User-Specific Concepts of Aging – A Qualitative Approach on AAL-Acceptance Regarding Ultrasonic Whistles

  • Hannah BiermannEmail author
  • Simon Himmel
  • Julia Offermann-van Heek
  • Martina Ziefle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10927)


Against the background of demographic change, today’s society is getting increasingly older. In order to handle growing care needs and shortages of skilled workers, ambient assisted living (AAL) technologies provide prevention and rehabilitation measures which facilitate aging in place and relieve caregivers. In this context, ultrasonic whistles could represent an innovative assistance system for home automation, safety prevention, positioning, and motion analysis. However, the acceptance of AAL-technologies is challenging due to perceived restrictions, e.g., on privacy and autonomy, and depends on individual attitudes, demands, and concerns. As health impairments and care dependency increase with age, research focus is set on age-related user factors. We examined user-specific concepts of aging in relation to the assessment of ultrasonic whistles in home care. For this purpose, semi-structured interviews and a scenario-based ground plan interaction were conducted. Results indicate that particularly positive or negative associations with aging affect AAL-acceptance, strongly related to issues of quality of life, active aging, social integration, dealing with change, health, and care dependency. Regarding trade-offs between perceived benefits and barriers, users with positive concepts of aging consider AAL as relief to maintain autonomy, ensure safety prevention, and facilitate everyday life whereas users with negative concepts of aging express concerns about dependency on technology, loss of control, restrictions on privacy, and data security. The findings contribute to an understanding of -aging concepts and their relation to care assistance that can be used for age-specific communication concepts.


Ambient assisted living Aging in place Ultrasonic whistles Technology acceptance Qualitative approach 


