Evidence map›Paper›PMID 42395327›Full record

ArticleDigital health

Heterogeneity of information across seven curated national or international digital health app repositories.

Viet-Thi Tran, Philippe Ravaud, Marleen Kunneman, Victor M Montori, Ngan Thi Thuy Phi

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Viet-Thi TranCenter for Research in Epidemiology and StatisticS (CRESS), Université Paris Citéand Université Sorbonne Paris Nord, INSERM, INRAE, Paris, France.ORCID https://orcid.org/0000-0003-1863-6739
Philippe RavaudCenter for Research in Epidemiology and StatisticS (CRESS), Université Paris Citéand Université Sorbonne Paris Nord, INSERM, INRAE, Paris, France.
Marleen KunnemanDepartment of Public Health and Primary Care, Health Campus The Hague, Leiden University Medical Center, Leiden, The Netherlands.
Victor M MontoriKnowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA.
Ngan Thi Thuy PhiCenter for Research in Epidemiology and StatisticS (CRESS), Université Paris Citéand Université Sorbonne Paris Nord, INSERM, INRAE, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Digital health applications (health apps) are increasingly integrated in clinical care. Yet the information describing these apps varies across curated app repositories supporting prescription. We aimed to identify the information items used to describe health apps in repositories; and to quantify the completeness of publicly displayed app-entry information across repositories. Methods: We conducted a cross-sectional study of seven national or international curated health app repositories: mHealthBelgium, DiGA, AppThera, ORCHA, GGD AppStore, MIND, and AppGuide. In January 2025, we randomly selected 140 health apps, with 20 apps per repository. For each app, one reviewer extracted the publicly available information displayed in the repository entry and inductively identified the information items reported (i.e., atomic information elements used to describe apps). These information items were then grouped into categories by an expert committee. We calculated, for each repository, the median number of items reported across apps, overall and by category. Results: Health apps were described by 32 information items grouped into 10 categories: general information, regulatory information, compatibility, costs, indication, functions, evidence, user experience, data governance and security, and change history. The median number of items reported in repositories ranged from a median of 9/32 items, IQR 9 to 11 in MIND to 27/32, IQR 26 to 28 in DiGA. Only, three repositories (AppThera, DiGA and AppGuide) systematically reported information on the evidence supporting the apps for all listed apps. Conclusions: Curated health app repositories differed in the information items presented to clinicians and patients. Incomplete reporting of clinically relevant information, particularly evidence and data governance, may limit informed app selection and prescription. Minimum reporting standards are needed to enable safe prescription and reliable integration of health apps into clinical practice.

Indexed as

digitaldigital healthdiseasegeneralhealth communicationspublic healthquantitativestudies

Identifiers

PMID42395327
PMCPMC13323647

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.