Practitioner Perspectives on the Uses of Generative AI Chatbots in Mental Health Care: Mixed Methods Study

Area of Science:

• Mental Health Technology
• Artificial Intelligence in Healthcare
• Clinical Psychology

Background:

• Generative artificial intelligence (AI) chatbots show promise for enhancing mental health care delivery.
• AI chatbots can support practitioners with documentation, research, and client-facing therapeutic exercises.
• Limited research exists on mental health practitioners' views regarding AI chatbot integration.

Purpose of the Study:

• To investigate mental health practitioners' perspectives on various applications of generative AI chatbots.
• To assess practitioners' likelihood of recommending AI chatbots to their clients.
• To determine if a chatbot demonstration influences practitioners' recommendation likelihood.

Main Methods:

• A mixed-methods approach was employed with 23 mental health practitioners.
• Participants engaged in 45-minute interviews, selecting top AI chatbot uses and rating recommendation likelihood.
• A 11-minute AI chatbot demonstration preceded post-demonstration likelihood ratings.

Main Results:

• Generating case notes was identified as a highly favored AI chatbot application (65%, P=.001).
• Client recommendation likelihood increased significantly post-demonstration (83%, P=.002).
• Pre-demonstration recommendation likelihood did not significantly differ from chance (55%, P=.74).

Conclusions:

• Practitioners prioritize administrative AI applications, such as case note generation.
• Exposure to AI chatbot demonstrations increases practitioner willingness to recommend them to clients.
• There is a need for practitioner education and guidelines for safe and effective AI integration in mental health settings.