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
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".