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Paper Type
ERF
Description
Since its introduction, ChatGPT has generated significant interest in many areas in just a few months, including healthcare. Recently, researchers have claimed that it has passed the U.S. medical licensure examination (Kung et. al, 2022). However, few empirical studies have investigated whether ChatGPT would be valued and accepted by public in the healthcare context. To understand the public's willingness to accept Artificial Intelligence-Generated Content (AIGC) applications like ChatGPT in the healthcare sector, this study proposes a model of factors affecting the user acceptance of ChatGPT for healthcare purposes integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Trust Theory, the Perceived Risk Theory, and the Perceived Illness Theory. We will analyze the data collected from questionnaires using Structural Equation Modeling (SEM). The findings of this study will provide insights into the factors affecting the user acceptance of ChatGPT for healthcare services.
Paper Number
1307
Recommended Citation
Kong, Deli; Qi, Jiayin; and Fu, Xiangling, "Would You Accept Doctor ChatGPT: An Empirical Study Based on the UTAUT Model" (2023). AMCIS 2023 Proceedings. 6.
https://aisel.aisnet.org/amcis2023/sig_health/sig_health/6
Would You Accept Doctor ChatGPT: An Empirical Study Based on the UTAUT Model
Since its introduction, ChatGPT has generated significant interest in many areas in just a few months, including healthcare. Recently, researchers have claimed that it has passed the U.S. medical licensure examination (Kung et. al, 2022). However, few empirical studies have investigated whether ChatGPT would be valued and accepted by public in the healthcare context. To understand the public's willingness to accept Artificial Intelligence-Generated Content (AIGC) applications like ChatGPT in the healthcare sector, this study proposes a model of factors affecting the user acceptance of ChatGPT for healthcare purposes integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Trust Theory, the Perceived Risk Theory, and the Perceived Illness Theory. We will analyze the data collected from questionnaires using Structural Equation Modeling (SEM). The findings of this study will provide insights into the factors affecting the user acceptance of ChatGPT for healthcare services.
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