Machine learning-based association analysis and cross-sectional classification of physical exercise behaviors and mental health among vocational medical students

Psychological distress is common among vocational medical students, yet how multidimensional exercise behavior relates to their mental health remains coarsely described. This cross-sectional study surveyed 1,127 students at three vocational medical colleges in China between September and November 2024, applying machine learning to two analytically separate tasks: describing association patterns between exercise profiles and psychological status, and classifying concurrent psychological risk. Exercise behavior was measured with the IPAQ Short Form plus purpose-written items on modality, motivation, social context and temporal regularity; psychological status with the GAD-7, PHQ-9, PSS-10 and SWLS, combined into three ordered categories that are operational rather than diagnostic.

Random forest ranking, Apriori rule mining and K-Means profiling agreed on three points: weekly frequency carried the most information among behavioral variables; frequent moderate-intensity aerobic activity co-occurred most often with low anxiety and depression; and four partially overlapping profiles emerged. XGBoost classified best on an internal hold-out test set of 226 students, one fifth of the full sample (accuracy 0.889, 95% CI 0.842 to 0.924; macro-averaged AUC 0.943), yet reached only 0.769 sensitivity for severe distress, and accuracy fell to 0.858 under leave-one-college-out validation. Because the design is cross-sectional and validation internal, these findings describe associations rather than supply a screening tool.

International Physical Activity Questionnaire Generalized Anxiety Disorder 7-item scale Cohen’s Perceived Stress Scale (10-item version) Synthetic Minority Oversampling Technique This work was supported by Key Project of Jiangsu Provincial Educational Science Planning in 2023, Project Number B/2023/02/127. Physical Education Department, Jiangsu Health Vocational College, Nanjing, 211800, Jiangsu, China Physical Education Department, Nanjing Tech University Pujiang Institute, Nanjing, 211200, Jiangsu, China The authors declare no competing interests. This study was approved by the Research Ethics Committee of Jiangsu Health Vocational College (Reference Number: JHVC-HS-2026-002).

Participants aged 18 years and over provided written informed consent themselves prior to enrollment. For the 214 participants who were 17 years old at the time of the survey, written informed consent was obtained from a parent or legal guardian and written assent was obtained from the student, as required by the approved protocol and by the national regulations governing research with minors. The study was conducted in accordance with the Declaration of Helsinki and relevant national regulations.

All authors have reviewed the manuscript and consent to its publication. No identifiable information regarding participants has been included. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material.