Cyberbullying and associated factors among middle school students

JIANG Xuanli; WANG Xiaoyu; GU Jiachang; MENG Yanyuan; SHENG Jiating; LIU Fangdu; LI Minhui; FEI Gaoqiang; ZHANG Xujun; LIN Ping

doi:10.16835/j.cnki.1000-9817.2023.03.018

Volume 44 Issue 3

Mar. 2023

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Article Navigation > CHINESE JOURNAL OF SCHOOL HEALTH > 2023 > 44(3): 398-402

JIANG Xuanli, WANG Xiaoyu, GU Jiachang, MENG Yanyuan, SHENG Jiating, LIU Fangdu, LI Minhui, FEI Gaoqiang, ZHANG Xujun, LIN Ping. Cyberbullying and associated factors among middle school students[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(3): 398-402. doi: 10.16835/j.cnki.1000-9817.2023.03.018

Citation:

JIANG Xuanli, WANG Xiaoyu, GU Jiachang, MENG Yanyuan, SHENG Jiating, LIU Fangdu, LI Minhui, FEI Gaoqiang, ZHANG Xujun, LIN Ping. Cyberbullying and associated factors among middle school students[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(3): 398-402. doi: 10.16835/j.cnki.1000-9817.2023.03.018

Citation:

JIANG Xuanli, WANG Xiaoyu, GU Jiachang, MENG Yanyuan, SHENG Jiating, LIU Fangdu, LI Minhui, FEI Gaoqiang, ZHANG Xujun, LIN Ping. Cyberbullying and associated factors among middle school students[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(3): 398-402. doi: 10.16835/j.cnki.1000-9817.2023.03.018

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Cyberbullying and associated factors among middle school students

doi: 10.16835/j.cnki.1000-9817.2023.03.018

1.
Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing (210009), China

Received Date: 2022-11-11
Rev Recd Date: 2023-01-28
Publish Date: 2023-03-25

Abstract

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.
- Internet,
- Violence,
- Mental health,
- Regression analysis,
- Students

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References(27)

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