STICK ITT - Study to Increase Current Knowledge of Injuries in Trampoline and Tumbling
Bibliographic record
Abstract
Objectives: To examine incidence rates, severity, characteristics, mechanism and potential risk factors for injury in competitive Trampoline and Tumbling (T&T) athletes ages 8 to 25 years. Methods: Competitive T&T athletes were recruited from across Canada to complete an online questionnaire (e.g., demographics, one-year injury history, injury type and location). Injury was defined as an injury that kept the athlete from T&T training and/or competing for more than one day and/or required medical attention. Univariate Poisson regression analyses were used to estimate incidence rates (IR) and incidence rate ratios (IRR), controlling for cluster by club and offset by exposure hour. Differences in rates were estimated across level of competition (sub-elite/elite), sex (male/female), age (years), T&T experience (years) and exposure (training/competition hours). Descriptive statistics (medians, ranges, proportions, 95% confidence intervals) for athlete demographics and injury characteristics are reported. Results: A total of 132 athletes [89 female; median age=14 (range 10-24 years), 43 males; median age 15 (range 9-24)] from 25 clubs completed the survey with 65% reporting at least one T&T related injury in the previous year. A total of 135 injuries were reported (IR 2.01/1000 exposure hours 95%CI 1.69-2.39). The median time-loss was 30 days (range 0-482) and 125/135 (92.5%) of the injured athletes sought medical attention. The injury rate for elite athletes was 115 injuries/100 athletes/year (95% CI 89.4-143.1) and 92 injuries/100 athletes (95%CI 70.8-116.6) for sub-elite. The most common injury locations were the ankle [28% (24/135)] and head/face [18% (24/135)]. Ligament sprains [22% (30/135)] and concussion [17% (23/135)] were the most common injury type. Females reported significantly higher rate of injury than males [IRR 1.49 (95%CI 1.12-1.92)]. Conclusion: This study examined injury incidence in terms of exposure and found females were at greater rate of injury over their male counterparts. Athletes experience ankle, head (concussion) and overuse type injuries as they engage in competitive T&T. Additional prospective research is needed to inform the development of effective injury prevention strategies among these high-risk young athletes.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".