Precarious Employment Typologies and Psychotropic Medication Use and Misuse

Abstract

Introduction: Precarious employment has emerged as a significant social determinant of worker health. This cross-sectional study examined the association between precarious employment and psychotropic medication use and misuse using a typological approach. Methods: A nationally representative sample of 8,993 young workers in Korea was analyzed. Data collection was conducted in 2022, and the analyses for this study were performed in 2025. Eight precarious employment indicators related to employment security, income adequacy, worker rights, and protection were included. Latent class analysis was employed to classify employment typologies. The associations between employment typologies, psychotropic medication use, and misuse were determined using ORs and 95% CIs. Results: Three latent employment typologies were identified: standard employment relationship -like type (n=4,864; 59.7%), instrumental type (n=1,973; 20.3%), and precarious type (n=2,156; 19.9%). Psychotropic medication use was reported by 2.6%, 4.7%, and 6.5% of individuals in the standard employment relationship-like, instrumental, and precarious types, respectively. Psychotropic medication misuse was reported by 0.4%, 1.1%, and 1.4% of individuals in the standard employment relationship-like, instrumental, and precarious types, respectively. After adjusting for the sociodemographic factors, individuals in the precarious type had 6.16 times higher odds of psychotropic medication use (95% CI=3.10, 12.25) and 10.34 times higher odds of psychotropic medication misuse (95% CI=1.64, 65.39) than those in the standard employment relationship-like type. Conclusions: Precarious employment experience is closely linked with psychotropic medication use and misuse among young Korean wage workers. Policy interventions are required to improve the employment quality and ensure appropriate psychotropic medication use in this population. Am J Prev Med 2025;69(6):108064. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.