Metaanalysis of the relationship between violent video game play and physical aggression over time

Abstract

To clarify and quantify the influence of video game violence (VGV) on aggressive behavior, we conducted a metaanalysis of all prospective studies to date that assessed the relation between exposure to VGV and subsequent overt physical aggression. The search strategy identified 24 studies with over 17,000 participants and time lags ranging from 3 months to 4 years. The samples comprised various nationalities and ethnicities with mean ages from 9 to 19 years. For each study we obtained the standardized regression coefficient for the prospective effect of VGV on subsequent aggression, controlling for baseline aggression. VGV was related to aggression using both fixed [β = 0.113, 95% CI = (0.098, 0.128)] and random effects models [β = 0.106 (0.078, 0.134)]. When all available covariates were included, the size of the effect remained significant for both models [β = 0.080 (0.065, 0.094) and β = 0.078 (0.053, 0.102), respectively]. No evidence of publication bias was found. Ethnicity was a statistically significant moderator for the fixed-effects models (P ≤ 0.011) but not for the random-effects models. Stratified analyses indicated the effect was largest among Whites, intermediate among Asians, and nonsignificant among Hispanics. Discussion focuses on the implications of such findings for current debates regarding the effects of violent video games on physical aggression.

Keywords: aggression; ethnicity; longitudinal; metaanalysis; video games.

Fig. 1.

Standardized regression coefficients (β) associating baseline violent video game play with subsequent physical aggression including an autoregressive lag for aggression and based on data selected for ethnicity moderator analyses. Estimated effect size β (ES; square) and 95% confidence interval (CI; lines) are displayed for all effects entered into the metaanalysis (–, –, –40). Diamonds represent metaanalytically weighted mean β. Weight percentages for fixed-effects and random-effects models are labeled W(fix) and W(rand), respectively. For studies with multiple independent samples, the result for each sample is reported separately and numbered 1, 2, or 3.