ORIGINAL RESEARCH article
Front. Digit. Health
Sec. Digital Mental Health
Volume 7 - 2025 | doi: 10.3389/fdgth.2025.1588759
This article is part of the Research TopicSociotechnical Factors Impacting AI Integration into Mental Health CareView all 3 articles
Healthcare Professionals' Perspectives on AI-Driven Decision Support in Young Adult Mental Health: An analysis through the lens of a shared decision-making framework
Provisionally accepted
- 1Academy for Health and Welfare, Halmstad University, Halmstad, Sweden
- 2Academy of Entrepreneurship, Innovation and Sustainability, Halmstad University, Halmstad, Halland, Sweden
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Abstract Background Mental healthcare faces growing challenges due to rising mental health issues, particularly among young adults. AI-based systems show promise in supporting prevention, diagnosis, and treatment through personalized care but raise concerns about trust, inclusivity, and workflow integration. Limited research exists on aligning AI functionalities with healthcare professionals' needs or incorporating shared decision-making (SDM) into AI-supported mental health services, emphasizing the need for further exploration. Objective This study aims to explore how AI-based decision support systems can be used in mental healthcare from the perspective of healthcare professionals and in the light of a SDM framework. Methods A qualitative approach using deductive content analysis was employed. Sixteen healthcare professionals working with young adults participated in semi-structured interviews. The analysis was guided by elements of SDM to identify key needs and concerns related to AI. Results Healthcare professionals acknowledged both the potential benefits and challenges of integrating AI-based decision support systems into SDM for mental healthcare. Fifteen of 23 SDM elements were identified as relevant. AI was valued for its potential in early detection, holistic assessments, and personalized treatment recommendations. However, concerns were raised about inaccuracies in interpreting non-verbal cues, risks of overdiagnosis, reduced clinician autonomy, and weakened trust and therapeutic relationships. Conclusions AI holds promise for enhancing triage, patient participation, and information exchange in mental healthcare. However, concerns about trust, safety, and overreliance on technology must be addressed. Future efforts should prioritize human-centric SDM, ensuring AI implementation mitigates risks related to equity, data privacy, and the preservation of therapeutic relationships.
Keywords: Artifici al Intelligence, shared decision making, Decision Support System - DSS, Healthcare professionals (HCP), young adults, healthcare
Received: 11 Mar 2025; Accepted: 08 Sep 2025.
Copyright: © 2025 Auf, Nygren, Lundgren, Petersson and Svedberg. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Petra Svedberg, Academy for Health and Welfare, Halmstad University, Halmstad, Sweden
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