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Allameh Tabataba'i University , farhadjomehri@yahoo.com
Abstract: (32 Views)
Background: Cyberbullying, as one of the serious challenges in the cyberspace, particularly among adolescents, has significant negative consequences on their mental health and social relationships. Various factors can contribute to cyberbullying, and there is a gap in comprehensive research regarding cyberbullying among adolescents.
Aims: This study aimed to examine the model of cyberbullying based on family communication patterns and interpersonal relationships, with the mediating role of dark personality traits among adolescent social media users.
Methods: The present study was descriptive-correlational research using structural equation modeling. The statistical population consisted of all male and female high school students in Tehran during the academic year 2023-2024. A sample of 400 participants was selected through cluster sampling, and the questionnaires were completed. The research instruments included the Cyber-bullying/Victimization Experience Questionnaire (Antoniadou et al., 2016), the Interpersonal skills Assessment (Fetro, 2000), the Revised Family Communication Patterns Questionnaire (Ritchie & Fitzpatrick, 1990), and the Dark Triad Dirty Dozen Scale (Jonason & Webster, 2010). Data were analyzed using structural equation modeling (SEM) with SPSS and Amos software.
Results: The results of the structural equation modeling indicated a good fit of the model. The findings showed that family communication patterns and interpersonal relationships were directly able to predict cyberbullying (p< 0.01). Additionally, family communication patterns and interpersonal relationships could indirectly predict cyberbullying through dark personality traits (p< 0.01).
Conclusion: These results suggest that family communication patterns and interpersonal relationships, considering the significant role of dark personality traits, can explain cyberbullying among adolescent social media users. It is essential to consider these factors when interacting with each other in programs aimed at reducing cyberbullying.
Aims: This study aimed to examine the model of cyberbullying based on family communication patterns and interpersonal relationships, with the mediating role of dark personality traits among adolescent social media users.
Methods: The present study was descriptive-correlational research using structural equation modeling. The statistical population consisted of all male and female high school students in Tehran during the academic year 2023-2024. A sample of 400 participants was selected through cluster sampling, and the questionnaires were completed. The research instruments included the Cyber-bullying/Victimization Experience Questionnaire (Antoniadou et al., 2016), the Interpersonal skills Assessment (Fetro, 2000), the Revised Family Communication Patterns Questionnaire (Ritchie & Fitzpatrick, 1990), and the Dark Triad Dirty Dozen Scale (Jonason & Webster, 2010). Data were analyzed using structural equation modeling (SEM) with SPSS and Amos software.
Results: The results of the structural equation modeling indicated a good fit of the model. The findings showed that family communication patterns and interpersonal relationships were directly able to predict cyberbullying (p< 0.01). Additionally, family communication patterns and interpersonal relationships could indirectly predict cyberbullying through dark personality traits (p< 0.01).
Conclusion: These results suggest that family communication patterns and interpersonal relationships, considering the significant role of dark personality traits, can explain cyberbullying among adolescent social media users. It is essential to consider these factors when interacting with each other in programs aimed at reducing cyberbullying.
Keywords: cyberbullying, dark personality traits, family communication patterns, interpersonal relationships
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This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. |
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)