Gender-Specific Differences in School Sports Injuries
Bibliographic record
Abstract
OBJECTIVE: About 5 % of the pupils suffer from an injury in school sports every year. In addition to the kind of injury, the localization and the type of sport, the corresponding reasons for the injuries should be investigated to provide insights for physical education. METHODS: In a prospective study 213 accident cases with 234 injuries during physical education classes were examined. At primary presentation in our clinic, an empirical questionnaire was used to document the grade of class, the exact time point of the injury, the question of guilt, out-of-school sports activity as well as the mechanisms of injuries and the type of sport. Clinicians who worked in our out-patient clinic completed the questionnaire after physical examination documenting diagnosis, therapy and the duration of restriction of sports practice. All patients were followed until returning to physical education at school. The data were statistically analyzed using the chi (2)-test to examine gender-specific differences. RESULTS: Gender-specific differences were seen in the type (p = 0.018) and mechanisms (p = 0.028) of injuries. The most common injuries were sprains (female pupils 36.8 % male pupils 24.5 %], contusions (female pupils 27.4 % male pupils 27.9 %) and fractures (female pupils 14.7 % male pupils 18.6 %). Frequent mechanisms of injuries were errors in basic motion training like running, jumping and catching (female pupils 35.8 % male pupils 28.8 %). No gender-specific differences could be shown for the localization of injuries or for the type of sport. The upper extremity with 55 % was more frequently involved than the lower extremity with 37 %. Playing soccer (21.2 %) and basketball (19.8 %) were the most frequent reasons for sports injuries. The highest prevalence of school sports injuries occurred at the onset of and during puberty. CONCLUSION: For the girls it is necessary to improve the basic motor skills, while the boys need to learn considerate behavior and how to read the game. Basic skill levels in ball games must be improved before practice in competition form is initiated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".