Characterising life-space mobility and its relationship to physical capacity and outdoor walking in older adults with difficulty walking outdoors: a secondary data analysis
Bibliographic record
Abstract
PURPOSE: To describe life-space mobility (LSM) and its relationship with physical capacity (PC) (walking endurance, walking speed, leg strength, balance), and outdoor walking in older adults with difficulty walking outdoors. METHODS: A secondary analysis of baseline data from 173 adults aged ≥ 65 years with mobility limitations in the Getting Older Adults Outdoors (GO-OUT) study was conducted. LSM was measured using the Life-space Assessment (LSA), and PC was assessed using the 6-minute walk test (6MWT), 10-meter walk test (10mWT) at a comfortable and fast pace, 30-second sit-to-stand (30sSTS), and mini-Balance Evaluation Systems Test (mini-BESTest). The relationship between scores on PC measures and outdoor walking time, assessed by the CHAMPS-OUTDOORS questionnaire, and LSA score, was examined using Spearman correlations and backward stepwise regression modelling, adjusted for age and sex. RESULTS: = 0.28). The final regression model, including 10mWT, 30sSTS, mini-BESTest, explained 31% of LSA score variance. CONCLUSION: PC and outdoor walking time relate to LSM in community-dwelling older adults with difficulty walking outdoors, though outdoor walking time has a weaker correlation with LSM.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".