Service user perspectives on palliative care education for health and social care professionals supporting people with learning disabilities
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Evidence from European and American studies indicates limited referrals of people with learning (intellectual) disabilities to palliative care services. Although professionals' perceptions of their training needs in this area have been studied, the perceptions of people with learning disabilities and family carers are not known. This study aimed to elicit the views of people with learning disabilities, and their family carers concerning palliative care, to inform healthcare professional education and training. METHODS: A qualitative, exploratory design was used. A total of 17 people with learning disabilities were recruited to two focus groups which took place within an advocacy network. Additionally, three family carers of someone with a learning disability, requiring palliative care, and two family carers who had been bereaved recently were also interviewed. RESULTS: Combined data identified the perceived learning needs for healthcare professionals. Three subthemes emerged: 'information and preparation', 'provision of care' and 'family-centred care'. CONCLUSIONS: This study shows that people with learning disabilities can have conversations about death and dying, and their preferred end-of-life care, but require information that they can understand. They also need to have people around familiar to them and with them. Healthcare professionals require skills and knowledge to effectively provide palliative care for people with learning disabilities and should also work in partnership with their family carers who have expertise from their long-term caring role. These findings have implications for educators and clinicians.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".