Browse > Article
http://dx.doi.org/10.14400/JDC.2020.18.8.201

Comprehensive Senior Technology Acceptance Model for Digital Health Devices  

Shin, Hye-Ri (Dept. of Gerontology, Kyung Hee University)
Yoon, Hee-Jeong (Dept. of Gerontology, Kyung Hee University)
Kim, Su-Kyoung (Dept. of Gerontology, Kyung Hee University)
Kim, Young-Sun (Dept. of Gerontology, Kyung Hee University)
Publication Information
Journal of Digital Convergence / v.18, no.8, 2020 , pp. 201-215 More about this Journal
Abstract
We conducted the analysis using the data of the '2019 Korean Middle and Elderly Technology Acceptance Survey' to verify the comprehensive senior technology acceptance model. In this study, we examined the significant effect the relationship between behavioral intention to use the diital health devices and perceived usefulness, perceived ease of use, gerontechnology self-efficacy, gerontechnology anxiety, facilitating conditions, attitude to life and satisfaction through the structural equation. The results of the research model are as follows. First, the usefulness and ease of use had significant effects on intention to use. Second, the self-efficacy had significant effects on the intention to use. But they had negative effect. Third, perceived usefulness, self-efficacy and anxiety had significant effects on ease of use. Lastly, self-efficacy, facilitating conditions, attitude to life and satisfaction had significant effects on perceived usefulness. These findings highlight that verified the comprehensive senior technology acceptance model in Korea.
Keywords
Comprehensive Senior Acceptance Model; Digital Health Device; Perceived Usefulness; Perceived Ease of Use; Gerontechnology Self-efficacy; Gerontechnology Anxiety;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
연도 인용수 순위
1 G. Shanko, S. Negash & T. Bandyopadhyay. (2016). Mobile Healthcare Services Adoption. International Journal of Networking and Virtual Organisations, 16(2), 143-156. DOI : 10.1504/IJNVO.2016.076485   DOI
2 S. M. Kim & C. W. Lee. (2013). Usage Intention of u-Healthcare Service Using Unified Theory of Technology Adoption and Usage. The Journal of the Korea Contents Association, 13(12), 379-388. DOI : 10.5392/JKCA.2013.13.12.379   DOI
3 S. Pan & M. Jordan-Marsh. (2010). Internet Use Intention and Adoption among Chinese Older Adults: From the Expanded Technology Acceptance Model Perspective. Computers in Human Behavior, 26(5), 1111-1119. DOI : 10.1016/j.chb.2010.03.015   DOI
4 S. K. Kim, H. R. Shin & Y. S. Kim. (2019). Accessibility to Digital Information of Middle-Aged and Elderly People, and its Impact on Life Satisfaction Level: Sequential Mediation Effects on Online Social Engagement and Online Network Activity. Journal of Digital Convergence. 17(12), 23-34. DOI : 10.14400/JDC.2019.17.12.023   DOI
5 B. S. Kim & J. M. Kim. (2009). A Study on Digital Divide Trigger Factor of Older People - Focused on Technology Acceptance Model -. Social Science Studies, 35(2), 193-222.
6 J. E. Cho. (2014). Mobile Phone Adoption by Elderly Users. Journal of Communication Science, 48(5), 211-242.
7 L. U. S. Nayak, L. Priest & A. P. White. (2010). An Application of the Technology Acceptance Model to the Level of Internet Usage by Older Adults. Universal Access in the Information Society, 9(4), 367-374. DOI : 10.1007/s10209-009-0178-8   DOI
8 S. Jin & H. C. Ahn. (2019). A Study on Wearable Healthcare Device Adoption: An Integrated Approach of UTAUT2 and MIR. The Journal of Information Systems, 28(3), 159-202. DOI : 10.5859/KAIS.2019.28.3.159   DOI
9 A. Bandura. (1986). Social Foundations of Thought and Action. New Jersey : Englewood Cliffs.
10 A. Bandura, W. H. Freeman & R. Lightsey (1999). Self-efficacy: The Exercise of Control. Journal of Cognitive Psychotherapy, 13(2), 158-166. DOI : 10.1891/0889-8391.13.2.158   DOI
11 R. J. Holden & B. T. Karsh. (2010). The Technology Acceptance Model: Its Past and its Future in Health Care. Journal of Biomedical Informatics, 43(1), 159-172. DOI : 10.1016/j.jbi.2009.07.002   DOI
12 R. L. Thompson, C. A. Higgins & J. M. Howell. (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS Quarterly, 15(1), 125-143. DOI : 10.2307/249443   DOI
13 R. P. Harte et al. (2014). Human Centered Design Considerations for Connected Health Devices for the Older Adult. Journal of Personalized Medicine, 4(2), 245-281. DOI : 10.3390/jpm4020245   DOI
14 S. H. Jeon, N. R. Park & C. C. Lee. (2011). Study on the Factors Affecting the Intention to Adopt Public Cloud Computing Service. Entrue Journal of Information Technology, 10(2), 97-112.
