Knowledge and Practice of Precautions and Prevention of COVID-19 Among Adolescents in Umuahia, Nigeria: A Cross-Sectional Study
Bibliographic record
Abstract
Background The coronavirus disease 2019 (COVID-19) pandemic has posed significant challenges worldwide, particularly in developing countries with limited healthcare resources. Among the various demographics, adolescents represent a crucial group in understanding and curbing the spread of the virus. Aim This research aims to assess the level of knowledge and practice of COVID-19 prevention measures among adolescents in a developing country. Methodology This study's descriptive cross-sectional study design was appropriate for capturing a snapshot of adolescents' understanding of COVID-19 in Umuahia, Abia State, Nigeria, a developing country. The study's participants were secondary school students in Umuahia's urban and rural secondary schools, aged 10-19. Fisher's formula was used to calculate the sample size. A multistage systematic sampling method was used to select 424 participants. Data were gathered using a self-administered questionnaire. The Statistical Package for the Social Sciences (SPSS) software version 25 (IBM SPSS Statistics, Armonk, NY) was used to handle and evaluate the data that had been obtained. Results All the respondents were aware of COVID-19, primarily informed through social media and television (TV). It is concerning that less than half correctly identify the disease as caused by a virus (46.9%), with some falsely attributing it to bacteria (31.1%) or fungi (15.6%). While the majority of respondents knew about the existence of COVID-19 vaccines, only 63.4% were aware that there was no definitive cure for the disease. The most worrying finding was the limited awareness and practice of recommended precautions to prevent the spread of COVID-19. Handwashing with soap and water, social distancing, and using hand sanitizers were the most frequently recognized precautions. However, even these were poorly practiced, with less than 30% of the respondents following them regularly. It was also noted that misconceptions about precautions exist, including unusual practices such as regularly drinking hot water or eating bitter kola/pepperfruit. Also, the most prominent reason for refusal among the respondents for COVID-19 vaccines was parental refusal, accounting for 57.5% of negative responses. Conclusion The study's findings underscore the urgent need for tailored, accessible, and effective health education strategies to improve adolescents' understanding and adoption of COVID-19 preventive measures in the region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".