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Record W4285387900 · doi:10.3389/fspor.2022.868518

An Investigation of Bilateral Symmetry in Softball Pitchers According to Body Composition

2022· article· en· W4285387900 on OpenAlexaff
Kenzie B. Friesen, Angelica E. Lang, Karen Chad, Gretchen D. Oliver

Bibliographic record

VenueFrontiers in Sports and Active Living · 2022
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInternal rotationMedicineIsometric exerciseExternal rotationPhysical therapyRange of motionSurgery

Abstract

fetched live from OpenAlex

Introduction High body fat percentage (bf%) is considered a potential injury risk factor for softball pitchers amidst the already high rates of pitching-related injury. Similarly, research points out that large bilateral asymmetries are another risk factor for softball pitchers. As softball pitching is a highly asymmetric sport and the repetitive nature of the windmill pitch places high stress on the body while pitchers are in unbalanced and asymmetric positions, research examining body composition and asymmetry is necessary. Purpose The purpose of this study was to compare functional characteristics of softball pitchers with a healthy and a high bf%. Bilateral symmetry was assessed for pitchers' hip and shoulder isometric strength (ISO) and range of motion (ROM) between the following two groups of softball pitchers: (1) those with a high bf% (≥32%) and (2) those with a healthy bf% (<32%). Methods A total of 41 high school female softball pitchers from the southern United States agreed to participate (1.69 ± 0.07 m, 76.14 ± 17.08 kg, 15.1 ± 1.1 years). Pitchers completed a dual-energy X-ray absorptiometry (DEXA) scan and were grouped into one of the following two categories based on their bf%: healthy (<32 bf%) and high (≥32 bf%). Bilateral symmetry was assessed for pitchers' hip and shoulder ISO and ROM using a handheld dynamometer and inclinometer, respectively. Bilateral arm bone and lean mass was also measured via the DEXA. Results Mixed analyses of variance revealed a significant interaction between bf% groups and side dominance for internal rotation shoulder ROM, F(1, 39) = 14.383, p < 0.001, η2p = 0.269. Main effects for side dominance were also observed for shoulder external rotation ISO, F(1, 39) = 8.133, p = 0.007, η2p = 0.173, hip internal rotation ISO, F(1, 39) = 4.635, p = 0.038, η2p = 0.106, arm bone mass, F(1, 39) = 38.620, p < 0.001, η2p = 0.498, and arm lean mass, F(1, 39) = 101.869, p < 0.001, η2p = 0.723. Conclusion Asymmetries and slight differences in functional characteristics exist between bf% groups. Altered functional characteristics may influence pitchers' windmill pitch movement and should be acknowledged by support staff to improve softball pitchers' health and longevity. Implications Insight into asymmetries can help researchers and clinicians understand the implication of excess body fat and further theorize mechanisms of injury among this athlete population.

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 score0.004
Threshold uncertainty score0.012

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.267
Teacher spread0.256 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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