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A six stage operational framework for individualising injury risk management in sport

Overview of attention for article published in Injury Epidemiology, September 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#23 of 197)
  • High Attention Score compared to outputs of the same age (94th percentile)

Mentioned by

70 tweeters
3 Facebook pages


18 Dimensions

Readers on

90 Mendeley
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A six stage operational framework for individualising injury risk management in sport
Published in
Injury Epidemiology, September 2017
DOI 10.1186/s40621-017-0123-x
Pubmed ID

Mark Roe, Shane Malone, Catherine Blake, Kieran Collins, Conor Gissane, Fionn Büttner, John C. Murphy, Eamonn Delahunt


Managing injury risk is important for maximising athlete availability and performance. Although athletes are inherently predisposed to musculoskeletal injuries by participating in sports, etiology models have illustrated how susceptibility is influenced by repeat interactions between the athlete (i.e. intrinsic factors) and environmental stimuli (i.e. extrinsic factors). Such models also reveal that the likelihood of an injury emerging across time is related to the interconnectedness of multiple factors cumulating in a pattern of either positive (i.e. increased fitness) or negative adaptation (i.e. injury).The process of repeatedly exposing athletes to workloads in order to promote positive adaptations whilst minimising injury risk can be difficult to manage. Etiology models have highlighted that preventing injuries in sport, as opposed to reducing injury risk, is likely impossible given our inability to appreciate the interactions of the factors at play. Given these uncertainties, practitioners need to be able to design, deliver, and monitor risk management strategies that ensure a low susceptibility to injury is maintained during pursuits to enhance performance. The current article discusses previous etiology and injury prevention models before proposing a new operational framework.

Twitter Demographics

The data shown below were collected from the profiles of 70 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 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 90 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 18%
Student > Bachelor 15 17%
Student > Master 10 11%
Other 9 10%
Researcher 8 9%
Other 18 20%
Unknown 14 16%
Readers by discipline Count As %
Sports and Recreations 40 44%
Medicine and Dentistry 11 12%
Nursing and Health Professions 10 11%
Social Sciences 3 3%
Psychology 2 2%
Other 6 7%
Unknown 18 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 46. 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 28 March 2019.
All research outputs
of 15,962,710 outputs
Outputs from Injury Epidemiology
of 197 outputs
Outputs of similar age
of 278,132 outputs
Outputs of similar age from Injury Epidemiology
of 1 outputs
Altmetric has tracked 15,962,710 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 197 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.2. This one has done well, scoring higher than 87% 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 278,132 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 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