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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Sorted by citations
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
Analyzing older users’ home telehealth services acceptance behavior—applying an Extended UTAUT model
Cimperman, M., Brenčić, M. M., & Trkman, P. (2016) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2016.03.002 · Cited by 634
Abdi, S., Spann, A., Borilovic, J., de Witte, L., & Hawley, M. (2019) · BMC Geriatrics · doi:10.1186/s12877-019-1189-9 · Cited by 624
Technology Acceptance in Healthcare: A Systematic Review
AlQudah, A. A., Al‐Emran, M., & Shaalan, K. F. (2021) · Applied Sciences · doi:10.3390/app112210537 · Cited by 461
Definitions, key themes and aspects of ‘ageing in place’: a scoping review
Pani-Harreman, K. E., Bours, G. J. J. W., Zander, I., Kempen, G. I. J. M., & van Duren, J. M. A. (2020) · Ageing and Society · doi:10.1017/s0144686x20000094 · Cited by 358
Internet-of-Things and Smart Homes for Elderly Healthcare: An End User Perspective
Pal, D., Funilkul, S., Charoenkitkarn, N., & Kanthamanon, P. (2018) · IEEE Access · doi:10.1109/access.2018.2808472 · Cited by 359
Technology Adoption by Older Adults: Findings From the PRISM Trial
Mitzner, T. L., Savla, J., Boot, W. R., Sharit, J., Charness, N., Czaja, S. J., & Rogers, W. A. (2019) · The Gerontologist · doi:10.1093/geront/gny113 · Cited by 311
Determinants of the intention to use e-Health by community dwelling older people
de Veer, A. J. E., Peeters, J. M., Brabers, A. E. M., Schellevis, F., Rademakers, J. J. D. J. M., & Francke, A. L. (2015) · BMC Health Services Research · doi:10.1186/s12913-015-0765-8 · Cited by 315
Moore, K., O'Shea, E., Kenny, L., Barton, J., Tedesco, S., Sica, M., Crowe, C., Alamäki, A., Condell, J., Nordström, A., et al. (2021) · JMIR mHealth and uHealth · doi:10.2196/23832 · Cited by 278
Inclusion of older adults in the research and design of digital technology
Mannheim, I., Schwartz, E., Xi, W., Buttigieg, S. C., McDonnell-Naughton, M., Wouters, E. J. M., & van Zaalen, Y. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16193718 · Cited by 291
Self-citationTaylor, D. J., Hobby, A. E., Binns, A. M., & Crabb, D. P. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-011504 · Cited by 289
Ten questions concerning age-friendly cities and communities and the built environment
van Hoof, J., Marston, H. R., Kazak, J. K., & Buffel, T. (2021) · Building and Environment · doi:10.1016/j.buildenv.2021.107922 · Cited by 325
Krick, T., Huter, K., Domhoff, D., Schmidt, A., Rothgang, H., & Wolf-Ostermann, K. (2019) · BMC Health Services Research · doi:10.1186/s12913-019-4238-3 · Cited by 279
Güner, H., & Acartürk, C. (2018) · Universal Access in the Information Society · doi:10.1007/s10209-018-0642-4 · Cited by 291
Ten questions concerning thermal comfort and ageing
van Hoof, J., Schellen, L., Soebarto, V. I., Wong, J. K. W., & Kazak, J. K. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.05.008 · Cited by 272
The Challenges of Urban Ageing: Making Cities Age-Friendly in Europe
van Hoof, J., Kazak, J. K., Perek-Białas, J. M., & Peek, S. T. M. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15112473 · Cited by 303
Self-citationSchroeder, T., Dodds, L., Georgiou, A., Gewald, H., & Siette, J. (2023) · JMIR Aging · doi:10.2196/44564 · Cited by 308
Aldboush, H. H., & Ferdous, M. (2023) · International Journal of Financial Studies · doi:10.3390/ijfs11030090 · Cited by 247
Participatory Design in Gerontechnology: A Systematic Literature Review
Merkel, S., & Kucharski, A. (2019) · The Gerontologist · doi:10.1093/geront/gny034 · Cited by 209
Holthe, T., Halvorsrud, L., Karterud, D., Hoel, K.-A., & Lund, A. (2018) · Clinical Interventions in Aging · doi:10.2147/cia.s154717 · Cited by 199
“242), who found that a perceived personal need for technology was the most frequent factor mentioned for technology use and acceptance.(56) Several authors referred to the International Organization for Standardization’s definition of usability.”
