Background: With an increasing number of digital health apps available in app stores, it is important to assess these technologies reliably regarding their quality. This is done to mitigate the risks associated with their use. There are many different guidelines, methods, and metrics available to assess digital health apps with regard to their quality.
Objective: This study aimed to give a holistic summary of the current methods and "condition agnostic" frameworks that are broadly applicable for the quality assessment of all digital health apps.
Methods: A systematic search of literature was conducted on 4 databases: Scopus, PubMed, ACM Digital Library, and IEEE Xplore. We followed the PICOS (Population, Patient, or Problem; Intervention; Comparison; Outcomes; and Study Design) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodologies when conducting this umbrella review. The search was conducted on January 26, 2024, for review articles published between 2018 and 2023. We identified 4781 candidate papers for inclusion; after title and abstract screening, 39 remained. After full-text analysis, we included 15 review articles in the full review.
Results: Of the 15 review articles, scoping reviews were the most common (n=6, 40%), followed by systematic reviews (n=4, 27%), narrative reviews (n=4, 27%), and a rapid review (n=1, 7%). A total of 4 (27%) review articles proposed assessment criteria for digital health apps. "Data privacy and/or security" was the most mentioned criterion (n=13, 87%) and "Cost" was the least mentioned criterion (n=1, 7%) for the assessment of digital health apps. The Mobile App Rating Scale was the most frequently used framework for quality assessment of digital health apps.
Conclusions: There is a lack of unity or consolidation across identified frameworks, as most do not meet all the identified criteria from the reviewed articles. Safety concerns associated with the use of digital health apps may be mitigated with the use of quality frameworks.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11502990 | PMC |
| http://dx.doi.org/10.2196/58616 | DOI Listing |
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