种族,民族以及在研究研究中收集和分析数据的考虑因素
Sima Sharghi1, Shokoufeh Khalatbari2, Amy Laird3
1Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA.
Journal of clinical and translational science
|December 10, 2024
概括
在人类受试者研究中收集和报告种族和种族数据需要标准化的指导方针,以防止偏见的结论. 这项研究批评了当前的做法,并提供了公平的替代方案,使用"我们都在计数"框架.
科学领域:
- 卫生公平研究 卫生公平研究
- 健康的社会决定因素
- 生物医学研究方法的方法.
背景情况:
- 关于种族和种族的人口统计数据在人类受试者研究中至关重要.
- 目前收集和报告这些数据的做法缺乏标准化,导致潜在的偏见和代表性不足的群体的误导.
- 人种/种族被误认为是一种生物变量,忽视了它的社会构造性质和对生活经验的影响.
研究的目的:
- 解决在研究中收集和报告种族和种族数据方面缺乏标准化指导方针的问题.
- 批评有关人口变量数据收集和分析的常见做法.
- 提出替代建议,将正义,公平,多样性和包容性 (JEDI) 纳入研究.
主要方法:
- 利用了"我们都在计数"数据公平框架,检查了数据项目的七个阶段.
- 对数据收集和分析阶段的集中批评和建议.
- 采用真实和假设的例子来说明常见的做法及其批评.
主要成果:
- 确定了当前种族和种族数据实践中的重大缺陷.
- 提供了对常见数据收集和分析方法的批评.
- 为更公平的数据处理提供了替代建议.
结论:
- 标准化,公平的做法对于准确和公正的研究结果至关重要.
- 我们都能计算的框架为整合JEDI原则提供了一个结构化的方法.
- 建议旨在指导研究人员从研究概念到传播,提高数据公平性.
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