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Trajectories of Depressive Symptoms among Multicultural Adolescents in Korea: Longitudinal Analysis Using Latent Class Growth Model.

Min Kyung SongJu Young YoonEunjoo Kim
Published in: International journal of environmental research and public health (2020)
The purpose of this study was to investigate the trajectory of depressive symptoms in multicultural adolescents using longitudinal data, and to identify predictive factors related to depressive symptoms of multicultural adolescents using latent class analysis. We used six time-point data derived from the 2012 to 2017 Multicultural Adolescents Panel Study (MAPS). Latent growth curve modeling was used to assess the overall features of depressive symptom trajectories in multicultural adolescents, and latent class growth modeling was used to determine the number and shape of trajectories. We applied multinomial logistic regression analysis to each class to explore predictive factors. We found that the overall slope of depressive symptoms in multicultural adolescents increased. Latent class analysis demonstrated three classes: (1) high-increasing class (i.e., high intercept, significantly increasing slope), (2) moderate-increasing class (i.e., moderate intercept, significantly increasing slope), and (3) low-stable class (i.e., low intercept, no significant slope). In particular, we found that the difference in the initial intercept of depressive symptoms determined the subsequent trajectory. There is a need for early screening for depressive symptoms in multicultural adolescents and preparing individual mental health care plans.
Keyphrases
  • depressive symptoms
  • young adults
  • physical activity
  • social support
  • sleep quality
  • cross sectional
  • bipolar disorder
  • machine learning
  • artificial intelligence
  • data analysis