Cross‐cultural similarities and differences in the theoretical predictors of cyberbullying perpetration: Results from a seven‐country study

Abstract

The Barlett Gentile cyberbullying model (BGCM) posits that correlated anonymity perceptions and the belief in the irrelevance of muscularity for online bullying (BIMOB) predict positive cyberbullying attitudes to predict subsequent cyberbullying perpetration. Much research has shown the BGCM to be the only published theory that differentiates traditional and cyberbullying while validly predicting cyberbullying. So far, however, the cross‐cultural ubiquity has gone understudied. Thus, 1,592 adult participants across seven countries (USA, Australia, Brazil, China, Germany, Japan, and Singapore) completed measures germane to the BGCM. Supporting the BGCM, the variables were significantly correlated for the entire sample, participants from independent cultures, and participants from interdependent cultures. However, the relationship between BIMOB and positive cyberbullying attitudes as well as the relationship between positive cyberbullying attitudes and cyberbullying perpetration were stronger for independent cultures. These results suggest that the BGCM postulates are mostly universal, but several relations appear to be culturally different. Theoretical implications are discussed.

Theoretically Predicting Cyberbullying Perpetration in Youth With the BGCM: Unique Challenges and Promising Research Opportunities

“…Moreover, longitudinal data has validated the entire model and found that Wave 2 cyberbullying attitudes mediate the relationships between (a) Wave 1 BIMOB and Wave 3 cyberbullying perpetration and (b) Wave 1 anonymity perceptions and Wave 3 cyberbullying perpetration (with waves separated by ~3 months; Barlett et al, 2017a ). Moreover, the BGCM has been validated cross-culturally (Barlett et al, 2021 ). Finally, and most importantly, studies have shown that these effects remain while statistically controlling for traditional bullying perpetration by covarying this measured variable in primary path models (Barlett and Helmstetter, 2018 ).…”

“…Finally, empirical evidence suggests that the BGCM is robust. Indeed, the tenets of the BGCM have been shown in (a) youth (Barlett, 2015 ) and adults alike (Barlett and Gentile, 2012 ), (b) using correlational (Barlett et al, 2019 ) and longitudinal studies (Barlett and Kowalewski, 2019 ), and in several countries across the world (e.g., USA, Brazil, Australia, China, Singapore, Japan, and Germany; Barlett et al, 2021 ). Overall, the amount of replicated findings across multiple studies on various samples with different empirical designs suggests a valid theoretical model.…”

Network Anonymity and Cyberbullying among Chinese Adolescents: A Moderated Mediation Model

“…There has been disagreement on the relationship between perceived anonymity and cyberbullying behavior. Many researchers considered anonymity as a situational risk factor of aggressive behavior and found that there was a positive relationship between anonymity and cyberbullying behavior [ 12 , 13 , 14 ].…”

Predictive Model of The Factors Involved in Cyberbullying of Adolescent Victims

“…Although it seems that the victim should be the only one affected, these behaviors also negatively influence aggressors and witnesses since they are at risk of suffering psychosocial and psychopathological imbalances in adolescence and their adult life (Ostrov and Kamper, 2015;Wu et al, 2015;Carrascosa et al, 2016;Sidera et al, 2021). A possible and the most severe consequence of bullying and cyberbullying is suicide, and becoming criminals or aggressors in the relatively near future (Nocito, 2017;Barlett et al, 2021;Martínez-Ferrer et al, 2021).…”

“…For this reason, this work gives continuity to those studies mentioned above, predicting the cyberbullying that students may suffer in schools. There are several studies that have worked on the prediction of cyberbullying (Barlett et al, 2017(Barlett et al, , 2021Ortega-Barón, 2017;Beltrán-Catalán et al, 2018;Flores et al, 2019;Orue and Calvete, 2019;Wang and Ngai, 2020) and consider that anonymity, insensitive traits, and moral disconnection are predictive attitudes. Directive leaders of the centers and the teaching staff could estimate and prevent potential bullying and cyberbullying situations.…”