Bed net use and associated factors in a rice farming community in Central Kenya
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Use of insecticide-treated nets (ITNs) continues to offer potential strategy for malaria prevention in endemic areas. However their effectiveness, sustainability and massive scale up remain a factor of socio-economic and cultural variables of the local community which are indispensable during design and implementation stages. METHODS: An ethnographic household survey was conducted in four study villages which were purposefully selected to represent socio-economic and geographical diversity. In total, 400 households were randomly selected from the four study villages. Quantitative and qualitative information of the respondents were collected by use of semi-structured questionnaires and focus group discussions. RESULTS: Malaria was reported the most frequently occurring disease in the area (93%) and its aetiology was attributed to other non-biomedical causes like stagnant water (16%), and long rains (13%). Factors which significantly caused variation in bed net use were occupant relationship to household head (chi2 = 105.705; df 14; P = 0.000), Age (chi2 = 74.483; df 14; P = 0.000), village (chi2 = 150.325; df 6; P = 0.000), occupation (chi2 = 7.955; df 3; P = 0.047), gender (chi2 = 4.254; df 1; P = 0.039) and education levels of the household head or spouse (chi2 = 33.622; df 6; P = 0.000). The same variables determined access and conditions of bed nets at household level. Protection against mosquito bite (95%) was the main reason cited for using bed nets in most households while protection against malaria came second (54%). Colour, shape and affordability were some of the key potential factors which determined choice, use and acceptance of bed nets in the study area. CONCLUSION: The study highlights potential social and economic variables important for effective and sustainable implementation of bed nets-related programmes in Sub-Saharan Africa.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it