Cyberbullying and associated factors among middle school students
10.16835/j.cnki.1000-9817.2023.03.018
- VernacularTitle:中学生遭受网络欺凌现状及相关因素分析
- Author:
JIANG Xuanli, WANG Xiaoyu, GU Jiachang, MENG Yanyuan, SHENG Jiating, LIU Fangdu, LI Minhui, FEI Gaoqiang, ZHANG Xujun,LIN Ping
1
Author Information
1. Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing (210009) , China
- Publication Type:Journal Article
- Keywords:
Internet;
Violence;
Mental health;
Regression analysis;
Students
- From:
Chinese Journal of School Health
2023;44(3):398-402
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore cyberbullying and risk factors of middle school students, and to provide a reference for cyberbullying prevention in school settings.
Methods:A stratified cluster random sampling method was used to select 12 940 students from three junior high schools and four senior high schools in Yixing City of Jiangsu Province, China, to conduct a questionnaire survey from March 1 to May 31, 2019. The Chi -square test was performed to compare differences in the prevalence of cyberbullying among groups with different sociodemographic characteristics, and the multivariate Logistic regression model was employed to analyze the risk factors. A risk predictive nomogram model was constructed and then verified.
Results:Middle school students were found to be victims of cyberbullying at a rate of 12.3%. The Logistic regression results showed that alcohol use ( OR =1.93), lack of emotional management ( OR =1.30), feeling unsafe ( OR =1.70), not trusting people ( OR =1.66), increased daily online time ( OR =1.39), higher frequency of using social software or websites ( OR =2.24), poor relationships with family members ( OR =1.46), parental neglect ( OR =1.50), class leadership ( OR =1.30) and poor relationships with classmates ( OR =1.34) were risk factors for middle school students who were victims of cyberbullying ( P <0.05). Based on these 10 independent risk factors, the nomogram prediction model, had good discrimination ( AUC =0.73).
Conclusion:Cyberbullying is common among middle school students. Internet use, parental neglect and class leadership all have an impact on cyberbullying.
