Prevalence and Predictors of Need for Seating Intervention and Mobility for Persons in Long-Term Care
Bibliographic record
Abstract
A descriptive cross-sectional study was conducted to (a) determine the prevalence of need for wheel-chair seating intervention in two long-term care facilities in Vancouver, BC, (b) determine the extent of the residents' independent mobility within these facilities, and (c) explore the relationship between proper wheel-chair seating and positioning and independent mobility. The study population comprised 99 wheel-chair-using older adults. Four trained raters assessed need for seating intervention, using the Seating Identification Tool, and quantified extent and frequency of wheel-chair mobility, using the Nursing Home Life-Space Diameter. Results indicated that (a) there was a low need (overall 22%) for wheel-chair seating intervention in the two facilities, (b) half of the residents were independently mobile in their own rooms and on their units, but independent mobility decreased when greater distances needed to be travelled, and (c) the need for wheel-chair seating intervention was the only significant predictor of extent of independent mobility. These findings suggest that, where there are dedicated staff and equipment resources, the need for wheel-chair seating intervention can be minimized and independent mobility for long-term care residents maximized.
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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 | 0.004 |
| 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 | 0.000 |
| 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".