Glancing at School Nutrition Programs from the Perspective of Students: A Case Study of Primary Schools in Eastern Nepal
Bibliographic record
Abstract
INTRODUCTION/BACKGROUND: Developing nutritional awareness is paramount for school children as it significantly influences their knowledge, attitudes, and practices (KAP) towards nutrition, safeguarding them from deficiencies and malnutrition. Schools play a pivotal role in shaping children’s nutritional understanding, fostering positive attitudes, and cultivating healthy practices. Focusing on nutrition-related KAP can instill the right behaviors early on, paving the way for a healthier lifestyle. This approach not only enhances the well-being of children but also lays the foundation for a lifelong commitment to good nutrition, ensuring a healthier and more prosperous future. AIM/OBJECTIVE: The main objective of this study is to compare the Knowledge, Attitude, and Practices (KAP) among male and female school children and assess association of school models/types with KAP in Halesi Tuwachung Municipality of Khotang district, Nepal. METHODOLOGY: A cross-sectional survey in the field site in Eastern Nepal involved 187 school children drawn from four distinct educational institutions, collectively encompassing students enrolled in grades 4, 5, and 6. The data collection utilized a purposive sampling method to enhance the relevance and specificity, thereby ensuring the comprehensiveness and validity of the research findings. RESULTS: The research findings indicated that private institutions, namely YouMe School and Halesi Pathshala (Note 1), displayed notably higher average knowledge scores than public schools such as Shree Mahendradaya Secondary School and Shree Durchhim Secondary School. Furthermore, it was observed that female school students exhibited lower knowledge scores than their male counterparts. Regarding attitudes, no significant disparities were identified between school types, but, on average, female students demonstrated lower attitudes than their male counterparts. Regarding practices, the study revealed that female students tended to exhibit lower levels than their male counterparts. CONCLUSION: The study demonstrated notable differences in Knowledge, Attitudes, and Practices (KAP) concerning nutrition among children enrolled in schools with diverse educational models or types. This research offered valuable insights into how the educational environment across different school settings could influence the nutritional KAP of young students.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".