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Survey Of Sport Participation, Sport Injury And Sport Safety Practices In Calgary Area High Schools

2005· article· en· W1970843559 on OpenAlexaffabout
Carolyn A. Emery, Willem Meeuwisse

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2005
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBasketballMedicinePhysical therapyInjury preventionFootballPopulationOccupational safety and healthDemographicsPoison controlIncidence (geometry)Medical emergencyDemographyEnvironmental health

Abstract

fetched live from OpenAlex

Sports are the leading cause of injury in adolescents. Injury, incomplete recovery and development of osteoarthritis secondary to injury will have a significant impact on sport participation and future health. Research that will lead to prevention of injuries in adolescents is critical. PURPOSE To conduct a survey in a random sample of high school students to examine: 1) rates of sport participation, 2) sport injury incidence rates, 3) risk factors for sport injury, and 4) current sport safety behaviors. METHODS This was a retrospective survey design. The study population was a random sample of 2873 adolescents from 24 Calgary area high schools. Students completed an anonymous, written, in class questionnaire in March 2004. The questionnaire included: subject demographics, sport participation, injury, and safety practices. RESULTS The rate of compliance in completing the survey was 72%. In the previous one year 94% of students participated in sport. The top 5 sports by participation for boys were basketball, hockey, football, soccer and golf and for girls were basketball, dance, volleyball, snowboarding and soccer. The cumulative incidence rate was 62.2 injuries/100 adolescents/year (95% CI; 60.4 – 64). The injury rate accounting for only those injuries requiring medical attention was 38.1 injuries/100 adolescents/year (95% CI; 36.3 – 39.9). The injury rate including only injuries presenting to a hospital emergency department was 7.6 injuries/100 adolescents/year (95% CI; 6.6 – 8.6). The injury rate based on injuries that resulted in time loss from sport was 47.3 injuries/100 adolescents/year (95% CI; 45.4 – 49.1). The rate of loss of consciousness associated with a sport injury was 8.8 injuries/100 adolescents/year (95% CI; 7.8 – 9.9). The greatest proportion of injuries occurred in basketball, hockey, soccer, snowboarding and football. The greatest sport-specific injury rates were in wrestling, gymnastics, hockey, football and soccer. The top 5 body parts injured were the ankle, knee, head, back and wrist. The most common injury types were sprain, contusion, concussion, fracture, and muscle strain. A previous injury to the same body part was associated with 49% of the injuries. Direct contact was the mechanism of injury reported for 45% of injuries. CONCLUSIONS Rates of participation and sport injury are high in adolescents. Prevention strategies will have the greatest population health impact in sports that have both high participation and injury rates such as basketball, hockey, soccer, snowboarding, and football. Future research should focus on determining, implementing and evaluating injury prevention strategies in adolescent sport.

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)0.002
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 score0.934
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.342
Teacher spread0.315 · 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

Citations2
Published2005
Admission routes2
Has abstractyes

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