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Background: Depression is a highly prevalent mental disorder, but only a fraction of those affected receive evidence-based treatments. Recently, Internet-based interventions were introduced as an efficacious and cost-effective approach. However, even though depression is a heterogenous construct, effects of treatments have mostly been determined using aggregated symptom scores. This carries the risk of concealing important effects and working mechanisms of those treatments. Methods: In this study, we analyze outcome and long-term follow-up data from the EVIDENT study, a large (N = 1,013) randomized-controlled trial comparing an Internet intervention for depression (Deprexis) with care as usual. We use Network Intervention Analysis to examine the symptom-specific effects of the intervention. Using data from intermediary and long-term assessments that have been conducted over 36 months, we intend to reveal how the treatment effects unfold sequentially and are maintained. Results: Item-level analysis showed that scale-level effects can be explained by small item-level effects on most depressive symptoms at all points of assessment. Higher scores on these items at baseline predicted overall symptom reduction throughout the whole assessment period. Network intervention analysis offered insights into potential working mechanisms: while deprexis directly affected certain symptoms of depression (e.g., worthlessness and fatigue) and certain aspects of the quality of life (e.g., overall impairment through emotional problems), other domains were affected indirectly (e.g., depressed mood and concentration as well as activity level). The configuration of direct and indirect effects replicates previous findings from another study examining the same intervention. Conclusions: Internet interventions for depression are not only effective in the short term, but also exert long-term effects. Their effects are likely to affect only a small subset of problems. Patients reporting these problems are likely to benefit more from the intervention. Future studies on online interventions should examine symptom-specific effects as they potentially reveal the potential of treatment tailoring. Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT02178631.
RESUMO
OBJECTIVE: To explore the moderating effects of sociodemographic variables on treatment benefits received from participating in an internet intervention for depression. DESIGN: Randomised, assessor-blind, controlled trial. SETTING: Online intervention, with participant recruitment using multiple settings, including inpatient and outpatient medical and psychological clinics, depression online forums, health insurance companies and the media (eg, newspaper, radio). PARTICIPANTS: The EVIDENT trial included 1013 participants with mild to moderate depressive symptoms. INTERVENTIONS: The intervention group subjects (n=509) received an online intervention (Deprexis) in addition to care as usual (CAU), while 504 participants received CAU alone. METHODS: To explore subgroup differences, moderating effects were investigated using linear regression models based on intention-to-treat analyses. Moderating effects included sex, age, educational attainment, employment status, relationship status and lifetime frequency of episodes. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary endpoint was change in self-rated depression severity measured by the Patient Health Questionnaire-9 (PHQ-9), comparing baseline versus 12-week post-test assessment. Secondary outcome measures were the Hamilton Rating Scale for Depression and the Quick Inventory of Depressive Symptoms each at 12 weeks and at 6 and 12 months, and PHQ-9 at 6 and 12 months, respectively. In this article, we focus on the primary outcome measure only. RESULTS: Between-group differences were observed in post-test scores, indicating the effectiveness of Deprexis. While the effects of the intervention could be demonstrated across all subgroups, some showed larger between-group differences than others. However, after exploring the moderating effects based on linear regression models, none of the selected variables was found to be moderating treatment outcomes. CONCLUSIONS: Our findings suggest that Deprexis is equally beneficial to a wide range of people; that is, participant characteristics were not associated with treatment benefits. Therefore, participant recruitment into web-based psychotherapeutic interventions should be broad, while special attention may be paid to those currently under-represented in these interventions. TRIAL REGISTRATION NUMBER: NCT01636752.
