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Wearable Technologies: Acceptance Model for Smartwatch Adoption Among Older Adults

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12207))

Abstract

Wrist-worn wearable technologies such as smartwatches are seen to be one of the breakthrough devices that would help older adults age successfully. However, to date, there is still a lack of systematic evaluation of smartwatch adoption for older adults. Thus, in order to gain a better understanding of older adults’ attitude towards the acceptance of wearable technologies, a user acceptance model was proposed by extending the previously validated Technology Acceptance Model (TAM). A 26-item Likert-type questionnaire was administered to 76 older adults, aged 50 to 74, following the actual demonstration of the usage and features of two smartwatches (Samsung Galaxy Watch 42 mm and MiBand 4). Results reveal that prior experience, affective quality and technology-related anxiety affected older adults’ perception of ease of use. While social support impacted their attitude, accessibility had an effect on their intention to use the smartwatch. These results provide a good insight with regards to the acceptability factors for smartwatch adoption among older adults.

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References

  • Barnard, Y., Bradley, M.D., Hodgson, F., Lloyd, A.D.: Learning to use new technologies by older adults: perceived difficulties, experimentation behaviour and usability. Comput. Hum. Behav. 29(4), 1715–1724 (2013)

    Article  Google Scholar 

  • Bajaj, A., Nidumolu, S.R.: A feedback model to understand information system usage. Inf. Manag. 33(4), 213–224 (1998)

    Article  Google Scholar 

  • Brown, S.A., Venkatesh, V.: Model of adoption of technology in households: a baseline model test and extension incorporating household life cycle. MIS Q. 399–426 (2005)

    Google Scholar 

  • Conci, M., Pianesi, F., Zancanaro, M.: Useful, social and enjoyable: mobile phone adoption by older people. In: Gross, T., et al. (eds.) INTERACT 2009. LNCS, vol. 5726, pp. 63–76. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03655-2_7

    Chapter  Google Scholar 

  • Cooper, C., et al.: The impact of wearable motion sensing technology on physical activity in older adults. Exp. Gerontol. 112, 9–19 (2018)

    Article  Google Scholar 

  • Czaja, S.J., et al.: Factors predicting the use of technology: findings from the center for research and education on aging and technology enhancement (CREATE). Psychol. Aging 21(2), 333 (2006)

    Article  Google Scholar 

  • Davis, F.D.: User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. Int. J. Man Mach. Stud. 38(3), 475–487 (1993)

    Article  Google Scholar 

  • Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology: a comparison of two theoretical models. Manag. Sci. 35(8), 982–1003 (1989)

    Article  Google Scholar 

  • Disztinger, P., Schlögl, S., Groth, A.: Technology acceptance of virtual reality for travel planning. In: Schegg, R., Stangl, B. (eds.) Information and Communication Technologies in Tourism 2017, pp. 255–268. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-51168-9_19

    Chapter  Google Scholar 

  • Edmunds, R., Thorpe, M., Conole, G.: Student attitudes towards and use of ICT in course study, work and social activity: a technology acceptance model approach. Br. J. Edu. Technol. 43(1), 71–78 (2012)

    Article  Google Scholar 

  • Harbich, S., Auer, S.: Rater bias: the influence of hedonic quality on usability questionnaires. In: Costabile, M.F., Paternò, F. (eds.) INTERACT 2005. LNCS, vol. 3585, pp. 1129–1133. Springer, Heidelberg (2005). https://doi.org/10.1007/11555261_121

    Chapter  Google Scholar 

  • Heinz, M., et al.: Perceptions of technology among older adults. J. Gerontol. Nurs. 39(1), 42–51 (2013)

    Article  Google Scholar 

  • Joo, J., Sang, Y.: Exploring Koreans’ smartphone usage: an integrated model of the technology acceptance model and uses and gratifications theory. Comput. Hum. Behav. 29(6), 2512–2518 (2013)

    Article  Google Scholar 

  • Kim, K.J., Shin, D.H.: An acceptance model for smart watches: Implications for the adoption of future wearable technology. Internet Research 25(4), 527–541 (2015)

    Article  Google Scholar 

  • Kim, K.J., Sundar, S.S.: Does screen size matter for smartphones? Utilitarian and hedonic effects of screen size on smartphone adoption. Cyberpsychol. Behav. Soc. Networking 17(7), 466–473 (2014)

    Article  Google Scholar 

  • Lee, C., Coughlin, J.F.: PERSPECTIVE: older adults’ adoption of technology: an integrated approach to identifying determinants and barriers. J. Prod. Innov. Manag. 32(5), 747–759 (2015)

    Article  Google Scholar 

  • Lewis, J.E., Neider, M.B.: Designing wearable technology for an aging population. Ergon. Des. 25(3), 4–10 (2017)

    Google Scholar 

  • Masrom, M.: Technology acceptance model and e-learning. Technology 21(24), 81 (2007)

    Google Scholar 

  • McCreadie, C., Tinker, A.: The acceptability of assistive technology to older people. Ageing Soc. 25(1), 91–110 (2005)

