Beyond Engagement: A Multidimensional Framework to Evaluate the Safe Development of Agentic AI in Mental Health
Introduces a nine-domain framework for evaluating the safe development of agentic AI systems used in mental health — spanning clinical validity, relational risk, and regulatory compliance — and applies it to eight real-world tools to expose gaps between conversational fluency and user safety.
Publisher
Lecture Notes in Computer Science (Springer Nature) — AI for Clinical Applications
Published
22 Sept 2025
Added
1 week ago
Key Findings
- Defines nine evaluation domains for agentic mental-health AI, including a dedicated relational-risk domain.
- Applied to eight real-world tools, the most popular agents often lack basic safeguards while clinically validated solutions are underused.
- Calls for structured oversight, external validation, and public awareness of agentic mental-health AI.
Methodology Notes
Peer-reviewed book chapter (LNCS, 'AI for Clinical Applications', Springer Nature; DOI 10.1007/978-3-032-06004-4_8; online 2025-09-22, print 2026). Framework development plus application to eight deployed tools. Springer landing page is auth-walled to automated fetchers; title, authors, venue, and date verified via Crossref DOI metadata, with a Zenodo supplementary record (10.5281/zenodo.15797144).
Sources
Springer LNCS chapter (primary)
Archived snapshot (Wayback Machine) — preserved against link rot
Authors
Beatriz Garcia Santa Cruz, Carlos Vega, Philip Santangelo, Venkata Satagopam
Tags
Cite This
APA
Beatriz Garcia Santa Cruz et al. (2025). Beyond Engagement: A Multidimensional Framework to Evaluate the Safe Development of Agentic AI in Mental Health. Lecture Notes in Computer Science (Springer Nature) — AI for Clinical Applications. https://link.springer.com/chapter/10.1007/978-3-032-06004-4_8
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