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Record W2979971995 · doi:10.5539/jedp.v9n2p150

The Effect of Different Musical Rhythms on Anaerobic Abilities in Taekwondo Athletes

2019· article· en· W2979971995 on OpenAlexvenueno aff
Rami Hammad, Amro Abu Baker, Julika Schatte, Adnan Alqaraan, Ahmad AlMulla, Saleh Hammad

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
FundersUniversity of Jordan
KeywordsAnaerobic exerciseHeart rateRhythmAthletesBlood lactateWingate testBlood pressureAnalysis of variancePsychologyMedicineAudiologyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

The aim of this study was to determine the effects of different musical rhythms on taekwondo athletes. The variance in athletes’ anaerobic abilities performed under slow and fast musical rhythms was tested in the study presented. Previous studies have demonstrated how music may cause physiological responses before, during, or after different types of exercises. The aim of this study was to identify the effect of music played in two different rhythms (slow 80 b/m, and fast 200 b/m) during anaerobic exercises by measuring four specific physiological variables: heart rate (HR), blood pressure (BP), blood lactate (BL), and rate of perceived exertion (RPE). Additionally, the peak power of each athlete was assessed. Ten black-belt taekwondo male athletes (average age 20.38±1.51) performed for 30 seconds at their maximum anaerobic power on a Monarch Ergonomic that was connected to the Wingate test. The RPE indicated significant differences with a probability value of 0.014 when measured two minutes after the testing. Measurements of heart rate, blood lactate, and diastolic blood pressure after exposure to slow and fast rhythms did not show significant differences. While it has been shown in previous research that the human body tends to synchronize with rhythmic elements of music, this only holds true for exposure to specific rhythms after a longer period of time. The study conducted was based on exposure to different rhythms for only 30 seconds, which may be why these variables did not differ significantly. Yet, results for systolic blood pressure proved significantly different for fast and slow musical rhythms with a probability value of 0.0004. 

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.347
Teacher spread0.328 · 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 teacher head, not a consensus.

Study designObservational
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

Citations6
Published2019
Admission routes1
Has abstractyes

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