Domestic Robots for Homecare: A Technology Acceptance Perspective

  • Martina ZiefleEmail author
  • André Calero Valdez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10297)


In times of the demographic change and the increasing need of novel concepts to meet the requirements of older adults’ care in the near future, health care robots could be a potent solution to meet shortcomings in the health care sector. Even though the potential of robotic home care assistance is promising, the question if older persons would accept a robotic assistance at home is still underexplored. Adopting a three-step procedure, older adults’ perceptions towards home care robots are empirically explored. In a first step, focus groups were accomplished to understand older persons’ perceptions on benefits and barriers. Second, a survey study was applied to determine acceptance criteria, the perceived usefulness and the extent and types of concerns toward a domestic robot in homecare. Finally, in a further survey study, specific care situations in the home care settings had to be evaluated in a third study, thereby comparing preferences for a human care persons vs. a robotic care assistant. Outcomes reveal both, age-sensitive as well as age-insensitive findings. While overall a positive attitude towards home care robots was found, serious concerns in terms of fear of loss of control and connection to family members are prevailing. Outcomes contribute to an understanding of social factors in the development and implementation of accepted home care solutions and might be helpful to develop age-sensitive information and communication concepts.


Domestic robots Technology acceptance Demographic change Older adults User centered design Smart home 



We would like to thank the following students for conducting the survey studies: Anna Chatzopoulos, Marcel Derichs, Vi Anh Do, Theresa Eichhorn, Patrick Halbach, Christian Henn, Corinna Körner, Alexander Kwiatkowski, Dennis Lohse, Vivian Lotz, Dirk Nettelnbreker, Lorena Niebuhr, Oliver Oschmann, Hava Osmanbeyoglu, Yulia Ponomarenko, Nina Rußkamp, and Valerie Scharmer. In addition, authors thank Lisa Schwier, Anais Habermann, Sylvia Kowalewski and Carola Caesar for supporting this research. The authors would like to thank the German Research Foundation DFG for the kind support within the Cluster of Excellence “Integrative Production Technology for High-Wage Countries”.


