Jessica Yingst1, Jonathan Foulds2, Susan Veldheer2, Ping Du3. 1. Penn State University College of Medicine, Department of Public Health Sciences, Tobacco Center of Regulatory Science, Hershey, PA 17033, United States. Electronic address: jyingst@phs.psu.edu. 2. Penn State University College of Medicine, Department of Public Health Sciences, Tobacco Center of Regulatory Science, Hershey, PA 17033, United States. 3. Penn State University College of Medicine, Department of Public Health Sciences, Tobacco Center of Regulatory Science, Hershey, PA 17033, United States; Penn State University College of Medicine, Department of Medicine, Hershey, PA 17033, United States.
Abstract
INTRODUCTION: Electronic cigarette (e-cig) device characteristics affect use but few studies have evaluated the types of devices commonly used or how users transition between devices. This study examines e-cig device usage patterns and explores the relationship between device transitions and continued use. METHODS: E-cig users completed an online survey from 2012 to 2015 about their e-cig use, preferred device, and preferences and were followed-up via an emailed survey in January 2017. Continuing users were those reporting any e-cig use in the past 30 days at both time points while stoppers reported no use at follow-up. Means, frequencies, and Chi-square tests were used as appropriate to describe the sample, the transition between devices, and differences between groups. RESULTS: The sample was 83.6% (n = 511) continuers and 16.3% (n = 100) stoppers. At follow-up, most continuers had transitioned to using more advanced devices like mods (62.6%) with variable voltage (67.7%) and/or wattage (76.8%) and with a tank system (78.6%). Nicotine concentration decreased by half from baseline to follow-up (p < .01). Baseline cigalike users were the most likely to report stopping e-cig use (p < .01) and the most likely to return to other tobacco use (p = .02). CONCLUSION: The majority of e-cig users continued exclusive e-cig use over 3+ years and were likely to transition to devices with more advanced characteristics like variable voltage and to reduce the nicotine concentration of their liquid. Baseline cigalike users were the most likely to stop e-cig use at follow-up.
INTRODUCTION: Electronic cigarette (e-cig) device characteristics affect use but few studies have evaluated the types of devices commonly used or how users transition between devices. This study examines e-cig device usage patterns and explores the relationship between device transitions and continued use. METHODS: E-cig users completed an online survey from 2012 to 2015 about their e-cig use, preferred device, and preferences and were followed-up via an emailed survey in January 2017. Continuing users were those reporting any e-cig use in the past 30 days at both time points while stoppers reported no use at follow-up. Means, frequencies, and Chi-square tests were used as appropriate to describe the sample, the transition between devices, and differences between groups. RESULTS: The sample was 83.6% (n = 511) continuers and 16.3% (n = 100) stoppers. At follow-up, most continuers had transitioned to using more advanced devices like mods (62.6%) with variable voltage (67.7%) and/or wattage (76.8%) and with a tank system (78.6%). Nicotine concentration decreased by half from baseline to follow-up (p < .01). Baseline cigalike users were the most likely to report stopping e-cig use (p < .01) and the most likely to return to other tobacco use (p = .02). CONCLUSION: The majority of e-cig users continued exclusive e-cig use over 3+ years and were likely to transition to devices with more advanced characteristics like variable voltage and to reduce the nicotine concentration of their liquid. Baseline cigalike users were the most likely to stop e-cig use at follow-up.
Authors: Melissa D Blank; Jennifer Pearson; Caroline O Cobb; Nicholas J Felicione; Marzena M Hiler; Tory R Spindle; Alison Breland Journal: Tob Control Date: 2019-11-04 Impact factor: 7.552
Authors: Shunsaku Goto; Robert M H Grange; Riccardo Pinciroli; Ivy A Rosales; Rebecca Li; Sophie L Boerboom; Katrina F Ostrom; Eizo Marutani; Hatus V Wanderley; Aranya Bagchi; Robert B Colvin; Lorenzo Berra; Olga Minaeva; Lee E Goldstein; Rajeev Malhotra; Warren M Zapol; Fumito Ichinose; Binglan Yu Journal: Arch Toxicol Date: 2022-10-04 Impact factor: 6.168
Authors: Nicholas J Felicione; Brian Vincent Fix; Ann McNeill; K Michael Cummings; Maciej Lukasz Goniewicz; David Hammond; Ron Borland; Bryan W Heckman; Maansi Bansal-Travers; Shannon Gravely; Sara C Hitchman; David T Levy; Geoffrey T Fong; Richard O'Connor Journal: Tob Control Date: 2021-03-22 Impact factor: 6.953