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Record W4405201719 · doi:10.3389/frhs.2024.1425353

Comprehensive scoping review of palliative care development in Africa: recent advances and persistent gaps

2024· review· en· W4405201719 on OpenAlexaff
Fernanda Bastos, Eduardo Garralda, Álvaro Montero, John Y. Rhee, Natalia Arias-Casais, Emmanuel Luyirika, Eve Namisango, José Pereira, Carlos Centeno, Vilma Tripodoro

Bibliographic record

VenueFrontiers in Health Services · 2024
Typereview
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPalliative careMedicineNursing

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.184
GPT teacher head0.470
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations14
Published2024
Admission routes1
Has abstractyes

Explore more

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