Addressing COVID-19 Testing Disparities in Vulnerable Populations Using a Community JITAI (Just in Time Adaptive Intervention) Approach: RADxUP Phase III

使用社区 JITAI(及时自适应干预)方法解决弱势群体中的 COVID-19 检测差异:RADxUP 第三阶段

基本信息

  • 批准号:
    10617103
  • 负责人:
  • 金额:
    $ 109.69万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-12-01 至 2024-11-30
  • 项目状态:
    已结题

项目摘要

Vulnerable populations including those with medical comorbidities, people living in rural settings and minorities experience significant COVID-19 disparities. Additionally, Hispanics and Blacks are significantly more likely to be infected and hospitalized when compared to White, Non-Hispanics. The proposed study builds on RADx-UP Phases I & Phase II work reaching these populations in three racially diverse regions: Houston/Harris County, South Texas, and Northeast Texas to increase SARS-CoV-2 testing, vaccination, and risk mitigation behaviors to reduce COVID-19 morbidity, mortality, and inequities among underserved populations in Texas. The proposed study leverages the partnerships and resources of the Center for Clinical and Translational Science (CCTS) including long-standing community partnerships. Phase III will include mixed methods and community-engaged approaches to inform adaptation of our existing (and the development of new) multilevel intervention messages, materials and strategies with a focus on increasing rapid SARS-CoV-2 testing. It will also include a broader focus on addressing the social determinants of health (SDOH) and an emphasis on combating misinformation. Innovative elements of the proposed study include testing a novel approach to optimize community engagement that uses real-time data to inform intervention adaptation and implementation, using advances in social computing and machine learning to better understand patterns of misinformation in social media, and using multilevel social network analysis techniques to increase intervention agility, intensity, and reach. This project has three aims: Aim 1) Expand existing sources of population-based COVID-19 surveillance data to quantify infection, testing and vaccination trends in three Texas regions, and use innovative methods to inform and evaluate the proposed interventions; Aim 2) Adapt, implement and evaluate the multilevel community just-in-time adaptive intervention (MC-JITAI) developed in Phase II to increase SARS-CoV-2 testing, mitigation behaviors, and COVID-19 vaccination, among underserved and vulnerable populations in three regions of Texas; and Aim 3) Determine the feasibility and effectiveness of leveraging multilevel social networks to improve SARS-CoV-2 testing and COVID-19 vaccination, in three regions of Texas.
弱势人群,包括患有医学合并症的人群、生活在农村地区的人群 环境和少数民族经历了显著的COVID-19差异。此外,西班牙裔和 与白色相比,黑人更容易被感染和住院, 非西班牙裔。拟议的研究建立在RADx-UP第一阶段和第二阶段工作的基础上, 这些人口分布在三个种族多样化的地区:休斯顿/哈里斯县,南德克萨斯州, 德克萨斯州东北部增加SARS-CoV-2检测,疫苗接种和风险缓解行为, 降低得克萨斯州COVID-19发病率、死亡率和服务不足人群的不平等。 这项拟议的研究利用了临床和医学中心的合作伙伴关系和资源, 转化科学(CCTS),包括长期的社区合作伙伴关系。第三阶段将 包括混合方法和社区参与的方法, 现有的(和新的)多层次干预信息、材料和 战略重点是增加SARS-CoV-2的快速检测。它还将包括更广泛的 重点解决健康的社会决定因素(SDOH), 错误信息拟议研究的创新要素包括测试一种新的方法, 优化社区参与,使用实时数据为干预措施适应提供信息, 实现,利用社会计算和机器学习的进步,以更好地了解 社交媒体中的错误信息模式,并使用多层次社交网络分析 提高干预灵活性、强度和覆盖范围的技术。该项目有三个目标: 目标1)扩大现有的基于人群的COVID-19监测数据来源,以量化 感染,检测和疫苗接种的趋势,并使用创新的方法, 通报和评价拟议的干预措施;目标2)调整、执行和评价 多层次社区即时适应性干预(MC-JITAI)在第二阶段发展, 增加SARS-CoV-2检测、缓解行为和COVID-19疫苗接种, 得克萨斯州三个地区的服务不足和弱势群体;目标3)确定 利用多层次社交网络改善SARS-CoV-2的可行性和有效性 测试和COVID-19疫苗接种,在德克萨斯州的三个地区。

项目成果

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Cici Bauer其他文献

Cici Bauer的其他文献

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{{ truncateString('Cici Bauer', 18)}}的其他基金

Addressing COVID-19 Testing Disparities in Vulnerable Populations Using a Community JITAI (Just in Time Adaptive Intervention) Approach: RADxUP Phase III
使用社区 JITAI(及时自适应干预)方法解决弱势群体中的 COVID-19 检测差异:RADxUP 第三阶段
  • 批准号:
    10847026
  • 财政年份:
    2022
  • 资助金额:
    $ 109.69万
  • 项目类别:
Predict to Prevent: Dynamic Spatiotemporal Analyses of Opioid Overdose to Guide Pre-Emptive Public Health Responses
预测预防:阿片类药物过量的动态时空分析以指导预防性公共卫生应对
  • 批准号:
    10618998
  • 财政年份:
    2022
  • 资助金额:
    $ 109.69万
  • 项目类别:
Predict to Prevent: Dynamic Spatiotemporal Analyses of Opioid Overdose to Guide Pre-Emptive Public Health Responses
预测预防:阿片类药物过量的动态时空分析以指导预防性公共卫生应对
  • 批准号:
    10444263
  • 财政年份:
    2022
  • 资助金额:
    $ 109.69万
  • 项目类别:

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