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Reporting guidelines for health care simulation research: extensions to the CONSORT and STROBE statements

Overview of attention for article published in Advances in Simulation, July 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
104 tweeters
facebook
1 Facebook page

Citations

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28 Dimensions

Readers on

mendeley
137 Mendeley
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Title
Reporting guidelines for health care simulation research: extensions to the CONSORT and STROBE statements
Published in
Advances in Simulation, July 2016
DOI 10.1186/s41077-016-0025-y
Pubmed ID
Authors

Adam Cheng, David Kessler, Ralph Mackinnon, Todd P. Chang, Vinay M. Nadkarni, Elizabeth A. Hunt, Jordan Duval-Arnould, Yiqun Lin, David A. Cook, Martin Pusic, Joshua Hui, David Moher, Matthias Egger, Marc Auerbach, for the International Network for Simulation-based Pediatric Innovation, Research, and Education (INSPIRE) Reporting Guidelines Investigators

Abstract

Simulation-based research (SBR) is rapidly expanding but the quality of reporting needs improvement. For a reader to critically assess a study, the elements of the study need to be clearly reported. Our objective was to develop reporting guidelines for SBR by creating extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statements. An iterative multistep consensus-building process was used on the basis of the recommended steps for developing reporting guidelines. The consensus process involved the following: (1) developing a steering committee, (2) defining the scope of the reporting guidelines, (3) identifying a consensus panel, (4) generating a list of items for discussion via online premeeting survey, (5) conducting a consensus meeting, and (6) drafting reporting guidelines with an explanation and elaboration document. The following 11 extensions were recommended for CONSORT: item 1 (title/abstract), item 2 (background), item 5 (interventions), item 6 (outcomes), item 11 (blinding), item 12 (statistical methods), item 15 (baseline data), item 17 (outcomes/ estimation), item 20 (limitations), item 21 (generalizability), and item 25 (funding). The following 10 extensions were recommended for STROBE: item 1 (title/abstract), item 2 (background/rationale), item 7 (variables), item 8 (data sources/measurement), item 12 (statistical methods), item 14 (descriptive data), item 16 (main results), item 19 (limitations), item 21 (generalizability), and item 22 (funding). An elaboration document was created to provide examples and explanation for each extension. We have developed extensions for the CONSORT and STROBE Statements that can help improve the quality of reporting for SBR (Sim Healthcare00:00-00, 2016).

Twitter Demographics

The data shown below were collected from the profiles of 104 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 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
Spain 1 <1%
Ireland 1 <1%
United States 1 <1%
Netherlands 1 <1%
Sweden 1 <1%
Colombia 1 <1%
Unknown 130 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 18%
Researcher 24 18%
Student > Master 15 11%
Professor > Associate Professor 14 10%
Other 12 9%
Other 47 34%
Readers by discipline Count As %
Medicine and Dentistry 67 49%
Nursing and Health Professions 20 15%
Unspecified 15 11%
Social Sciences 10 7%
Agricultural and Biological Sciences 6 4%
Other 19 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 68. 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 18 September 2018.
All research outputs
#204,409
of 12,152,830 outputs
Outputs from Advances in Simulation
#3
of 78 outputs
Outputs of similar age
#9,192
of 266,154 outputs
Outputs of similar age from Advances in Simulation
#1
of 5 outputs
Altmetric has tracked 12,152,830 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 78 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.7. This one has done particularly well, scoring higher than 96% 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 266,154 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them