Impact of home visits to pregnant women and their spouses on gender norms and dynamics in Bauchi State, Nigeria: Narratives from visited men and women
Bibliographic record
Abstract
BACKGROUND: Maternal and newborn child health are priority concerns in Bauchi State, northern Nigeria. Increased male involvement in reproductive health is recommended by the World Health Organization. A trial of a program of universal home visits to pregnant women and their spouses, with an intention to increase male involvement in pregnancy and childbirth, showed improvements in actionable risk factors and in maternal morbidity. We used a narrative technique to explore experiences of the visits and their effect on gender roles and dynamics within the households. METHODS: Trained fieldworkers collected narratives of change from 23 visited women and 21 visited men. After translation of the stories into English, we conducted an inductive thematic analysis to examine the impact of the visits on gender norms and dynamics. RESULTS: The analysis indicated that the visits improved men's support for antenatal care, immunization, and seeking help for danger signs, increased spousal communication, and led to changes in perceptions about gender violence and promoted non-violent gender relationships. However, although some stories described increased spousal communication, they did not mention that this translated into shared decision-making or increased autonomy for women. Many of the men's stories described a continuing paternalistic, male-dominant position in decision-making. CONCLUSIONS: Few studies have examined the gender-transformative potential of interventions to promote male involvement in reproductive health; our analysis provides some initial insights into this.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".