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推进护理科学领域健康公平性的多种方法:招募、数据与传播。

Multiple approaches to advance health equity in nursing science: Recruitment, data, and dissemination.

作者信息

Wu Bei, Zhu Zheng

机构信息

Rory Meyers College of Nursing, New York University, New York, NY.

Rory Meyers College of Nursing, New York University, New York, NY; School of Nursing, Fudan University, Shanghai, China.

出版信息

Nurs Outlook. 2025 Jan-Feb;73(1):102343. doi: 10.1016/j.outlook.2024.102343. Epub 2024 Dec 12.

DOI:10.1016/j.outlook.2024.102343
PMID:39671773
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11810570/
Abstract

Ensuring equitable care and health outcomes for all populations is essential in nursing science. However, achieving health equity in nursing science necessitates a multifaceted approach to address the complex factors influencing health disparities. This paper presented the keynote address delivered at the Advanced Methods Conference hosted by the Council for Advancement of Nursing Science in 2023. We identified critical gaps in health equity within nursing science, emphasizing the need for innovative recruitment strategies, comprehensive data analysis, and targeted dissemination efforts. This paper underscores the importance of equity in artificial intelligence research, highlighting issues such as biases in machine learning models and the underrepresentation of minoritized groups. Bridging the current gaps in health equity research within nursing science requires a systematic and forward-thinking approach.

摘要

确保所有人群获得公平的护理和健康结果在护理科学中至关重要。然而,在护理科学中实现健康公平需要采取多方面的方法来应对影响健康差距的复杂因素。本文介绍了在2023年护理科学促进理事会主办的高级方法会议上发表的主题演讲。我们确定了护理科学中健康公平方面的关键差距,强调了创新招募策略、全面数据分析和有针对性的传播努力的必要性。本文强调了人工智能研究中公平性的重要性,突出了机器学习模型中的偏差和少数群体代表性不足等问题。弥合护理科学中当前健康公平研究的差距需要一种系统且具有前瞻性的方法。

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Turning the Health Equity Lens to Diversity in Asian American Health Profiles.将健康公平视角转向亚裔美国人健康特征中的多样性。
Annu Rev Public Health. 2024 May;45(1):169-193. doi: 10.1146/annurev-publhealth-060222-023852. Epub 2024 Apr 3.
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Residential Structural Racism and Prevalence of Chronic Health Conditions.住宅结构性种族主义与慢性健康状况的流行。
JAMA Netw Open. 2023 Dec 1;6(12):e2348914. doi: 10.1001/jamanetworkopen.2023.48914.
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Perceptions of Data Set Experts on Important Characteristics of Health Data Sets Ready for Machine Learning: A Qualitative Study.数据专家对适合机器学习的健康数据集的重要特征的看法:一项定性研究。
JAMA Netw Open. 2023 Dec 1;6(12):e2345892. doi: 10.1001/jamanetworkopen.2023.45892.
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Advancing health equity-Agency for Healthcare Research and Quality research and action agenda.推进健康公平——医疗保健研究与质量局的研究及行动议程。
Health Serv Res. 2023 Dec;58 Suppl 3(Suppl 3):275-280. doi: 10.1111/1475-6773.14230.
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Advancing health equity through nursing research.通过护理研究促进健康公平。
Nurs Outlook. 2023 Nov-Dec;71(6):102049. doi: 10.1016/j.outlook.2023.102049. Epub 2023 Sep 16.
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Considerations for addressing bias in artificial intelligence for health equity.解决人工智能中影响健康公平性的偏差的考量因素。
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Data Equity for Asian American and Native Hawaiian and Other Pacific Islander People in Reproductive Health Research.亚裔美国人、夏威夷原住民和其他太平洋岛民在生殖健康研究中的数据公平性。
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Socioeconomic Status Disparities in Cognitive and Physical Functional Impairment among Older Adults: Comparison of Asians with other Major Racial/Ethnic Groups.老年人认知和身体功能障碍的社会经济地位差异:亚洲人与其他主要种族/族裔群体的比较。
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Raising the Bar for Language Equity Health Care Research.提高语言平等医疗保健研究的标准。
JAMA Netw Open. 2023 Jul 3;6(7):e2324485. doi: 10.1001/jamanetworkopen.2023.24485.
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