Skip to main content
SpringerLink
Log in

Socially Assistive Robots in Aged Care: Expectations of Older Adults with MCI in Assisted Living Facilities and Their Caregivers

  • Published:
International Journal of Social Robotics Aims and scope Submit manuscript

Abstract

In the context of recent demographic changes and related societal challenges, socially assistive robots (SARs) are considered having the potential to support independence and care of older adults. However, little is known about the preferred SAR-features of older adults with mild cognitive impairment (MCI) residing in assisted living and their caregivers. Semi-structured interviews were conducted with two stakeholder groups: older adults with MCI and their (in)formal caregivers. Inductive thematic analysis was used to analyse the data. Forty individual semi-structured interviews were conducted with older adults with MCI (N = 30) and (in)formal caregivers (N = 10). Data revealed seven common role-expectations regarding SARs for both the older adults and caregivers: (1) companion, (2) health assistant, (3) household assistant, (4) physical assistant, (5) cognitive assistant, (6) coach, (7) leisure buddy. One additional, eighth role was identified for the caregivers, i.e. job assistant. The results of this study provide a better knowledge of the features to consider during the development process of SARs in order to maximize the perceived usefulness and hence the intention to use and actual adoption. Additionally, a feasibility analysis showed which features should have the primary focus during the further software development of an existing SAR called James® within the ReMIND-project.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. World Health Organization (WHO) (2015) World report on ageing and health. Geneva

  2. Bedaf S, Draper H, Gelderblom G-J, Sorell T, Witte L (2016) Can a service robot which supports independent living of older people disobey a command? The views of older people, informal carers and professional caregivers on the acceptability of robots. Int J Soc Robot 8:409–420

    Article  Google Scholar 

  3. Boldy D, Grenade L, Lewin G, Karol E, Burton E (2011) Older people’s decisions regarding ‘ageing in place’: a Western Australian case study. Australas J Ageing 30(3):136–142

    Article  Google Scholar 

  4. Matsumoto H, Naruse T, Sakai M, Nagata S (2016) Who prefers to age in place? Cross-sectional survey of middle-aged people in Japan. Geriatr Gerontol Int 16(5):631–637

    Article  Google Scholar 

  5. Span M, Hettinga M, Vernooij-Dassen M, Eefsting J, Smits C (2013) Involving people with dementia in the development of supportive IT applications: a systematic review. Ageing Res Rev 12(2):535–551

    Article  Google Scholar 

  6. Abdi J, Al-Hindawi A, Ng T, Vizcaychipi MP (2018) Scoping review on the use of socially assistive robot technology in elderly care. BMJ Open 8(2):e018815

    Article  Google Scholar 

  7. Beuscher LM, Fan J, Sarkar N, Dietrich MS, Newhouse PA, Miller KF et al (2017) Socially Assistive Robots: Measuring Older Adults’ Perceptions. J Gerontol Nurs 43(12):35–43

    Article  Google Scholar 

  8. Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340

    Article  Google Scholar 

  9. Venkatesh V, Morris M, Davis G, Davis F (2003) User acceptance of information technology: toward a unified view. MIS Q 27:425–478

    Article  Google Scholar 

  10. Kamin S, Lang F (2013) The subjective technology adaptivity inventory (STAI): a motivational measure of technology usage in old age. Gerontechnol Int J Fundam Asp Technol Serve Ageing Soc 12:16–25

    Google Scholar 

  11. Heerink M, Kröse B, Evers V, Wielinga B (2010) Assessing acceptance of assistive social agent technology by older adults: the Almere Model. Int J Soc Robot 2(4):361–375

    Article  Google Scholar 

  12. Pino M, Boulay M, Jouen F, Rigaud AS (2015) “Are we ready for robots that care for us?” Attitudes and opinions of older adults toward socially assistive robots. Front Aging Neurosci 7:141

    Article  Google Scholar 

  13. Bedaf S, Marti P, Amirabdollahian F, de Witte L (2018) A multi-perspective evaluation of a service robot for seniors: the voice of different stakeholders. Disabil Rehabil Assist Technol 13(6):592–599

    Article  Google Scholar 

  14. Bedaf S, Gelderblom GJ, de Witte L, Syrdal D, Lehmann H, Amirabdollahian F et al (2013) Selecting services for a service robot: evaluating the problematic activities threatening the independence of elderly persons. IEEE Int Conf Rehabil Robot Proc 2013:6650458

    Google Scholar 

  15. Bedaf S, Marti P, De Witte L (2019) What are the preferred characteristics of a service robot for the elderly? A multi-country focus group study with older adults and caregivers. Assist Technol Off J RESNA 31(3):147–157

    Article  Google Scholar 

  16. Wang RH, Sudhama A, Begum M, Huq R, Mihailidis A (2017) Robots to assist daily activities: views of older adults with Alzheimer’s disease and their caregivers. Int Psychogeriatr 29(1):67–79

    Article  Google Scholar 

  17. D’Onofrio G, Fiorini L, Hoshino H, Matsumori A, Okabe Y, Tsukamoto M et al (2019) Assistive robots for socialization in elderly people: results pertaining to the needs of the users. Aging Clin Exp Res 31(9):1313–1329

    Article  Google Scholar 

  18. Smarr CA, Prakash A, Beer JM, Mitzner TL, Kemp CC, Rogers WA (2012) Older adults’ preferences for and acceptance of robot assistance for everyday living tasks. Proc Hum Factors Ergon Soc Annu Meet Hum Factors Ergon Soc Annu Meet 56(1):153–157

