Psychosocial Factors Affecting Artificial Intelligence Adoption in Health Care in China: Cross-Sectional Study
Open accessAbstract
Background: Poor quality primary health care is a major issue in China, particularly in blindness prevention. Artificial intelligence (AI) could provide early screening and accurate auxiliary diagnosis to improve primary care services and reduce unnecessary referrals, but the application of AI in medical settings is still an emerging field. Objective: This study aimed to investigate the general public’s acceptance of ophthalmic AI devices, with reference to those already used in China, and the interrelated influencing factors that shape people’s intention to use these devices. Methods: We proposed a model of ophthalmic AI acceptance based on technology acceptance theories and variables from other health care–related studies. The model was verified via a 32-item questionnaire with 7-point Likert scales completed by 474 respondents (nationally random sampled). Structural equation modeling was used to evaluate item and construct reliability and validity via a confirmatory factor analysis, and the model’s path effects, significance, goodness of fit, and mediation and moderation effects were analyzed. Results: Standardized factor loadings of items were between 0.583 and 0.876. Composite reliability of 9 constructs ranged from 0.673 to 0.841. The discriminant validity of all constructs met the Fornell and Larcker criteria. Model fit indicators such as standardized root mean square residual (0.057), comparative fit index (0.915), and root mean squared error of approximation (0.049) demonstrated good fit. Intention to use (R2=0.515) is significantly affected by subjective norms (beta=.408; P<.001), perceived usefulness (beta=.336; P=.03), and resistance bias (beta=–.237; P=.02). Subjective norms and perceived behavior control had an indirect impact on intention to use through perceived usefulness and perceived ease of use. Eye health consciousness had an indirect positive effect on intention to use through perceived usefulness. Trust had a significant moderation effect (beta=–.095; P=.049) on the effect path of perceived usefulness to intention to use. Conclusions: The item, construct, and model indicators indicate reliable interpretation power and help explain the levels of public acceptance of ophthalmic AI devices in China. The influence of subjective norms can be linked to Confucian culture, collectivism, authoritarianism, and conformity mentality in China. Overall, the use of AI in diagnostics and clinical laboratory analysis is underdeveloped, and the Chinese public are generally mistrustful of medical staff and the Chinese medical system. Stakeholders such as doctors and AI suppliers should therefore avoid making misleading or over-exaggerated claims in the promotion of AI health care products.
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Ease of use; complex interfaces; and inconsistent performance, for example, due to false positives and negatives, add burden to the workflow, creating more work for clinicians, thereby impeding adoption.
“Ease of use; complex interfaces; and inconsistent performance, for example, due to false positives and negatives add burden to the workflow, creating more work for clinicians, thereby impeding adoption [42,52,57-59].”
From Barriers to and facilitators of artificial intelligence adoption in health care: scoping review (2024) · cites this paper as [52]
The Methods > Measurement section considers ease of use, possible performance failure, and incorrect screening results for ophthalmic AI devices. But the study examines the public’s intention to use those devices, not added work for clinicians or complex interfaces; the Discussion > Principal Findings reports no significant direct effect of ease of use on intention to use. The cited paper therefore supports some concerns named in the sentence, but not its clinician-workflow explanation for impeded adoption. Page numbers are not available in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredIn some studies, patients reported the need to assess the usefulness of the AI before using it and had concerns around the quality and accuracy of the output, thereby questioning the value of AI as a whole.
“In some studies, patients reported the need to assess the usefulness of the AI before using it and had concerns around the quality and accuracy of the output, thereby questioning the value of AI as a whole [39,42,52-55].”
From Barriers to and facilitators of artificial intelligence adoption in health care: scoping review (2024) · cites this paper as [52]
The Discussion (Principal Findings; page unavailable) says people may assess an ophthalmic AI device’s usefulness before switching from a face-to-face eye examination. The Methods (Measurement; page unavailable) includes survey items about inaccurate diagnoses and incorrect screening results. But the paper does not report that these concerns led respondents to question the value of AI as a whole; the Discussion says perceived risks did not affect intention to use the devices. (LLM, conf=0.86)
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- Authors
- Ye, T., Xue, J., He, M., Gu, J., Lin, H., Xu, B., & Cheng, Y.
- Affiliations
- Sun Yat-sen University (CN)
- Corresponding author
- Cheng, Yu
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2019-10-17
- Volume
- 21
- Issue
- 10
- Pages
- e14316
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC6913088
- OpenAlex
- W2981124546
- Cited by
- 141
- References
- 75
- Citations by year
- 2026: 21 · 2025: 37 · 2024: 29 · 2023: 19 · 2022: 16 · 2021: 14 · 2020: 5
- FWCI
- 10.35
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- China Medical Board
- Natural Science Foundation of Guangdong Province (2018A030310005)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- artificial intelligence adoption, public acceptance, intention to use, technology acceptance model, perceived usefulness, perceived ease of use, subjective norms, trust in medical staff, blindness prevention, primary care, Confucian culture, collectivism, authoritarianism, China
- MeSH terms
- Adolescent, Adult, Artificial Intelligence, China, Cross-Sectional Studies, Delivery of Health Care, Female, Humans, Male, Middle Aged, Psychology, Young Adult
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