Identifying risk profile for adolescent e-cigarette use: A sex-stratified machine learning analysis
The findings of this study underscore the importance of considering sex differences when identifying risk profiles associated with e-cigarette use and developing targeted prevention and intervention programs for adolescents.
Authors
- Raina D. Pang (ORCID: https://orcid.org/0000-0002-0216-1655)
- Jimi Huh (ORCID: https://orcid.org/0000-0002-2727-5966)
- Jessica Barrington-Trimis
- Ming Li
- Adam M. Leventhal
- Dae-Hee Han
- Danyi Li
Institutions
- University of Southern California (US)
- Emory University (US)
Publication Details
- Journal
- Drug and Alcohol Dependence Reports
- Published
- 2026-03-11
- DOI
- https://doi.org/10.1016/j.dadr.2026.100427
- Primary Topic
- Smoking Behavior and Cessation
- Type
- article
- Field-Weighted Citation Impact
- 0.00