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 signifi-
cant 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 challeng