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Enregistrement W4239255676 · doi:10.1097/00005768-200205001-01739

Pre-Competition Habits and Injuries in Taekwondo Athletes

2002· article· en· W4239255676 sur OpenAlexaffabout
Mohsen Kazemi, Young Soo Choung

Notice bibliographique

RevueMedicine & Science in Sports & Exercise · 2002
Typearticle
Langueen
DomaineMedicine
ThématiqueSports injuries and prevention
Établissements canadiensCanadian Memorial Chiropractic College
Organismes subventionnairesnon disponible
Mots-clésAthletesMedicinePhysical therapyDietingWeight lossObesity

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,023
Score d'incertitude au seuil0,046

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,273
Écart entre enseignants0,261 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations18
Publié2002
Routes d'admission2
Résumé présentoui

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