Understanding the Chinese Medical Students’ AI Acceptance Intention in Healthcare: from a Facilitator and Barrier Perspective

Authors

  • Fan Junhao Macao University of Science and Technology

DOI:

https://doi.org/10.25047/ijhitech.v3i2.6428

Keywords:

AI acceptance intention, technology acceptance model, perceived risk of losing professional autonomy, perceived risk of losing job security

Abstract

Current studies have documented that medical experts’ AI acceptance is influenced by the benefit-and-cost evaluation of its applications in healthcare systems. Guided by the Technology Acceptance Model, the research aim of this study is to explore how positive factors and risk factors might influence Chinese medical students’ AI acceptance intention. This study used a quantitative approach, and the data were collected by a convenience sample from an online survey (N = 419). The statistics software tools, including SPSS 28 and SmartPLS4, were used to perform hypothesis testing. The results revealed that Chinese medical students’ AI acceptance intention was positively related to perceived usefulness and perceived ease of use, but risk factors, which were supposed to inhibit their acceptance intention, showed a positive relationship with AI acceptance intention as well. The perceived usefulness is positively correlated with the risk factors. This means that participants in this study hold a positive attitude towards AI, even though they sensed a slight risk of its application. The theoretical contributions are two-fold. Firstly, this study discussed the impacts of two risk factors and added them to the research model simultaneously. Secondly, this study explored how the perceived usefulness might serve as an antecedent of risk evaluations of AI applications. As for practical implications, this study recommends that in-hand experience with AI practice is crucial for medical students.

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Published

2025-11-27

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How to Cite

Understanding the Chinese Medical Students’ AI Acceptance Intention in Healthcare: from a Facilitator and Barrier Perspective. (2025). International Journal of Healthcare and Information Technology, 3(2), 64-77. https://doi.org/10.25047/ijhitech.v3i2.6428

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