Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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A study on the Influence of Usage Intention of IoT Healthcare service for Elderly

노인의 IoT 기반 스마트 건강관리서비스 이용의도에 미치는 영향

  • 홍성정 (안동대학교 생명과학대학 간호학과) ;
  • 이성현 ((주)플라잉마운틴) ;
  • 김경미 (충북대학교 의과대학 간호학과)
  • Received : 2019.12.31
  • Accepted : 2020.03.20
  • Published : 2020.03.28
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Abstract

The purpose of this study was conducted to explain the intention of use of IoT (internet of things) healthcare service for elderly using TAM (Technology Acceptance Model). The exogenous variables were professional support, personalization, interaction, and convenience, The endogenous variables were usefulness and intention. Data were collected from 220 elderly residents aged 65 over in welfare center and were analyzed using structural equation modeling using AMOS 25.0. The result of this study showed that professional support and personalization did not significantly difference perceived usefulness, and there were significant differences interaction, and convenience. Futhermore, perceived usefulness influence intention of use of IoT healthcare service for elderly. IoT health care service for elderly is affected by perceived usefulness. This study systematically verified the elderly's intention of using IoT-based smart healthcare services. The result of this study would be able to be used as basic data for preparing strategies to enhance their intention to use the services.

본 연구는 기술수용모델을 기반으로 IoT 기반의 스마트 건강관리 서비스에 대한 노인들의 이용의도를 알아보고자 시도되었다. 본 연구에서는 전문적 지원, 개인화, 상호작용, 사용편의성을 외생변수로 하고, 매개 내생 변수로 인지된 유용성, 사용의도를 최종 내생변수로 선정하였다. 본 연구의 대상자는 노인복지센터를 이용하는 220명의 65세 이상 노인이었으며, 수집된 자료는 AMOS 25.0을 활용하여 분석하였다. 본 연구결과 전문가 지원, 개인화는 인지된 유용성에 유의한 영향을 나타내지 않았고, 상호작용, 사용편의성과는 유의한 차이가 있었다. 또한 인지된 유용성은 사용의도에 영향을 미치는 것으로 나타났다. 본 연구는 노인의 IoT기반 스마트 건강관리 서비스 이용의도를 구조적으로 검증함으로써 노인들의 이용의도를 높이기 위한 전략 마련에 기초자료로 사용될 수 있을 것으로 생각한다.

