Predictors of Adolescents’ Transition Through the Stages of Change for Quitting E-Cigarettes: Findings From the Population Assessment of Tobacco and Health Study

Author:

Ahuja Nikhil1ORCID,Kedia Satish2ORCID,Ward Kenneth D.2,Jiang Yu3,Dillon Patrick J.4

Affiliation:

1. Department of Public Health, Slippery Rock University of Pennsylvania, Slippery Rock, PA, USA

2. Division of Social and Behavioral Sciences, University of Memphis, School of Public Health, Memphis, TN, USA

3. Division of Epidemiology and Biostatistics, University of Memphis, School of Public Health, Memphis, TN, USA

4. School of Communication Studies, Kent State University at Stark, North Canton, OH, USA

Abstract

Purpose To identify predictive factors associated with US adolescents’ transition through the stages of change for potentially quitting e-cigarettes using the Trans-theoretical model of behavior change. Design Prospective cohort study. Setting United States. Subjects We utilized data from adolescents (12-17 years) in Wave 3 of the Population Assessment of Tobacco and Health study who used e-cigarettes exclusively over the past 30 days (n = 177) and were followed up with in Wave 4. Measures Outcome variables were 3 transition categories: those who remained stagnant, those who progressed, and those who regressed in their stage of quitting e-cigarettes. Predictor variables were socio-demographics, e-cigarette harm perception, e-cigarette use at home or by important people, social norms, e-cigarette and anti-tobacco advertisements, and e-cigarette health warnings. Analysis Weighted-adjusted multinomial regression analysis was performed to determine the association between predictor and outcome variables. Results From Wave 3 to Wave 4, 19% of adolescents remained stagnant; 73.3% progressed; and 7.7% regressed. Adolescents were less likely to progress in their stage of change if they perceived nicotine in e-cigarettes to be “not at all/slightly harmful” (AOR = .26 [95% CI: .25, .27], P < .001); reported important people’s use of e-cigarettes (AOR = .18 [95% CI: .05, .65, P = .009); and “rarely” noticed e-cigarette health warnings (AOR = .28 [95% CI: .08, .98, P = .054). Conclusion Intervention efforts must target specific predictive factors that may help adolescents quit e-cigarettes.

Publisher

SAGE Publications

Subject

Public Health, Environmental and Occupational Health,Health (social science)

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