Manual Wheelchair Skills Training for Community-Dwelling Veterans with Spinal Cord Injury: A Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVES: To test the hypotheses that community-dwelling veterans with spinal cord injury (SCI) who receive the Wheelchair Skills Training Program (WSTP) in their own environments significantly improve their manual wheelchair-skills capacity, retain those improvements at one year and improve participation in comparison with an Educational Control (EC) group. METHODS: We carried out a randomized controlled trial, studying 106 veterans with SCI from three Veterans Affairs rehabilitation centers. Each participant received either five one-on-one WSTP or EC sessions 30-45 minutes in duration. The main outcome measures were the total and subtotal percentage capacity scores from the Wheelchair Skills Test 4.1 (WST) and Craig Handicap Assessment and Reporting Technique (CHART) scores. RESULTS: Participants in the WSTP group improved their total and Advanced-level WST scores by 7.1% and 30.1% relative to baseline (p < 0.001) and retained their scores at one year follow-up. The success rates for individual skills were consistent with the total and subtotal WST scores. The CHART Mobility sub-score improved by 3.2% over baseline (p = 0.021). CONCLUSIONS: Individualized wheelchair skills training in the home environment substantially improves the advanced and total wheelchair skills capacity of experienced community-dwelling veterans with SCI but has only a small impact on participation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".