Abstract
INTRODUCTION: The aim of this study was to empirically identify subgroups of dual cigarette and electronic nicotine delivery systems (ENDS) product users based on their motivations for ENDS use. METHODS: Data came from n = 713 adult dual cigarette/ENDS users in the Population Assessment of Tobacco and Health Wave 6 public use data file. We used latent class analysis to identify qualitatively different subgroups within the sample and applied logistic regression to assess correlates of latent class membership. RESULTS: We identified two latent classes: "Substituters" (62.81%) and Complementers (37.19%). Classes were primarily distinguished by Substituters reporting a higher probability of using ENDS to cut down on (97.99%) or quit (86.12%) cigarette smoking; the converse was true for Complementers (16.95%; 3.17%, respectively). Compared to Substituters, Complementers (aOR = 0.87, 95% CI = 0.81 to 0.96) expressed less interest in smoking cessation. Moreover, Complementers were less likely to have made a past-year smoking quit attempt (aOR = 0.46, 95% CI = 0.27 to 0.77) and more likely to smoke the same number of cigarettes as usual (aOR = 3.62, 95% CI = 2.04 to 6.42) or more cigarettes than usual (aOR = 5.96, 95% CI = 1.92 to 18.51) on days when they both smoked and vaped than were Substituters. No sociodemographic differences were observed. CONCLUSIONS: We identified distinct latent classes of dual cigarette/ENDS users, predominantly differentiated based on their reported probabilities of using ENDS to assist in quitting or cutting down on cigarette smoking. Findings that class membership is associated with interest in quitting and quit attempts have significant health, treatment, and study design implications. IMPLICATIONS: The identification of distinct classes of dual cigarette/ENDS users based on their motivations for ENDS use and differential associations between class membership and tobacco use characteristics has a number of implications. Class membership may affect cessation treatment approaches and has significant implications for scientific study design.