Using remote learning to teach clinicians manual wheelchair skills: a cohort study with pre- vs post-training comparisons
Bibliographic record
Abstract
PURPOSE: To test the hypothesis that remote learning to teach clinicians manual wheelchair skills is efficacious. MATERIALS AND METHODS: A convenience sample of therapists (physical and occupational) and students were enrolled in pairs in a cohort study with pre- versus post-training comparisons. The intervention was a hybrid of self-study and hands-on practice paired with remote feedback for ten intermediate and advanced manual wheelchair skills. Participants practiced with self-selected frequency and duration, uploading a session log and video(s) to an online platform. A remote trainer provided asynchronous feedback prior to the next practice session. Capacity and confidence in completing the ten skills were evaluated using the Wheelchair Skills Test Questionnaire (WST-Q). Knowledge of wheelchair skills training and motor learning was assessed using a 62-item Knowledge Test. Secondary outcome measures included skill achievement, as confirmed by submitted video recordings, and participant feedback about the training. RESULTS: = 0.004). CONCLUSIONS: Remote learning can increase wheelchair skills capacity and confidence as well as knowledge about such training and assessment. This model should be further investigated as a delivery method for training rehabilitation professionals. CLINICAL TRIAL REGISTRATION NUMBER: NCT01807728.Implications for rehabilitationWheelchair skills training is one of the 8 steps of wheelchair provision as outlined by the World Health Organization.Wheelchair skills are not a core part of most clinical curriculums and many clinicians cite a lack of resources and uncertainty on how to implement wheelchair skills training into practice as major barriers to providing such training.Remote learning offers the benefits of structured wheelchair skills training with expert feedback on an individual's own schedule that is not afforded by one-day "bootcamp"-type courses or on-the-job training, which are how many clinicians currently learn wheelchair skills.In a sample of physical and occupational therapists and students, remote learning was effective at increasing capacity and confidence to perform manual wheelchair skills as well as knowledge of wheelchair training.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".