Cutoffs to Identify Restricted Life-space Mobility in Older Adults Across Different Contexts: The International Mobility in Aging Study
Bibliographic record
Abstract
Abstract different populations have different averages of life-space assessment scores and defining cutoff values of clinical significance by each population should take into consideration. Different cutoffs to define restricted life space have been reported. The most common is a score of 60 points. There are other cutoffs derived from receiver operating characteristic (ROC) analysis and used to classify older adults according to their ability in activities of daily living (ADLs) (52.3 points) or instrumental activities of daily living (IADLs) (56 points); other cutoffs are specialized for people with cognitive impairment (26.75 points) or people with spinal cord injury who need mobility aids (78.5 points). The aims were to identify cutoff points of Life Space Assessment (LSA) in older adults in different sites and to determine the relationship of the cutoff scores with mobility disability and depression. The study population was composed of community-dwelling adults aged 65–74 years who were not institutionalized. An ROC analysis was constructed, and the area under the curve (AUC) was calculated to identify the optimal cutoff that discriminates life-space restriction for each city. Logistic regressions were executed by site to comprehend the association among restricted LSA and mobility disability and depression. In total, 1890 participants were included in the analyses (52.38% women, 37.19% mobility disability and 21.32% had depression). Canada cities had the highest cutoff, while Tirana and Natal had the lowest cutoff (< 50). Kingston was the site with the highest association between life-space restriction and mobility disability (OR 5.4, 95% CI 2.9–10). Saint-Hyacinthe, Tirana, and Manizales had significant associations between depression and restricted life space (OR 3.25, 95% CI 1.53–6.89, OR 3.14, 95% CI 1.88–5.24, and OR 3.99, 95% CI 2.28–6.98, respectively). Different cutoffs to define restricted life-space have been identified in elderly people at different sites. The analysis of the relationship between the restricted life space and personal characteristics like depression and mobility disability supported these findings. The groupings produced by the cutoff points for each site showed notable variations. These findings emphasize the importance of population-based cutoffs to improve the general applicability of LSM criteria and take into consideration the importance of site-specific approaches.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".