Impact Of Workload On Female Ice Hockey Player Complaints, Time-loss, And Perceived Performance
Notice bibliographique
Résumé
Associations between athlete load and injury risk have been investigated in field-based sports, with variability depending on specific measures used to assess exposure. However, work examining this relationship in ice hockey is currently limited, especially in female players. PURPOSE: To assess the association between female ice hockey player external and internal loads and the odds of self-reported complaints of injury and pain, time-loss from sport, and perceived effect on performance. METHODS: Twenty-three female university ice hockey players’ (19.9 ± 1.4 y, 68.2 ± 7.3 kg, 167.7 ± 5.6 cm) external (time-on-ice (TOI), skating distance, time spent skating in speed zones, and number of skating events measured via local positioning system) and internal (training impulse (TRIMP) and sessional rate of perceived exertion (sRPE)) loads were measured for an entire season, which were separated into low, low-medium, medium-high, and high load quartiles for analyses. Players’ self-reported injuries and pain, time-loss from sport, and perceived effect on performance prior to each practice and game. Using binomial logistic regression, crude odds ratios (OR) were calculated to assess weekly cumulative load measures and the odds of the various outcomes during that week. RESULTS: Players reported a total of 57 injury or pain complaints over the season. There were significant increases in the odds of a complaint within the low-medium (OR = 2.16, p = 0.049), medium-high (OR = 2.39, p = 0.03), and high (OR = 2.16, p < 0.05) load groups for TOI, and the high load group (OR = 2.22, p = 0.04) for TRIMP compared to the low load group. Interestingly, high load groups for TOI (OR = 0.18, p = 0.03), sRPE (OR = 0.22, p = 0.02), skating distance (OR = 0.16, p = 0.02), time spent in very low to high skating speed zones (OR = 0.16-0.30, p < 0.05), number of decelerations (OR = 0.31, p < 0.05) and skating transitions (OR = 0.09, p = 0.02) had a significant protective effect against time-loss from sport compared to the low load group. Apart from TRIMP (OR = 2.35, p = 0.03), high loads did not increase the odds of players reporting a perceived effect on their performance. CONCLUSION: Female ice hockey players who had high loads in various measures had greater odds of reporting complaints. However, these findings do not translate to time-loss or perceived effect on performance. PepsiCo and Mitacs
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».