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相关概念视频

Stereotypes, Prejudice, and Discrimination02:55

Stereotypes, Prejudice, and Discrimination

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Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
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Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

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Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
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Cross-Sectional Research01:50

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In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
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Archival Research01:40

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Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
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Structuralism01:26

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Structuralism, an early psychological theory developed by Wilhelm Wundt and his student Edward Bradford Titchener, sought to dissect the human mind into its most fundamental components. Wundt's groundbreaking work in his laboratory set the stage for Titchener to define structuralism's goal as cataloging the "atoms" of the mind—sensations, images, and feelings—akin to how chemists identify elements of matter.
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The halo effect is a cognitive bias in which an individual's overall impression influences judgments about their specific traits. This psychological phenomenon leads people to associate positive characteristics with those they perceive as generally good and negative characteristics with those they view as bad. This effect is particularly influential in social perception, professional evaluations, and decision-making processes.The Psychological Basis of the Halo EffectThe halo effect is rooted...
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开发一个指数来衡量结构性种族主义:方法论过程,挑战和考虑.

Christopher M Amissah1,2, Alisha A Crump1,3, Yu-Hua Fu1

  • 1Department of Practice, Sciences, and Health Outcomes Research, School of Pharmacy, University of Maryland, Baltimore, MD 21201, USA.

International journal of environmental research and public health
|February 27, 2026
PubMed
概括

制定对结构性种族主义的测量措施对于健康公平研究至关重要. 这篇论文详细介绍了方法上的挑战,并为为黑人和西班牙裔人口创建生态水平指数提供了指南.

关键词:
德尔菲的过程 德尔菲的过程数据挑战数据挑战生态水平指数指数在健康方面存在差异.卫生公平性健康公平性发展指数发展指数指数发展措施发展措施方法论上的挑战 方法论上的挑战心理测量是指心理测量.结构性种族主义是结构性种族主义.

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科学领域:

  • 公共卫生 公共卫生
  • 社会流行病学 社会流行病学
  • 健康 公平 研究 健康 公平 研究

背景情况:

  • 解决健康不平等问题需要有效的结构性种族主义措施.
  • 现有的生态水平指标对结构性种族主义影响美国黑人和西班牙裔人口是有限的.
  • 国家少数民族健康研究所和健康差异框架指导了开发过程.

研究的目的:

  • 描述开发生态层面结构性种族主义指数的方法过程.
  • 记录遇到的实质方法和数据相关挑战.
  • 为开发类似指数的研究人员提供指南.

主要方法:

  • 一个经过修改的Delphi共识过程,涉及各种各样的专家 (社会流行病学家,健康不平等研究人员,社区成员,经济不平等专家,心理学家).
  • 从公共来源提取和协调地理层面数据的五步方法.
  • 识别和选择结构性种族主义的指标.

主要成果:

  • 在指数开发过程中遇到了重大的方法和数据挑战.
  • 关键的挑战包括有限的细粒度地理数据,不良的数据文档,不一致的报告和数据适应困难.
  • 这篇论文侧重于过程和挑战,而不是提出最终的索引.

结论:

  • 开发结构性种族主义的生态测量是复杂的,数据密集的.
  • 透明度,适应性和严格的数据选择对于推进公共卫生公平研究至关重要.
  • 这篇论文是未来研究的方法指南和警告帐户.