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Record W4392850506 · doi:10.1136/bjsports-2024-ioc.308

725 MEP091 – Its time to slash injuries: video analysis of in-game physical contacts and suspected-injuries in Canadian youth box lacrosse

2024· article· en· W4392850506 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsnot available
Fundersnot available
KeywordsVideo gamePoisson regressionDemographyPoison controlRate ratioPsychologyMedicineComputer scienceMultimediaMedical emergencyPopulation

Abstract

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Background Lacrosse (Canada’s National summer-sport) hosts >80,000 registrants annually. Unfortunately, few prevention efforts have been examined in Box lacrosse. Therefore, examining in-game player-to-play physical-contacts is paramount for future prevention work. Objective To examine the incidence rates (IRs) of physical-contacts, including bodychecks (BC; high-intensity trunk-contact), high-intensity cross-checks (HICC; two-handed push with stick), head contacts (HCs), and video suspected-injuries (SI) across elite division-A youth (ages 9–16) Box lacrosse tournament-play. Design Cross-sectional video-analysis study. Setting Canada. Participants Elite Division-A (highest division) Box lacrosse players within U11 (ages 9–10), U13 (ages 11–12), U15 (ages 13–14), and U17 (ages 15–16) levels. Assessment of Risk Factors Comparison of physical-contact measures during tournament-play between the 4 age levels (n=24 games/6 per level). Main Outcome Measurements Games were analyzed using Dartfish video-analysis software and validated physical-contact criteria. Poisson regression analyses (adjusted for cluster by game and offset by playing time) were used to compare the IRs (per 100 game-minutes) using incidence rate ratios (IRR) for BCs, HCs, HICCs, and video-SIs. Results When compared with U13 (reference), the BC IR was 4.34-fold higher in U11 (IRR=4.34;95%CI:1.74–10.81), 3.26-fold higher in U15 (IRR=3.26;95%CI:1.31–8.13), and 3.65-fold higher in U17 (IRR=3.65;95%CI:1.48–9.00). Moreover, the HICC IR was 38% higher in U11 (IRR=1.38;95%CI:1.00–1.90), did not differ for U15, and was 47% lower in U17 (IRR=0.53;95%CI:0.35–0.78). The HC IRs were 3.81-fold higher in U11 (IRR=3.81;95%CI:2.38–6.11) and 3.40-fold higher in U17 (IRR=3.40;95%CI:2.21–5.23), but not different in U15 (when compared with U13). SI-IRs in U11 (IR-U11=6.24;95%CI:3.54–10.98) were 3.91-fold higher than in U13 (IR-U13=1.60;95%CI:0.60–4.25) (IRR=3.91; 95%CI:1.26–12.12) and did not differ for U15 nor U17. Conclusion The high BC, HICC, and HC IRs in U11 are concerning and likely associated with the 3-fold higher SI-IR. Lacrosse Canada should consider exploring strategies related to policy that lowers BC, HICC, and HC physical-contacts in U11 to promote player safety.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.285
Teacher spread0.277 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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