A(H1N1) pandemic influenza and its prevention by vaccination : Paediatricians’ opinions before and after the beginning of the vaccination campaign
Bibliographic record
Abstract
Background: In June 2009, the World Health Organization declared an A(H1N1) influenza pandemic. In October 2009, the largest vaccination campaign in Canadian history began. The aim of this study was to document paediatricians’ knowledge, attitudes and practices (KAP) regarding A(H1N1) pandemic influenza and its prevention by vaccination just after the beginning of the A(H1N1) vaccination campaign and to compare the results with those obtained before campaign initiation. Methods: A self-administered mail-based questionnaire was sent to all Canadian paediatricians. Questionnaires were analyzed in two subsets: those received before and after the beginning of the vaccination campaign. Results: Overall the response rate was 50%. Respondents’ characteristics were comparable between the two subsets. Before the beginning of the campaign, 63% of paediatricians perceived A(H1N1) pandemic infection as a serious disease, that would occur frequently without vaccination compared to more than 75% after. Before the vaccination campaign, half of respondents or less thought that the A(H1N1) vaccine was safe (50%) and effective (35%) compared to 77% and 72% after. The proportion of paediatricians who reported they had received sufficient information on A (H1N1) vaccine increased from 31% before to 73% after the beginning of the vaccination campaign. The majority of respondents intended to get vaccinated against A(H1N1) influenza themselves (84% before and 92% after). Respondents’ intention to recommend the A(H1N1) vaccine to their patients increased from 80% before the beginning of the campaign to 92% after. In multivariate analysis, the main determinants of paediatricians’ intention to recommend the A(H1N1) vaccine were their intention to get vaccinated against A(H1N1) influenza themselves and a belief that A (H1N1) vaccine would be well accepted by health professionals who administer vaccines to the public. Conclusion: Results of this study show important increases in physicians’ level of confidence about A(H1N1) vaccine’s safety and immunogenicity and their willingness to recommend this vaccine to their patients. These changes could be explained, at least partially, by the important effort done by public health authorities to disseminate information regarding A(H1N1) vaccination.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".