Tweed Mike, Purdie Gordon, Lacey Cameron
Senior Lecturer, Department of Medicine, University of Otago, Wellington.
Biostatistician, University of Otago, Wellington.
N Z Med J. 2019 Mar 8;132(1491):71-77.
There is inequitable distribution of health risks, exposures, resources and outcomes by ethnicity. This may be contributed to by health professional bias. The aim of this study was to investigate the relationship between ethnicity of patients, within written assessment case scenarios, and medical students' response correctness and certainty.
Otago Medical School students sit a 150 MCQ progress test with item level response certainty. Patient ethnicity for 60 MCQ case scenarios was varied between two ethnic groups (New Zealand European, Māori) and none specified. Analysis of responses by patient ethnicity was undertaken to compare: odds of correctness; level of certainty; correctness for level of certainty and also by year groups and ability.
One thousand one hundred and three students sat the test. There was no significant difference in odds of correctness or level of certainty by the ethnicity of the patient case scenario. These did not differ significantly by year groups or ability groups, or for correctness by level of certainty.
No systematic differences in correctness or certainty of student responses to case scenarios by patient ethnicity were detected. Further exploration is warranted, including incorporating more ethnicity descriptors, analysis of incorrect answers, analyses for patterns responses over time by individual students, and selecting questions where varying patient ethnicity is expected to alter the correct response or difficulty.
健康风险、暴露因素、资源和结果在不同种族间的分布存在不平等。这可能是由医疗专业人员的偏见导致的。本研究的目的是在书面评估病例场景中，调查患者种族与医学生回答的正确性和确定性之间的关系。
奥塔哥医学院的学生参加一场有150道多项选择题的进度测试，并提供每题回答的确定性程度。60道多项选择题病例场景中的患者种族在两个种族群体（新西兰欧洲裔、毛利人）之间变化，且有一些未明确说明。对按患者种族分类的回答进行分析，以比较：回答正确的几率；确定性程度；确定性程度与回答正确性的关系，以及按年级和能力的情况。
1103名学生参加了测试。患者病例场景的种族对回答正确的几率或确定性程度没有显著差异。这些在年级组或能力组之间，以及确定性程度与回答正确性之间也没有显著差异。
未检测到学生对病例场景的回答在正确性或确定性方面因患者种族而存在系统差异。有必要进行进一步探索，包括纳入更多种族描述符、分析错误答案、分析个别学生随时间的回答模式，以及选择预计不同患者种族会改变正确答案或难度的问题。
