Suppr超能文献

利用出勤数据对社区参与式研究伙伴关系进行社会网络分析。

Using attendance data for social network analysis of a community-engaged research partnership.

作者信息

Vasquez Kimberly S, Chatterjee Shirshendu, Khalida Chamanara, Moftah Dena, D'Orazio Brianna, Leinberger-Jabari Andrea, Tobin Jonathan N, Kost Rhonda G

机构信息

Community and Collaboration Core, The Rockefeller University, Center for Clinical and Translational Science, New York, NY, USA.

Department of Mathematics, City University of New York, City College & Graduate Center, New York, NY, USA.

出版信息

J Clin Transl Sci. 2020 Dec 21;5(1):e75. doi: 10.1017/cts.2020.571.

Abstract

BACKGROUND

The Rockefeller University Center for Clinical and Translational Science (RU-CCTS) and Clinical Directors Network (CDN), a Practice-Based Research Network (PBRN), fostered a community-academic research partnership involving Community Health Center (CHCs) clinicians, laboratory scientists, clinical researchers, community, and patient partners. From 2011 to 2018, the partnership designed and completed Community-Associated Methicillin-Resistant Project (CAMP1), an observational study funded by the National Center for Advancing Translational Sciences (NCATS), and CAMP2, a Comparative Effectiveness Research Study funded by the Patient-Centered Outcomes Research Institute (PCORI). We conducted a social network analysis (SNA) to characterize this Community-Engaged Research (CEnR) partnership.

METHODS

Projects incorporated principles of Community-Based Participatory Research (CAMP1/2) and PCORI engagement rubrics (CAMP2). Meetings were designed to be highly interactive, facilitate co-learning, share governance, and incentivize ongoing engagement. Meeting attendance formed the raw dataset enriched by stakeholder roles and affiliations. We used SNA software (Gephi) to form networks for four project periods, characterize network attributes (density, degree, centrality, vulnerability), and create sociograms. Polynomial regression models were used to study stakeholder interactions.

RESULTS

Forty-seven progress meetings engaged 141 stakeholders, fulfilling 7 roles, and affiliated with 28 organizations (6 types). Network size, density, and interactions across organizations increased over time. Interactions between Community Members or Recruiters/Community Health Workers and almost every other role increased significantly across CAMP2 ( < 0.005); Community Members' centrality to the network increased over time.

CONCLUSIONS

In a partnership with a highly interactive meeting model, SNA using operational attendance data afforded a view of stakeholder interactions that realized the engagement goals of the partnership.

摘要

背景

洛克菲勒大学临床与转化科学中心(RU-CCTS)以及临床主任网络(CDN),一个基于实践的研究网络(PBRN),促成了一项社区-学术研究合作,该合作涉及社区卫生中心(CHCs)的临床医生、实验室科学家、临床研究人员、社区以及患者合作伙伴。从2011年到2018年,该合作设计并完成了社区相关耐甲氧西林金黄色葡萄球菌项目(CAMP1),这是一项由美国国立转化医学推进中心(NCATS)资助的观察性研究,以及CAMP2,一项由患者为中心的结果研究协会(PCORI)资助的比较效果研究。我们进行了一项社会网络分析(SNA)以描述这种社区参与研究(CEnR)合作。

方法

项目纳入了基于社区的参与性研究原则(CAMP1/2)和PCORI参与准则(CAMP2)。会议设计为高度互动式,促进共同学习、共享治理并激励持续参与。会议出席情况构成了由利益相关者角色和所属机构丰富后的原始数据集。我们使用SNA软件(Gephi)为四个项目阶段构建网络,描述网络属性(密度、度、中心性、脆弱性)并创建社会关系图。使用多项式回归模型研究利益相关者的互动。

结果

47次进展会议有141名利益相关者参与,履行7种角色,并隶属于28个组织(6种类型)。网络规模、密度以及各组织间的互动随时间增加。在CAMP2期间,社区成员或招募者/社区卫生工作者与几乎所有其他角色之间的互动显著增加(<0.005);社区成员在网络中的中心性随时间增加。

结论

在一个采用高度互动会议模式的合作中,使用实际出席数据的SNA提供了对利益相关者互动的一种观察视角,实现了合作的参与目标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c381/8057467/78746ebf376a/S2059866120005713_fig1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验