Evidence map›Paper›PMID 37797065›Full record

ArticlePloS one2023

The intensity of a resistance exercise session can be quantified by the work rate of exercise.

Brendan R Scott, Kieran J Marston, Shaun Y M Teo, Mitchell R L Forrest, Andrew Jonson, Thomas P Walden, Brook Galna, Jeremiah J Peiffer

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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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

8 authors.

Brendan R ScottCentre for Healthy Ageing, Murdoch University, Murdoch, Australia.ORCID 0000-0002-2484-4019
Kieran J MarstonCentre for Healthy Ageing, Murdoch University, Murdoch, Australia.
Shaun Y M TeoTelethon Kids Institute, Perth Children's Hospital, Nedlands, Australia.
Mitchell R L ForrestMurdoch Applied Sports Science Laboratory, Discipline of Exercise Science, Murdoch University, Murdoch, Australia.
Andrew JonsonMurdoch Applied Sports Science Laboratory, Discipline of Exercise Science, Murdoch University, Murdoch, Australia.
Thomas P WaldenCentre for Healthy Ageing, Murdoch University, Murdoch, Australia.
Brook GalnaCentre for Healthy Ageing, Murdoch University, Murdoch, Australia.
Jeremiah J PeifferCentre for Healthy Ageing, Murdoch University, Murdoch, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAthletes regularly perform resistance training, yet it is unknown how best to monitor its intensity. This study compared different resistance exercise intensity metrics to determine their sensitivity to manipulating work rate (via altering inter-set rest and load).

methodsFollowing baseline testing for 10- and 3-repetition maximum (RM; squat and bench press), fourteen trained participants completed four volume-matched protocols in a randomised order: 3x10 with 85% 10RM, 60 s rest (3x1060s); 3x10 with 85% 10RM, 180 s (3x10180s); 8x3 with 85% 3RM, 120 s (8x3120s); 8x3 with 85% 3RM, 300 s (8x3300s). Internal intensity was quantified via rate of oxygen consumption ([Formula: see text]), heart rate, blood lactate concentration, and rating of perceived exertion (RPE). External intensity was assessed via previously developed "Training-Intensity" (TI) and "Intensity-Index" (II) metrics, and from exercise work rate (expressed as kg∙min-1 and joules∙min-1).

resultsInternal intensity and work-rate metrics were highest for 3x1060s, followed by 3x10180s, 8x3120s and 8x3300s (p≤0.027). TI and II were higher for 8x3 than 3x10 protocols (p<0.001), but not different within these configurations. Internal intensity measures were more strongly correlated with work rate (r = 0.37-0.96) than TI and II (r = -0.42-0.33) metrics.

conclusionsWork rate corroborated objective internal intensity metrics during resistance exercise, with the highest work rate session (3x1060s) also eliciting greater RPE scores than other protocols. In contrast, the TI and II did not agree with other intensity measures, likely because they do not consider rest periods. Practitioners can plan for the physiological and perceptual demands of resistance training by estimating work rate.

Indexed as

Physical ExertionResistance TrainingExerciseHeart RateHumansLactic AcidLactic Acid

Identifiers

PMID37797065
PMCPMC10553797

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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.