↓ Skip to main content

Can We Draw General Conclusions from Interval Training Studies?

Overview of attention for article published in Sports Medicine, April 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
27 X users
facebook
1 Facebook page

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
138 Mendeley
Title
Can We Draw General Conclusions from Interval Training Studies?
Published in
Sports Medicine, April 2018
DOI 10.1007/s40279-018-0925-1
Pubmed ID
Authors

Ricardo Borges Viana, Claudio Andre Barbosa de Lira, João Pedro Araújo Naves, Victor Silveira Coswig, Fabrício Boscolo Del Vecchio, Rodrigo Ramirez-Campillo, Carlos Alexandre Vieira, Paulo Gentil

Abstract

Interval training (IT) has been used for many decades with the purpose of increasing performance and promoting health benefits while demanding a relatively small amount of time. IT can be defined as intermittent periods of intense exercise separated by periods of recovery and has been divided into high-intensity interval training (HIIT), sprint interval training (SIT), and repeated sprint training (RST). IT use has resulted in the publication of many studies and many of them with conflicting results and positions. The aim of this article was to move forward and understand the studies' protocols in order to draw accurate conclusions, as well as to avoid previous mistakes and effectively reproduce previous protocols. When analyzing the literature, we found many inconsistencies, such as the controversial concept of 'supramaximal' effort, a misunderstanding with regard to the term 'high intensity,' and the use of different strategies to control intensity. The adequate definition and interpretation of training intensity seems to be vital, since the results of IT are largely dependent on it. These observations are only a few examples of the complexity involved in IT prescription, and are discussed to illustrate some problems with the current literature regarding IT. Therefore, it is our opinion that it is not possible to draw general conclusions about IT without considering all variables used in IT prescription, such as exercise modality, intensity, effort and rest times, and participants' characteristics. In order to help guide researchers and health professionals in their practices it is important that experimental studies report their methods in as much detail as possible and future reviews and meta-analyses should critically discuss the articles included in the light of their methods to avoid inappropriate generalizations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 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 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 138 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 25 18%
Student > Bachelor 22 16%
Student > Ph. D. Student 10 7%
Student > Doctoral Student 8 6%
Professor 8 6%
Other 22 16%
Unknown 43 31%
Readers by discipline Count As %
Sports and Recreations 49 36%
Nursing and Health Professions 10 7%
Agricultural and Biological Sciences 8 6%
Medicine and Dentistry 8 6%
Social Sciences 3 2%
Other 6 4%
Unknown 54 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 31 July 2023.
All research outputs
#2,286,223
of 25,247,084 outputs
Outputs from Sports Medicine
#1,487
of 2,901 outputs
Outputs of similar age
#46,507
of 333,571 outputs
Outputs of similar age from Sports Medicine
#29
of 45 outputs
Altmetric has tracked 25,247,084 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,901 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.9. This one is in the 48th percentile – i.e., 48% 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 333,571 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 86% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.