Medical students'self-medication practice and knowledge of over-the-counter medications in south eastern nigeria
Bibliographic record
Abstract
Background : Community health insurance is now seen as a very viable and sustainable pre-payment scheme for individuals in the informal sector, especially those living in rural and semiurban communities in sub-Saharan Africa. This study was conducted to assess the willingness of household heads' to pay premium for community health insurance in a semi-urban community. Methods : This was a descriptive cross-sectional study conducted among 436 household heads in Oghara community using a semi-structured interviewer administered questionnaire for data collection. Results : About a third (31.0 %) of the respondents were in the age group 30-39 years while 24.0 %, 22.0 %, 15.0 % and 8.0 % of them were in the age groups 20-29, 40-49, 50-59; and 60 and above years respectively. Slightly above half (53.0 %) of the respondents were females while 47.0 % of them were males. About three quarter (72.7 %) of the respondents were willing to pay premium and the mean amount of money they were willing to pay as premium was N 514.59 (US Dollar 3.22) monthly. Sex, educational status, monthly income and past health expenditure for health care were factors found to influence the mean amount the respondents were willing to pay as premium. Conclusion : This study brings to the fore a high level willingness to pay premium for community health among household heads. It is therefore imperative that financing arrangements through community health insurance be incrementally scaled-up as a key strategy to achieving sustainable universal health coverage. Keywords : Willingness to pay, community health insurance, premium
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".