Male partner involvement in delivery care service and associated factors in Ethiopia: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Promoting the involvement of male partners in skilled delivery care is a strategy supported by the World Health Organization (WHO) to improve maternal and infant health outcomes. This systematic review and meta-analysis aimed to estimate the pooled prevalence of male partner involvement in delivery care service in Ethiopia and its contributing factors. METHODS: We retrieved observational studies conducted in Ethiopia from PubMed, Google Scholar, Embase, Cochrane Library, Hinari, and Mednar using Boolean search terms. The Newcastle Ottawa 2016 Critical Appraisal Checklist assessed the methodological quality of the studies. Publication bias was evaluated with a funnel plot and Egger's test, and heterogeneity was checked using the I-squared test. Data were extracted into Microsoft Excel and analyzed using Stata 11 software. RESULTS: 10 articles with 5,307 participants were included for analysis. The pooled prevalence of male partner involvement in delivery care service was 52.99% (95% CI: 40.63-65.35). Paternal secondary education and above (OR 1.99, 95% CI: 1.69, 2.30), paternal knowledge (OR 3.129, 95% CI: 1.901, 4.356), partner attitude (OR 2.39, 95% CI: 1.45-3.34), having ANC accompanying experience (OR 8.09, 95% CI: 3.14, 19.32), and urban residence (OR 2.12, 95% CI: 1.61, 2.64) were significantly associated with male partner involvement in delivery care service in Ethiopia. CONCLUSION: This study found that more than half of male partners in Ethiopia were involved in delivery care services. The key contributing factors for male partner involvement in delivery care services were paternal secondary education and above, paternal knowledge, partner attitude, ANC accompanying experience, and urban residence. Campaigns should be organized to improve knowledge, attitude, and effectively recognize men's involvement in skilled birth care.
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 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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.027 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".