Mobile health and privacy: cross sectional study
Abstract
Abstract Objectives To investigate whether and what user data are collected by health related mobile applications (mHealth apps), to characterise the privacy conduct of all the available mHealth apps on Google Play, and to gauge the associated risks to privacy. Design Cross sectional study Setting Health related apps developed for the Android mobile platform, available in the Google Play store in Australia and belonging to the medical and health and fitness categories. Participants Users of 20 991 mHealth apps (8074 medical and 12 917 health and fitness found in the Google Play store: in-depth analysis was done on 15 838 apps that did not require a download or subscription fee compared with 8468 baseline non-mHealth apps. Main outcome measures Primary outcomes were characterisation of the data collection operations in the apps code and of the data transmissions in the apps traffic; analysis of the primary recipients for each type of user data; presence of adverts and trackers in the app traffic; audit of the app privacy policy and compliance of the privacy conduct with the policy; and analysis of complaints in negative app reviews. Results 88.0% (n=18 472) of mHealth apps included code that could potentially collect user data. 3.9% (n=616) of apps transmitted user information in their traffic. Most data collection operations in apps code and data transmissions in apps traffic involved external service providers (third parties). The top 50 third parties were responsible for…
Read the paper
Related studies
- Challenges and opportunities with drug repurposing: finding strategies to find alternative uses of therapeutics
- Challenges in Chagas Disease Drug Development
- T Cell Specificity: A Great Challenge in Chagas Disease
- Benznidazole treatment leads to DNA damage in Trypanosoma cruzi and the persistence of rare widely dispersed non-replicative amastigotes in mice
- Rapid Molecular Detection of Terbinafine-resistant Dermatophytes
- Identifying novel drugs with new modes of action for neglected tropical fungal skin diseases (fungal skinNTDs) using an Open Source Drug discovery approach
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.