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Language, Reading, and Math Learning Profiles in an Epidemiological Sample of School Age Children

Overview of attention for article published in PLoS ONE, October 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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
3 news outlets
twitter
304 tweeters
facebook
2 Facebook pages

Readers on

mendeley
112 Mendeley
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Title
Language, Reading, and Math Learning Profiles in an Epidemiological Sample of School Age Children
Published in
PLoS ONE, October 2013
DOI 10.1371/journal.pone.0077463
Pubmed ID
Authors

Lisa M. D. Archibald, Janis Oram Cardy, Marc F. Joanisse, Daniel Ansari

Abstract

Dyscalculia, dyslexia, and specific language impairment (SLI) are relatively specific developmental learning disabilities in math, reading, and oral language, respectively, that occur in the context of average intellectual capacity and adequate environmental opportunities. Past research has been dominated by studies focused on single impairments despite the widespread recognition that overlapping and comorbid deficits are common. The present study took an epidemiological approach to study the learning profiles of a large school age sample in language, reading, and math. Both general learning profiles reflecting good or poor performance across measures and specific learning profiles involving either weak language, weak reading, weak math, or weak math and reading were observed. These latter four profiles characterized 70% of children with some evidence of a learning disability. Low scores in phonological short-term memory characterized clusters with a language-based weakness whereas low or variable phonological awareness was associated with the reading (but not language-based) weaknesses. The low math only group did not show these phonological deficits. These findings may suggest different etiologies for language-based deficits in language, reading, and math, reading-related impairments in reading and math, and isolated math disabilities.

Twitter Demographics

The data shown below were collected from the profiles of 304 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 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Canada 3 3%
Algeria 1 <1%
Malaysia 1 <1%
United Kingdom 1 <1%
Japan 1 <1%
PR 1 <1%
Unknown 101 90%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 23%
Student > Ph. D. Student 21 19%
Researcher 19 17%
Professor > Associate Professor 10 9%
Student > Postgraduate 8 7%
Other 28 25%
Readers by discipline Count As %
Psychology 51 46%
Social Sciences 18 16%
Neuroscience 8 7%
Linguistics 7 6%
Medicine and Dentistry 7 6%
Other 21 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 236. 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 22 March 2017.
All research outputs
#30,752
of 8,656,857 outputs
Outputs from PLoS ONE
#799
of 118,467 outputs
Outputs of similar age
#485
of 144,193 outputs
Outputs of similar age from PLoS ONE
#30
of 3,974 outputs
Altmetric has tracked 8,656,857 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 118,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one has done particularly well, scoring higher than 99% 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 144,193 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 99% of its contemporaries.
We're also able to compare this research output to 3,974 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 99% of its contemporaries.