Nicotine Dependence in Dual Users of Cigarettes and E-Cigarettes: Common and Distinct Elements

Abstract

Abstract Introduction In a sample of dual users of cigarettes and electronic nicotine delivery systems (ENDS; e-cigarettes), we evaluated psychometric properties of ENDS versions of the Nicotine Dependence Syndrome Scale (NDSS), the brief Wisconsin Inventory of Smoking Dependence Motives (WISDM), and the Fagerström Test for Nicotine Dependence (FTND). Using the NDSS, we tested the hypothesis that there would be one common underlying factor of dependence across the cigarette and ENDS scales and other product-specific factors. Aims and Methods Adult dual users (N = 404) completed baseline cigarette and ENDS versions of the NDSS, WISDM, and FTND, and biweekly surveys of their smoking and vaping. Analyses included bifactor modeling, which helps to identify both a general and product-specific factor for each item, and exploratory factor analyses of the combined cigarette and ENDS NDSS items and examinations of concurrent and predictive validity. Results The bifactor model was not a good fit, suggesting the lack of one common underlying dependence factor. Factor analyses revealed separate, similar factors for both products, with only one factor (priority) showing overlap of cigarette and ENDS items. ENDS scales significantly predicted ENDS use over time, but not cigarette use. Cigarette scales did not predict ENDS use over time. Conclusions Although the cigarette and ENDS NDSS versions showed similar factor structure, there was not a primary common underlying factor reflecting drive or tolerance, but rather product-specific factors. The cigarette scales were not valid for predicting ENDS use. These results highlight the importance of separately assessing dependence for cigarettes and ENDS in dual users. Implications Although underlying dimensions of nicotine dependence may be similar for ENDS and cigarettes, separate, product-specific measures may be needed to understand differences in product-specific dependency and predict changes in use of each product over time.