Determinants of adherence to COVID-19 preventive behaviours in Canada: Results from the iCARE Study
Bibliographic record
Abstract
Abstract Objective Key to slowing the spread of SARS-Cov-2 is adherence to preventive behaviours promoted through government policies, which may be influenced by policy awareness, attitudes and concerns about the virus and its impacts. This study assessed determinants of adherence to major coronavirus preventive behaviours, including demographics, attitudes and concerns, among Canadians during the first pandemic wave. Methods As part of the iCARE study ( www.iCAREstudy.com ), we weighted data from two population-based, online surveys (April and June, 2020) of Canadian adults. Questions tapped into behaviour change constructs. Multivariate regression models identified determinants of adherence. Results Data from 6,008 respondents (51% female) were weighted for age, sex, and province. Awareness of government policies was high at both time points (80-99%), and adherence to prevention behaviours was high in April (87.5%-93.5%) but decreased over time, particularly for avoiding social gatherings (68.1%). Adherence was worse among men, those aged 25 and under, and those currently working. Aligned with the Health Beliefs Model, perceptions of the importance of prevention behaviours and the nature of people’s COVID-19-related concerns were highly predictive of adherence. Interestingly, health and social/economic concerns predicted better adherence, but having greater personal financial concerns predicted worse adherence at both time points. Conclusion Adherence to COVID-19 prevention behaviours was worse among men, younger adults, and workers, and deteriorated over time. Perceived importance of prevention behaviours measures and health and social/economic concerns predicted better adherence, but personal financial concerns predicted worse adherence. Results have implications for tailoring policy and communication strategies during subsequent pandemic waves.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".