  1. 1.
    United Nations: World Population Prospects: The 2017 Revision, Key Findings and Advance Tables. Department of Economic and Social Affairs, Population, Division. Working Paper No. ESA/P/WP/248 (2017)Google Scholar
  2. 2.
    Destatis: Older People in Germany and the EU. Federal Statistical Office of Germany, Wiesbaden (2016)Google Scholar
  3. 3.
    Pickard, L.: A growing care gap? The supply of unpaid care for older people by their adult children in England to 2032. Ageing Soc. 35, 96–123 (2015)CrossRefGoogle Scholar
  4. 4.
    Wiles, J.L., Leibing, A., Guberman, N., Reeve, J., Allen, R.E.S.: The meaning of “aging in place” to older people. Gerontologist 52(3), 357–366 (2012)CrossRefGoogle Scholar
  5. 5.
    Vasunilashorn, S., Steinman, B.A., Liebig, P.S., Pynoos, J.: Aging in place: evolution of a research topic whose time has come. J. Aging Res. 2012 (2012) (120952)Google Scholar
  6. 6.
    Augusto, J.C.: Smart homes as a vehicle for AAL. In: Augusto, J.C., Huch, M., Kameas, A., Maitland, J., McCullagh, P., Roberts, J. (eds.) Handbook of Ambient Assisted Living. Technology for Healthcare, Rehabilitation and Well-being, pp. 387–388. IOS Press, Amsterdam (2012)Google Scholar
  7. 7.
    Ibargüen, J.M., Lewandowski, R., Gerhardy, C., Schomburg, W.K.: Position detection with micro whistles. In: Transducers 2013, Barcelona, Spain, pp. 940–943. IEEE, Piscataway (2013)Google Scholar
  8. 8.
    Gerhardy, C.: Ultraschallerzeugende Mikrostrukturen für batterielose Fernbedienungen [Ultrasonic Microstructures for Remote Control without Batteries]. RWTH Aachen University, Aachen (2009)Google Scholar
  9. 9.
    Wilkowska, W., Gaul, S., Ziefle, M.: A small but significant difference – the role of gender on acceptance of medical assistive technologies. In: Leitner, G., Hitz, M., Holzinger, A. (eds.) USAB 2010. LNCS, vol. 6389, pp. 82–100. Springer, Heidelberg (2010). Scholar
  10. 10.
    Arning, K., Ziefle, M.: Different perspectives on technology acceptance: the role of technology type and age. In: Holzinger, A., Miesenberger, K. (eds.) USAB 2009. LNCS, vol. 5889, pp. 20–41. Springer, Heidelberg (2009). Scholar
  11. 11.
    Himmel, S., Ziefle, M., Arning, K.: From living space to urban quarter: acceptance of ICT monitoring solutions in an ageing society. In: Kurosu, M. (ed.) HCI 2013, Part III. LNCS, vol. 8006, pp. 49–58. Springer, Heidelberg (2013). Scholar
  12. 12.
    van Heek, J., Himmel, S., Ziefle, M.: Helpful but Spooky? Acceptance of AAL-systems contrasting user groups with focus on disabilities and care needs. In: Röcker, C., O’Donoghue, J., Ziefle, M., Maciaszek, L., Molloy, W. (eds.) Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2017), pp. 78–90. SCITEPRESS - Science and Technology Publications, Lda (2017)Google Scholar
  13. 13.
    Centers for Disease Control and Prevention: Healthy Places Terminology. Aging in Place. Accessed 21 Feb 2018
  14. 14.
    Andò, B., Siciliano, P., Marletta, V., Monteriù, A. (eds.): Ambient Assisted Living. Italian Forum 2014. Springer, Cham (2015). Scholar
  15. 15.
    Ahn, M., Kwon, H.J., Kang, J.: Supporting aging-in-place well: findings from a cluster analysis of the reasons for aging-in-place and perceptions of well-being. J. Appl. Gerontol., 1–27 (2017)Google Scholar
  16. 16.
    Oswald, F., Jopp, D., Rott, C., Wahl, H.W.: Is aging in place a resource for or risk to life satisfaction? Gerontologist 51(2), 238–250 (2010)CrossRefGoogle Scholar
  17. 17.
    Cook, D.J.: Health monitoring and assistance to support aging in place. J. Univers. Comput. Sci. 12(1), 15–29 (2006)Google Scholar
  18. 18.
    Rashidi, P., Mihailidis, A.: A survey on ambient-assisted living tools for older adults. IEEE J. Biomed. Heal. Inform. 17(3), 579–590 (2013)CrossRefGoogle Scholar
  19. 19.
    Augusto, J.C., Huch, M., Kameas, A., Maitland, J., McCullagh, P., Roberts, J., Sixsmith, A., Wichert, R. (eds.): Handbook of Ambient Assisted Living. Technology for Healthcare, Rehabilitation and Well-being. IOS Press, Amsterdam (2012)Google Scholar
  20. 20.
    Weiser, M.: The computer for the 21st century. Sci. Am. 265, 94–104 (1991)CrossRefGoogle Scholar
  21. 21.
    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, Part II. LNCS, vol. 4555, pp. 103–112. Springer, Heidelberg (2007). Scholar
  22. 22.
    Georgieff, P.: Ambient Assisted Living: Marktpotenziale IT-unterstützter Pflege für ein selbstbestimmtes Altern [Ambient Assisted Living: Market Potentials of IT-Supported Care for Active Aging]. MFG Foundation, Stuttgart (2008)Google Scholar
  23. 23.
    van Hoof, J., Demiris, G., Wouters, E.J. (eds.): Handbook of Smart Homes, Health Care and Well-being. Springer, Cham (2017). Scholar
