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Acceptance of an assistive robot in older adults: a mixed-method study of human–robot interaction over a 1-month period in the Living Lab setting
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BACKGROUND: There is growing interest in investigating acceptance of robots, which are increasingly being proposed as one form of assistive technology to support older adults, maintain their independence, and enhance their well-being. In the present study, we aimed to observe robot-acceptance in older adults, particularly subsequent to a 1-month direct experience with a robot. SUBJECTS AND METHODS: Six older adults with mild cognitive impairment (MCI) and five cognitively intact healthy (CIH) older adults were recruited. Participants interacted with an assistive robot in the Living Lab once a week for 4 weeks. After being shown how to use the robot, participants performed tasks to simulate robot use in everyday life. Mixed methods, comprising a robot-acceptance questionnaire, semistructured interviews, usability-performance measures, and a focus group, were used. RESULTS: Both CIH and MCI subjects were able to learn how to use the robot. However, MCI subjects needed more time to perform tasks after a 1-week period of not using the robot. Both groups rated similarly on the robot-acceptance questionnaire. They showed low intention to use the robot, as well as negative attitudes toward and negative images of this device. They did not perceive it as useful in their daily life. However, they found it easy to use, amusing, and not threatening. In addition, social influence was perceived as powerful on robot adoption. Direct experience with the robot did not change the way the participants rated robots in their acceptance questionnaire. We identified several barriers to robot-acceptance, including older adults' uneasiness with technology, feeling of stigmatization, and ethical/societal issues associated with robot use. CONCLUSION: It is important to destigmatize images of assistive robots to facilitate their acceptance. Universal design aiming to increase the market for and production of products that are usable by everyone (to the greatest extent possible) might help to destigmatize assistive devices.
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“Seven studies reported that technology was neither accepted nor adhered to [22, 25, 26, 28, 39, 40, 48].”
From Acceptance and use of innovative assistive technologies among people with cognitive impairment and their caregivers: a systematic review (2019) · cites this paper as [48]
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“When it comes to use of robots in health care, our results show that the users had generally low interest to use the robot, as well as negative attitudes toward and negative images for this type of devices [24, 26, 48].”
From Acceptance and use of innovative assistive technologies among people with cognitive impairment and their caregivers: a systematic review (2019) · cites this paper as [48]
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Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414
(2014) · SAGE Publications Ltd eBooks · doi:10.4135/9781446294406.n148 · Cited by 7,272
Neufeld, A., & Ryan, A. G. (1988) · Canadian Journal of Program Evaluation · doi:10.3138/cjpe.3.006 · Cited by 5,906
Current concepts in mild cognitive impairment
Petersen, R. C., Doody, R., Kurz, A., Mohs, R. C., Morris, J. C., Rabins, P. V., Ritchie, K., Rossor, M., Thal, L., & Winblad, B. (2001) · Archives of Neurology · doi:10.1001/archneur.58.12.1985 · Cited by 4,781
Assessing Acceptance of Assistive Social Agent Technology by Older Adults: the Almere Model
Heerink, M., Kröse, B., Evers, V., & Wielinga, B. (2010) · International Journal of Social Robotics · doi:10.1007/s12369-010-0068-5 · Cited by 1,229
Assistive social robots in elderly care: a review
Broekens, J., Heerink, M., & Rosendal, H. (2009) · Gerontechnology · doi:10.4017/gt.2009.08.02.002.00 · Cited by 950
Acceptance of Healthcare Robots for the Older Population: Review and Future Directions
Broadbent, E., Stafford, R., & MacDonald, B. (2009) · International Journal of Social Robotics · doi:10.1007/s12369-009-0030-6 · Cited by 887
Older adults' use of information and communications technology in everyday life
SELWYN, N., GORARD, S., FURLONG, J., & MADDEN, L. (2003) · Ageing and Society · doi:10.1017/s0144686x03001302 · Cited by 617
Older adults: Are they ready to adopt health-related ICT?
