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Networks of Collaboration among Scientists in a Center for Diabetes Translation Research.

Harris JK, Wong R, Thompson K, Haire-Joshu D, Hipp JA - PLoS ONE (2015)

Bottom Line: Network members in the same discipline were over twice as likely to collaborate in the overall network (OR: 2.10; 95% CI: 1.40-3.15); however, discipline was not associated with collaboration in the other networks.Rank was not associated with collaboration in any network.As transdisciplinary centers become more common, it is important to identify structural features, such as a central leader and ongoing collaboration over time, associated with scholarly productivity and, ultimately, with advancing science and practice.

View Article: PubMed Central - PubMed

Affiliation: Brown School, Washington University in St. Louis, One Brookings Dr., St. Louis, Missouri, United States of America; Center for Public Health Systems Science, Washington University in St. Louis, One Brookings Dr., St. Louis, Missouri, United States of America; Center for Diabetes Translation Research, Washington University in St. Louis, One Brookings Dr., St. Louis, Missouri, United States of America.

ABSTRACT

Background: Transdisciplinary collaboration is essential in addressing the translation gap between scientific discovery and delivery of evidence-based interventions to prevent and treat diabetes. We examined patterns of collaboration among scientists at the Washington University Center for Diabetes Translation Research.

Methods: Members (n = 56) of the Washington University Center for Diabetes Translation Research were surveyed about collaboration overall and on publications, presentations, and grants; 87.5% responded (n = 49). We used traditional and network descriptive statistics and visualization to examine the networks and exponential random graph modeling to identify predictors of collaboration.

Results: The 56 network members represented nine disciplines. On average, network members had been affiliated with the center for 3.86 years (s.d. = 1.41). The director was by far the most central in all networks. The overall and publication networks were the densest, while the overall and grant networks were the most centralized. The grant network was the most transdisciplinary. The presentation network was the least dense, least centralized, and least transdisciplinary. For every year of center affiliation, network members were 10% more likely to collaborate (OR: 1.10; 95% CI: 1.00-1.21) and 13% more likely to write a paper together (OR: 1.13; 95% CI: 1.02-1.25). Network members in the same discipline were over twice as likely to collaborate in the overall network (OR: 2.10; 95% CI: 1.40-3.15); however, discipline was not associated with collaboration in the other networks. Rank was not associated with collaboration in any network.

Conclusions: As transdisciplinary centers become more common, it is important to identify structural features, such as a central leader and ongoing collaboration over time, associated with scholarly productivity and, ultimately, with advancing science and practice.

No MeSH data available.


Related in: MedlinePlus

Collaborative ties among all full and provisional members of the WU-CDTR.Node size represents the number of collaborators each network member has in the network (larger nodes indicate more collaborators) and node color represents discipline.
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pone.0136457.g001: Collaborative ties among all full and provisional members of the WU-CDTR.Node size represents the number of collaborators each network member has in the network (larger nodes indicate more collaborators) and node color represents discipline.

Mentions: The overall collaboration network included 209 ties among the 56 network members for a network density of .13, or 13% of possible ties (Table 2). On average, WU-CDTR members collaborated with 7.2 other WU-CDTR network members on diabetes-related projects in the past year, consistent with other work examining collaboration on translational research [2], every WU-CDTR member had at least one collaborator in the network. The most connected person in the network, the WU-CDTR director, had collaborative ties with 41 WU-CDTR members (Fig 1A).


Networks of Collaboration among Scientists in a Center for Diabetes Translation Research.

Harris JK, Wong R, Thompson K, Haire-Joshu D, Hipp JA - PLoS ONE (2015)

Collaborative ties among all full and provisional members of the WU-CDTR.Node size represents the number of collaborators each network member has in the network (larger nodes indicate more collaborators) and node color represents discipline.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4547723&req=5

pone.0136457.g001: Collaborative ties among all full and provisional members of the WU-CDTR.Node size represents the number of collaborators each network member has in the network (larger nodes indicate more collaborators) and node color represents discipline.
Mentions: The overall collaboration network included 209 ties among the 56 network members for a network density of .13, or 13% of possible ties (Table 2). On average, WU-CDTR members collaborated with 7.2 other WU-CDTR network members on diabetes-related projects in the past year, consistent with other work examining collaboration on translational research [2], every WU-CDTR member had at least one collaborator in the network. The most connected person in the network, the WU-CDTR director, had collaborative ties with 41 WU-CDTR members (Fig 1A).

Bottom Line: Network members in the same discipline were over twice as likely to collaborate in the overall network (OR: 2.10; 95% CI: 1.40-3.15); however, discipline was not associated with collaboration in the other networks.Rank was not associated with collaboration in any network.As transdisciplinary centers become more common, it is important to identify structural features, such as a central leader and ongoing collaboration over time, associated with scholarly productivity and, ultimately, with advancing science and practice.

View Article: PubMed Central - PubMed

Affiliation: Brown School, Washington University in St. Louis, One Brookings Dr., St. Louis, Missouri, United States of America; Center for Public Health Systems Science, Washington University in St. Louis, One Brookings Dr., St. Louis, Missouri, United States of America; Center for Diabetes Translation Research, Washington University in St. Louis, One Brookings Dr., St. Louis, Missouri, United States of America.

ABSTRACT

Background: Transdisciplinary collaboration is essential in addressing the translation gap between scientific discovery and delivery of evidence-based interventions to prevent and treat diabetes. We examined patterns of collaboration among scientists at the Washington University Center for Diabetes Translation Research.

Methods: Members (n = 56) of the Washington University Center for Diabetes Translation Research were surveyed about collaboration overall and on publications, presentations, and grants; 87.5% responded (n = 49). We used traditional and network descriptive statistics and visualization to examine the networks and exponential random graph modeling to identify predictors of collaboration.

Results: The 56 network members represented nine disciplines. On average, network members had been affiliated with the center for 3.86 years (s.d. = 1.41). The director was by far the most central in all networks. The overall and publication networks were the densest, while the overall and grant networks were the most centralized. The grant network was the most transdisciplinary. The presentation network was the least dense, least centralized, and least transdisciplinary. For every year of center affiliation, network members were 10% more likely to collaborate (OR: 1.10; 95% CI: 1.00-1.21) and 13% more likely to write a paper together (OR: 1.13; 95% CI: 1.02-1.25). Network members in the same discipline were over twice as likely to collaborate in the overall network (OR: 2.10; 95% CI: 1.40-3.15); however, discipline was not associated with collaboration in the other networks. Rank was not associated with collaboration in any network.

Conclusions: As transdisciplinary centers become more common, it is important to identify structural features, such as a central leader and ongoing collaboration over time, associated with scholarly productivity and, ultimately, with advancing science and practice.

No MeSH data available.


Related in: MedlinePlus