Privacy and User Satisfaction in Digital Health Applications

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dc.contributor.authorSchewina, Kai
dc.date.accessioned2023-12-26T18:40:04Z
dc.date.available2023-12-26T18:40:04Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.395
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other87aa4a8a-c1d9-4734-bc9e-62b03e9a0d6a
dc.identifier.urihttps://hdl.handle.net/10125/106778
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData Platforms and Ecosystems in Healthcare
dc.subjectdigital health
dc.subjectmhealth
dc.subjectprivacy
dc.subjectuser satisfaction
dc.titlePrivacy and User Satisfaction in Digital Health Applications
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractDigital health applications are promising to healthcare due to their important position in the digital health ecosystem. User satisfaction with apps is crucial for their widespread use, but there are substantial concerns regarding the usage of users’ health data preventing their dissemination. To study the relationship between privacy and user satisfaction, we utilize a dataset encompassing almost 94,412 apps from the Apple App Store. We apply propensity score matching to estimate the average treatment effects of multiple privacy settings that describe what data is collected and to what extent. We find that not collecting data on users is associated with a decrease in user satisfaction. Linking data to users’ profiles and tracking users’ data across applications increases user satisfaction. Our findings challenge the currently assumed relationship between the two variables and provide nuanced information for decision-makers about data collection in digital health applications.
dcterms.extent10 pages
prism.startingpage3265

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