LIFE SPACE MOBILITY IS ASSOCIATED WITH DISTINCT FACTORS BELOW AND ABOVE THE AGE OF 75 YEARS
Bibliographic record
Abstract
Abstract Life-space mobility (LSM) is associated with the quality of life and well-being of older adults, and it is influenced by individual and environmental factors. However, age-related differences are ignored. This study aimed to explore which factors are associated with LSM in community-dwelling older adults from two age groups (< 75 and≥75 years). This cross-sectional study included older adults aged 65 and over, independently mobile, without neurologic conditions or dementia. LSM, the dependent variable, was assessed using the Life-Space Assessment-(LSA). Independent variables were assessed using Timed Up and Go-(TUG) for mobility, Montreal Cognitive Assessment-(MoCA) for cognition, Activities-specific Balance Confidence Scale-(ABC) for fear of falling, Hospital Anxiety and Depression Scale-(HADS) for depression, and four-functional mobility tasks for participation. Additionally, functional status and number of medications were assessed. Two separate stepwise regression models were conducted for older adults aged< 75 and≥75 years. Two-hundred forty-two older adults (28.9% men) were included [mean(SD) age: 73.7(6.4) years], of whom 40.9% were≥75 years. Results revealed that different factors were associated with LSM in each age group. For those< 75 years, participation and TUG explained 33% and 9.4% of the variance in LSM, respectively. Conversely, for the older group, ABC, MoCA, and TUG explained 33.5%, 4.1% and 5.2% of the variance in LSM, respectively. Our finding shows that distinct factors are associated with LSM in each group, particularly mobility in the younger and fear of falling in the older. By highlighting these specific factors, interventions can be tailored more effectively to enhance the quality of life and well-being of older adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".