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Record W4366830569 · doi:10.2147/oaem.s403145

Effective Coverage of Emergency Obstetric and Newborn Care Services in Africa: A Scoping Review

2023· review· en· W4366830569 on OpenAlexaff
Mihiretu Alemayehu, Bereket Yakob, Nelisiwe Khuzwayo

Bibliographic record

VenueOpen Access Emergency Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of British Columbia
FundersInyuvesi Yakwazulu-Natali
KeywordsMedicineMedical emergencyNursingIntensive care medicine

Abstract

fetched live from OpenAlex

Objective: This scoping review aimed to map the evidence of effective coverage (EC) of EmONC (Emergency Obstetric and Neonatal Care) services and associated factors in Africa. Methodology: The review used PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) checklist to select, appraise, and report the findings. We searched four databases (PubMed, Web of Science, Google Scholar, and Scopus) and grey literature published between Jan 01, 2011 - Dec 31, 2020. The search terms included "emergency", "obstetric", "newborn", "effective coverage", and "quality" with Boolean terms, AND and OR. The review was conducted using title, abstract, and full-article screenings. The results were analyzed thematically using NVivo v12 qualitative research data analysis software. Results: Of the 1811 searched studies, 32 met the eligibility criteria for review. The majority of the studies were from East (56.3%) and Western (28.1%) Africa. Most studies were cross-sectional, had targeted health facilities, and combined two or more data collection techniques. The thematic analysis yielded three themes: EmONC service utilization, quality of EmONC service, and factors associated with the quality of EmONC services. The review showed a scarcity of evidence and variations regarding the crude coverage, quality of care, and factors affecting the quality of EmONC services in Africa. Conclusion: The review reported that the utilization of EmONC services was below the WHO-recommended 100% in all studies, though some reported improvements over time. Disparities in EmONC services quality were paramount across studies and contexts. However, the methodological and analytical incongruity across studies brought difficulties in tracing and comparing the progress made in EmONC services utilizations. Registration: This scoping review protocol was first registered on the Open Science Framework (OSF) on Aug 27, 2021 (https://osf.io/khcte/).

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 imitation

Not 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.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.146
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.033
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.146
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0250.020
Science and technology studies0.0010.002
Scholarly communication0.0070.006
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.160
GPT teacher head0.502
Teacher spread0.342 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2023
Admission routes1
Has abstractyes

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