Injury Profile in Youth Female Athletes: A Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
BACKGROUND: An increasing number of epidemiological studies assessing the incidence, prevalence and severity of injury in youth female sport are available. However, no study has sought to synthesise the current evidence base across all youth female sport. As such, a systematic review and meta-analysis of injury in this cohort is necessary to understand the diversity of injury and its associated burden between sports in addition to identifying the density of research available. OBJECTIVE: To conduct a systematic review and meta-analysis of epidemiological data of injuries in youth female athletes with particular attention to injury incidence, mean days lost and injury burden. METHODS: Searches were performed in PubMed, EBSCO (SPORTDiscus with Full Text MEDLINE, APA PsycINFO, CINAHL, Academic Search Complete) and Cochrane databases. Studies were considered if they reported time-loss injury incidence or prevalence in youth female (≤ 19 years old) athletes. Study quality and risk of bias were assessed using STROBE-SIIS extension, Newcastle-Ottawa Scale, and funnel plots, respectively. Injury incidence and burden rate data were modelled using a mixed-effect Poisson regression model. Days lost data were modelled using a generalised linear mixed model. RESULTS: Thirty-two studies were included. The overall incidence rate, mean days lost per injury, and burden rate were 4.4 injuries per 1000 h (95% CI 3.3-5.9), 10 days (95% CI 6-15), and 46 days per 1000 h (95% CI 23-92), respectively. Forty percent of athletes sustained at least one time-loss injury. Competitive level was a significant moderator of match and training injury incidence, with elite youth athletes presenting greater pooled injury incidence estimates than non-elite athletes (p = 0.0315 and p = 0.0047, respectively). The influence of moderators on days lost and injury burden could not be determined due to an insufficient number of studies for analysis. CONCLUSION: Despite a broad inclusion criterion, there is limited injury surveillance research available across youth female sport. Outside of soccer, little research density is evidenced with single studies available in popular team sports such as Australian football and rugby union. Insufficient study numbers reporting mean days lost and injury burden data were available for analysis, and pooled days lost data could only be estimated for soccer. This highlights a need for future research to report days lost data alongside injury number and exposure so burden can be calculated and the full risk of injury to youth female athletes can be identified.
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 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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,018 | 0,003 |
| Bibliométrie | 0,001 | 0,003 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».