FIU-RCMI ADMINISTRATIVE CORE

金融情报机构-RCMI 管理核心

基本信息

  • 批准号:
    10270605
  • 负责人:
  • 金额:
    $ 19.56万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-09-20 至 2022-06-30
  • 项目状态:
    已结题

项目摘要

SUMMARY Background: The United States (US) remains one of the epicenters of the global COVID-19 public health emergency, resulting in the government’s implementation of mitigation policies to stem and contain the virus. Despite these measures, people of color (POC - Blacks, Latinx and American Indian/Alaska Native populations) in the US are disproportionately represented in the epidemic. Objectives: The overall objective of this study is to evaluate the impact of macro and ecological policies by (a) using state and county level data to report on COVID-19 health outcomes experienced by communities of color and (b) conducting in-depth interviews among community members and providers to understand their perceptions about accessing and providing healthcare services. Design: Firstly, there will be an ecological study at the US state and county levels examining the relationship between racial/ethnic density and COVID-19 outcomes, considering selected COVID-19 risk factors (crowding, poverty level, percentage of essential workers) as moderators in that relationship. Secondly, there will be a policy study of differences on timing, interpretation and implementation of federal and state level mitigation policies on COVID-19 outcomes. Finally, interviews will be conducted to understand provider and patient viewpoints about how macro level social and health policies implemented by federal and local governments influence providers’ perception about delivery of care and community members’ perception about accessing COVID-19 healthcare services. Analysis: Descriptive statistics will be used to describe COVID-19 prevalence by racial/ethnic density in states and counties, followed by bivariate correlations. Any statistically significant correlation (<0.10) in the bivariate correlations will be incorporated into the regression models with COVID-19 incidence, prevalence and death rate as outcomes. Regression models will be used to determine the relationship between COVID-19 outcomes and state and county level demographic data and COVID-19 policy data. For the interviews, content analysis will be used to analyze qualitative data about perceived barriers and facilitators accessing and providing care. Significance: The results of this study will help to understand the underpinnings of social mechanisms and disparities contributing to the overrepresentation of underrepresented minority populations in the COVID-19 public health crisis. The study objectives are in line with recent NIMHD priorities issued for the COVID-19 response to support studies that investigate the “influence of state and local mitigation policies on differences in health services utilization and health outcomes, the role of community-level protective factors and interventions in mitigating the adverse consequences of the sector disruptions caused by the outbreak, the influence of COVID-19–related racism and other types of discrimination, and the role of social determinants of health in influencing preventive health behaviors”.
摘要 背景:美国仍是全球新冠肺炎公共卫生的中心之一 紧急情况,导致政府实施缓解政策以遏制和遏制病毒。 尽管采取了这些措施,有色人种(POC-黑人、拉丁裔和美国印第安人/阿拉斯加原住民 美国的人口)在疫情中的比例不成比例。目标:总体目标 这项研究旨在评估宏观和生态政策的影响,方法是:(A)使用州和县一级的数据来评估 有色人种社区体验到的新冠肺炎健康成果报告和(B)深入开展 对社区成员和提供商进行访谈,以了解他们对访问和 提供医疗保健服务。设计:首先,将在美国各州和县进行一项生态研究 审查种族/民族密度与新冠肺炎结果之间的关系的水平,考虑到选定的 新冠肺炎风险因素(拥挤、贫困水平、基本劳动者比例)作为调节因素 两性关系。其次,将对时间、解释和执行方面的差异进行政策研究 联邦和州两级缓解政策对新冠肺炎成果的影响。最后,将进行访谈,以 了解提供者和患者对宏观层面的社会和健康政策如何实施的观点 联邦和地方政府影响医疗服务提供者和社区成员对医疗服务提供的看法 对使用新冠肺炎医疗服务的看法。分析:描述性统计将用于 按州和县的种族/民族密度描述新冠肺炎的流行情况,然后是两个变量 关联性。双变量相关性中的任何统计显著相关性(&lt;0.10)都将被合并到 以新冠肺炎发病率、患病率和死亡率为影响因素的回归模型。回归模型 将用于确定新冠肺炎成果与州和县两级的关系 人口统计数据和新冠肺炎政策数据。对于访谈,将使用内容分析来分析 关于感知到的障碍和促进者获得和提供护理的定性数据。意义: 这项研究的结果将有助于理解社会机制和差异贡献的基础 在新冠肺炎公共卫生危机中,代表不足的少数族裔人口比例过高。这个 研究目标与最近为支持研究而发布的新冠肺炎优先事项保持一致 调查国家和地方缓解政策对卫生服务利用差异的影响 和健康结果,社区一级的保护因素和干预措施在减轻不利影响方面的作用 疫情造成的行业中断的后果,与新冠肺炎有关的种族主义和 其他类型的歧视,以及健康的社会决定因素在影响预防性健康方面的作用 行为“。

项目成果

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ERIC F WAGNER其他文献

ERIC F WAGNER的其他文献

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{{ truncateString('ERIC F WAGNER', 18)}}的其他基金

FIU Center for Reducing Health Disparities in Substance Abuse & HIV in South Florida
金融情报机构减少药物滥用健康差异中心
  • 批准号:
    10261849
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
FIU Center for Reducing Health Disparities in Substance Abuse & HIV in South Florida
金融情报机构减少药物滥用健康差异中心
  • 批准号:
    10201385
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
The FIU Research Center in a Minority Institution (FIU-RCMI)
金融情报机构少数族裔机构研究中心 (FIU-RCMI)
  • 批准号:
    10556507
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10556508
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
The FIU Research Center in a Minority Institution (FIU-RCMI)
金融情报机构少数族裔机构研究中心 (FIU-RCMI)
  • 批准号:
    10707394
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
Research Infrastructure Core
研究基础设施核心
  • 批准号:
    10194593
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
FIU-RCMI ADMINISTRATIVE CORE
金融情报机构-RCMI 管理核心
  • 批准号:
    10194585
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
FIU-RCMI ADMINISTRATIVE CORE
金融情报机构-RCMI 管理核心
  • 批准号:
    10194592
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
FIU-RCMI ADMINISTRATIVE CORE
金融情报机构-RCMI 管理核心
  • 批准号:
    10493616
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10707395
  • 财政年份:
    2017
  • 资助金额:
    $ 19.56万
  • 项目类别:

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