Heart, T., & Kalderon, E. (2013) · Int. J. Medical Informatics · doi:10.1016/j.ijmedinf.2011.03.002 · Cited by 599
Universal Design : Barrier Free Environments for Everyone
Mace, R. L. (1985) · Medical Entomology and Zoology · Cited by 275
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Wang, Y., & Wang, Y. (2019) · Interactive Learning Environments · doi:10.1080/10494820.2019.1674887 · Cited by 830
Older people, assistive technologies, and the barriers to adoption: A systematic review
Yusif, S., Soar, J., & Hafeez-Baig, A. (2016) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2016.07.004 · Cited by 548
A Systematic Review of Attitudes, Anxiety, Acceptance, and Trust Towards Social Robots
Naneva, S., Gou, M. S., Webb, T. L., & Prescott, T. J. (2020) · International Journal of Social Robotics · doi:10.1007/s12369-020-00659-4 · Cited by 389
Lin, H., Chi, O. H., & Gürsoy, D. (2019) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2020.1685053 · Cited by 388
Pino, M., Boulay, M., Jouen, F., & Rigaud, A. (2015) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2015.00141 · Cited by 352
Self-citationDigital Engagement of Older Adults: Scoping Review
Kebede, A. S., Ozolins, L.-L., Holst, H., & Galvin, K. (2022) · Journal of Medical Internet Research · doi:10.2196/40192 · Cited by 298
Young Russian adults' attitudes towards the potential use of robots in hotels
Ivanov, S. H., Webster, C., & Garenko, A. (2018) · Technology in Society · doi:10.1016/j.techsoc.2018.06.004 · Cited by 262
Wu, Y.-H., Ware, C., Damnée, S., Kerhervé, H., & Rigaud, A. (2015) · Clinical Interventions in Aging · doi:10.2147/cia.s72399 · Cited by 280
Self-citationPapadopoulos, I., Koulouglioti, C., Lazzarino, R., & Ali, S. (2020) · BMJ Open · doi:10.1136/bmjopen-2019-033096 · Cited by 219
Sapci, A. H., & Sapci, H. A. (2019) · JMIR Aging · doi:10.2196/15429 · Cited by 214
Ethical Design of Intelligent Assistive Technologies for Dementia: A Descriptive Review
Ienca, M., Wangmo, T., Jotterand, F., Kressig, R. W., & Elger, B. S. (2017) · Science and Engineering Ethics · doi:10.1007/s11948-017-9976-1 · Cited by 221
Artificial intelligence in elderly healthcare: A scoping review
Ma, B., Yang, J. H., Wong, F. K. Y., Wong, A. K. C., Ma, T., Meng, J., Zhao, Y., Wang, Y., & Lu, Q. (2022) · Ageing Research Reviews · doi:10.1016/j.arr.2022.101808 · Cited by 217
A systematic review of research into how robotic technology can help older people
Shishehgar, M., Kerr, D. V., & Blake, J. (2018) · Smart Health · doi:10.1016/j.smhl.2018.03.002 · Cited by 184
Thordardottir, B., Malmgren Fänge, A., Lethin, C., Rodriguez Gatta, D., & Chiatti, C. (2019) · BioMed Research International · doi:10.1155/2019/9196729 · Cited by 169
Hebesberger, D., Koertner, T., Gisinger, C., & Pripfl, J. (2017) · International Journal of Social Robotics · doi:10.1007/s12369-016-0391-6 · Cited by 163
Vandemeulebroucke, T., de Casterlé, B. D., & Gastmans, C. (2018) · Aging & Mental Health · doi:10.1080/13607863.2017.1286455 · Cited by 160
Whelan, S., Murphy, K., Barrett, E., Krusche, C., Santorelli, A., & Casey, D. (2018) · International Journal of Social Robotics · doi:10.1007/s12369-018-0471-x · Cited by 162
Christoforakos, L., Gallucci, A., Surmava-Große, T., Ullrich, D., & Diefenbach, S. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.640444 · Cited by 154
Bradwell, H. L., Edwards, K. J., Winnington, R., Thill, S., & Jones, R. B. (2019) · BMJ Open · doi:10.1136/bmjopen-2019-032468 · Cited by 137
Friend or Foe? Understanding Assembly Workers’ Acceptance of Human-robot Collaboration
Meißner, A., Trübswetter, A., Conti, A. S., & Schmidtler, J. (2020) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3399433 · Cited by 137
Koh, W. Q., Felding, S. A., Budak, K. B., Toomey, E. C., & Casey, D. (2021) · BMC Geriatrics · doi:10.1186/s12877-021-02277-9 · Cited by 128
‘That's for old so and so's!’: does identity influence older adults’ technology adoption decisions?
