The Efficacy and Attrition Risk of Video-Based Versus In-Person Psychotherapy for Depression: A Meta-Analysis of Randomized Controlled Trials

Abstract

Background: One contributing factor to the societal burden of depression involves a mismatch between treatment need and its availability, and advances in the delivery of telehealth services represent a promising development for addressing coverage gaps in mental health interventions. There have been questions about the degree to which delivery via videoconferencing could match the effectiveness of in-person services, and there is now a sufficiently large literature comparing psychotherapy for depression to address this question meta-analytically. Methods: The Pubmed, PSYCinfo, and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched for articles from January 1, 2000 to May 1, 2020. A random-effects meta-analysis was conducted to evaluate potential differences in efficacy rates between the videoconferencing and in-person delivery of psychotherapy in reducing depressive symptoms. Odds ratios were calculated and meta-analyzed to examine any differences in attrition rates between video and in-person conditions. Subgroup analyses based on primary mental health outcome focus of the study (depression or other) were conducted using a mixed effects model. Results: Primary study analyses yielded no evidence that video-based psychotherapy is less efficacious than in-person psychotherapy for reducing depressive symptoms. Additionally, there was no evidence that attrition rates significantly differed between the two conditions. No significant subgroup differences in either efficacy or attrition were observed. Conclusion: The present findings suggest that video-based psychotherapy may be a feasible and effective alternative delivery modality to in-person services for reducing depressive symptoms. Continued research on the effectiveness of telehealth in clinically depressed samples and the barriers of each delivery modality can help the field better determine which patients benefit most from each type of service going forward.