Knowledge, Perception, and Willingness to Enrol in a Health Insurance Scheme: A Survey Among Uninsured Persons in Southern Nigeria
Bibliographic record
Abstract
Background: Out-of-pocket payments for healthcare services hinders the attainment of universal health coverage. Objectives: To assess the current level of knowledge, perception, and willingness to enrol in a health insurance scheme among uninsured persons in Nigeria. Methods: This was a descriptive cross-sectional study conducted among residents of Uyo, a city in southern Nigeria, who had not enrolled in any health insurance scheme Results: About 14.3% (n = 72) of the study participants visited healthcare facilities at least once a week to address medical conditions for either themselves or their dependents. Although 335 (66.5%) of our respondents had heard of health insurance schemes, only 92 (18.3%) claimed to know how they work. Moreover, about 42.3% (n = 213) of our respondent perceived health insurance schemes as being expensive, while 102 (20.2%) considered it a waste of resources. Only 25.4% (n = 128) of the study participants were willing to subscribe to a health insurance scheme. Conclusion: Knowledge of the concept of health insurance as well as awareness of the existence of affordable insurance plans is poor in a significant proportion of the population studied. Many respondents had a poor perception regarding health insurance schemes with the majority unwilling to enrol in one.
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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 | 0.026 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".