Support for mask use as a COVID-19 public health measure among a large sample of Canadian secondary school students
Bibliographic record
Abstract
BACKGROUND: Youth voice has been largely absent from deliberations regarding public health measures intended to prevent SARS-CoV-2 transmission, despite being one of the populations most impacted by school-based policies. To inform public health strategies and messages, we examined the level of student support of mask use in public spaces and school mask requirements, as well as factors associated with students' perspectives. METHODS: We used cross-sectional survey data from 42,767 adolescents attending 133 Canadian secondary schools that participated in the COMPASS study during the 2020/2021 school year. Multinomial regression models assessed support for i) wearing a mask in indoor public spaces and ii) schools requiring students to wear masks, in association with COVID-19 knowledge, concerns, and perceived risk. RESULTS: Wearing masks in indoor public spaces was supported by 81.9% of students; 8.7% were unsupportive and 9.4% were neutral/undecided. School mask requirements were supported by 67.8%, with 23.1% neutral and 9.1% unsupportive. More females supported mask wearing in public spaces (83.9% vs. 79.1%) and school mask requirements (70.8% vs. 63.5%) than males. Students had increased odds of supporting mask use in public spaces and school mask requirements if they reported concerns about their own or their family's health, had discussions regarding ways to prevent infection, perceived COVID-19 to be a risk to young people, and knew that signs are not always present in COVID-19 cases and that masks prevent SARS-CoV-2 transmission if someone coughs. CONCLUSIONS: During the year following the beginning of the pandemic, most students supported the required use of masks in schools and wearing masks in indoor public spaces. Improving knowledge around the effectiveness of masks appears likely to have the largest impact on mask support in adolescent populations among the factors studied.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".