Su Jiayu, Wang Yuhui, Liu Hongyi, Zhang Zuopeng, Wang Zhe, Li Zhirong
School of Architecture and Art, Central South University, Changsha, China.
Law School, University of Southampton, Southampton, UK.
Sci Rep. 2025 May 25;15(1):18215. doi: 10.1038/s41598-025-01897-0.
As an emerging healthcare technology, artificial intelligence (AI) health assistants have garnered significant attention. However, the acceptance and intention of ordinary users to adopt AI health assistants require further exploration. This study aims to identify factors influencing users' intentions to use AI health assistants and enhance understanding of the acceptance mechanisms for this technology. Based on the unified theory of acceptance and use of technology (UTAUT), we expanded the variables of perceived trust (PT) and perceived risk (PR). We recruited 373 Chinese ordinary users online and analyzed the data using covariance-based structural equation modeling (CB-SEM). The results indicate that the original UTAUT structure is robust, performance expectancy (PE), effort expectancy (EE), and social influence (SI) significantly positively affect behavioral intention (BI), while facilitating conditions (FC) do not show a significant impact. Additionally, perceived trust is closely related to performance expectancy, effort expectancy, and behavioral intention, negatively impacting perceived risk. Conversely, perceived risk adversely affects behavioral intention. Our findings provide valuable practical insights for developers and operators of AI health assistants.
作为一种新兴的医疗保健技术，人工智能（AI）健康助手已引起广泛关注。然而，普通用户对采用AI健康助手的接受度和意愿仍有待进一步探索。本研究旨在识别影响用户使用AI健康助手意愿的因素，并加深对该技术接受机制的理解。基于技术接受与使用统一理论（UTAUT），我们扩展了感知信任（PT）和感知风险（PR）变量。我们在网上招募了373名中国普通用户，并使用基于协方差的结构方程模型（CB-SEM）对数据进行分析。结果表明，原始的UTAUT结构是稳健的，绩效期望（PE）、努力期望（EE）和社会影响（SI）对行为意愿（BI）有显著正向影响，而促进条件（FC）未显示出显著影响。此外，感知信任与绩效期望、努力期望和行为意愿密切相关，对感知风险有负面影响。相反，感知风险对行为意愿有不利影响。我们的研究结果为AI健康助手的开发者和运营者提供了有价值的实践见解。
