Built environment interventions aimed at improving physical activity levels in rural Ontario health units: a descriptive qualitative study
Bibliographic record
Abstract
BACKGROUND: Few studies to date have explored the relationship between the built environment and physical activity specifically in rural settings. The Ontario Public Health Standards policies mandate that health units in Ontario address the built environment; however, it is unclear how public health practitioners are integrating the built environment into public health interventions aimed at improving physical activity in chronic disease prevention programs. METHODS: This descriptive qualitative study explored interventions that have or are being implemented which address the built environment specifically related to physical activity in rural Ontario health units, and the impact of these interventions. Data were collected through twelve in-depth semi-structured interviews with rural public health practitioners and managers representing 12 of 13 health units serving rural communities. Key themes were identified using qualitative content analysis. RESULTS: Themes that emerged regarding the types of interventions that health units are employing included: Engagement with policy work at a municipal level; building and working with community partners, committees and coalitions; gathering and providing evidence; developing and implementing programs; and social marketing and awareness raising. Evaluation of interventions to date has been limited. CONCLUSIONS: Public health interventions, and their evaluations, are complex. Health units who serve large rural populations in Ontario are engaging in numerous activities to address physical activity levels. There is a need to further evaluate the impact of these interventions on population health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".