Association Between Children’s and Parents’ Physical Activity During the COVID-19 Pandemic: A Cross-Lagged Analysis
Bibliographic record
Abstract
BACKGROUND: COVID-19 caused closures of movement supporting environments such as gyms and schools in Canada. This study evaluated the association between Ontario parents' and children's physical activity levels across time during COVID-19, controlling for variables that were identified as significant predictors of children's and parents' physical activity (e.g., children's age, parents' employment status). METHODS: Parents (n = 243; mean age = 38.8 y) of children aged 12 and under (n = 408; mean age = 6.3 y) living in Ontario, Canada completed 2 online surveys, the first between August and December 2020 and the second between August and December 2021. At baseline, parents were asked to recall prepandemic physical activity levels. To determine the association between parent and child physical activity during COVID-19, a cross-lagged model was estimated to determine the cross-sectional and longitudinal associations between parents' and children's physical activity across time. RESULTS: Bivariate associations revealed that parents' and children's physical activity levels were significantly related during lockdown and postlockdown but not prelockdown. The autoregressive paths from prelockdown to during lockdown were significant for children (β = 0.53, P < .001) and parents (β = 1.058, P < .001) as were the autoregressive paths from during lockdown to postlockdown for children (β = 0.61, P < .001) and parents (β = 0.48, P < .001). In fully adjusted models, the cross-lagged association between parents' physical activity prelockdowns was significantly positively associated with their children's physical activity during lockdowns (β = 0.19, P = .013). CONCLUSIONS: Resources are needed to ensure that children and parents are obtaining sufficient levels of physical activity, particularly during a 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 | 0.004 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".