In adolescence, the prevalence of depression is found to increase but often unrecognized. While adolescence is considered critical for the onset of most of the mental illnesses, depression figures out to be the most prevalent mental health problem. The current study aims to identify the factors associated with depression among urban adolescents in India using Multi-level modeling approach. The data from a cross-sectional school-based study was used to identify the risk factors for depression among adolescents. Conventional and different multilevel general linear models were fitted and the models were compared using Likelihood Ratio tests, AIC, BIC along with the regression estimates and standard errors. The results showed that ignoring the multiple levels leads to biased estimates of standard errors which highly influence the statistical inference. The current research identified the factors responsible for depression so that relevant strategies can be adopted to reduce the risk of depression among adolescents.
Presented in Session 2. Children & Youth