Psychological crisis detection based on behavioral data: a new approach to non-contact measurement
The findings suggest that the non-contact method is effective in predicting student psychological crisis. The use of Random Forest algorithm combined with Top-N assessment can effectively identify high-risk individuals and optimize intervention priorities. Furthermore, this study explored the applicability of non-contact methods for predicting students' psychological crisis in real-world scenarios.
Authors
- Xiaoqian Jiang (ORCID: https://orcid.org/0000-0001-9933-2205)
- Tulips Yiwen Wang (ORCID: https://orcid.org/0000-0001-6203-1142)
- Dagang Li (ORCID: https://orcid.org/0000-0002-8134-0538)
- Jiali Lin
- Jiadong Tian (ORCID: https://orcid.org/0009-0002-0142-7439)
Institutions
- Macau University of Science and Technology (MO)
- University of Macau (MO)
- Guangzhou Automobile Group (China) (CN)
- Zhuhai Institute of Advanced Technology (CN)
- City University of Macau (MO)
Publication Details
- Journal
- BMC Psychology
- Published
- 2025-12-11
- DOI
- https://doi.org/10.1186/s40359-025-03604-0
- Primary Topic
- Mental Health via Writing
- Type
- article
- Field-Weighted Citation Impact
- 0.00