What does ‘good’ palliative care look like for children and young people? A qualitative study of parents’ experiences and perspectives
Bibliographic record
Abstract
BACKGROUND: Worldwide, around 21 million children would benefit from palliative care and over 7 million babies and children die each year. Whilst provision of paediatric palliative care is advancing, there major gaps between what should be done, and what is being done, in clinical practice. In 2017, the National Institute for Health and Care Excellence (NICE) introduced a quality standard, to standardise and improve children's palliative care in England. However, there is little evidence about what good experiences of palliative care for children are, and how they relate to the quality standard for end-of-life care. AIM: This study explored how the NICE quality standard featured in parental experiences of palliative care for children to understand what 'good' palliative care is. DESIGN: Qualitative study, employing in-depth, telephone and video-call, semi-structured interviews. Data were analysed using thematic analysis, informed by Appreciative Inquiry. SETTING/PARTICIPANTS: Participants were parents of children and young people (aged 0-17 years) in England, who were receiving palliative care, and parents whose child had died. RESULTS: Fourteen mothers and three fathers were interviewed. Seven were bereaved. Parents were recruited via four children's hospices, one hospital, and via social media. Good palliative care is co-led and co-planned with trusted professionals; is integrated, responsive and flexible; encompasses the whole family; and enables parents to not only care for, but also to parent their child to end of life. CONCLUSIONS: Findings have implications for informing evidence based practice and clinical guidelines, overall improving experiences of care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".