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Systematic reviews need to consider applicability to disadvantaged populations: inter-rater agreement for a health equity plausibility algorithm

Overview of attention for article published in BMC Medical Research Methodology, December 2012
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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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

policy
1 policy source
twitter
25 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
54 Mendeley
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Title
Systematic reviews need to consider applicability to disadvantaged populations: inter-rater agreement for a health equity plausibility algorithm
Published in
BMC Medical Research Methodology, December 2012
DOI 10.1186/1471-2288-12-187
Pubmed ID
Authors

Vivian Welch, Kevin Brand, Elizabeth Kristjansson, Janet Smylie, George Wells, Peter Tugwell

Abstract

Systematic reviews have been challenged to consider effects on disadvantaged groups. A priori specification of subgroup analyses is recommended to increase the credibility of these analyses. This study aimed to develop and assess inter-rater agreement for an algorithm for systematic review authors to predict whether differences in effect measures are likely for disadvantaged populations relative to advantaged populations (only relative effect measures were addressed).

Twitter Demographics

The data shown below were collected from the profiles of 25 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 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Colombia 1 2%
Canada 1 2%
Unknown 50 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 20%
Student > Ph. D. Student 9 17%
Researcher 7 13%
Other 6 11%
Student > Postgraduate 5 9%
Other 10 19%
Unknown 6 11%
Readers by discipline Count As %
Medicine and Dentistry 22 41%
Social Sciences 6 11%
Psychology 4 7%
Nursing and Health Professions 3 6%
Business, Management and Accounting 2 4%
Other 5 9%
Unknown 12 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 01 January 2018.
All research outputs
#1,221,701
of 17,351,915 outputs
Outputs from BMC Medical Research Methodology
#180
of 1,610 outputs
Outputs of similar age
#16,530
of 265,013 outputs
Outputs of similar age from BMC Medical Research Methodology
#7
of 124 outputs
Altmetric has tracked 17,351,915 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,610 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has done well, scoring higher than 88% 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 265,013 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 93% of its contemporaries.
We're also able to compare this research output to 124 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.