A Scoping Review of Sport National Concussion Guidelines in Squash
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".