Depression and Anxiety Outcomes in a Technology-Enabled Psychotherapy Practice: Retrospective Cohort Study

Abstract

Background: Mental health conditions account for significant distress, burden, and societal costs. Despite efforts to implement evidence-based practices (EBPs), access to high-quality mental health treatment in general practice remains limited and clinical outcomes suboptimal. Measurement-based care (MBC) is a transtheoretical and transdiagnostic strategy that has the potential, when implemented effectively, to improve the quality of care. Digital tools can also support clinicians by alleviating administrative tasks and providing in-the-moment performance data and clinical decision support. Objective: This study aimed to examine patient retention in care and depression and anxiety outcomes in a technology-enabled psychotherapy practice where clinicians were supported by a suite of innovations, including an MBC platform and clinical decision support tools. Methods: This retrospective cohort study examined 2984 adults who initiated mental health treatment with Two Chairs, a hybrid technology–enabled behavioral health provider, from January 1 to June 30, 2024. Rates of reliable change, recovery, remission, deterioration, and the magnitude and trajectory of symptom change in depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder-7 (GAD-7). Results: The participants demonstrated high rates of retention in care (3183/3572, 89.1%) and MBC survey completion (3440/3572, 96.3%). From baseline to the 12th session, patients showed significant symptom improvements in depression and anxiety, achieving high rates of reliable improvement (65.8%, 95% CI 64.0%-67.5%) and recovery (53.2%, 95% CI 51.4%-55.0%), with 71.3% (95% CI 69.7%-72.9%) of patients achieving either outcome. Outcomes continued to improve up to the point of completion of the treatment episode (79.2%, 95% CI 77.5%-80.9%, of patients achieving improvement or recovery). Pre- to posttreatment effect sizes were large (all Cohen d>0.9). Conclusions: The results of this study show that technology-enabled MBC and clinical decision support systems (CDSSs) may support high-quality patient outcomes in mental health.