Comprehensive scoping review of palliative care development in Africa: recent advances and persistent gaps
Bibliographic record
Abstract
Worldwide 56·8 million people need palliative care (PC), and Africa shows the highest demand. This study updates the 2017 review of African PC development, using a scoping review methodology based on Arksey and O'Malley's framework and the PRISMA-ScR checklist. The review was conducted across PUBMED, CINAHL, Embase, government websites, and the African PC Association Atlas, from 2017 to 2023, charting its progress using the new WHO framework for PC Development, which, in addition to Services, Education, Medicines, and Policies, two new dimensions were incorporated: Research and Empowerment of people and Communities. Of the 4.420 records, 118 met the inclusion criteria. Findings showed increased adult specialised services (n = 675), and 15 of 54 countries have paediatric services. Nonetheless, the ratio of services per population mostly remains under 0,10 per 100.000 inhabitants. PC education was included in undergraduate curricula in 29 countries; despite the rise in morphine availability (28 countries), median consumption remains under 3 mg/per capita/year, and 14 countries presented stand-alone policies. Publications on PC development increased, and 26 countries have National PC Associations. Notwithstanding progress since 2017, significant hurdles remain, highlighting the need for ongoing research and policy development to ensure equitable access to palliative care in Africa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.028 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.023 | 0.028 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".