ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2026
Continuous associations of the brief Wisconsin Inventory of Smoking Dependence Motives with transitions between cigarette and e-cigarette use.
Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionMeasures of cigarette and e-cigarette dependence may predict product transitions, and they could be used to inform tailored messaging for cigarette cessation.
methodsWe used data from a longitudinal cohort study of 353 adults who smoked cigarettes daily, with or without e-cigarettes, with product dependence assessed at baseline and year one and follow-up visits every two months (enrolled 2015-17 in Madison and Milwaukee, WI). We estimated continuous, non-linear associations between the brief Wisconsin Inventory of Smoking Dependence Motives scores for cigarettes (WISDM) and e-cigarettes (e-WISDM) with transition rates using a multistate transition model.
resultsLower WISDM scores were associated with lower rates of transitioning from cigarette-only to dual use; only 3.5% (95% CI: 1.4%, 9.3%) of those at the 10th WISDM percentile were predicted to transition to dual use compared with 25.0% (95% CI: 14.0%, 39.1%) at the 50th percentile. Higher e-WISDM scores were associated with lower rate of transitioning from dual use to either cigarette-only or e-cigarette-only use, with 50.7% (95% CI: 31.9%, 65.7%) of those who used both products predicted to continue to do so at the 50th percentile of e-WISDM compared with 91.1% (95% CI: 78.7%, 96.1%) predicted to continue both products at the 90th percentile. Ratios of e-WISDM:WISDM above 1 were associated with an increased likelihood of transitioning from dual to e-cigarette-only rather than cigarette-only use.
conclusionsProduct dependence scores were non-linearly associated with transition rates between cigarette and e-cigarette use, which may help to guide the development of personalized, adaptive cigarette cessation recommendations.
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