Little associations exist between the three commonly used functional screening tests in collegiate athletes
Notice bibliographique
Résumé
Although an abundant number of studies have investigated the predictability of the commonly used functional screening tests and despite their popularity and applicability, the relationships between these tests have rarely been studied and have not been well established. This study aimed to examine the potential association between the Functional Movement Screen (FMS), Y Balance Test (YBT), and Landing Error Scoring System (LESS). Six hundred twenty-seven Iranian collegiate athletes (347 males, age = 22.63 ± 4.07, weight = 75.98 ± 13.79, height = 181.99 ± 10.15, BMI = 22.84 ± 3.16; and 280 females, age = 22.22 ± 3.37, weight = 60.63 ± 9.58, height = 166.55 ± 6.49, BMI = 21.81 ± 2.84) participated in this study. Following a 5-min warm-up, each participant underwent a standardized screening battery including the FMS, YBT, and LESS, and the scores were recorded and live coded for the statistical analysis, except for the LESS. The LESS tests were video recorded and scored by one expert examiner using an open-source 2D video analysis software (Kinovea- version 0.9.5), afterwards. The Spearman correlation was utilized as a measure for the correlation, and the Mann‒Whitney U test with a significance level of 0.05 was used to check the differences between male and female athletes. The statistical analysis was performed with RStudio 2023.03.0 using R 4.3.1. A small correlation (0.364) was observed between the FMS composite score and the YBT in male athletes. All other pairwise correlations were negligible among male and female athletes, ranging from - 0.096 to 0.294. Reducing the FMS to the component scores targeting the lower extremities did not alter the correlation to the other screening scores. The median FMS composite score in female athletes was significantly higher than that in males (p < 0.001). Negligible correlations exist between the FMS, LESS, and YBT; they do not measure the same values and therefore are irreplaceable with one another. A combination of these tests as a standardized screening battery may potentially better identify injury-predisposed athletes than the application of each test as a stand-alone screening test. Females outperformed males in the FMS test significantly, so sex must be considered a key variable in the FMS studies. Males had slightly higher LESS scores (median difference = 0.5) than females, but this difference is not clinically meaningful. Future research should continue to explore the relationships between various functional screening tests and identify the most effective combinations for comprehensive assessment in different populations and sports disciplines.
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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 | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 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 ».