Concussions in Community-Level Rugby: Risk, Knowledge, and Attitudes
Bibliographic record
Abstract
BACKGROUND: Rugby is a popular collision sport where participants are at risk of sustaining concussions. Most research focuses on elite-level or youth divisions. Comparatively, little is known about adult community rugby. The aim of this research was to estimate the risk of sustaining a concussion during participation in community-level rugby and summarize the collective knowledge and attitudes toward concussions. HYPOTHESIS: Concussion symptoms will be reported frequently among community-level rugby players and a substantial proportion will report a willingness to continue participation despite the risk. STUDY DESIGN: Cross-sectional analysis. LEVEL OF EVIDENCE: Level 3. METHODS: An anonymous, voluntary survey was administered to all 464 senior rugby players registered in the province of Manitoba in 2015. Two primary domains were assessed: (1) concussion history from the preceding season including occurrence, symptomatology, and impact on daily activities and (2) knowledge and attitudes toward concussion risks and management. RESULTS: In total, 284 (61.2%) rugby players responded. Concussive symptoms were reported by 106 (37.3%). Of those, 87% were formally diagnosed with a concussion and 27% missed school and/or work as a result. The danger of playing while symptomatic was recognized by 93.7% of participants, yet 29% indicated they would continue while symptomatic. Furthermore, 39% felt they were letting others down if they stopped playing due to a concussion. CONCLUSION: Concussive symptoms were common among the study cohort and had a notable impact on daily activities. A high proportion of players were willing to continue while experiencing symptoms despite recognizing the danger. The observed discord between knowledge and attitudes implicates a culture of "playing injured." CLINICAL RELEVANCE: Understanding the risk of injury may affect an individual's decision to participate in community-level rugby. Moreover, evidence of discord between the knowledge and attitudes of players may direct future research initiatives and league governance.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".