Exploring the Scale-up of a Free Community-Based Physical Activity Intervention to Rural and Smaller Urban Settings in Southwestern Ontario
Bibliographic record
Abstract
The purpose of this dissertation was to examine the physical activity context for children in rural and smaller urban settings and identify strategies for scaling up interventions for lower-density communities by exploring how to appropriately and effectively expand the ACT-i-Pass Program, a community-based intervention for children ages 9-11 years, into the counties of Oxford, Elgin and Middlesex in Southwestern Ontario. This dissertation entailed four interrelated studies, which start with exploring the movement behaviours of the children in the study area via online surveys. Study 1 entailed a longitudinal assessment of children’s physical activity levels pre-pandemic and during COVID-19 public health measures, while Study 2 explored the movement behaviours of children following the COVID-19 protections based on socio-demographic and geographic factors. To assess the communities for the potential scale-up of the ACT-i-Pass Program, Study 3 comprised community forums with service providers (n = 37) and parents (n = 9) to understand their perspectives on, and recommendations for, physical activity programming in rural and smaller urban areas. Study 4 expanded on these findings, with the prevalence of the existing physical activity offerings and their relationship with neighbourhood-level characteristics analyzed via an environmental scan. The findings from the parent-reported surveys highlighted declines in children’s physical activity and shift to screen-based activities during COVID-19 stay-at-home orders, with parents reporting their children continue to exhibit lower physical activity levels than the national guidelines and many detailing excessive screen use. The findings indicated children from areas with limited local amenities and lower urbanicity engaged in less physical activity. The environmental scan revealed numerous recreational facilities (n = 238) and organized programs (n = 212) in smaller communities, demonstrating their capacity to adopt physical activity promotion interventions. Important considerations for future physical activity interventions include the areas with higher proportions of children having fewer physical activity facilities, vehicular transport not alleviating disparities in local recreational opportunities, investment in skill-building programming and non-competitive activities, and commitment to cross-sectoral collaborators during intervention development. In conclusion, the findings from this dissertation provide key insights into scaling up physical activity interventions and recommendations for adapting interventions to rural and smaller urban settings.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".