MétaCan
Menu
Back to cohort
Record W4414564217 · doi:10.3390/sports13090325

A Scoping Review of Sport National Concussion Guidelines in Squash

2025· review· en· W4414564217 on OpenAlexaboutno aff
Nina Mangan, Neil Heron

Bibliographic record

VenueSports · 2025
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
FundersAspetar Orthopaedic and Sports Medicine Hospital
KeywordsConcussionSquashPoison controlSuicide preventionAthletesInjury prevention

Abstract

fetched live from OpenAlex

Squash is a commonly played racquet sport in which players are at risk of concussion injuries. This review aims to identify and assess the squash concussion guidelines in top squash countries. Design: Scoping review. Method: This review follows the framework laid out by Arksey and O’Malley and later advanced by Levac et al. This review adheres to the PRISMA-ScR checklist. Eligibility criteria included countries with either a female or male player in the World Squash Federation Top 50 World Rankings in June 2025. This produced a list of twenty-one countries, and seven concussion guidelines were eligible for review. Results: Twenty-one countries matched the inclusion criteria. Canada is the only country identified with a squash-specific concussion guideline. Seven countries had national concussion guidance, and fourteen countries had no national concussion guidance. Conclusions: There is a lack of squash-specific concussion guidelines. The World Squash Federation and national squash organisations should produce squash-specific concussion guidelines that are in line with the Amsterdam Statement and their own respective country’s national guidelines. The World Squash Federation should specifically reference concussion in their rules and should strongly consider updating their self-inflicted injury time rules to allow for the suspension of play for up to fifteen minutes if there is a suspected head 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.197
GPT teacher head0.528
Teacher spread0.330 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueSportsSame topicTraumatic Brain Injury ResearchFrench-language works237,207