Abstract
Depression is a large-scale and consequential problem in youth and young adults. Conversational agents (CAs) can contribute to addressing current barriers to seeking treatment, such as long waiting lists, and reduce the high dropout rates reported for other digital health interventions. However, existing CAs have not considered differences between youth and adults and are primarily designed based on a ‘one-size-fits-all’ approach that neglects individual symptoms and preferences. Therefore, we propose a theory-driven design for personalized CAs to treat depression in youth and young adults. Based on interviews with patients (i.e., people diagnosed with depression), we derive two design principles to personalize the character of the CA and its therapeutic content. These principles are instantiated in prototypes and evaluated in interviews with experts experienced in delivering psychotherapy and potential nondiagnosed users. Personalization was perceived as crucial for treatment success, and autonomy and transparency emerged as important themes for personalization. We contribute by providing design principles for personalized CAs for mental health that extend previous CA research in the context of mental health.
Keywords
- Conversational agent
- Mental health
- Personalization
- Transdisciplinary research
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Kuhlmeier, F.O., Gnewuch, U., Lüttke, S., Brakemeier, EL., Mädche, A. (2022). A Personalized Conversational Agent to Treat Depression in Youth and Young Adults – A Transdisciplinary Design Science Research Project. In: Drechsler, A., Gerber, A., Hevner, A. (eds) The Transdisciplinary Reach of Design Science Research. DESRIST 2022. Lecture Notes in Computer Science, vol 13229. Springer, Cham. https://doi.org/10.1007/978-3-031-06516-3_3
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