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Record W3216029393 · doi:10.1136/bjsports-2021-ioc.267

289 Injury rates and mechanisms of injury in female high school rugby

2021· article· en· W3216029393 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePoster presentations · 2021
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsHotchkiss Brain InstituteSpinal Cord Injury AlbertaAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsInjury preventionPhysical therapyMedicinePoison controlTeam sportOccupational safety and healthSuicide preventionHuman factors and ergonomicsInjury surveillanceFootballEmergency medicineAthletes

Abstract

fetched live from OpenAlex

<h3>Background</h3> In Canada, unlike many countries, youth rugby players often have their first exposure to the sport in high school (ages 15–16). There are few studies examining injuries in female high school rugby union. <h3>Objective</h3> To describe injury rates and mechanisms among females participating in high school rugby union. <h3>Design</h3> Prospective cohort study. <h3>Setting</h3> Rugby pitches (Calgary, Canada). <h3>Participants</h3> Female high school rugby players (ages 15–18) participating in 2018 (7 teams, n=214) and 2019 (7 teams, n=207) seasons. <h3>Assessment of Risk Factors</h3> Mechanism of injury was recorded by team designates on an electronic injury report form, validated by a certified athletic therapist. <h3>Main Outcome Measurements</h3> Training and match injuries were identified by a team designate or study therapist if the player 1) required medical attention, 2) was unable to complete the session, and/or 3) unable to participate in activity for ≥ one day. <h3>Results</h3> There were 155 match [93.7 injuries/1000-match-hours (95%CI, 78.6–111.7)] and 85 training injuries [5.3 injuries/1000-training-hours ( 95%CI, 4.0–6.9)] across two years of injury surveillance. Match injuries most commonly occurred while tackling [62 injuries (40%) 37.5 injuries/1000-match-hours (95%CI, 27.1–51.8), being tackled [47 injuries (30%), 28.4 injuries/1000-match-hours (95%CI, 20.3–39.8)], and during a ruck/maul [12 injuries (8%), 7.3 injuries/1000-match-hours]. Training injuries most commonly occurred while tackling [20 injuries (24%), 1.2 injuries/1000-training-hours (95%CI, 0.7–2,4)], being tackled [17 injuries (20%), 1.1 injuries/1000-training-hours (95%CI, 0.7–1.7)], and running [9 injuries (11%), 0.6 injuries/1000-training-hours (95%CI, 0.3–1.0)]. <h3>Conclusions</h3> Tackling was identified as the most common mechanism of injury among female high school rugby players, with the highest rates in the active tackler during matches. Safe tackling interventions are an ideal primary prevention target to reduce the risk of injury within this population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.326
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it