Home births in the context of free health care: The case of Kaya health district in Burkina Faso
Bibliographic record
Abstract
OBJECTIVE: To identify the factors associated with home births in the Kaya health district in Burkina Faso, where child delivery was free of charge between 2007 and 2011. METHODS: Both qualitative and quantitative data were collected from the Kaya Health and Demographic Surveillance System (Kaya HDSS) among women who delivered at home or in a health facility between January 2008 and December 2010. Multilevel logistic regression was applied to quantitative data, while the qualitative data were analyzed thematically based on emerging themes, subthemes, and patterns across group and individual cases. RESULTS: The findings indicate that 12% (n=311) of childbirths occurred at home (n=2560). Key factors associated with home birth were age, distance from the household to the primary health center, and prenatal visits. The qualitative analysis showed that immediate child delivery, previous experience of giving birth at home, negative experiences with health centers, fear of cesarean delivery, and lack of transport are key predictors of home births. CONCLUSION: Though relevant, addressing the financial barrier to health care is not enough. Additional measures are necessary to further reduce the rate of home births.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".