Bullying prevalence across contexts: a meta-analysis measuring cyber and traditional bullying

J Adolesc Health. 2014 Nov;55(5):602-11. doi: 10.1016/j.jadohealth.2014.06.007. Epub 2014 Aug 25.


Bullying involvement in any form can have lasting physical and emotional consequences for adolescents. For programs and policies to best safeguard youth, it is important to understand prevalence of bullying across cyber and traditional contexts. We conducted a thorough review of the literature and identified 80 studies that reported corresponding prevalence rates for cyber and traditional bullying and/or aggression in adolescents. Weighted mean effect sizes were calculated, and measurement features were entered as moderators to explain variation in prevalence rates and in traditional-cyber correlations within the sample of studies. Prevalence rates for cyber bullying were lower than for traditional bullying, and cyber and traditional bullying were highly correlated. A number of measurement features moderated variability in bullying prevalence; whereas a focus on traditional relational aggression increased correlations between cyber and traditional aggressions. In our meta-analytic review, traditional bullying was twice as common as cyber bullying. Cyber and traditional bullying were also highly correlated, suggesting that polyaggression involvement should be a primary target for interventions and policy. Results of moderation analyses highlight the need for greater consensus in measurement approaches for both cyber and traditional bullying.

Keywords: Aggression; Cyber bullying; Intervention; Meta-analysis; Prevalence; Traditional bullying.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Adolescent
  • Adolescent Behavior*
  • Aggression / classification*
  • Bullying / classification*
  • Crime Victims / statistics & numerical data*
  • Female
  • Humans
  • Internal-External Control
  • Internet*
  • Interpersonal Relations*
  • Male
  • Peer Group
  • Prevalence
  • Self Concept
  • Students / statistics & numerical data