청소년의 정신건강에 대한 잠재성장모형 분석

Latent Growth Model Analysis of Mental Health among Adolescents in South Korea

(Purpose) Adolescent mental health issues are increasingly prevalent, posing significant risks to overall development. This study examines the effects of self-awareness, consideration for others, peer attachment, and relationship with teachers on adolescent mental health. Given that these interactions primarily occur in school settings, this study also explores the potential for school-based interventions. By analyzing changes in adolescent mental health from middle school to high school, this study aims to identify key determinants influencing mental health and provide insights into effective support strategies. (Design/Methodology/Approach) Using data from the Korean Education Longitudinal Study 2013, this study tracked 7,324 students from middle to high school. A latent growth model (LGM) was used to analyze mental health trajectories, comparing invariant, linear, and nonlinear change models based on model fit indices. Key factors—including self-awareness, peer attachment, consideration for others, and relationship with teachers—were examined in relation to initial mental health, rate of change, and acceleration patterns. (Findings) The results indicated a gradual decline in adolescent mental health from middle school to high school, following a nonlinear trajectory. Peer attachment and relationship with teachers had the most significant influence on initial mental health levels, followed by self-awareness and consideration for others. However, students with higher self-awareness, peer attachment, and relationship with teachers experienced a more rapid decline in mental health over time. Gender differences were also evident, with female students exhibiting lower initial mental health levels and a steeper decline compared to male students. (Research Implications) This study highlights the need for school-based mental health programs, SEL initiatives, and gender-specific support to enhance adolescent well-being. Future research should explore longitudinal interactions using multivariate models for more effective interventions.