Maintaining the momentum: Key factors influencing acceptance of influenza vaccination among pregnant women following the H1N1 pandemic
Bibliographic record
Abstract
This survey study compared pre- and post-pandemic knowledge, attitudes, beliefs, and intended behaviors of pregnant women regarding influenza vaccination (seasonal and/or pandemic) during pregnancy in order to determine key factors influencing their decision to adhere to influenza vaccine recommendations. Only 36% of 662 pre-pandemic respondents knew that influenza was more severe in pregnant women, compared to 62% of the 159 post-pandemic respondents. Of the pre-pandemic respondents, 41% agreed or strongly agreed that that it was safer to wait until after the first 3 months to receive the seasonal influenza vaccine, whereas 23% of the post-pandemic cohort agreed or strongly agreed; 32% of pre-pandemic participants compared to 11% of post-pandemic respondents felt it was best to avoid all vaccines while pregnant. Despite 61% of the pre-pandemic cohort stating that they would have the vaccine while pregnant if their doctor recommended it and 54% citing their doctor/nurse as their primary source of vaccine information, only 20% said their doctor discussed influenza vaccination during their pregnancy, compared to 77% of the post-pandemic respondents who reported having this conversation. Women whose doctors discussed influenza vaccine during pregnancy had higher overall knowledge scores (P<0.0001; P=0.005) and were more likely to believe the vaccine is safe in all stages of pregnancy (P<0.0001; P=0.001) than those whose doctors did not discuss influenza vaccination. The 2009 H1N1 pandemic experience appeared to change attitudes and behaviours of health care providers and their pregnant patients toward influenza vaccination.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".