Understanding national trends in COVID-19 vaccine hesitancy in Canada: results from five sequential cross-sectional representative surveys spanning April 2020–March 2021
Bibliographic record
Abstract
OBJECTIVE: To examine rates of vaccine hesitancy and their correlates among Canadian adults between April 2020 and March 2021. DESIGN: Five sequential cross-sectional age, sex and province-weighted population-based samples who completed online surveys. SETTING: Canada. PARTICIPANTS: A total of 15 019 Canadians aged 18 years and over were recruited through a recognised polling firm (Leger Opinion). Respondents were 51.5% female with a mean age of 48.1 (SD 17.2) years (range 18-95 years) and predominantly white (80.8%). PRIMARY AND SECONDARY OUTCOME MEASURES: Rates of vaccine hesitancy over the five surveys (time points) and their sociodemographic, clinical and psychological correlates. RESULTS: A total of 42.2% of respondents reported some degree of vaccine hesitancy, which was lowest during surveys 1 (April 2020) and 5 (March 2021) and highest during survey 3 (November 2020). Fully adjusted multivariate logistic regression analyses revealed that women, those aged 50 and younger, non-white, those with high school education or less, and those with annual household incomes below the poverty line in Canada were significantly more likely to report vaccine hesitancy, as were essential and healthcare workers, parents of children under the age of 18 and those who do not get regular influenza vaccines. Endorsing prevention behaviours as important for reducing virus transmission and high COVID-19 health concerns were associated with 77% and 54% reduction in vaccine hesitancy, respectively. Having high personal financial concerns was associated with 1.33 times increased odds of vaccine hesitancy. CONCLUSIONS: Results highlight the importance of targeting vaccine efforts to specific groups by emphasising the outsized health benefits compared with risks of vaccination. Future research should monitor changes in vaccine intentions and behaviour to better understand underlying factors.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".