IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v216y2025ics0040162525001751.html
   My bibliography  Save this article

Drivers of artificial intelligence integrated healthcare applications. Patients' perspective

Author

Listed:
  • Kalisz, David E.

Abstract

The healthcare sector has extensively adopted Artificial Intelligence (AI) to improve operational efficiency and care quality. However, patients' adoption and use of AI-integrated healthcare applications (AIIHA) for consultation and treatment have not been investigated sufficiently. Our study addresses this gap by examining a unique contextual model comprising antecedents of patients' intentions and behavior towards AIIHA. The proposed model is contextualized to the AIIHA context by incorporating four new constructs, namely privacy concern, hedonic motivation, trust, and patient healthcare engagement, along with performance and effort expectancy. The model hypothesizing the association of the aforementioned variables with patients' behavioral intentions is tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data (N = 522) collected online from respondents in different countries. In addition, the moderating effect of the recent pandemic is also tested to evaluate the strength of the association between behavioral intentions and usage behavior towards AIIHA. The results reveal that performance expectancy, effort expectancy, hedonic motivation, patient healthcare engagement, and trust shape patients' behavioral intentions towards AIIHA. Also, there is a statistically significant effect of effort expectancy on performance expectancy, patients' behavioral intentions on usage behavior, and the negative impact of privacy concerns on patients' trust.

Suggested Citation

  • Kalisz, David E., 2025. "Drivers of artificial intelligence integrated healthcare applications. Patients' perspective," Technological Forecasting and Social Change, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:tefoso:v:216:y:2025:i:c:s0040162525001751
    DOI: 10.1016/j.techfore.2025.124144
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162525001751
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2025.124144?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:tefoso:v:216:y:2025:i:c:s0040162525001751. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.