The COvid-19 Pandemic and Exercise (COPE) Trial: A multi-group randomized controlled trial comparing effects of an app-based, at-home exercise program to waitlist control on depressive symptoms
Notice bibliographique
Résumé
Abstract Background The number of adults across the globe with significant depressive symptoms has grown substantially during the COVID-19 pandemic. The extant literature supports exercise as a potent behavior that can significantly reduce depressive symptoms in clinical and non-clinical populations. Objective Using a suite of mobile applications, at-home exercise, including high intensity interval training (HIIT) and/or yoga, was completed to reduce depressive symptoms in the general population in the early months of the pandemic. Methods A 6-week, parallel, multi-arm, randomized controlled trial was completed with 4 groups: [1] HIIT, [2] Yoga, [3] HIIT+Yoga, and [4] waitlist control (WLC). Low active, English-speaking, non-retired Canadians aged 18-64 years were included. Depressive symptoms were measured at baseline and weekly following randomization. Results A total of 334 participants were randomized to one of four groups. No differences in depressive symptoms were evident at baseline. The results of latent growth modeling showed significant treatment effects for each active group compared to the WLC, with small effect sizes in the community-based sample of participants. Treatment groups were not significantly different from each other. Effect sizes were very large when restricting analyses only to participants with high depressive symptoms at baseline. Conclusions At-home exercise is a potent behavior to improve mental health in adults during the pandemic, especially in those with increased levels of depressive symptoms. Promotion of at-home exercise may be a global public health target with important personal, social, and economic implications as the world emerges scathed by the pandemic. Trial registration number clinicaltrials.gov # NCT04400279 Summary Box This randomized controlled trial provides strong evidence suggesting that at-home app-based exercise in various forms (high intensity interval training or yoga or their combination) can significantly improve depression symptoms over a 6-week period in community adults during the pandemic. When the sample was restricted to only those with high baseline depression symptoms, the weekly effects were substantially large. At-home exercise during the COVID-19 pandemic proved to be an impactful and affordable health behavior in which community living adults, especially those with high depression symptoms, can engage to bolster their mental health. In light of the long-term mental health consequences of COVID-19 with which many adults are expected to struggle, even after a return to normal, promoting and supporting programming in communities at the individual level will emerge as a necessary health policy initiative.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».