Evidence map›Paper›PMID 42821639›Full record

ArticlePLOS digital health2026

Value in app store metadata and user reviews: A dual perspective on quality of Parkinson's and dementia apps.

Isabel Schwaninger, Paria Ighanian, Liyousew Borga, Marijus Giraitis, Petra Hoogendoorn, Jochen Klucken

Abstract read
In one paragraph

Article in PLOS digital health, 2026. 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

6 authors.

Isabel SchwaningerDigital Medicine, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.ORCID https://orcid.org/0000-0002-8794-8464
Paria IghanianDigital Medicine, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Liyousew BorgaDigital Medicine, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Marijus GiraitisDigital Medicine, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Petra HoogendoornNational eHealth Living Lab, Public Health and Primary Care Department, Leiden University Medical Center, Leiden, Netherlands.
Jochen KluckenDigital Medicine, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

App stores provide a range of health applications for people living with Alzheimer's disease (AD) and Parkinson's disease (PD). Users like patients can access information from both manufacturer-provided app descriptions and metadata, as well as from user reviews. However, navigating this information to identify value-generating apps of high quality remains challenging. From a health technology assessment (HTA) standpoint, quality is defined by evidence-based medicine, safety, and user-centeredness. To explore the potential value of app store information available to patients, we conducted a descriptive, mixed-methods analysis of unstructured app metadata and user feedback from the Apple App Store and Google Play Store (as of May 2024). We analyzed 1,237 AD/PD-related apps which included 50 duplicates (resulting in 1,187 apps), utilizing descriptive statistics, content analysis, large language model-supported exploratory classification, and a topic modeling approach. In total, only about 2% of the apps claimed to be certified medical devices. Moreover, 24% of Apple apps and 14% of Google apps were in the "Medical" app store genre, among which we found that 63% of Apple and 54% of Google apps were patient-facing. We manually categorized patient-facing apps predominantly under "Care Support," followed by "Health & Wellness" and "Patient Monitoring." Importantly, user feedback provided exploratory, potentially valuable patient-reported outcome and experience information but is derived from personal opinions on "user experience," "health improvement," and "costs." As quality information on DHTs could be identified in unstructured app metadata, this information should be improved in trustworthiness and more accessible to users like patients, supporting the public to find high-quality health apps. Furthermore, as user opinions contained information with potential value for patients, these should be explored as complementary value-generating indicators of health apps in future work.

Identifiers

PMID42821639
PMCPMC13630307

What OpenQuestion holds

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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.