Sex Disparities: Couple’s Knowledge and Attitude Towards Obstetric Danger Signs and Maternal Health Care: in Rural Jimma Zone of Ethiopia
Bibliographic record
Abstract
Purpose: This study aimed to compare knowledge and attitudes towards obstetric danger signs and care between females receiving maternal care and their male partners. Methods and Materials: A community-based comparative cross-sectional study was conducted in the rural setting of Jimma, Ethiopia. Female and their male partners were selected randomly. The number of participants included from each sex was 3235 totaling 6470. Face-to-face data collection was employed using open data kit (ODK) software. A pre-test was performed before the data collection. Descriptive and analytical statistical analysis was used to compare knowledge and attitudes regarding obstetric danger signs and care. Predictor variables were declared considering a 95% confidence interval, adjusted odds ratio (AOR) and P-value less than 0.05. Results: On average, male and female participants identified at least two obstetric danger signs. More females could mention more antenatal, childbirth, and postnatal danger signs than their male partners. Both females and their male partners who listened to the radio at least once per week had a statistically significant positive attitude towards obstetric care. Nonetheless, both had an almost similar magnitude of attitude towards obstetric care irrespective of belonging to different occupational, educational, and other social strata. Males' knowledge of danger signs during pregnancy (95% CI = (1.07-1.62), AOR = 1.32, P < 0.008) and postnatal care (95% CI = (1.16-1.89), AOR = 1.48, P < 0.002) had a statistically significant association with the females utilization antenatal care (ANC) service, though not delivery care (DC) or postnatal (PNC). Conclusion: There were inequalities in obstetric danger signs knowledge between females and their male partners. Male partners' knowledge of obstetric danger signs is not only significant during pregnancy and delivery but also has a lasting impact on post-natal service utilization, which underscores the importance of their involvement in maternal healthcare.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".