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Record W4380285878 · doi:10.3389/fspor.2023.1080356

A case-control study of tackle based head impact event (HIE) risk factors from the first three seasons of the National Rugby League Women's competition

2023· article· en· W4380285878 on OpenAlexaff
Shreya McLeod, Ross Tucker, Suzi Edwards, Ben Jones, Georgia Page, Mily Spiegelhalter, Grant L. Iverson, Andrew J. Gardner

Bibliographic record

VenueFrontiers in Sports and Active Living · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLeagueConcussionMedicineDemographyFootballEnvironmental healthPoison controlPolitical scienceInjury preventionLawSociology

Abstract

fetched live from OpenAlex

Objective: The tackle is the most injurious event in rugby league and carries the greatest risk of concussion. This study aims to replicate previous research conducted in professional men's rugby league by examining the association between selected tackle characteristics and head impact events (HIEs) in women's professional rugby league. Methods: We reviewed and coded 83 tackles resulting in an HIE and every tackle (6,318 tackles) that did not result in an HIE for three seasons (2018-2020) of the National Rugby League Women's (NRLW) competition. Tackle height, body position of the tackler and ball carrier, as well as the location of head contact with the other player's body were evaluated. Propensity of each situation that caused an HIE was calculated as HIEs per 1,000 tackles. Results: The propensity for tacklers to sustain an HIE was 6.60 per 1,000 tackles (95% CI: 4.87-8.92), similar to that of the ball carrier (6.13 per 1,000 tackles, 95% CI: 4.48-8.38). The greatest risk of an HIE to either the tackler or ball carrier occurred when head proximity was above the sternum (21.66 per 1,000 tackles, 95% CI: 16.55-28.35). HIEs were most common following impacts between two heads (287.23 HIEs per 1,000 tackles, 95% CI: 196.98-418.84). The lowest propensity for both tackler (2.65 per 1,000 tackles, 95% CI: 0.85-8.20) and ball carrier HIEs (1.77 per 1,000 tackles, 95% CI: 0.44-7.06) occurred when the head was in proximity to the opponent's shoulder and arm. No body position (upright, bent or unbalanced/off feet) was associated with an increased propensity of HIE to either tackler or ball carrier. Conclusions: In the NRLW competition, tacklers and ball carriers have a similar risk of sustaining an HIE during a tackle, differing from men's NRL players, where tacklers have a higher risk of HIEs. Further studies involving larger samples need to validate these findings. However, our results indicate that injury prevention initiatives in women's rugby league should focus on how the ball carrier engages in contact during the tackle as well as how the tackler executes the tackle.

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)0.004
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.303
Teacher spread0.273 · 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

Citations24
Published2023
Admission routes1
Has abstractyes

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