Dementia Education for Physiotherapy Students: A Questionnaire of Australian and Canadian Entry-to-Professional Practice Programmes
Bibliographic record
Abstract
Purpose: To determine (1) what dementia education is provided to entry-to-professional practice physiotherapy students in Canada and Australia; (2) how this education is delivered; and (3) the challenges in delivering this education. Method: A designated education provider from each university who offered entry-to-professional practice physiotherapy programmes received a web-based questionnaire. Data were analyzed using descriptive statistics and qualitative content analysis. Results: Responses from 30/36 eligible universities resulted in 35 physiotherapy programmes included for analysis. Canadian programmes had a median of 5.5 hours (range, min-max, 0.5–13.0 hours), and Australia 4.0 hours (range, min-max, 2.0–22.0 hours) of dementia education. Lectures and tutorials were the most common method of delivery. There were varying amounts of education on topics such as cognition, communication, and behavioural symptoms and strategies. Challenges included dementia being difficult to teach, student stigma about people with dementia, difficulty providing students with real-life exposure to people with dementia, engaging students in the topic, and integrating dementia education into full programmes. Conclusions: Dementia education across programmes varies, with some programmes lacking content on key topics such as cognitive, communication, and behavioural symptoms and strategies. These results may help physiotherapy accreditation organizations and universities develop dementia education standards and content.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".