Men’s perception of barriers to women’s use and access of skilled pregnancy care in rural Nigeria: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Greater paternal engagement is positively associated with improved access to and utilization of maternal services. Despite evidence that male involvement increased uptake of maternal and child services, studies show that few men are participating in MNCH programs. Community leaders have long been engaged in public health promotion in rural settings and have been shown to mobilize communities to enhance changes in cultural practices related to public health. With the ultimate goal of increasing men's involvement in maternal health, this study seeks to understand men's perceptions of community and health systems barriers to maternal access and usage of skilled care in rural Edo, Nigeria. METHODS: This qualitative study involved the analysis of data collected from community conversations with male elders in Etsako East and Esan South East Local Government Areas of Edo State, Nigeria. Community conversations participants (n = 128) comprised of elders between the ages of 50-101. A total of 9 community conversations were conducted. Discussions were audio recorded, transcribed and imported into Atlas.ti 6.2 for content analysis. RESULTS: Men's perceptions of barriers to maternal use of skilled care are presented in two overarching themes: community systems and health systems. Three sub themes were generated as community systems barriers to maternal healthcare use, they include: gender roles, traditional treatment and policy changes. Three sub themes emerged under health system barriers and they include: cost of health facilities, dissatisfaction with facilities and distance from facilities. CONCLUSION: Findings suggest that community elders are not only in a good position to influence men's behavior, they are also a source of information to policy makers on strategies to overcome barriers to maternal health, especially at the community level. Furthermore, community elders need support to enact regulations that will promote men's involvement in maternal health, thereby increasing maternal use of skilled 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".