Influenza Vaccination and Intention to Receive the Pandemic H1N1 Influenza Vaccine among Healthcare Workers of British Columbia, Canada: A Cross-Sectional Study
Bibliographic record
Abstract
OBJECTIVE: To assess healthcare workers' attitudes and concerns regarding seasonal and pandemic influenza vaccines in order to improve vaccination campaign communications. DESIGN: Cross-sectional survey. SETTING: All 6 health authorities in British Columbia, Canada. METHODS: An anonymous, self-administered online survey was conducted from August 30 through September 30, 2009. Question topics included demographic characteristics, factors influencing acceptance of seasonal influenza vaccine, factors influencing intentions to accept pandemic H1N1 influenza vaccine, and knowledge and concerns regarding the effect of the influenza pandemic. PARTICIPANTS: All 96,217 British Columbia healthcare workers were eligible to participate. RESULTS: A volunteer sample of 4,046 healthcare workers returned the survey; 3,563 (88%) were women, 58% were under 50 years old (mean age + or - standard deviation, 45.3 + or - 10.9 years), 3,152 of 4,023 (79%) had 5 or more years of experience in their profession, 1,853 of 4,023 (46%) were nurses, and 2,833 (70%) had been vaccinated against seasonal influenza the previous year. Two thousand eight hundred (69%) respondents reported intending to receive the pandemic H1N1 vaccine. The most important predictor of this intention was having received the seasonal vaccine the previous year (odds ratio [OR], 6.25 [95% confidence interval {CI}, 5.39-7.26]). Worry about making loved ones ill was the only attitude associated with intention to receive the pandemic H1N1 vaccine (adjusted OR, 1.38 [95% CI, 1.27-1.50]). Concerns with vaccine safety (adjusted OR, 0.31 [95% CI, 0.25-0.39]) and belief "that H1N1 is not severe enough" (adjusted OR, 0.29 [95% CI, 0.26-0.32]) were independently associated with the intention to reject the pandemic H1N1 vaccine. CONCLUSIONS: Vaccination campaigns for pandemic H1N1 vaccine should use messages that emphasize the risk of illness among younger people and the opportunity to protect loved ones by getting the vaccine and should address concerns about the safety and effectiveness of the vaccine.
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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 | 0.003 | 0.008 |
| 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 | 0.000 | 0.000 |
| 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".