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Willingness of older adults to share data and privacy concerns after exposure to unobtrusive in-home monitoring
Open accessAbstract
Older adult participants in the Intelligent Systems for Assessment of Aging Changes study (ISAAC) carried out by the Oregon Center for Aging and Technology (ORCATECH) were surveyed regarding their attitudes about unobtrusive home monitoring and computer use at baseline and after one year (n=119). The survey was part of a longitudinal study using in-home sensor technology to detect cognitive changes and other health problems. Our primary objective was to measure willingness to share health or activity data with one's doctor or family members and concerns about privacy or security of monitoring over one year of study participation. Differences in attitudes of participants with Mild Cognitive Impairment (MCI) compared to those with normal cognition were also examined. A high proportion (over 72%) of participants reported acceptance of in-home and computer monitoring and willingness to have data shared with their doctor or family members. However, a majority (60%) reported concerns related to privacy or security; these concerns increased after one year of participation. Few differences between participants with MCI and those with normal cognition were identified. Findings suggest that involvement in this unobtrusive in-home monitoring study may have raised awareness about the potential privacy risks of technology. Still, results show high acceptance, stable over time, of sharing information from monitoring systems with family members and doctors. Our findings have important implications for the deployment of technologies among older adults in research studies as well as in the general community.
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“Twelve studies presented results on IAT that were both accepted and used by the participants [19–21, 23, 27, 30–33, 42, 43, 45].”
From Acceptance and use of innovative assistive technologies among people with cognitive impairment and their caregivers: a systematic review (2019) · cites this paper as [19]
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“In some cases users did not even mind being monitored by IAT if this was understood as a useful strategy to allow their physician to provide a better care [19].”
From Acceptance and use of innovative assistive technologies among people with cognitive impairment and their caregivers: a systematic review (2019) · cites this paper as [19]
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Metadata
- Authors
- Boise, L., Wild, K., Mattek, N., Ruhl, M., Dodge, H. H., & Kaye, J.
- Affiliations
- Oregon Health & Science University (US)
- Venue
- Gerontechnology
- Published
- 2013-01-22
- Volume
- 11
- Issue
- 3
- Pages
- 428-435
- ISSN
- 1569-1101 (ISSN-L)
- 1569-111X
- PMC
- PMC3604979
- OpenAlex
- W2045440422
- Cited by
- 139
- References
- 32
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 9 · 2023: 16 · 2022: 11 · 2021: 22 · 2020: 11 · 2019: 17 · 2018: 7 · 2017: 9 · 2016: 7 · 2015: 7 · 2014: 4 · 2013: 4
- FWCI
- 19.99
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Gerontechnology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Department of Veterans Affairs
- University of Oregon
- National Institute on Aging (R01AG024059, P30AG008017, P30AG024978, K01AG023014)
- Topics
- Health Sciences › Medicine › Geriatrics and Gerontology › Technology Use by Older Adults
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Health Sciences › Nursing › Issues, ethics and legal aspects › Patient Dignity and Privacy
- Keywords
- older adults, home monitoring, non-intrusive monitoring, privacy concerns, data sharing, mild cognitive impairment, computer monitoring, health data sharing, technology acceptance
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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