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Applying GRADE-CERQual to qualitative evidence synthesis findings—paper 2: how to make an overall CERQual assessment of confidence and create a Summary of Qualitative Findings table

Overview of attention for article published in Implementation Science, January 2018
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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)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

news
1 news outlet
policy
1 policy source
twitter
2 tweeters

Citations

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76 Dimensions

Readers on

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168 Mendeley
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Title
Applying GRADE-CERQual to qualitative evidence synthesis findings—paper 2: how to make an overall CERQual assessment of confidence and create a Summary of Qualitative Findings table
Published in
Implementation Science, January 2018
DOI 10.1186/s13012-017-0689-2
Pubmed ID
Authors

Simon Lewin, Meghan Bohren, Arash Rashidian, Heather Munthe-Kaas, Claire Glenton, Christopher J. Colvin, Ruth Garside, Jane Noyes, Andrew Booth, Özge Tunçalp, Megan Wainwright, Signe Flottorp, Joseph D. Tucker, Benedicte Carlsen

Abstract

The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on making an overall assessment of confidence in a review finding and creating a CERQual Evidence Profile and a CERQual Summary of Qualitative Findings table. We developed this guidance by examining the methods used by other GRADE approaches, gathering feedback from relevant research communities and developing consensus through project group meetings. We then piloted the guidance on several qualitative evidence syntheses before agreeing on the approach. Confidence in the evidence is an assessment of the extent to which a review finding is a reasonable representation of the phenomenon of interest. Creating a summary of each review finding and deciding whether or not CERQual should be used are important steps prior to assessing confidence. Confidence should be assessed for each review finding individually, based on the judgements made for each of the four CERQual components. Four levels are used to describe the overall assessment of confidence: high, moderate, low or very low. The overall CERQual assessment for each review finding should be explained in a CERQual Evidence Profile and Summary of Qualitative Findings table. Structuring and summarising review findings, assessing confidence in those findings using CERQual and creating a CERQual Evidence Profile and Summary of Qualitative Findings table should be essential components of undertaking qualitative evidence syntheses. This paper describes the end point of a CERQual assessment and should be read in conjunction with the other papers in the series that provide information on assessing individual CERQual components.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 168 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 168 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 23%
Student > Ph. D. Student 31 18%
Student > Master 27 16%
Student > Doctoral Student 10 6%
Other 8 5%
Other 37 22%
Unknown 16 10%
Readers by discipline Count As %
Medicine and Dentistry 45 27%
Social Sciences 34 20%
Nursing and Health Professions 26 15%
Psychology 11 7%
Engineering 5 3%
Other 19 11%
Unknown 28 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 26 January 2018.
All research outputs
#1,356,706
of 14,555,805 outputs
Outputs from Implementation Science
#415
of 1,435 outputs
Outputs of similar age
#48,814
of 359,047 outputs
Outputs of similar age from Implementation Science
#6
of 15 outputs
Altmetric has tracked 14,555,805 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,435 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 71% 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 359,047 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 15 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.