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人工智能(AI)在冠状病毒大流行期间在初级保健中的接受度:患者的性别、年龄和健康意识的作用是什么?一项两阶段试点研究。

Artificial intelligence (AI) acceptance in primary care during the coronavirus pandemic: What is the role of patients' gender, age and health awareness? A two-phase pilot study.

机构信息

Department of Industrial Engineering and Management, Afeka College of Engineering, Tel Aviv, Israel.

出版信息

Front Public Health. 2023 Jan 9;10:931225. doi: 10.3389/fpubh.2022.931225. eCollection 2022.


DOI:10.3389/fpubh.2022.931225
PMID:36699881
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9868720/
Abstract

BACKGROUND: Artificial intelligence (AI) is steadily entering and transforming the health care and Primary Care (PC) domains. AI-based applications assist physicians in disease detection, medical advice, triage, clinical decision-making, diagnostics and digital public health. Recent literature has explored physicians' perspectives on the potential impact of digital public health on key tasks in PC. However, limited attention has been given to patients' perspectives of AI acceptance in PC, specifically during the coronavirus pandemic. Addressing this research gap, we administered a pilot study to investigate criteria for patients' readiness to use AI-based PC applications by analyzing key factors affecting the adoption of digital public health technology. METHODS: The pilot study utilized a two-phase mixed methods approach. First, we conducted a qualitative study with 18 semi-structured interviews. Second, based on the Technology Readiness and Acceptance Model (TRAM), we conducted an online survey ( = 447). RESULTS: The results indicate that respondents who scored high on innovativeness had a higher level of readiness to use AI-based technology in PC during the coronavirus pandemic. Surprisingly, patients' health awareness and sociodemographic factors, such as age, gender and education, were not significant predictors of AI-based technology acceptance in PC. CONCLUSIONS: This paper makes two major contributions. First, we highlight key social and behavioral determinants of acceptance of AI-enabled health care and PC applications. Second, we propose that to increase the usability of digital public health tools and accelerate patients' AI adoption, in complex digital public health care ecosystems, we call for implementing adaptive, population-specific promotions of AI technologies and applications.

摘要

背景:人工智能(AI)正稳步进入并改变医疗保健和初级保健(PC)领域。基于 AI 的应用程序可帮助医生进行疾病检测、医疗建议、分诊、临床决策、诊断和数字公共卫生。最近的文献探讨了医生对数字公共卫生对 PC 关键任务的潜在影响的看法。然而,对于患者在 PC 中接受 AI 的看法,特别是在冠状病毒大流行期间,关注的程度有限。为了弥补这一研究空白,我们进行了一项试点研究,通过分析影响数字公共卫生技术采用的关键因素,来调查患者使用基于 AI 的 PC 应用程序的准备情况的标准。

方法:该试点研究采用了两阶段混合方法。首先,我们进行了一项有 18 名参与者的半结构式访谈的定性研究。其次,根据技术准备和接受模型(TRAM),我们进行了一项在线调查(n = 447)。

结果:结果表明,在冠状病毒大流行期间,创新性得分较高的受访者对基于 AI 的技术在 PC 中的使用准备程度更高。令人惊讶的是,患者的健康意识和社会人口因素,如年龄、性别和教育程度,并不是 PC 中基于 AI 的技术接受度的显著预测因素。

结论:本文有两个主要贡献。首先,我们强调了接受 AI 支持的医疗保健和 PC 应用程序的关键社会和行为决定因素。其次,我们提出,为了提高数字公共卫生工具的可用性并加速患者对 AI 的采用,在复杂的数字公共卫生保健生态系统中,我们呼吁实施适应性的、针对特定人群的 AI 技术和应用推广。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd44/9868720/534394d432b5/fpubh-10-931225-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd44/9868720/809ae30ed82c/fpubh-10-931225-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd44/9868720/f24f2b9aa2bd/fpubh-10-931225-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd44/9868720/534394d432b5/fpubh-10-931225-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd44/9868720/809ae30ed82c/fpubh-10-931225-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd44/9868720/f24f2b9aa2bd/fpubh-10-931225-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd44/9868720/534394d432b5/fpubh-10-931225-g0003.jpg

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[7]
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[9]
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本文引用的文献

[1]
A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare.

Digit Health. 2022-3-24

[2]
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[3]
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Artif Intell Med. 2021-11

[4]
The Response of Governments and Public Health Agencies to COVID-19 Pandemics on Social Media: A Multi-Country Analysis of Twitter Discourse.

Front Public Health. 2021

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miRNAs as biomarkers for early cancer detection and their application in the development of new diagnostic tools.

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BMC Public Health. 2021-1-6

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Digital Health Strategies to Fight COVID-19 Worldwide: Challenges, Recommendations, and a Call for Papers.

J Med Internet Res. 2020-6-16

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