TY - JOUR
T1 - Prospective predictors of electronic nicotine delivery system initiation in tobacco naive young adults
T2 - A machine learning approach
AU - Atuegwu, Nkiruka C.
AU - Mortensen, Eric M.
AU - Krishnan-Sarin, Suchitra
AU - Laubenbacher, Reinhard C.
AU - Litt, Mark D.
N1 - Funding Information:
Dr. Atuegwu receives support from Robert E. Leet and Clara Guthrie Patterson Trust Mentored Research grant.
Publisher Copyright:
© 2023 The Authors
PY - 2023/4
Y1 - 2023/4
N2 - The use of electronic nicotine delivery systems (ENDS) is increasing among young adults. However, there are few studies regarding predictors of ENDS initiation in tobacco-naive young adults. Identifying the risk and protective factors of ENDS initiation that are specific to tobacco-naive young adults will enable the creation of targeted policies and prevention programs. This study used machine learning (ML) to create predictive models, identify risk and protective factors for ENDS initiation for tobacco-naive young adults, and the relationship between these predictors and the prediction of ENDS initiation. We used nationally representative data of tobacco-naive young adults in the U.S drawn from the Population Assessment of Tobacco and Health (PATH) longitudinal cohort survey. Respondents were young adults (18–24 years) who had never used any tobacco products in Wave 4 and who completed Waves 4 and 5 interviews. ML techniques were used to create models and determine predictors at 1-year follow-up from Wave 4 data. Among the 2,746 tobacco-naive young adults at baseline, 309 initiated ENDS use at 1-year follow-up. The top five prospective predictors of ENDS initiation were susceptibility to ENDS, increased days of physical exercise specifically designed to strengthen muscles, frequency of social media use, marijuana use and susceptibility to cigarettes. This study identified previously unreported and emerging predictors of ENDS initiation that warrant further investigation and provided comprehensive information on the predictors of ENDS initiation. Furthermore, this study showed that ML is a promising technique that can aid ENDS monitoring and prevention programs.
AB - The use of electronic nicotine delivery systems (ENDS) is increasing among young adults. However, there are few studies regarding predictors of ENDS initiation in tobacco-naive young adults. Identifying the risk and protective factors of ENDS initiation that are specific to tobacco-naive young adults will enable the creation of targeted policies and prevention programs. This study used machine learning (ML) to create predictive models, identify risk and protective factors for ENDS initiation for tobacco-naive young adults, and the relationship between these predictors and the prediction of ENDS initiation. We used nationally representative data of tobacco-naive young adults in the U.S drawn from the Population Assessment of Tobacco and Health (PATH) longitudinal cohort survey. Respondents were young adults (18–24 years) who had never used any tobacco products in Wave 4 and who completed Waves 4 and 5 interviews. ML techniques were used to create models and determine predictors at 1-year follow-up from Wave 4 data. Among the 2,746 tobacco-naive young adults at baseline, 309 initiated ENDS use at 1-year follow-up. The top five prospective predictors of ENDS initiation were susceptibility to ENDS, increased days of physical exercise specifically designed to strengthen muscles, frequency of social media use, marijuana use and susceptibility to cigarettes. This study identified previously unreported and emerging predictors of ENDS initiation that warrant further investigation and provided comprehensive information on the predictors of ENDS initiation. Furthermore, this study showed that ML is a promising technique that can aid ENDS monitoring and prevention programs.
KW - E-cigarette
KW - ENDS
KW - Electronic nicotine delivery systems
KW - Machine learning
KW - Never tobacco users
KW - PATH
KW - Population Assessment of Tobacco and Health survey
KW - Prospective predictors
KW - Tobacco naïve
KW - Vaping
KW - Young adults
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U2 - 10.1016/j.pmedr.2023.102148
DO - 10.1016/j.pmedr.2023.102148
M3 - Article
C2 - 36865398
AN - SCOPUS:85148347052
SN - 2211-3355
VL - 32
JO - Preventive Medicine Reports
JF - Preventive Medicine Reports
M1 - 102148
ER -