Cultural and religious structures influencing the use of maternal health services in Nigeria: a focused ethnographic research
Bibliographic record
Abstract
BACKGROUND: Cultural and religious structures encompass a set pattern of values, beliefs, systems and practices that define a community's behaviour and identity. These structures influence women's health-seeking behaviour and access to maternal health services, predisposing women to preventable maternal health complications. However, most maternal health policies have focused on biomedical strategies, with limited attention to women's cultural challenges around childbirth. The overall aim of this paper is to provide a thick description and understanding of cultural and religious structures in Nigeria, their meaning and how they influence women's use of maternal health services. METHODS: Roper and Shapira's (2000) focused ethnography comprising 189 h of observation of nine women from the third trimester to deliveries. Using purposive and snowballing techniques, 21 in-depth interviews and two focus group discussions comprising 13 women, were conducted in two Nigerian primary healthcare facilities in rural and urban area of Kogi State. Data was analyzed using the steps described by Roper and Shapira. RESULTS: Using the PEN-3 cultural model, nine themes were generated. Positive factor, such as the language of communication, existential factor, such as religion, and negative factors, such as the use of prayer houses and lack of women's autonomy, were either positive or negative enablers influencing women's use of maternal health services. Additionally, women's perceptions, such as their dependency on God and reliance on cultural norms were significant factors that influence the use of maternal health services. We also found that the use of herbal medicine was a negative enabler of women's access to facility care. At the same time, family support was also a positive and a negative nurturer that could influence how women use facility care. Finally, factors such as religion, Ibegwu, and male child syndrome were negative nurturers influencing women's contraceptive use. CONCLUSION: Cultural and religious structures are significant factors that could promote or limit women's use of maternal health services. Further studies are needed to understand culturally focused approaches to enhance women's use of maternal health services in Nigeria.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".