Evaluating Therabot: A Randomized Control Trial Investigating the Feasibility and Effectiveness of a Generative AI Therapy Chatbot for Depression, Anxiety, and Eating Disorder Symptom Treatment

Abstract

Background:Chatbots powered by generative AI (Gen-AI) hold promise for building highly personalized, effective mental health treatments at scale, while also addressing existing user engagement and retention issues common among digital therapeutics. We present the first RCT testing an expert-fine-tuned Gen-AI-powered chatbot, Therabot, for mental health treatment. Methods: Participants (N=210) were randomized to a four-week Therabot intervention (N=106) or waitlist control (WLC; N=104). Subjects were clinically stratified into major depressive disorder (MDD), generalized anxiety disorder (GAD), or clinically high risk feeding and eating disorder (CHR-FED) groups using baseline symptom severity. Primary outcomes included disorder-specific symptom changes from baseline to four and eight weeks. Secondary outcomes included user engagement, acceptability, and therapeutic alliance. Cumulative link mixed models examined differential changes pre- to post-intervention and from pre-intervention to follow-up, between the Therabot and WLC groups. Results: The Therabot group showed large and significantly greater reductions in MDD (d = 0.845-0.903), GAD (d = 0.794-0.840), and CHR-FED (d = 0.627-0.819) symptoms relative to controls at post-intervention and follow-up. Therabot was well received and well-utilized (average use >6 hours), and participants rated the therapeutic alliance comparable to human therapists. Conclusions: This is the first RCT demonstrating the effectiveness of a fully…