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Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies

Overview of attention for article published in BMC Medicine, November 2013
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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 (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
6 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
69 Mendeley
citeulike
1 CiteULike
Title
Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies
Published in
BMC Medicine, November 2013
DOI 10.1186/1741-7015-11-243
Pubmed ID
Authors

IC McManus, Chris Dewberry, Sandra Nicholson, Jonathan S Dowell, Katherine Woolf, Henry WW Potts

Abstract

Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 6%
Malaysia 1 1%
Unknown 64 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 23%
Other 9 13%
Student > Bachelor 8 12%
Student > Master 8 12%
Researcher 7 10%
Other 17 25%
Unknown 4 6%
Readers by discipline Count As %
Medicine and Dentistry 30 43%
Social Sciences 13 19%
Psychology 9 13%
Agricultural and Biological Sciences 3 4%
Computer Science 2 3%
Other 3 4%
Unknown 9 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 29 November 2018.
All research outputs
#628,214
of 13,945,598 outputs
Outputs from BMC Medicine
#517
of 2,191 outputs
Outputs of similar age
#9,705
of 183,893 outputs
Outputs of similar age from BMC Medicine
#77
of 261 outputs
Altmetric has tracked 13,945,598 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,191 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 34.3. This one has done well, scoring higher than 76% 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 183,893 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 94% of its contemporaries.
We're also able to compare this research output to 261 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 70% of its contemporaries.