Predicting bullying victimization among adolescents using the risk and protective factor framework: a large-scale machine learning approach

Predicting bullying victimization among adolescents using the risk and protective factor framework: a large-scale machine learning approach

Abstract Background Bullying, encompassing physical, psychological, social, or educational harm, affects approximately 1 in 20 United States teens aged 12-18. The prevalence and impact of bullying, including online bullying, necessitate a deeper understanding of risk and protective factors to enhanc...

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Bibliographic Details
Main Authors: Ethan Low, Joshua Monsen, Lindsay Schow, Rachel Roberts, Lucy Collins, Hayden Johnson, Carl L. Hanson, Quinn Snell, E. Shannon Tass
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Public Health
Subjects:
Bullying victimization
Adolescents
Risk and prevention
Machine learning
Online Access:https://doi.org/10.1186/s12889-025-21521-0
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https://doi.org/10.1186/s12889-025-21521-0

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