Strategies to improve treatment adherence of digital health applications—rapid review and mixed-method analysis
Bibliographic Data
| ID | 24020617 |
|---|---|
| Authors | Ulf Gerhardt (HNO-Praxis, corresponding author), Cordula Kreuzenbeck (IU International University of Applied Sciences, corresponding author) |
| Year | 2026 |
| Publication date | 2026-08-08 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | AI & Society (JOURNAL) |
| Journal identifiers | ISSN: 0951-5666 • E-ISSN: 1435-5655 |
| Publisher | Springer Nature (PUBLISHER • SG) |
| DOI | 10.1007/s00146-026-03264-7 |
| OpenAlex | W7201951536 |
| Language | EN |
| References cited | 64 |
Digital health applications (DHA) are digital medical devices that are used to support patients in the treatment of diseases. Therapy adherence is crucial for the success of therapy, but digital applications often result in high dropout rates. The work therefore pursues two central research questions: (1) quantification of DHA adherence and (2) identification of causes for dropout and development of improvement strategies. To answer these questions, a systematic literature analysis was carried out in which relevant studies between 2017 and 2025 were analyzed quantitatively and qualitatively. The quantitative results show that dropout rates show a high variance and are 60% in the pooled analysis. In the qualitative analysis, patient-immanent, application-immanent, social and technology-associated factors as well as political or structural conditions were identified as key factors influencing therapy adherence. The paper concludes with recommendations for action to improve adherence, for example through better user guidance, motivating elements and more individual adaptations of the applications. It contributes to the scientific discussion on the integration of DHA into the healthcare system.
Action (physics) · Digital health · Dropout (neural networks) · Health care · Identification (biology) · Key (lock) · Variance (accounting) · Work (physics) · Digital Mental Health Interventions · Medication Adherence and Compliance · Mobile Health and mHealth Applications
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| Citation velocity | historical |
|---|---|
| Highly cited | No |