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Determinants of Trust in Acceptance of Medical Assistive Technologies

  • Wiktoria WilkowskaEmail author
  • Martina Ziefle
Conference paper
  • 223 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 982)

Abstract

This article examines the relevance of trust in the process of adoption of health-related technologies in home environments. In a multi-method empirical approach this topic is firstly qualitatively explored (focus groups) and in the second step the findings are quantitatively validated (online questionnaire). The research focused on different user factors (user diversity) in the evaluation of opinions and attitudes towards the relevance of trust conditions (e.g., reliability, trustworthiness, operability) and trust “mediators” (e.g., physician as a role model, scientific evidence, hands-on experience) as well as assessment of the importance and expectations regarding various features of the devices. Results showed significant effects of factors age and gender, and influences of persons’ health conditions on the examined trust indicators. In addition, analyses revealed that aspects of trust in medical assistive technology to a certain degree can be perceived as predictors of technology acceptance. Next to trust, the findings of this research underline the relevance of considering the users’ diversity in the research and design of health-supporting technologies in home environments in order to ensure their successful integration in the long term.

Keywords

Trust User diversity Technology acceptance Medical assistive technology 

Notes

Acknowledgements

The authors thank all participants for their patience and openness to share opinions on trust in medical technology. This work has been funded partly by Excellence Initiative of Germany’s Federal Ministry of Education and Research and the German Research Foundation and partly by the project PAAL, funded by the German Ministry of Research and Education (under the reference number 6SV7955).

