Insights from neighbourhood walking interviews using the Living Environments and Active Aging Framework (LEAAF) in community-dwelling older adults
Bibliographic record
Abstract
We aimed to understand whether neighbourhood characteristics are associated with movement and social behaviors using walking interviews with 28 community-dwelling older adults (aged 65+). Results indicated support for each component and each relationship in our proposed “Living Environments and Active Aging Framework”. Additional themes such as neighbourhoods with children, moving to neighbourhoods with opportunities for social activity and movement, and lingering effects of pandemic closures provided novel insights into the relationship between the living environment (neighbourhood) and active aging. Future work exploring sex and gender effects on these relationships, and work with equity-deserving groups is needed. • Older adults move to neighborhoods that provide opportunities for active aging. • Social and movement behaviors influence each other, and are impacted by the neighbourhood. • Programs aimed at improving physical activity must include social interactions. • Programs aimed at improving social health can inadvertently influence sedentary time.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".