ArticleBMC health services research2013
Who are the key players in a new translational research network?
Article in BMC health services research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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.
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.
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Who cites it
17 citing papers in PubMed, 45 citations in OpenAlex.
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProfessional networks are used increasingly in health care to bring together members from different sites and professions to work collaboratively. Key players within these networks are known to affect network function through their central or brokerage position and are therefore of interest to those who seek to optimise network efficiency. However, their identity may not be apparent. This study using social network analysis to ask: (1) Who are the key players of a new translational research network (TRN)? (2) Do they have characteristics in common? (3) Are they recognisable as powerful, influential or well connected individuals?
methodsTRN members were asked to complete an on-line, whole network survey which collected demographic information expected to be associated with key player roles, and social network questions about collaboration in current TRN projects. Three questions asked who they perceived as powerful, influential and well connected. Indegree and betweenness centrality values were used to determine key player status in the actual and perceived networks and tested for association with demographic and descriptive variables using chi square analyses.
resultsResponse rate for the online survey was 76.4% (52/68). The TRN director and manager were identified as key players along with six other members. Only two of nine variables were associated with actual key player status; none with perceived. The main finding was the mismatch between actual and perceived brokers. Members correctly identified two of the three central actors (the two mandated key roles director and manager) but there were only three correctly identified actual brokers among the 19 perceived brokers. Possible reasons for the mismatch include overlapping structures and weak knowledge of members.
conclusionsThe importance of correctly identifying these key players is discussed in terms of network interventions to improve efficiency.
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What OpenQuestion holds
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.