Prevalence and Facility Level Correlates of Need for Wheelchair Seating Assessment among Long-Term Care Residents
Bibliographic record
Abstract
BACKGROUND: Wheelchairs are frequently prescribed for residents with mobility impairments in long-term care. Many residents receive poorly fitting wheelchairs, compromising functional independence and mobility, and contributing to subsequent health issues such as pressure ulcers. The extent of this problem and the factors that predict poor fit are poorly understood; such evidence would contribute greatly to effective and efficient clinical practice in long-term care. OBJECTIVE: To identify the prevalence of need for wheelchair seating intervention among residents in long-term care facilities in Vancouver and explore the relationship between the need for seating intervention and facility level factors. METHODS: Logistic regression analysis using secondary data from a cross-sectional study exploring predictors of resident mobility. A total of 263 residents (183 females and 80 males) were randomly selected from 11 long-term care facilities in the Vancouver health region (mean age 84.2 ± 8.6 years). The Seating Identification Tool was used to establish subject need for wheelchair seating intervention. Individual item frequency was calculated. Six contextual variables were measured at each facility including occupational therapy staffing, funding source, policies regarding wheelchair-related equipment, and decision-making philosophy. RESULTS: The overall prevalence rate of inappropriate seating was 58.6% (95% CI 52.6-64.5), ranging from 30.4 to 81.8% among the individual facilities. Discomfort, poor positioning and mobility, and skin integrity were the most common issues. Two facility level variables were significant predictors of need for seating assessment: ratio of occupational therapists per 100 residents [OR 0.11 (CI 0.04, 0.31)] and expectation that residents purchase wheelchair equipment beyond the basic level [OR 2.78 (1.11, 6.97)]. A negative association between facility prevalence rate and ratio of occupational therapists (r(p) = -0.684, CI -0.143 to -0.910) was found. CONCLUSION: Prevalence of need for seating assessment in long-term care is high overall but it varies considerably between facilities. Increasing access to occupational therapy services appears to mediate this need.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".