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The Willingness of Doctors to Adopt Artificial Intelligence–Driven Clinical Decision Support Systems at Different Hospitals in China: Fuzzy Set Qualitative Comparative Analysis of Survey Data

The Willingness of Doctors to Adopt Artificial Intelligence–Driven Clinical Decision Support Systems at Different Hospitals in China: Fuzzy Set Qualitative Comparative Analysis of Survey Data

We used fs QCA to explore the complex causal mechanisms influencing clinical doctors’ willingness to adopt AI-CDSSs, primarily for the following reasons. First, using this method uncovers the nonlinear relationships between various influencing factors and the doctors’ willingness to adopt AI-CDSSs. The fs QCA method also explores combinations of influencing factors instead of individual factors [40].

Zhongguang Yu, Ning Hu, Qiuyi Zhao, Xiang Hu, Cunbo Jia, Chunyu Zhang, Bing Liu, Yanping Li

J Med Internet Res 2025;27:e62768

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Understanding Prospective Physicians’ Intention to Use Artificial Intelligence in Their Future Medical Practice: Configurational Analysis

Understanding Prospective Physicians’ Intention to Use Artificial Intelligence in Their Future Medical Practice: Configurational Analysis

In a nutshell, fs QCA is a second-generation configurational analysis method that uses Boolean algebra for determining different configurations of elements that generate the same outcome [37]. In this method, each configurational element (or causal condition) is considered a fuzzy set. Consistent with the configurational theory, fs QCA allows for equifinality and causal asymmetry [22].

Gerit Wagner, Louis Raymond, Guy Paré

JMIR Med Educ 2023;9:e45631

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