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THE EFFECT OF BODY CHECKING POLICY CHANGE ON CONTACT MECHANISMS IN 13 AND 14 YEAR OLD YOUTH ICE HOCKEY PLAYERS

2017· article· en· W2617347101 on OpenAlexaffabout
German Martinez, Leticia Janzen, Maciej Krolikowski, Nicole Romanow, Luz Palacios‐Derflingher, Claude Goulet, Luc Nadeau, Carolyn A. Emery

Bibliographic record

VenueBritish Journal of Sports Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité LavalUniversity of Calgary
Fundersnot available
KeywordsIce hockeyLeaguePoisson regressionTrunkDemographyConcussionPsychologyPhysical therapyMedicinePhysical medicine and rehabilitationPoison controlInjury preventionPopulationMedical emergencyEnvironmental healthPhysics

Abstract

fetched live from OpenAlex

Background A 2015, Hockey Calgary body checking (BC) policy change disallowed BC from non-elite Bantam (ages 13–14, lower 60% of divisions). This was informed by evidence that disallowing BC in Pee Wee (ages 11–12) reduced the risk of injury, specifically concussion, by >3-fold. Objective To compare the frequency of type and intensity of player-to-player contacts (PC) and head contact in non-elite Bantam ice hockey games in leagues allowing BC (2014–15) compared with leagues disallowing BC (2015–16). Design Cohort study. Setting Ice-hockey arenas in Calgary, Canada. Participants Non-elite Bantam players in 2014–15 (n=348 players) and 2015–16 (n=309 players) seasons. Interventions In the 2014–15 season, non-elite Bantam leagues allowed BC. In 2015–2016, BC was disallowed. Main Outcome Measurements Thirteen games pre-policy change (2014–2015) and 13 post-policy change were video recorded. Analysis using validated methodology was used to compare the frequency, type (i.e., trunk, head and other types of PC with limb/head/stick), and intensity (trunk contacts level 1–5 with increasing intensity) of PCs. Incidence rate ratios (IRR) were estimated using Poisson regression (controlling for cluster by team, offset by player minutes). Results There were a total of 3485 trunk contacts and 1395 other contacts in 26 games. The overall risk of trunk PCs was lower post-policy change (IRR=0.50, 95% CI; 0.45–0.56). Post-policy change, high intensity (body checking - level 4,5) contacts decreased (IRR4=0.19, 95% CI; 0.13–0.26 IRR5=0.11, 95% CI; 0.03–0.51), lower intensity (level 2,3) PCs were less frequent (IRR2=0.45, 95% CI; 0.40–0.50 and IRR3=0.47, 95% CI; 0.35–0.63), and other contacts made with the limb/stick also decreased (IRR=0.60, 95% CI; 0.48–0.73). Head contact decreased (IRR=0.40, 95% CI; 0.25–0.61). Conclusions Post-policy change disallowing BC in non-elite Bantam, incidence of high intensity (level 4,5) PCs decreased 82%. Head contact decreased 60% and stick/limbs contact decreased 40%. These findings inform the mechanisms of injury explaining concussion risk reduction post-BC policy change.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.137
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.336
Teacher spread0.293 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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