Translating ‘dementia friends’ programme to undergraduate medical and nursing practice: a qualitative exploration
Bibliographic record
Abstract
INTRODUCTION: Dementia awareness is a key priority of medical and nursing pre-registration education. The 'dementia friends' programme is an internationally recognised and accredited dementia awareness workshop that is led by a trained facilitator. While this programme has been associated with positive outcomes, few studies have examined how medical and nursing students apply their learning in practice after the workshop. The aim of his study was to explore how nursing and medical students apply the dementia friend's programme into practice when caring for people living with dementia. METHODS: Seven focus-group interviews were conducted with 36 nursing students and 14 medical students at one university in Northern Ireland (n = 50), following 'the dementia friends programme. Interview guides were co-designed alongside people living with dementia. Interviews were audio-recorded, transcribed verbatim and analysed using thematic analysis. Ethical approval was granted for this study. RESULTS: Four themes emerged: 'reframing dementia', which highlighted how the education had enabled students to actively empower and support people living with dementia in practice; 'dementia friendly design', which focused on how students had modified their clinical environments when providing care for people living with dementia, 'creative communication', which considered how students had used their education to adapt their verbal and non-verbal communication with people living with dementia and 'realities of advanced dementia' which contemplated how students believed their dementia education could be improved within their current curriculum. DISCUSSION: The Dementia Friends programme has actively supported nursing and medical students to improve the lives of people with dementia in their care through environmental adaptions and creative approaches to communication. This study provides an evidence base that supports the provision of 'a dementia friends programme to healthcare professional students. The study also highlights how this education can actively influence how nursing and medical students support people living with dementia in their practice in the months and years after education.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".