Literature DB >> 34710840

Device features and user behaviors as predictors of dependence among never-smoking electronic cigarette users: PATH Wave 4.

Ashley E Douglas1, Margaret G Childers2, Katelyn F Romm3, Nicholas J Felicione4, Jenny E Ozga5, Melissa D Blank6.   

Abstract

INTRODUCTION: Electronic cigarettes (ECIGs) vary greatly in their ability to deliver nicotine, which suggests they may also vary in their ability to produce dependence. This study examined individual and combined ECIG device features, and also user behaviors, as predictors of dependence in never-smoking ECIG users. Methods Data were collected from 711 current ECIG users who had smoked <100 cigarettes in their lifetime at Wave 4 of the Population Assessment of Tobacco and Health (PATH) Study. Multivariable linear regressions examined individual (e.g., contains nicotine, uses a tank, flavor preference) and combined (e.g., refillable tanks, refillable mods) device features, and user behaviors (e.g., uses/day) as predictors of dependence, withdrawal, and craving after accounting for demographic variables. Results Results for ECIG dependence and craving showed a similar pattern; higher levels were observed for older age, more frequent past 30-day use, using an ECIG containing nicotine (vs no nicotine), and using a non-refillable cartridge or refillable tank style (vs disposables). Higher withdrawal levels were observed for higher education levels and individual device features of tank (vs no tank), cartridge (vs no cartridge), refillable (vs non-refillable), and "other" flavor preference (vs tobacco flavor). Lower withdrawal levels were associated with a preference for sweet/fruit flavor(s) (vs tobacco flavor). Conclusions Few use behaviors and device features, whether examined alone or in combination, predicted dependence-related outcomes. Findings underscore the challenge with regulating ECIG products in the current marketplace, which is inundated with a myriad of device types. Published by Elsevier Ltd.

Entities:  

Keywords:  Behavior; Dependence; Device; Electronic cigarette; PATH study; Withdrawal

Mesh:

Substances:

Year:  2021        PMID: 34710840      PMCID: PMC8629948          DOI: 10.1016/j.addbeh.2021.107161

Source DB:  PubMed          Journal:  Addict Behav        ISSN: 0306-4603            Impact factor:   3.913


  42 in total

1.  A clinical laboratory model for evaluating the acute effects of electronic "cigarettes": nicotine delivery profile and cardiovascular and subjective effects.

Authors:  Andrea R Vansickel; Caroline O Cobb; Michael F Weaver; Thomas E Eissenberg
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-07-20       Impact factor: 4.254

2.  Psychometric Evaluation of the E-cigarette Dependence Scale.

Authors:  Meghan E Morean; Suchitra Krishnan-Sarin; Steve Sussman; Jonathan Foulds; Howard Fishbein; Rachel Grana; Stephanie S O'Malley
Journal:  Nicotine Tob Res       Date:  2019-10-26       Impact factor: 4.244

3.  Smoke and Vapor: Exploring the Terminology Landscape among Electronic Cigarette Users.

Authors:  Jennifer P Alexander; Blair N Coleman; Sarah E Johnson; Greta K Tessman; Cindy Tworek; Denise M Dickinson
Journal:  Tob Regul Sci       Date:  2016-07-01

4.  Assessing electronic cigarette effects and regulatory impact: Challenges with user self-reported device power.

Authors:  Alyssa K Rudy; Adam M Leventhal; Nicholas I Goldenson; Thomas Eissenberg
Journal:  Drug Alcohol Depend       Date:  2017-08-18       Impact factor: 4.492

5.  Trends in E-Cigarette Use by Age Group and Combustible Cigarette Smoking Histories, U.S. Adults, 2014-2018.

Authors:  Priti Bandi; Zachary Cahn; Ann Goding Sauer; Clifford E Douglas; Jeffrey Drope; Ahmedin Jemal; Stacey A Fedewa
Journal:  Am J Prev Med       Date:  2020-10-05       Impact factor: 5.043

6.  Clinical Laboratory Evaluation of Electronic Cigarettes/Electronic Nicotine Delivery Systems: Methodological Challenges.

Authors:  Melissa D Blank; Alison B Breland; Caroline O Cobb; Tory Spindle; Carolina Ramôa; Thomas Eissenberg
Journal:  Tob Regul Sci       Date:  2016-10

7.  Elevated Nicotine Dependence Scores among Electronic Cigarette Users at an Electronic Cigarette Convention.

Authors:  Jona M Johnson; Jessica L Muilenburg; Stephen L Rathbun; Xiaozhong Yu; Luke P Naeher; Jia-Sheng Wang
Journal:  J Community Health       Date:  2018-02

8.  Evolution of Electronic Cigarette Brands From 2013-2014 to 2016-2017: Analysis of Brand Websites.

Authors:  Greta Hsu; Jessica Y Sun; Shu-Hong Zhu
Journal:  J Med Internet Res       Date:  2018-03-12       Impact factor: 5.428

9.  A Qualitative Approach to Understanding Real-World Electronic Cigarette Use: Implications for Measurement and Regulation.

Authors:  Maria Cooper; Melissa B Harrell; Cheryl L Perry
Journal:  Prev Chronic Dis       Date:  2016-01-14       Impact factor: 2.830

10.  Dependence on e-cigarettes and cigarettes in a cross-sectional study of US adults.

Authors:  Saul Shiffman; Mark A Sembower
Journal:  Addiction       Date:  2020-04-20       Impact factor: 6.526

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