Published on in Vol 14 (2025)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/62865, first published
.
Exploring the Credibility of Large Language Models for Mental Health Support: Protocol for a Scoping Review
Exploring the Credibility of Large Language Models for Mental Health Support: Protocol for a Scoping Review
Journals
- Zhou J, Cheng Y, He S, Chen Y, Chen H. Large Language Models for Transforming Healthcare: A Perspective on DeepSeek‐R1. MedComm – Future Medicine 2025;4(2) View
- Wang S, Zhao F, Bu D, Lu Y, Gong M, Liu H, Yang Z, Zeng X, Yuan Z, Wan B, Sun J, Wu Y, Zhao L, Wan X, Huang W, Wang T, Xu M, Luo J, Liu J, Zheng J, Zhang W, Zhang K, Zhang H, Wang S, Chen R, Zhao Y. LINS: A general medical Q&A framework for enhancing the quality and credibility of LLM-generated responses. Nature Communications 2025;16(1) View
- Voultsiou E, Moussiades L. A Systematic Review of Large Language Models in Mental Health: Opportunities, Challenges, and Future Directions. Electronics 2026;15(3):524 View
- Yang J, Liu T, Luo Y, Niu T, Pang P, Xiang A, Yang Q. Exploring the application boundaries of LLMs in mental health: a systematic scoping review. Frontiers in Psychology 2026;16 View
- Salinas-Layana A, Jiménez-Molina Á, Lira D, Véliz-Montoya F, Venegas A, Muñoz N, Chandía M, Rojas R, Martínez V. Frameworks, Methodologies, and Tools for Evaluating Large Language Models in Digital Mental Health Interventions: Protocol for a Scoping Review. JMIR Research Protocols 2026;15:e91677 View
Books/Policy Documents
- Fu M, Chan W. Oxford Intersections: AI in Society. View