Ranking factors across multiple domains in predicting adolescent mental health: a Bayesian machine learning approach
Our results revealed the importance of life experience and resilience factors in predicting adolescent mental health. Future studies should investigate the causal relationship between these understudied factors and adolescent mental health.
Authors
- Yang Cao (ORCID: https://orcid.org/0000-0001-9209-3897)
- Guodong Mi (ORCID: https://orcid.org/0000-0002-0401-7753)
- Xiang Gao (ORCID: https://orcid.org/0000-0001-8510-7373)
- Li Niu (ORCID: https://orcid.org/0000-0003-1970-8634)
- Yipeng Lv
- Xuanjing Li
- Hui Wang (ORCID: https://orcid.org/0000-0002-7970-6772)
- Yan Li (ORCID: https://orcid.org/0000-0002-6680-5413)
- Shan Zhao (ORCID: https://orcid.org/0000-0002-5916-4240)
Institutions
- Shanghai Jiao Tong University (CN)
- Beijing Normal University (CN)
- Shanghai Mental Health Center (CN)
- Sichuan University of Arts and Science (CN)
- Icahn School of Medicine at Mount Sinai (US)
Publication Details
- Journal
- Child and Adolescent Psychiatry and Mental Health
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1186/s13034-025-00969-3
- Primary Topic
- Child and Adolescent Psychosocial and Emotional Development
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China