  1. 1.
    Salmond, S.W., Echevarria, M.: Healthcare transformation and changing roles for nursing. Orthop. Nurs. 36(1), 12 (2017)CrossRefGoogle Scholar
  2. 2.
    Holzinger, A., Röcker, C., Ziefle, M.: From smart health to smart hospitals. In: Holzinger, A., Röcker, C., Ziefle, M. (eds.) Smart Health. LNCS, vol. 8700, pp. 1–20. Springer, Cham (2015). doi: 10.1007/978-3-319-16226-3_1 Google Scholar
  3. 3.
    Leonhardt, S.: Personal healthcare devices. In: Mekherjee, S., et al. (eds.) Malware: Hardware Technology Drivers of Ambient Intelligence, pp. 349–370. Springer, Dordrecht (2006)Google Scholar
  4. 4.
    Demiris, G., Hensel, B.K., Skubic, M., Rantz, M.: Senior residents’ perceived need of and preferences for “smart home” sensor technologies. Int. J. Technol. Assess. Health Care 24, 120–124 (2008)CrossRefGoogle Scholar
  5. 5.
    Gaul, S., Ziefle, M.: Smart home technologies: insights into generation-specific acceptance motives. In: Holzinger, A., Miesenberger, K. (eds.) HCI for eInclusion, pp. 321–332. Springer, Heidelberg (2009)Google Scholar
  6. 6.
    Kleinberger, T., Becker, M., Ras, E., Holzinger, A., Müller, P.: Ambient intelligence in assisted living: enable elderly people to handle future interfaces. In: Stephanidis, C. (ed.) UAHCI 2007. LNCS, vol. 4555, pp. 103–112. Springer, Heidelberg (2007). doi: 10.1007/978-3-540-73281-5_11 CrossRefGoogle Scholar
  7. 7.
    Ziefle, M., Röcker, C.: Acceptance of pervasive healthcare systems: a comparison of different implementation concepts. In: 4th ICST Conference on Pervasive Computing Technologies for Healthcare and Workshop User-Centred-Design of Pervasive Health Applications (UCD-PH 2010) (2010)Google Scholar
  8. 8.
    Mynatt, E.D., Rogers, W.A.: Developing technology to support the functional independence of older adults. Ageing Int. 27(1), 24–41 (2002)CrossRefGoogle Scholar
  9. 9.
    Meyer, S., Mollenkopf, H.: Home technology, smart homes, and the aging user. In: Schaie, K.W., Wahl, H.-W., Mollenkopf, H., Oswald, F. (eds.) Aging Independently: Living Arrangements and Mobility. Springer, Heidelberg (2003)Google Scholar
  10. 10.
    Mynatt, E.D., Melenhorst, A.-S., Fisk, A.D., Rogers, W.A.: Aware technologies for aging in place: understanding user needs and attitudes. Pervasive Comput. IEEE 20(3), 36–41 (2004)CrossRefGoogle Scholar
  11. 11.
    Warren, S., Craft, R.L.: Designing smart health care technology into the home of the future. In: Engineering in Medicine and Biology, vol. 2, p. 677 (1999).
  12. 12.
    Weeks, L.E., Branton, O., Nilsson, T.: The influence of the family on the future housing preferences of seniors in Canada. Hous. Care Support 8(2), 29–34 (2005)CrossRefGoogle Scholar
  13. 13.
    Ziefle, M., Schaar, A.K.: Technology acceptance by patients: empowerment and stigma. In: Handbook of Smart Homes, Health Care and Well-Being, pp. 167–177 (2017)Google Scholar
  14. 14.
    Lalou, S.: Identity, social status, privacy and face-keeping in the digital society. J. Soc. Sci. Inf. 47(3), 299–330 (2008)CrossRefGoogle Scholar
  15. 15.
    Necheles, T.: Standards of medical care: how does an innovative medical procedure become accepted. Med. Health Care 10, 15–18 (1982)Google Scholar
  16. 16.
    Zimmer, Z., Chappell, N.L.: Receptivity to new technology among older adults. Disabil. Rehabil. 21, 222–230 (1999)CrossRefGoogle Scholar
  17. 17.
    Wilkowska, W., Ziefle, M.: Privacy and data security in e-health: requirements from users’ perspective. Health Inf. J. 18(3), 191–201 (2012)CrossRefGoogle Scholar
  18. 18.
    Bedaf, S., Huijnen, C., Heuvel, R.V.D., Witte, L.D.: Robots supporting care for elderly people. In: Robotic Assistive Technologies: Principles and Practice, pp. 309–332. CRC Press (2017)Google Scholar
  19. 19.
    Broadbent, E., Stafford, R., MacDonald, B.: Acceptance of healthcare robots for the older population: review and future directions. Int. J. Soc. Robot. 1(4), 319 (2009)CrossRefGoogle Scholar
  20. 20.
    Broekens, J., Heerink, M., Rosendal, H.: Assistive social robots in elderly care: a review. Gerontechnology 8(2), 94–103 (2009)CrossRefGoogle Scholar
  21. 21.
    Karabegović, I., Doleček, V.: The role of service robots and robotic systems in the treatment of patients in medical institutions. In: Hadžikadić, M., Avdaković, S. (eds.) Advanced Technologies, Systems, and Applications. LNNS, vol. 3, pp. 9–25. Springer, Cham (2017). doi: 10.1007/978-3-319-47295-9_2 CrossRefGoogle Scholar
