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Record W2981618089 · doi:10.1097/corr.0000000000000995

Women Are at Higher Risk for Concussions Due to Ball or Equipment Contact in Soccer and Lacrosse

2019· review· en· W2981618089 on OpenAlexaboutno aff
Daphne I. Ling, Jennifer Cheng, Kristen Santiago, Brittany Ammerman, Bridget Jivanelli, Jo A. Hannafin, Ellen Casey

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2019
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsConcussionMedicineBasketballAthletesPhysical therapyInjury preventionPoison controlRate ratioIncidence (geometry)Psychological interventionSports medicineConfidence intervalInternal medicinePsychiatryEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There is ample evidence to suggest sex- and gender-based differences in the incidence of sports-related concussions. The mechanisms of concussion may vary between male and female athletes and contribute to this observed difference. Understanding the underlying etiology by pooling data from primary studies across different settings and sport types will inform interventions that can reduce concussion rates. QUESTIONS/PURPOSES: Specifically, we asked: (1) In which sports are female athletes less likely to experience concussions from player contact? (2) In which sports are female athletes more likely to experience concussions because of ball or equipment contact? METHODS: PubMed, EMBASE, and Cochrane Library databases were searched to identify articles published from January 2000 to December 2018. Ten studies met the inclusion criteria, which were studies that reported concussion incidence by mechanism for both male and female athletes. Exclusion criteria included non-English studies, conference abstracts, and studies on non-sports related concussions. The sports represented by the 10 studies included ice hockey (n = 4), soccer (n = 5), basketball (n = 4), baseball/softball (n = 4), and lacrosse (n = 5). The rate ratio was calculated as the incidence rate in female athletes/male athletes for each concussion mechanism or activity. Data were pooled using the DerSimonian-Laird random-effects model. Study quality was assessed with the Newcastle-Ottawa Scale. RESULTS: Female athletes were at lower risk of player-contact-induced concussions in lacrosse (pooled rate ratio 0.33 [95% CI 0.25 to 0.43]; p < 0.001), basketball (pooled rate ratio 0.86 [95% CI 0.76 to 0.97]; p = 0.01), ice hockey (pooled rate ratio 0.64 [95% CI 0.56 to 0.73]; p < 0.001), soccer (pooled rate ratio 0.70 [95% CI 0.66 to 0.75]; p < 0.001), and soccer heading (pooled rate ratio 0.80 [95% CI 0.72 to 0.90]; p < 0.001); in these sports, men were at higher risk of concussions from player contact. Female athletes were more likely to experience concussions because of ball or equipment contact in lacrosse (pooled rate ratio 3.24 [95% CI 2.10 to 4.99]; p < 0.001), soccer (pooled rate ratio 2.04 [95% CI 1.67 to 2.49]; p < 0.001), and soccer heading (pooled rate ratio 2.63 [95% CI 1.84 to 3.77]; p < 0.001). CONCLUSIONS: The mechanism or activity underlying concussions differs between male and female athletes across different sports. This finding remains the same regardless of whether there are rule differences between the men's and women's games. The implementation of other interventions are required to further ensure player safety, including protective head equipment, concussion prevention training, or rules limiting player contact in the men's game. LEVEL OF EVIDENCE: Level III, retrospective study.

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)0.005
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.462
GPT teacher head0.561
Teacher spread0.100 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations31
Published2019
Admission routes1
Has abstractyes

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