Children and youth’s movement behaviours differed across phases and by geographic region throughout the COVID-19 pandemic in Nova Scotia, Canada: an explanatory sequential mixed-methods study
Bibliographic record
Abstract
BACKGROUND: Like many places globally, the health and well-being of children and youth living in Canada were significantly affected by the COVID-19 pandemic. Restricted access to the outdoors, schools, and public green spaces impacted children's physical activity (PA), sedentary behaviour, and sleep. Restrictions changed throughout the pandemic, and children's and youth's movement behaviours may have been differentially affected based on time and place. This paper aimed to examine the impact of the COVID-19 pandemic on the movement behaviours of children and youth living in Nova Scotia (NS), Canada, over time and by geographic region using mixed methods. METHODS: This study employed an explanatory sequential mixed-methods design. Secondary data from three repeated cross-sectional surveys of parent-reported demographic, movement, and geographic data of 291 children and youth aged 5-17 years were analyzed. Spatial cluster analyses were applied to identify geographic concentrations of children and youth who were more or less likely to meet the moderate-vigorous PA (MVPA) guideline during the pandemic. Semi-structured interviews were conducted with 14 Nova Scotian parents to understand their perspectives on their child's movement behaviours during the pandemic. Interviews were analyzed deductively based on quantitative results using reflexive thematic analysis. RESULTS: Our findings showed only 5.5% of children and youth were meeting all guidelines throughout the pandemic. Of the movement behaviours, screen time (ST) differed across the pandemic and by age and gender. Clusters of children and youth meeting the MVPA recommendation on fewer days were found in regions within NS's three largest population centres (Truro, Sydney, and the Halifax Regional Municipality (HRM)), and clusters of those meeting the MVPA recommendation on more days were also identified in the HRM. From semi-structured interviews, themes indicated: (1) escaping screens during early parts of the COVID-19 pandemic and when weather was colder was hard; (2) having access to spaces to be active near the home helped facilitate children's movement; and (3) higher socioeconomic status enabled more opportunities for movement. CONCLUSION: Overall, fewer public health restrictions led to more favourable movement behaviours and spatial and sociodemographic factors may have been at play. Decision-makers should consider these factors when identifying strategies to keep children active during future health crises.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".