{ "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. Author summary: People living with Alzheimer’s disease and Parkinson’s disease increasingly turn to mobile health apps to support their daily care and well-being. However, finding trustworthy, high-quality apps remains difficult, as app stores provide large amounts of information that are not always easy to interpret. In this study, we explored what information patients can access in app stores and whether it can help identify signals of value in health applications. We analyzed nearly 1,200 apps from Apple App Store and Google Play Store. We used artificial intelligence-assisted text analysis of app descriptions and user reviews to identify common themes, including patterns across different star ratings. We found that only about 2% of apps are certified medical devices, and many are not categorized as medical apps. Most patient-facing apps focus on care support, health and wellness, or patient monitoring. User reviews revealed exploratory insights into patient experiences, including usability, perceived health benefits, and costs. These findings suggest that app store information, particularly user feedback, contains potentially useful but currently underused signals about app quality. Making this information more accessible and easier to interpret could help patients and caregivers make better-informed decisions when choosing digital health tools.", "abstract_shown": true, "affiliations": [ "Digital Medicine, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg", "Centre Hospitalier de Luxembourg (CHL), Strassen, Luxembourg", "National eHealth Living Lab, Public Health and Primary Care Department, Leiden University Medical Center, Leiden, Netherlands" ], "article_type": "Research Article", "arxiv": null, "author_total": 6, "authors": [ { "affs": [ 0 ], "name": "Isabel Schwaninger" }, { "affs": [ 1 ], "name": "Paria Ighanian" }, { "affs": [ 2 ], "name": "Liyousew Borga" }, { "name": "Marijus Giraitis" }, { "name": "Petra Hoogendoorn" }, { "name": "Jochen Klucken" } ], "bibtex": "https://research.draconitic.com/paper/3gs72c5scc18g.bib", "cited_by": 0, "doi": "10.1371/journal.pdig.0001730", "fulltext_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001730", "id": "3gs72c5scc18g", "issns": [ "2767-3170" ], "landing_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001730", "language": null, "licence": "CC-BY-4.0", "licence_label": "CC BY 4.0", "licence_source": "journal", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "openalex", "3600|Mobile Health and mHealth Applications" ], [ "plos", "/Biology and life sciences/Bioengineering/Biotechnology/Medical devices and equipment" ], [ "plos", "/Biology and life sciences/Neuroscience/Cognitive science/Cognitive psychology/Language" ], [ "plos", "/Biology and life sciences/Psychology/Cognitive psychology/Language" ], [ "plos", "/Computer and information sciences/Data management/Metadata" ], [ "plos", "/Computer and information sciences/Information technology/Text mining" ], [ "plos", "/Engineering and technology/Bioengineering/Biotechnology/Medical devices and equipment" ], [ "plos", "/Medicine and health sciences/Diagnostic medicine" ], [ "plos", "/Medicine and health sciences/Medical conditions/Neurodegenerative diseases/Alzheimer's disease" ], [ "plos", "/Medicine and health sciences/Medical conditions/Neurodegenerative diseases/Movement disorders/Parkinson disease" ], [ "plos", "/Medicine and health sciences/Medical devices and equipment" ], [ "plos", "/Medicine and health sciences/Mental health and psychiatry/Dementia/Alzheimer's disease" ], [ "plos", "/Medicine and health sciences/Neurology/Dementia/Alzheimer's disease" ], [ "plos", "/Medicine and health sciences/Neurology/Neurodegenerative diseases/Alzheimer's disease" ], [ "plos", "/Medicine and health sciences/Neurology/Neurodegenerative diseases/Movement disorders/Parkinson disease" ], [ "plos", "/Social sciences/Linguistics/Semantics" ], [ "plos", "/Social sciences/Psychology/Cognitive psychology/Language" ] ], "openalex": "W7215108091", "pdf_url": "https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0001730&type=printable", "pmcid": null, "pmid": null, "published": "2026-10-01", "publisher": "Public Library of Science", "ris": "https://research.draconitic.com/paper/3gs72c5scc18g.ris", "sources": [ { "first_seen": "2026-10-30T12:17:37Z", "native_id": "10.1371/journal.pdig.0001730", "source": "plos", "url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001730" } ], "subjects": [ { "field": "biology", "origin": "plos:biotechnology", "subfield": "systems-synthetic" }, { "field": "medicine", "origin": "plos:neurology", "subfield": "neurology" } ], "title": "Value in app store metadata and user reviews: A dual perspective on quality of Parkinson’s and dementia apps", "title_text": "Value in app store metadata and user reviews: A dual perspective on quality of Parkinson’s and dementia apps", "type": "peer-reviewed", "updated_at": "2026-10-30T12:17:37Z", "url": "https://research.draconitic.com/paper/3gs72c5scc18g", "venue": "PLOS Digital Health", "versions": [] }