Injuries in Synchronized Skating
Bibliographic record
Abstract
Synchronized skating is a relatively new competitive sport and data about injuries in this discipline are lacking. Therefore the purpose of this study was to investigate the frequency and pattern of acute and overuse injuries in synchronized skaters. Before and during the World Synchronized Skating Championship 2004, a questionnaire inquiring about the frequency of injuries in this skating discipline was given to 23 participating teams. A total of 514 women and 14 men senior skaters completed the questionnaires (100 % response). Two hundred and eighteen (42.4 %) female and 6 (42.9 %) male skaters had suffered from acute injuries during their synchronized skating career. As some skaters had suffered from more than one injury, the total number of acute injuries in females was 398 and in males 14. In female skaters 19.8 % of acute injuries were head injuries, 7.1 % trunk, 33.2 % upper, and 39.9 % lower extremity injuries. In male skaters 14.3 % were head injuries, 28.6 % upper, and 57.1 % lower extremity injuries, with no report of trunk injuries. Sixty-nine female and 2 male skaters had low back problems and 112 female and 2 male skaters had one or more overuse syndromes during their skating career. Of 155 overuse injuries in female skaters, 102 (65.8 %) occurred during their figure skating career, while 53 injuries (34.2 %) only occurred when they skated in synchronized skating teams. In male skaters, out of 5 overuse injuries, 4 (80 %) occurred in their figure skating career, while 1 (20 %) occurred during their synchronized skating career. Out of the total of 412 injuries, 338 (82 %) occurred during on-ice practice, while 74 (18 %) happened during off-ice training. Ninety-one (26.9 %) acute injures occurred while practicing individual elements, and 247 (73.1 %) on-ice injuries occurred while practicing different team elements. We conclude that injuries in synchronized skating should be of medical concern due to an increasing number of acute injuries, especially those that go beyond the soft tissue and include head injuries and fractures. We feel that these more significant injuries MAY TO SOME EXTENT BE attributable to the increasing physical demands and technical difficulty required of the teams now participating in a more competitive environment over the last four years.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".