Changes in physical activity and sedentary behaviours from before to during the COVID-19 pandemic lockdown: a systematic review
Bibliographic record
Abstract
OBJECTIVE: In March 2020, several countries banned unnecessary outdoor activities during COVID-19, commonly called 'lockdowns. These lockdowns have the potential to impact associated levels of physical activity and sedentary behaviour. Given the numerous health outcomes associated with physical activity and sedentary behaviour, the aim of this review was to summarise literature that investigated differences in physical activity and sedentary behaviour before vs during the COVID-19 lockdown. DESIGN DATA SOURCES AND ELIGIBILITY CRITERIA: Electronic databases were searched from November 2019 to October 2020 using terms and synonyms relating to physical activity, sedentary behaviour and COVID-19. The coprimary outcomes were changes in physical activity and/or sedentary behaviour captured via device-based measures or self-report tools. Risk of bias was measured using the Newcastle-Ottawa Scale. RESULTS: Sixty six articles met the inclusion criteria and were included in the review (total n=86 981). Changes in physical activity were reported in 64 studies, with the majority of studies reporting decreases in physical activity and increases in sedentary behaviours during their respective lockdowns across several populations, including children and patients with a variety of medical conditions. CONCLUSION: Given the numerous physical and mental benefits of increased physical activity and decreased sedentary behaviour, public health strategies should include the creation and implementation of interventions that promote safe physical activity and reduce sedentary behaviour should other lockdowns occur.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".