ONUBHOB-BD: A CES-D-Based Dataset on Depressive Symptoms and Associated Psychological Factors Among University Students in Bangladesh

Le résumé fourni par la source

Depression has become a growing mental health challenge among university students, especially in developing regions where academic demands, economic hardship, social pressures, and uncertainty about future careers can negatively influence psychological well-being. While previous research has extensively explored depressive symptoms and their associated determinants, openly accessible datasets based on the Center for Epidemiologic Studies Depression Scale (CES-D) remain scarce in developing-country settings such as Bangladesh, particularly for computational and machine learning research. To help address this limitation, this article introduces a structured survey dataset obtained from university students in Bangladesh through a bilingual questionnaire available in both English and Bangla and designed around the CES-D framework. The dataset contains responses from 3,168 students representing different academic years and fields of study. It incorporates demographic and academic information, psychological and contextual stress-related factors, and responses to 20 CES-D-oriented items assessing depressive symptoms. Additional information reflects several aspects of students’ psychosocial experiences, including career-related uncertainty, financial pressure, loneliness, sleep-related difficulties, motivation, emotional well-being, and social engagement. Descriptive statistical analyses and graphical examinations demonstrate meaningful variation in depressive symptom patterns across demographic and psychological characteristics. This dataset can support future investigations into student mental health, depression prediction, computational mental health research, explainable artificial intelligence, educational analytics, and the development of evidence-informed support strategies.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.