A Peer-Led Pulse-based Nutrition Education Intervention Improved School-Aged Children’s Knowledge, Attitude, Practice (KAP) and Nutritional Status in Southern Ethiopia
Bibliographic record
Abstract
Background: Peer-led nutrition education intervention on promoting locally available pulses among school-aged children could be one strategy to overcome child malnutrition in poor communities. Objectives: This study was aimed at assessing the effect of a peer-led pulse nutrition education intervention on knowledge, attitude, practice of pulse consumption and nutritional status among 202 school children.Methods: School based randomized controlled trial was conducted among 202 (101 control and 101 cases). School age children were selected from the two groups using simple random sampling technique. Baseline data were collected from 1st May to 15th May, 2016. Six month peer led nutrition intervention was provided for the study subjects. Pre-test, post-test and anthropometric measurements (weight and height) were conducted at baseline and end of the intervention. Statistical tests such as independent two samples t-test were employed. World Health Organization (WHO) Anthrop Plus software version 1.0.4 was used to calculate anthropometric indices. Results: The mean diet diversity score was significantly (P<0.001) improved from 2.78 (0.96) to 3.60 (1.10) after a six month intervention in the intervention group. The independent two samples t-test showed significant differences (p<0.001) in knowledge, attitude and practice mean scores of school age children about pulse preparation and consumption. There was no significant difference in nutritional status: BAZ (p=0.774) and HAZ (p=0.516) of school age children between the intervention and control groups at baseline. Post-intervention showed significant (p=0.01) differences between intervention and control schools in BAZ mean score of the children which was reflected in significantly (P<0.001) decreased prevalence of thinnessConclusion: The study concluded that peer led education strategy provides an opportunity to reduce malnutrition and its impacts if properly designed, including the use of behavioural change mode.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".