JMIR Publications

ABSTRACT

Background:

AI‑enabled conversational tools may extend access to brief, structured self‑management support. There is limited evidence on how these tools should be deployed and fit within the wider mental healthcare pathways.

Objective:

a) to examine views and experiences of AI-DIALOG+, an AI-assisted tool delivering DIALOG+ an evidence based psychosocial intervention, among potential users and health professionals; and b) to explore how AI-DIALOG+ could be safely and effectively integrated within mental health care pathways.

Methods:

Two in‑person workshops were arranged at a UK university. One workshop included non-clinical users and one included mental health professionals. Participants interacted with a working prototype of AI-DIALOG+ during the workshop and then took part in facilitated group discussions. Workshops were recorded, transcribed, and analysed through thematic analysis. In addition, two NHS medical professionals reviewed and commented on anonymised AI–user transcripts generated during the workshops.

Results:

Four main themes emerged: 1) Perceived value: AI-DIALOG+ was perceived as valuable because of its potential to promote accessibility, autonomy, and support for structured reflection. This could be used on its own or before and during sessions with human healthcare professionals; 2) Fit within the healthcare system: participants felt that AI-DIALOG+ can be usefully integrated within existing care pathways and help patients formulate their needs and clinicians access valuable information for care planning. To achieve this integration, there is a need for the tool to include links to trusted healthcare providers or social activities, ensure accuracy of localised information and enhance alignment with service governance mechanisms; 3) Engagement and equity: to support sustained use, participants emphasised ongoing engagement mechanisms (e.g. notifications, follow-ups), culturally and linguistically competent design (e.g. quality-assured translation, plain language, voice-based interaction), and clear communication about data use and confidentiality; 4) Safety and governance: defined human oversight, structured risk assessment and risk escalation pathways were seen as crucial to ensure safety, as well as avoiding handling questions which are best dealt with by human clinicians (e.g. substance use or medication queries).

Conclusions:

AI-DIALOG+ is a flexible AI conversational tool which may be a highly useful addition to mental health care, improving access to care and supporting patient autonomy and agency. Our findings offer useful indications on how AI tools could be integrated within clinical pathways and how robust human oversight and governance could be arranged. The preliminary framework which emerged, encompassing value, system fit, engagement and equity, and safe implementation conditions, may support the evaluation of other AI-enabled conversational tools in mental health care. This framework will help to evaluate AI-supported tools not only as individual-level interventions, but as components of wider clinical and organisational health systems. This appears to be critical if such tools interact with people with complex mental health needs.