Associations and Potential Pathways Linking Excessive Short-Video Use to Mental Health Among Vocational High School Students in China: An Integrated Analysis Based on Machine Learning and Path Analysis
Zhang Q, Huang B, Song H
Behavioral sciences (Basel, Switzerland) · 0 citations
How it was studied
- Design
- Cross-sectional study (classified by our AI screen)
- Studied in
- People
- Main outcome
- Health markers and function
Who paid for it
- Funding
- Independent funding
Based on full-text disclosure statement.
Publication
- Published
- 2026-08-19 · Behav Sci (Basel) · vol. 16 · issue 8 · p. 1429
- Publisher
- Multidisciplinary Digital Publishing Institute
- Cited
- 0 citations · more than 76% of similar papers · 0.0× the field average
- References
- 51 works
- Access
- Open access (journal) · CC-BY
- Research areas
- COVID-19 and Mental Health · Digital Mental Health Interventions · Child and Adolescent Psychosocial and Emotional Development
- Keywords
- mental health, vocational high school students, social support, coping, positive coping, negative coping, mediation pathways, predictors of mental health, screen time, adolescent mental health
3 authors
From CN
- Qihan ZhangTianjin Normal University
- Baidong HuangTianjin Normal University
- Hongwen Song · correspondingUniversity of Science and Technology of China
Abstract
Excessive short-video consumption is a global concern, yet its association with mental health among vocational high school students in China remains under-researched. Among many candidate individual, psychological, and behavioral factors, it remains unclear which are the most robust predictors of mental health. This study develops a comprehensive framework to identify core predictors and examine potential pathways linking short-video use to mental health. A survey was administered to 8346 vocational high school students recruited from vocational high schools in Tianjin, China, yielding 6096 valid responses for multi-stage analysis. First, Random Forest (RF) and linear Support Vector Regression (SVR) screened 13 individual, psychological, and behavioral features to identify core predictors. Subsequently, a Path Analysis (PA) with the Bootstrap method was used to examine statistical mediating pathways involving these core features. Across RF and SVR, social support, excessive short-video use, positive coping, and negative coping emerged as the four most important predictors of mental health. PA showed generally good fit (χ2/df = 5.86, CFI = 0.998, TLI = 0.99, RMSEA = 0.03, SRMR = 0.01). Excessive short-video use was significantly and directly associated with mental health problems (effect = 0.221, 95% CI = [0.189, 0.253], 76.7% of the total association) and showed small indirect associations through three statistical pathways: (1) lower social support (effect = 0.023, 8.1%); (2) higher negative coping (effect = 0.035, 12.0%); and (3) a small serial indirect association from reduced social support to decreased positive coping (effect = 0.007, 2.6%). Findings suggest that potential intervention efforts may consider regulating short-video use while simultaneously enhancing social support and adaptive coping mechanisms as part of strategies to reduce psychological risks.
Abstract via Europe PMC. Copyright remains with the authors or publisher (CC BY).
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