Psychological Health and Physical Activity Levels during the COVID-19 Pandemic: A Systematic Review
Bibliographic record
Abstract
The coronavirus disease (COVID-19) pandemic has been devastating in all senses, particularly psychologically. Physical activity (PA) is known to aid psychological well-being, and it is worth investigating whether PA has been a coping strategy during this pandemic. The objective of this literature review is to analyze the extent to which engaging in PA during the COVID-19 pandemic impacts psychological health in the adult population. The literature was searched in all databases from the EBSCOhost Research Database-MEDLINE, APA PsycArticles, between others-published between 1 January 2019 and 15 July 2020. From 180 articles found, 15 were eligible. The reviewed articles showed an association between mental health distress-e.g., stress, anxiety, depressive symptoms, social isolation, psychological distress-and PA. This research concludes that the COVID-19 pandemic and the lockdown measures caused psychological distress. Those studies that analyzed PA showed that, during quarantine, adults increased their sedentary time and reduced their PA levels, showing controversial psychological outcomes. This review discusses whether PA is an effective strategy to face the COVID-19 pandemic psychological effects contributing to a further putative increase in the prevalence of psychiatric disorders.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".