Why rural women do not use primary health centres for pregnancy care: evidence from a qualitative study in Nigeria
Bibliographic record
Abstract
BACKGROUND: While Primary Health Care has been designed to provide universal access to skilled pregnancy care for the prevention of maternal deaths in Nigeria, available evidence suggests that pregnant women in rural communities often do not use Primary Health Care Centres for skilled care. The objective of this study was to investigate the reasons why women do not use PHC for skilled pregnancy care in rural Nigeria. METHODS: Qualitative data were obtained from twenty focus group discussions conducted with women and men in marital union to elicit their perceptions about utilisation of maternal and child health care services in PHC centres. Groups were constituted along the focus of sex and age. The group discussions were tape-recorded, transcribed verbatim and analyzed thematically. RESULTS: The four broad categories of reasons for non-use identified in the study were: 1) accessibility factors - poor roads, difficulty with transportation, long distances, and facility not always open; 2) perceptions relating to poor quality of care, including inadequate drugs and consumables, abusive care by health providers, providers not in sufficient numbers and not always available in the facilities, long waiting times, and inappropriate referrals; 3) high costs of services, which include the inability to pay for services even when costs are not excessive, and the introduction of informal payments by staff; and 4) Other comprising partner support and misinterpretation of signs of pregnancy complications. CONCLUSION: Addressing these factors through adequate budgetary provisions, programs to reduce out-of-pocket expenses for maternal health, adequate staffing and training, innovative methods of transportation and male involvement are critical in efforts to improve rural women's access to skilled pregnancy care in primary health care centres in the country.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".