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Lower Limb Strength Asymmetries Predicts Perceptions Of Limb Function In University Athletes

2024· article· en· W4402662525 on OpenAlexaff
Zachary J. McClean, Nathan Boon-van Mossel, Mark McKenzie, Per Aagaard, Kati Pasanen, Victor Lun, Walter Herzog, Matthew J. Jordan

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAthletesPhysical medicine and rehabilitationLower limbPsychologyPhysical therapyFunction (biology)MedicineBiologySurgery

Abstract

fetched live from OpenAlex

Previous musculoskeletal injury is a primary risk factor for future injury in part due to persistent neuromuscular deficits and reduced psychological readiness. Central to the aim of reducing sport injuries and increasing athletic performance, a bio-psycho-social approach to athlete monitoring has been adopted that incorporates both objective measures of neuromuscular function and subjective assessments of psychological readiness such as the Sport Fitness Index (SFI) which quantifies athletes’ perceptions of lower-limb function (perceived-function). However, the relationship between perceived-function and objective functional measures such as the between-limb asymmetry index (AI) remains unknown. PURPOSE: To evaluate the relationship between perceived-function and limb AI across a lower body muscle strength testing battery. METHODS: University athletes (n = 196, females: n = 96) from six high risk sports for lower body injury completed the SFI, maximal countermovement jump (CMJ) testing with extra loads corresponding to 0%, 30% and 60% body mass (n = 5), unilateral CMJ (n = 3) testing, and unilateral repeated hop testing (n = 20) on a dual force plate system. Athletes also performed isokinetic multi-joint eccentric and concentric strength testing in a robotic leg press dynamometer. Between-limb AIs were calculated for each testing condition. Perceived-function in the SFI was rated on a 0-100 scale, to obtain GOOD (SFI >86), FAIR (61 < SFI < 85), and POOR (SFI < 60) perceived-function groups. A cumulative link mixed effects model was used to examine the effects of between-limb AI on perceived-function groups. RESULTS: For every absolute unit increase in isokinetic concentric strength AI and CMJ with 60% body mass concentric impulse AI, the odds of belonging to a lower perceived-function group increased by 1.036 (95% CI: 1.001-1.070) and 1.161 (CI: 1.010-1.336) times; respectively. CONCLUSIONS: Increased concentric muscle strength asymmetries predicted decreased perceived-function in university athletes. By combining introspective measures of limb function such as the SFI along with mechanical muscle function testing, it is possible to achieve an integrated bio-psycho-social approach to preseason testing that may inform targeted intervention protocols to mitigate injury risk on a group level.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.011
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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