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Position Papers of the 20th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 44

Evaluating Depression and Stress Among Young Adults Using DASS-21: Towards Personalized Intervention Strategies

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DOI: http://dx.doi.org/10.15439/2025F7347

Citation: Position Papers of the 20th Conference on Computer Science and Intelligence Systems, M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 44, pages 49–54 ()

Full text

Abstract. Depression, anxiety, and stress are commonly studied in the elderly, often manifesting as a loss of interest in previously enjoyed activities, disrupted sleep patterns, and other emotional or behavioral changes. However, with rapid technological advancements, young adults particularly those between the ages of 20 and 40 are emerging as a highly vulnerable group. This demographic faces a unique psychological burden, as they attempt to navigate the cultural and generational gap between two vastly different worlds: an older generation that often resists or struggles to adapt to revolutionary technologies, and a younger generation having a grip on modern technology. This generational divide can create a sense of isolation and pressure for young adults especially those people living in developing countries where open conversations about mental health still remain stigmatized and difficult to initiate. This research aims to develop a mental health app that can evaluate depression, and stress among young adults using the DASS-21 self-assessment test and suggest a personalized intervention keeping in view the level and severity of depression and stress. For personalized interventions, upper confidence bound algorithm is used to maintain a balance between exploration and exploitation. Agent's performance and effectiveness of intervention is evaluated by a post-test.

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