Does free of charge policy increase care-seeking for children under five in Sierra Leone? Evidence from population-based studies from 2008-2016
Bibliographic record
Abstract
Abstract Background In 2010, the Government of Sierra Leone has implemented the Free Health Care Initiative (FHCI) in the country with the objective to reduce under five mortality. The biggest share of this mortality in the country is attributable to infectious diseases. Care-seeking for children under five is a key point to reduce mortality due to infectious diseases as it permits early diagnosis and prompt and correct treatment. The objective of this study was therefore to assess the trend in the prevalence of care-seeking as well as to identify determinants of utilization of healthcare services by under-five (U5) caregivers under the policy initiative. Methods The analysis of care-seeking behavior was done using data from three population-based studies in Sierra Leone (2008-before FHCI and 2013, and 2016-After FHCI). Care-seeking behavior was assessed through care-seeking of caregivers of children U5 with a history of fever in the 2 weeks prior to the survey. We compared the percentages of care-seeking and performed modified Poisson modeling to evaluate the determinants of care-seeking during the period of FHCI (2013–2016). Results In 2008, a total of 1,208 feverish children were identified, as compared with 2,823 children in 2013, and 1,633 in 2016. Fewer children had seeking care for fever in 2008 (51% [95% CI (46.4–55.5)]) than in 2013 (71.5% [95% CI (68.4–74.5)]) and in 2016 (70.3% [95% CI (66.6–73.8)] (p < 0.001)). Care-seeking was low when the household head was a man, when the head of the household was 15–24 years old, when the child was living in a poorest household, in north or west region and when the child was more than one year old. Conclusions The increase of care-seeking in children under five with fever coincided with the initiation of the FHCI in Sierra Leone. Effective interventions to improve the health facilities’ visitation of the children under five should target the identified factors.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".