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识别新兴的研究合作与网络:方法开发

Identifying emerging research collaborations and networks: method development.

作者信息

Dozier Ann M, Martina Camille A, O'Dell Nicole L, Fogg Thomas T, Lurie Stephen J, Rubinstein Eric P, Pearson Thomas A

机构信息

Public Health Sciences, University of Rochester, Rochester, NY, USA.

出版信息

Eval Health Prof. 2014 Mar;37(1):19-32. doi: 10.1177/0163278713501693. Epub 2013 Sep 8.

Abstract

Clinical and translational research is a multidisciplinary, collaborative team process. To evaluate this process, we developed a method to document emerging research networks and collaborations in our medical center to describe their productivity and viability over time. Using an e-mail survey, sent to 1,620 clinical and basic science full- and part-time faculty members, respondents identified their research collaborators. Initial analyses, using Pajek software, assessed the feasibility of using social network analysis (SNA) methods with these data. Nearly 400 respondents identified 1,594 collaborators across 28 medical center departments resulting in 309 networks with 5 or more collaborators. This low-burden approach yielded a rich data set useful for evaluation using SNA to: (a) assess networks at several levels of the organization, including intrapersonal (individuals), interpersonal (social), organizational/institutional leadership (tenure and promotion), and physical/environmental (spatial proximity) and (b) link with other data to assess the evolution of these networks.

摘要

临床与转化研究是一个多学科的协作团队过程。为了评估这一过程,我们开发了一种方法,用于记录我们医学中心新出现的研究网络和合作,以描述它们随时间推移的生产力和可行性。通过向1620名临床和基础科学领域的全职和兼职教员发送电子邮件调查,受访者确定了他们的研究合作者。最初使用Pajek软件进行的分析评估了对这些数据使用社会网络分析(SNA)方法的可行性。近400名受访者在28个医学中心部门中确定了1594名合作者,形成了309个拥有5名或更多合作者的网络。这种低负担的方法产生了一个丰富的数据集,可用于使用SNA进行评估,以:(a)在组织的几个层面评估网络,包括个人层面(个体)、人际层面(社交)、组织/机构领导层面(任期和晋升)以及物理/环境层面(空间接近度);(b)与其他数据相联系,以评估这些网络的演变。

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