Complexity of concussion management in youth ice hockey: Context matters
Bibliographic record
Abstract
The public's concussion awareness is increasing. However, youth may still participate in sport through concussion symptoms and parents may not take their child with a suspected concussion to a physician for assessment and clearance to return to sport. This study uses qualitative methodology to explore parent and coach experiences with concussion management in youth ice hockey. Potential barriers and facilitators to a coach removing a player from play following a suspected concussion and parents taking their child to see a physician are highlighted. We purposively selected twenty-four hockey parents and coaches in Calgary, Canada, and interviewed them to understand their experience managing youth following a suspected concussion. Using thematic analysis, we highlight barriers and facilitators to coaches appropriately removing a player from participation and parents taking their child to a physician for assessment. Contextual factors including competing priorities, emotional responses, severity of injury, parent and coach beliefs, appropriate communication, and concussion awareness can influence coach and parent concussion management strategies. Coaches, parents, and players play a vital role in facilitating concussion identification and appropriate management. While further education of coaches and parents is indicated, it is important to consider contextual factors that interfere with concussion management behaviors.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".