Evidence map›Paper›PMID 37628149›Full record

ArticleEntropy (Basel, Switzerland)2023

A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon.

Florent Palacin, Luc Poinsard, Jean Renaud Pycke, Véronique Billat

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Brain, Metabolic, and RPE Responses during a Free-Pace Marathon: A Preliminary Study.International journal of environmental research and public health · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Florent PalacinLaboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles Neuroscience Institut, 1070 Bruxelles, Belgium.
Luc PoinsardLaboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles Neuroscience Institut, 1070 Bruxelles, Belgium.
Jean Renaud PyckeUMR8071-CNRS-Laboratoire de Mathématiques et Modélisation d'Evry, Université Paris-Saclay, Univ Evry, 91000 Evry-Courcouronnes, France.
Véronique BillatEA 4526-Laboratoire IBISC Paris-Saclay, Univ Evry, 91000 Evry-Courcouronnes, France.ORCID 0000-0002-6085-998X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A new group of marathon participants with minimal prior experience encounters the phenomenon known as "hitting the wall," characterized by a notable decline in velocity accompanied by the heightened perception of fatigue (rate of perceived exertion, RPE). Previous research has suggested that successfully completing a marathon requires self-pacing according to RPE rather than attempting to maintain a constant speed or heart rate. However, it remains unclear how runners can self-pace their races based on the signals received from their physiological and mechanical running parameters. This study aims to investigate the relationship between the amount of information conveyed in a message or signal, RPE, and performance. It is hypothesized that a reduction in physiological or mechanical information (quantified by Shannon Entropy) affects performance. The entropy of heart rate, speed, and stride length was calculated for each kilometer of the race. The results showed that stride length had the highest entropy among the variables, and a reduction in its entropy to less than 50% of its maximum value (H = 3.3) was strongly associated with the distance (between 22 and 40) at which participants reported "hard exertion" (as indicated by an RPE of 15) and their performance (

Indexed as

hitting the wallmarathon runningperformanceShannon entropystride length

Identifiers

PMID37628149
PMCPMC10453470

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.