Préfinancement communautaire : le consentement à payer des ménages pour les soins de santé primaires au Bénin
Bibliographic record
Abstract
OBJECTIVES: This study aims to determine factors associated with Benin rural households' willingness to pre-finance their primary health care. METHODS: This study was conducted in Sèmè-Podji, Department Ouémé Benin. The contingent valuation method, namely "bidding game" or "dichotomous choice" was used to determine the willingness to pay for health care. We conducted a probit regression analysis on a sample of 150 rural households. RESULTS: The value of household willingness to pre-finance their primary health care is between 6,000 and 12,000 FCFA per person per year with a median value of 8,000 FCFA/person/year. This value is determined by several factors. Income level, age, usage patterns of health services and promptness in receiving patients have a positive impact on the households' willingness to pay for their health care. The physical characteristics of health centers seem to constitute a barrier to the willingness to pay for health care. CONCLUSION: The pre-financing of health care by households is determined by socio-economic characteristics as well as physical characteristics of health centers.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".