    Article  Google Scholar 

  • Mercer, K., Giangregorio, L., Schneider, E., Chilana, P., Li, M., Grindrod, K.: Acceptance of commercially available wearable activity trackers among adults aged over 50 and with chronic illness: a mixed-methods evaluation. JMIR mHealth and uHealth 4(1), e7 (2016). https://doi.org/10.2196/mhealth.4225

    Article  Google Scholar 

  • Mitzner, T.L., Boron, J.B., Fausset, C.B., et al.: Older adults talk technology: technology usage and attitudes. Comput Human Behav. 26(6), 1710–1721 (2010)

    Article  Google Scholar 

  • Muchna, A., Najafi, B., Wendel, C.S., Schwenk, M., Armstrong, D.G., Mohler, J.: Foot problems in older adults: associations with incident falls, frailty syndrome, and sensor-derived gait, balance, and physical activity measures. J. Am. Podiatr. Med. Assoc. 108(2), 126–139 (2018)

    Article  Google Scholar 

  • Niemelä-Nyrhinen, J.: Baby boom consumers and technology: shooting down stereotypes. J. Consum. Mark. (2007)

    Google Scholar 

  • Oetting, E.R.: Manual for Oetting’s Computer Anxiety Scale (COMPAS). Rocky Mountain Behavioral Science Institute (1983)

    Google Scholar 

  • Peek, S.T., Wouters, E.J., van Hoof, J., Luijkx, K.G., Boeije, H.R., Vrijhoef, H.J.: Factors influencing acceptance of technology for aging in place: a systematic review. Int. J. Med. Inform. 83(4), 235–248 (2014)

    Article  Google Scholar 

  • Phang, C.W.J., Sutano, A., Kankanhalli, L., Yan, B.C.Y., Teo, H.H.: Senior citizens’ acceptance of informations systems: a study in the context of e-Government services. IEEE Trans. Eng. Manage. 53, 555–569 (2006)

    Article  Google Scholar 

  • Piwek, L., Ellis, D.A., Andrews, S., Joinson, A.: The rise of consumer health wearables: promises and barriers. PLoS Med. 13(2), e1001953 (2016)

    Article  Google Scholar 

  • Quan-Hasse, A., Williams, C., Kicevski, M., Elueze, I., Wellman, B.: Dividing the grey divide: Deconsructing myths about older adults’ online activities, skills, and attitudes. American Behavioral Scientist 62(9), 1207–1228 (2018)

    Article  Google Scholar 

  • Saadé, R.G., Kira, D.: Mediating the impact of technology usage on perceived ease of use by anxiety. Comput. Educ. 49(4), 1189–1204 (2007)

    Article  Google Scholar 

  • Saner, H.: Wearable sensors for assisted living in elderly people. Front. ICT 5, 1 (2018)

    Article  Google Scholar 

  • Schulz, R., Wahl, H.W., Matthews, J.T., De Vito Dabbs, A., Beach, S.R., Czaja, S.J.: Advancing the aging and technology agenda in gerontology. Gerontologist 55(5), 724–734 (2014)

    Article  Google Scholar 

  • Tanriverdi, H., Iacono, C.S.: Toy or useful technology?: the challenge of diffusing telemedicine in three boston hospitals. In: Success and Pitfalls of Information Technology Management, pp. 1–13. IGI Global (1999)

    Google Scholar 

  • The Best Senior Wearables and Trackers (2018). https://smartwatches.org/learn/best-senior-wearables-gps-trackers/. Accessed 10 Nov 2018

  • Tsai, T.H., Lin, W.Y., Chang, Y.S., Chang, P.C., Lee, M.Y.: Technology anxiety and resistance to change behavioral study of a wearable cardiac warming system using an extended TAM for older adults. PLoS ONE 15(1), e0227270 (2020)

    Article  Google Scholar 

  • United Nations, Department of Economic and Social Affairs, Population Division. World Population Ageing 2017 - Highlights (ST/ESA/SER.A/397) (2017)

    Google Scholar 

  • Venkatesh, V.: Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf. Syst. Res. 11(4), 342–365 (2000)

    Article  Google Scholar 

  • Wixom, B.H., Todd, P.A.: A theoretical integration of user satisfaction and technology acceptance. Inf. Syst. Res. 16(1), 85–102 (2005)

    Article  Google Scholar 

  • Yanagisawa, H.: Kansei quality in product design. In: Fukuda, S. (ed.) Emotional engineering, pp. 289–310. Springer, London (2011). https://doi.org/10.1007/978-1-84996-423-4_16

    Chapter  Google Scholar 

  • Zhang, P., Li, N.: The importance of affective quality. Commun. ACM 48(9), 105–108 (2005)

    Article  Google Scholar 

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Correspondence to May Jorella S. Lazaro .

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Lazaro, M.J.S., Lim, J., Kim, S.H., Yun, M.H. (2020). Wearable Technologies: Acceptance Model for Smartwatch Adoption Among Older Adults. In: Gao, Q., Zhou, J. (eds) Human Aspects of IT for the Aged Population. Technologies, Design and User Experience. HCII 2020. Lecture Notes in Computer Science(), vol 12207. Springer, Cham. https://doi.org/10.1007/978-3-030-50252-2_23

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  • DOI: https://doi.org/10.1007/978-3-030-50252-2_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50251-5

  • Online ISBN: 978-3-030-50252-2

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