Association of COVID-19 Government-Instituted Mask Mandates With Incidence of Mask Use Among Children in Alberta, Canada
Bibliographic record
Abstract
Importance: To help prevent the spread of SARS-CoV-2, government-instituted nonpharmaceutical interventions (eg, social distancing, mask use, isolating), a provincewide government-instituted mask mandate occurred on December 8, 2020, in Alberta, Canada, although some local jurisdictions implemented an earlier mask mandate. There remains a limited understanding of the association between government-implemented public health measures and individual health behaviors of children. Objective: To examine the association between government mask mandates and mask use among children in Alberta, Canada. Design, Setting, and Participants: A cohort of children from Alberta, Canada, was recruited to examine longitudinal SARS-CoV-2 serologic factors. Parents were prospectively asked about their child's mask use in public places every 3 months (5-point Likert scale: never to always) from August 14, 2020, to June 24, 2022. A multivariable logistic generalized estimating equation was used to examine government mandatory masking mandates and child mask use. Child mask use was operationalized into a single composite dichotomous outcome by grouping parents who reported their child often or always wore a mask vs those who reported their child never, rarely, or occasionally wore a mask. Exposures: The primary exposure variable was the government masking mandate (began on different dates in 2020). The secondary exposure variable was government private indoor and outdoor gathering restrictions. Main Outcomes and Measures: The primary outcome was parent report of child mask use. Results: A total of 939 children participated (467 female [49.7%]; mean [SD] age, 10.61 [1.6] years). The odds of parents' report of child mask use (often or always) was 18.3 times higher (95% CI, 5.7-58.6; P < .001; risk ratio, 1.7; 95% CI, 1.5-1.8; P < .001) with the mask mandate on compared with the mask mandate off. There was no significant change in mask use over the course of the mask mandate due to time. In contrast, each day with the mask mandate off was associated with a 1.6% decrease in mask use (odds ratio, 0.98; 95% CI, 0.98-0.99; P < .001). Conclusions and Relevance: The results of this study suggest that government-mandated mask use and providing the public with up-to-date health information (eg, case counts) is associated with increased parent-reported child mask use, while increasing time without a mask mandate is associated with decreased mask use.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".