Knowledge, Perceptions, and Self-Reported Rates of Influenza Immunization among Canadians at High Risk from Influenza: A Cross-Sectional Survey
Bibliographic record
Abstract
The Public Health Agency of Canada recommends that 80% of high-risk persons, including adults aged ≥65 years and 18-64 years with certain comorbidities, be vaccinated against influenza. During the 2022-2023 influenza season, we conducted an online survey of 3000 Canadian residents aged ≥18 years randomly recruited from the Léger Opinion (LEO) consumer panel to assess knowledge and perceptions about influenza vaccination as well as survey self-reported vaccination rates. Overall, 47.3% received an influenza vaccination during the 2022-2023 season. Vaccination rates among persons aged 18-64 years with high-risk medical conditions (n = 686) and among adults aged ≥65 years (n = 708) were 46.4% and 77.4%, respectively; 77.8% and 88.5%, respectively, believed influenza vaccination was important for people at high risk from influenza. Only 35.8% of adults aged 18-64 years with comorbidities were aware of being at high risk; 66.0% of this group was vaccinated against influenza, compared with 37.0% of those unaware of being at high-risk. During 2022-2023, 51.3% of people aged ≥65 years and 43.0% of people aged 18-64 years with comorbidities discussed influenza vaccination with healthcare providers. These findings suggest gaps in education regarding the importance of influenza vaccination among people at risk of influenza complications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".