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

Kim A.G.J. Romijnders, Jeroen L.A. Pennings, Liesbeth van Osch, Hein de Vries and Reinskje Talhout
Additional contact information
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: Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan, 9, 3721 MA Bilthoven, The Netherlands
Liesbeth van Osch: Department of Health Promotion, CAPHRI School for Public Health and Primary Care, Maastricht University, POB 616 6200 MD Maastricht, The Netherlands
Hein de Vries: Department of Health Promotion, CAPHRI School for Public Health and Primary Care, Maastricht University, POB 616 6200 MD Maastricht, The Netherlands
Reinskje Talhout: Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan, 9, 3721 MA Bilthoven, The Netherlands

IJERPH, 2019, vol. 16, issue 21, 1-12

Abstract: 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.

Keywords: e-cigarettes; dual use; public health; machine learning; random forest; smoking behavior; attractiveness; socio-cognitive factors (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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