Using a classification tree modeling approach to predict cigarette use among adolescents in the United States.
Objective: The purpose of this study was to screen pertinent variables to identify ordered relations that provide easily interpretable and accurate predictions of the probability of cigarette use among adolescents using a classification tree modeling approach. Methods: This cross-sectional study included a national sample of 3717 U.S. adolescents aged between 12 and 20 years old from the 2016 National Survey on Drug Use and Health. Results: The results indicated that age was the most influential variable, followed by depression, race/ethnicity, family income, gender, and alcohol abuse and dependence. Additionally, several interaction emerged that identified higher and lower cigarette use profiles: youth who were between 18 and 20 years old and self-identified as non-Hispanic White, Native American/Alaska Native, and "Other" racial/ethnic group and African American, Asian, and Latinx adolescents, with depressive symptoms were at higher risk of cigarette use; while youth who reported lower family incomes, were 16-17 years old, who identified as African American, Asian, and Latinx, were also likely to report lower use of cigarettes when they reported lower depressive symptom scores. Discussion: These results are discussed relative to practice implications.
PubMed Abstracts
PubMed Abstracts