InfluentialPotential of Augmented Reality and Virtual Reality Technologies to Promote Wellbeing in Older Adults
Lee, L. N., Kim, M. J., & Hwang, W. J. (2019) · Applied Sciences · doi:10.3390/app9173556 · Cited by 209
Facilitators of and Barriers to mHealth Adoption in Older Adults With Heart Failure
Cajita, M., Hodgson, N. A., Lam, K. K. W., Yoo, S., & Han, H. (2018) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000000442 · Cited by 208
Mobile Health Applications to Promote Active and Healthy Ageing
Helbostad, J. L., Vereijken, B., Becker, C., Todd, C. J., Taraldsen, K., Pijnappels, M. A. G. M., Aminian, K., & Mellone, S. (2017) · Sensors · doi:10.3390/s17030622 · Cited by 223
Designing mobile technology for elderly. A theoretical overview
Iancu, I., & Iancu, B. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.119977 · Cited by 165
Co-Designing Technology for Aging in Place: A Systematic Review
Sumner, J., Chong, L. S., Bundele, A., & Lim, Y. W. (2020) · The Gerontologist · doi:10.1093/geront/gnaa064 · Cited by 216
Ghorayeb, A., Comber, R., & Gooberman‐Hill, R. (2020) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2020.102571 · Cited by 224
Tavares, J., & Oliveira, T. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5069 · Cited by 204
Bereavement in the time of coronavirus: unprecedented challenges demand novel interventions
Carr, D., Boerner, K., & Moorman, S. (2020) · Journal of Aging & Social Policy · doi:10.1080/08959420.2020.1764320 · Cited by 189
Digital health platforms for the elderly? Key adoption and usage barriers and ways to address them
Frishammar, J., Essén, A., Bergström, F., & Ekman, T. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122319 · Cited by 194
Acceptance Factors of Mobile Apps for Diabetes by Patients Aged 50 or Older: A Qualitative Study
Scheibe, M., Reichelt, J., Bellmann, M., & Kirch, W. (2015) · Medicine 2.0 · doi:10.2196/med20.3912 · Cited by 207
Review of the Factors Affecting Acceptance of AI-Infused Systems
Ismatullaev, U. V. U., & Kim, S. (2022) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211064707 · Cited by 198
Peek, S. T. M., Wouters, E., Luijkx, K. G., & Vrijhoef, H. J. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5253 · Cited by 171
Self-citationLuijkx, K., Peek, S., & Wouters, E. (2015) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph121214999 · Cited by 161
Self-citationPuri, A., Kim, B. Y., Nguyen, O., Stolee, P., Tung, J. Y., & Lee, J. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.8211 · Cited by 167
Ethics and acceptance of smart homes for older adults
Pirzada, P., Wilde, A., Doherty, G. H., & Harris‐Birtill, D. (2021) · Informatics for Health and Social Care · doi:10.1080/17538157.2021.1923500 · Cited by 170
Thordardottir, B., Malmgren Fänge, A., Lethin, C., Rodriguez Gatta, D., & Chiatti, C. (2019) · BioMed Research International · doi:10.1155/2019/9196729 · Cited by 169
Tsertsidis, A., Kolkowska, E., & Hedström, K. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.06.027 · Cited by 166
Golant, S. M. (2017) · Journal of Aging Studies · doi:10.1016/j.jaging.2017.07.003 · Cited by 173
Analysis of Software Development Methodologies
Soobia.et.al., S. (2019) · International Journal of Computing and Digital Systems · doi:10.12785/ijcds/080502 · Cited by 148
Marston, H. R., & van Hoof, J. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16193525 · Cited by 163
Analyzing the Elderly Users’ Adoption of Smart-Home Services
Pal, D., Funilkul, S., Vanijja, V., & Papasratorn, B. (2018) · IEEE Access · doi:10.1109/access.2018.2869599 · Cited by 152
Factors that affect health information technology adoption by seniors: A systematic review.
