Measuring wheelchair intervention outcomes: Development of the Wheelchair Outcome Measure
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Provision of a wheelchair has immediate intuitive benefits; however, it can be difficult to evaluate which wheelchair and seating components best meet an individual's needs. As well, funding agencies now prefer evidence of outcomes; and therefore measurement upon prescription of a wheelchair or its components is essential to demonstrate the efficacy of intervention. As no existing tool can provide individualized goal-oriented measure of outcome after wheelchair prescription, a research project was undertaken to create the Wheelchair Outcome Measure (WhOM). METHOD: A mixed methods research design was employed to develop the instrument, which used in-depth interviews of prescribers, individuals who use wheelchairs and their associates, supplemented by additional questions in which participant preferences in key areas of the measure were quantified. RESULTS: The WhOM is a client-specific wheelchair intervention measurement tool that is based on the World Health Organization's International Classification of Function, Disability, and Health. It identifies desired outcomes at a participation level and also acknowledges concerns about body structure and function. CONCLUSION: The new outcome instrument will allow clients to identify and evaluate the outcomes they wish to achieve with their wheelchairs and seating and provide clinicians a way to quantify outcomes of their interventions in a way that is meaningful to the client and potential funding sources.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it