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

Journal: BMC public health
PMID: 39863846

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 enhance prevention efforts. This study investigated the key risk and protective factors most highly associated with adolescent bullying victimization.

Authors

  • Ethan Low
    Computer Science, Brigham Young University, Provo, 84602, Utah, USA.
  • Joshua Monsen
    Public Health, Brigham Young University, Provo, 84602, Utah, USA.
  • Lindsay Schow
    Public Health, Brigham Young University, Provo, 84602, Utah, USA.
  • Rachel Roberts
    Public Health, Brigham Young University, Provo, 84602, Utah, USA.
  • Lucy Collins
    Computer Science, Brigham Young University, Provo, 84602, Utah, USA.
  • Hayden Johnson
    Public Health, Brigham Young University, Provo, 84602, Utah, USA.
  • Carl L Hanson
    Public Health, Brigham Young University, Provo, 84602, Utah, USA.
  • Quinn Snell
    Department of Computer Science, Brigham Young University, Provo, Utah, United States of America.
  • E Shannon Tass
    Department of Statistics, Brigham Young University, Provo, Utah, United States of America.

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