根据临床学习者偏好,开发基于公平评估特征的证据,使用离散选择实验
Sandra Perez1, Alan Schwartz2, Karen E Hauer3
1S. Perez is a resident, Department of Pathology, University of California, San Francisco, School of Medicine, San Francisco, California.
概括
医疗培训中的公平评价价值学习者身份和同行比较的成长. 这支持一种反赤字模式,以增强医学中的多样性和包容性.
科学领域:
- 医学教育 医学教育
- 健康 公平 卫生 公平
- 医生劳动力发展工作人员
背景情况:
- 在临床环境中公平评估对于多元化的医生劳动力至关重要.
- 了解学习者的偏好,为优质的医学教育提供信息,并解决医疗保健差异.
研究的目的:
- 为了在临床培训中建立一个公平评估模型,收集证据.
- 将"反赤字成就框架"应用于医学教育评估.
主要方法:
- 一个离散的选择实验与306医学学生和住户在9个美国机构.
- 一个具有6个属性的2个级别的工具评估了学习者对公平评估组件的偏好.
- 一个混合效应的逻辑模型确定了最有价值的评估属性.
主要成果:
- 学习者优先考虑认同,背景和轨迹的欣赏,监督者偏见培训和叙事评估,而不是同行比较.
- 在医学中代表性不足 (UIM) 和非UIM学习者之间,没有发现属性价值的显著差异.
- 与医学生相比,居民更重视监督者对学习者身份和偏见培训的认可.
结论:
- 调查结果支持在医疗评估中公平的反赤字模型.
- 这项研究为促进UIM学习者成功的倡议提供了信息.
- 该研究指导医疗教育中的公平,多样性和包容性努力.
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