Mental health and physical activity during the outbreak of COVID-19: Analysis of rapid response research using a systematic review
Bibliographic record
Abstract
The rapid response to the COVID-19 pandemic changed people’s lives abruptly, causing decreased physical activity (PA). This situation led to an array of studies exploring the impact of restrictions on mental health (MH) and the potential benefits of PA. We aimed to evaluate how the rapid research response generated adequate evidence for guiding the response to COVID-19 restrictions, in order to inform evidence-generating responses in future health emergencies. For this, a systematic review was conducted, encompassing 17 articles published during the first six months of the pandemic (March to August 2020), with a predominant focus on MH and its association with PA. A positive association between PA and MH, particularly regarding depression, stress, and well-being, was observed in the literature. However, the variation in outcomes and the influence of contextual factors underscored the need for better methodological consensus in emergency research. A noticeable gap in published research from certain regions highlighted concerns about equitable representation. This disparity could introduce bias, due to a substantial proportion of available research originated from industrialized and developed nations. Importantly, the published research during the first six months predominantly emphasized morbidity in the assessment of MH, though evidence advocates for a more holistic approach. As the world continues to face unforeseen crises, these findings suggest that emergency research must account for context diversity and promote a more comprehensive understanding of MH beyond psychopathological symptoms. This approach is essential for maximizing the impact of research resources in emergency response and ensuring equitable scientific representation.
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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 | 0.023 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.023 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".