SCC-CIVIC-PG Track B: Community-Based Research meets Systems Approach: Closing the Loop on Child Lead Poisoning

SCC-CIVIC-PG 轨道 B:基于社区的研究与系统方法的结合:关闭儿童铅中毒的循环

基本信息

  • 批准号:
    2228687
  • 负责人:
  • 金额:
    $ 5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-10-01 至 2023-09-30
  • 项目状态:
    已结题

项目摘要

Even in communities where lead (Pb) exposure pathways are well understood, there are significant barriers to getting resources to the most affected individuals. These disparities in access to healthcare lead to a generational disadvantage as the households that face lead poisoning are disproportionately composed of racial minorities that live in low-income neighborhoods. This CIVIC research is at the intersection of community-based research and technology-driven frameworks. The goal of this research is to understand how to close communication gaps among households, healthcare providers, and policymakers. This has the potential to increase access to in-time health care, and enables quick and aggressive interventions via an app to be developed to tie all relevant parties together to improve the coordination of care to prevent child lead poisoning. The initial target community is St. Joseph County, Indiana. The research engages all relevant stakeholders in the process of lead poisoning diagnosis, intervention, and remediation/abatement. Broader impacts of the work include better health outcomes and less lead poisoning in children from low-income neighborhoods as well as engagement and training of engineering and chemistry undergraduate students. Students will be involved in developing accessible educational materials to inform households about the risks of lead exposure, especially in children, with the goal of helping community members identify and pursue lead assessment/abatement resources to protect the health of their loved ones. Student teams involved in the Stage 1 and follow-on Stage 2 program, if funded, will receive experiential learning opportunities and work with communities to translate community challenges into problem statements and help with the implementation of possible solutions. Research findings and developed technologies and informational materials will be scalable to other localities in the US and elsewhere with high soil and home lead concentrations.Although Community-Based Participatory Research encourages multidisciplinary case review teams to evaluate the effectiveness of interventions, an understanding of the relationship between individual, community, provider, and system factors is presently underexplored. This prevents the critical insight necessary to create risk reduction strategies, improve clinical pathways, and eliminate barriers to care. Through the CIVIC Stage 1 planning period, an interdisciplinary and multi stakeholder group of community members, health providers, researchers, and policymakers will be convened to understand the targeted community and the overlapping roles and responsibilities that each group has in closing the loop of lead detection in children and connecting households to resources that provide abatement interventions. These design thinking sessions and discussions will inform a framework for deploying community health workers, who work directly with impacted communities, and provide informational and technological solutions in the form of an app which will be co-designed by the community and university researchers as part of the pilot project. In the following Stage 2 project, the app and identified solutions will be deployed and evaluated alongside the performance of a previously developed, low-cost, lead, screening kit through a pilot program. The techno-sociological framework will enable a greater understanding about if and how the voices of marginalized patients are being heard, understood, and acted upon. This project is in response to the Civic Innovation Challenge program—Track B. Bridging the gap between essential resources and services & community needs—and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
即使在对铅 (Pb) 暴露途径有充分了解的社区中,向受影响最严重的个人提供资源也存在很大障碍,因为面临铅中毒的家庭由种族组成,这些在获得医疗保健方面的差异导致了代际劣势。这项 CIVIC 研究是基于社区的研究和技术驱动框架的交叉点,旨在了解如何缩小家庭、医疗保健提供者和政策制定者之间的沟通差距。有潜力增加访问及时的医疗保健,并通过开发应用程序进行快速、积极的干预,将所有相关方联系在一起,以改善护理协调,防止儿童铅中毒。研究的最初目标社区是印第安纳州圣约瑟夫县。让所有相关利益相关者参与铅中毒诊断、干预和补救/减轻工作的更广泛影响,包括改善低收入社区儿童的健康状况和减少铅中毒,以及工程和化学本科生的参与和培训。学生将参与开发。教育材料,让家庭了解铅暴露的风险,尤其是儿童,目的是帮助社区成员识别和寻求铅评估/减排资源,以保护其亲人的健康,参与第一阶段的学生团队并遵循 -第二阶段计划如果获得资助,将获得体验式学习机会,并与社区合作,将社区挑战转化为问题陈述,并帮助实施可能的解决方案。研究成果和开发的技术和信息材料将扩展到美国其他地区。以及其他有高土和家园的地方尽管基于社区的参与性研究鼓励多学科案例审查小组评估干预措施的有效性,但目前对个人、社区、提供者和系统因素之间关系的理解尚未得到充分探索,这阻碍了降低风险所需的关键洞察力。在 CIVIC 第一阶段规划期间,将召集一个由社区成员、卫生服务提供者、研究人员和政策制定者组成的跨学科和多利益相关者小组,以了解目标社区和目标社区。每个小组在儿童铅检测闭环以及将家庭与提供减排干预措施的资源联系起来方面具有重叠的角色和责任。这些设计思维会议和讨论将为部署直接与受影响社区合作的社区卫生工作者提供框架。并以应用程序的形式提供信息和技术解决方案,该解决方案将由社区和大学研究人员共同设计,作为试点项目的一部分,在接下来的第二阶段项目中,将部署应用程序和确定的解决方案并与性能一起部署。先前开发的低成本、技术社会学框架将有助于更好地了解边缘化患者的声音是否以及如何被听到、理解和采取行动。该项目是对公民创新挑战计划的回应。 B 轨道。弥合基本资源和服务与社区需求之间的差距,是 NSF、国土安全部和能源部之间的合作。该奖项反映了 NSF 的法定使命,并通过评估被认为值得支持基金会的智力价值以及更广泛的影响审查标准。

