Understanding COVID-19 vaccination decisions during pregnancy and while breastfeeding in a Canadian province
Bibliographic record
Abstract
BACKGROUND: Vaccination in pregnancy is important for preventing illness for mothers and babies; however, vaccine uptake in pregnant individuals is lower than non-pregnant females of fertile age. Given the devastating effects of COVID-19 and the increased morbidity and mortality risk for pregnant individuals, it is important to understand the determinants of vaccine hesitancy in pregnancy. The focus of our study was to explore COVID-19 vaccination among pregnant and breastfeeding individuals and its association with their reasons (psychological factors) for vaccination using the 5C scale and other factors. METHODS: An online survey investigating prior vaccinations, level of trust in healthcare providers, demographic information, and the 5C scale was used for, pregnant and breastfeeding individuals in a Canadian province. RESULTS: Prior vaccinations, higher levels of trust in medical professionals, education, confidence, and collective responsibility predicted increased vaccine uptake pregnant and breastfeeding individuals. CONCLUSIONS: There are specific psychological and socio-demographic determinants that affect COVID-19 vaccine uptake in pregnant populations. Implications of these findings include targeting these determinants when informing and developing intervention and educational programs for both pregnant and breastfeeding individuals, as well as healthcare professionals who are making vaccine recommendations to patients. Study limitations include a small sample and lack of ethnic and socioeconomic diversity.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".