Efficacy of prescription-eligible digital health applications for depression and generalized anxiety disorder in Germany: a systematic review and meta-analysis.

Authors

A Schmitz, S Frey, A Karimzadeh, A L Neves, A Mayr, B Weltermann

Published in

Scientific reports. Volume 16. Issue 1. Sep 11, 2026. Epub Sep 11, 2026.

Abstract

In Germany, prescription-eligible digital mental health applications (DiGA) were introduced in 2020 as promising interventions to address, among others, depression and anxiety disorders, two of the most prevalent mental health conditions worldwide. Despite growing interest in DiGAs, their overall efficacy remains uncertain. This study aimed to systematically evaluate and quantify the efficacy of prescription-eligible digital interventions for depression and generalized anxiety disorder by synthesizing evidence from randomized controlled trials (19 trials; total N = 4,078; pooled mean age = 38.7 years, SD = 12.1). Here we show that prescription-eligible digital applications for depression and generalized anxiety disorder reduce symptom severity compared with control conditions. For depression, effects were observed both immediately after the intervention (number of apps = 5; k = 17; SMD = - 0.49; 95% CI - 0.65 to - 0.32) and at follow-up (number of apps = 1; k = 4; SMD = - 0.35; 95% CI - 0.46 to - 0.29), while evidence for generalized anxiety disorder was limited due to a small number of available studies (number of studies = 2). These findings support the integration of evidence-based digital tools into mental health treatment strategies in Germany. However, the available evidence is currently dominated by a small number of applications, particularly Deprexis, and should therefore not be interpreted as equally representative of all DiGAs currently listed for depression in Germany. The findings also highlight methodological limitations of current research and underscore the need for real-world evaluations, which address not only efficacy but also the effectiveness, content, quality and implementation.

PMID:
42728340
Bibliographic data and abstract were imported from PubMed on 12 Sep 2026.

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