Adolescent female rugby union players’ attitudes, beliefs and behaviours towards injury and injury prevention strategies in England
Bibliographic record
Abstract
Background and aims: Within adolescent female rugby union, various effective injury prevention strategies are available to players to mitigate injury. However, little is known regarding the players' attitudes, beliefs and behaviours towards those strategies, as well as injuries. The primary aim of the study was to investigate the attitudes, beliefs, behaviours and injury-reporting behaviours of adolescent female rugby players regarding injury and injury prevention strategies. The secondary aim was to examine associations between individual factors (eg, player demographics) and injury-reporting behaviours. Methods: Participants completed an online cross-sectional survey and were recruited from under-16 and under-18 rugby teams in schools/colleges, clubs and developing player pathway programmes in England. Results: 1062 players were contacted to participate, 424 responded and 422 met the eligibility criteria; 79 participants had incomplete responses. 14% of players had not previously reported a suspected concussion to a coach/medical staff member, and 37% of players had previously not reported sustaining one or more musculoskeletal (MSK) injuries to a coach/medical staff member. Factors cited for non-disclosure of concussion and MSK injuries included not wanting to miss rugby sessions (43% and 39%) and not knowing that symptom(s) were related to an injury (11% and 17%). Players held positive attitudes, beliefs and behaviours towards injury and injury prevention, but their understanding of the effectiveness of protective equipment varied. Conclusion: This study provides a greater understanding of adolescent female rugby players' attitudes, beliefs and behaviours towards injury and injury prevention and aids in the development of effective injury prevention initiatives.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".