Assessing the Privacy of mHealth Apps for Self-Tracking: Heuristic Evaluation Approach
- Submitting institution
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The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1451852
- Type
- D - Journal article
- DOI
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10.2196/mhealth.9217
- Title of journal
- JMIR mHealth and uHealth
- Article number
- e185
- First page
- -
- Volume
- 6
- Issue
- 10
- ISSN
- 2291-5222
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2018
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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7
- Research group(s)
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-
- Citation count
- 14
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Health data are often highly sensitive yet there is no way to compare health apps for privacy. This paper was the first to develop and present a replicable methodology for objectively evaluating and comparing multiple aspects of privacy of self-tracking apps. It showed that health apps performed worse than others in preserving privacy and led to a £1M EPSRC grant (EP/P01013X/1) on monitoring older adults to reduce healthcare costs, and informed subsequent research on responding to Covid-19 (Rauschenberg et al. 2020) and health policy (Jogova et al, 2019) and led to a subsequent £500k EPSRC grant (EP/V027263/1).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -