ArticleBMC health services research2014
Patterns of collaboration in complex networks: the example of a translational research network.
Article in BMC health services research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
35 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- A systematic review of the emerging definition of 'deprescribing' with network analysis: implications for future research and clinical practice.British journal of clinical pharmacology · 2015Pooled it
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- A large National Institute for Health Research (NIHR) Biomedical Research Centre facilitates impactful cross-disciplinary and collaborative translational research publications and research collaboration networks: a bibliometric evaluation study.Journal of translational medicine · 2021Article
- Collaborative relationships in translational medical research among Chinese clinicians: an internet-based cross-sectional survey.Journal of translational medicine · 2021Article
- Organizational supports for knowledge translation in paediatric health centres and research institutes: insights from a Canadian environmental scan.Implementation science communications · 2021Article
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis paper examines collaboration in a complex translational cancer research network (TRN) made up of a range of hospital-based clinicians and university-based researchers. We examine the phenomenon of close-knit and often introspective clusters of people (silos) and test the extent that factors associated with this clustering (geography, profession and past experience) influence patterns of current and future collaboration on TRN projects. Understanding more of these patterns, especially the gaps or barriers between members, will help network leaders to manage subgroups and promote connectivity crucial to efficient network function.
methodsAn on-line, whole network survey was used to collect attribute and relationship data from all members of the new TRN based in New South Wales, Australia in early 2012. The 68 members were drawn from six separate hospital and university campuses. Social network analysis with UCInet tested the effects of geographic proximity, profession, past research experience, strength of ties and previous collaborations on past, present and future intended partnering.
resultsGeographic proximity and past working relationships both had significant effects on the choice of current collaboration partners. Future intended collaborations included a significant number of weak ties and ties based on other members' reputations implying that the TRN has provided new opportunities for partnership. Professional grouping, a significant barrier discussed in the translational research literature, influenced past collaborations but not current or future collaborations, possibly through the mediation of network brokers.
conclusionsSince geographic proximity is important in the choice of collaborators a dispersed network such as this could consider enhancing cross site interactions by improving virtual communication technology and use, increasing social interactions apart from project related work, and maximising opportunities to meet members from other sites. Key network players have an important brokerage role facilitating linkages between groups.
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Registered trials
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.