人工智能 (AI) 可以在打破坏消息时帮助开发通用临床技能吗:定量评估
Miriam E Armstrong1, Phil Bright2, Stephen Glen1
1Federation of the Royal Colleges of Physicians of the United Kingdom, 11 St Andrews Place, Regent's Park, London, United Kingdom NW1 4LE.
Clinical medicine (London, England)
|February 28, 2026
概括
人工智能 (AI) 可以有效地支持教学敏感的沟通技巧,如打破坏消息,补充传统方法. 结合人工智能与人类辅助的混合方法提供了全面的研究生医学教育.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 沟通技巧培训 培训 沟通技巧培训
背景情况:
- 人工智能 (AI) 越来越多地被用于医学教育.
- 它在培养复杂的沟通技能的作用,例如打破坏消息,不那么明确.
- 皇家医学院联合医师培训委员会 (JRCPTB) 调查了AI在这个领域的潜力.
研究的目的:
- 探索人工智能产生的指导是否可以补充或增强传统的人类辅助教学方法,以打破坏消息.
- 将人工智能生成的内容与通过医疗专业人员之间促进讨论开发的内容进行比较.
主要方法:
- 开发了两套关于打破坏消息的指导:一个是使用生成人工智能 (ChatGPT),另一个是通过促进讨论.
- 每种方法的总结陈述通过匿名在线咨询向JRCPTB专业咨询委员会 (SAC) 成员提交.
- 受访者使用利克尔特比例表来评价协议,并提供了定性反;收集了人口统计数据.
主要成果:
- 69名医生和11名世俗代表完成了传统方法的80次评估和AI方法的75次评估.
- 两种方法都产生了11个高度一致的陈述 (>85%) 的共同核心,以及独特的陈述.
- 61%的人更喜欢人工智能产生的内容,22%的人更喜欢传统内容,17%的人没有偏好;女性对人工智能表现出明显的偏好 (p=0.003).
结论:
- 人工智能产生的内容,当策划,有效地支持教学敏感的沟通技巧,补充传统方法.
- 将人工智能与人类辅助整合在一起的混合模型可以提供一个全面而高效的研究生医学教育方法.
- 需要进一步的研究,以确保AI内容的质量,适当性,并保持监督者-学习者信任.
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