References

  1. 1.
    Little, L., Marsh, S., Briggs, P.: Trust and privacy permissions for an ambient world. In: Trust in e-Services: Technologies, Practices and Challenges, pp. 259–292. IGI Global, Hershey (2007)Google Scholar
  2. 2.
    Li, X., Hess, T.J., Valacich, J.S.: Why do we trust new technology? A study of initial trust formation with organizational information systems. J. Strateg. Inf. Syst. 17(1), 39–71 (2008)CrossRefGoogle Scholar
  3. 3.
    Pavlou, P.A., Gefen, D.: Building effective online marketplaces with institution-based trust. Inf. Syst. Res. 15(1), 37–59 (2004)CrossRefGoogle Scholar
  4. 4.
    Lewis, J.D., Weigert, A.: Trust as a social reality. Soc. Forces 63(4), 967–985 (1985)CrossRefGoogle Scholar
  5. 5.
    Falcone, R., Castelfranchi, C.: The socio-cognitive dynamics of trust: does trust create trust? Trust Cyber-Soc. 2246, 55–72 (2001)CrossRefGoogle Scholar
  6. 6.
    Boon, S.D., Holmes, J.G.: Cooperation and Prosocial Behaviour, 1st edn. Cambridge University Press, Cambridge (1991)Google Scholar
  7. 7.
    Corritore, C.L., Kracher, B., Wiedenbeck, S.: Online trust: concepts, evolving themes, a model. Int. J. Hum. Comput. Stud. 58(6), 737–758 (2003)CrossRefGoogle Scholar
  8. 8.
    Wang, Y.D., Emurain, H.H.: An overview of online trust: concepts, elements and implications. Comput. Hum. Behav. 21, 105–125 (2005)CrossRefGoogle Scholar
  9. 9.
    Siau, K., Shen, Z.: Building customer trust in mobile commerce. Commun. ACM 46(4), 91–94 (2003)CrossRefGoogle Scholar
  10. 10.
    Sillence, E., Briggs, P., Harris, P., Fishwick, L.: A framework for understanding trust factors in web-based health advice. Int. J. Hum.0 Comput. Stud. 64(8), 697–713 (2006)CrossRefGoogle Scholar
  11. 11.
    Montague, E.N., Kleiner, B.M., Winchester, W.W.: Empirically understanding trust in medical technology. Int. J. Ind. Ergon. 39(4), 628–634 (2009)CrossRefGoogle Scholar
  12. 12.
    Wilkowska, W.: Acceptance of eHealth Technology in Home Environments: Advanced Studies on User Diversity in Ambient Assisted Living. Apprimus, Aachen (2015)Google Scholar
  13. 13.
    Montague, E.N.: Validation of a trust in medical technology instrument. Appl. Ergon. 41(6), 812–821 (2010)CrossRefGoogle Scholar
  14. 14.
    Muir, B.: Trust in automation: part 1. Theoretical issues in the study and human intervention in automated systems. Ergonomics 37, 1905–1923 (1994)CrossRefGoogle Scholar
  15. 15.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)CrossRefGoogle Scholar
  16. 16.
    Mathieson, K., Peacock, E., Chin, W.W.: Extending the technology acceptance model: the influence of perceived user resources. ACM SIGMIS Database 32(3), 86–112 (2001)CrossRefGoogle Scholar
  17. 17.
    Turner, M., Kitchenham, B., Brereton, P., Charters, S., Budgen, D.: Does the technology acceptance model predict actual use? A systematic literature review. Inf. Softw. Technol. 52(5), 463–479 (2010)CrossRefGoogle Scholar
  18. 18.
    Zmud, R.W.: Individual differences and MIS success: a review of the empirical literature. Manag. Sci. 25(10), 966–979 (1979)CrossRefGoogle Scholar
  19. 19.
    Gefen, D., Straub, D.W.: Gender differences in the perception and use of e-mail: an extension to the technology acceptance model. MIS Q. 21(4), 389–400 (1997)CrossRefGoogle Scholar
  20. 20.
    Rogers, W.A., Fisk, A.D.: Human Factors, Applied Cognition, and Aging. Lawrence Erlbaum Associates Publishers, Mahwah (2000)Google Scholar
  21. 21.
    Ong, C.-S., Lai, J.-Y.: Gender differences in perceptions and relation-ships among dominants of e-learning acceptance. Comput. Hum. Behav. 22(5), 816–829 (2006)CrossRefGoogle Scholar
  22. 22.
    Wilkowska, W., Ziefle, M.: Which factors form older adults’ acceptance of mobile information and communication technologies? In: Holzinger, A., Miesenberger, K. (eds.) USAB 2009. LNCS, vol. 5889, pp. 81–101. Springer, Heidelberg (2009).  https://doi.org/10.1007/978-3-642-10308-7_6CrossRefGoogle Scholar
  23. 23.
    Sackmann, R., Winkler, O.: Technology generations revisited: the internet generation. Gerontechnology 11(4), 493–503 (2013)CrossRefGoogle Scholar
  24. 24.
    Schumacher, P., Morahan-Martin, J.: Gender, internet and computer attitudes and experiences. Comput. Hum. Behav. 17(1), 95–110 (2001)CrossRefGoogle Scholar
  25. 25.
    Broos, A.: Gender and information and communication technologies (ICT) anxiety: male self-assurance and female hesitation. Cyber Psychol. Behav. 8(1), 21–31 (2005)CrossRefGoogle Scholar
  26. 26.
    Kowalewski, S., Wilkowska, W., Ziefle, M.: Accounting for user diversity in the acceptance of medical assistive technologies. In: Szomszor, M., Kostkova, P. (eds.) eHealth 2010. LNICST, vol. 69, pp. 175–183. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-23635-8_22CrossRefGoogle Scholar
  27. 27.
    Demiris, G., et al.: Older adults’ attitudes towards and perceptions of ‘smart home’ technologies: a pilot study. Med. Inform. Internet Med. 29(2), 87–94 (2004)CrossRefGoogle Scholar
  28. 28.
