Access to maternal-child health and HIV services for women in North-Central Nigeria: A qualitative exploration of the male partner perspective
Bibliographic record
Abstract
BACKGROUND: In much of sub-Saharan Africa, male partners play influential roles in women's access to maternal-child healthcare, including prevention of mother-to-child transmission of HIV services. We explored male partner perspectives on women's access to maternal-child healthcare in North-Central Nigeria. METHODS: Three focus groups were conducted with 30 men, purposefully-selected on the basis of being married, and rural or urban residence. Major themes explored were men's maternal-child health knowledge, gender power dynamics in women's access to healthcare, and peer support for pregnant and postpartum women. Data were manually analyzed using Grounded Theory, which involves constructing theories out of data collected, rather than applying pre-formed theories. RESULTS: Mean participant age was 48.3 years, with 36.7% aged <40 years, 46.7% between 41 and 60 years, and 16.6% over 60 years old. Religious affiliation was self-reported; 60% of participants were Muslim and 40% were Christian. There was consensus on the acceptability of maternal-child health services and their importance for optimal maternal-infant outcomes. Citing underlying patriarchal norms, participants acknowledged that men had more influence in family health decision-making than women. However, positive interpersonal couple relationships were thought to facilitate equitable decision-making among couples. Financial constraints, male-unfriendly clinics and poor healthcare worker attitudes were major barriers to women's access and male partner involvement. The provision of psychosocial and maternal peer support from trained women was deemed highly acceptable for both HIV-positive and HIV-negative women. CONCLUSIONS: Strategic engagement of community leaders, including traditional and religious leaders, is needed to address harmful norms and practices underlying gender inequity in health decision-making. Gender mainstreaming, where the needs and concerns of both men and women are considered, should be applied in maternal-child healthcare education and delivery. Clinic fee reductions or elimination can facilitate service access. Finally, professional organizations can do more to reinforce respectful maternity care among healthcare workers.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".