Pre-Competition Habits and Injuries in Taekwondo Athletes
Bibliographic record
Abstract
Introduction: No research has been conducted on the way taekwondo athletes prepare themselves prior to competition. The objective of this retrospective survey, therefore, was to assess training characteristics, competition preparation habits and injury profiles of taekwondo athletes. Methods: Subjects for this study were Canadian male and female taekwondo athletes participating in a national tournament. Questionnaires, comprising items on training characteristics, diet, and injuries sustained during training and competition, were handed out to 60 athletes prior to competition. Results: Twenty-eight questionnaires (46.7%) were returned. The mean age, weight and height of the athletes were 22 years, 149 lbs and 68.6 inches, respectively. Most of the respondents (75%) had 6 years or more experience in taekwondo. Fifty-seven percent of the athletes were practicing taekwondo for 8 or more years, 18% for 6–7 years and 21% for 4–5 years. Fifty-four percent of the athletes dieted before competition. Fifty percent of them did not eat but drank, 33% neither ate nor drank and 17% did not drink but ate. Thirty-six percent did aerobic exercises in addition to dieting to make the weight. Thirty-nine percent practiced 5–6 times per week, 25% 4 times, 21% 2–3 times and 14% 7 or more times per week. Fifty-four percent practiced 2 hours per session, 18% 1 hour, 18% 3 hours and 11% 4 or more. Twenty-five percent sparred 1–2 times per week, 53.5% 3–4 times per week and 21% 5 times or more per week. Forty-one percent stretched before and 57% stretched before and after training. Fifty-seven percent of athletes always did warm-up exercises, whereas 43% sometimes warmed up. Sixty-four percent of athletes sometimes, 21% always and 14% never did cool-down exercises. The location of first injuries reported were 46.5% to the lower extremities, 18% upper extremities, 10.8% back, 3.6% head with 21.4% not reporting any injuries. Forty-five percent of these injuries were sprains/strains, 32% contusions, 14% fractures, and 5% concussions. Fifty-nine percent of the first injuries were incurred during training versus 41% during competition. A hundred percent of the third to fifth injuries reported happened during training. Discussion: As expected in a weight-categorized sport, more than half of the competitors dieted to make weight prior to competition. The adverse effects on the taekwondo athlete's health and performance of dehydration techniques to lose weight were highlighted before (Pieter and Taaffe, 1991), especially when practiced over several years as was also suggested for judoka (judo athletes) (Maslen et al., 1993). Not surprisingly, the lower extremities received most of the injuries reported. Sprains and strains were the most common injuries followed by contusions, which was also found in an earlier study on competition injuries in Canadian taekwondo athletes (Kazemi and Pieter, 2000). When considering all the reported injuries, the frequency of injuries was higher during training. However, in the absence of any exposure data, it cannot be concluded that the risk of injury is higher during training (Kazemi and Pieter, 2000). The sample size of this study was small and hence any definitive conclusions would be premature. Further research with more subjects should also consider the relationship between training and competition injuries, and dieting. In addition, the relationship between warm-up and cool-down routines, and injuries should be investigated.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".