Application of machine learning in predicting adolescent Internet behavioral addiction.

Journal: Frontiers in psychiatry
Published Date: Apr 1, 2025

Abstract

OBJECTIVE: To explore the risk factors affecting adolescents' Internet addiction behavior and build a prediction model for adolescents' Internet addiction behavior based on machine learning algorithms.

Authors

  • Yao Gan
    Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Li Kuang
    Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Xiao-Ming Xu
    Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Ming Ai
    Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Jing-Lan He
    Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Wo Wang
    Mental Health Center, University-Town Hospital of Chongqing Medical University, Chongqing, China.
  • Su Hong
    Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Jian Mei Chen
    Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Jun Cao
    Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Qi Zhang
    Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.

Keywords

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