App Stores Overflow With Parkinson’s and Dementia Apps, but Only a Fraction Claim Medical Certification

The digital storefronts on our phones have quietly become one of the largest distribution channels for health technology in the world. A search for apps related to Parkinson’s disease or Alzheimer’s disease returns hundreds of results promising symptom tracking, cognitive training, medication reminders, and caregiver support. Yet a new analysis published in PLOS Digital Health suggests that the information patients rely on to judge these apps is fragmented, largely unregulated, and often far removed from the standards that clinicians and health technology assessors would use to define quality. The study, led by Isabel Schwaninger and colleagues, examined more than a thousand apps marketed for these two neurodegenerative conditions and found that only around two percent claimed to be certified medical devices.

The research team set out to answer a deceptively simple question: what can a patient actually learn about an app’s quality from the information available in the Apple App Store and Google Play Store? For most people, the answer to whether an app is trustworthy comes down to two sources. The first is the manufacturer’s own description and metadata, the text, categories, and technical details that developers supply when they publish an app. The second is the stream of user reviews and star ratings left by previous downloaders. Both sources are unstructured, meaning they were never designed to communicate clinical quality, and both are shaped by incentives that have little to do with evidence-based medicine.

To map this landscape systematically, the researchers collected data from both major app stores as of May 2024. Their initial search identified 1,237 apps related to Alzheimer’s disease or Parkinson’s disease, which after removing 50 duplicates yielded a final dataset of 1,187 unique applications. Analyzing a corpus of this size required more than manual reading. The team combined descriptive statistics with qualitative content analysis, employed large language model-supported exploratory classification to sort apps into functional categories, and applied topic modeling to detect recurring themes across thousands of app descriptions and user reviews. This mixed-methods design allowed them to quantify broad patterns while still capturing the nuances of how apps describe themselves and how users respond to them.

The headline finding is stark. In a market saturated with applications aimed at some of the most vulnerable patients in medicine, only about two percent claimed any certification as a medical device. Medical device certification, whether under European Union regulations or the United States Food and Drug Administration’s framework, signals that a product has undergone formal assessment of its safety and performance. From the standpoint of health technology assessment, the discipline that evaluates whether medical interventions deliver value, quality rests on three pillars: evidence-based medicine, safety, and user-centeredness. By that standard, the overwhelming majority of apps in this space exist outside the traditional machinery of clinical evaluation, leaving patients to navigate on their own.

Genre classification within the app stores offered another revealing lens. On the Apple App Store, 24 percent of the analyzed apps were listed in the Medical genre, while on Google Play the figure was 14 percent. Within that Medical genre, the researchers found that 63 percent of Apple apps and 54 percent of Google apps were patient-facing, meaning they were designed to be used directly by people living with the conditions rather than by clinicians. That so few apps overall sit in the Medical category, and that even within it many are not oriented toward patients, underscores how difficult it is for a layperson to distinguish a clinically grounded tool from a general wellness product with a neurological theme.

Among the patient-facing apps, the team’s manual categorization revealed a clear hierarchy of purpose. The dominant category was Care Support, followed by Health & Wellness and then Patient Monitoring. This distribution tells a story about what the market actually supplies. Apps that help patients organize care, coordinate with family members, and manage daily routines outnumber apps that monitor symptoms with clinical precision or deliver therapeutic interventions. While care support is genuinely valuable to families coping with progressive neurodegenerative disease, the imbalance suggests that the app ecosystem has grown around convenience and communication rather than around measurable health outcomes, the currency of formal medical evaluation.

The second half of the study turned to user reviews, and here the findings become more provocative. The researchers found that user feedback, despite being anecdotal and unstructured, contains exploratory information that resembles patient-reported outcomes and patient experience measures, both of which are increasingly prized in modern health care evaluation. Topic modeling of the reviews surfaced recurring themes of user experience, health improvement, and costs. When a reviewer writes that a medication reminder app helped them stay on schedule for a month, or that a cognitive training program produced noticeable changes, they are generating a form of real-world evidence, albeit one contaminated by selection bias, fake reviews, and the fact that people who stop using an app rarely leave detailed explanations.

This dual perspective, manufacturer metadata on one side and user opinion on the other, frames the study’s central argument. The information needed to judge the quality of digital health technologies does exist in app stores, embedded in descriptions, category assignments, certification claims, and the collective voice of reviewers. But it is not trustworthy enough, not standardized, and not accessible enough for patients to act on. A developer can write almost anything in an app description, and the store genre labels are self-selected rather than verified. Meanwhile, the genuinely useful signals buried in reviews, the reports of improvement, frustration, or harm, are mixed with noise and never aggregated in a way that supports decision-making.

The implications reach beyond Parkinson’s and Alzheimer’s disease to the entire digital health ecosystem. Regulators in Europe and the United States have struggled for years to define when a wellness app becomes a medical device, and enforcement has lagged far behind market growth. The authors argue that app store metadata should be improved in trustworthiness and made more accessible to users, so that the public can find high-quality health apps rather than simply the most heavily marketed ones. They also call for user opinions to be explored as complementary value-generating indicators in future work, a suggestion that would effectively formalize what patients already do informally: crowdsource their own quality assessments.

For the millions of people living with or caring for someone with a neurodegenerative disease, the practical takeaway is cautionary but not despairing. The app stores are not empty of value; they are full of it, but the signals are buried. Certification claims, when they appear, remain the strongest proxy for formal quality, and they are vanishingly rare. Genre labels and descriptions provide weak guidance, and reviews offer texture but not proof. Until app stores, regulators, and developers align the metadata that shapes patient choices with the standards of evidence-based medicine, the burden of distinguishing a genuinely helpful digital tool from a well-marketed one will continue to fall on the very patients least equipped to carry it. This study provides the first systematic, dual-perspective map of that burden, and a data-driven case for rebuilding the information layer of digital health commerce around quality rather than marketing.

Subject of Research: Quality assessment of Parkinson's disease and dementia apps using app store metadata and user reviews

Article Title: Value in app store metadata and user reviews: A dual perspective on quality of Parkinson’s and dementia apps

Article References: Schwaninger, I., Ighanian, P., Borga, L., Giraitis, M., Hoogendoorn, P., & Klucken, J. (2026). Value in app store metadata and user reviews: A dual perspective on quality of Parkinson’s and dementia apps. PLOS Digital Health, 5(10), e0001730. https://doi.org/10.1371/journal.pdig.0001730

Image Credits: AI Generated

DOI: 10.1371/journal.pdig.0001730

Keywords: Parkinson's disease, Alzheimer's disease, mobile health apps, app stores, medical device certification, health technology assessment, user reviews, patient-reported outcomes, digital health technologies, topic modeling, large language models, app metadata