  24. 24.
    Ziefle, M.: Ungewissheit und Unsicherheit bei der Einführung neuer Technologien [Uncertainty and Insecurity Concerning the Introduction of New Technology]. In: Jeschke, S., Jakobs, E.-M. (eds.) Exploring Uncertainty, pp. 83–104. Springer, Wiesbaden (2013). Scholar
  25. 25.
    Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology: a comparison of two theoretical models. Manage. Sci. 35(8), 982–1003 (1989)CrossRefGoogle Scholar
  26. 26.
    Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage. Sci. 46(2), 186–204 (2000)CrossRefGoogle Scholar
  27. 27.
    Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)CrossRefGoogle Scholar
  28. 28.
    Venkatesh, V., Thong, J.Y.L., Xu, X.: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 36(1), 157–178 (2012)Google Scholar
  29. 29.
    Ziefle, M., Brauner, P., van Heek, J.: Intentions to use smart textiles in AAL home environments: comparing younger and older adults. In: Zhou, J., Salvendy, G. (eds.) ITAP 2016, Part I. LNCS, vol. 9754, pp. 266–276. Springer, Cham (2016). Scholar
  30. 30.
    Himmel, S., Ziefle, M., Lidynia, C., Holzinger, A.: Older users’ wish list for technology attributes. In: Cuzzocrea, A., Kittl, C., Simos, D.E., Weippl, E., Xu, L. (eds.) CD-ARES 2013. LNCS, vol. 8127, pp. 16–27. Springer, Heidelberg (2013). Scholar
  31. 31.
    Himmel, S., Ziefle, M.: Smart home medical technologies: users’ requirements for conditional acceptance. i-com 15(1), 39–50 (2016)CrossRefGoogle Scholar
  32. 32.
    Balta-Ozkan, N., Davidson, R., Bicket, M., Whitmarsh, L.: Social barriers to the adoption of smart homes. Energy Policy 63(2013), 363–374 (2013)CrossRefGoogle Scholar
  33. 33.
    Demiris, G., Hensel, B., Skubic, M., Rantz, M.: Senior residents’ perceived need of and preferences for “smart home” sensor technologies. Int. J. Technol. Assess. Health Care 24(1), 120–124 (2008)CrossRefGoogle Scholar
  34. 34.
    Mitzner, T.L., Boron, J.B., Fausset, C.B., Adams, A.E., Charness, N., Czaja, S.J., Dijkstra, K., Fisk, A.D., Rogers, W.A., Sharit, J.: Older adults talk technology: technology usage and attitudes. Comput. Hum. Behav. 26(6), 1710–1721 (2010)CrossRefGoogle Scholar
  35. 35.
    Wilkowska, W., Ziefle, M.: User diversity as a challenge for the integration of medical technology into future smart home environments. In: Ziefle, M., Röcker, C. (eds.) Human-Centered Design of E-Health Technologies: Concepts, Methods and Applications, pp. 96–126. IGI Global, Hershey (2011)Google Scholar
  36. 36.
    Mayring, P.: Qualitative Inhaltsanalyse. Grundlagen und Techniken [Qualitative Content Analysis. Basics and Techniques], 12th edn. Beltz, Weinheim (2015)Google Scholar
  37. 37.
    Wilkowska, W., Ziefle, M.: Privacy and data security in E-health: requirements from the user’s perspective. Health Inform. J. 18(3), 191–201 (2012)CrossRefGoogle Scholar
  38. 38.
    Patton, M.Q.: Qualitative research. In: Everitt, B.S., Howell, D.C. (eds.) Encyclopedia of Statistics in Behavioral Science. Wiley, New Jersey (2005)Google Scholar
  39. 39.
    Neuman, W.L.: Social Research Methods: Quantitative and Qualitative Approaches. Allyn Bacon, Boston. Sect. Accept. Study. Int. J. Med. Inform. 81(2), 88–97 (2005)Google Scholar
  40. 40.
    Mitzner, T.L., Dijkstra, K.: E-Health for older adults: assessing and evaluating user centered design with subjective methods. In: Ziefle, M., Röcker, C. (eds.) Human-Centered Design of E-Health Technologies. Concepts, Methods and Applications, pp. 1–21. IGI Global, Hershey (2011)Google Scholar
  41. 41.
    Beier, G.: Kontrollüberzeugungen im Umgang mit Technik: Ein Persönlichkeitsmerkmal mit Relevanz für die Gestaltung technischer Systeme [Locus of Control in a Technological Context]. Humboldt-Universität zu Berlin, Berlin (2004)Google Scholar
  42. 42.
    van Heek, J., Himmel, S., Ziefle, M.: Privacy, data security, and the acceptance of AAL-systems – a user-specific perspective. In: Zhou, J., Salvendy, G. (eds.) ITAP 2017, Part I. LNCS, vol. 10297, pp. 38–56. Springer, Cham (2017). Scholar
  43. 43.
    Wilkowska, W., Ziefle, M., Himmel, S.: Perceptions of personal privacy in smart home technologies: do user assessments vary depending on the research method? In: Tryfonas, T., Askoxylakis, I. (eds.) HAS 2015. LNCS, vol. 9190, pp. 592–603. Springer, Cham (2015). Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Hannah Biermann
    • 1
    Email author
  • Simon Himmel
    • 1
  • Julia Offermann-van Heek
    • 1
  • Martina Ziefle
    • 1
  1. 1.Human-Computer Interaction CenterRWTH Aachen UniversityAachenGermany

Personalised recommendations