Healthcare providers and Caregivers’ perspectives on factors underlying the persistent malnutrition of Children aged 0-59 months in Buhweju district, southwestern Uganda
Bibliographic record
Abstract
Abstract Background The nutritional well-being of infants and young children is influenced by economic, environmental and maternal factors that range from food intake, health, sanitation and care. All regions of Uganda have registered unacceptably high levels of childhood malnutrition over the years, although with an uneven distribution across regions. This study assessed health provider and caregiver perspectives on factors responsible for persistent malnutrition among children aged 0-59 months in Engaju and Nyakishana sub counties in Buhweju district.Methods In this phenomenological qualitative study, we conducted six Focus group discussions with Village Health Team members and care takers of children aged 0-59 months in Engaju and Nyakishana sub-counties and two key informant interviews with two members of the district health team to explore their perceptives on the factors responsible for persistent malnutrition in Buhweju District in May 2018. Data were thematically analyzed manually and using Atals Ti 7.5Results Historical and geographical challenges, poverty and economic occupation, parental alcoholism and domestic violence as well as inadequate childcare services were identified as factors responsible for persistent malnutrition among children aged 0-59 months in Engaju and Nyakishana sub counties in Buhweju district Conclusion Persistent malnutrition in children aged 0-59 months in Buhweju district is mainly due to historical and geographical challenges and its associated factors that include poverty and economic occupation, parental alcoholism and domestic violence and inadequate childcare services . Addressing these factors from the grassroots up through, multisectoral collaboration between infrastructure, Agriculture, Education and health, engaging communities and effective policy changes and implementation has the potential to improve the nutrition status of children in Buhweju district
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".