Literature DB >> 33097952

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

Eva C Rest1, Robin J Mermelstein1,2, Donald Hedeker3.   

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.
© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Year:  2021        PMID: 33097952      PMCID: PMC7976930          DOI: 10.1093/ntr/ntaa217

Source DB:  PubMed          Journal:  Nicotine Tob Res        ISSN: 1462-2203            Impact factor:   4.244


  21 in total

1.  Development of the Brief Wisconsin Inventory of Smoking Dependence Motives.

Authors:  Stevens S Smith; Megan E Piper; Daniel M Bolt; Michael C Fiore; David W Wetter; Paul M Cinciripini; Timothy B Baker
Journal:  Nicotine Tob Res       Date:  2010-03-15       Impact factor: 4.244

2.  Effects of user puff topography, device voltage, and liquid nicotine concentration on electronic cigarette nicotine yield: measurements and model predictions.

Authors:  Soha Talih; Zainab Balhas; Thomas Eissenberg; Rola Salman; Nareg Karaoghlanian; Ahmad El Hellani; Rima Baalbaki; Najat Saliba; Alan Shihadeh
Journal:  Nicotine Tob Res       Date:  2014-09-03       Impact factor: 4.244

3.  E-cigarette Dependence Measures in Dual Users: Reliability and Relations With Dependence Criteria and E-cigarette Cessation.

Authors:  Megan E Piper; Timothy B Baker; Neal L Benowitz; Stevens S Smith; Douglas E Jorenby
Journal:  Nicotine Tob Res       Date:  2020-04-21       Impact factor: 4.244

4.  Changes in Use Patterns Over 1 Year Among Smokers and Dual Users of Combustible and Electronic Cigarettes.

Authors:  Megan E Piper; Timothy B Baker; Neal L Benowitz; Douglas E Jorenby
Journal:  Nicotine Tob Res       Date:  2020-04-21       Impact factor: 4.244

5.  The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire.

Authors:  T F Heatherton; L T Kozlowski; R C Frecker; K O Fagerström
Journal:  Br J Addict       Date:  1991-09

6.  Assessing dimensions of nicotine dependence: an evaluation of the Nicotine Dependence Syndrome Scale (NDSS) and the Wisconsin Inventory of Smoking Dependence Motives (WISDM).

Authors:  Megan E Piper; Danielle E McCarthy; Daniel M Bolt; Stevens S Smith; Caryn Lerman; Neal Benowitz; Michael C Fiore; Timothy B Baker
Journal:  Nicotine Tob Res       Date:  2008-06       Impact factor: 4.244

7.  E-cigarettes: Comparing the Possible Risks of Increasing Smoking Initiation with the Potential Benefits of Increasing Smoking Cessation.

Authors:  Kenneth E Warner; David Mendez
Journal:  Nicotine Tob Res       Date:  2019-01-01       Impact factor: 4.244

8.  Comparing cigarette and e-cigarette dependence and predicting frequency of smoking and e-cigarette use in dual-users of cigarettes and e-cigarettes.

Authors:  Meghan Morean; Suchitra Krishnan-Sarin; Stephanie S O'Malley
Journal:  Addict Behav       Date:  2018-06-26       Impact factor: 4.591

9.  Tobacco Product Use Among Adults - United States, 2017.

Authors:  Teresa W Wang; Kat Asman; Andrea S Gentzke; Karen A Cullen; Enver Holder-Hayes; Carolyn Reyes-Guzman; Ahmed Jamal; Linda Neff; Brian A King
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2018-11-09       Impact factor: 17.586

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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  2 in total

1.  Biomarkers of nicotine exposure correlate with the Hooked on Nicotine Checklist among adolescents in California, United States.

Authors:  Benjamin W Chaffee; Bonnie Halpern-Felsher; Peyton Jacob; Gideon St Helen
Journal:  Addict Behav       Date:  2022-01-11       Impact factor: 3.913

2.  Response To: Can We Measure Nicotine Dependence in Dual Users of Cigarettes and ENDS?

Authors:  Robin J Mermelstein; Donald Hedeker; Eva C Rest
Journal:  Nicotine Tob Res       Date:  2021-05-04       Impact factor: 4.244

  2 in total

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