项目成果

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Nitesh Chawla其他文献

Neural Tree Kernel Learning
神经树核学习
  • DOI:
  • 发表时间:
    2024-09-13
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Su;Martin Wistuba;Ambrish Rawat;Nitesh Chawla
  • 通讯作者:
    Nitesh Chawla
Fast Explainability via Feasible Concept Sets Generator
通过可行概念集生成器快速解释
Understanding imbalanced data: XAI & interpretable ML framework
了解不平衡数据:XAI
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Damien Dablain;Colin Bellinger;Bartosz Krawczyk;D. Aha;Nitesh Chawla
  • 通讯作者:
    Nitesh Chawla
GHC: G: Deep Reinforcement Learning for Heterogeneous Relational Reasoning in Knowledge Graphs
GHC:G:知识图中异构关系推理的深度强化学习
Modeling Considerations for Quantitative Social Science Research Using Social Media Data
使用社交媒体数据进行定量社会科学研究的建模注意事项
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ceren Budak;Stuart Soroka;Lisa Singh;Michael Bailey;Leticia Bode;Nitesh Chawla;P. Davis‐Kean;M. de Choudhury;Richard De Veaux;Ulrike Hahn;J. Jensen;J. Ladd;Zeina Mneimneh;Josh Pasek;T. Raghunathan;Rebecca Ryan;Noah A. Smith;Karen Stohr;Michael Traugott
  • 通讯作者:
    Michael Traugott

Nitesh Chawla的其他文献

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{{ truncateString('Nitesh Chawla', 18)}}的其他基金

HDR: DSC: Interdisciplinary Traineeship for Socially Responsible and Engaged Data Scientists
HDR:DSC:具有社会责任感和参与度的数据科学家的跨学科培训
  • 批准号:
    1924279
  • 财政年份:
    2019
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
HDR: DSC: Interdisciplinary Traineeship for Socially Responsible and Engaged Data Scientists
HDR:DSC:具有社会责任感和参与度的数据科学家的跨学科培训
  • 批准号:
    1924279
  • 财政年份:
    2019
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
Student Travel Support for the 2015 SIAM International Conference on Data Mining
2015 年 SIAM 国际数据挖掘会议的学生旅行支持
  • 批准号:
    1535285
  • 财政年份:
    2015
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
BIGDATA: F: DKM: Addressing the two V's of Veracity and Variety in Big Data
BIGDATA:F:DKM:解决大数据中的准确性和多样性这两个 V
  • 批准号:
    1447795
  • 财政年份:
    2014
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
CDI-TYPE II: Building and studying a virtual organization for adaptation to climate change
CDI-TYPE II:建立和研究适应气候变化的虚拟组织
  • 批准号:
    1029584
  • 财政年份:
    2010
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
Collaborative Research: AIS: Incremental Learning from Unbalanced Data in Nonstationary Environments
合作研究:AIS:非平稳环境中不平衡数据的增量学习
  • 批准号:
    0926170
  • 财政年份:
    2009
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
CSR-AES: Troubleshooting Large Scale Computing Grids with Machine Learning Techniques
CSR-AES:利用机器学习技术对大规模计算网格进行故障排除
  • 批准号:
    0720813
  • 财政年份:
    2007
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant

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  • 批准号:
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