Kavandi, H., & Jaana, M. (2020) · Health and Social Care in the community · doi:10.1111/hsc.13011 · Cited by 127
Schomakers, E.-M., Lidynia, C., Vervier, L., Valdez, A. S. C., & Ziefle, M. (2021) · JMIR mhealth and uhealth · doi:10.2196/27095 · Cited by 151
How can technology support ageing in place in healthy older adults? A systematic review
Ollevier, A., Noury, G. A., Palomino, M. A., & Simpelaere, I. S. (2020) · Public health reviews · doi:10.1186/s40985-020-00143-4 · Cited by 156
Simonetti, A., Pais, C., Jones, M. B., Cipriani, M. C., Janiri, D., Monti, L., Landi, F., Bernabei, R., Liperoti, R., & Sani, G. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.579842 · Cited by 140
Assistive Technologies in Dementia Care: An Updated Analysis of the Literature
Pappadà, A., Chattat, R., Chirico, I., Valente, M., & Ottoboni, G. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.644587 · Cited by 131
Aging in the Digital Age: Conceptualizing Technology Adoption and Digital Inequalities
Francis, J., Ball, C., Kadylak, T., & Cotten, S. R. (2019) · Springer eBooks · doi:10.1007/978-981-13-3693-5_3 · Cited by 140
Zaman, S. B., Khan, R. K., Evans, R. G., Thrift, A. G., Maddison, R., & Islam, S. M. S. (2021) · JMIR Aging · doi:10.2196/25251 · Cited by 129
Evans, J., Papadopoulos, A., Silvers, C. T., Charness, N., Boot, W. R., Schlachta-Fairchild, L., Crump, C., Martinez, M., & Ent, C. B. (2016) · Telemedicine and e-Health · doi:10.1089/tmj.2015.0140 · Cited by 119
Insights into Older Adults’ Technology Acceptance through Meta-Analysis
Ma, Q., Chan, A., & Teh, P. (2021) · International journal of human computer interactions · doi:10.1080/10447318.2020.1865005 · Cited by 113
FakhrHosseini, S., Chan, K., Lee, C., Jeon, M., Son, H., Rudnik, J., & Coughlin, J. F. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2118851 · Cited by 146
Elderly Perception on the Internet of Things-Based Integrated Smart-Home System
Jo, T. H., Hoon, J., & Cha, S. H. (2021) · Sensors · doi:10.3390/s21041284 · Cited by 120
Claes, V., Devriendt, E., Tournoy, J., & Milisen, K. (2014) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2014.05.010 · Cited by 114
Rodrigues, N. G., Han, Q., Su, Y., Klainin‐Yobas, P., & Wu, X. V. (2021) · Journal of Advanced Nursing · doi:10.1111/jan.15063 · Cited by 121
Older Adults’ Acceptance of Activity Trackers
Preusse, K. C., Mitzner, T. L., Fausset, C. B., & Rogers, W. A. (2017) · Journal of Applied Gerontology · doi:10.1177/0733464815624151 · Cited by 128
Ferreira, L., Oliveira, T., & das Neves, C. P. P. C. (2022) · Energy · doi:10.1016/j.energy.2022.125814 · Cited by 112
Nikitas, A., Avineri, E., & Parkhurst, G. P. (2018) · Cities · doi:10.1016/j.cities.2018.02.024 · Cited by 111
Abd-Alrazaq, A. A., Bewick, B. M., Farragher, T. M., & Gardner, P. H. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.03.014 · Cited by 113
Factors Influencing Intention to Technological Use in Older Adults. The TAM Model Aplication
Martín‐García, A. V., Redolat, R., & Hernandis, S. P. (2021) · Research on Aging · doi:10.1177/01640275211063797 · Cited by 127
Blok, M., van Ingen, E. J., de Boer, A. H., & Slootman, M. W. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.106173 · Cited by 111
