Background: Mild to moderate depressive symptoms are common but often remain unrecognized and treated inadequately. We hypothesized that an Internet intervention in addition to usual care is superior to care as usual alone (CAU) in the treatment of mild to moderate depressive symptoms in adults. Methods: This trial was controlled, randomized and assessor-blinded. Participants with mild to moderate depressive symptoms (Patient Health Questionnaire, PHQ-9, score 5-14) were recruited from clinical and non-clinical settings and randomized to either CAU or a 12-week Internet intervention (Deprexis) adjunctive to usual care. Outcomes were assessed at baseline, 3 months (post-assessment) and 6 months (follow-up). The primary outcome measure was self-rated depression severity (PHQ-9). The main analysis was based on the intention-to-treat principle and used linear mixed models. Results: A total of 1,013 participants were randomized. Changes in PHQ-9 from baseline differed significantly between groups (t₈₂₅ = 6.12, p < 0.001 for the main effect of group). The post-assessment between-group effect size in favour of the intervention was d = 0.39 (95% CI: 0.13-0.64). It was stable at follow-up, with d = 0.32 (95% CI: 0.06-0.69). The rate of participants experiencing at least minimally clinically important PHQ-9 change at the post-assessment was higher in the intervention group (35.6 vs. 20.2%) with a number needed to treat of 7 (95% CI: 5-10). Conclusions: The Internet intervention examined in this trial was superior to CAU alone in reducing mild to moderate depressive symptoms. The magnitude of the effect is clinically important and has public health implications.

BackgroundWeb-based interventions for individuals with depressive disorders have been a recent focus of research and may be an effective adjunct to face-to-face psychotherapy or pharmacological treatment.ObjectiveThe aim of our study was to examine the early change patterns in Web-based interventions to identify differential effects.MethodsWe applied piecewise growth mixture modeling (PGMM) to identify different latent classes of early change in individuals with mild-to-moderate depression (n=409) who underwent a CBT-based web intervention for depression.ResultsOverall, three latent classes were identified (N=409): Two early response classes (n=158, n=185) and one early deterioration class (n=66). Latent classes differed in terms of outcome (P<.001) and adherence (P=.03) in regard to the number of modules (number of modules with a duration of at least 10 minutes) and the number of assessments (P<.001), but not in regard to the overall amount of time using the system. Class membership significantly improved outcome prediction by 24.8% over patient intake characteristics (P<.001) and significantly added to the prediction of adherence (P=.04).ConclusionsThese findings suggest that in Web-based interventions outcome and adherence can be predicted by patterns of early change, which can inform treatment decisions and potentially help optimize the allocation of scarce clinical resources.

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3.5.3 Patients' baseline characteristics as predictors of the patterns of change………………………………………………………….... 3.5.4 Patterns of change as predictors of treatment outcome at termination and follow-up……………………………….……… 4. Results………………………………………………………...…………… 4.1 Patterns of Change for Group and Individual Therapy………………….. 4.2 Patients' Characteristics within Each Pattern………………...………… 4.3 Patients' Baseline Characteristics as Predictors of the Patterns of Change………………………………………………………….……… 4.4 Patterns of Change as Predictors of Treatment Outcome at Termination and Follow-up…………………………………………………..……… 5. Discussion…………………………………….…………………………… 5.1 Limitations of the Study………………………………………………...

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