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Core strengthening and synchronized swimming: TRX® suspension training in young female athletes

2017· article· en· W2465312145 on OpenAlexaboutno aff
Amalia Tinto, Milena Fasano

Bibliographic record

VenueThe Journal of Sports Medicine and Physical Fitness · 2017
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsAthletesCore stabilityPhysical therapyMedicineCore (optical fiber)Supine positionPhysical medicine and rehabilitationCore strengthComputer scienceSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Developing muscle strength and full body stability is essential for the efficient execution of technical moves in synchronized swimming. However, many swimmers find it difficult to control body stability while executing particular figures in water. We evaluated the effects of TRX® suspension training (2 sessions weekly for 6 months on core strength and core stability in young female. METHODS: Twenty synchronized swimmers (Beginners A category, mean age 10±1 years) are divided in experimental group (EG; N.=10 athletes) and control group (CG; N.=10 athletes). EG received suspension training twice weekly (each session lasting about 15 min) as dryland exercises for 6 months in addition to routine training. CG completed routine training with conventional dryland exercises. Before (T1) and after (T2) completion of the study oblique and transversus abdominis muscle force was measured using a Stabilizer Pressure Biofeedback unit, in prone and supine positions, and isotonic muscle endurance was evaluated with the McGill Test. RESULTS: Non-parametric statistical analysis showed a significant increase (P<0.0001) in the majority of the parameters in the experimental group. CONCLUSIONS: The study results provide evidence for the benefit of integrating TRX® suspension training in dryland exercises for muscle strengthening in young athletes practicing synchronized swimming, and in general reiterates the importance of strengthening the core area to ensure stability and specific adaptations, improve the quality of the movement and prevent against injury.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.468
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.386
Teacher spread0.307 · 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.

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

Citations23
Published2017
Admission routes1
Has abstractyes

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