Effect of a comic story on orphan children's knowledge and hand washing practice about pandemic of COVID-19
Bibliographic record
Abstract
World Health Organization (WHO) declared COVID-19 as a pandemic in 11th of March 2020. COVID-19 that disrupts Children’s growth and development, friendships, daily routines and has a negative consequence for their well-being, development and protection. About 1 in 3 children hospitalized with COVID-19 in the United States were admitted to the intensive care unit. Aim: The aim of this study was evaluating the effect of a comic story on children’s knowledge and hand washing practices about pandemic of COVID-19. Study design: A quasi-experimental design was used. Setting: Nour Al-Huda Charitable Society that caring males and females orphaned children in separate setting Sample: A convenient sample including all children in the orphanage, there was 41 children and their age range between 3 to less than 12 years. Tools of data collection: An interview questionnaire sheet as a tool one that had two parts first one concerned with sociodemographic data of children and second one assessed children’s knowledge about pandemic of COVID-19, an observational check list sheet as a tool two and had two parts; where part one assessed facilities required for applying precautionary measures inside the home, while part two assessed children’s hand washing practice inside the home. Results: there was a statistically significant differences between the total children’s knowledge regarding COVID-19 and total observed practice score regarding correct technique of hand washing pre/post comic story implementation. Conclusion: It was concluded that the implementation of a comic story had improved children’s total mean score of knowledge and hand washing practice regarding COVID-19 with statistically significant differences of both in relation to pre and post comic story implementation. Recommendations: The study recommended that to breakdown the ring of transmission of COVID-19; the collaboration between governmental and non-governmental agencies and stakeholders are main supporters for those children via appropriate and friendly communication tools that improve their knowledge; practice and also providing those setting by funding and resources for applying precautionary measures of COVID-19 with periodical follow up for personals, setting, services and resources.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".