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Structural analysis of health-relevant policy-making information exchange networks in Canada

Overview of attention for article published in Implementation Science, September 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

blogs
1 blog
twitter
13 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
76 Mendeley
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Title
Structural analysis of health-relevant policy-making information exchange networks in Canada
Published in
Implementation Science, September 2017
DOI 10.1186/s13012-017-0642-4
Pubmed ID
Authors

Damien Contandriopoulos, François Benoît, Denise Bryant-Lukosius, Annie Carrier, Nancy Carter, Raisa Deber, Arnaud Duhoux, Trisha Greenhalgh, Catherine Larouche, Bernard-Simon Leclerc, Adrian Levy, Ruth Martin-Misener, Katerina Maximova, Kimberlyn McGrail, Candace Nykiforuk, Noralou Roos, Robert Schwartz, Thomas W. Valente, Sabrina Wong, Evert Lindquist, Carolyn Pullen, Anne Lardeux, Melanie Perroux

Abstract

Health systems worldwide struggle to identify, adopt, and implement in a timely and system-wide manner the best-evidence-informed-policy-level practices. Yet, there is still only limited evidence about individual and institutional best practices for fostering the use of scientific evidence in policy-making processes The present project is the first national-level attempt to (1) map and structurally analyze-quantitatively-health-relevant policy-making networks that connect evidence production, synthesis, interpretation, and use; (2) qualitatively investigate the interaction patterns of a subsample of actors with high centrality metrics within these networks to develop an in-depth understanding of evidence circulation processes; and (3) combine these findings in order to assess a policy network's "absorptive capacity" regarding scientific evidence and integrate them into a conceptually sound and empirically grounded framework. The project is divided into two research components. The first component is based on quantitative analysis of ties (relationships) that link nodes (participants) in a network. Network data will be collected through a multi-step snowball sampling strategy. Data will be analyzed structurally using social network mapping and analysis methods. The second component is based on qualitative interviews with a subsample of the Web survey participants having central, bridging, or atypical positions in the network. Interviews will focus on the process through which evidence circulates and enters practice. Results from both components will then be integrated through an assessment of the network's and subnetwork's effectiveness in identifying, capturing, interpreting, sharing, reframing, and recodifying scientific evidence in policy-making processes. Knowledge developed from this project has the potential both to strengthen the scientific understanding of how policy-level knowledge transfer and exchange functions and to provide significantly improved advice on how to ensure evidence plays a more prominent role in public policies.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 17%
Researcher 9 12%
Student > Master 9 12%
Professor 5 7%
Student > Doctoral Student 4 5%
Other 17 22%
Unknown 19 25%
Readers by discipline Count As %
Social Sciences 17 22%
Medicine and Dentistry 10 13%
Business, Management and Accounting 6 8%
Nursing and Health Professions 4 5%
Engineering 2 3%
Other 12 16%
Unknown 25 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 February 2018.
All research outputs
#1,420,751
of 15,922,017 outputs
Outputs from Implementation Science
#405
of 1,505 outputs
Outputs of similar age
#37,557
of 278,134 outputs
Outputs of similar age from Implementation Science
#2
of 4 outputs
Altmetric has tracked 15,922,017 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,505 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 278,134 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.