Assessment of Food Safety Knowledge among School-Going Adolescents: An Interventional Study
Bibliographic record
Abstract
Background: Recognizing the complex health issues that school-going adolescents face due to ignorance of proper food handling techniques, which impact their general development and severely threaten the health of both the present and future generations in all developing nations. This interventional study aimed to compare food safety knowledge among school-going teenagers (13–15 years) before and after intervention, taking into account the significance of students' health importance in the early adolescent stages. Materials and Methods: The cluster sampling method was used to choose 400 students from four different schools. A food safety intervention education was given online using the Google Meet platform. The World Health Organization's food safety questionnaire was used to gauge participant knowledge of food safety before and after the intervention. A committee of subject matter experts evaluated the research tool's relevance for content validity. Results: Following the implementation of the intervention, significant increases in food safety knowledge were noticed among school-going adolescents in the post-test. A maximum of 81.5% of subjects gained a high-level knowledge regarding food safety after the food safety intervention. Statistics showed that the differences were substantial. After the intervention program, school-aged teenagers' overall understanding of food safety dramatically increased. Conclusion: In order to reduce the health problems caused by unsafe food among school-going teenagers, awareness of food safety must be greatly raised through a variety of food safety training programs in the early stages of adolescence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".