Investigating the Cross-app Data Sharing Implications of Using Android Health Connect

Mobile health and fitness (mHealth) apps are widely used, and they process sensitive user data. To improve the interoperability among them and enable fine-grained permission controls for users, Google strategically introduced an on-device centralized mHealth data sharing platform, Android Health Connect (AHC), in 2022. However, we argue that the current AHC design may exacerbate privacy risks because it enables broad but implicit mHealth data sharing across apps. In this article, we first conduct a cross-app data sharing study on 41 AHC-compatible apps; by analyzing their declared AHC-related permissions and privacy practice disclosures, we reveal that they can broadly and intensively share different types of mHealth data with each other but do not adequately disclose AHC-related practices. We further conduct an online user study for 105 participants to interact with our simulated AHC permission management interfaces for two apps; by quantitatively and qualitatively analyzing participants’ interactions and their responses to the follow-up questions, we demonstrate that most participants have a flawed understanding of AHC’s permission model and its implicit cross-app data sharing implications. Our findings highlight the pressing need to improve the design of this new and pivotal AHC platform to better protect mHealth app users’ privacy.

Authors

Institutions

Publication Details

Journal
ACM Transactions on Computing for Healthcare
Published
2026-07-23
DOI
https://doi.org/10.1145/3831593
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating the Cross-app Data Sharing Implications of Using Android Health Connect

Anhao Xiang, Weiping Pei, Chuan Yue, Madelyn Swelstad et al.
ACM Transactions on Computing for Healthcare
Mobile Health and mHealth Applications
article

Investigating the Cross-app Data Sharing Implications of Using Android Health Connect

Anhao Xiang, Weiping Pei, Chuan Yue, Madelyn Swelstad, Andrew Plute
article en

Abstract

Mobile health and fitness (mHealth) apps are widely used, and they process sensitive user data. To improve the interoperability among them and enable fine-grained permission controls for users, Google strategically introduced an on-device centralized mHealth data sharing platform, Android Health Connect (AHC), in 2022. However, we argue that the current AHC design may exacerbate privacy risks because it enables broad but implicit mHealth data sharing across apps. In this article, we first conduct a cross-app data sharing study on 41 AHC-compatible apps; by analyzing their declared AHC-related permissions and privacy practice disclosures, we reveal that they can broadly and intensively share different types of mHealth data with each other but do not adequately disclose AHC-related practices. We further conduct an online user study for 105 participants to interact with our simulated AHC permission management interfaces for two apps; by quantitatively and qualitatively analyzing participants’ interactions and their responses to the follow-up questions, we demonstrate that most participants have a flawed understanding of AHC’s permission model and its implicit cross-app data sharing implications. Our findings highlight the pressing need to improve the design of this new and pivotal AHC platform to better protect mHealth app users’ privacy.

ACM Transactions on Computing for Healthcare
Colorado School of Mines (US), Kennesaw State University (US), University of Tulsa (US)
Openalex Percentile: Top 6%
Mobile Health and mHealth Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.