Internet and Computer-Based Cognitive Behavioral Therapy for Anxiety and Depression in Adolescents and Young Adults: Systematic Review and Meta-Analysis

Digital Interventions for People With Co-Occurring Depression and Problematic Alcohol Use: A Systematic Review and Meta-Analysis

Aims

This systematic review and meta-analysis assessed the effectiveness of digital interventions addressing depressive symptoms and alcohol use simultaneously among people with co-occurring depression and problematic alcohol use.

Methods

Seven databases were searched for trials evaluating digital interventions aimed at depression and alcohol use. Random-effects meta-analyses were conducted to pool effects on depressive symptoms and alcohol use up to 3-month and 6-month follow-up. Overall quality for every outcome was assessed with GRADE (Grading of Recommendations Assessment, Development and Evaluation).

Results

The pooled effect of digital interventions compared to their comparators was in favour of digital interventions. Small but significant effects on depressive symptoms at 3-month follow-up were found (g = 0.34, 95% confidence interval (CI): 0.06–0.62, P = 0.02, k = 6) and non-significant effects at 6-month follow-up (g = 0.29, 95% CI: −0.16 to 0.73, P = 0.15, k = 5). For alcohol use, the pooled effect of digital interventions was small and non-significant at 3-month follow-up (g = 0.14, 95% CI: −0.02 to 0.30, P = 0.07, k = 6) and significant at 6-month follow-up (g = 0.14, 95% CI: 0.07–0.20, P = 0.005, k = 5). Sensitivity analysis indicated the latter finding to be sensitive to statistical estimator choice. Quality of evidence was moderate, except for depressive symptoms at 6-month follow-up for which it was low.

Conclusion

Based on the literature, digital interventions are effective in reducing depressive symptoms at 3-month follow-up and alcohol use at 6-month follow-up among people with comorbid depression and problematic alcohol use. More high-quality trials are needed to confirm the current findings.

Maintaining Outcomes of Internet-Delivered Cognitive-Behavioral Therapy for Depression: A Network Analysis of Follow-Up Effects

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.