Machine learning identified different predictors of sustained cannabis vaping depending on state legalization
Using PATH Study data, machine learning found that predictors of multi-year cannabis vaping differed by legalization status: cigarette use and bullying in legal states versus heroin use and nicotine vaping in non-legal states.
Quick Facts
What This Study Found
In legalized states, CART split on cannabis use, cigarette use, bullying, and ethnicity; in non-legal states, split on cannabis use, heroin use, nicotine vaping, and hookah; predictors of sustained vaping differed from initiation predictors.
Key Numbers
PATH Waves 4-6 (December 2016-November 2021); five-terminal-node CART models for each legalization stratum; prior cannabis use was primary split in both.
How They Did This
Secondary analysis of PATH Study Waves 4-6 (2016-2021); two-stage ML (LASSO + CART) stratified by state recreational cannabis legalization; representative US young adult sample.
Why This Research Matters
Understanding who continues vaping cannabis over years is more relevant for intervention than who starts, and different predictor profiles by legalization status suggest policy context shapes sustained use.
The Bigger Picture
As cannabis vaping becomes the predominant consumption method among young adults, identifying who progresses to sustained use can help target prevention.
What This Study Doesn't Tell Us
ML identifies associations not causes; legalization status changed during study; self-reported measures; PATH attrition may bias results.
Questions This Raises
- ?Why do bullying and cigarette use predict sustained vaping only in legal states?
- ?Does the heroin-cannabis vaping connection reflect polysubstance risk?
- ?Would post-2021 data differ?
Trust & Context
- Key Stat:
- Predictors of multi-year cannabis vaping differed completely between legalized and non-legalized states
- Evidence Grade:
- Nationally representative longitudinal data with sophisticated ML, but observational design and changing policy landscape complicate interpretation.
- Study Age:
- Published 2025, data from 2016-2021
- Original Title:
- Identifying predictors of multi-year cannabis vaping in U.S. Young adults using machine learning.
- Published In:
- Addictive behaviors, 160, 108167 (2025)
- Authors:
- Choe, Siyoung, Agley, Jon(2), Elam, Kit, Bidulescu, Aurelian, Seo, Dong-Chul
- Database ID:
- RTHC-06213
Evidence Hierarchy
Follows a group of people over time to track how outcomes develop.
What do these levels mean? →Frequently Asked Questions
What predicts long-term cannabis vaping?
It depends on location. In legal states, cigarette use, bullying, and ethnicity were key. In non-legal states, heroin use, nicotine vaping, and hookah use predicted sustained vaping.
Is starting cannabis vaping the same as continuing it?
No. Predictors of multi-year cannabis vaping differed from those previously identified for vaping initiation.
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Cite This Study
https://rethinkthc.com/research/RTHC-06213APA
Choe, Siyoung; Agley, Jon; Elam, Kit; Bidulescu, Aurelian; Seo, Dong-Chul. (2025). Identifying predictors of multi-year cannabis vaping in U.S. Young adults using machine learning.. Addictive behaviors, 160, 108167. https://doi.org/10.1016/j.addbeh.2024.108167
MLA
Choe, Siyoung, et al. "Identifying predictors of multi-year cannabis vaping in U.S. Young adults using machine learning.." Addictive behaviors, 2025. https://doi.org/10.1016/j.addbeh.2024.108167
RethinkTHC
RethinkTHC Research Database. "Identifying predictors of multi-year cannabis vaping in U.S...." RTHC-06213. Retrieved from https://rethinkthc.com/research/choe-2025-identifying-predictors-of-multiyear
Access the Original Study
Study data sourced from PubMed, a service of the U.S. National Library of Medicine, National Institutes of Health.
This study breakdown was produced by the RethinkTHC research team. We analyze and report published research findings without making health recommendations. All interpretations are based solely on the published abstract and study data.