Face Mask Use and Associated Factors Among Students: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: COVID-19 has gravely affected the world, including students, due to the high level of contracting infections. OBJECTIVE: This study assessed the magnitude of mask use and associated factors among students. METHODS: A cross-sectional study using mixed methods was conducted among students at Gambella Teachers' Education and Health Science College, Gambella Region, Southwest Ethiopia, from March 5 to March 30, 2021. The stratified random sampling technique was used. Proportional allocation of samples was used to randomly select case teams, and a simple random sampling technique was used to recruit the students. The data were collected by trained and experienced enumerators. Data were entered into EpiData (version 3.1; EpiData Association) and exported to SPSS (version 22; IBM Corp) for analysis. Logistic regression was executed. The adjusted odds ratio (AOR) with the 95% CI was used to determine the association and strength with the outcome variable. The qualitative data were transcribed, translated, coded, and analyzed using thematic analysis. Then, the themes were used to triangulate the quantitative study. RESULTS: The study included a total of 379 participants and yielded a response rate of 95.5% (379/397). The majority of study participants were older than 25 years, with the mean age being 26.34 (SD 5.8) years. This study found that the magnitude of mask use among students was 87% (330/379). The odds of mask use were higher among students who were female (AOR 3.32, 95% CI 1.191-9.248), younger (AOR 2.55, 95% CI 1.155-5.627), agreed that not all persons with COVID-19 develop severe disease (AOR 3.38, 95% CI 1.36-8.41), agreed that there is currently no effective cure (AOR 6.28, 95% CI 1.36-28.99), performed proper washing with soap and water (AOR 0.027, 95% CI 0.004-0.182), had started to stay home (AOR 0.168, 95% CI 0.054-0.52), agreed that COVID-19 is fatal (AOR 0.236, 95% CI 0.084-0.666), agreed that a flu vaccine is sufficient for COVID-19 prevention (AOR 3.874, 95% CI 1.540-9.749), and disinfected equipment and working areas at least once a day (AOR 0.222, 95% CI 0.086-0.575). CONCLUSIONS: This study found that the magnitude of mask use among students was relatively moderate in Ethiopia. Sex, age, agreeing that not all persons with COVID-19 develop severe disease, agreeing that there is currently no effective cure, performing proper washing with soap and water, starting to stay home, agreeing that COVID-19 is fatal, and agreeing that the flu vaccine is sufficient to prevent COVID-19 were independently associated with mask use among students. Therefore, colleges should aggressively encourage students to wear masks and monitor the implementation of COVID-19 prevention regulations along with the accessibility of masks.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".