A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression Among University Students: A Secondary Analysis of a Randomized Clinical Trial.

Key Points: Question: Can an individualized treatment rule identify patients who benefit as much or more from self-guided internet-delivered cognitive behavioral therapy (i-CBT) as from guided i-CBT? Findings: In this secondary analysis of a randomized clinical trial of 1319 university students with anxiety and/or depression, guided i-CBT optimized the probability of (1) joint remission of anxiety and depression for 91.7% of participants, (2) remission of anxiety for 100% of participants, and (3) remission of depression for 71.5% of participants. Self-guided i-CBT, in comparison, optimized the probability of remission of depression for the remaining 28.5% of participants. Meaning: Self-guided i-CBT is sometimes equally or more effective than guided i-CBT for depression but not anxiety. Importance: Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT. Objective: To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors. Design, Setting, and Participants: This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022. Interventions: Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435). Main Outcomes and Measures: Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline. Results: The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P =.003) or treatment as usual (40.0% [2.7%]; P =.001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P =.007; self-guided i-CBT: 25.4% [8.8%]; P =.004; treatment as usual: 31.0% [9.4%]; P =.001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P =.14; treatment as usual: 53.0% [6.0%]; P =.25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P =.001; treatment as usual: 41.8% [3.2%]; P <.001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P =.07). Conclusions and Relevance: Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings. Trial Registration: ClinicalTrials.gov Identifier: NCT04780542 This prespecified secondary analysis of a randomized clinical trial discusses the development of an individualized treatment rule using machine learning methods for guided vs self-guided internet-delivered cognitive behavioral therapy based on a rich set of baseline predictors. [ABSTRACT FROM AUTHOR]