Integrating the unified theory of acceptance and use of technology and the uses and gratifications theory in exploring generative AI adoption for health information seeking: Cross-sectional study
Yihan Qi, Emma Mohamad, Arina Anis Azlan, Chenglin Zhang, Xixi Zhao, Anqi Wu, Yilian MaBackground
Generative artificial intelligence (AI) is transforming digital health by enabling interactive health information services. As reliance on AI for health information seeking (HIS) grows, understanding user adoption becomes essential. However, prior research has focused mainly on technological and ethical issues, with limited attention to adoption mechanisms integrating technological perceptions and user motivations.
Objective
This study integrates the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Uses and Gratifications Theory (UGT) to explore the determinants of generative AI adoption for HIS in China.
Methods
A cross-sectional online survey was conducted among information technology professionals in China from January 3 to 17, 2025. A total of 624 valid responses were analysed using partial least squares structural equation modelling (PLS-SEM). Constructs from UTAUT (performance expectancy, effort expectancy, social influence, facilitating conditions) and UGT (instrumental and ritualized use) were assessed alongside behavioural intention and usage behaviour.
Results
Performance expectancy (β = 0.362, p < 0.001), effort expectancy (β = 0.207, p < 0.001), and social influence (β = 0.120, p = 0.006) were positively associated with behavioural intention toward using generative AI. In turn, behavioural intention (β = 0.239, p < 0.001) and facilitating conditions (β = 0.281, p < 0.001) were positively associated with generative AI usage behaviour. Instrumental use (β = 0.418, p < 0.001) and ritualized use (β = 0.256, p < 0.001) were positively associated with performance expectancy and effort expectancy. The model explains meaningful variance and shows satisfactory predictive relevance.
Conclusions
Generative AI shows promise for HIS among IT professionals in China. Integrating UTAUT and UGT provides a more comprehensive understanding of how technology-related beliefs and user motivations are associated with generative AI adoption for HIS. Findings should be interpreted cautiously given the specific occupational context and cross-sectional study design.