The Effects of Trunk Muscle Training on Physical Fitness and Sport-Specific Performance in Young and Adult Athletes: A Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
BACKGROUND: The role of trunk muscle training (TMT) for physical fitness (e.g., muscle power) and sport-specific performance measures (e.g., swimming time) in athletic populations has been extensively examined over the last decades. However, a recent systematic review and meta-analysis on the effects of TMT on measures of physical fitness and sport-specific performance in young and adult athletes is lacking. OBJECTIVE: To aggregate the effects of TMT on measures of physical fitness and sport-specific 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 effects. DATA SOURCES: A systematic literature search was conducted with PubMed, Web of Science, and SPORTDiscus, with no date restrictions, up to June 2021. STUDY ELIGIBILITY CRITERIA: Only controlled trials with baseline and follow-up measures were included if they examined the effects of TMT on at least one measure of physical fitness (e.g., maximal muscle strength, change-of-direction speed (CODS)/agility, linear sprint speed) and sport-specific performance (e.g., throwing velocity, swimming time) in young or adult competitive athletes at a regional, national, or international level. The expertise level was classified as either elite (competing at national and/or international level) or regional (i.e., recreational and sub-elite). STUDY APPRAISAL AND SYNTHESIS METHODS: The methodological quality of TMT studies was assessed using the Physiotherapy Evidence Database (PEDro) scale. A random-effects model was used to calculate weighted standardized mean differences (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. RESULTS: 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 fitness, there were significant, small-to-large effects 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 significant and moderate TMT effect was found for sport-specific performance (SMD = 0.64). Univariate sub-group analyses for subject-related moderator variables revealed significant effects of age on CODS/agility (p = 0.04), with significantly large effects for children (SMD = 1.53, p = 0.002). Further, there was a significant effect of number of training sessions on muscle power and linear sprint speed (p ≤ 0.03), with significant, small-to-large effects of TMT for > 18 sessions compared to ≤ 18 sessions (0.45 ≤ SMD ≤ 0.84, p ≤ 0.003). Additionally, session duration significantly modulated TMT effects on linear sprint speed, CODS/agility, and sport-specific performance (p ≤ 0.05). TMT with session durations ≤ 30 min resulted in significant, large effects on linear sprint speed and CODS/agility (1.66 ≤ SMD ≤ 2.42, p ≤ 0.002), whereas session durations > 30 min resulted in significant, large effects on sport-specific performance (SMD = 1.22, p = 0.008). CONCLUSIONS: Our findings indicate that TMT is an effective means to improve selected measures of physical fitness and sport-specific 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 effective for improving lower limb muscle power, linear sprint speed, and CODS/agility in young or adult competitive athletes.
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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 | 0,010 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,017 | 0,023 |
| Bibliométrie | 0,006 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 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 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 ».