Excellence in Research: Scaling Social Capital and Health across Space

本研究探讨集体行动与集体效能对健康素养的影响。 这项工作是为当地和偏远地区的群体开展的，其中包括当地人和已搬迁到该地区的人。 收集数据的方式有两种，一种是通过调查进行统计分析，另一种是通过访谈。 其目标是为未来的学者，研究人员和从业人员提供新的理论见解，这些学者，研究人员和从业人员致力于健康和人口流动的社会决定因素及其在地方和全球层面的交叉点。 该项目还将为代表性不足的学生提供实地考察的机会，使他们获得实践研究经验。 本研究采用序贯混合方法探讨集体效能与健康素养的关系，为集体效能与健康素养的研究提供理论和实证依据，并为公共卫生从业者和决策者提供参考。 利用社区参与的方法，与社区成员建立伙伴关系，收集数据，使用，调查，重点小组，并为当地和搬迁群体的访谈。具体而言，集体效能的主要组成部分-社会凝聚力，非正式的社会控制，社会参与-以及它们与健康素养的关系在这两个群体的情况下进行测量。 根据混合方法检验估计样本量。 数据分析使用分层统计方法和定性编码方法（如适用）。 该项目由社会学计划、HBCU-EIR计划和建设与发展计划共同支持。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

In this project, the effects of collective action and collective efficacy on health literacy are investigated. This is undertaken for local and remote groups, including those native to their area and those who have relocated into the region. Data are collected in two ways, through surveys, which are analyzed statistically, and through interviews. The goal is to produce new theoretical insights for future scholars, researchers, and practitioners working on social determinants of health and population movements and their intersections at the local and global levels. The project will also provide under-represented students with hands-on research experience by providing them with the opportunity to undertake fieldwork. Findings from this study contribute both theoretically and empirically to the study of collective efficacy and health literacy and are relevant to public health practitioners and decision makers.In this study, sequential mixed methods are used to understand the relationship between collective efficacy and health literacy. Drawing on a community-engaged approach for partnership building with community members, data are collected using, surveys, focus groups, and interviews for both local and relocated groups. Specifically, the main components of collective efficacy – social cohesion, informal social control, and social participation – and their relationship with health literacy are measured in both groups’ contexts. A sample size is estimated based on Mixed Methods Test. Data analyses use hierarchical statistical methods and qualitative coding methods as appropriate. This project is supported jointly by the Sociology Program, the HBCU-EIR Program, and the Build and Broaden Program.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.