Environmental Demands Associated With Community Mobility in Older Adults With and Without Mobility Disabilities
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In this study, the influence of 8 dimensions of the physical environment on mobility in older adults with and without mobility disability was measured. This was done in order to identify environmental factors that contribute to mobility disability. SUBJECTS: Subjects were 36 older adults ((> or = 70 years of age) who were recruited from 2 geographic sites (Seattle, Wash, and Waterloo, Ontario, Canada) and were grouped according to level of mobility function (physically able [ability to walk 1/2 mile (0.8 km) or climb stairs without assistance], physically disabled). METHODS: Subjects were observed and videotaped during 3 trips into the community (trip to grocery store, physician visit, recreational trip). Frequency of encounters with environmental features within each of the 8 dimensions was recorded. Differences in baseline characteristics and environmental encounters were analyzed using an analysis of variance or the Fisher exact test, as appropriate. RESULTS: Mobility disability among older adults was not associated with a uniform decrease in encounters with environmental challenges across all dimensions. Environmental dimensions that differed between subjects who were physically able and those with physical disability included temporal factors, physical load, terrain, and postural transition. Dimensions that were not different included distance, density, ambient conditions (eg, light levels and weather conditions), and attentional demands. DISCUSSION AND CONCLUSION: Understanding the relationship of the environment to mobility is crucial to both prevention and rehabilitation of mobility disability in older adults. Among older adults, certain dimensions of the environment may disable community mobility more than others.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".