Digital Interventions for the Treatment of Depression: A Meta-Analytic Review

The high global prevalence of depression, together with the recent acceleration of remote care owing to the COVID-19 pandemic, has prompted increased interest in the efficacy of digital interventions for the treatment of depression. We provide a summary of the latest evidence base for digital interventions in the treatment of depression based on the largest study sample to date. A systematic literature search identified 83 studies (N = 15,530) that randomly allocated participants to a digital intervention for depression versus an active or inactive control condition. Overall heterogeneity was very high (I2 = 84%). Using a random-effects multilevel metaregression model, we found a significant medium overall effect size of digital interventions compared with all control conditions (g =.52). Subgroup analyses revealed significant differences between interventions and different control conditions (WLC: g =.70; attention: g =.36; TAU: g =.31), significantly higher effect sizes in interventions that involved human therapeutic guidance (g =.63) compared with self-help interventions (g =.34), and significantly lower effect sizes for effectiveness trials (g =.30) compared with efficacy trials (g =.59). We found no significant difference in outcomes between smartphone-based apps and computer and Internet-based interventions and no significant difference between human-guided digital interventions and face-to-face psychotherapy for depression, although the number of studies in both comparisons was low. Findings from the current meta-analysis provide evidence for the efficacy and effectiveness of digital interventions for the treatment of depression for a variety of populations. However, reported effect sizes may be exaggerated because of publication bias, and compliance with digital interventions outside of highly controlled settings remains a significant challenge.