Sport-related concussion in soccer –a scoping review of available guidelines and a call for action to FIFA & soccer governing bodies
Bibliographic record
Abstract
Introduction: Sport-related concussions (SRC) have been a concern in all sports, including soccer. The long-term effects of soccer-related head injuries are a public health concern. The Concussion in Sport Group (CISG) released a consensus statement in 2017 and several soccer governing associations have published their own SRC guidelines while referring to it but it is unclear whether this has been universally adopted. Research question: We aimed to investigate whether guidelines published by soccer associations have any discrepancies; and the extent to which they follow the CISG recommendations. Materials and methods: A scoping review of available soccer-specific SRC guidelines was performed via databases PubMed, Google Scholar, and official soccer association websites via web browser Google. The inclusion criteria were soccer-specific SRC guidelines. Comparisons between guidelines were made concerning the following index items: initial (on-site) assessment, removal from play, re-evaluation with neuroimaging, return-to-sport protocol, special populations, and education. Results: Nine soccer associations with available guidelines were included in this review. Guidelines obtained were from official associations in the United Kingdom, United States of America, Canada, Australia, and New Zealand. When compared to each other and the CISG recommendations, discrepancies were found within guidelines regarding the index items. Additionally, major soccer associations in some countries famous for soccer were found to have not published any publicly available guidelines. Discussion and conclusion: SRC guidelines from different soccer associations contain discrepancies which may be detrimental to athletes, both short and long-term. We recommend that all major soccer governing associations publish guidelines that are standardised and accessible to all athletes.
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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 | 0.033 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.026 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".