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Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach

Author

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  • Debora Bettiga

    (Politecnico di Milano)

  • Lucio Lamberti

    (Politecnico di Milano)

  • Emanuele Lettieri

    (Politecnico di Milano)

Abstract

Healthcare is moving towards new patterns and models, with an increasing attention paid to prevention. Smart technologies for mobile health care are emerging as new instruments to monitor the state of essential parameters in citizens. A very debated subject in literature is the critical role played by citizens’ acceptance and willingness to pay for mobile health technologies, especially whereas the services provided are preventive rather than curative. The adoption of such technologies is, indeed, a necessary condition for the success of mobile personalized health care. In this view, a conceptual framework, grounded on Technology Acceptance Model, is developed to explore the determinants of users’ willingness to adopt and pay for a mobile health care application for cardiovascular prevention. Empirical data are collected from a sample of 212 non-hypertensive Italian individuals and analyzed through Structural Equation Modeling. Results confirm that usefulness and ease of use determine both intention to accept and willingness to pay for mobile health smart technologies. Results show also the significant role played by social influence as well the role as antecedents played by technology promptness, innovativeness and prevention awareness. This study offers novel insights to design and promote smart application to improve mobile health care, with implications for researchers and practitioners in health care, research & development, and marketing.

Suggested Citation

  • Debora Bettiga & Lucio Lamberti & Emanuele Lettieri, 2020. "Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach," Health Care Management Science, Springer, vol. 23(2), pages 203-214, June.
  • Handle: RePEc:kap:hcarem:v:23:y:2020:i:2:d:10.1007_s10729-019-09468-2
    DOI: 10.1007/s10729-019-09468-2
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    References listed on IDEAS

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    2. Pal, Debajyoti & Vanijja, Vajirasak, 2020. "Perceived usability evaluation of Microsoft Teams as an online learning platform during COVID-19 using system usability scale and technology acceptance model in India," Children and Youth Services Review, Elsevier, vol. 119(C).
    3. Fuyong Lu & Xian Huang & Xintao Wang, 2022. "Willingness to Pay for Mobile Health Live Streaming during the COVID-19 Pandemic: Integrating TPB with Compatibility," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
    4. Liyuan Liu & Yen Hsu, 2022. "Motivating factors behind the public’s use of smart recycling systems: perceived playfulness and environmental concern," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
    5. Jiaxin Chen & Ting Li & Hua You & Jingyu Wang & Xueqing Peng & Baoyi Chen, 2023. "Behavioral Interpretation of Willingness to Use Wearable Health Devices in Community Residents: A Cross-Sectional Study," IJERPH, MDPI, vol. 20(4), pages 1-11, February.
    6. Gerli, Paolo & Clement, Jessica & Esposito, Giovanni & Mora, Luca & Crutzen, Nathalie, 2022. "The hidden power of emotions: How psychological factors influence skill development in smart technology adoption," Technological Forecasting and Social Change, Elsevier, vol. 180(C).

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