UPTAKE OF INFLUENZA VACCINE IN PREGNANT WOMEN IN GEORGIA IN 2020-2021
Bibliographic record
Abstract
Utilization of influenza vaccine among pregnant women in Georgia remains suboptimal. To uncover some of the contributing factors to low uptake of influenza vaccine among pregnant women in Georgia. A cross-sectional survey was conducted in Spring-Summer 2021 on the postpartum women as the focus population. Females >18 years old were asked to complete the survey. The survey contained 14 items. The questions were categorized into 5 main groups. A total of 200 surveys were delivered to the hospitals. Survey results reveal that regnant women’s awareness and attitudes regarding the Influenza vaccination were subpar and not conductive to reliable efforts in optimal vaccine uptake. While the absolute majority of the study subjects confirmed that they had heard about the Influenza vaccine, less than a quarter of them accepted to be immunized. Importantly, half of the responders discussed the subject of immunization with their healthcare provider, however, had not made the final decision for vaccination. There is meaningful space to encourage pregnant women’s awareness and education on benefits and safety of influenza vaccination during pregnancy. This is preferable to be performed through the education and information campaigning conducted by health care providers working in perinatal care facilities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".