Relationships between changes in self-reported physical activity, sedentary behaviour and health during the coronavirus (COVID-19) pandemic in France and Switzerland
Bibliographic record
Abstract
To assess whether changes in physical activity and sedentary behaviour during the COVID-19 lockdown are associated with changes in mental and physical health. Observational longitudinal study. Participants living in France or Switzerland responded to online questionnaires measuring physical activity, physical and mental health, anxiety, and depressive symptoms. Paired sample t-tests were used to assess differences in physical activity and sedentary behaviour before and during lockdown. Multiple linear regressions were used to investigate associations between changes in physical activity and changes in mental and physical health during lockdown. 267 (wave1) and 110 participants (wave2; 2 weeks later) were recruited. Lockdown resulted in higher time spent in walking and moderate physical activity (~10min/day) and in sedentary behaviour (~75min/day), compared to pre COVID-19. Increased physical activity during leisure time from week 2 to week 4 of lockdown was associated with improved physical health (β=.24, p=.002). Additionally, an increase in sedentary behaviour during leisure time was associated with poorer physical health (β=−.35, p=.002), mental health (β=−.25, p=.003), and subjective vitality (β=−.30, p=.004). Ensuring sufficient levels of physical activity and reducing sedentary time can play a vital role in helping people to cope with a major stressful event, such as the COVID-19 pandemic.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".