AI-Enabled Continuous Care Features in Real-World Psychotherapy: Treatment Engagement and Clinical Outcomes

ImportanceAI-enabled features may improve the effectiveness of routine mental health care, yet large-scale real-world evidence remains limited. ObjectiveTo evaluate whether access to AI-enabled continuous care features embedded within routine psychotherapy delivery is associated with improved treatment engagement and clinical outcomes under real-world conditions. DesignPreregistered cluster-level, matched, quasi-experimental study using a real-world rollout of AI-enabled continuous care features compared with psychotherapy alone (intention-to-treat framework). SettingAn employer-sponsored behavioral health program providing outpatient psychotherapy for employees and dependents. ParticipantsAdults initiating a new episode of psychotherapy from 25 employers with access to continuous care features and 75 matched employers without access. Treatment engagement was assessed over 7 weeks (n=26,208), and clinical outcomes were evaluated for up to 180 days (n=5,518). ExposureEmployer-level access to AI-enabled continuous care features supporting engagement and continuity before and between psychotherapy sessions, compared with psychotherapy alone. Main OutcomesEarly treatment engagement (number of psychotherapy sessions attended and time to second session) and changes in depressive and anxiety symptom severity measured using the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7). ResultsCompared with matched controls receiving psychotherapy alone, the intervention group attended 5% more psychotherapy sessions during the first 7 weeks (rate ratio, 1.05 [1.01, 1.10]) and completed their second session sooner (mean difference, -0.62 days [-1.05, -0.18]). Both groups demonstrated substantial symptom improvement over time; however, access to continuous care features was associated with additional improvement in depressive symptoms (d=0.16) and anxiety symptoms (d=0.15) at the median duration of care (day 44). These effects translated into clinically meaningful differences in reliable improvement by the median duration of care (NNT=25 for both outcomes). Conclusions and RelevanceIn this real-world evaluation, access to AI-enabled continuous care features embedded within routine psychotherapy delivery was associated with greater early engagement and a higher likelihood of reliable symptom improvement beyond psychotherapy alone. These findings suggest that augmenting routine psychotherapy with AI-enabled continuous care can meaningfully shift recovery trajectories during a standard treatment episode, strengthening early treatment momentum and improving outcomes at scale. Key PointsO_ST_ABSQuestionC_ST_ABSIs access to AI-enabled continuous care features embedded within routine psychotherapy delivery associated with improved treatment engagement and clinical outcomes under real-world conditions? FindingsIn this cluster-level, matched, quasi-experimental study of adults receiving psychotherapy within an employer-sponsored behavioral health program, access to AI-enabled continuous care features was associated with significantly greater early treatment engagement and faster improvement in depressive and anxiety symptoms compared with psychotherapy alone. MeaningAI-enabled support features may incrementally enhance the delivery and effectiveness of established psychotherapies when implemented as complements to routine care at scale.