15 H. S. Yoo, M. Y. Kim & O. B. Kwon. (2008). A Study of Factors Influencing Ubiquitous Computing Service Acceptance. The Jounal of Society for e-Business Studies, 13(2), 117-147.
16 M. A. Jarvis, B. Sartorius & J. Chipps. (2019). Technology Acceptance of Older Persons Living in Residential Care. Information Development, 0266666919854164. DOI : 10.1177/0266666919854164
17 J. M. Werner, M. Carlson, M. Jordan-Marsh & F. Clar. (2011). Predictors of Computer Use in Community-Dwelling, Ethnically Diverse Older Adults. Human Factors, 53(5), 431-447. DOI : 10.1177/0018720811420840   DOI
18 C. W. Lee & S. H. Jang. (2012). A Study of Usage Intention on the u-Healthcare Service with Voluntariness. Journal of the Korean Operations Research and Management Science Society, 37(4), 225-238. DOI : 10.7737/JKORMS.2012.37.4.225   DOI
19 Z. Deng, X. Mo & S. Liu. (2014). Comparison of the Middle-Aged and Older Users' Adoption of Mobile Health Services in China. International journal of medical informatics, 83(3), 210-224. DOI : 10.1016/j.ijmedinf.2013.12.002   DOI
20 A. J. de Veer, J. M. Peeters, A. E. Brabers, F. G. Schellevis, J. J. J. Rademakers & A. L. Francke. (2015). Determinants of the Intention to Use e-Health by Community Dwelling Older People. BMC Health Services Research, 15(1), 103. DOI 10.1186/s12913-015-0765-8   DOI
21 E. M. Jeon & H. J. Seo. (2016). Acceptability of Service Targets for ICT-based Healthcare. Healthcare informatics research, 22(4), 333-341. DOI : 10.4258/hir.2016.22.4.333   DOI
22 Y. W. Kim, S. M. Han & K. S. Kim. (2018). Determinants of Intention to Use Digital Healthcare Service of Middle and Older Users. Information Society & Media, 19(3), 1-23.
23 S. T. An, H. N. Kang & S. D. Chung. (2018). Older Adults' Adoption of Health-Related Mobile Application : The Role of Empowerment. Journal of Public Relations, 22(6), 53-74. DOI : 10.15814/jpr.2018.22.6.53   DOI
24 S. Nikou, W. Agahari, W. Keijzer-Broers & M. D. Reuver. (2019). Digital Healthcare Technology Adoption by Elderly People: A Capability Approach Model. Telematics and Informatics, 101315. DOI : 10.1016/j.tele.2019.101315
25 J. H. Park et al. (2019). An Analysis of Cognitive Ability and Technology Acceptance Behavior for the Elderly: Towards the Use of Wearable Healthcare Devices. Journal of Information Technology Applications and Management, 26(1), 21-38. DOI : 10.21219/jitam.2019.26.1.021
26 K. Chen & A. H. S Chan. (2014). Gerontechnology Acceptance by Elderly Hong Kong Chinese: A Senior Technology Acceptance Model (STAM). Ergonomics, 57(5), 635-652. DOI : 10.1080/00140139.2014.895855   DOI
27 J. S. Lee. (2014). Digital Healthcare Platforms and Major Business Trends. [KHIDI Brief]. Sejong : Korea Institute for Health and Social Affairs
28 B. Xie. (2007). Older Chinese, the Internet, and Well-being. Care Management Journals, 8(1), 33-38. DOI : 10.1891/152109807780494122   DOI
29 S. T. M. Peek et al. (2016). Older Adults' Reasons for Using Technology While Aging in Place. Gerontology, 62(2), 226-237. DOI : 10.1159/000430949   DOI
30 P. L. Teh & C. C. Yong. (2011). Knowledge Sharing in IS Personnel: Organizational Behavior's Perspective. Journal of Computer Information Systems, 51(4), 11-21.
31 J. Li, C. C. Hsu & C. T. Lin. (2019). Leisure Participation Behavior and Psychological Well-Being of Elderly Adults: An Empirical Study of Tai Chi Chuan in China. International Journal of Environmental Research and Public Health, 16(18), 3387. DOI : 10.3390/ijerph16183387   DOI
32 M. Conci, F. Pianesi & M. Zancanaro. (2009). Useful, Social and Enjoyable: Mobile Phone Adoption by Older People. Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I, 63-76. DOI : 10.1007/978-3-642-03655-2_7
33 M. S. Lee, S. B. Hong & K. B. Suh (2019). An Analysis of Active Senior’s Leisure Smart Device Using Intention Applying Extended Technology Acceptance Model: Focusing on Leisure Engagement. The Korea Journal of Sports Science, 28(4), 183-194. DOI : 10.35159/kjss.2019.08.28.4.183   DOI
34 F. D. Davis. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340. DOI : 10.2307/249008   DOI
35 S. G. LEE. (2017). Global Digital Healthcare Technology Trends and Challenges. [Weeklytrend]. Daejeon : Institute for Information & communication Technology Planning & evaluation
36 M. j. Seo. (2017. 2. 2). Digital Healthcare, 14 Trillion Market in 2020. Sedaily. https://www.sedaily.com/NewsVIew/1OBXT61TKV
37 F. D. Davis. (1985). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Doctoral dissertation. Massachusetts Institute of Technology, Cambridge
38 F. D. Davis, R. P. Bagozzi & P. R. Warshaw. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982-1003. DOI : 10.1177/001872679204500702   DOI
39 M. Fishbein & I. Ajzen. (1977). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Journal of Business venturing, 5, 177-I89   DOI
40 S. I. Han. (2005). Determinants of the User's Intention to Use of Mobile Banking. The Journal of Society for e-Business Studies, 10(3), 135-157.
