Examining How Cognition, Neighborhood Characteristics, and Physical Function are Associated with Outdoor Frequency Among United States Community‐Dwelling Medicare Beneficiaries
Bibliographic record
Abstract
Abstract Background A large body of research supports the benefits of older adults engaging in physical activity outdoors. However, a paucity of research explores factors associated with the frequency of older adults going outdoors. The aim of this study was to explore how factors including cognition, neighborhood characteristics, and physical ability were associated with community‐dwelling older adults’ outdoor frequency. Method This cross‐sectional study used National Health and Aging Trends Study data to investigate determinants of outdoor frequency among Medicare beneficiaries aged 65 and older. We descriptively characterized the distribution of outdoor frequency by participant demographic, health, and neighborhood characteristics using counts and percentages, and estimated odds ratios of relationships between key characteristics (including cognitive status, neighborhood characteristics, and physical ability) and outdoor frequency using survey ordinal logistic regression. Result The final sample included 3,368 participants, ages 65 and older (57% female). Most participants went outside every day (60.4%) and few went outside rarely or never (3.5%). Compared to those who went outside daily, individuals who went outside rarely or never were more likely to have probable dementia, live in neighborhoods with street disorder and continuous sidewalks, and have physical limitations requiring assistive devices and help to go outside. Conclusion Older adults with dementia and physical limitations may be less likely to experience the benefits of outdoor activity. Neighborhood characteristics may contribute to going outdoors. More research is needed to understand the experiences of people living with dementia and physical limitations in order to develop interventions and age‐friendly neighborhoods promoting outdoor activity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".