ABSTRACT
Introduction
Internet-based cognitive behavioral therapy (iCBT) could help bridge the gap in treatment provision for mental disorders. iCBT is efficacious for the treatment of anxiety and depression in RCTs. However, more research is needed to translate findings from controlled trials to natural clinical settings. Additionally, more research is needed on predictors for treatment outcome in iCBT to guide allocation of treatment resources.
Method
Data originated from a routine care guided iCBT clinic and covered 1475 adults treated for either mild-moderate depression (n = 719), panic disorder (n = 376), social phobia (n = 276), or specific phobia (n = 104). Joint models were used to examine treatment effects and predictors. Effect estimates were supported by effect sizes (Cohen’s d) and calculations of the reliable change index (RCI).
Results
All four treatments showed significant reductions on their primary outcome measure at each assessment point, according to the joint models (depression, PHQ-9: −1.35, 95% CI: −1.44; −1.27; panic disorder, PDSS-SR: −0.96, 95% CI: −1.04; −0.88; social phobia, SIAS: −0.96, 95% CI: −1.25; −0.67; specific phobia, FQ Main Phobia: −0.25, 95% CI: −0.33; −0.16), and effect sizes were moderate to large from baseline to the last observation (depression, d = 0.87; panic disorder, d = 0.62; social phobia, d = 0.80; specific phobia, d = 0.47). In total, 26.7% of patients improved according to RCI, and 27.0% recovered at last observation. Higher baseline symptom severity was significantly associated with the extent of improvement for all programs. Similarly, baseline comorbid severity was associated with faster improvements on primary symptoms for depression and panic disorder. Lower age, being in a relationship, and studying increased the rate of improvement for panic disorder.
Conclusion
iCBT treatments for depression, panic disorder and social phobia were effective. For specific phobia, effects were smaller but still significant. Future studies should investigate process variables, theoretically relevant predictors or full prediction models to enable impactful predictions.