A description of manual wheelchair skills training: current practices in Canadian rehabilitation centers
Bibliographic record
Abstract
PURPOSE: To describe current practices for manual wheelchair (MWC) skills training in Canadian rehabilitation centers. METHODS: An online survey was sent to practice leaders in occupational (OT) and physical therapy (PT) at 87 Canadian rehabilitation centers. Responses were solicited from individuals who could report about wheelchair skills training at facilities with at least 10 beds designated for rehabilitation. Thirty-four questions asked about: (1) demographics, (2) components of MWC training, (3) amount of MWC skills training, (4) use of validated programs and (5) perceived barriers to using validated programs. Data were analyzed using summary statistics. RESULTS: About 68/87 responses were received primarily from OTs (42/68). Basic MWC skills training (e.g. wheel-locks) was consistently part of clinical practice (45/68), while advanced skills training (e.g. curb-cuts) was rare (8/68). On an average, 1-4 h of training was done (29/68). Validated training programs were used by 16/68, most of whom used them "rarely" (7/16). Common barriers to using validated programs were lack of time (43/68) and resources (39/68). CONCLUSIONS: Learning to use a wheelchair is important for those with ambulation impairments because the wheelchair enables mobility and social participation. Providing opportunities for advanced wheelchair skills training may enhance mobility and social participation in a safe manner. Implications for Rehabilitation There is evidence confirming the benefits of a validated wheelchair skills program, yet most clinicians do no not use them. A variety of perceived barriers may help to explain the limited use of existing programs, such as time, resources and knowledge. Effective knowledge translation efforts may help alleviate some of these barriers, and novel wheelchair training approaches may alleviate some burden on clinicians to help accommodate the increasing number of older wheelchair users.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".