Patient acceptance of medical service robots in the medical intelligence era: an empirical study based on an extended AI device use acceptance model
Wenjia Li, Huangyi Ding, Jingjing Gui, Qinghe Tang
Abstract
In the era of medical intelligence, there are still few studies focusing on medical service robots from a user experience perspective. Guided by the model of artificial intelligence (AI) device use acceptance (AIDUA), this article develops a theoretical model to explain patients’ intention to use medical service robots at hospitals. The proposed model specifically distinguished the dimensions of anthropomorphic attributes of service robots and further introduces two variables, perceived empathy and interaction experience, as a way to construct a three-stage psychological mechanism for patient acceptance of robots. 400 questionnaires from Chinese patients were collected offline and analyzed using structural equation modeling (SEM). The results revealed that the four attributes of anthropomorphism play a differential influence in performance expectations and effort expectations, but all positively contribute to empathy, which in turn positively affects interaction quality. Interaction quality, performance expectations, and effort expectations all influence patients’ emotions, thus having an impact on patients’ intentions to accept service robots. The findings from this study will assist the healthcare sector in upgrading medical service robots, which will improve patient acceptance of these robots.