User Experience and Therapeutic Alliance in AI-Driven Mental Health Interventions: A Protocol for a Systematic Review of Qualitative Studies

BackgroundArtificial intelligence (AI) technologies are increasingly being integrated into mental health interventions, but their impact on user experience and the therapeutic alliance remains poorly understood. This protocol outlines a systematic review of methods and applications. ObjectiveTo synthesize qualitative evidence on how AI influences user experience and therapeutic alliance in mental health interventions. MethodsWe will search PubMed, Web of Science, Embase, CINAHL, MEDLINE, The Cochrane Library, PsycINFO, and Scopus from inception to June 2025. Qualitative studies exploring user experiences of AI-driven mental health interventions will be included. The ECLIPSE framework will guide the review process. Two reviewers will independently screen studies, extract data, and assess methodological quality using the CASP Qualitative Checklist. Thematic synthesis will be used to analyze and integrate findings across studies. Confidence in the evidence will be assessed using GRADE-CERQual. DiscussionThis review will provide insights into the factors shaping user engagement and therapeutic alliance with AI-driven mental health interventions. Findings will inform the design and implementation of AI technologies that optimize user experience and clinical effectiveness. Strengths, limitations, and implications for research and practice will be discussed.