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|Latent Class Analysis of Substance Use and Predictors of Latent Class Membership Among Adolescents in the Republic of Korea|
|Sunhee Park(Kyung Hee University) , Junghee Kim(Kyung Hee University)|
|Purpose: We aimed to investigate substance use patterns and identify predictors of homogeneous
subgroups of adolescent substance users.
Methods: We analyzed nationally representative secondary data collected from Korean adolescents
(N = 72,435). To investigate substance use patterns, we conducted latent class analysis using seven
behaviors linked to alcohol, cigarette, and e-cigarette use. After choosing the best latent class model, we
investigated predictors of latent class membership (LCM) for substance use, using demographics and
mental health conditions.
Results: A four-latent class model best fit the data. Non-users (74%) had low likelihoods of reporting
lifetime and current use of alcohol, cigarette, and e-cigarette. Experimenters (10%) had high likelihoods
of reporting lifetime alcohol and cigarette use. Current drinkers (10%) had high likelihoods of reporting
lifetime and current alcohol use. Multi-substance users (6%) had high likelihoods of reporting lifetime
and current use of alcohol and cigarettes, lifetime e-cigarette use, and current binge drinking.
Additionally, demographics (gender, grades, socioeconomic status, co-residence with family members,
and grade point average) and mental health conditions (depression, suicidal ideation, and subjective
unhappiness) successfully predicted LCM.
Conclusions: In developing interventions for addressing substance-related issues, health professionals
should focus on adolescent substance use patterns and take into account factors predicting LCM.
|Journal of Substance Use, 23 (1)|