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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 OpenAlex
Shreya McLeod, Ross Tucker, Suzi Edwards, Ben Jones, Georgia Page, Mily Spiegelhalter, Grant L. Iverson, Andrew J. Gardner

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.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.026
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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