Astell, A. J., McGrath, C., & Dove, E. (2020) · Ageing and Society · doi:10.1017/s0144686x19000230 · Cited by 112
ARI: the Social Assistive Robot and Companion
Cooper, S., Fava, A. D., Vivas, C., Marchionni, L., & Ferro, F. (2020) · IEEE RO-MAN · doi:10.1109/ro-man47096.2020.9223470 · Cited by 112
An autonomous robotic exercise tutor for elderly people
Görer, B., Salah, A. A., & Akın, H. L. (2016) · Autonomous Robots · doi:10.1007/s10514-016-9598-5 · Cited by 109
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
A Review on the Use of Mobile Service Robots in Elderly Care
Asgharian, P., Panchea, A. M., & Ferland, F. (2022) · Robotics · doi:10.3390/robotics11060127 · Cited by 116
Isabet, B., Pino, M., Lewis, M., Benveniste, S., & Rigaud, A. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18073597 · Cited by 128
Self-citationMobile activity recognition and fall detection system for elderly people using Ameva algorithm
de la Concepción, M. Á. Á., Morillo, L. M. S., Álvarez-García, J. A., & Abril, L. G. (2016) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2016.05.002 · Cited by 105
Vandemeulebroucke, T., Dzi, K. T. J., & Gastmans, C. (2021) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2021.104399 · Cited by 96
Impacts of Low-cost Robotic Pets for Older Adults and People With Dementia: Scoping Review
Koh, W. Q., Ang, F. X. H., & Casey, D. (2021) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/25340 · Cited by 87
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
The effectiveness of various robotic technologies in assisting older adults
Shishehgar, M., Kerr, D. V., & Blake, J. (2017) · Health Informatics Journal · doi:10.1177/1460458217729729 · Cited by 92
Zhang, S., Hu, Z., Li, X., & Ren, A. (2022) · Journal of Hospitality and Tourism Management · doi:10.1016/j.jhtm.2022.06.014 · Cited by 93
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
Koumpouros, Y. (2016) · Journal of Healthcare Engineering · doi:10.1155/2016/1048964 · Cited by 83
How smart homes are used to support older people: An integrative review
Turjamaa, R., Aki, P., & Kangasniemi, M. K. (2019) · International Journal of Older People Nursing · doi:10.1111/opn.12260 · Cited by 95
Humanoid robots in the care of older persons: A scoping review
Andtfolk, M., Nyholm, L., Eide, H., & Fagerström, L. (2021) · Assistive Technology · doi:10.1080/10400435.2021.1880493 · Cited by 81
Shore, L., Power, V., de Eyto, A., & O'Sullivan, L. W. (2018) · Robotics · doi:10.3390/robotics7010003 · Cited by 81
Han, J., & Conti, D. (2020) · Robotics · doi:10.3390/robotics9020034 · Cited by 79
Socially Assistive Robots Helping Older Adults through the Pandemic and Life after COVID-19
Getson, C., & Nejat, G. (2021) · Robotics · doi:10.3390/robotics10030106 · Cited by 72
Carros, F., Schwaninger, I., Preussner, A., Randall, D. W., Wieching, R., Fitzpatrick, G., & Wulf, V. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517435 · Cited by 69
Towards a Holistic Approach to Studying Human–Robot Interaction in Later Life
Zafrani, O., & Nimrod, G. (2018) · The Gerontologist · doi:10.1093/geront/gny077 · Cited by 68
Jatileni, C. N., Sanusi, I. T., Olaleye, S. A., Ayanwale, M. A., Agbo, F. J., & Oyelere, P. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12341-z · Cited by 88
Rossi, S., Conti, D., Garramone, F., Santangelo, G., Staffa, M., Varrasi, S., & Nuovo, A. G. D. (2020) · Robotics · doi:10.3390/robotics9020039 · Cited by 64
Living labs for health: an integrative literature review
Kim, J.-H., Kim, Y. L., Jang, H., Cho, M., Lee, M., Kim, J., & Lee, H. (2019) · European Journal of Public Health · doi:10.1093/eurpub/ckz105 · Cited by 61
