Use of local area facilities for involvement in physical activity in Canada: insights for developing environmental and policy interventions
Bibliographic record
Abstract
Despite growing literature showing associations of availability and accessibility of facilities to greater levels of physical activity, considerably less is known about the actual extent of use of these facilities. The purpose of this study was to examine the individual (sex, age, education and extent of involvement in vigorous physical activity) and local area characteristics (socioeconomic status, locations and number of physical activity organizations per 1000 residents) associated with the use of local facilities for involvement in physical activity. A telephone survey was conducted with 3191 randomly selected adults in 22 non-contiguous areas across Canada. Use of local facilities for involvement in physical activity was examined among a subset of 1006 physically active adults. Data were analyzed using multilevel modeling. Findings revealed significant variation across areas in likelihood of use of local facilities among women but not men. Women in the 25-34 and 45-55 age categories were significantly more likely to use local facilities than women of 35-44 years of age. Women reporting greater levels of involvement in vigorous physical activity were more likely to use local area facilities. Higher area affluence and living in areas located in small urban towns were associated with greater use of local facilities among women only. None of the individual and local area characteristics was associated with the outcome among men. Understanding the processes associated with differential use of local area facilities for physical activity is essential for the implementation of effective environmental and policy interventions to increase physical activity in the population.
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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 | 0.000 |
| 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 | 0.000 | 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".