Citation

Ding Y, Li D, Li X, Xiao J, Zhang H, Wang Y. Comput. Hum. Behav. 2020; 111: e106439.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.chb.2020.106439

PMID

unavailable

Abstract

Cyber bullying and victimization are prevalent in the daily lives of a large number of individuals in the current digital age. Both traditional and cyber bullying and victimization among adolescents have raised global concern. Accumulating evidence suggests that there are inter-individual differences between patterns of bullying and victimization among adolescents. However, previous research has primarily relied on variable-centered approaches and failed to reveal the heterogeneity among groups with regard to bullying and victimization. Using a cross-sectional design, we included traditional and cyber bullying and victimization as indicators and employed a person-centered approach to identify distinct subgroups and their associations with demographic, individual, family, school, and peer factors. A total of 1,529 Chinese adolescents (Mage = 14.74 years, SD = 1.48) participated in the study. Latent profile analysis identified three profiles that evidenced heterogeneity of bullying and victimization groups: uninvolved group (92%), high traditional bully-victims group (6%), and high cyber bully-victims group (2%). The findings suggest that these distinct subgroups can be predicted by factors from multiple domains. High traditional bully-victims can be predicted by male, younger age, high depressive symptoms, low classmate support, and high deviant peer affiliation. High cyber bully-victims can be predicted by male, younger age, high depressive symptoms, high interparental conflict, and high deviant peer affiliation. In addition, interparental conflict, parental warmth and acceptance, school climate, and peer attachment can further differentiate high traditional bully-victims from high cyber bully-victims. Our results provide implications for tailored prevention and intervention strategies to reduce adolescent bullying and victimization.

Language: en

Keywords

Cyber bullying and victimization; Latent profile analysis; Multiple risk exposure; Traditional bullying and victimization