Telework and 24-hour movement behaviours among adults living in Canada during the COVID-19 pandemic
Bibliographic record
Abstract
OBJECTIVE: To assess the association between work location and movement behaviours (physical activity [PA], screen time, sleep) and adherence to the Canadian 24-Hour Movement Guidelines (24-H Guidelines) among Canadian workers during the COVID-19 pandemic. METHODS: Using cross-sectional data from the 2021 Canadian Community Health Survey (n = 10,913 working adults 18-75 years), primary work location was categorized as: worked outside the home at a fixed location (fixed workplace), worked at home (telework), and worked outside the home at no fixed location (non-fixed workplace). Recreational, transportation and occupational/household PA, as well as leisure screen time and sleep duration were self-reported. Logistic regression assessed associations between work location and adherence to movement behaviour recommendations, adjusting for covariates. RESULTS: Compared to a fixed workplace, those teleworking reported more recreational PA (21.1 vs 17.0 min/day, p < 0.0001) and sleep (7.2 vs 7.1 h/night, p = 0.026) and were more likely to meet sleep duration recommendations (adjusted odds ratio [aOR] = 1.28, 95% CI: 1.08-1.51) and the 24-H Guidelines (aOR = 1.25, 95% CI: 1.04-1.51). Compared to fixed workplaces, those at non-fixed workplaces reported more occupational PA (62.7 vs 32.8 min/day, p < 0.0001) and less leisure screen time (2.5 vs 2.7 h/day, p = 0.021), and were more likely to meet the PA recommendation (aOR = 1.46, 95% CI: 1.15-1.85) and the 24-H Guidelines (aOR = 1.38, 95% CI: 1.09-1.75). CONCLUSIONS: Results suggest that adherence to the 24-H Guidelines varies by work location, and work location should be considered when developing strategies to promote healthy movement behaviours. Future studies could explore hybrid work arrangements, and longitudinal study designs.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".