Attitudes, Beliefs, and Self-Reported Rates of Influenza and COVID-19 Vaccinations in the Canadian 2023–2024 National Influenza and Respiratory Viruses Survey
Bibliographic record
Abstract
Background: We conducted a cross-sectional, online survey of adult Canadian residents to evaluate their attitudes and beliefs about vaccination against respiratory viruses, particularly influenza and coronavirus 2019 (COVID-19). Methodology: Survey participants aged ≥ 18 years were randomly recruited from the Léger Opinion (LEO) consumer panel. Results: Out of 3002 respondents, 76% reported being “up-to-date” on all of their recommended vaccinations, 86% reported understanding why the influenza vaccine was needed annually, 79% reported believing the influenza vaccine was safe, and 83% reported understanding that vaccines, in general, were important for health. However, only 49% reported receiving the influenza vaccine in the fall of 2023, and 46% received a COVID-19 vaccine (68% of those who received one received the other). More than half of the respondents (55%) reported that they found it difficult to keep track of which vaccines were recommended for them, while 74% indicated that they valued the opinion of their healthcare provider (HCP) when deciding whether to be vaccinated against influenza, and 73% said they would not hesitate to receive multiple vaccines at the same time if their HCP recommended it. Conclusions: These findings highlight the ongoing need for education and outreach in Canada.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".