The DOI matches its Crossref record; 67 of the 69 references it cites were found in a registry or an index.
Factors influencing acceptance of technology for aging in place: A systematic review
Open accessAbstract
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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Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,670
Valente, T. W. (2003) · Genetics in Medicine · doi:10.1097/01.gim.0000061743.67794.c4 · Cited by 20,559
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
Revisiting the Behavioral Model and Access to Medical Care: Does it Matter?
Andersen, R. M. (1995) · Journal of Health and Social Behavior · doi:10.2307/2137284 · Cited by 9,831
Methods for the thematic synthesis of qualitative research in systematic reviews
Thomas, J., & Harden, A. (2008) · BMC Medical Research Methodology · doi:10.1186/1471-2288-8-45 · Cited by 9,312
Why do people use information technology? A critical review of the technology acceptance model
Legris, P., Ingham, J., & Collerette, P. (2003) · Information & Management · doi:10.1016/s0378-7206(01)00143-4 · Cited by 4,250
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999) · MIS Quarterly · doi:10.2307/249751 · Cited by 3,833
A meta-analysis of the technology acceptance model
King, W. R., & He, J. (2006) · Information & Management · doi:10.1016/j.im.2006.05.003 · Cited by 2,906
Cited by
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Older Adults' Reasons for Using Technology while Aging in Place
Peek, S. T. M., Luijkx, K. G., Rijnaard, M. D., Nieboer, M. E., van der Voort, C. S., Aarts, S., van Hoof, J., Vrijhoef, H. J., & Wouters, E. (2015) · Gerontology · doi:10.1159/000430949 · Cited by 19,852
Self-citationTechnology acceptance model in educational context: A systematic literature review
Granić, A., & Marangunić, N. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12864 · Cited by 1,204
A systematic review of the smart home literature: A user perspective
Marikyan, D., Papagiannidis, S., & Alamanos, E. (2019) · Technological forecasting & social change · doi:10.1016/j.techfore.2018.08.015 · Cited by 633
Smart homes and home health monitoring technologies for older adults: A systematic review
Liu, L., Stroulia, E., Nikolaidis, I., Cruz, A. M., & Rincon, A. M. R. (2016) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2016.04.007 · Cited by 711
Barriers and facilitators to the use of e-health by older adults: a scoping review
Wilson, J. W., Heinsch, M., Betts, D. N., Booth, D., & KAY‐LAMBKIN, F. J. (2021) · BMC Public Health · doi:10.1186/s12889-021-11623-w · Cited by 706
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
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