Mental Health Issues and 24-Hour Movement Guidelines-Based Intervention Strategies for University Students With High-Risk Social Network Addiction: Cross-Sectional Study Using a Machine Learning Approach.

Journal: Journal of medical Internet research
Published Date: Jun 13, 2025

Abstract

BACKGROUND: The exponential growth of digital technologies and the ubiquity of social media platforms have led to unprecedented mental health challenges among college students, highlighting the critical need for effective intervention approaches.

Authors

  • Lin Luo
    Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
  • Junfeng Yuan
    School of Physical Education, Guizhou Normal University, Guiyang, 550075, China.
  • Chen Xu
    Department of Mathematics and Statistics, University of Ottawa, Ottawa, ON K1N 6N5, Canada.
  • Huilin Xu
    Department of Radiology, Second Affiliated Hospital, Army Medical University, Chongqing, 400037, P. R. China.
  • Haojie Tan
    School of Physical Education, Guizhou Normal University, University Town, Siya Road, Huaxi District, Guiyang, 550025, China, 86 86751983.
  • Yinhao Shi
    School of Physical Education, Guizhou Normal University, University Town, Siya Road, Huaxi District, Guiyang, 550025, China, 86 86751983.
  • Haiping Zhang
    Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Oilseeds processing, Ministry of Agriculture, Oil Crops and Lipids Process Technology National & Local Joint Engineering Laboratory, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Wuhan 430062, China.
  • Haijun Xi
    School of Physical Education, Guizhou Normal University, University Town, Siya Road, Huaxi District, Guiyang, 550025, China, 86 86751983.

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