Randomized Trial of a Generative AI Chatbot for Mental Health Treatment

BACKGROUND Generative artificial intelligence (Gen-AI) chatbots hold promise for building highly personalized, effective mental health treatments at scale, while also addressing user engagement and retention issues common among digital therapeutics. We present a randomized controlled trial (RCT) testing an expert–fine-tuned Gen-AI–powered chatbot, Therabot, for mental health treatment. METHODS We conducted a national, randomized controlled trial of adults (N=210) with clinically significant symptoms of major depressive disorder (MDD), generalized anxiety disorder (GAD), or at clinically high risk for feeding and eating disorders (CHR-FED). Participants were randomly assigned to a 4-week Therabot intervention (N=106) or waitlist control (WLC; N=104). WLC participants received no app access during the study period but gained access after its conclusion (8 weeks). Participants were stratified into one of three groups based on mental health screening results: those with clinically significant symptoms of MDD, GAD, or CHR-FED. Primary outcomes were symptom changes from baseline to postintervention (4 weeks) and to follow-up (8 weeks). Secondary outcomes included user engagement, acceptability, and therapeutic alliance (i.e., the collaborative patient and therapist relationship). Cumulative-link mixed models examined differential changes. Cohen’s d effect sizes were unbounded and calculated based on the log-odds ratio, representing differential change between groups.

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Source: Semantic Scholar - NEJM AI (123 citations) PDF: N/A Original Link: https://www.semanticscholar.org/paper/999e64cf92fe72297e2011f6285180d4bc30f4b5