Breaking Down Silos: Mapping Growth of Cross‐Disciplinary Collaboration in a Translational Science Initiative. Issue 2 (4th December 2014)

• Record Type: Journal Article
• Authors: Luke, Douglas A.; Carothers, Bobbi J.; Dhand, Amar; Bell, Ryan A.; Moreland‐Russell, Sarah; Sarli, Cathy C.; Evanoff, Bradley A.
• Is Part Of: Clinical and translational science. Volume 8:Issue 2(2015)
• Page Start: 143
• Page End: 149
• Publication Date: 2014-12-04
• Subjects: network analysis -- scientific collaboration -- interdisciplinary science -- science of team science -- bibliometrics; Medicine, Experimental -- Periodicals; Medical innovations -- Periodicals; 616.027
• DOI: 10.1111/cts.12248
• Languages: English
• ISSNs: 1752-8054

Abstract

Abstract: The importance of transdisciplinary collaboration is growing, though not much is known about how to measure collaboration patterns. The purpose of this paper is to present multiple ways of mapping and evaluating the growth of cross‐disciplinary partnerships over time. Social network analysis was used to examine the impact of a Clinical and Translational Science Award (CTSA) on collaboration patterns. Grant submissions from 2007 through 2010 and publications from 2007 through 2011 of Institute of Clinical and Translational Sciences (ICTS) members were examined. A Cohort Model examining the first‐year ICTS members demonstrated an overall increase in collaborations on grants and publications, as well as an increase in cross‐discipline collaboration as compared to within‐discipline. A Growth Model that included additional members over time demonstrated the same pattern for grant submissions, but a decrease in cross‐discipline collaboration as compared to within‐discipline collaboration for publications. ICTS members generally became more cross‐disciplinary in their collaborations during the CTSA. The exception of publications for the Growth Model may be due to the time lag between funding and publication, as well as pressure for younger scientists to publish in their own fields. Network analysis serves as a valuable tool for evaluating changes in scientific collaboration.