Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, OH, USA.
Nat Neurosci. 2024 Apr;27(4):615-628. doi: 10.1038/s41593-024-01608-4. Epub 2024 Mar 22.
The growing availability of large-population human biomedical datasets provides researchers with unique opportunities to conduct rigorous and impactful studies on brain and behavioral development, allowing for a more comprehensive understanding of neurodevelopment in diverse populations. However, the patterns observed in these datasets are more likely to be influenced by upstream structural inequities (that is, structural racism), which can lead to health disparities based on race, ethnicity and social class. This paper addresses the need for guidance and self-reflection in biomedical research on conceptualizing, contextualizing and communicating issues related to race and ethnicity. We provide recommendations as a starting point for researchers to rethink race and ethnicity choices in study design, model specification, statistical analysis and communication of results, implement practices to avoid the further stigmatization of historically minoritized groups, and engage in research practices that counteract existing harmful biases.
越来越多的大型人群人类生物医学数据集为研究人员提供了独特的机会，可以对大脑和行为发育进行严格而有影响力的研究，从而更全面地了解不同人群的神经发育。然而，这些数据集中观察到的模式更有可能受到上游结构不平等（即结构性种族主义）的影响，这可能导致基于种族、族裔和社会阶层的健康差异。本文针对在概念化、情境化和交流与种族和族裔相关问题方面的生物医学研究中指导和自我反思的需求提供了建议。我们提供了一些建议，作为研究人员重新思考研究设计、模型规范、统计分析和结果交流中种族和族裔选择的起点，实施避免历史上少数群体进一步污名化的实践，并参与对抗现有有害偏见的研究实践。
