ArticleSubstance use & misuse2025
Identifying and Understanding Use Trajectories of Cigarettes and E-Cigarettes.
Article in Substance use & misuse, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Trends in adult exclusive and dual use of combustible and non-combustible tobacco products in the United States.JNCI cancer spectrum · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundThe rising use of e-cigarettes, particularly dual use with cigarettes, necessitates understanding usage patterns and identifying participant and product characteristics that influence behaviors to guide tobacco regulatory decisions.
methodsAnalysis included adults (≥18 years) from the Population Assessment of Tobacco and Health (PATH) study, a nationally representative, longitudinal cohort. Participants were classified into six e-cigarette/cigarette category at each of waves 1-5 (2013-2019). Latent class analysis (LCA) was performed to identify distinct trajectories of cigarette and e-cigarette use patterns over time in Mplus. Random forest was used to examine the importance of baseline participant and product characteristics in predicting the distinct groups of use trajectories. Within each cigarette class, odds ratios and 95% CIs of the top 15 predictors of e-cigarette use group were calculated in multinomial logistic regression controlling for age, race/ethnicity, and education.
resultsFour cigarette-use trajectories were identified: "Cigarette never smokers" (31.3%), "Past experimental cigarette smokers" (23.8%), "Current experimental cigarette smokers" (18.8%), and "Current cigarette smokers" (26.0%). E-cigarette-use trajectories included "Never users" (53.6%), "Past progressors" (32.3%), and "Current progressors" (14.3%). Random forest highlighted common and unique predictors across cigarette-use groups. For example, perceptions of e-cigarette harm relative to cigarettes strongly predicted e-cigarette progression among current smokers, whereas younger age and higher social media use were more relevant among never and past smokers.
conclusionsDistinct cigarette and e-cigarette use trajectories were identified, with predictors varying by cigarette-use group. These findings underscore the importance of targeted regulatory strategies based on subgroup-specific behaviors and characteristics.
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