Adherence to and Motivations for Complying With Public Health Measures Among Adolescents During the Coronavirus Disease (COVID-19) Pandemic in Canada
Bibliographic record
Abstract
Background: Public health measures (e.g., minimizing social interactions, social distancing, and mask wearing) have been implemented in Canada to reduce the transmission of COVID-19. Given that adolescents may be a high-risk demographic for spreading COVID-19, this study investigated adherence to and motivations for complying with public health measures among Canadian youth at two points of the COVID-19 pandemic. Methods: Adolescents ( N = 1,484, 53% girls, M age = 15.73 [ SD = 1.41]) completed an online survey in either Summer 2020 (Cohort 1 [C1]; n = 809, 56% girls) or Winter 2020/2021 (Cohort 2 [C2]; n = 675, 50% girls). We investigated differences in adherence across cohorts using independent sample t -tests and predictors of adherence using a path analysis. Results: Youth engaged in similar levels of social interaction in C1 and C2. Relative to adolescents in C1, adolescents in C2 reported more mask wearing, but less social distancing. Social responsibility was associated with adherence to almost all public health measures across both cohorts, with one exception: it did not predict minimizing social interactions in C2. Not wanting to get sick predicted minimizing social interactions and mask wearing. Concern with population health predicted adherence to all public health measures in C1 and all but mask wearing in C2. Maintaining social ties was negatively associated with minimizing social interactions in both cohorts, and with social distancing in C1. Conclusions: Youth engaged in more mask wearing but less social distancing as the pandemic progressed. Social responsibility and not wanting to get sick were consistent predictors of adherence to most public health measures throughout the pandemic. Youth shifted away from adhering to mask wearing measures due to concern with population health over the course of the pandemic. These results can inform targeted campaigns to bolster compliance with public health measures among adolescents.
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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".