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Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model

Author

Listed:
  • Jianfei Cao

    (Graduate School of Technology Management, Ritsumeikan University, Ibaraki 567-8570, Japan)

  • Karin Kurata

    (Graduate School of Corporate Business, Ritsumeikan University, Ibaraki 567-8570, Japan)

  • Yeongjoo Lim

    (Graduate School of Corporate Business, Ritsumeikan University, Ibaraki 567-8570, Japan)

  • Shintaro Sengoku

    (School of Environment and Society, Tokyo Institute of Technology, Tokyo 152-8550, Japan)

  • Kota Kodama

    (Graduate School of Technology Management, Ritsumeikan University, Ibaraki 567-8570, Japan
    Center for Research and Education on Drug Discovery, The Graduate School of Pharmaceutical Sciences, Hokkaido University, Sapporo 060-0812, Japan)

Abstract

The unprecedented development of information and communication technologies has opened up immense possibilities in the field of health care. Mobile health (mHealth) is gaining increasing attention as an important technology for solving health-related problems. Although a high rate of smartphone usage among young people in Japan has been identified, smartphone usage for health management is not high. As Japanese youth are important potential users of mHealth, it is necessary to explore theories that influence the behavioral intention of Japanese youth to adopt mHealth. This study conducted a questionnaire survey in a Japanese university and collected 233 valuable responses. This study was adapted and extended from the unified theory of acceptance and use of technology (UTAUT) model to measure eight constructs: health consciousness, social influence, facilitation conditions, perceived risk, trust, performance expectancy, effort expectancy, and behavioral intention. Structural equation modeling was used for hypothesis testing. We found that trust, performance expectancy, and effort expectancy directly influenced the behavioral intention to use mHealth. Health consciousness and social influence indirectly influence behavioral intention through trust and performance expectancy. Facilitation conditions indirectly influenced behavioral intention through effort expectancy. This study makes a vital theoretical contribution to policymakers and product developers for the further diffusion of mHealth among young people in Japan.

Suggested Citation

  • Jianfei Cao & Karin Kurata & Yeongjoo Lim & Shintaro Sengoku & Kota Kodama, 2022. "Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model," IJERPH, MDPI, vol. 19(22), pages 1-16, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:22:p:15156-:d:975302
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    References listed on IDEAS

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    1. Jianfei CAO & Yeongjoo Lim & Kota Kodama, 2021. "Smartphone Addiction and Life Satisfaction: Mediating Effects of Sleep Quality and Self-Health," Global Journal of Health Science, Canadian Center of Science and Education, vol. 13(3), pages 1-8, March.
    2. Mohamed Farid & Jianfei Cao & Yeongjoo Lim & Teruyo Arato & Kota Kodama, 2020. "Exploring Factors Affecting the Acceptance of Genetically Edited Food Among Youth in Japan," IJERPH, MDPI, vol. 17(8), pages 1-22, April.
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    4. Deng, Zhaohua & Liu, Shan & Hinz, Oliver, 2015. "The Health Information Seeking and Usage Behavior Intention of Chinese Consumers through Mobile Phone," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77133, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Nicole Koenig-Lewis & Morgan Marquet & Adrian Palmer & Anita Lifen Zhao, 2015. "Enjoyment and social influence: predicting mobile payment adoption," The Service Industries Journal, Taylor & Francis Journals, vol. 35(10), pages 537-554, July.
    6. Yumei Luo & Guiping Wang & Yuwei Li & Qiongwei Ye, 2021. "Examining Protection Motivation and Network Externality Perspective Regarding the Continued Intention to Use M-Health Apps," IJERPH, MDPI, vol. 18(11), pages 1-17, May.
    7. 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.
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    Cited by:

    1. Muhammad Azeem Ashraf & Nadia Shabnam & Samson Maekele Tsegay & Guoqin Huang, 2023. "Acceptance of Smart Technologies in Blended Learning: Perspectives of Chinese Medical Students," IJERPH, MDPI, vol. 20(3), pages 1-14, February.

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