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Factors influencing acceptance of technology for aging in place: A systematic review
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PURPOSE: To provide an overview of factors influencing the acceptance of electronic technologies that support aging in place by community-dwelling older adults. Since technology acceptance factors fluctuate over time, a distinction was made between factors in the pre-implementation stage and factors in the post-implementation stage. METHODS: A systematic review of mixed studies. Seven major scientific databases (including MEDLINE, Scopus and CINAHL) were searched. Inclusion criteria were as follows: (1) original and peer-reviewed research, (2) qualitative, quantitative or mixed methods research, (3) research in which participants are community-dwelling older adults aged 60 years or older, and (4) research aimed at investigating factors that influence the intention to use or the actual use of electronic technology for aging in place. Three researchers each read the articles and extracted factors. RESULTS: Sixteen out of 2841 articles were included. Most articles investigated acceptance of technology that enhances safety or provides social interaction. The majority of data was based on qualitative research investigating factors in the pre-implementation stage. Acceptance in this stage is influenced by 27 factors, divided into six themes: concerns regarding technology (e.g., high cost, privacy implications and usability factors); expected benefits of technology (e.g., increased safety and perceived usefulness); need for technology (e.g., perceived need and subjective health status); alternatives to technology (e.g., help by family or spouse), social influence (e.g., influence of family, friends and professional caregivers); and characteristics of older adults (e.g., desire to age in place). When comparing these results to qualitative results on post-implementation acceptance, our analysis showed that some factors are persistent while new factors also emerge. Quantitative results showed that a small number of variables have a significant influence in the pre-implementation stage. Fourteen out of the sixteen included articles did not use an existing technology acceptance framework or model. CONCLUSIONS: Acceptance of technology in the pre-implementation stage is influenced by multiple factors. However, post-implementation research on technology acceptance by community-dwelling older adults is scarce and most of the factors in this review have not been tested by using quantitative methods. Further research is needed to determine if and how the factors in this review are interrelated, and how they relate to existing models of technology acceptance.
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“Some older adults will perceive a technology as being more relevant for other elderly people with more extensive functional impairments56 and be less motivated to use it themselves.”
From Usability and acceptability of technology for community-dwelling older adults with mild cognitive impairment and dementia: a systematic literature review (2018) · cites this paper as [56]
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“Engaging older adults in a preimplementation study thus risks obtaining a “prototypical result,” according to Peek et al (2014).56”
From Usability and acceptability of technology for community-dwelling older adults with mild cognitive impairment and dementia: a systematic literature review (2018) · cites this paper as [56]
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“This is in line with Peek et al (2014, p. 242), who found that a perceived personal need for technology was the most frequent factor mentioned for technology use and acceptance.56”
From Usability and acceptability of technology for community-dwelling older adults with mild cognitive impairment and dementia: a systematic literature review (2018) · cites this paper as [56]
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Metadata
- Authors
- Peek, S. T. M., Wouters, E. J. M., van Hoof, J., Luijkx, K. G., Boeije, H. R., & Vrijhoef, H. J. M.
- Affiliations
- Tilburg University (NL)
- Fontys University of Applied Sciences (NL)
- Utrecht University (NL)
- National University of Singapore (SG)
- Corresponding author
- Peek, Sebastiaan T.M.
- ORCID
- Venue
- International Journal of Medical Informatics
- Publisher
- Elsevier BV
- Published
- 2014-04
- Volume
- 83
- Issue
- 4
- Pages
- 235-248
- ISSN
- 1386-5056 (ISSN-L)
- OpenAlex
- W2105499459
- Cited by
- 1,206
- References
- 69
- Citations by year
- 2026: 159 · 2025: 117 · 2024: 95 · 2023: 120 · 2022: 105 · 2021: 120 · 2020: 129 · 2019: 91 · 2018: 103 · 2017: 70 · 2016: 53 · 2015: 32 · 2014: 10
- FWCI
- 19.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Medical Informatics (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Utrecht University Repository (Utrecht University) (acceptedVersion)
- Research portal (Tilburg University) (submittedVersion, cc-by-nc-nd)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by-nc-nd)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc-nd)
- Utrecht University Repository (Utrecht University) (submittedVersion)
- Funders
- Dutch Ministry of Education, Culture and Science (OCW) (PRO-3-37)
- Topics
- Health Sciences › Medicine › Geriatrics and Gerontology › Technology Use by Older Adults
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Keywords
- technology acceptance, aging in place, community-dwelling older adults, electronic health technology, perceived usefulness, perceived ease of use, privacy concerns, usability, social influence, family caregivers, safety technology, technology adoption
- MeSH terms
- Adult, Aged, Attitude to Computers, Health Services Needs and Demand, Humans, Patient Acceptance of Health Care, Technology Assessment, Biomedical, Independent Living
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
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