Age-stratified predictions of suicide attempts using machine learning in middle and late adolescence
To date, this is the first study to use machine learning models to predict suicide attempts at different ages. Our findings suggest that the optimal suicide risk prediction model differs by stage of adolescence. Future research and interventions should consider that risk presentations can change rapidly during adolescence.
Authors
- Michelle Torok (ORCID: https://orcid.org/0000-0003-3741-8075)
- Mark Larsen (ORCID: https://orcid.org/0000-0002-0272-2053)
- Juan C. Quiroz (ORCID: https://orcid.org/0000-0003-0241-5376)
- Karen Kusuma (ORCID: https://orcid.org/0000-0002-9888-9471)
Institutions
- UNSW Sydney (AU)
Publication Details
- Journal
- Journal of Affective Disorders
- Published
- 2024-08-12
- DOI
- https://doi.org/10.1016/j.jad.2024.08.043
- Citations
- 5
- Primary Topic
- Suicide and Self-Harm Studies
- Type
- article
- Field-Weighted Citation Impact
- 3.20
Funders
- Anika Therapeutics