Global development of children’s palliative care: An international survey of in-nation expert perceptions in 2017
Bibliographic record
Abstract
Background: The growing interest in tracking the global development of palliative care provision is not matched by research on the development of palliative care services specifically for children. Yet it is estimated that worldwide, 21 million children annually could benefit from the provision of palliative care. We report on a global study of children’s palliative care development and offer suggestions for further improvement in design and method. Methods: Primary data on the level of children’s palliative care development in 2017 was collected from in-country experts through a specific question in an online questionnaire that sought to measure the overall level of palliative care provision globally. Countries were assigned to one of six categories on the basis of the responses obtained. Conflicting responses from the same country were resolved with reference to a hierarchy of preferred respondents. Results: Our data allowed the categorisation of 113 countries, accounting for 65% of the global population aged under 20. Number of countries (% of global child population) in each category were as follows: 1) no known activity, 21 (4%); 2) capacity-building, 16 (24%); 3a) isolated provision, 55 (30%); 3b) generalized provision, 5 (1%); 4a) preliminary integration into mainstream provision, 14 (8%); 4b) advanced integration, 7 (2%). Conclusions: Children’s palliative care at the highest level of provision is available in just 21 countries, accounting for fewer than 10% of the global population aged under 20. It is concentrated in high income settings, whilst the majority of the global need for such care is in low- and middle-income countries. Our study is a useful tool for global advocacy relating to children’s palliative care and a stimulus for the creation of improved indicators to measure it at the country level.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 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".