Chen, K., LOU, V. W. Q., Tan, K. C., Wai, M., & Chan, L. L. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104241 · Cited by 112
Robots for Elderly Care: Review, Multi-Criteria Optimization Model and Qualitative Case Study
Sawik, B., Tobis, S., Baum, E., Suwalska, A., Kropińska, S., Stachnik, K., Bernabeu, E. P., Cildoz, M., Agustín, A., & Wieczorowska–Tobis, K. (2023) · Healthcare · doi:10.3390/healthcare11091286 · Cited by 107
Farmers’ adoption of agricultural innovations: A systematic review on willingness to pay studies
Olum, S., Gellynck, X., Juvinal, J., Ongeng, D., & Steur, H. D. (2019) · Outlook on Agriculture · doi:10.1177/0030727019879453 · Cited by 105
Brims, L., & Oliver, K. A. (2018) · Aging & Mental Health · doi:10.1080/13607863.2018.1455805 · Cited by 103
Reyes, E. P. G., Kelly, R., Buchanan, G. R., & Waycott, J. (2023) · JMIR Aging · doi:10.2196/43197 · Cited by 102
Lee, L., & Kim, M. J. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.03080 · Cited by 106
Digital healthcare technology adoption by elderly people: A capability approach model
Nikou, S., Agahari, W., Keijzer-Broers, W., & de Reuver, M. (2019) · Telematics and Informatics · doi:10.1016/j.tele.2019.101315 · Cited by 98
Carnemolla, P. (2018) · Visualization in Engineering · doi:10.1186/s40327-018-0066-5 · Cited by 97
Assistive robotic systems in nursing care: a scoping review
Ohneberg, C., Stöbich, N., Warmbein, A., Rathgeber, I., Mehler-Klamt, A., Fischer, U., & Eberl, I. (2023) · BMC Nursing · doi:10.1186/s12912-023-01230-y · Cited by 104
Oderanti, F. O., Li, F., Čubrić, M., & Shi, X. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120969 · Cited by 102
Electronic Health Record Portal Adoption: a cross country analysis
Tavares, J., & Oliveira, T. (2017) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-017-0482-9 · Cited by 99
Schomakers, E.-M., Lidynia, C., & Ziefle, M. (2021) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2021.1994211 · Cited by 94
Identifying Features that Enhance Older Adults’ Acceptance of Robots: A Mixed Methods Study
Chu, L., Chen, H.-W., Cheng, P.-Y., Ho, P., Weng, I.-T., Yang, P.-L., Chien, S.-E., Tu, Y.-C., Yang, C.-C., Wang, T.-M., et al. (2019) · Gerontology · doi:10.1159/000494881 · Cited by 76
Developing a Healthcare Technology Acceptance Model (H-TAM) for Older Adults with Hypertension
Harris, M., & Rogers, W. (2021) · Ageing & Society · doi:10.1017/s0144686x21001069 · Cited by 72
Older adults’ acceptance of a robot for partner dance-based exercise
Chen, T. L. B., Bhattacharjee, T., Beer, J. M., Ting, L. H., Hackney, M. E., Rogers, W. A., & Kemp, C. C. (2017) · PLoS ONE · doi:10.1371/journal.pone.0182736 · Cited by 85
El‐Awaisi, A., Joseph, S., Hajj, M. S. E., & Diack, L. (2017) · Research in Social and Administrative Pharmacy · doi:10.1016/j.sapharm.2017.11.001 · Cited by 84
Peek, S. T. M., Luijkx, K. G., Vrijhoef, H. J. M., Nieboer, M. E., Aarts, S., van der Voort, C. S., Rijnaard, M. D., & Wouters, E. J. M. (2019) · BMC Geriatrics · doi:10.1186/s12877-019-1241-9 · Cited by 84
Self-citationElectronic Health Record Portals adoption: Empirical model based on UTAUT2
Tavares, J., Goulão, A. P. B. A., & Oliveira, T. (2017) · Informatics for Health and Social Care · doi:10.1080/17538157.2017.1363759 · Cited by 97
