Evidence map›Paper›PMID 24610246›Full record

ArticleEuropean journal of applied physiology2014

The interplay between arms-only propelling efficiency, power output and speed in master swimmers.

P Zamparo, E Turri, R Peterson Silveira, A Poli

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Article in European journal of applied physiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The energy cost of swimming and its determinants.European journal of applied physiology · 2020
    Review
  6. Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

P ZamparoDepartment of Neurological and Movement Sciences, University of Verona, Via F. Casorati 43, 37131, Verona, Italy, paola.zamparo@univr.it.
E Turri
R Peterson Silveira
A Poli

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo explore the interplay between arms-only propelling efficiency (η(p)), mechanical power output (W(tot)) and swimming speed (V); these three parameters are indeed related through the following equation V(3) = 1/kη(p)W(tot) (where k is the speed-specific drag; k = F/V(2)); thus, the larger are η(p) and W(tot) the larger is V. We furthermore wanted to test the hypothesis that a multiple linear regression between W(tot), η(p) and V would have a stronger correlation coefficient than a linear regression between W(tot) and V alone.

methodsTo this aim we recruited 29 master swimmers (21 M/8F) who were asked to perform (1) an incremental protocol at the arm-ergometer (dry-land test) to determine W(tot) at VO(2max) (e.g. V(max)); (2) a maximal 200 m swim trial (with a pull buoy: arms only) during which V and η(p) were determined.

resultsNo relationship was found between W(max) and η(p) (not necessarily the swimmers with the largest W(max) are those with the largest η(p) and vice versa) whereas significant correlations were found between W(max) and V (R = 0.419, P = 0.024) and η(p) and V (R = 0.741, P = 0.001); a multiple linear regression indicates that about 75% of the variability of V can be explained by the variability of W(max) and η(p) (R = 0.865, P < 0.001).

conclusionsThese findings indicate that η(p) should be taken into consideration when the relationship between W(max) and V is investigated and that this allows to better explain the inter-subject variability in performance (swimming speed).

Indexed as

Athletic PerformanceOxygen ConsumptionAdultArmFemaleHeart RateHumansMaleSwimming

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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.