Psychological crisis detection based on behavioral data

A new approach to non-contact measurement

Bibliographic Data

ID15698776
AuthorsJiali Lin (0000-0001-5124-3588, University of Macau, corresponding author), Jiadong Tian (0009-0002-0142-7439, Macau University of Science and Technology), T Y Wang (0000-0001-6203-1142, City University of Macau), Dagang Li (0000-0002-9705-6742, Macau University of Science and Technology), Xiaoqian Jiang (0000-0001-9933-2205, Guangzhou Automobile Group (China))
Year2025
Volume13
Issue1
Pages1355-1355
Publication date2025-12-11
Open AccessYes
TypeARTICLE
VenueBMC Psychology (JOURNAL)
Journal identifiersISSN: 2050-7283 • E-ISSN: 2050-7283
PublisherBioMed Central (PUBLISHER • GB)
DOI10.1186/s40359-025-03604-0
PMID41373056
OpenAlexW4417274163
LanguageEN
References cited54

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

Crisis intervention · Intervention (counseling · Psychological intervention · Psychological research · Psychological Testing · Psychological Theory · Emotion and Mood Recognition · Mental Health Research Topics · Mental Health via Writing

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