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Record W4401106180 · doi:10.1139/apnm-2024-0151

A quasi-experimental study on the energy expenditure, exercise intensity, and rating of perceived exertion of a male bodybuilding posing training

2024· article· en· W4401106180 on OpenAlexvenueno aff
Douglas Leão Peixoto, Dahan da Cunha Nascimento, Ronaldo Ferreira Moura, Wilson Max Almeida Monteiro de Moraes, Bruno Magalhães de Castro, Leandro Lima de Sousa, Nicholas Rolnick, Jonato Prestes

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2024
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsRating of perceived exertionPerceived exertionMedicineAthletesHeart rateIntensity (physics)Physical therapyMetabolic equivalentExertionEnergy expenditureInternal medicineBlood pressurePhysical activity

Abstract

fetched live from OpenAlex

This study aimed to evaluate the intensity of posing training in male bodybuilders by comparing it to vigorous intensity parameters and examining the effects of stimulant usage and preparation phases. Specifically, this study compared posing training to established vigorous intensity benchmarks using metabolic equivalents (METs) and heart rate (HR) responses and assessed differences between athletes using stimulants versus those not using stimulants, as well as during peak week versus other preparation phases. Fifteen male bodybuilding athletes (mean age: 32.07 ± 7.82 years; mean body mass: 92.89 ± 9.06 kg; mean height: 1.76 ± 0.05 m; mean body mass index: 29.78 ± 2.24 kg/m²) completed four compulsory posing sets. Findings demonstrated that posing training can be classified as vigorous training intensity using METs (mean difference of −0.50 METs, p = 0.067, ES = −0.51) and maximum HR (mean difference of 14.55 bpm, p = 0.009, ES = 0.79) compared to the established values of 6.0 METs and 77% vigorous intensity of %HRmax, respectively. Additionally, athletes using stimulants exhibited higher ratings of perceived exertion (RPE) of 2.20 arbitrary units ( p = 0.008) and maximum HR (mean difference of 24.37 bpm, p = 0.005, ES = 0.79) compared to those not using stimulants. During peak week, athletes showed higher RPE of 2.38 arbitrary units ( p = 0.004) and maximum HR (mean difference of 14.55 bpm, p = 0.009, ES = 0.79) compared to other preparation phases. These results indicate that bodybuilding posing training meets the criteria for vigorous exercise intensity and that stimulant use and peak week significantly affect physiological responses and perceived exertion. Novelty This study is novel in classifying bodybuilding posing training as vigorous intensity exercise using metabolic equivalents (METs) and heart rate (HR) responses. It provides empirical evidence showing that posing training meets the vigorous intensity benchmarks, with METs and %HRmax values comparable to established vigorous exercise standards. The research highlights the novel finding that stimulant usage and the peak week phase of preparation significantly influence physiological responses and perceived exertion in bodybuilders. Specifically, athletes using stimulants and those in peak week displayed higher ratings of perceived exertion (RPE) and maximum heart rates, indicating that these factors notably affect the intensity and perceived difficulty of posing training.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.286
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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