Exploring emerging physician competencies: Analyzing insights from medical care influencers on X.

IF 3.3 2区教育学 Q1 EDUCATION, SCIENTIFIC DISCIPLINES

Medical Teacher Pub Date : 2025-09-20 DOI:10.1080/0142159X.2025.2560578

Yunzhu Ouyang, Qi Guo, Cecilia B Alves, Andrea J Gotzmann, Marguerite Roy, Judy L McCormick

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引用次数: 0

Abstract

Purpose: In the post-COVID era, recognizing evolving physician competencies is crucial for guiding medical education and test development. This study aimed to extract valuable insights concerning emerging physician competencies from influencers' posts on X, leveraging an AI-driven approach.

Method: Two datasets pertaining to medical competency were analyzed, with posts collected from January 1, 2020, to June 1, 2023. Social network analyses were performed to identify influencers leading medical competency conversations on X. ChatGPT was utilized for textual analyses of influencers' posts to reveal core themes of physician competencies.

Results: Social network analysis revealed that medical professionals played a predominant role in disseminating information on medical competency on X. Textual analysis identified six core themes in the CanMEDS dataset-clinical learning environment, anti-racism, EDI, adaptive expertise, planetary health, and leadership development-and seven in the MedEd dataset-cultural competency, structural competency, assessment models, virtual care, EDI, leadership development, and wellness.

Conclusion: The identified themes emphasize physicians' competencies in addressing health disparities, preparing for real-world challenges, adapting to the evolving healthcare landscape, and leading effectively in diverse healthcare settings. The findings hold significant implications for medical education, test development, and the integration of artificial intelligence in physician competency assessment.

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探索新兴医师能力：分析医疗保健影响者对X的见解。

目的：在后covid时代，认识到不断发展的医生能力对于指导医学教育和测试开发至关重要。本研究旨在利用人工智能驱动的方法，从有影响力的人在X上的帖子中提取有关新兴医生能力的宝贵见解。方法：对2020年1月1日至2023年6月1日收集的两组医疗胜任力相关数据进行分析。进行社会网络分析以确定在x上领导医疗能力对话的影响者。ChatGPT用于对影响者的帖子进行文本分析，以揭示医生能力的核心主题。结果：社会网络分析显示，医疗专业人员在x上传播医疗能力信息方面发挥了主导作用。文本分析确定了CanMEDS数据中的6个核心主题：临床学习环境、反种族主义、EDI、适应性专业知识、行星健康和领导力发展，以及medd数据中的7个核心主题：文化能力、结构能力、评估模型、虚拟护理、EDI、领导力发展和健康。结论：确定的主题强调医生解决健康差异的能力，为现实世界的挑战做准备，适应不断变化的医疗保健环境，并在不同的医疗保健环境中有效地领导。这些发现对医学教育、测试开发以及人工智能在医生能力评估中的整合具有重要意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Medical Teacher 医学-卫生保健

CiteScore

7.80

自引率

8.50%

发文量

396

审稿时长

3-6 weeks

期刊介绍： Medical Teacher provides accounts of new teaching methods, guidance on structuring courses and assessing achievement, and serves as a forum for communication between medical teachers and those involved in general education. In particular, the journal recognizes the problems teachers have in keeping up-to-date with the developments in educational methods that lead to more effective teaching and learning at a time when the content of the curriculum—from medical procedures to policy changes in health care provision—is also changing. The journal features reports of innovation and research in medical education, case studies, survey articles, practical guidelines, reviews of current literature and book reviews. All articles are peer reviewed.