Ivkov, M., Blešić, I., Dudić, B., Bartáková, G. P., & Dudić, Z. (2020) · Electronics · doi:10.3390/electronics9091442 · Cited by 62
Bradwell, H. L., Noury, G. A., Edwards, K. J., Winnington, R., Thill, S., & Jones, R. B. (2021) · Health Policy and Technology · doi:10.1016/j.hlpt.2021.100544 · Cited by 60
Gerłowska, J., Skrobas, U., Grabowska-Aleksandrowicz, K., Korchut, A., Szklener, S., Szczęśniak-Stańczyk, D., Tzovaras, D. K., & Rejdak, K. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00392 · Cited by 63
Safe, Flexible and Productive Human-Robot-Collaboration for Disassembly of Lithium-Ion Batteries
Gerbers, R., Wegener, K., Dietrich, F., & Dröder, K. (2017) · Sustainable production, life cycle engineering and management · doi:10.1007/978-3-319-70572-9_6 · Cited by 58
The Role of Healthcare Robotics in Providing Support to Older Adults: a Socio-ecological Perspective
Moiş, G., & Beer, J. M. (2020) · Current Geriatrics Reports · doi:10.1007/s13670-020-00314-w · Cited by 48
Łukasik, S., Tobis, S., Kropińska, S., & Suwalska, A. (2020) · Journal of Medical Internet Research · doi:10.2196/18003 · Cited by 54
Qualitative Research in HRI: A Review and Taxonomy
Veling, L., & McGinn, C. (2021) · International Journal of Social Robotics · doi:10.1007/s12369-020-00723-z · Cited by 54
Assessment of personal care and medical robots from older adults’ perspective
Goher, K., Mansouri, N., & Fadlallah, S. O. (2017) · Robotics and Biomimetics · doi:10.1186/s40638-017-0061-7 · Cited by 51
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Liu, B., Tetteroo, D., & Markopoulos, P. (2022) · International Journal of Social Robotics · doi:10.1007/s12369-022-00870-5 · Cited by 53
Cruz, A. M., Daum, C., Comeau, A. K., Salamanca, J. D. G., McLennan, L., Neubauer, N., & Liu, L. (2020) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2020.1864671 · Cited by 50
Fracasso, F., Buchweitz, L., Theil, A., Cesta, A., & Korn, O. (2022) · International Journal of Social Robotics · doi:10.1007/s12369-022-00884-z · Cited by 51
Acceptance and Long-Term Use of a Social Robot by Elderly Users in a Domestic Environment
Piasek-Skupna, J., & Wieczorowska–Tobis, K. (2018) · Conference on Human System Interactions · doi:10.1109/hsi.2018.8431348 · Cited by 49
Novel Technological Solutions for Assessment, Treatment, and Assistance in Mild Cognitive Impairment
Mancioppi, G., Fiorini, L., Sportiello, M. T., & Cavallo, F. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00058 · Cited by 54
Khaksar, S. M. S., Khosla, R., Singaraju, S., & Slade, B. (2019) · Behaviour and Information Technology · doi:10.1080/0144929x.2019.1690046 · Cited by 47
Park, Y., Chang, H., Lee, M. H., & Lee, S. H. (2019) · BMC Geriatrics · doi:10.1186/s12877-019-1227-7 · Cited by 47
McGinn, C., Bourke, E., Murtagh, A., Donovan, C., Lynch, P., Cullinan, M. F., & Kelly, K. (2020) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-019-01051-9 · Cited by 46
Bradwell, H. L., Winnington, R., Thill, S., & Jones, R. B. (2020) · BMC Geriatrics · doi:10.1186/s12877-020-01641-5 · Cited by 44
Desires for active ageing technology
Angeli, A. D., Jovanovic, M., McNeill, A. R., & Coventry, L. (2020) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2020.102412 · Cited by 40
An integrated model for predicting pupils’ acceptance of artificially intelligent robots as teachers
Chen, S., Qiu, S., Li, H., Zhang, J., Wu, X., Zeng, W., & Huang, F. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11601-2 · Cited by 39
Research Hotspots and Trends of Social Robot Interaction Design: A Bibliometric Analysis
Wang, J., Chen, Y., Huo, S., Mai, L., & Jia, F. (2023) · Sensors · doi:10.3390/s23239369 · Cited by 37
