人工智能集成医疗保健应用的驱动因素。病人的角度

IF 12.9 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2025-04-15 DOI:10.1016/j.techfore.2025.124144

David E. Kalisz

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引用次数: 0

摘要

医疗保健行业广泛采用人工智能（AI）来提高运营效率和护理质量。然而，患者采用和使用人工智能集成医疗保健应用程序（AIIHA）进行咨询和治疗的情况尚未得到充分调查。我们的研究通过检查一个独特的上下文模型来解决这一差距，该模型包括患者对AIIHA的意图和行为的前因。所提出的模型结合了四个新结构，即隐私关注、享乐动机、信任和患者医疗保健参与，以及绩效和努力预期，从而与AIIHA上下文相结合。采用偏最小二乘结构方程模型（PLS-SEM）对上述变量与患者行为意图之间的关联模型进行了假设，并对从不同国家的受访者在线收集的数据（N = 522）进行了分析。此外，还测试了最近大流行的缓和作用，以评估行为意图与使用AIIHA行为之间的关联强度。结果表明，绩效期望、努力期望、享乐动机、患者医疗保健参与和信任影响患者对AIIHA的行为意向。努力期望对绩效期望有显著影响，患者行为意图对使用行为有显著影响，隐私关注对患者信任有显著负向影响。

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Drivers of artificial intelligence integrated healthcare applications. Patients' perspective

The healthcare sector has extensively adopted Artificial Intelligence (AI) to improve operational efficiency and care quality. However, patients' adoption and use of AI-integrated healthcare applications (AIIHA) for consultation and treatment have not been investigated sufficiently. Our study addresses this gap by examining a unique contextual model comprising antecedents of patients' intentions and behavior towards AIIHA. The proposed model is contextualized to the AIIHA context by incorporating four new constructs, namely privacy concern, hedonic motivation, trust, and patient healthcare engagement, along with performance and effort expectancy. The model hypothesizing the association of the aforementioned variables with patients' behavioral intentions is tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data (N = 522) collected online from respondents in different countries. In addition, the moderating effect of the recent pandemic is also tested to evaluate the strength of the association between behavioral intentions and usage behavior towards AIIHA. The results reveal that performance expectancy, effort expectancy, hedonic motivation, patient healthcare engagement, and trust shape patients' behavioral intentions towards AIIHA. Also, there is a statistically significant effect of effort expectancy on performance expectancy, patients' behavioral intentions on usage behavior, and the negative impact of privacy concerns on patients' trust.

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来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

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