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Survey of Sport Participation and Sport Injury in Calgary and Area High Schools

2005· article· en· W2084462554 on OpenAlex
Carolyn A. Emery, Willem Meeuwisse, Jenelle McAllister

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueClinical Journal of Sport Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBasketballMedicinePhysical therapyInjury preventionConcussionFootballPoison controlEmergency departmentOccupational safety and healthMedical emergencyNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine (1) sport participation and (2) sport injury in adolescents. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective survey design. In total, 2873 adolescents were recruited from a random sample of classes from 24 Calgary and area high schools. Each subject completed an in-class questionnaire in March 2004. MAIN OUTCOME MEASUREMENTS: Overall and sport-specific participation rates (number of sport participants/number of students completing survey). Overall and sport-specific injury rates (number of injuries/number of participants). RESULTS: In the previous 1 year, 94% of students participated in sport. The top 5 sports by participation for males were basketball, hockey, football, snowboarding, and soccer, and for females, basketball, dance, volleyball, snowboarding, and soccer. The injury rate including only injuries requiring medical attention was 40.2 injuries/100 adolescents/y (95% CI, 38.4-42.1), presenting to a hospital emergency department was 8.1 injuries/100 adolescents/y (95% CI, 7.1-9.2), resulting in time loss from sport was 49.9 injuries/100 adolescents/y (95% CI, 48-51.8), and resulting in loss of consciousness was 9.3 injuries/100 adolescents/y (95% CI, 8.3-10.5). The greatest proportion of injuries occurred in basketball, hockey, soccer, and snowboarding. The top 5 body parts injured were the ankle, knee, head, back, and wrist. The top 5 injury types were sprain, contusion, concussion, fracture, and muscle strain. A previous injury was associated with 49% of the injuries and direct contact with 45% of injuries. CONCLUSIONS: Rates of participation in sport and sport injury are high in adolescents. Future research should focus on prevention strategies in sports with high participation and injury rates to maximize population health impact.

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)0.011
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 score0.025
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.092
GPT teacher head0.441
Teacher spread0.349 · 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