Thoumi Andrea, Kukoyi Olurotimi, Kaalund Kamaria, Garcia Rico Yazmin, Gonzalez-Guarda Rosa M, Pearson Jay, Martinez-Bianchi Viviana
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA.
UNC-Chapel Hill, Chapel Hill, North Carolina, USA.
Health Equity. 2025 May 27;9(1):281-289. doi: 10.1089/heq.2024.0127. eCollection 2025.
Collecting accurate and consistent sociodemographic data is needed to improve health measurement and public health interventions. Missing or inaccurate data hinders the adequate assessment of the state of access, quality, and coverage in the overall population and communities experiencing social marginalization. Health measurement requires data labels that humanize all populations living, working, and residing across the United States and territories. Humanization is fundamentally grounded in the concepts of human dignity and ethical identity integrity. An often-overlooked form of exclusion in health care is the long-standing use of dehumanizing language, including its use in health measurement and data collection efforts, to refer to immigrant populations. In this perspective, we delineate ethical concerns regarding the use of dehumanizing language when referring to immigrant populations. We provide recommendations for health providers, researchers, and policy makers in improving humanizing language in health equity data collection and reporting through engagement of community experts, use of alternative language, implementation, and monitoring.
收集准确且一致的社会人口学数据对于改善健康测量和公共卫生干预措施而言是必要的。缺失或不准确的数据会妨碍对总体人群以及经历社会边缘化的社区的可及性、质量和覆盖范围状况进行充分评估。健康测量需要数据标签，以体现生活、工作和居住在美国及各领地的所有人的人性。人性化从根本上基于人的尊严和道德身份完整性的概念。医疗保健中一种常被忽视的排斥形式是长期使用非人性化语言，包括在健康测量和数据收集工作中提及移民人口时使用这种语言。从这个角度出发，我们阐述了在提及移民人口时使用非人性化语言所涉及的伦理问题。我们为医疗服务提供者、研究人员和政策制定者提供建议，通过社区专家的参与、使用替代语言、实施和监测，在健康公平数据收集和报告中改善人性化语言的使用。
