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Articles

Latent class analysis of substance use and predictors of latent class membership among adolescents in the Republic of Korea

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Pages 20-28 | Received 19 Sep 2016, Accepted 24 Apr 2017, Published online: 25 Aug 2017
 

ABSTRACT

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.

Acknowledgements

We express our sincere appreciation to Mr. Jon Mann, College Instructor at the University of Illinois at Chicago, Academic Center for Excellence, for reviewing and editing this manuscript.

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