Applying network analysis to understand depression and substance use in Indian adolescents.

INTRODUCTION

Network analysis has been used to better understand relationships between depressive symptoms. Existing work has rarely examined networks of adolescents or individuals in non-western countries.

METHODS

We used data from 13,035 adolescents (52.5% male; Mage=13.8) from Bihar, a low-resource state in India. Depression was measured using the Patient Health Questionnaire-9, and substance use was measured using a questionnaire adapted from the World Health Organization. We modeled a network of depressive symptoms and a network examining connections between depressive symptoms and substance use.

RESULTS

The most commonly reported depressive symptoms were sleep problems, poor appetite, and low energy. In the depression network, feeling like a failure and sad mood were the most central symptoms, and somatic symptoms clustered together. To our surprise, depressive symptoms were only weakly associated with substance use.

LIMITATIONS

Our study uses cross-sectional data, which are not sufficient to draw causal inferences about the relationships between symptoms. Additionally, we used an exploratory data-driven approach, and we did not pose a priori hypotheses about the relationships between symptoms.

DISCUSSION

Our findings suggest that feelings like a failure and sad mood are highly central symptoms in Indian adolescents; future research may examine if these symptoms are strong targets for intervention. Sad mood has commonly been identified as a central symptom of depression in western samples, while feeling like a failure has not. We offer avenues for future research, illustrating how network analysis may enhance our ability to understand, prevent, and treat psychopathology in LMICs.