    Article  Google Scholar 

  19. Chu L, Chen HW, Cheng PY, Ho P, Weng IT, Yang PL et al (2019) Identifying features that enhance older adults’ acceptance of robots: a mixed methods study. Gerontology 65(4):441–450

    Article  Google Scholar 

  20. Park YH, Chang HK, Lee MH, Lee SH (2019) Community-dwelling older adults’ needs and acceptance regarding the use of robot technology to assist with daily living performance. BMC Geriatr 19(1):208

    Article  Google Scholar 

  21. Anderson ND (2019) State of the science on mild cognitive impairment (MCI). CNS Spectr 24(1):78–87

    Article  Google Scholar 

  22. Li JQ, Tan L, Wang HF, Tan MS, Tan L, Xu W et al (2016) Risk factors for predicting progression from mild cognitive impairment to Alzheimer’s disease: a systematic review and meta-analysis of cohort studies. J Neurol Neurosurg Psychiatry 87(5):476–484

    Article  Google Scholar 

  23. Braun V, Clarke V (2006) Using thematic analysis in psychology. Qual Res Psychol 3(2):77–101

    Article  Google Scholar 

  24. Tong A, Sainsbury P, Craig J (2007) Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care J Int Soc Qual Health Care 19(6):349–357

    Article  Google Scholar 

  25. Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I et al (2005) The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc 53(4):695–699

    Article  Google Scholar 

  26. Braun V, Clarke V (2014) What can “thematic analysis” offer health and wellbeing researchers? Int J Qual Stud Health Well-being 9:26152

    Article  Google Scholar 

  27. Wu YH, Wrobel J, Cornuet M, Kerhervé H, Damnée S, Rigaud AS (2014) 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. Clin Interv Aging 9:801–811

    Article  Google Scholar 

  28. Melkas H, Hennala L, Pekkarinen S, Kyrki V (2020) Impacts of robot implementation on care personnel and clients in elderly-care institutions. Int J Med Inform 134:104041

    Article  Google Scholar 

  29. Köttl H, Mannheim I (2021) Ageism & digital technology: Policy measures to address ageism as a barrier to adoption and use of digital technology: EuroAgeism

  30. Mitzner TL, Tiberio L, Kemp CC, Rogers WA (2018) Understanding healthcare providers’ perceptions of a personal assistant robot. Gerontechnol Int J Fundam Asp Technol Serve Ageing Soc 17(1):48–55

    Google Scholar 

  31. Broadbent E, Stafford R, MacDonald B (2009) Acceptance of healthcare robots for the older population: review and future directions. Int J Soc Robot 1(4):319

    Article  Google Scholar 

  32. Law M, Sutherland C, Ahn HS, MacDonald BA, Peri K, Johanson DL et al (2019) Developing assistive robots for people with mild cognitive impairment and mild dementia: a qualitative study with older adults and experts in aged care. BMJ Open 9(9):e031937

    Article  Google Scholar 

  33. Mitzner TL, Chen TL, Kemp CC, Rogers WA (2014) Identifying the potential for robotics to assist older adults in different living environments. Int J Soc Robot 6(2):213–227

    Article  Google Scholar 

  34. Peek ST, Wouters EJ, van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJ (2014) Factors influencing acceptance of technology for aging in place: a systematic review. Int J Med Inform 83(4):235–248

    Article  Google Scholar 

  35. Sharkey A, Sharkey N (2012) Granny and the robots: ethical issues in robot care for the elderly. Ethics Inf Technol 14(1):27–40

    Article  Google Scholar 

  36. Cornelis E, Gorus E, Beyer I, Bautmans I, De Vriendt P (2017) Early diagnosis of mild cognitive impairment and mild dementia through basic and instrumental activities of daily living: development of a new evaluation tool. PLoS Med 14(3):e1002250

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the older adults and caregivers that participated so willingly in this Project. The authors are also grateful to colleagues in the ReMIND consortium (Technical University of Cluj-Napoca, Romania; Universitatea medicina si farmace Victor Babes Timisoara, Romania; Ovos Media GmbH, Austria; The Medical University of Vienna, Austria; Zora Robotics PLC, Belgium).

Funding

The ReMIND-project was funded by Active and Assisted Living (AAL) programme. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Faculty of Medicine and Health Sciences, Department of Rehabilitation Sciences, Occupational Therapy, Physiotherapy and Speech-Language Pathology/Audiology, Ghent University, Ghent, Belgium

    Maaike Van Assche, Dirk Cambier, Patrick Calders, Patrick Van Gelder & Dominique Van de Velde

  2. Section of Geriatrics, Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium

    Mirko Petrovic

  3. University of Applied Sciences, FH Campus Wien, Vienna, Austria

    Franz Werner

Authors
  1. Maaike Van Assche
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mirko Petrovic
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dirk Cambier
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Patrick Calders
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Patrick Van Gelder
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Franz Werner
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Dominique Van de Velde
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Maaike Van Assche and Dominique Van de Velde. The first draft of the manuscript was written by Maaike Van Assche and authors Mirko Petrovic, Dirk Cambier, Patrick Calders, Patrick Van Gelder and Dominique Van de Velde commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Maaike Van Assche.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical Approval

This study was approved by the ethical committee of Ghent University with registration number B670201938741.

Consent to Participate

Informed consent was obtained from all individual participants included in the study.

Consent for Publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Van Assche, M., Petrovic, M., Cambier, D. et al. Socially Assistive Robots in Aged Care: Expectations of Older Adults with MCI in Assisted Living Facilities and Their Caregivers. Int J of Soc Robotics 16, 687–698 (2024). https://doi.org/10.1007/s12369-024-01115-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12369-024-01115-3

Keywords

Search

Navigation