Korea Journal of Hospital Management (한국병원경영학회지)

Korean Society of Hospital Management (한국병원경영학회)
권호 표지

Appropriate App Services and Acceptance for Contact Tracing: Survey Focusing on High-Risk Areas of COVID-19 in South Korea

코로나 19 동선 관리를 위한 적정 앱 서비스와 도입: 고위험 지역 설문 연구

  • Rho, Mi Jung (College of Health Science, Dankook University)
  • 노미정 (단국대학교 공공.보건과학대학)
  • Received : 2022.04.21
  • Accepted : 2022.06.07
  • Published : 2022.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Purposes: Prompt evaluation of routes and contact tracing are very important for epidemiological investigations of coronavirus disease 2019 (COVID-19). To ensure better adoption of contact tracing apps, it is necessary to understand users' expectations, preferences, and concerns. This study aimed to identify main reasons why people use the apps, appropriate services, and basis for voluntary app services that can improve app participation rates and data sharing. Methodology/Approach: This study conducted an online survey from November 11 to December 6, 2020, and received a total of 1,048 survey responses. This study analyzed the questionnaire survey findings of 883 respondents in areas with many confirmed cases of COVID-19. This study used a multiple regression analysis. Findings: Respondents who had experience of using related apps showed a high intention to use contact-tracing apps. Participants wished for the contact tracking apps to be provided by the government or public health centers (74%) and preferred free apps (93.88%). The factors affecting the participants' intention to use these apps were their preventive value, performance expectancy, perceived risk, facilitative ability, and effort expectancy. The results highlighted the need to ensure voluntary participation to address participants' concerns regarding privacy protection and personal information exposure. Practical Implications: The results can be used to accurately identify user needs and appropriate services and thereby improve the development of contact tracking apps. The findings provide the basis for voluntary app that can enhance app participation rates and data sharing. The results will also serve as the basis for developing trusted apps that can facilitate epidemiological investigations.

연구목적: 적절한 동선 파악과 동선 추적은 코로나19 역학조사를 위해서 매우 중요하다. 동선 추적 앱 도입을 활발히 하기 위해서는 사용자들의 앱에 대한 기대, 선호 그리고 우려하는 부분에 대한 이해가 필요하다. 본 연구는 동선 추적 앱의 사용률을 높이고, 데이터 공유를 원활히 할 수 있게 해주는 자발적 앱 서비스에 대한 기본적 특징과 적절한 서비스를 찾고자 하였다. 또한 사람들이 왜 동선 추적 앱을 사용하려고 하는지에 대한 주요요인을 확인하였다. 연구방법: 이 연구는 2020년 11월 11일부터 12월 6일까지 온라인 서베이를 실시하였고, 통 1,048명의 응답 데이터를 수집하였다. 응답 데이터 중 2020년 가장 많은 코로나19 확진자가 나온 지역의 883명의 응답자 데이터를 분석에 사용하였다. 결과: 코로나 19 관련 앱을 사용해본 경험자들은 동선 추적 앱에 대한 높은 사용의도를 가지고 있는 것으로 나타났다. 응답자들은 보건소와 같은 공공기관에서(74%), 무료(93.88%)로 앱을 제공해주기를 원했다. 동선 추적 앱 사용의도에 영향을 미치는 요인으로는 예방적 가치, 기대성과, 인지된 위험, 촉진기능, 노력기대 등으로 나타났다. 또한 개인정보 보호 및 개인정보 노출에 대한 사용자들의 우려를 해결하고 자발적 앱 사용이 필요한 것으로 분석되었다. 함의: 본 연구 결과는 동선 추적 개발에 있어, 적절한 서비스와 사용자들의 니즈를 파악하는데 유용할 것이다. 사람들의 앱 참여율과 데이터 공유를 높일 수 있는 자발적 앱 개발을 위한 기반을 제공해준다. 또한 본 연구는 역학조사에 협조가 가능한 신뢰 가능한 동선 추적 앱 개발의 근간을 마련할 수 있다.

Keywords

Acknowledgement

이 논문은 2020년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(NRF-2020R1I1A1A01072400)

