Digital health competences and AI beliefs as conditions for the practice of evidence-based medicine: a study of prospective physicians in Canada.

IF 3.1 2区 医学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Medical Education Online Pub Date : 2025-12-01 Epub Date: 2025-01-31 DOI:10.1080/10872981.2025.2459910
Gerit Wagner, Mickaël Ringeval, Louis Raymond, Guy Paré
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引用次数: 0

Abstract

Background: The practice of evidence-based medicine (EBM) has become pivotal in enhancing medical care and patient outcomes. With the diffusion of innovation in healthcare organizations, EBM can be expected to depend on medical professionals' competences with digital health (dHealth) and artificial intelligence (AI) technologies.

Objective: We aim to investigate the effect of dHealth competences and perceptions of AI on the adoption of EBM among prospective physicians. By focusing on dHealth and AI technologies, the study seeks to inform the redesign of medical curricula to better prepare students for the demands of evidence-based medical practice.

Methods: A cross-sectional survey was administered online to students at the University of Montreal's medical school, which has approximately 1,400 enrolled students. The survey included questions on students' dHealth competences, perceptions of AI, and their practice of EBM. Using structural equation modeling (SEM), we analyzed data from 177 respondents to test our research model.

Results: Our analysis indicates that medical students possess foundational knowledge competences of dHealth technologies and perceive AI to play an important role in the future of medicine. Yet, their experiential competences with dHealth technologies are limited. Our findings reveal that experiential dHealth competences are significantly related to the practice of EBM (β = 0.42, p < 0.001), as well as students' perceptions of the role of AI in the future of medicine (β = 0.39, p < 0.001), which, in turn, also affect EBM (β = 0.19, p < 0.05).

Conclusions: The study underscores the necessity of enhancing students' competences related to dHealth and considering their perceptions of the role of AI in the medical profession. In particular, the low levels of experiential dHealth competences highlight a promising starting point for training future physicians while simultaneously strengthening their practice of EBM. Accordingly, we suggest revising medical curricula to focus on providing students with practical experiences with dHealth and AI technologies.

数字健康能力和人工智能信念作为循证医学实践的条件:对加拿大未来医生的研究。
背景:循证医学(EBM)的实践已成为提高医疗保健和患者的结果的关键。随着创新在医疗保健组织中的传播,EBM可以预期依赖于医疗专业人员在数字健康(dHealth)和人工智能(AI)技术方面的能力。目的:我们的目的是调查dHealth能力和人工智能对未来医生采用循证医学的影响。通过关注数字健康和人工智能技术,该研究旨在为医学课程的重新设计提供信息,以更好地为学生提供循证医学实践的需求。方法:对蒙特利尔大学医学院约1400名在校生进行在线横断面调查。调查的问题包括学生的dHealth能力、对人工智能的看法以及他们对循证医学的实践。我们使用结构方程模型(SEM)对177名受访者的数据进行分析,以验证我们的研究模型。结果:我们的分析表明,医学生拥有dHealth技术的基础知识能力,并认为AI在未来医学中发挥重要作用。然而,他们对数字健康技术的经验能力是有限的。我们的研究结果显示,体验性数字健康能力与EBM实践显著相关(β = 0.42, p p p)。结论:该研究强调了提高学生与数字健康相关的能力的必要性,并考虑到他们对人工智能在医学专业中的作用的看法。特别是,低水平的体验式dHealth能力突出了培训未来医生的一个有希望的起点,同时加强了他们的EBM实践。因此,我们建议修改医学课程,重点为学生提供dHealth和人工智能技术的实践经验。
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来源期刊
Medical Education Online
Medical Education Online EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
6.00
自引率
2.20%
发文量
97
审稿时长
8 weeks
期刊介绍: Medical Education Online is an open access journal of health care education, publishing peer-reviewed research, perspectives, reviews, and early documentation of new ideas and trends. Medical Education Online aims to disseminate information on the education and training of physicians and other health care professionals. Manuscripts may address any aspect of health care education and training, including, but not limited to: -Basic science education -Clinical science education -Residency education -Learning theory -Problem-based learning (PBL) -Curriculum development -Research design and statistics -Measurement and evaluation -Faculty development -Informatics/web
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