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A Combination of Factors Related to Smoking Behavior, Attractive Product Characteristics, and Socio-Cognitive Factors are Important to Distinguish a Dual User from an Exclusive E-Cigarette User

Bibliographic Data

ID15470477
AuthorsKim Romijnders (0000-0002-1491-3826, Maastricht University, corresponding author), Kim A G J Romijnders (Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan, 9, 3721 MA Bilthoven, The Netherlands), Jeroen L A Pennings (0000-0002-9188-6358, National Institute for Public Health and the Environment), Liesbeth van Osch (0000-0002-8157-1870, Maastricht University), Hein De Vries (0000-0002-3640-2517, Maastricht University), Reinskje Talhout (0000-0002-5310-9064, National Institute for Public Health and the Environment)
Year2019
Volume16
Issue21
Pages4191-4191
Publication date2019-10-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph16214191
PMID31671505
OpenAlexW2982289347
LanguageEN
Citations received2
References cited41

Although total cessation of nicotine and tobacco products would be most beneficial to improve public health, exclusive e-cigarette use has potential health benefits for smokers compared to cigarette smoking. This study investigated differences between dual users and exclusive e-cigarette users provide information to optimize health communication about smoking and vaping. A cross-sectional survey (n = 116) among 80 current, adult dual users and 36 current, adult-exclusive e-cigarette users was conducted in the Netherlands. The questionnaire assessed four clusters of factors: (1) Past and current smoking and vaping behavior, (2) product characteristics used, (3) attractiveness and reasons related to cigarettes and e-cigarettes, and (4) socio-cognitive factors regarding smoking, vaping, and not smoking or vaping. We used random forest-a machine learning algorithm-to identify distinguishing features between dual users and e-cigarette users. We are able to discern a dual user from an exclusive e-cigarette user with 86.2% accuracy based on seven factors: Social ties with other smokers, quantity of tobacco cigarettes smoked in the past (e-cigarette users) or currently (dual users), self-efficacy to not vape and smoke, unattractiveness of cigarettes, attitude towards e-cigarettes, barriers: accessibility of e-cigarettes, and intention to quit vaping (A). This combination of features provides information on how to improve health communication about smoking and vaping

Cigarette smoking · Cognition · Dual (grammatical number · Environmental health · Human–computer interaction · Product (mathematics · Psychiatry · Behavioral Health and Interventions · Computer Science · Mathematics · Medicine · Obesity, Physical Activity, Diet · Psychology · Smoking Behavior and Cessation

  • E-Liquid Flavor Preferences and Individual Factors Related to Vaping

    Open Access•Kim Romijnders, Kim AGJ Romijnders et al.•International Journal of…•2019

  • Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022

    Open Access•Wei Fang, Ying Liu et al.•International Journal of…•2024

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    Open Access•Wouter F Visser, Walther Klerx et al.•International Journal of…•2019

  • Differences between Dual Users and Switchers Center around Vaping Behavior and Its Experiences Rather than Beliefs and Attitudes

    Open Access•Karolien Adriaens, Dinska Van Gucht et al.•International Journal of…•2017

  • How and Why Do Smokers Start Using E-Cigarettes? Qualitative Study of Vapers in London, UK

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    Thomas Ashby Wills, Rebecca Knight et al.•Tobacco Control•2016

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    Open Access•Filippos T Filippidis, Anthony A Laverty et al.•Tobacco Control•2016

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    Open Access•Kathryn Hummel, Karin Hummel et al.•International Journal of Drug…•2015

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Unique citing works2
Citations per year0,29
Citation span2019 - 2024 (6)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 2

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