Exploring Factors Influencing Patients’ Intention to Adopt Generative AI on Online Healthcare Platforms

The development of generative AI has disrupted various fields, and the field of online healthcare is no exception. However, there is a lack of research on patients’ intention to adopt generative AI on online healthcare platforms. Therefore, the aim of this study is to investigate the factors influencing patients’ intention to adopt generative AI. Employing a questionnaire-based survey, we explore the factors influencing patients’ intention to adopt generative AI through the UTAUT2 model, considering the moderating effects of construal level, health literacy, and AI literacy. We find that performance expectancy, social influence, and facilitating conditions are positively associated with patients’ intention. Surprisingly, effort expectancy and hedonic motivation do not have a significant impact on patients’ intention. Construal level positively moderates the relationship between performance expectancy and patients’ intention; health literacy negatively moderates the relationship between social influence and patients’ intention. AI literacy positively moderates the relationship between effort expectancy and patients’ intention but negatively moderates the relationship between social influence and patients’ intention. This study enriches UTAUT2 theory and provides practical insights for the development and promotion of generative AI on online healthcare platforms.

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Publication Details

Journal
Journal of theoretical and applied electronic commerce research
Published
2025-10-15
DOI
https://doi.org/10.3390/jtaer20040287
Primary Topic
Technology Adoption and User Behaviour
Type
article
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article

Exploring Factors Influencing Patients’ Intention to Adopt Generative AI on Online Healthcare Platforms

Xi Chen, Yu Li, Tian Shen, Shi‐Qiang Yang
Journal of theoretical and applied electronic commerce research
Technology Adoption and User Behaviour
article

Exploring Factors Influencing Patients’ Intention to Adopt Generative AI on Online Healthcare Platforms

Xi Chen, Yu Li, Tian Shen, Shi‐Qiang Yang
article en

Abstract

The development of generative AI has disrupted various fields, and the field of online healthcare is no exception. However, there is a lack of research on patients’ intention to adopt generative AI on online healthcare platforms. Therefore, the aim of this study is to investigate the factors influencing patients’ intention to adopt generative AI. Employing a questionnaire-based survey, we explore the factors influencing patients’ intention to adopt generative AI through the UTAUT2 model, considering the moderating effects of construal level, health literacy, and AI literacy. We find that performance expectancy, social influence, and facilitating conditions are positively associated with patients’ intention. Surprisingly, effort expectancy and hedonic motivation do not have a significant impact on patients’ intention. Construal level positively moderates the relationship between performance expectancy and patients’ intention; health literacy negatively moderates the relationship between social influence and patients’ intention. AI literacy positively moderates the relationship between effort expectancy and patients’ intention but negatively moderates the relationship between social influence and patients’ intention. This study enriches UTAUT2 theory and provides practical insights for the development and promotion of generative AI on online healthcare platforms.

Journal of theoretical and applied electronic commerce researchVol. 20(4)
Nanjing University of Chinese Medicine (CN), Hunan University (CN), Nanjing University (CN)
Openalex Percentile: Top 72%
Technology Adoption and User Behaviour
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