Månsson, L., Wiklund, M., Öhberg, F., Danielsson, K., & Sandlund, M. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17113768 · Cited by 90
Implementation of robotic devices in nursing care. Barriers and facilitators: an integrative review
Servaty, R., Kersten, A., Brukamp, K., Mohler, R. A., & Müller, M. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-038650 · Cited by 83
Rasekaba, T., Pereira, P., Vinaya Rani, G., Johnson, R., McKechnie, R., & Blackberry, I. (2022) · Geriatrics · doi:10.3390/geriatrics7020028 · Cited by 77
Terp, R., Kayser, L., & Lindhardt, T. (2021) · JMIR Human Factors · doi:10.2196/27005 · Cited by 78
Boyle, L. D., Husebo, B. S., & Vislapuu, M. (2022) · BMC Health Services Research · doi:10.1186/s12913-022-08968-2 · Cited by 104
Smart Homes and Quality of Life for the Elderly: A Systematic Review
Pal, D., Triyason, T., & Funikul, S. (2017) · IEEE International Symposium on Multimedia (ISM) · doi:10.1109/ism.2017.83 · Cited by 80
Cardiac patients show high interest in technology enabled cardiovascular rehabilitation
Buys, R., Claes, J., Walsh, D. M. J., Cornelis, N., Moran, K., Budts, W., Woods, C. B., & Cornelissen, V. (2016) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-016-0329-9 · Cited by 79
Older adults’ attitudes and barriers toward the use of mobile phones
Ghaffari, F., Navabi, N., & Alipoor, Z. J. (2016) · Clinical Interventions in Aging · doi:10.2147/cia.s112893 · Cited by 77
Assistive robots to improve the independent living of older persons: results from a needs study
Fiorini, L., de Mul, M., Fabbricotti, I. N., Limosani, R., Vitanza, A., D’Onofrio, G., Tsui, M., Sancarlo, D., Giuliani, F., Greco, A., et al. (2019) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2019.1642392 · Cited by 78
A study on smart home use intention of elderly consumers based on technology acceptance models
Zhou, C., Qian, Y., & Kaner, J. (2024) · PLoS ONE · doi:10.1371/journal.pone.0300574 · Cited by 93
Weering, M. D.-V., Jansen-Kosterink, S. M., Frazer, S. W. T., & Vollenbroek-Hutten, M. M. R. (2017) · Frontiers in Medicine · doi:10.3389/fmed.2017.00208 · Cited by 74
Carter, D. D., Robinson, K., Forbes, J., & Hayes, S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0208759 · Cited by 83
Karlsen, C., Ludvigsen, M. S., Moe, C. E., Haraldstad, K., & Thygesen, E. (2017) · JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2017-003345 · Cited by 66
Smart Environments and Social Robots for Age-Friendly Integrated Care Services
Anghel, I. M., Cioara, T., Moldovan, D., Antal, C., Pop, C. D., Salomie, I., Pop, C. B., & Chifu, V. R. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17113801 · Cited by 82
Examining a Model of Mobile Healthcare Technology Acceptance by the Elderly in Taiwan
Hsiao, C., & Tang, K. (2015) · Journal of Global Information Technology Management · doi:10.1080/1097198x.2015.1108099 · Cited by 74
The acceptance of personal health devices among patients with chronic conditions
Sun, N., & Rau, P. P. (2015) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2015.01.002 · Cited by 75
Profiles and Predictors of Smart Home Technology Adoption by Older Adults
Arthanat, S., Wilcox, J., & Macuch, M. (2018) · OTJR Occupational Therapy Journal of Research · doi:10.1177/1539449218813906 · Cited by 74
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