41 V. Venkatesh, M. G. Morris, G. B. Davis & F. D. Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478. DOI : 10.2307/30036540   DOI
42 Z. Zheng. (2015). User Acceptance of Mobile Healthcare Applications: An Integrated Model of UTAUT and HBM Theory. Korean Policy Sciences Review, 19(3), 203-236.
43 Accenture. (2019). Australian Seniors Ride Digital Care Wave. Ireland, Dublin : Accenture
44 R. Hoque & G. Sorwar. (2017). Understanding Factors Influencing the Adoption of mHealth by the Elderly: An Extension of the UTAUT Model. International Journal of Medical Informatics, 101, 75-84. DOI : 10.1016/j.ijmedinf.2017.02.002   DOI
45 K. H. Jeong. et al. (2017). A Survey of The Elderly, 2017. Sejong : Korea Institute for Health and Social Affairs, Ministry of Health and Welfare
46 National Health Insurance Service. (2019). 2018 Health Insurance Key Statistics. Wonju : National Health Insurance Service
47 I. K. Oh. (2019. 3. 29). Digital Health, Is There a Solution to The Aging?. The Medical News. http://www.bosa.co.kr/news/articleView.html?idxno=2102197
48 Zebra Technologies. (2017). 2022 Hospital Vision Study Report. Illinois, USA : Zebra Technologies
49 T. K. Kim & M. Choi. (2019). Older Adults' Willingness to Share Their Personal and Health Information When Adopting Healthcare Technology and Services. International Journal of Medical Informatics, 126, 86-94. DOI : 10.1016/j.ijmedinf.2019.03.010   DOI
50 Y. S. Ki, S. M. Ahn, M. G. Cho & B. G. Choi. (2019). An Analysis on Affecting Factors of Healthcare Applications Continuous Usage Intention and their Relationships. The Jounal of Society for e-Business Studies, 24(1), 49-89. DOI : 10.7838/jsebs.2019.24.1.049
51 R. Mostaghel & P. Oghazi. (2017). Elderly and Technology Tools: A Fuzzyset Qualitative Comparative Analysis. Quality & quantity, 51(5), 1969-1982. DOI : 10.1007/s11135-016-0390-6   DOI
52 J. S. Jeong, J. M. Park & K. Y. Noh. (2019). Factors Influencing Intention to Continuous Use of Mobile Healthcare Apps: The Breakdown of Perceived Ease of Use. Journal of Cybercommunication Academic Society. 36(2), 81-117.   DOI
53 M. Cimperman, M. M. Brenčič, P. Trkman & M. D. L. Stanonik. (2013). Older Adults' Perceptions of Home Telehealth Services. Telemedicine and e-Health, 19(10), 786-790. DOI : 10.1089/tmj.2012.0272   DOI
54 H. M. Kuo, C. W. Chen & C. H. Hsu. (2012). Retracted: A Study of a B2C Supporting Interface Design System for the Elderly. Human Factors and Ergonomics in Manufacturing & Service Industries, 22(6), 528-540. DOI : 10.1002/hfm.20297   DOI
55 M. A. Farage, K. W. Miller, F. Ajayi & D. Hutchins. (2012). Design Principles to Accommodate Older Adults. Global Journal of Health Science, 4(2), 2-25. DOI : 10.5539/gjhs.v4n2p2   DOI
56 R. Tenneti, D. Johnson, L. Goldenberg, R. A. Parker & F. A. Huppert. (2012). Towards a Capabilities Database to Inform Inclusive Design: Experimental Investigation of Effective Survey-based Predictors of Human-Product Interaction. Applied Ergonomics, 43(4), 713-726. DOI : 10.1016/j.apergo.2011.11.005   DOI
57 D. R. Kaufman et al. (2003). Usability in the Real World: Assessing Medical Information Technologies in Patients' Homes. Journal of Biomedical Informatics, 36(1-2), 45-60. DOI : 10.1016/S1532-0464(03)00056-X   DOI
58 E. M. Rogers. (1995). Diffusion of Innovation. New York : Free Press.
59 C. W. Lee & J. F. Coughlin. (2015). PERSPECTIVE: Older Adults' Adoption of Technology: An Integrated Approach to Identifying Determinants and Barriers. Journal of Product Innovation Management, 32(5), 747-759. DOI : 10.1111/jpim.12176   DOI
60 I. Ajzen. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. DOI : 10.1016/0749-5978(91)90020-t   DOI