Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67114, first published .
Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study

Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study

Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study

Authors of this article:

Kayley Moylan1 Author Orcid Image ;   Kevin Doherty1 Author Orcid Image

Journals

  1. Guglielmucci F, Di Basilio D. Predicting Engagement With Conversational Agents in Mental Health Therapy by Examining the Role of Epistemic Trust, Personality, and Fear of Intimacy: Cross-Sectional Web-Based Survey Study. JMIR Human Factors 2025;12:e70698 View
  2. Pichowicz W, Kotas M, Piotrowski P. Performance of mental health chatbot agents in detecting and managing suicidal ideation. Scientific Reports 2025;15(1) View
  3. Xiao W, Yang X, Xie W, Deng Y, Liu S, Huang S, Zhang W, Zhang C. Global research trends in anticipatory grief associated with incurable diseases: A bibliometric analysis (2001–2024). Death Studies 2025:1 View
  4. Boit S, Patil R. A Prompt Engineering Framework for Large Language Model–Based Mental Health Chatbots: Conceptual Framework. JMIR Mental Health 2025;12:e75078 View
  5. Zhai N, Ma X, Ding X. Unpacking AI Chatbot Dependency: A Dual-Path Model of Cognitive and Affective Mechanisms. Information 2025;16(12):1025 View

Books/Policy Documents

  1. KADAM N, GUDUR R, MANE D, DESHPANDE V. AI‐driven Innovations in Physiotherapy and Oncology 1. View