Machine learning and network analysis of psychosocial factors associated with non-suicidal self-injury severity among college students.
- DOI
- 10.1016/j.psychres.2026.117541
- Published
- 2026 Oct 24
- Container
- Psychiatry research
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.psychres.2026.117541,
title = {Machine learning and network analysis of psychosocial factors associated with non-suicidal self-injury severity among college students.},
author = {Liu H and Guo Y and Hu J and Xue D and Xie G and Mao C and Ren Z},
year = {2026},
journal = {Psychiatry research},
doi = {10.1016/j.psychres.2026.117541},
url = {https://doi.org/10.1016/j.psychres.2026.117541}
}RIS
TY - JOUR TI - Machine learning and network analysis of psychosocial factors associated with non-suicidal self-injury severity among college students. AU - Liu H AU - Guo Y AU - Hu J AU - Xue D AU - Xie G AU - Mao C AU - Ren Z PY - 2026 JO - Psychiatry research DO - 10.1016/j.psychres.2026.117541 UR - https://doi.org/10.1016/j.psychres.2026.117541 ER -
APA
H, L., Y, G., J, H., D, X., G, X., C, M., & Z, R. (2026). Machine learning and network analysis of psychosocial factors associated with non-suicidal self-injury severity among college students.. Psychiatry research. https://doi.org/10.1016/j.psychres.2026.117541
Source records
- pubmed · retrieved 2026-11-10T13:35:38.970Z