IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i20p13311-d943300.html
   My bibliography  Save this article

Promoting Healthcare Workers’ Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human–Computer Trust

Author

Listed:
  • Mengting Cheng

    (School of Economic and Management, Anhui University of Science and Technology, Huainan 232001, China)

  • Xianmiao Li

    (School of Economic and Management, Anhui University of Science and Technology, Huainan 232001, China)

  • Jicheng Xu

    (School of Economic and Management, Anhui University of Science and Technology, Huainan 232001, China)

Abstract

Artificial intelligence (AI)-assisted diagnosis and treatment could expand the medical scenarios and augment work efficiency and accuracy. However, factors influencing healthcare workers’ adoption intention of AI-assisted diagnosis and treatment are not well-understood. This study conducted a cross-sectional study of 343 dental healthcare workers from tertiary hospitals and secondary hospitals in Anhui Province. The obtained data were analyzed using structural equation modeling. The results showed that performance expectancy and effort expectancy were both positively related to healthcare workers’ adoption intention of AI-assisted diagnosis and treatment. Social influence and human–computer trust, respectively, mediated the relationship between expectancy (performance expectancy and effort expectancy) and healthcare workers’ adoption intention of AI-assisted diagnosis and treatment. Furthermore, social influence and human–computer trust played a chain mediation role between expectancy and healthcare workers’ adoption intention of AI-assisted diagnosis and treatment. Our study provided novel insights into the path mechanism of healthcare workers’ adoption intention of AI-assisted diagnosis and treatment.

