Evidence map›Paper›PMID 25442221›Full record

ArticleClinical and translational science2015

Social network analysis to assess the impact of the CTSA on biomedical research grant collaboration.

Radhakrishnan Nagarajan, Charlotte A Peterson, Jane S Lowe, Stephen W Wyatt, Timothy S Tracy, Philip A Kern

Abstract read
In one paragraph

Article in Clinical and translational science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Article
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  11. Approaches to Measuring Trends in Interdisciplinary Research Publications at One Academic Medical Center.Academic medicine : journal of the Association of American Medical Colleges · 2020
    Article
  12. Article
  13. Network Abstractions of Prescription Patterns in a Medicaid Population.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019
    Article
  14. Article
  15. Network-based assessment of collaborative research in neuroscience.Alzheimer's & dementia (New York, N. Y.) · 2018
    Article
  16. Toward a science of translational science.Journal of clinical and translational science · 2017
    Article
  17. Article
  18. Scientific retreats with 'speed dating': networking to stimulate new interdisciplinary translational research collaborations and team science.Journal of investigative medicine : the official publication of the American Federation for Clinical Research · 2017
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Radhakrishnan NagarajanDivision of Biomedical Informatics, College of Public Health, University of Kentucky, Lexington, Kentucky, USA; Center for Clinical and Translational Sciences, University of Kentucky, Lexington, Kentucky, USA.
Charlotte A Peterson
Jane S Lowe
Stephen W Wyatt
Timothy S Tracy
Philip A Kern

Funding

Kentucky Center for Clinical and Translational ScienceUL1TR000117 · NCATS · UNIVERSITY OF KENTUCKY · PI KERN, PHILIP A · 2012 to 2015
$13.3M
KENTUCKY CENTER FOR CLINICAL AND TRANSLATIONAL SCIENCEUL1RR033173 · NCRR · UNIVERSITY OF KENTUCKY · PI KERN, PHILIP A · 2011 to 2011
$3.5M
NCATS NIH HHS 1UL1TR000117NCATS NIH HHS UL1 TR000117NCRR NIH HHS UL1 RR033173
6 · The paper itself

Abstract

Success of the Clinical Translational Science Award (CTSA) program implicitly demands team science efforts and well-orchestrated collaboration across the translational silos (T1-T4). Networks have proven to be useful abstractions of research collaborations. Networks provide novel system-level insights and exhibit marked changes in response to external interventions, making them potential evaluation tools that complement more traditional approaches. This study is part of our ongoing efforts to assess the impact of the CTSA on Biomedical Research Grant Collaboration (BRGC). Collaborative research grants are a complex undertaking and an outcome of sustained interaction among researchers. In this report, BRGC networks representing collaborations among CTSA-affiliated investigators constructed from grants management system data at the University of Kentucky across a period of six years (2007-2012) corresponding to pre- and post-CTSA are investigated. Overlapping community structure detection algorithms, in conjunction with surrogate testing, revealed the presence of intricate research communities rejecting random graphs as generative mechanisms. The deviation from randomness was especially pronounced post-CTSA, reflecting an increasing trend in collaborations and team-science efforts potentially as a result of CTSA. Intercommunity cross talk was especially pronounced post-CTSA.

Indexed as

Social NetworkingAlgorithmsBiomedical ResearchFinancing, OrganizedHealthcare DisparitiesInterdisciplinary CommunicationKentuckyResearch PersonnelResearch Support as TopicSocial SupportTranslational Research, BiomedicalUniversitiesCTSAgrant collaborationrandom graphssocial networksteam science

Identifiers

PMID25442221
PMCPMC4571459

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.