Abstract
BackgroundPoor 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.ObjectiveThis 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.MethodsWe 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.ResultsStandardized 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.ConclusionsThe 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.
Highlights
BackgroundAs part of the fourth industrial revolution, artificial intelligence (AI) has achieved massive progress and explosive growth
J Med Internet Res 2019 | vol 21 | iss. 10 | e14316 | p. 1 analysis is underdeveloped, and the Chinese public are generally mistrustful of medical staff and the Chinese medical system
As no prior studies have been conducted on the implementation of ophthalmic Artificial intelligence (AI) devices in the Chinese context, we have briefly described the results of our formative qualitative studies of 3 community health center composite reliability (CR) (CHC) where an ophthalmic AI device was used
Summary
As part of the fourth industrial revolution, artificial intelligence (AI) has achieved massive progress and explosive growth It is actively applied in health care to perform a wide range of functions such as patient administration and monitoring, clinical decision support, risk prediction, medical error reduction, health care intervention, and productivity improvement [1,2]. These potential benefits could contribute greatly to primary care services in China, where the health system is facing great challenges owing to an aging population and an increase in chronic noncommunicable diseases [3]. 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
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