Keywords

References

  1. Statistics Korea. (2019). Korean social indicators. [Online]. https://kosis.kr/search/search.do.
  2. Y. J Kim. (2012). Exploratory study on acceptance intention of mobile devices and applications for healthcare service. Journal of Contents Association, 12(9), 369-379. DOI : 10.5392/JKCA.2012.12.09.369
  3. J. M. Baek, Y. R. Jung & H. R. Kim. (2016). Smart-Health-Care for health promotion of the elderly, The Korea Journal of Sports Science, 25(6), 887-898.
  4. Korea Centers for Disease Control and Prevention. (2017), 2016 Annual report on the notified HIV/AIDS in Korea. Cheongju: Korea Centers for Disease Control and Prevention.
  5. W. S. Jeong, S. H. Kim & K. S. Min. (2013). An analysis of the economic effects for the IoT industry. Journal of Internet Computing and Services, 14(5), 119-128. DOI : 10.7472/jksii.2013.14.5.119
  6. W. Kang, M. S. Kim & J. U. Ko. (2013). Effects of the smartphone information use and performance on life satisfaction among the elderly. Journal of the Korean Gerontological Society, 33(1), 199-214. DOI : 10.9716/KITS.2015.14.2.033
  7. M. Y, Kim & H. J. Jun. (2017). The effects of smartphone use on life satisfaction in older adults: The mediating role of participation in social activities. Korean Journal of Gerontological Social Welfare, 72(3), 343-370. DOI : 10.5762/KITS.2018.19.11.264
  8. E. Choi et al. (2016). The relationships among mental, health behavior, and the ability and range of the smartphone utilization of the elderly. The Journal of Kyungpook Nursing Science, 20(1), 36-47.
  9. S. H. Lee, & S. S. Yoo. (2014). The status and outlook of mobile healthcare application. ICT & Media Policy, 26(7), 1-23.
  10. H. Shim, J. H. Lee, S. O. Hwang, H. R. Yoon & Y. R. Yoon. (2009) Development of heart rate monitoring for mobile telemedicine using smartphone. 13th international conference on biomedical engineering. IFMBE proceedings. (pp 1116-1119). Berlin, Heidelberg : Springer. DOI : 10.1007/978-3-540-92841-6_274
  11. M. R. Lee, S. J. Choi & Y. J. Lee. (2015). A study on the adoption of UHD for usere pereceived usefulness and ease of use of UHDTV. Journal of Broadcast Engineering. 2015. Jan, 20(1), 48-56. DOI : 10.5909/JBE.2015.20.1.48
  12. D. S. Kyo. (2019). Elderly's intention to use wearable device: Application of technology acceptance model, Journal of Sport and Leisure Studies, 1(78), 347-360. https://doi.org/10.51979/KSSLS.2019.10.78.347
  13. T. Y. Park, J. W. Nam. (2017). The effects of perceived interactivity on information acceptance in mobile health information service, Journal of the Korean society for information management, 34(3), 151-177. DOI : 10.3743/KOSIM.2017.34.3.151
  14. S. W. Lee, H. Y. Kim & J. H. Song. (2011). The effect of personalized Email messages on consumers perceived interactivity, purchase intention and loyalty. Academy of customer satisfaction management, 13(3), 85-100.
  15. H. J. Seo et al. (2015). Mhealth apps; The current status of usage and the factors of 26. continuous use. Journal of the HCI society of Korea, 10(1), 19-27. https://doi.org/10.17210/jhsk.2015.05.10.1.19
  16. National Information Society Agency. (2017). 2016 Survey on the digital divide. Daegu : NIA.
  17. M. O. Kim. (2018). The effects of smartphone use on spouse relationship satisfaction, children relationship, and satisfaction with social acquaintance relationship among older adults. Journal of the Korean Academia-Industrial cooperation Society, 19(3), 219-228. DOI : 10.5762/KAIS.2018.19.3.219
  18. M. K. Nam. (2016). An analysis on the present conditions of smart health care product design industry centered on IoT, Journal of The Korean Society Design Culture, 22(1), 115-126.
  19. T. Y. Kim, S. K. Youm, J. J. Jung & E. J. Kim. (2015). Multi-Hop WBAN Construction for Healthcare IoT Systems, 2015 International Platform Technology and Service(PlatCon). (pp. 27-28). Jeju : IEEE.
  20. Y. S. Jeong. (2017). Data storage and security model for mobile healthcare service based on IoT, Journal of digital convergence, 15(3), 187-193. DOI : 10.14400/JDC.2017.15.3.187
  21. F. D. Davis. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340. DOI : 10.2307/249008
  22. H. N. Kang & S. T. Ahn. (2019). Content analysis of news reports about older adults' health-related information and communication technology(ICT) based on technology acceptance modle(TAM). Journal of Speech, Media and Communication Research, 18(2), 7-45. https://doi.org/10.22902/JSMCR.2019.18.2.001
  23. K. Chen & A. H. Chan. (2011). A review of technology acceptance by older adults. Gerontechnology, 10(1), 1-12. DOI : 10.4017/gt.2011.10.01.006.00
  24. Q. Ma, A. H. Chan & K. Chen. (2016). Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Applied Ergonomics, 54, 62-71. DOI : 10.1016/j.apergo.2015.11.015
  25. L. Dogruel, S. Joeckel & N. D. Bowman. (2015). The use and acceptance of new media entertainment technology by elderly users: Development of an expanded technology acceptance model. Behaviour & Information Technology, 34(11), 1052-1063. DOI : 10.1080/0144929X.2015.1077890
  26. J. Y. Kim. (2015). A study on factors affecting to intention to use the IoT based smart health care service. Unpublished master's thesis, Dankook University, Jukjeon.
  27. R. Agarwal & E. Karahanna (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24, 665-694. DOI : 10.2307/3250951
  28. P. Brusilovsky. (2000). Adaptive hypermedia: from intelligent tutoring systems to web-based education. Intelligent tutoring systems. ITS 2000. (pp. 1-7). Berlin: Lecture Notes in Computer Science 1839. Springer. DOI : 10.1007/3-540-45108-0_1
  29. W. Lewis, R. Agarwal & V. Sambamurthy. (2003). Sources of influence on beliefs about information technology use; An empirical study of knowledge workers. MIS quarterly, 27(4), 657-678. DOI : 10.2307/30036552
  30. D. Gefen, E. Karahanna & D. W. Straub. (2003). Trust and TAM in online shopping; an integrated model. MIS quarterly, 27(1), 51-90. DOI : 10.2307/30036519
  31. R. R. Dholakia, M. Zhao, N. Dholakia & D. R. Fortin. (2000). Interactivity and revisits to websites: A theoretical framework. working paper, 1-19.
  32. S. J. McMillan & J. S. Hwang. (2002). Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity. Journal of Advertising, 31(3), 29-42. DOI : 10.1080/00913367.2002.10673674
  33. Y. Liu & L. J. Shrum. (2002). What is interactivity and is it always such a good thing? Implications of definition, person, and situation for the influence of interactivity on advertising effectiveness. Journal of advertising, 31(4), 53-64. DOI : 10.1080/00913367.2002.10673685
  34. J. S. Dyer, P. C. Fishburn, R. E. Steuer, J. Wallenius & S. Zionts. (1992). Multiple criteria decision making, multiattribute utility theory: the next ten years. Management science, 38(5), 645-654. DOI : 10.1287/mnsc.38.5.645
  35. L. Ha & E. L. James. (1998). Interactivity reexamined: A baseline analysis of early business web sites. Journal of Broadcasting and Electronic Media, 42(4), 457-474. DOI : 10.1080/08838159809364462
  36. J. P. Woo. (2016). Professor Woo Jong-pil's concept and understanding of structural equation modelling: Amos 4.0-20.0 public. Seoul: Hannarae Academy.
  37. S. S. Kim, K. S. Han, B. S. Kim, S. K. Park & S. K. Ahn. (2011). An empirical study on users intention to use mobile applications. The Journal of Korean Institute of Information Technology, 9(8), 213-228.
  38. M. M. Tsang, S. C. Ho & T. P. Liang. (2004). Consumer attitudes toward mobile advertising: An empirical study. International Journal of Electronic Commerce, 8(3), 65-78. https://doi.org/10.1080/10864415.2004.11044301
  39. G. Y. Noh, M. S. Kwon & H. J. Jang. (2014). The acceptance model of telemedicine for chronic disease in rural community. Journal of Contents Association, 14(8), 287-296. DOI : 10.5392/JKCA.2014.14.08.287
  40. V. Venkatesh. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), 342-365. DOI : 10.1287/isre.11.4.342.11872
  41. H. P. Lu & Y. J. S. Philip. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19(4), 442-458. DOI : 10.1108/10662240910981399