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Common data elements collected among universities for sport-related concussion studies

Overview of attention for article published in Injury Epidemiology, February 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#48 of 127)
  • High Attention Score compared to outputs of the same age (81st percentile)

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1 blog
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2 tweeters

Citations

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3 Dimensions

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45 Mendeley
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Title
Common data elements collected among universities for sport-related concussion studies
Published in
Injury Epidemiology, February 2018
DOI 10.1186/s40621-018-0132-4
Pubmed ID
Authors

Jingzhen Yang, Corinne Peek-Asa, James M. Noble, James Torner, Paul Schmidt, Martha L. Cooper

Abstract

Universities are increasingly implementing programs to effectively respond to and manage sport-related concussions (SRCs). One such effort is to develop common data elements (CDEs) and standardize data collection methods. The objectives of this study were to describe CDEs currently collected by Big Ten and Ivy League universities for SRC studies, and to compare the data collected with the core CDEs recommended by the National Institute of Neurological Disorders and Stroke (NINDS). We conducted an anonymous cross-sectional online survey among medical staff at the 14 Big Ten and 8 Ivy League universities (one per university) between September and October 2015. The survey instrument, including 9 questions corresponding to the concussion data collected before, during, and after a concussion, was developed and pilot-tested before field use. We analyzed patterns of the concussion CDEs being collected, including when, what, and how the data were collected and stored, and compared them with the NINDS' recommended core CDEs. A total of 19 out of 22 universities were included, with 13 from Big Ten and 6 from Ivy-League universities. All 19 participating universities currently collected concussion data with athletes before, during, and after a concussion. Great similarities in data collection were observed at baseline and acutely post-concussion across participating universities. All 19 universities collected at least one of the ten recommended acute symptoms checklists, and 18 universities collected one of the four recommended core neuropsychological function cognitive measures. However, CDEs in the sub-acute and chronic timeframes were limited, with only 9 (47%) universities collecting post-concussion short to long term outcome data. While over 60% of universities collected and stored concussion data electronically, only 17% to 42% of data collected were readily available for research. Significant inter-institutional similarities in acute concussion CDEs were found. Further efforts should focus on collecting sub-acute and chronic timeframe core CDEs and creating data access protocols to facilitate evidence-based concussion prevention and treatment for all collegiate athletes.

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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 24%
Student > Ph. D. Student 7 16%
Student > Master 6 13%
Student > Doctoral Student 3 7%
Other 2 4%
Other 4 9%
Unknown 12 27%
Readers by discipline Count As %
Medicine and Dentistry 13 29%
Psychology 6 13%
Nursing and Health Professions 3 7%
Computer Science 2 4%
Neuroscience 2 4%
Other 6 13%
Unknown 13 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 18 February 2018.
All research outputs
#1,684,908
of 12,526,930 outputs
Outputs from Injury Epidemiology
#48
of 127 outputs
Outputs of similar age
#65,349
of 346,433 outputs
Outputs of similar age from Injury Epidemiology
#1
of 1 outputs
Altmetric has tracked 12,526,930 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.1. This one has gotten more attention than average, scoring higher than 60% 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 346,433 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 81% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them