A Wheelchair Workshop for Medical Students Improves Knowledge and Skills
Bibliographic record
Abstract
OBJECTIVE: To test the hypothesis that a multicomponent workshop about wheelchairs, tailored for undergraduate medical students, is effective in improving medical students' wheelchair-related knowledge, skills, and attitudes. DESIGN: A randomized controlled trial of 24 first- and second-year medical students randomly allocated into intervention and control groups was undertaken. The intervention group received a 4-hr workshop that included didactic, practical, community, and reflective elements. The educational objectives were validated by a focus group. The main outcome measures were a written knowledge test, a practical examination, the Scale of Attitudes Toward Disabled Persons, and students' perceptions. RESULTS: The baseline characteristics of the groups were comparable. After the workshop, the mean scores on the written knowledge test and practical examination for the intervention group were higher than for the control group by 23.9% (95% confidence interval, 17.6%-30.3%; P < 0.0001) and 34.4% (95% confidence interval, 26.3%-42.5%; P < 0.0001), respectively. The difference (-1.6%) for the Scale of Attitudes Toward Disabled Persons scores was not significant (P = 0.93), but there may have been a ceiling effect (both groups' mean scores were >87%). The perceptions of the students who took the workshop were highly positive. CONCLUSIONS: A wheelchair workshop designed for medical students was practical, well received by students, and effective at improving students' knowledge and skills. Although students' attitudes were not measurably affected by the intervention, there was qualitative evidence of a positive effect.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".