Factors predicting the Major depressive disorder of engineering students in Bangladesh: a structural equation modeling approach

Abstract

ABSTRACT The global prevalence of Major Depressive Disorder (MDD) among university students is a major public health concern. However, previous studies rarely emphasized on the contributing factors to MDD among engineering students, particularly in the context of developing countries. Bangladesh is one of them where this issue has yet to be adequately studied. Therefore, the present study sought to bridge this gap by utilizing a quantitative cross-sectional research design to explore the factors affecting MDD among Bangladeshi engineering students. Data were collected from both public and private universities and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings revealed that past negative experiences (β = 0.325, t = 4.654, p < 0.001) and an unhealthy lifestyle (β = 0.366, t = 11.015, p < 0.001) are the most prominent predictors of MDD, while educational issues (β = 0.186, t = 6.582, p < 0.001), social media addiction (β = 0.143, t = 4.634, p < .001), and personal relationship issues (β = 0.071, t = 2.443, p < 0.001) are comparatively less predictive in explaining engineering students’ MDD. In contrast, family support and bonding (β = –0.247, t = 8.905, p < .001) were negatively correlated with students’ MDD. The overall findings of this study sheds light on the factors that contribute to MDD among Bangladeshi engineering students and highlights the need for development of coordinated policies aimed at improving the mental health of university students in Bangladesh.