Blaurock, M., Čaić, M., Okan, M., & Henkel, A. P. (2022) · International Journal of Consumer Studies · doi:10.1111/ijcs.12808 · Cited by 41
Schüssler, S., Zuschnegg, J., Paletta, L., Fellner, M., Lodron, G., Steiner, J., Pansy-Resch, S., Lammer, L., Prodromou, D., Brunsch, S., et al. (2019) · JMIR Research Protocols · doi:10.2196/14927 · Cited by 37
The Influence of Feedback Type in Robot-Assisted Training
Akalın, N., Kristoffersson, A., & Loutfi, A. (2019) · Multimodal Technologies and Interaction · doi:10.3390/mti3040067 · Cited by 37
Robotics to support aging in place
Mois, G., & Beer, J. M. (2020) · Living with Robots · doi:10.1016/b978-0-12-815367-3.00003-7 · Cited by 36
Chen, K., LOU, V. W. Q., & Lo, S. S. C. (2021) · Applied Ergonomics · doi:10.1016/j.apergo.2021.103381 · Cited by 37
User Requirements for Inclusive Technology for Older Adults
Jovanovic, M., Angeli, A. D., McNeill, A. R., & Coventry, L. (2021) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2021.1921365 · Cited by 35
Older adult perspectives on emotion and stigma in social robots
Dosso, J. A., Kailley, J. N., Guerra, G. K., & Robillard, J. M. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1051750 · Cited by 35
Dembovski, A., Amitai, Y., & Levy‐Tzedek, S. (2022) · Frontiers in Rehabilitation Sciences · doi:10.3389/fresc.2021.793233 · Cited by 36
He, Y., He, Q., & Liu, Q. (2022) · Journal of Healthcare Engineering · doi:10.1155/2022/6334732 · Cited by 35
Lim, S., & Kim, M. (2025) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2025.104259 · Cited by 46
Koh, W. Q., Whelan, S., Heins, P., Casey, D., Toomey, E. C., & Dröes, R. (2021) · JMIR Aging · doi:10.2196/29224 · Cited by 34
Healthcare robots and human generations: Consequences for nursing and healthcare
Betriana, F., Tanioka, R., Gunawan, J., & Locsin, R. C. (2022) · Collegian Journal of the Royal College of Nursing Australia · doi:10.1016/j.colegn.2022.01.008 · Cited by 33
Göngör, F., & Tutsoy, Ö. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2342101 · Cited by 38
Hurtado, L. C., Viñas, P. F., Zalama, E., Gómez‐García‐Bermejo, J., Delgado, J. M., & García, B. V. (2021) · Healthcare · doi:10.3390/healthcare9081067 · Cited by 32
Co-design and Robots: A Case Study of a Robot Dog for Aging People
Leong, T. W., & Johnston, B. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-47437-3_69 · Cited by 31
Babamiri, M., Heidarimoghadam, R., Ghasemi, F., Tapak, L., & Mortezapour, A. (2022) · PLoS ONE · doi:10.1371/journal.pone.0268942 · Cited by 30
Co-creation of an assistive robot for independent living: lessons learned on robot design
Fiorini, L., Tabeau, K., D’Onofrio, G., Coviello, L., de Mul, M., Sancarlo, D., Fabbricotti, I. N., & Cavallo, F. (2019) · International Journal on Interactive Design and Manufacturing (IJIDeM) · doi:10.1007/s12008-019-00641-z · Cited by 30
Wamba, S. F., de Queiroz, M. M., & Hamzi, L. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122912 · Cited by 31
Elderly’s acceptance of companion robots from the perspective of user factors
Huang, T., & Huang, C. (2019) · Universal Access in the Information Society · doi:10.1007/s10209-019-00692-9 · Cited by 28
Turjamaa, R., Kapanen, S., & Kangasniemi, M. K. (2020) · Geriatric Nursing · doi:10.1016/j.gerinurse.2020.02.005 · Cited by 28
Werner, C., Kardaris, N., Koutras, P., Zlatintsi, A., Maragos, P. A., Bauer, J. M., & Hauer, K. A. (2019) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2019.103996 · Cited by 28
Conversational Interfaces: Devices, Wearables, Virtual Agents, and Robots
McTear, M., Callejas, Z., & Griol, D. (2016) · Springer eBooks · doi:10.1007/978-3-319-32967-3_13 · Cited by 26
