Lay knowledge and management of malaria in Baringo county, Kenya
Bibliographic record
Abstract
BACKGROUND: Malaria, a disease caused by protozoan parasites of the genus Plasmodium and transmitted by female anopheline mosquitoes, is a major cause of morbidity, mortality and loss in productivity in humans. Baringo County is prone to seasonal transmissions of malaria mostly in the rainy seasons. METHODS: This cross-sectional study used a mixed methods approach to collect data on knowledge and lay management of malaria. A questionnaire survey was administered to 560 respondents while qualitative data was collected through 20 focus group discussions in four ecological zones covering Baringo North, Baringo South and Marigat sub-Counties of Baringo County. Analyses were done through summary and inferential statistics for quantitative data and content analysis for qualitative data. RESULTS: The study communities were knowledgeable of malaria signs, symptoms, cause and seasonality but this biomedical knowledge co-existed with other local perceptions. This knowledge, however, did not influence their first (p = 0.77) or second choice treatments (p = 0.49) and compliance to medication (p = 0.84). Up to 88 % of respondents reported having suffered from malaria. At the onset of a suspected malaria case community members reported the following: 28.9 % visited a health facility, 37.2 % used analgesics, 26.6 % herbal treatments, 2.2 % remnant malaria medicines, 2.2 % over the counter malaria medicines, 1 % traditional healers and 1.8 % other treatments. Nearly all respondents (97.8 %) reported visiting a health facility for subsequent treatments. Herbal treatments comprised of infusions and decoctions derived from roots, barks and leaves of plants believed to have medicinal value. Compliance to conventional malaria treatment regime was, however, identified as a challenge in malaria management. Quick relief from symptoms, undesirable qualities like drug bitterness and bad smell, undesirable side-effects, such as nausea and long regimen of treatment were some of the contributors to non-compliance. Men and women exhibited different health-seeking behaviours based on the cultural expectations of masculinity, femininity, gender roles and acceptability of health services. CONCLUSIONS: While knowledge of malaria is important in identifying the disease, it does not necessarily lead to good management practice. Treatment-seeking behaviour is also influenced by perceived cause, severity of disease, timing, anticipated cost of seeking treatment and gender, besides the availability of both traditional and conventional medicines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".