Children’s palliative care education and training: developing an education standard framework and audit
Bibliographic record
Abstract
BACKGROUND: The need to align the range of guidance and competencies concerning children's palliative care and develop an education framework have been recommended by a UK All-Party Parliament Group and others. In response to these recommendations the need for a revised children's palliative care competency framework was recognized. A Children's Palliative Care Education and Training Action Group, comprising champions in the field, was formed across UK and Ireland in 2019 to take this work forward. Their aim was to agree core principles of practice in order to standardize children's palliative care education and training. METHODS: Over four meetings the Action Group reviewed sources of evidence and guidance including palliative care competency documents and UK and Ireland quality and qualification frameworks. Expected levels of developing knowledge and skills were then agreed and identified competencies mapped to each level. The mapping process led to the development of learning outcomes, local indicative programme content and assessment exemplars. RESULTS: Four sections depicting developing levels of knowledge and skills were identified: Public Health, Universal, Core, Specialist. Each level has four learning outcomes: Communicating effectively, Working with others in and across various settings, Identifying and managing symptoms, Sustaining self-care and supporting the well-being of others. An audit tool template was developed to facilitate quality assurance of programme delivery. The framework and audit tool repository is on the International Children's Palliative Care Network website for ease of international access. CONCLUSIONS: The framework has received interest at UK, Ireland and International launches. While there are education programmes in children's palliative care this is the first international attempt to coordinate education, to address lay carer education and to include public health.
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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 | 0.226 | 0.198 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".