Injury Rates, Mechanisms, Risk Factors and Prevention Strategies in Youth Rugby Union: What’s All the Ruck-Us About? A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Rugby Union is a collision team sport played globally. Despite this, significant concerns have been raised regarding the sport's safety, particularly in youth players. Given this, a review of injury rates, risk factors and prevention strategies is required across different youth age groups as well as in males and females. OBJECTIVE: The objective of this systematic review (SR) and meta-analysis was to investigate injury and concussion rates, risk factors and primary prevention strategies in youth rugby. METHODS: To be included, studies were required to report either rates, risk factors or prevention strategies in youth rugby and to have a randomised controlled trial, quasi-experimental, cohort, case control, or ecological study design. Exclusion criteria included non-peer-reviewed grey literature, conference abstracts, case studies, previous systematic reviews and studies not written in English. Nine databases were searched. The full search strategy and list of sources are available and pre-registered on PROSPERO (Ref: CRD42020208343). Each study was assessed for risk of bias using the Downs and Black quality assessment tool. Meta-analyses were conducted using a DerSimonian Laird random effect model for each age group and sex. RESULTS: Sixty-nine studies were included in this SR. The match injury rates (using a 24-h time-loss definition) were 40.2/1000 match hours (95% CI 13.9-66.5) in males and 69.0/1000 match hours (95% CI 46.8-91.2) in females. Concussion rates were 6.2/1000 player-hours (95% CI 5.0-7.4) for males and 33.9/1000 player-hours (95% CI: 24.1-43.7) for females. The most common injury site was lower extremity (males) and the head/neck (females). The most common injury type was ligament sprain (males) and concussion (females). The tackle was the most common event associated with injury in matches (55% male, 71% females). Median time loss was 21 days for males and 17 days for females. Twenty-three risk factors were reported. The risk factors with the strongest evidence were higher levels of play and increasing age. Primary injury prevention strategies were the focus of only eight studies and included law changes (n = 2), equipment (n = 4), education (n = 1) and training (n = 1). The prevention strategy with the most promising evidence was neuromuscular training. The primary limitations included a broad range of injury definitions (n = 9) and rate denominators (n = 11) used, as well as a limited number of studies which could be included in the meta-analysis for females (n = 2). CONCLUSION: A focus on high-quality risk factor and primary prevention evaluation should be considered in future studies. Targeting primary prevention and stakeholder education remain key strategies in the prevention, recognition and management of injuries and concussions in youth rugby.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".