Could Robots Help Older People with Age-Related Nutritional Problems? Opinions of Potential Users
Łukasik, S., Tobis, S., Wieczorowska–Tobis, K., & Suwalska, A. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15112535 · Cited by 26
Using Living Labs to Explore Needs and Solutions for Older Adults With Dementia: Scoping Review
Verloo, H., Lorette, A., Amoussou, J. R., Pélichy, E. G. D., Queirós, A. M., von Gunten, A., & Perruchoud, É. (2021) · JMIR Aging · doi:10.2196/29031 · Cited by 29
Tobis, S., Cylkowska-Nowak, M., Wieczorowska–Tobis, K., Pawlaczyk, M., & Suwalska, A. (2017) · Occupational Therapy International · doi:10.1155/2017/9592405 · Cited by 25
Reinhardt, D., Khurana, M., & Acosta, L. H. (2021) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2021.101397 · Cited by 25
Tobis, S., Piasek-Skupna, J., Cylkowska-Nowak, M., & Suwalska, A. (2022) · Sensors · doi:10.3390/s22051717 · Cited by 25
Shin, M. H., McLaren, J. E., Ramsey, A., Sullivan, J. L., & Moo, L. R. (2022) · JMIR Aging · doi:10.2196/32322 · Cited by 25
Vargas, A. M., Cominelli, L., Dell’Orletta⋄, F., & Scilingo, E. P. (2021) · Frontiers in Computer Science · doi:10.3389/fcomp.2020.591164 · Cited by 25
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Madi, M., Nielsen, S., Schweitzer, M., Siebert, M., Körner, D., Langensiepen, S., Stephan, A., & Meyer, G. (2024) · BMC Nursing · doi:10.1186/s12912-024-01849-5 · Cited by 23
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Shao, M., Pham-Hung, M., Alves, S. F. D. R., Snyder, M., Eshaghi, K., Benhabib, B., & Nejat, G. (2023) · Robotics · doi:10.3390/robotics12010009 · Cited by 24
Haltaufderheide, J., Lucht, A., Strünck, C., & Vollmann, J. (2023) · Science and Engineering Ethics · doi:10.1007/s11948-022-00419-9 · Cited by 27
Conde, M., Mikhailova, V., & Döring, N. M. (2024) · International Journal of Social Robotics · doi:10.1007/s12369-024-01143-z · Cited by 22
Wright, J. D. (2021) · Innovation The European Journal of Social Science Research · doi:10.1080/13511610.2021.1909460 · Cited by 21
Metadata
- Authors
- Wu, Y.-H., Wrobel, J., Cornuet, M., Kerhervé, H., Damnée, S., & Rigaud, A.-S.
- Affiliations
- Assistance Publique – Hôpitaux de Paris (FR)
- Corresponding author
- Wu, Ya-Huei
- Venue
- Clinical Interventions in Aging
- Publisher
- Informa UK Limited
- Published
- 2014-05
- Volume
- 9
- Pages
- 801
- ISSN
- 1176-9092 (ISSN-L)
- 1178-1998
- PMC
- PMC4020879
- OpenAlex
- W2060200729
- Cited by
- 261
- References
- 29
- Citations by year
- 2026: 18 · 2025: 30 · 2024: 24 · 2023: 27 · 2022: 39 · 2021: 36 · 2020: 25 · 2019: 26 · 2018: 14 · 2017: 8 · 2016: 9 · 2015: 5
- FWCI
- 10.88
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Clinical Interventions in Aging (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Agence Nationale de la Recherche (ANR-09-TECS-0012)
- Caisse nationale de solidarité pour l'autonomie
- Direction Générale de l’Armement
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Health Sciences › Medicine › Geriatrics and Gerontology › Technology Use by Older Adults
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Keywords
- assistive robots, robot acceptance, older adults, mild cognitive impairment, human-robot interaction, living labs, intention to use, social influence, stigmatization, universal design, technology adoption barriers
- MeSH terms
- Activities of Daily Living, Aged, Aged, 80 and over, Attitude to Computers, Female, Humans, Interviews as Topic, Male, Surveys and Questionnaires, Robotics, Self-Help Devices, User-Computer Interface, Focus Groups, Cognitive Dysfunction
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