Men’s knowledge of obstetrics danger sign and associated factors in low-income countries: a systematic review and meta-analysis
Notice bibliographique
Résumé
Obstetric danger signs refer to unexpected signs that arise during pregnancy, childbirth, or the postpartum period, indicating potential complications that require immediate medical attention. Globally, approximately 15% of pregnant women experience such complications, contributing to an estimated 287,000 maternal deaths annually-equivalent to nearly 800 deaths each day. This review evaluates the literature on men's knowledge of obstetric danger signs, a critical factor in enhancing maternal health outcomes. We performed a comprehensive search for articles using PubMed, Web of Science, Scopus, Hinari, and Google Scholar databases. To identify relevant studies, we employed search terms such as "knowledge," "awareness," "information," "recognition," "pregnancy danger signs," "obstetric danger signs," "obstetric warning signs," and "labor complications," combined with "low-income countries." six reviewers independently screened the articles and extracted data. The included articles in the review are cross-sectional studies, conducted in low-income countries and published in English, with no restrictions of publication years. Study quality was evaluated using a Newcastle-Ottawa Scale. The study was reported following the PRISMA checklist and the protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (protocol ID: CRD42024488979). Of the 366 articles initially screened by title and abstract, 13 studies met the inclusion criteria. All the included studies assessed men's knowledge of obstetric danger signs during pregnancy, and childbirth, while only ten assessed their knowledge during the postpartum period. The pooled random-effects meta-analysis indicated that men's knowledge of obstetric danger signs was 36.96% during pregnancy, 40.86% during childbirth, and 35.84% during the postpartum period, with an overall knowledge level of 37.29% based on the summarized random-effects meta-analysis. Key factors influencing men's knowledge included urban residence, educational attainment, access to antenatal care, participation in the health development army, and previous experience with obstetric complications. In low-income countries, men's knowledge of obstetric danger signs remains notably low, potentially hindering their ability to seek timely obstetric care for their partners during complications. Addressing this gap requires strengthening counseling services during antenatal care, expanding community meetings, and enhancing community-based health education on obstetric danger signs.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,017 | 0,023 |
| Bibliométrie | 0,006 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».