Environmental Factors Associated With Social Participation of Older Adults Living in Metropolitan, Urban, and Rural Areas: The NuAge Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: We compared the social participation of older adults living in metropolitan, urban, and rural areas, and identified associated environmental factors. METHODS: From 2004 to 2006, we conducted a cross-sectional study using an age-, gender-, and area-stratified random sample of 1198 adults (aged 67-82 years). We collected data via interviewer-administered questionnaires and derived from Canadian censuses. RESULTS: Social participation did not differ across living areas (P = .09), but after controlling for potential confounding variables, we identified associated area-specific environmental variables. In metropolitan areas, higher social participation was associated with greater proximity to neighborhood resources, having a driver's license, transit use, and better quality social network (R(2) = 0.18). In urban areas, higher social participation was associated with greater proximity to neighborhood resources and having a driver's license (R(2) = 0.11). Finally, in rural areas, higher social participation was associated with greater accessibility to key resources, having a driver's license, children living in the neighborhood, and more years lived in the current dwelling (R(2) = 0.18). CONCLUSIONS: To enhance social participation of older adults, public health interventions need to address different environmental factors according to living areas.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it