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Risk Factors Influencing Cyberbullying Perpetration among Middle School Students in Korea: Analysis Using the Zero-Inflated Negative Binomial Regression Model

Author

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  • Kyung Im Kang

    (Department of Nursing, College of Medicine, Dongguk University, Gyeongju 38066, Korea)

  • Kyonghwa Kang

    (Department of Nursing, Chungwoon University, Hongseong 32244, Korea)

  • Chanhee Kim

    (College of Nursing, Dong-A University, Busan 49201, Korea)

Abstract

This cross-sectional descriptive study identified risk factors and predictors related to the perpetration of and potential for cyberbullying among adolescents, respectively. The analysis included a zero-inflated negative binomial regression model. Data were assessed from 2590 middle-school student panels obtained during the first wave of the Korean Child and Youth Panel Survey 2018. Of these respondents, 63.7% said they had not experienced the perpetration of cyberbullying. However, a subsequent count model analysis showed that several factors were significantly associated with cyberbullying, including offline delinquency, aggression, smartphone dependency, and smartphone usage on weekends (either 1–3 h or over 3 h). A logit model analysis also showed several predictive factors that increased the likelihood of cyberbullying, including gender (boys), offline delinquency, aggression, smartphone usage during weekdays (1–3 h), computer usage during weekends (1–3 h), and negative parenting. These identified risks and predictors should be useful for interventions designed to prevent the perpetration of cyberbullying among middle school students.

Suggested Citation

  • Kyung Im Kang & Kyonghwa Kang & Chanhee Kim, 2021. "Risk Factors Influencing Cyberbullying Perpetration among Middle School Students in Korea: Analysis Using the Zero-Inflated Negative Binomial Regression Model," IJERPH, MDPI, vol. 18(5), pages 1-12, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:5:p:2224-:d:504918
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    References listed on IDEAS

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    Cited by:

    1. Víctor González-Calatayud & María Paz Prendes Espinosa, 2021. "Role-Based Cyberbullying Situations: Cybervictims, Cyberaggressors and Cyberbystanders," IJERPH, MDPI, vol. 18(16), pages 1-9, August.
    2. Han, Yoonsun & Kim, Seonyeong & Lee, Taekho & Kim, Suna, 2024. "Family factors and offline/online risk behaviors among South Korean adolescents: A multidimensional approach using latent profile analysis," Children and Youth Services Review, Elsevier, vol. 156(C).
    3. Mohamad Khoirun Najib & Sri Nurdiati & Ardhasena Sopaheluwakan, 2022. "Multivariate fire risk models using copula regression in Kalimantan, Indonesia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(2), pages 1263-1283, September.
    4. Yudhie Andriyana & Rinda Fitriani & Bertho Tantular & Neneng Sunengsih & Kurnia Wahyudi & I Gede Nyoman Mindra Jaya & Annisa Nur Falah, 2023. "Modeling the Cigarette Consumption of Poor Households Using Penalized Zero-Inflated Negative Binomial Regression with Minimax Concave Penalty," Mathematics, MDPI, vol. 11(14), pages 1-13, July.
    5. Omar A. Alismaiel, 2023. "Digital Media Used in Education: The Influence on Cyberbullying Behaviors among Youth Students," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    6. Pamela Tozzo & Oriana Cuman & Eleonora Moratto & Luciana Caenazzo, 2022. "Family and Educational Strategies for Cyberbullying Prevention: A Systematic Review," IJERPH, MDPI, vol. 19(16), pages 1-17, August.

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