Leveraging Artificial Intelligence for Stress, Anxiety, And Depression Assessment: An Empirical Study Using Dass-42 Among Postgraduate Management Students
Abstract This research examines the psychological well-being of postgraduate management students at Sanjay Ghodawat University, Atigre, by integrating the Depression Anxiety Stress Scales (DASS-42) framework with the conceptual use of Artificial Intelligence (AI). The study involved 89 MBA students from both first and second year, allowing for an in-depth evaluation of mental health patterns in an academic context. Its key aims were to assess the levels of depression, anxiety, and stress among students, analyze differences across demographic factors such as gender and age, and conceptually investigate how AI could enhance psychological evaluation through automated classification, predictive analysis, and personalized intervention systems. By merging psychological insights with AI-based approaches, this study adds value to existing literature on mental health assessment and supports the growing field of digital mental health practices in higher education.
Institutions
- FOM University of Applied Sciences for Economics and Management (DE)
- Russian State University for Physical Education Sport Youth and Tourism (RU)
- Saigon University (VN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-31
- DOI
- https://doi.org/10.5281/zenodo.17812861
- Primary Topic
- Mental Health via Writing
- Type
- article
- Field-Weighted Citation Impact
- 0.00