  22. 22.
    Fischinger, D., Einramhof, P., Papoutsakis, K., Wohlkinger, W., Mayer, P., Panek, P., Vincze, M.: Hobbit, a care robot supporting independent living at home: first prototype and lessons learned. Robot. Auton. Syst. 75, 60–78 (2016)CrossRefGoogle Scholar
  23. 23.
    Graf, B., Hans, M., Schraft, R.D.: Care-o-bot II—development of a next generation robotic home assistant. Auton. Robots 16(2), 193–205 (2004)CrossRefGoogle Scholar
  24. 24.
    Pollack, M.E., Engberg, S., Matthews, J.T., Thrun S, Brown, L., Colbry, D., Orosz, C., Peintner, B., Ramakrishnan, S., Dunbar-Jacob, J., Mc-Carthy, C., Montemerlo, M., Pineau, J., Roy, N.: Pearl: a mobile robotic assistant for the elderly. In: AAAI Workshop on Automation as Eldercare, Edmonton, Canada (2002)Google Scholar
  25. 25.
    Tamura, T., Yonemitsu, S., Itoh, A., Oikawa, D., Kawakami, A., Higashi, Y., Fujimooto, T., Nakajima, K.: Is an entertainment robot useful in the care of elderly people with severe dementia? J. Gerontol. Biol. Med. Sci. 59, M83–M85 (2004)CrossRefGoogle Scholar
  26. 26.
    Banks, M.R., Willoughby, L.M., Banks, W.A.: Animal-assisted therapy and loneliness in nursing homes: use of robotic versus living dogs. J. Am. Med. Dir. Assoc. 9, 173–177 (2008)CrossRefGoogle Scholar
  27. 27.
    Stiehl, W.D., Lieberman, J., Breazeal, C., Basel, L., Cooper, R., Knight, H., Lalla, L., Maymin, A., Purchase, S.: The huggable: a therapeutic robotic companion for relational, affective touch. In: Proceedings of the 3rd IEEE Consumer Communications and Networking Conference, Las Vegas, Nevada, pp. 1290–1291 (2006)Google Scholar
  28. 28.
    Mutlu, B., Osman, S., Forlizzi, J., Hodgins, J., Kiesler, S.: Task structure and user attributes as elements of human–robot interaction design. In: Proceedings of 15th IEEE International Symposium Robot Human Interactive Communication, RO-MAN 2006, p. 74 (2006)Google Scholar
  29. 29.
    Kuo, I.H., Rabindran, J.M., Broadbent, E., Lee, Y.I., Kerse, N., Stafford, R.MQ., MacDonald, B.A.: Age and gender factors in user acceptance of healthcare robots. In: The 18th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2009, pp. 214–219. IEEE (2009)Google Scholar
  30. 30.
    Young, J.E., Hawkins, R., Sharlin, E., Igarashi, T.: Toward acceptable domestic robots: applying insights from social psychology. Int. J. Soc. Robot. 1(1), 95 (2009)CrossRefGoogle Scholar
  31. 31.
    Beer, J.M., Smarr, C.A., Chen, T.L., Prakash, A., Mitzner, T.L., Kemp, C.C., Rogers, W.A.: The domesticated robot: design guidelines for assisting older adults to age in place. In: Proceedings of the Seventh Annual ACM/IEEE International Conference on Human-Robot Interaction, pp. 335–342. ACM (2012)Google Scholar
  32. 32.
    Parette, P., Scherer, M.: Assistive technology use and stigma. Educ. Train. Develop. Disabil. 39(3), 217–226 (2004)Google Scholar
  33. 33.
    Dijkers, M.I., deBear, P.C., Erlandson, R.F., Kristy, K., Geer, D.M., Nichols, A.: Patient and staff acceptance of robotic technology in occupational therapy: a pilot study. J. Rehabil. Res. Dev. 28, 33–44 (1991)CrossRefGoogle Scholar
  34. 34.
    Broadbent, E., Tamagawa, R., Patience, A., Knock, B., Kerse, N., Day, K., MacDonald, B.A.: Attitudes towards health-care robots in a retirement village. Australas. J. Ageing 31(2), 115–120 (2012)CrossRefGoogle Scholar
  35. 35.
    Heerink, M.:. Exploring the influence of age, gender, education and computer experience on robot acceptance by older adults. In: Proceedings of the 6th International Conference on Human-Robot Interaction, pp. 147–148. ACM (2011)Google Scholar
  36. 36.
    Flandorfer, P.: Population ageing and socially assistive robots for elderly persons: the importance of sociodemographic factors for user acceptance. Int. J. Popul. Res. (2012)Google Scholar
  37. 37.
    Smarr, C.A., Prakash, A., Beer, J.M., Mitzner, T.L., Kemp, C.C., Rogers, W.A.: Older adults’ preferences for and acceptance of robot assistance for everyday living tasks. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 56, no. 1, pp. 153–157. SAGE Publications, Los Angeles (2012) Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Human-Computer Interaction CenterRWTH Aachen UniversityAachenGermany

Personalised recommendations