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Sport-Specific Assessment of the Effectiveness of Neuromuscular Training in Young Athletes

Overview of attention for article published in Frontiers in Physiology, April 2018
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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9 X users

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Title
Sport-Specific Assessment of the Effectiveness of Neuromuscular Training in Young Athletes
Published in
Frontiers in Physiology, April 2018
DOI 10.3389/fphys.2018.00264
Pubmed ID
Authors

Erika Zemková, Dušan Hamar

Abstract

Neuromuscular training in young athletes improves performance and decreases the risk of injuries during sports activities. These effects are primarily ascribed to the enhancement of muscle strength and power but also balance, speed and agility. However, most studies have failed to demonstrate significant improvement in these abilities. This is probably due to the fact that traditional tests do not reflect training methods (e.g., plyometric training vs. isometric or isokinetic strength testing, dynamic balance training vs. static balance testing). The protocols utilized in laboratories only partially fulfill the current needs for testing under sport-specific conditions. Moreover, laboratory testing usually requires skilled staff and a well equipped and costly infrastructure. Nevertheless, experience demonstrates that high-technology and expensive testing is not the only way to proceed. A number of physical fitness field tests are available today. However, the low reliability and limited number of parameters retrieved from simple equipment used also limit their application in competitive sports. Thus, there is a need to develop and validate a functional assessment platform based on portable computerized systems. Variables obtained should be directly linked to specific features of particular sports and capture their complexity. This is essential for revealing weak and strong components of athlete performance and design of individually-tailored exercise programs. Therefore, identifying the drawbacks associated with the assessment of athlete performance under sport-specific conditions would provide a basis for the formation of an innovative approach to their long-term systematic testing. This study aims (i) to review the testing methods used for the evaluation of the effect of neuromuscular training on sport-specific performance in young athletes, (ii) to introduce stages within the Sport Longlife Diagnostic Model, and (iii) to propose future research in this topic. Analysis of the literature identified gaps in the current standard testing methods in terms of their low sensitivity in discriminating between athletes of varied ages and performance levels, insufficent tailoring to athlete performance level and individual needs, a lack of specificity to the requirements of particular sports and also in revealing the effect of training. In order to partly fill in these gaps, the Sport Longlife Diagnostic Model was proposed.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 279 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 279 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 42 15%
Student > Bachelor 31 11%
Student > Ph. D. Student 25 9%
Student > Doctoral Student 15 5%
Student > Postgraduate 14 5%
Other 54 19%
Unknown 98 35%
Readers by discipline Count As %
Sports and Recreations 88 32%
Nursing and Health Professions 24 9%
Medicine and Dentistry 17 6%
Unspecified 7 3%
Agricultural and Biological Sciences 6 2%
Other 22 8%
Unknown 115 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 24 December 2018.
All research outputs
#6,173,306
of 23,026,672 outputs
Outputs from Frontiers in Physiology
#2,839
of 13,773 outputs
Outputs of similar age
#108,431
of 329,131 outputs
Outputs of similar age from Frontiers in Physiology
#118
of 467 outputs
Altmetric has tracked 23,026,672 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 13,773 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 79% 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 329,131 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 467 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 74% of its contemporaries.