An artificial intelligence tool to assess the risk of severe mental distress among college students in terms of demographics, eating habits, lifestyles, and sport habits: an externally validated study using machine learning.

Journal: BMC psychiatry
PMID: 39192305

Abstract

BACKGROUND: Precisely estimating the probability of mental health challenges among college students is pivotal for facilitating timely intervention and preventative measures. However, to date, no specific artificial intelligence (AI) models have been reported to effectively forecast severe mental distress. This study aimed to develop and validate an advanced AI tool for predicting the likelihood of severe mental distress in college students.

Authors

  • Lirong Zhang
    School of Physical Science and Technology, Inner Mongolia University, Hohhot 010021, China.
  • Shaocong Zhao
    Department of Physical Education, Xiamen University of Technology, No. 600, Ligong Road, Jimei District, Xiamen, Fujian, 361024, People's Republic of China.
  • Zhongbing Yang
    School of Physical Education, Guizhou Normal University, Guizhou, 550025, People's Republic of China.
  • Hua Zheng
    College of Physical Education and Health Sciences, Chongqing Normal University, No. 37, Middle Road, University Town, Shapingba District, Chongqing, 401331, People's Republic of China. 20130296@cqnu.edu.cn.
  • Mingxing Lei
    Department of Orthopedic Surgery, Hainan Hospital of Chinese People's Liberation Army (PLA) General Hospital, Sanya, China.

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