中国青少年网络欺凌影响因素的元分析
A Meta-Analysis of Factors Influencing Cyberbullying among Chinese Adolescents
DOI: 10.12677/ap.2025.1511616, PDF,    科研立项经费支持
作者: 王紫莹, 朱会兴, 李丽娜, 艾莉波*：华北理工大学心理与精神卫生学院，河北 唐山
关键词: 元分析；网络欺凌；中学生；Meta-Analysis； Cyberbullying； Secondary-School Students
摘要: 近年来，青少年网络欺凌的发生率呈上升趋势，了解与网络欺凌相关的因素是一个重要的社会问题。本研究旨在探讨中国青少年网络欺凌的关键影响因素。我们在PubMed、Web of Science、ScienceDirect、SpringerLink、CNKI、维普和万方数据中进行了系统的文献检索，以识别符合我们纳入标准的研究(截至2024年6月发表)。使用R语言中的meta包进行元分析，以计算汇总效应量(r)。本分析共纳入196项研究，样本量为324,443，考察了34个家庭、学校、个体和社会因素。汇总效应量(r)显示，27个因素与网络欺凌行为存在相关性。其中，关系欺凌与网络欺凌的关联最强。家庭、学校、个体和社会等多个因素显著影响中国青少年的网络欺凌行为。针对这些因素的预防和干预研究可能对未来青少年网络欺凌的研究有所帮助。
Abstract: In recent years, the prevalence of cyberbullying among adolescents has been on the rise, making the identification of its associated factors a significant social concern. This study aims to investigate the key determinants of cyberbullying among Chinese adolescents. A systematic literature search was conducted across PubMed, Web of Science, ScienceDirect, SpringerLink, CNKI, VIP, and Wanfang Data to identify eligible studies published up to June 2024. A meta-analysis was performed using the “meta” package in R to calculate pooled effect sizes (r). A total of 196 studies, involving 324,443 participants, were included in the analysis. Thirty-four factors at the family, school, individual, and societal levels were examined. The pooled effect sizes (r) indicated that 27 of these factors were significantly associated with cyberbullying behavior, with relational bullying showing the strongest association. Family, school, individual, and societal factors all significantly influence cyberbullying among Chinese adolescents. Prevention and intervention strategies targeting these factors may contribute to future efforts in addressing adolescent cyberbullying.
文章引用：王紫莹, 朱会兴, 李丽娜, 艾莉波 (2025). 中国青少年网络欺凌影响因素的元分析. 心理学进展, 15(11), 403-418. https://doi.org/10.12677/ap.2025.1511616

参考文献

[1] Aloe, A. M., & Thompson, C. G. (2021). The Synthesis of Partial Effect Sizes: A Statistical Approach to Meta-Analysis. In M. Schmidt, & K. Peng (Eds.), Handbook of Meta-Analysis in Social and Behavioral Sciences (pp. 127-152). Wiley.
[2] Buelga, S., Martínez-Ferrer, B., & Cava, M. J. (2022). Family Variables and Adolescent Cyberbullying Involvement: The Mediating Role of Communication Problems. Computers in Human Behavior, 128, 107-115.
[3] Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in Meta-Analysis Detected by a Simple, Graphical Test. BMJ, 315, 629-634.[CrossRef] [PubMed]
[4] Higgins, J. P. T., & Thompson, S. G. (2002). Quantifying Heterogeneity in a Meta-Analysis. Statistics in Medicine, 21, 1539-1558.[CrossRef] [PubMed]
[5] Noret, N., Hunter, S. C., & Rasmussen, S. (2020). The Role of Perceived Social Support in the Relationship between Being Bullied and Mental Health Difficulties in Adolescents. School Mental Health, 12, 156-168.[CrossRef] 
[6] Shek, D. T. L., Leung, K. H., Li, X., & Dou, D. (2023). Psychometric Properties of the Chinese Family Assessment Instrument: Evidence from Mainland China. Frontiers in Psychology, 14.[CrossRef] [PubMed]
[7] Valkenburg, P. M., & Peter, J. (2011). Social Consequences of the Internet for Adolescents: A Decade of Research. Current Directions in Psychological Science, 20, 27-31.
[8] Wethington, E., & Kessler, R. C. (1986). Perceived Support, Received Support, and Adjustment to Stressful Life Events. Journal of Health and Social Behavior, 27, 78.[CrossRef] 
[9] Wong, D. S. W., Chan, H. C., & Cheng, C. H. K. (2022). Cyberbullying and Face-to-Face Bullying in Collectivist Societies: The Mediating Role of “Loss of Face”. Children and Youth Services Review, 138, 106521.
[10] Wright, M. F. (2021). The Role of Anonymity in the Cyber Escalation of Relational Aggression: A Longitudinal Social Capital Perspective. Journal of Youth and Adolescence, 50, 1788-1803.