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Examining Users’ Adoption of Precision Medicine: The Moderating Role of Medical Technical Knowledge

Author

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  • Xingyuan Wang

    (School of Management, Shandong University, Jinan 250100, China)

  • Yun Liu

    (School of Management, Shandong University, Jinan 250100, China)

  • Hongchen Liu

    (School of Management, Shandong University, Jinan 250100, China)

Abstract

Precision medical technologies have received a great deal of attention, but promoting such technologies remains a problem for enterprises and medical institutions. Adopting the unified theory of acceptance and use of technology (UTAUT) model and the health belief model (HBM), this study investigated the key factors affecting users’ willingness to adopt precision medicine (PM) in terms of technical factors and external stimuli. Based on 415 questionnaires, performance expectancy, price value, social influence, and perceived threat of disease were found to significantly increase users willingness to adopt PM; meanwhile, privacy risks had the opposite effect. Knowledge about PM was found to strengthen the positive effect of performance expectancy, price value, social influence, and perceived threat of disease on willingness to adopt PM and weaken the negative effect of privacy risk. This study demonstrates the successful application of UTAUT to the medical field while also providing guidance for the promotion of PM.

Suggested Citation

  • Xingyuan Wang & Yun Liu & Hongchen Liu, 2020. "Examining Users’ Adoption of Precision Medicine: The Moderating Role of Medical Technical Knowledge," IJERPH, MDPI, vol. 17(3), pages 1-16, February.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:3:p:1113-:d:318597
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    1. Wu, Yanfang & Lau, Tuenyu & Atkin, David J. & Lin, Carolyn A., 2011. "A comparative study of online privacy regulations in the U.S. and China," Telecommunications Policy, Elsevier, vol. 35(7), pages 603-616, August.
    2. Znabu Hadush Kahsay & Molla Kahssay Hiluf & Reda Shamie & Yordanos Tadesse & Alessandra N. Bazzano, 2019. "Pregnant Women’s Intentions to Deliver at a Health Facility in the Pastoralist Communities of Afar, Ethiopia: An Application of the Health Belief Model," IJERPH, MDPI, vol. 16(5), pages 1-9, March.
    3. McLean, Graeme & Osei-Frimpong, Kofi, 2019. "Chat now… Examining the variables influencing the use of online live chat," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 55-67.
    4. Brucks, Merrie, 1985. "The Effects of Product Class Knowledge on Information Search Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(1), pages 1-16, June.
    5. Hui-Ting Huang & Yu-Ming Kuo & Shiang-Ru Wang & Chia-Fen Wang & Chung-Hung Tsai, 2016. "Structural Factors Affecting Health Examination Behavioral Intention," IJERPH, MDPI, vol. 13(4), pages 1-15, April.
    6. Park, C Whan & Mothersbaugh, David L & Feick, Lawrence, 1994. "Consumer Knowledge Assessment," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 71-82, June.
    7. Wanchuan Lin & Gordon G. Liu & Gang Chen, 2009. "The Urban Resident Basic Medical Insurance: a landmark reform towards universal coverage in China," Health Economics, John Wiley & Sons, Ltd., vol. 18(S2), pages 83-96, July.
    8. Mitchell, Andrew A & Dacin, Peter A, 1996. "The Assessment of Alternative Measures of Consumer Expertise," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 23(3), pages 219-239, December.
    9. Vincenzo Restivo & Claudio Costantino & Antonello Marras & Giuseppe Napoli & Sabrina Scelfo & Tiziana Scuderi & Alessandra Casuccio & Achille Cernigliaro & Angela Giusti & Stefania Spila Alegiani, 2018. "Pap Testing in a High-Income Country with Suboptimal Compliance Levels: A Survey on Acceptance Factors among Sicilian Women," IJERPH, MDPI, vol. 15(9), pages 1-10, August.
    10. Latrice Rollins & Angela Sy & Nicole Crowell & Desiree Rivers & Assia Miller & Pamela Cooper & Debra Teague & Cassandra Jackson & Tabia Henry Akintobi & Elizabeth Ofili, 2018. "Learning and Action in Community Health: Using the Health Belief Model to Assess and Educate African American Community Residents about Participation in Clinical Research," IJERPH, MDPI, vol. 15(9), pages 1-14, August.
    11. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    12. Man Lai Cheung & Ka Yin Chau & Michael Huen Sum Lam & Gary Tse & Ka Yan Ho & Stuart W. Flint & David R Broom & Ejoe Kar Ho Tso & Ka Yiu Lee, 2019. "Examining Consumers’ Adoption of Wearable Healthcare Technology: The Role of Health Attributes," IJERPH, MDPI, vol. 16(13), pages 1-16, June.
    13. Duarte, Paulo & Pinho, José Carlos, 2019. "A mixed methods UTAUT2-based approach to assess mobile health adoption," Journal of Business Research, Elsevier, vol. 102(C), pages 140-150.
    14. Hui-Lung Hsieh & Yu-Ming Kuo & Shiang-Ru Wang & Bi-Kun Chuang & Chung-Hung Tsai, 2016. "A Study of Personal Health Record User’s Behavioral Model Based on the PMT and UTAUT Integrative Perspective," IJERPH, MDPI, vol. 14(1), pages 1-14, December.
    15. Park, C Whan & Lessig, V Parker, 1977. "Students and Housewives: Differences in Susceptibility to Reference Group Influence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 4(2), pages 102-110, Se.
    16. Rese, Alexandra & Baier, Daniel & Geyer-Schulz, Andreas & Schreiber, Stefanie, 2017. "How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 306-319.
    17. Kristopher J. Hult, 2017. "Measuring the Potential Health Impact of Personalized Medicine: Evidence from MS Treatments," NBER Working Papers 23900, National Bureau of Economic Research, Inc.
    18. Gaurav Khatwani & Praveen Ranjan Srivastava, 2015. "Employing Group Decision Support System for the Selection of Internet Information Search Channels for Consumers," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 6(4), pages 72-93, October.
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