References

  1. Li J, Guo X. Global deployment mappings and challenges of contact-tracing apps for COVID-19. Available at SSRN 3609516 2020.
  2. Munzert S, Selb P, Gohdes A, Stoetzer LF, Lowe W. Tracking and promoting the usage of a COVID-19 contact tracing app. Nature Human Behaviour 2021;5:247-55. https://doi.org/10.1038/s41562-020-01044-x
  3. Cho H, Ippolito D, Yu YW. Contact tracing mobile apps for COVID-19: Privacy considerations and related trade-offs. arXiv preprint arXiv:200311511 2020.
  4. Hogan K, Macedo B, Macha V, Barman A, Jiang X. Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation. JMIR Medical Informatics 2021;9:e27449. https://doi.org/10.2196/27449
  5. Baker A, Biazzo I, Braunstein A, Catania G, Dall' Asta L, Ingrosso A, et al. Epidemic mitigation by statistical inference from contact tracing data. Proceedings of the National Academy of Sciences 2021;118.
  6. Wymant C, Ferretti L, Tsallis D, Charalambides M, Abeler-Dorner L, Bonsall D, et al. The epidemiological impact of the NHS COVID-19 App. Nature 2021;594:408-12. https://doi.org/10.1038/s41586-021-03606-z
  7. Albrecht R, Jarecki JB, Meier DS, Rieskamp J. Risk preferences and risk perception affect the acceptance of digital contact tracing. Humanities and Social Sciences Communications 2021;8:1-9. https://doi.org/10.1057/s41599-020-00684-8
  8. Hargittai E, Redmiles EM, Vitak J, Zimmer M. Americans' willingness to adopt a COVID-19 tracking app. First Monday 2020;25:online.
  9. Ahmed N, Michelin RA, Xue W, Ruj S, Malaney R, Kanhere SS, et al. A survey of COVID-19 contact tracing apps. IEEE access 2020;8:134577-601. https://doi.org/10.1109/access.2020.3010226
  10. Agency KDCaP. Coronavirus Infectious Disease-19 Outbreak in Korea (December 6). http://ncov.mohw. go.kr/
  11. Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: Toward a unified view. MIS quarterly 2003:425-78.
  12. Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly 2012:157-78.
  13. Yamin MAY, Alyoubi BA. Adoption of telemedicine applications among Saudi citizens during COVID-19 pandemic: An alternative health delivery system. Journal of Infection and Public Health 2020;13:1845-55. https://doi.org/10.1016/j.jiph.2020.10.017
  14. Li T, Faklaris C, King J, Agarwal Y, Dabbish L, Hong JI. Decentralized is not risk-free: Understanding public perceptions of privacy-utility trade-offs in COVID-19 contact-tracing apps. arXiv preprint arXiv:200511957 2020.
  15. Sirdeshmukh D, Singh J, Sabol B. Consumer trust, value, and loyalty in relational exchanges. Journal of marketing 2002;66:15-37. https://doi.org/10.1509/jmkg.66.1.15.18449
  16. Yang H, Yu J, Zo H, Choi M. User acceptance of wearable devices: An extended perspective of perceived value. Telematics and Informatics 2016;33:256-69. https://doi.org/10.1016/j.tele.2015.08.007
  17. Kim H-W, Chan HC, Gupta S. Value-based adoption of mobile internet: an empirical investigation. Decision support systems 2007; 43:111-26. https://doi.org/10.1016/j.dss.2005.05.009
  18. Sheth JN, Newman BI, Gross BL. Consumption values and market choices: Theory and applications: South-Western Pub. Cinicinnati, OH; 1991.
  19. Nunnally JC. Psychometric theory 3E: Tata McGraw-hill education; 1994.
  20. Xiang Y-T, Zhao Y-J, Liu Z-H, Li X-H, Zhao N, Cheung T, et al. The COVID-19 outbreak and psychiatric hospitals in China: managing challenges through mental health service reform. International journal of biological sciences 2020;16:1741. https://doi.org/10.7150/ijbs.45072
  21. Steardo L, Verkhratsky A. Psychiatric face of COVID-19. Translational psychiatry 2020;10: 1-12. https://doi.org/10.1038/s41398-019-0665-5
  22. Bojdani E, Rajagopalan A, Chen A, Gearin P, Olcott W, Shankar V, et al. COVID-19 pandemic: impact on psychiatric care in the United States. Psychiatry research 2020;289:113069. https://doi.org/10.1016/j.psychres.2020.113069
  23. Altmann S, Milsom L, Zillessen H, Blasone R, Gerdon F, Bach R, et al. Acceptability of app-based contact tracing for COVID-19: Cross-country survey study. JMIR mHealth and uHealth 2020;8:e19857. https://doi.org/10.2196/19857
  24. Hansen JM, Saridakis G, Benson V. Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers' use of social media for transactions. Computers in human behavior 2018;80:197-206. https://doi.org/10.1016/j.chb.2017.11.010
  25. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly 1989:319-40.
  26. Martinez A, Everss E, Rojo-Alvarez JL, Figal DP, Garcia-Alberola A. A systematic review of the literature on home monitoring for patients with heart failure. Journal of telemedicine and telecare 2006;12:234-41. https://doi.org/10.1258/135763306777889109
  27. Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science 2000;46:186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  28. Bengio Y, Ippolito D, Janda R, Jarvie M, Prud'homme B, Rousseau J-F, et al. Inherent privacy limitations of decentralized contact tracing apps. Journal of the American Medical Informatics Association 2021;28:193-5. https://doi.org/10.1093/jamia/ocaa153
  29. Nakamoto I, Jiang M, Zhang J, Zhuang W, Guo Y, Jin M-H, et al. Evaluation of the design and implementation of a peer-to-peer COVID-19 contact tracing mobile app (COCOA) in Japan. JMIR mHealth and uHealth 2020;8:e22098. https://doi.org/10.2196/22098
  30. Temsah M-H, Al-Sohime F, Alamro N, Al-Eyadhy A, Al-Hasan K, Jamal A, et al. The psychological impact of COVID-19 pandemic on health care workers in a MERS-CoV endemic country. Journal of infection and public health 2020;13:877-82. https://doi.org/10.1016/j.jiph.2020.05.021