National health insurance scheme enrolment and antenatal care among women in <scp>G</scp>hana: is there any relationship?
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to examine whether enrolment in the National Health Insurance Scheme (NHIS) affects the likelihood and timing of utilising antenatal care among women in Ghana. METHODS: Data were drawn from the Ghana Demographic and Health Survey, a nationally representative survey collected in 2008. The study used a cross-sectional design to examine the independent effects of NHIS enrolment on two dependent variables (frequency and timing of antenatal visits) among 1610 Ghanaian women. Negative binomial and logit models were fitted given that count and categorical variables were employed as outcome measures, respectively. RESULTS: Regardless of socio-economic and demographic factors, women enrolled in the NHIS make more antenatal visits compared with those not enrolled; however, there was no statistical association with the timing of the crucial first visit. Women who are educated, living in urban areas and are wealthy were more likely to attend antenatal care than those living in rural areas, uneducated and from poorer households. CONCLUSION: The NHIS should be strengthened and resourced as it may act as an important tool for increasing antenatal care attendance among women in Ghana.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".