Barriers and facilitators to meeting recommended physical activity levels among new immigrant and refugee children in Saskatchewan, Canada
Bibliographic record
Abstract
Newcomers are often healthy when they arrive in Canada, yet experience health declines shortly thereafter, possibly due to lifestyle changes. As part of the Healthy Immigrant Children study, this mixed-methods study aims to analyze possible predictors of physical activity among 300 newcomer children, and explore their lived experiences using a sub-sample of 19 parents and 24 service providers. Data collection involved questionnaires concerning socioeconomic status and physical activity, anthropometric measurements, and in-depth interviews. Participants aged 5 years and older largely met physical activity recommendations (82.9%), while none of the 3–4-year-olds did. Males were more active than females, especially among older ages. Many participants engaged in too much screen time (53.4–90.0%). Age and income predicted physical activity among males, while parents’ education level was the only significant predictor among females. Barriers to physical activity included: recreational physical activity being an unfamiliar concept, gender limitations, financial resources, safety concerns, and children’s preference for screen time. Schools played a central role in newcomer children’s health by providing accessible opportunities for physical activity. Newcomer families preferred to have their children involved in culturally relevant physical activities. Given the growing newcomer population, it is important to support active lifestyle practices among them. Novelty: About 83% of newcomer children aged 5 years and older met physical activity recommendations, while none of the 3–4-year-olds did. Age and income predicted males’ physical activity, while parents’ education level predicted females’ physical activity. Schools provide accessible opportunities for newcomer children to engage in physical activity.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".