Evaluation of an injury prevention programme (Prep-to-Play) in women and girls playing Australian Football: design of a pragmatic, type III, hybrid implementation-effectiveness, stepped-wedge, cluster randomised controlled trial
Bibliographic record
Abstract
Introduction Due to the increase in participation and risk of anterior cruciate ligament (ACL) injuries and concussion in women’s Australian Football, an injury prevention programme (Prep-to-Play) was codesigned with consumers (eg, coaches, players) and stakeholders (eg, the Australian Football League). The impact of supported and unsupported interventions on the use of Prep-to-Play (primary aim) and injury rates (secondary aim) will be evaluated in women and girls playing community Australian Football. Methods and analysis This stepped-wedge, cluster randomised controlled trial will include ≥140 teams from U16, U18 or senior women’s competitions. All 10 geographically separated clusters (each containing ≥14 teams) will start in the control (unsupported) phase and be randomised to one of five dates (or ‘wedges’) during the 2021 or 2022 season to sequentially transition to the intervention (supported Prep-to-Play), until all teams receive the intervention. Prep-to-Play includes four elements: a neuromuscular training warm-up, contact-focussed football skills (eg, tackling), strength exercises and education (eg, technique cues). When transitioning to supported interventions, study physiotherapists will deliver a workshop to coaches and player leaders on how to use Prep-to-Play, attend team training at least two times and provide ongoing support. In the unsupported phase, team will continue usual routines and may freely access available Prep-to-Play resources online (eg, posters and videos about the four elements), but without additional face-to-face support. Outcomes will be evaluated throughout the 2021 and 2022 seasons (~14 weeks per season). Primary outcome: use of Prep-to-Play will be reported via a team designate (weekly) and an independent observer (five visits over the two seasons) and defined as the team completing 75% of the programme, two-thirds (67%) of the time. Secondary outcomes: injuries will be reported by the team sports trainer and/or players. Injury definition: any injury occurring during a football match or training that results in: (1) being unable to return to the field of play for that match or (2) missing ≥ one match. Outcomes in the supported and unsupported phases will be compared using a generalised linear mixed model adjusting for clustering and time. Due to the type III hybrid implementation-effectiveness design, the study is powered to detect a improvement in use of Prep-to-Play and a reduction in ACL injuries. Ethics and dissemination La Trobe University Ethics Committee (HREC 20488) approved. Coaches provided informed consent to receive the supported intervention and players provided consent to be contacted if they sustained a head or knee injury. Results will be disseminated through partner organisations, peer-reviewed publications and scientific conferences. Trial registration number NCT04856241 .
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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 | 0.021 | 0.023 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".