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Record W2398596261 · doi:10.1055/s-0042-104199

A Preliminary Exploration of Concussion and Strength Performance in Youth Ice Hockey Players

2016· article· en· W2398596261 on OpenAlexaff
Nick Reed, Tim Taha, Georges Monette, Michelle Keightley

Bibliographic record

VenueInternational Journal of Sports Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsYork UniversityUniversity of TorontoHolland Bloorview Kids Rehabilitation Hospital
Fundersnot available
KeywordsConcussionIce hockeyAthletesPhysical therapyGrip strengthPhysical medicine and rehabilitationMedicineInjury preventionPoison controlPsychologyMedical emergency

Abstract

fetched live from OpenAlex

The objective of this study was to describe the effect of concussion on upper and lower body strength in children and youth athletes. The participant group was made up of 178 unique male and female ice hockey players (ages 8-14 years). Using a 3-year prospective longitudinal research design, baseline and post-concussion data on hand grip strength, jump tests, and leg maximal voluntary contraction were collected. Using a linear mixed-effects model, no significant differences were found when comparing the baseline strength performance of individuals who went on to experience a concussion and those who did not. When accounting for sex, multiple concussions, and ongoing changes in strength associated with age, weaker hand grip scores were found following concussion while participants were still symptomatic. Lower squat jump heights were achieved while participants were symptomatic as well as when they were no longer self-reporting symptoms associated with concussion. This study represents an initial step towards better understanding strength performance following concussion that may limit the on and off ice performance of youth ice hockey players, as well as predispose youth to subsequent injuries.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.059
GPT teacher head0.338
Teacher spread0.279 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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