Identifying the Individual and Contextual Risk Factors of Adolescent Substance Use: A Machine Learning Analysis

• In Event: Drug Use in Adolescence and Early Adulthood

Abstract

Adolescent substance use has been a severe concern in U.S. society and has caused serious health and social damage to young people. Studies revealed that multiple individual and contextual risk factors significantly influenced adolescent substance use, including individual dispositions, family environment, peer effect, life event, and school context. This study aims to clarify the impact of these various risk factors with the Machine Learning analysis of nationally representative panel data from 2010 to 2022. We also compare the results with the traditional regression method and discuss the differences to identify the benefits of using Machine Learning approaches in the study of adolescent substance use.

Authors

• Yiwei Song, University of Nevada, Las Vegas

• Seong Park, University of Nevada, Las Vegas