Suggested Citation

  • Mengting Cheng & Xianmiao Li & Jicheng Xu, 2022. "Promoting Healthcare Workers’ Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human–Computer Trust," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:20:p:13311-:d:943300
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/20/13311/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/20/13311/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cheng-Chia Yang & Cheng-Lun Li & Te-Feng Yeh & Yu-Chia Chang, 2022. "Assessing Older Adults’ Intentions to Use a Smartphone: Using the Meta–Unified Theory of the Acceptance and Use of Technology," IJERPH, MDPI, vol. 19(9), pages 1-14, April.
    2. 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).
    3. Wenjuan Fan & Jingnan Liu & Shuwan Zhu & Panos M. Pardalos, 2020. "Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS)," Annals of Operations Research, Springer, vol. 294(1), pages 567-592, November.
    4. Peng Liu & Run Yang & Zhigang Xu, 2019. "Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions," Risk Analysis, John Wiley & Sons, vol. 39(2), pages 326-341, February.
    5. Vinod, Dasari Naga & Prabaharan, S.R.S., 2020. "Data science and the role of Artificial Intelligence in achieving the fast diagnosis of Covid-19," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    6. Hengstler, Monika & Enkel, Ellen & Duelli, Selina, 2016. "Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 105-120.
    7. Adi Alsyouf & Abdalwali Lutfi & Mohammad Al-Bsheish & Mu’taman Jarrar & Khalid Al-Mugheed & Mohammed Amin Almaiah & Fahad Nasser Alhazmi & Ra’ed Masa’deh & Rami J. Anshasi & Abdallah Ashour, 2022. "Exposure Detection Applications Acceptance: The Case of COVID-19," IJERPH, MDPI, vol. 19(12), pages 1-26, June.
    8. Fernandes, Teresa & Oliveira, Elisabete, 2021. "Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption," Journal of Business Research, Elsevier, vol. 122(C), pages 180-191.
    9. Francesca De Angelis & Nicola Pranno & Alessio Franchina & Stefano Di Carlo & Edoardo Brauner & Agnese Ferri & Gerardo Pellegrino & Emma Grecchi & Funda Goker & Luigi Vito Stefanelli, 2022. "Artificial Intelligence: A New Diagnostic Software in Dentistry: A Preliminary Performance Diagnostic Study," IJERPH, MDPI, vol. 19(3), pages 1-10, February.
    10. Adi Alsyouf & Awanis Ku Ishak & Abdalwali Lutfi & Fahad Nasser Alhazmi & Manaf Al-Okaily, 2022. "The Role of Personality and Top Management Support in Continuance Intention to Use Electronic Health Record Systems among Nurses," IJERPH, MDPI, vol. 19(17), pages 1-30, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Xiaoyue & Huo, Yudi, 2023. "Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework," Technology in Society, Elsevier, vol. 75(C).
    2. Adi Alsyouf & Abdalwali Lutfi & Nizar Alsubahi & Fahad Nasser Alhazmi & Khalid Al-Mugheed & Rami J. Anshasi & Nora Ibrahim Alharbi & Moteb Albugami, 2023. "The Use of a Technology Acceptance Model (TAM) to Predict Patients’ Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability," IJERPH, MDPI, vol. 20(2), pages 1-24, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Peng & Xu, Zhigang & Zhao, Xiangmo, 2019. "Road tests of self-driving vehicles: Affective and cognitive pathways in acceptance formation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 354-369.
    2. Liu, Peng & Ma, Yanjiao & Zuo, Yaqing, 2019. "Self-driving vehicles: Are people willing to trade risks for environmental benefits?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 139-149.
    3. Adi Alsyouf & Abdalwali Lutfi & Nizar Alsubahi & Fahad Nasser Alhazmi & Khalid Al-Mugheed & Rami J. Anshasi & Nora Ibrahim Alharbi & Moteb Albugami, 2023. "The Use of a Technology Acceptance Model (TAM) to Predict Patients’ Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability," IJERPH, MDPI, vol. 20(2), pages 1-24, January.
    4. Abdalwali Lutfi & Saleh Nafeth Alkelani & Malak Akif Al-Khasawneh & Ahmad Farhan Alshira’h & Malek Hamed Alshirah & Mohammed Amin Almaiah & Mahmaod Alrawad & Adi Alsyouf & Mohamed Saad & Nahla Ibrahim, 2022. "Influence of Digital Accounting System Usage on SMEs Performance: The Moderating Effect of COVID-19," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    5. Yoganathan, Vignesh & Osburg, Victoria-Sophie, 2024. "The mind in the machine: Estimating mind perception's effect on user satisfaction with voice-based conversational agents," Journal of Business Research, Elsevier, vol. 175(C).
    6. Qian, Lixian & Yin, Juelin & Huang, Youlin & Liang, Ya, 2023. "The role of values and ethics in influencing consumers’ intention to use autonomous vehicle hailing services," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    7. Lutfi, Abdalwali & Alrawad, Mahmaod & Alsyouf, Adi & Almaiah, Mohammed Amin & Al-Khasawneh, Ahmad & Al-Khasawneh, Akif Lutfi & Alshira'h, Ahmad Farhan & Alshirah, Malek Hamed & Saad, Mohamed & Ibrahim, 2023. "Drivers and impact of big data analytic adoption in the retail industry: A quantitative investigation applying structural equation modeling," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    8. Ponzoa, José M. & Gómez, Andrés & Mas, José M., 2023. "EU27 and USA institutions in the digital ecosystem: Proposal for a digital presence measurement index," Journal of Business Research, Elsevier, vol. 154(C).
    9. Qun Wu & Lan Huang & Jiecong Zong, 2023. "User Interface Characteristics Influencing Medical Self-Service Terminals Behavioral Intention and Acceptance by Chinese Elderly: An Empirical Examination Based on an Extended UTAUT Model," Sustainability, MDPI, vol. 15(19), pages 1-12, September.
    10. Zehua Li & Jiaran Niu & Zhenzhou Li & Yukun Chen & Yang Wang & Bin Jiang, 2022. "The Impact of Individual Differences on the Acceptance of Self-Driving Buses: A Case Study of Nanjing, China," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    11. Blume, Maximilian & Oberländer, Anna Maria & Röglinger, Maximilian & Rosemann, Michael & Wyrtki, Katrin, 2020. "Ex ante assessment of disruptive threats: Identifying relevant threats before one is disrupted," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    12. Ra’ed Masa’deh & Dmaithan A. AlMajali & Abdullah A. M. AlSokkar & Mohammad Alshinwan & Maha Shehadeh, 2023. "Antecedents of Intention to Use E-Auction: An Empirical Study," Sustainability, MDPI, vol. 15(6), pages 1-11, March.
    13. Zhu, Yimin & Zhang, Jiemin & Wu, Jifei & Liu, Yingyue, 2022. "AI is better when I'm sure: The influence of certainty of needs on consumers' acceptance of AI chatbots," Journal of Business Research, Elsevier, vol. 150(C), pages 642-652.
    14. Weina Qu & Hongli Sun & Yan Ge, 2021. "The effects of trait anxiety and the big five personality traits on self-driving car acceptance," Transportation, Springer, vol. 48(5), pages 2663-2679, October.
    15. Li, Dun & Huang, Youlin & Qian, Lixian, 2022. "Potential adoption of robotaxi service: The roles of perceived benefits to multiple stakeholders and environmental awareness," Transport Policy, Elsevier, vol. 126(C), pages 120-135.
    16. Zhiwei Liu & Jianrong Liu, 2023. "Shared Autonomous Vehicles as Last-Mile Public Transport of Metro Trips," Sustainability, MDPI, vol. 15(19), pages 1-15, October.
    17. Erik Karger & Marvin Jagals & Frederik Ahlemann, 2021. "Blockchain for Smart Mobility—Literature Review and Future Research Agenda," Sustainability, MDPI, vol. 13(23), pages 1-32, November.
    18. Khaksar, Seyed Mohammad Sadegh & Shahmehr, Fatemeh S. & Miah, Shah & Daim, Tugrul & Ozdemir, Dilek, 2024. "Privacy concerns versus personalisation benefits in social robot acceptance by employees: A paradox theory — Contingency perspective," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    19. Wang, Fan & Gu, Jibao & Wu, Jianlin, 2020. "Perspective taking, energy policy involvement, and public acceptance of nuclear energy: Evidence from China," Energy Policy, Elsevier, vol. 145(C).
    20. Alrawad, Mahmaod & Lutfi, Abdalwali & Alyatama, Sundus & Al Khattab, Adel & Alsoboa, Sliman S. & Almaiah, Mohammed Amin & Ramadan, Mujtaba Hashim & Arafa, Hussin Mostafa & Ahmed, Nazar Ali & Alsyouf, , 2023. "Assessing customers perception of online shopping risks: A structural equation modeling–based multigroup analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:20:p:13311-:d:943300. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.