2.18 Preseason cervical, vestibulo-ocular, and oculomotor measures in youth sport participants: sex does matter
Bibliographic record
Abstract
Objective Examine preseason performance of cervical, vestibulo-ocular, and oculomotor measures by sex and concussion history in youth sport participants Design Cross-sectional Setting Youth sport settings (Calgary, Canada) Participants 948 youth [579(61%) male; 363(38%) females; 6(0.6%) undisclosed;11–19 years-old] Interventions (or Assessment of Risk Factors) Sex and concussion history using test-of-proportions or Mann-Whitney-u-test. Outcome Measures Cervical (range of motion[ROM], flexor-endurance[CFE], flexion-rotation test, head-perturbation[HPT]), Vestibulo-ocular (Head thrust, dynamic visual acuity), Oculomotor (symptom provocation/performance on smooth pursuit[SP], horizontal-saccades[HS], vertical-saccades[VS] and convergence[CV]) Main Results Females had a poorer CFE (20.67,IQR=15.00–28.15) and HPT (8,IQR=6–8) than males (CFE=27.82,IQR=20.67–36.12; p<0.001; HPT=8,IQR=7–8; p<0.001), while males performed poorer on ROM (F=0.28,%CI:0.23–0.33; M=0.46,95%CI=0.42–0.51; p<0.001). Females with a previous concussion had poorer CFE (19.03,IQR=12.42–26.79) than females without a previous concussion (20.75,IQR=15.67–28.51; p=0.036). Females had higher proportions of symptom provocation than males for oculomotor measures and a higher proportion of abnormal performance was also observed in females for SP (F=0.21,95%CI=0.17–0.26; M=0.15,95%CI=0.12–0.18; p=0.023). Males had a higher proportion of abnormal performance with HS (F=0.11,95%CI=0.07–0.14; M=0.14,95%CI=0.14–0.21; p=0.011). Only females demonstrated differences by previous concussion history with a greater proportion demonstrating abnormal outcomes on HSSymptoms, VSsymptoms, VSPerformance, and CVSymptoms (range;p<0.001-p=0.0084). There were no differences by sex for vestibular measures. Conclusions Females had poorer performance and more abnormal tests than males. Females with a previous history of concussion performed poorer on CFE and had increased symptom provocation on oculomotor measures. Multivariable modeling will support consideration of other covariables (e.g., age, number of previous concussions, sport-type).
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".