Men’s knowledge of obstetrics danger sign and associated factors in low-income countries: a systematic review and meta-analysis
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.023 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".