helped their problem-solving skills, friendships and ability to work with others. For instance, 55% of teen boys who play video games say this has helped their friendships, compared with 35% of teen girls.

As for ways that it may hurt their lives, boys who play them are more likely than girls to say that it has hurt the amount of sleep they get (45% vs. 37%) and how well they do in school (21% vs. 11%). 

Teens who consider themselves gamers are more likely than those who aren’t gamers but play video games to say video games have helped their friendships (60% vs. 35%), ability to work with others (52% vs. 32%), problem-solving skills (66% vs. 47%) and mental health (41% vs. 24%).

Gamers, though, are somewhat more likely to say playing them hurt their sleep (48% vs. 36%) and how well they do in school (20% vs. 14%).

By whether teens play too much, too little or the right amount

Teens who report playing video games too much stand out for thinking video games have hurt their sleep and school performance. Two-thirds of these teens say it has hurt the amount of sleep they get, and 39% say it hurt their schoolwork. Far fewer of those who say they play the right amount (38%) or too little (32%) say it has hurt their sleep, or say it hurt their schoolwork (12% and 16%).

Teens who play video games say they largely do so to be entertained. And many also play them to be social with and interact with others. Teens who play video games were asked about four reasons why they play video games. Among those who play video games:

• Nearly all say fun or entertainment is a major or minor reason why they play video games – with a large majority (87%) saying it’s a major reason.
• Roughly three-quarters say spending time with others is a reason, and two-thirds say this of competing with others. Roughly three-in-ten say each is a major reason.
• Fewer – 50% – see learning something as a reason, with just 13% saying it’s a major reason.

While entertainment is by far the most common reason given by teens who play video games, differences emerge across groups in why they play video games.

Teens who identify as gamers are particularly likely to say each is major reason, especially when it comes to competing against others. About four-in-ten gamers (43%) say this is a major reason, compared with 13% of those who play video games but aren’t gamers.

Teen boys who play video games are more likely than girls to say competing (36% vs. 15%), spending time with others (36% vs. 27%) and entertainment (90% vs. 83%) are major reasons they play video games.

Black and Hispanic teens who play video games are more likely than White teens to say that learning new things and competing against others are major reasons they play them. For instance, 29% of Black teen video game players say learning something new is a major reason, higher than 17% of Hispanic teen video game players. Both are higher than the 7% of White teen video game players who say the same.

Teens who play video games and live in lower-income households are especially likely to say competing against others and learning new things are major reasons. For instance, four-in-ten teen video game players who live in households with an annual income of less than $30,000 say competing against others is a major reason they play. This is higher than among those in households with annual incomes of $30,000 to $74,999 (29%) and $75,000 or more (23%).

Cyberbullying can happen in many online environments, but many teens encounter this in the video game world.

Our survey finds that name-calling is a relatively common feature of video game life – especially for boys. Roughly four-in-ten teen video game players (43%) say they have been harassed or bullied while playing a video game in one of three ways: 

• 41% have been called an offensive name
• 12% have been physically threatened
• 8% have been sent unwanted sexually explicit things

Teen boys are particularly likely to say they have been called an offensive name. About half of teen boys who play video games (48%) say this has happened while playing them, compared with about a third of girls (32%). And they are somewhat more likely than girls to have been physically threatened (15% vs. 9%).

Teen gamers are more likely than those who play video games but aren’t gamers to say they been called and offensive name (53% vs. 30%), been physically threatened (17% vs. 8%) and sent unwanted sexually explicit things (10% vs. 6%).

Teens – regardless of whether they’ve had these experiences – think bullying is a problem in gaming. Eight-in-ten U.S. teens say that when it comes to video games, harassment and bullying is a problem for people their age. This includes 29% who say it is a major problem.

It’s common for teens to think harassment while playing video games is a problem, but girls are somewhat more likely than boys to say it’s a major problem (33% vs. 25%).

There have also been decades-long debates about how violent video games can influence youth behavior , if at all – such as by encouraging or desensitizing them to violence. We wanted to get a sense of how commonly violence shows up in the video games teens are playing.

Just over half of teens who play video games (56%) say at least some of the games they play contain violence. This includes 16% who say it’s in all or most of the games they play.

Teen boys who play video games are far more likely than girls to say that at least some of the games they play contain violence (69% vs. 37%).

About three-quarters of teen gamers (73%) say that at least some of the games they play contain violence, compared with 40% among video game players who aren’t gamers.   

• Throughout this report, “teens” refers to those ages 13 to 17. ↩
• Previous Center research of U.S. adults shows that men are more likely than women to identify as gamers – especially the youngest adults. ↩
• There were not enough Asian American respondents in the sample to be broken out into a separate analysis. As always, their responses are incorporated into the general population figures throughout the report. ↩

Sign up for our weekly newsletter

Fresh data delivery Saturday mornings

Sign up for The Briefing

Weekly updates on the world of news & information

• Friendships
• Online Harassment & Bullying
• Teens & Tech
• Teens & Youth

How Teens and Parents Approach Screen Time

Teens and internet, device access fact sheet, teens and social media fact sheet, teens, social media and technology 2023, what the data says about americans’ views of artificial intelligence, most popular, report materials.

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

• Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

© 2024 Pew Research Center