    Klack, L., Schmitz-Rode, T., Wilkowska, W., Kasugai, K., Heidrich, F., Ziefle, M.: Integrated home monitoring and compliance optimization for patients with mechanical circulatory support devices. Ann. Biomed. Eng. 39(12), 2911–2921 (2011)CrossRefGoogle Scholar
  29. 29.
    Wilkowska, W., Ziefle, M.: User diversity as a challenge for the integration of medical technology into future smart home environments. In: Human-Centered Design of E-Health Technologies, pp. 95–126. Hershey, PA (2011)Google Scholar
  30. 30.
    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. LNCS, vol. 9754, pp. 266–276. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-39943-0_26CrossRefGoogle Scholar
  31. 31.
    Wilkowska, W., Ziefle, M.: Understanding trust in medical technologies. In: Proceedings of the 4th International Conference on Communication and Information Technologies for Ageing Well and e-Health (ICT4AWE 2018), pp. 62–73. SCITEPRESS (2018)Google Scholar
  32. 32.
    Lambert, S.D., Loiselle, C.G.: Combining individual interviews and focus groups to enhance data richness. J. Adv. Nurs. 62(2), 228–237 (2008)CrossRefGoogle Scholar
  33. 33.
    Abras, C., Maloney-Krichmar, D., Preece, J.: User-centered design. In: Bainbridge, W. (ed.) Encyclopedia of Human-Computer Interaction, vol. 37, no. 4, pp. 445–456. Sage Publications, Thousand Oaks (2004)Google Scholar
  34. 34.
    Mao, J.Y., Vredenburg, K., Smith, P.W., Carey, T.: The state of user-centered design practice. Commun. ACM 48(3), 105–109 (2005)CrossRefGoogle Scholar
  35. 35.
    Cohen, J.: Statistical Power Analysis for the Behavioral Sciences. Erlbaum, Hillsdale (1988)zbMATHGoogle Scholar
  36. 36.
    Ziefle, M., Röcker, C., Holzinger, A.: Medical technology in smart homes: exploring the user’s perspective on privacy, intimacy and trust. In: IEEE 35th Annual Computer Software and Applications Conference Workshops (COMPSACW), pp. 410–415 (2011)Google Scholar
  37. 37.
    Ziefle, M., Schaar, A.K.: Gender differences in acceptance and attitudes towards an invasive medical stent. Electron. J. Health Inform. 6(2), e13 (2011)Google Scholar
  38. 38.
    Moody, H.R.: Aging: Concepts and Controversies. Pine Forge Press, Newbury Park (2006)Google Scholar
  39. 39.
    Morrow-Howell, N., Hinterlong, J., Sherraden, M.: Productive Aging: Concepts and Challenges. JHU Press, Baltimore (2001)Google Scholar
  40. 40.
    Thiede, M.: Information and access to health care: is there a role for trust? Soc. Sci. Med. 61(7), 1452–1462 (2005)CrossRefGoogle Scholar
  41. 41.
    Hallenbeck, J.L.: Intercultural differences and communication at the end of life. Prim. Care: Clin. Office Pract. 28(2), 401–413 (2001)CrossRefGoogle Scholar
  42. 42.
    Resnick, B., Gwyther, L.P., Roberto, K.A.: Resilience in Aging: Concepts, Research, and Outcomes. Springer, New York (2010).  https://doi.org/10.1007/978-1-4419-0232-0CrossRefGoogle Scholar
  43. 43.
    Hamel, L., Wu, B., Brodie, M.: Views and experiences with end-of-life medical care in the US [Internet]. Kaiser Family Foundation (2017)Google Scholar
  44. 44.
    Mechanic, D.: The functions and limitations of trust in the provision of medical care. J. Health Polit. Policy Law 23(4), 661–686 (1998)CrossRefGoogle Scholar
  45. 45.
    Wilkowska, W., Brauner, P., Ziefle, M.: Rethinking Technology development for older adults. A responsible research and innovation duty. In: Aging, Technology, and Health. Elsevier North Holland, Amsterdam (2018)Google Scholar
  46. 46.
    Stahl, B.C.: Responsible research and innovation: the role of privacy in an emerging framework. Sci. Publ. Policy 40(6), 708–716 (2013)CrossRefGoogle Scholar
  47. 47.
    Stahl, B.C., Eden, G., Jirotka, M.: Responsible research and innovation in information and communication technology: Identifying and engaging with the ethical implications of ICTs. In: Responsible Innovation, pp. 199–218 (2013)Google Scholar
  48. 48.
    Vervier, L., Zeissig, E.M., Lidynia, C., Ziefle, M.: Perceptions of digital footprints and the value of privacy. In: Proceedings of the International Conference on Internet of Things and Big Data (IoTBD 2017), pp. 80–91. SCITEPRESS (2017)Google Scholar
  49. 49.
    van Heek, J., Himmel, S., Ziefle, M.: Caregivers’ perspectives on ambient assisted living technologies in professional care contexts. In: 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2018), pp. 37–48. SCITEPRESS (2018)Google Scholar
  50. 50.
    Calero Valdez, A., Ziefle, M.: The users’ perspective on privacy trade-offs in health recommender systems. Int. J. Hum.-Comput. Stud. 121, 108–121 (2019)CrossRefGoogle Scholar
  51. 51.
    Ziefle, M., Halbey, J., Kowalewski, S.: Users’ willingness to share data in the internet: perceived benefits and caveats. In: Proceedings of the International Conference on Internet of Things and Big Data (IoTBD 2016), pp. 255–265. SCITEPRESS (2016)Google Scholar
  52. 52.
    Bowling, A., Banister, D., Sutton, S., Evans, O., Windsor, J.: A multidimensional model of the quality of life in older age. Aging Ment. Health 6(4), 355–371 (2002)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Human-Computer Interaction CenterRWTH Aachen UniversityAachenGermany

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