A systematic review of global health capacity building initiatives in low-to middle-income countries in the Middle East and North Africa region
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Low-and Middle-Income Countries (LMICs) in the Middle East and North Africa (MENA) region are facing increasing global health challenges with a reduced ability to manage them. Global Health Capacity Building (GHCB) initiatives have the potential to improve health workforce performance and health outcomes, however little is known about the GHCB topics and approaches implemented in this region. This is the first systematic review of GHCB initiatives among LMICs in the MENA region. METHODS: An academic database search of Medline (OVID), PubMed, Scopus, Embase.com , and Open Grey was conducted for articles published between January 2009 and September 2019 in English. Next, a grey literature search following a recommended search framework was conducted. Reviewed records addressed a global health topic, had a capacity building component, looked at specific learning outcomes, and reflected an LMIC in the MENA. Primary outcomes included country, topic, modality, pedagogy, and population. RESULTS: Reports of GHCB initiatives were retrieved from grey sources (73.2%) and academic sources (26.8%). Most GHCB initiatives were mainly conducted face-to-face (94.4%) to professional personnel (57.5%) through a theoretical pedagogical approach (44.3%). Dominant global health themes were non-communicable diseases (29.2%), sexual and reproductive health (18.4%), and mental health (14.5%). When matched against the Global Burden of Disease data, important gaps were found regarding the topics of GHCB initiatives in relation to the region's health needs. There were limited reports of GHCB initiatives addressing conflict and emergency topics, and those addressing non-communicable disease topics were primarily reported from Egypt and Iran. CONCLUSION: Innovative and practicum-based approaches are needed for GHCB initiatives among LMICs in the MENA region, with a focus on training community workers. Regional and country-specific analyses of GHCB initiatives relative to their health needs are discussed in the manuscript based on the results of this review.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it