Contextual factors as a key to understanding the heterogeneity of effects of a maternal health policy in Burkina Faso?
Bibliographic record
Abstract
Burkina Faso implemented a national subsidy for emergency obstetric and neonatal care (EmONC) covering 80% of the cost of normal childbirth in public health facilities. The objective was to increase coverage of facility-based deliveries. After implementation of the EmONC policy, coverage increased across the country, but disparities were observed between districts and between primary healthcare centres (PHC). To understand the variation in coverage, we assessed the contextual factors and the implementation of EmONC in six PHCs in a district. We conducted a contrasted multiple case study. We interviewed women (n = 71), traditional birth attendants (n = 7), clinic management committees (n = 11), and health workers and district health managers (n = 26). Focus groups (n = 62) were conducted within communities. Observations were carried out in the six PHCs. Implementation was nearly homogeneous in the six PHCs but the contexts and human factors appeared to explain the variations observed on the coverage of facility-based deliveries. In the PHCs of Nogo and Tara, the immediate increase in coverage was attributed to health workers' leadership in creatively promoting facility-based deliveries and strengthening relationships of trust with communities, users' positive perceptions of quality of care and the arrival of female professional staff. The change of healthcare team at Iata's PHC and a penalty fee imposed for home births in Belem may have caused the delayed effects there. Finally, the unchanged coverage in the PHCs of Fati and Mata was likely due to lack of promotion of facility-based deliveries, users' negative perceptions of quality of care, and conflicts between health workers and users. Before implementation, decision-makers should perform pilot studies to adapt policies according to contexts and human factors.
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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 | 0.001 | 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".