Health Problems of Professional Ballet Dancers: an Analysis of 1627 Weekly Self-Reports on Injuries, Illnesses and Mental Health Problems During One Season
Notice bibliographique
Résumé
BACKGROUND: Several studies have investigated injuries of (pre-)professional ballet dancers, however most used a medical-attention and/or time-loss definition and did not analyse the prevalence of all health problems. The aim was to analyse the frequency and characteristics of all self-reported physical and mental health complaints (i.e. injuries, illnesses and mental health problems) of professional ballet dancers during one season. METHODS: Three professional ballet companies were prospectively monitored weekly during one season with the Performing artist and Athlete Health Monitor (PAHM). Numerical rating scales (ranging 0-10) were used for severity of musculoskeletal pain, all health problems and impairment of the ability to dance at full potential in the previous seven days. If dancers rated the severity of their health problems or their impairment greater than 0, they were asked to answer specific questions on the characteristics of each health problem. RESULTS: Over a period of 44 weeks, 57 dancers (57.9% female) filled in 1627 weekly reports (response rate of 64.9%), in which 1020 (62.7%) health problem were registered. The dancers reported musculoskeletal pain in 82.2% of the weeks. They felt that their ability to dance at their full potential was affected due to a health problem in about every second week (52.6%) or on at least 29.1% of the days documented in the weekly reports. Almost all dancers (96.5%) reported at least one injury, almost two thirds (64.9%) an illness and more than a quarter (28.1%) a mental health problem. On average, every dancer reported 5.6 health problems during the season. Most of the 320 health problems were injuries (73.1%), 16.9% illnesses and 10.0% mental health problems. Injuries affected mainly ankle, thigh, foot, and lower back and were mostly incurred during rehearsal (41.6%) or training (26.1%). The most frequent subjective reasons of injury were "too much workload" (35.3%), "tiredness/exhaustion" (n = 22.4%) and "stress/overload/insufficient regeneration" (n = 21.6%). CONCLUSION: Preventive interventions are urgently required to reduce the prevalence of health problems and especially injuries of professional dancers. Injury prevention measures should regard the balance of the load capacity of professional dancers and the workload in training, rehearsals and performances.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».