Association between Handwashing Knowledge and Practices among the Students in Nepal
Bibliographic record
Abstract
Regular handwashing with soap and running water is one of the effective ways to stop spreading of germs that protects us from the disease. The aim of this study is to assess the handwashing knowledge and practice among the selected school students of Bardiya district in Nepal. To address this objective, the school-based descriptive cross-sectional design was applied. A total of 327 students including 9 to 12 grades were taken from four secondary schools using the multistage sampling technique. The validated self-administrated questionnaires were used to collect the data from the selected students. Similarly, the univariate (frequencies and percentage) and bivariate analyses (chi-square test for association) were performed to analyse the data, using the Statistical Package of Social Science (SPSS) 26 versions. Out of the total participants, 29.7% were between the ages of 15-16 years, 60.9% were male, and the majority (95.7%) were from Hindu. The study showed that 36.9% participants had the poor knowledge relating to handwashing. In contrast, it was found that 43.42% participants were found with the low practice of handwashing, which was higher than the knowledge level of handwashing. So having a good knowledge is not associated with good practices as regards to handwashing. It was noticed that the poor handwashing practice level remains higher as compared to the poor handwashing knowledge level. The study suggests that the schools have the responsibilities to give handwashing education to their students to raise the knowledge as well as the practice level of handwashing.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".