Wagner Gerit, Ringeval Mickaël, Raymond Louis, Paré Guy
Faculty Information Systems and Applied Computer Sciences, Otto-Friedrich Universität, Bamberg, DE, Germany.
Département de technologies de l'information, HEC Montréal, Montréal, CA, Canada.
Med Educ Online. 2025 Dec;30(1):2459910. doi: 10.1080/10872981.2025.2459910. Epub 2025 Jan 31.
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.
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.
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.
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, < 0.001), as well as students' perceptions of the role of AI in the future of medicine (β = 0.39, < 0.001), which, in turn, also affect EBM (β = 0.19, < 0.05).
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.
循证医学（EBM）实践已成为提升医疗护理和患者治疗效果的关键。随着医疗保健机构中创新的传播，循证医学有望依赖于医学专业人员在数字健康（dHealth）和人工智能（AI）技术方面的能力。
我们旨在调查数字健康能力和对人工智能的认知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，本研究旨在为医学课程的重新设计提供参考，以便更好地让学生为循证医学实践的需求做好准备。
对蒙特利尔大学医学院的学生进行了在线横断面调查，该医学院约有1400名注册学生。调查包括有关学生数字健康能力、对人工智能的认知以及他们的循证医学实践的问题。我们使用结构方程模型（SEM）分析了177名受访者的数据，以检验我们的研究模型。
我们的分析表明，医学生具备数字健康技术的基础知识能力，并认为人工智能在医学未来中将发挥重要作用。然而，他们在数字健康技术方面的实践能力有限。我们的研究结果表明，数字健康实践能力与循证医学实践显著相关（β = 0.42，< 0.001），以及学生对人工智能在医学未来中作用的认知（β = 0.39，< 0.001），而这反过来也会影响循证医学（β = 0.19，< 0.05）。
该研究强调了提高学生与数字健康相关能力并考虑他们对人工智能在医学职业中作用的认知的必要性。特别是，数字健康实践能力水平较低凸显了一个有前景的起点，可用于培训未来的医生，同时加强他们的循证医学实践。因此，我们建议修订医学课程，以专注于为学生提供数字健康和人工智能技术的实践经验。
