TY - GEN
T1 - Acceptance of mobile technology by older adults
T2 - 18th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2016
AU - Kim, Sunyoung
AU - Gajos, Krzysztof Z.
AU - Muller, Michael
AU - Grosz, Barbara J.
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/9/6
Y1 - 2016/9/6
N2 - Mobile technologies offer the potential for enhanced healthcare, especially by supporting self-management of chronic care. For these technologies to impact chronic care, they need to work for older adults, because the majority of people with chronic conditions are older. A major challenge remains: integrating the appropriate use of such technologies into the lives of older adults. We investigated how older adults would accept mobile technologies by interviewing two groups of older adults (technology adopters and non-adopters who aged 60+) about their experiences and perspectives to mobile technologies. Our preliminary results indicate that there is an additional phase, the intention to learn, and three relating factors, self-efficacy, conversion readiness, and peer support, that significantly influence the acceptance of mobile technologies among the participants, but are not represented in the existing models. With these findings, we propose a tentative theoretical model that extends the existing theories to explain the ways in which our participants came to accept mobile technologies. Future work should investigate the validity of the proposed model by testing our findings against younger people.
AB - Mobile technologies offer the potential for enhanced healthcare, especially by supporting self-management of chronic care. For these technologies to impact chronic care, they need to work for older adults, because the majority of people with chronic conditions are older. A major challenge remains: integrating the appropriate use of such technologies into the lives of older adults. We investigated how older adults would accept mobile technologies by interviewing two groups of older adults (technology adopters and non-adopters who aged 60+) about their experiences and perspectives to mobile technologies. Our preliminary results indicate that there is an additional phase, the intention to learn, and three relating factors, self-efficacy, conversion readiness, and peer support, that significantly influence the acceptance of mobile technologies among the participants, but are not represented in the existing models. With these findings, we propose a tentative theoretical model that extends the existing theories to explain the ways in which our participants came to accept mobile technologies. Future work should investigate the validity of the proposed model by testing our findings against younger people.
KW - Aging
KW - Digital health
KW - Healthcare technology
KW - Mobile technology adoption
KW - Older adults
UR - http://www.scopus.com/inward/record.url?scp=84991311766&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84991311766&partnerID=8YFLogxK
U2 - 10.1145/2935334.2935380
DO - 10.1145/2935334.2935380
M3 - Conference contribution
AN - SCOPUS:84991311766
T3 - Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2016
SP - 147
EP - 157
BT - Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2016
PB - Association for Computing Machinery, Inc
Y2 - 6 September 2016 through 9 September 2016
ER -