Improvement and Retention of Wheelchair Skills Training for Students in Entry-Level Occupational Therapy Education
Bibliographic record
Abstract
IMPORTANCE: Although an essential component of best practice, wheelchair skills training is often inadequate; occupational therapy practitioners' professional preparation is a contributing factor. OBJECTIVE: To assess the effectiveness of a boot camp on capacity and self-efficacy in wheelchair skills and self-efficacy in clinical practice, retention of improvements, and effective boot-camp attributes. DESIGN: Concurrent, embedded, mixed-methods cohort design that used blinded, repeated-measures quantitative evaluation with 4-mo follow-up and directed content analysis of a qualitative questionnaire. SETTING: University entry-to-practice program. PARTICIPANTS: Convenience sample (N = 42) of final-year students. INTERVENTION: A 4-hr boot camp with demonstration and supervised practice. Content incorporated skill performance, training and motor-learning strategies, and safe supervision. OUTCOMES AND MEASURES: Skill performance capacity (Wheelchair Skills Test-Questionnaire), self-efficacy with manual wheelchair use (Wheelchair Use Confidence Scale), confidence in provision of manual wheelchair training services (Self-Efficacy in Assessing, Training, and Spotting test), and a boot-camp experience questionnaire. RESULTS: = .68-.88). All measures except skill capacity demonstrated retention; skill capacity decreased 5.3% (95% confidence interval [2.0, 8.5]) but was significantly higher than baseline. Three themes influenced practice confidence: knowledge acquisition, experiential learning, and client empathy. CONCLUSIONS AND RELEVANCE: Results confirm improved wheelchair self-efficacy, capacity, and self-efficacy with clinical intervention skills. Retention of outcomes suggests the potential impact on future practice. Experiential learning supports performance component acquisition and imparts empathy of client experience, which may improve occupational therapy practitioners' perceptions of client potential. WHAT THIS ARTICLE ADDS: A 4-hr experiential boot camp can increase students' capacity and confidence to deliver wheelchair skills training to future clients. Experiential learning increased students' appreciation for clients' experience and expectation of client potential.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".