Digital Health Applications (DiGA) for Treating Depression and Generalized Anxiety Disorder: Protocol for a Systematic Health App Review and Systematic Review of Published Evidence.
Annika Schmitz, Lucas Kueppers, Jacob Klein, Silke Frey, Arian Karimzadeh, Ana Luísa Neves, Birgitta Weltermann
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引用次数: 0
Abstract
Background: Depression and generalized anxiety disorder (GAD) are widespread mental health diseases with significant individual and societal consequences. Psychotherapy, particularly cognitive behavioral therapy (CBT), is a common treatment approach, but its application is limited due to costs and staff shortages. Germany has been the first country to integrate and reimburse digital health applications (DiGAs) as an easily accessible treatment option since 2020. Despite regulatory processes, skepticism among physicians regarding clinical relevance and evidence persists.
Objective: This protocol aims to describe the methodology of the planned systematic review. Using expert ratings, the app review will assess the guideline conformity, functions, and usability of German DiGAs for depression and GAD listed at the Federal Institute for Drugs and Medical Devices (BfArM). The additional systematic review will synthesize the effectiveness and quality of these DiGAs based on randomized controlled trials.
Methods: The study protocol follows the 2015 PRISMA (Preferred Reporting Items for Systematic Reviews) guideline and was registered in the international Prospective Register of Systematic Reviews (PROSPERO). The review consists of 2 parts: (1) a systematic health app review of DiGAs addressing depression or GAD and (2) a systematic review of published evidence on these DiGAs. The systematic health app review comprises a summary of the DiGA features including the Institute for Healthcare Informatics (IMS) App Functionality Scoring System, a guideline conformity check, and the Mobile Application Rating Scale (MARS) assessment. The systematic review of published evidence is based on a systematic literature search in electronic databases (MEDLINE via PubMed, Cochrane Central Register of Controlled Trials [CENTRAL], Web of Science), as well as relevant websites. The approach includes an effectiveness evaluation, a risk of bias assessment using the Cochrane tool, Risk of Bias 2 (RoB2), and an overall quality evaluation using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) method.
Results: The systematic literature search was conducted in July 2024 and August 2024, and an updated search is planned for November 2025. Data extraction, narrative synthesis, and evaluation of DiGA and corresponding studies are expected to be completed in spring 2026. The results will be presented using a PRISMA flow diagram and tables to display general information, risk of bias, and overall quality.
Conclusions: The review will influence both the actual use and future developments of DiGAs. Good quality characteristics will enhance transparency and trust among physicians, while quality deficits provide options for improvement by manufacturers and governing institutions. Consequently, patients' care with DiGAs may improve.
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