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Record W4392753656 · doi:10.12982/jams.2024.033

Balance abilities in high dynamic-sport athletes with different maximal voluntary contraction

2024· article· en· W4392753656 on OpenAlexaboutno aff
Pornpimol Konkeaw, Sainatee Pratanaphon

Bibliographic record

VenueJournal of Associated Medical Sciences · 2024
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsIsometric exerciseDynamic balanceAthletesBalance testBalance (ability)Analysis of covariancePhysical therapyConfoundingMedicinePhysical medicine and rehabilitationPsychologyMathematicsStatisticsInternal medicine

Abstract

fetched live from OpenAlex

Background: Previous studies have shown that muscle force control during submaximal isometric contractions is associated with the ability of dynamic balance to a greater extent than static balance in healthy adults. However, the effect of maximal voluntary contraction (MVC) on balance abilities of athletes with high dynamicsport, which are most popular in Thailand, needs to be addressed. Objective: To determine static and balance abilities of high dynamic-sport athletes at different levels of MVC. Materials and methods: Three groups of high dynamic-sport athletes at different levels of maximal voluntary contraction (MVC), were voluntarily recruited using a sports matrix classification. Outcome measures comprised the Balance Error Scoring System (BESS) and the Star Excursion Balance Test (SEBT). Correlations between BESS and SEBT and confounding variables comprised of performance time of the Mcgill core endurance tests (Core), single-leg sit-to-stand (STS) test, and flexibility were investigated using Pearson’s correlation. After controlling for Core and STS, a factorial analysis of covariance (ANCOVA) was used to determine group differences in SEBT and BESS variables. Results: Athletes with high- and low- MVC had significantly different reaching distances in all SEBT directions (all, p<0.05). Significant differences between the high- and the moderate- MVC groups were observed in anterior and lateral directions (p<0.05). A significant difference between the moderate- and the low MVC groups was found in the medial direction (p<0.05). After controlling for Core and STS, the observed group differences disappeared, except in the posterolateral reaching distance between the high- and the low-MVC groups (p<0.05). A significant difference between the high- and the low-MVC groups was only observed in the total foam BESS scores with tandem stance (p<0.05) and then disappeared after adjusting for Core and STS (all, p>0.05). Conclusion: The observed differences in all SEBT directions among groups and the difference in the total BESS scores between the high- and the low- MVC, which were observed only in challenged conditions i.e., tandem-foam stance, suggested that dynamic, but not static balance performance of athletes with high dynamicsport appears to be associated with the magnitude of MVC. Core and STS, but not flexibility, are considered significant contributions to their balance performance.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.016
GPT teacher head0.339
Teacher spread0.323 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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