Adherence and Dropout Predictors in Telehealth Cognitive Behavioral Therapy for Depression: A Multi-Platform 12-Week Cohort Study

This study investigates predictors of session adherence and dropout in telehealth-delivered CBT for major depressive disorder across three delivery platform types within the context of digital psychiatry and implementation science, an area of growing scientific importance given its implications for telehealth mental health program design, platform selection for diverse populations, and targeted dropout prevention. Using prospective cohort study tracking session completion, PHQ-9 scores, and platform engagement metrics over a 12-week CBT protocol with logistic regression dropout prediction, we examine platform usability, videoconference therapeutic alliance quality, and socioeconomic technology barriers mediating adherence to digital mental health treatment in 824 adults (mean age 38.2 years, 64% female) enrolled in telehealth CBT across 3 platforms over 18 months drawn from primary care practices with integrated behavioral health in three metropolitan health systems. Results indicate that overall CBT completion was 62.4% with significantly higher completion on blended platforms (74.2%) versus asynchronous-only (51.4%); PHQ-9 improvement was 8.4 points in completers versus 3.2 points in dropouts (p < 0.001), with 62.4% overall completion, 74.2% in blended delivery as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to digital psychiatry and implementation science and carry actionable implications for the design of programs and policies targeting telehealth mental health program design, platform selection for diverse populations, and targeted dropout prevention.