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相关概念视频

Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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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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Structuralism01:26

Structuralism

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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.
Titchener's approach to structuralism was unique. He...
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Manipulation and Analysis01:21

Manipulation and Analysis

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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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Stereotype Content Model02:16

Stereotype Content Model

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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Levels of Use of a GIS01:29

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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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探索结构性种族主义与心理健康之间的关联:地理空间和机器学习分析.

Fahimeh Mohebbi1, Amir Masoud Forati2, Lucas Torres3

  • 1College of Engineering and Applied Science, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.

JMIR public health and surveillance
|May 3, 2024
PubMed
概括

结构性种族主义显著影响心理健康差异,不成比例地影响非洲裔美国人社区. 关键因素包括吸烟,贫困和缺乏医疗保险,需要有针对性的干预措施.

关键词:
深度学习是一种深度学习.地理空间地缘空间在健康方面存在差异.机器学习是机器学习.心理健康 心理健康种族差异是种族的差异.健康的社会决定因素.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
  • 地理空间分析的研究.
  • 深度学习 (Deep Learning) 是一种深度学习.

背景情况:

  • 结构性种族主义是精神健康差异的一个已知的驱动因素.
  • 之前的研究集中在个人因素上,对它们作为结构性种族主义表现的集体影响的探索较少.
  • 密尔沃基县的多样性为调查这些多因素影响提供了一个独特的环境.

研究的目的:

  • 确定密尔沃基县结构性种族主义和心理健康差异之间的联系.
  • 采用地理空间和深度学习技术进行全面分析.
  • 量化结构性种族主义对心理健康不良患病率的影响.

主要方法:

  • 编译了217个地理引用变量,最初不包括种族,以确定非种族决定因素.
  • 使用基于树的方法 (随机森林) 和常规技术进行变量选择,解决多对线性.
  • 应用地理加权随机森林和自组织地图,使用K-means集群来分析空间异质性和量化种族主义的影响.

主要成果:

  • 十二个影响因素解释了95.11%的心理健康变化.
  • 最主要的因素包括吸烟,贫困,睡眠不足,缺乏医疗保险,就业和年龄.
  • 非洲裔美国人社区的高风险心理健康群体的可能性增加了2.23倍.

结论:

  • 结构性种族主义显然塑造了心理健康差异,黑人社区承担了不成比例的负担.
  • 综合的地理空间和深度学习方法有效地阐明了心理健康的复杂社会决定因素.
  • 调查结果强调了有针对性的干预措施的必要性,该干预措施应对个人和系统因素,以减少心理健康不平等.