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Infant EEG activity as a biomarker for autism: a promising approach or a false promise?

Overview of attention for article published in BMC Medicine, May 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)

Mentioned by

1 blog


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75 Mendeley
1 CiteULike
Infant EEG activity as a biomarker for autism: a promising approach or a false promise?
Published in
BMC Medicine, May 2011
DOI 10.1186/1741-7015-9-61
Pubmed ID

Richard Griffin, Chris Westbury


The ability to determine an infant's likelihood of developing autism via a relatively simple neurological measure would constitute an important scientific breakthrough. In their recent publication in this journal, Bosl and colleagues claim that a measure of EEG complexity can be used to detect, with very high accuracy, infants at high risk for autism (HRA). On the surface, this appears to be that very scientific breakthrough and as such the paper has received widespread media attention. But a close look at how these high accuracy rates were derived tells a very different story. This stems from a conflation between "high risk" as a population-level property and "high risk" as a property of an individual. We describe the approach of Bosl et al. and examine their results with respect to baseline prevalence rates, the inclusion of which is necessary to distinguish infants with a biological risk of autism from typically developing infants with a sibling with autism. This is an important distinction that should not be overlooked. Please see research article: http://www.biomedcentral.com/1741-7015/9/18 and correspondence article: http://www.biomedcentral.com/1741-7015/9/60.

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 1%
United Kingdom 1 1%
United States 1 1%
Poland 1 1%
Unknown 71 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 23%
Researcher 16 21%
Student > Master 11 15%
Professor 6 8%
Other 5 7%
Other 18 24%
Unknown 2 3%
Readers by discipline Count As %
Psychology 26 35%
Medicine and Dentistry 12 16%
Agricultural and Biological Sciences 8 11%
Neuroscience 6 8%
Engineering 4 5%
Other 12 16%
Unknown 7 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 10 September 2011.
All research outputs
of 12,517,134 outputs
Outputs from BMC Medicine
of 2,010 outputs
Outputs of similar age
of 147,394 outputs
Outputs of similar age from BMC Medicine
of 25 outputs
Altmetric has tracked 12,517,134 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,010 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 33.9. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
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 147,394 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 79% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.