[sans titre]
Notice bibliographique
Résumé
Background The role of trunk muscle training (TMT) for physical ftness (e.g., muscle power) and sport-specifc performance measures (e.g., swimming time) in athletic populations has been extensively examined over the last decades. However, a\nrecent systematic review and meta-analysis on the efects of TMT on measures of physical ftness and sport-specifc performance in young and adult athletes is lacking.\nObjective To aggregate the efects of TMT on measures of physical ftness and sport-specifc performance in young and adult athletes and identify potential subject-related moderator variables (e.g., age, sex, expertise level) and training-related programming parameters (e.g., frequency, study length, session duration, and number of training sessions) for TMT efects.\nData Sources A systematic literature search was conducted with PubMed, Web of Science, and SPORTDiscus, with no date restrictions, up to June 2021.\nStudy Eligibility Criteria Only controlled trials with baseline and follow-up measures were included if they examined the efects of TMT on at least one measure of physical ftness (e.g., maximal muscle strength, change-of-direction speed (CODS)/\nagility, linear sprint speed) and sport-specifc performance (e.g., throwing velocity, swimming time) in young or adult competitive athletes at a regional, national, or international level. The expertise level was classifed as either elite (competing at\nnational and/or international level) or regional (i.e., recreational and sub-elite).\nStudy Appraisal and Synthesis Methods The methodological quality of TMT studies was assessed using the Physiotherapy Evidence Database (PEDro) scale. A random-efects model was used to calculate weighted standardized mean diferences (SMDs) between intervention and active control groups. Additionally, univariate sub-group analyses were independently computed for subject-related moderator variables and training-related programming parameters.\nResults Overall, 31 studies with 693 participants aged 11–37 years were eligible for inclusion. The methodological quality of the included studies was 5 on the PEDro scale. In terms of physical ftness, there were signifcant, small-to-large efects of TMT on maximal muscle strength (SMD =0.39), local muscular endurance (SMD =1.29), lower limb muscle power (SMD=0.30), linear sprint speed (SMD =0.66), and CODS/agility (SMD =0.70). Furthermore, a signifcant and moderate TMT efect was found for sport-specifc performance (SMD=0.64). Univariate sub-group analyses for subject-related moderator variables revealed signifcant efects of age on CODS/agility (p=0.04), with signifcantly large efects for children (SMD=1.53, p=0.002). Further, there was a signifcant efect of number of training sessions on muscle power and linear sprint speed (p≤0.03), with signifcant, small-to-large efects of TMT for>18 sessions compared to≤18 sessions (0.45≤SMD≤0.84, p≤0.003). Additionally, session duration signifcantly modulated TMT efects on linear sprint speed, CODS/agility, and sport-specifc performance (p≤0.05). TMT with session durations≤30 min resulted in signifcant, large efects on linear sprint speed and CODS/agility (1.66≤SMD≤2.42, p≤0.002), whereas session durations>30 min resulted in signifcant, large efects on sport-specifc performance (SMD=1.22, p=0.008).\nConclusions Our fndings indicate that TMT is an efective means to improve selected measures of physical ftness and sportspecifc performance in young and adult athletes. Independent sub-group analyses suggest that TMT has the potential to improve CODS/agility, but only in children. Additionally, more (>18) and/or shorter duration (≤30 min) TMT sessions appear to be more efective for improving lower limb muscle power, linear sprint speed, and CODS/agility in young or adult competitive athletes.
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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».