African Hospital‐Based Paediatric Palliative Oncology Care Independent of Economic Indicators: An International Society of Paediatric Oncology (SIOP) Global Mapping Programme Survey
Bibliographic record
Abstract
BACKGROUND: Paediatric palliative care (PPC) is considered an essential component of the management of children and adolescents with cancer. The International Society of Paediatric Oncology Global Mapping Programme (SIOP GMP) surveyed hospital-based paediatric oncology facilities across Africa from 2018 to 2020 to document PPC and provision of PPC services. We aimed to assess possible correlations between existing PPC services across Africa with economic indicators. PROCEDURE: An electronic and paper survey was widely distributed to elicit the presence of components of PPC: PPC teams, bereavement counselling services, patient support groups, and spiritual and religious support. Results were correlated with the countries' Gini coefficient, World Bank income status indicators and Human Development Index. RESULTS: Hospital-based paediatric oncology facilities in 16/54 African countries reported having all four PPC services, while those in 12 countries reported having none of the four PPC services. No clear correlations were found between provision of such services and selected economic factors. CONCLUSIONS: This study assesses components of PPC through four binary questions and demonstrates that hospital-based paediatric oncology facilities with limited resources caring for children and adolescents can provide PPC. Adoption of the World Health Organization's conceptual framework for palliative care and knowledge transfer between African facilities on the integration of PPC into paediatric oncology care, would benefit the increasing numbers of children and adolescents with cancer across the continent.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".