Sport Specialization, Physical Performance and Injury History in Canadian Junior High School Students
Bibliographic record
Abstract
BACKGROUND: Youth sports participation is encouraged for proposed physical and psychological benefits. However early sport specialization and the potentially negative consequences may be a cause for concern. PURPOSE: To describe sport specialization in Canadian youth and investigate associations with previous injury and physical performance. STUDY DESIGN: Cross-sectional study. METHODS: Junior high school students (grades 7-9, ages 11-16) were invited to participate. All participants completed a questionnaire capturing specialization level (low, moderate, high; based on year-round training, exclusion of other sports, and single-sport training) and injury history in the previous 12-months. Additionally, all participants completed physical performance measures including vertical jump (cm), predicted VO2max (mL/kg/min), single-leg balance (secs) and Y-Balance composite score (%). Logistic regression examined the association between school grade, school size, sex and sport specialization (Objective 1) and the association between sport specialization and injury history (Objective 2). Multivariable linear regression analyses (4) assessed associations between sport specialization category and physical performance measures (Objective 3). RESULTS: Two hundred and thirty-eight students participated in the study. Eighteen percent of participants reported high specialization, with no significant associations between sex, grade or school size and specialization category. There was no significant difference in the odds of sustaining previous injury between participants reporting moderate (odds ratio [OR]=1.94, 95% CI 0.86-4.35) or high (OR=2.21, 95% CI 0.43-11.37) compared to low specialization. There were no significant differences in vertical jump height (mean diff [MD] = -0.4 to 2.1cm), predicted VO2max (MD = 2.2 to 3.1mL/kg/min), single leg balance (MD = 0.5 to 1.9sec) or Y-balance (MD = 0.6 to 7.0%) between sport specialization categories. CONCLUSIONS: Sport specialization exists in Canadian junior high schools but may be less common than previously reported and it was not associated with sex, grade, or school size. Level of specialization was not associated with history of injury nor a range of physical performance measures. LEVEL OF EVIDENCE: Level 3.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".