Cyberbullying Victimization in Context: The Role of Social Inequalities in Countries and Regions. (September 2017)

• Record Type: Journal Article
• Authors: Görzig, Anke; Milosevic, Tijana; Staksrud, Elisabeth
• Other Names: Wright Michelle F. guest-editor.
• Is Part Of: Journal of cross-cultural psychology. Volume 48:Number 8(2017)
• Page Start: 1198
• Page End: 1215
• Publication Date: 2017-09
• Subjects: cyberbullying -- cross-national comparison -- bullying victimization -- culture -- contextual analyses -- multi-level analyses; Ethnopsychology -- Periodicals; 155.805
• DOI: 10.1177/0022022116686186
• Languages: English
• ISSNs: 0022-0221

Abstract

The phenomenon of cyberbullying is gaining ever more attention by media and policy makers in many countries. Theoretical frameworks using a socio-ecological approach emphasize the importance of contextual explanatory factors located at the societal level. It has been suggested that in addition to cross-national differences, the analysis of smaller units of more adjacent cultural contexts (i.e., regions) might yield more explanatory power. Leaning on previous findings and theory, the current article aims to identify and compare contextual explanatory factors associated with social inequality (i.e., crime rates, gross domestic product [GDP], life expectancy, and population density) for variation in cyber- and face-to-face bullying victimization rates within one sample. Moreover, corresponding explanatory factors are investigated across national and regional levels. Cyber- and face-to-face bullying victimization of 15, 813 nine- to sixteen-year-olds (50% female) from the cross-national survey data of EU Kids Online were linked with contextual variables of 18 countries and 179 regions obtained from data of the European Social Survey (ESS). Hierarchical multilevel-modeling analyses, adding first regional and then country-level contextual predictors for bullying victimization, were performed. Against expectations, differences for cyber- and face-to-face victimization between regions within countries were smaller than differences between countries. Regional-level life expectancy showed a negative and crime rates showed a marginal positive relation with both cyber- and face-to-face victimization. Population density showed a negative and GDP a positive relationship with cyber- but not face-to-face victimization. Adding the same predictors on the country level did not improve model fit. Possible research and policy implications are discussed.