A systematic review of global health capacity building initiatives in low-to middle-income countries in the Middle East and North Africa region
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Notice bibliographique
Résumé
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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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle