Stud Health Technol Inform. 2026 May 7;335:53-54. doi: 10.3233/SHTI260054.
ABSTRACT
While health technology assessment (HTA) aims to quantify the quality of digital health apps, app stores offer unstructured information on app quality to users like patients. This provides barriers for people with Parkinson’s disease (PD) and Alzheimer’s disease (AD) to identify high-quality apps. This study explores the discoverability of AD/PD-related apps and their quality information in app stores. We applied descriptive statistics and text mining such as large language models (LLMs) and topic modelling to analyze app descriptions and user reviews of 1237 apps. Only ∼2% of apps were discoverable as holding a CE-mark. Most apps were “Care Support”, followed by “Health & Wellness” and “Patient Monitoring” patient-facing categories. User reviews addressed “user experience”, “health improvement”, and “costs”. To help patients identify high-quality apps, quality information should be presented in a structured and trustworthy way. The use of user feedback for patient-reported measures should be explored in future work.
PMID:42119090 | DOI:10.3233/SHTI260054
