Effects of Passive or Active Recovery Regimes Applied During Long-Term Interval Training on Physical Fitness in Healthy Trained and Untrained Individuals: A Systematic Review
Notice bibliographique
Résumé
Abstract Background Intermittent exercise programs characterized through intensive exercise bouts alternated with passive or active recovery (i.e., interval training), have been proven to enhance measures of cardiorespiratory fitness. However, it is unresolved which recovery type (active or passive) applied during interval training results in larger performance improvements. Objectives This systematic review aimed to summarize recent evidence on the effects of passive or active recovery following long-term interval exercise training on measures of physical fitness and physiological adaptations in healthy trained and untrained individuals. The study protocol was registered in the Open Science Framework (OSF) platform ( https://doi.org/10.17605/OSF.IO/9BUEY ). Methods We searched nine databases including the grey literature (Academic Search Elite, CINAHL, ERIC, Open Access Theses and Dissertations, Open Dissertations, PsycINFO, PubMed/MEDLINE, Scopus, and SPORTDiscus) from inception until February 2023. Key terms as high-intensity interval training, recovery mode, passive or active recover were used. A systematic review rather than a meta-analysis was performed, as a large number of outcome parameters would have produced substantial heterogeneity. Results After screening titles, abstracts, and full texts, 24 studies were eligible for inclusion in our final analysis. Thirteen studies examined the effects of interval training interspersed with passive recovery regimes on physical fitness and physiological responses in trained (6 studies) and untrained (7 studies) individuals. Eleven out of 13 studies reported significant improvements in physical fitness (e.g., maximal aerobic velocity (MAV), Yo-Yo running test, jump performance) and physiological parameters (e.g., maximal oxygen uptake [VO2max], lactate threshold, blood pressure) in trained (effect sizes from single studies: 0.13 < Cohen’s d < 3.27, small to very large) and untrained individuals (effect sizes: 0.17 < d < 4.19, small to very large) despite the type of interval training or exercise dosage (frequency, intensity, time, type). Two studies were identified that examined the effects of passive recovery applied during interval training in young female basketball (15.1 ± 1.1 years) and male soccer players (14.2 ± 0.5 years). Both studies showed positive effects of passive recovery on VO2max, countermovement jump performance, and the Yo-Yo running test. Eleven studies examined the effects of interval training interspersed with active recovery methods on physical fitness and physiological parameters in trained (6 studies) and untrained individuals (5 studies). Despite the type of interval training or exercise dosage, nine out of eleven studies reported significant increases in measures of physical fitness (e.g., MAV) and physiological parameters (e.g., VO2max, blood pressures) in trained (effect sizes from single studies: 0.13 < d < 1.29, small to very large) and untrained individuals (effect sizes: 0.19 < d < 3.29, small to very large). There was no study available that examined the effects of active recovery on physical fitness and physiological responses in youth. Conclusions The results of this systematic review show that interval training interspersed with active or passive recovery regimes have the potential to improve measures of physical fitness and physiology outcomes in trained and untrained adults and trained youth. That is, the applied recovery type seems not to affect the outcomes. Nonetheless, more research is needed on the effects of recovery type on measures of physical fitness and physiological adaptations in youth.
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 | 0,007 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,009 | 0,010 |
| Bibliométrie | 0,005 | 0,006 |
| 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 ».