Obsessive Compulsive and Related Disorders
Remote cognitive-behavioral therapy for obsessive-compulsive symptoms in adults: A meta-analysis
Emily A. Mueller, M.A.
Doctoral Student
Bowling Green State University
Bowling Green, Ohio, United States
Sam Chung Xiann Lim, M.A.
Graduate student
Bowling Green State University
Bowling Green, Ohio, United States
Cognitive behavioral therapy (CBT) with Exposure and Response Prevention (ERP) is the front-line behavioral treatment for Obsessive Compulsive Disorder (OCD). Remote CBT can reduce potential barriers to treatment, including high cost, a sparse number of specialized providers, and the significant time commitment of traditional face-to-face CBT. The efficacy of remote CBT for OCD has been evaluated over the last three decades and has proved to be a promising treatment for individuals with OCD who cannot access in-person specialized care. However, there are still some gaps in our understanding of what factors contribute to favorable treatment outcomes and low attrition. The current meta-analysis incorporates studies from the last decade looking at the efficacy of remote CBT interventions for OCD that have not yet been incorporated into an updated meta-analysis. Therefore, the aims of the current study were to 1) provide an updated evaluation of the efficacy of remote CBT for the treatment of OCD in adults, and 2) to explore characteristics that influence the effect sizes of different types of remote CBT treatments, including correlated variables such as therapist training, client characteristics, and dropout rates. After an exhaustive search, 37 studies met criteria and were included in the meta-analysis. Using a random-effects model, a within-group analysis revealed that remote treatment for OCD conferred a large decrease in OCD symptoms (g = 1.06; 95% CI: 0.74-1.41, p < .001) which is consistent with the most recent meta-analyses on the topic. Ongoing analyses will examine between-group differences in effect size as well as potential moderators of treatment effect and dropout rates. These results, as well as their implications, will be discussed during this presentation.