COVID-19 Vaccine Uptake, Sources of Information and Side Effects Reported by Pregnant Women in Western Australia: Cross-Sectional Cohort Survey
Bibliographic record
Abstract
BACKGROUND: Pregnant women are a priority group for COVID-19 vaccination due to their vulnerability as a high-risk cohort. However, the current pregnancy uptake rate for the COVID-19 vaccination in Western Australia remains largely unknown. OBJECTIVE: This study aimed to explore pregnant women's uptake rates, information sources and experience of vaccination against COVID-19 during pregnancy. We hypothesise that uptake of vaccination among pregnant women is higher than indicated in previous studies given different disease burden and different public health restrictions at time when data was collected. METHODS: A cross-sectional survey was administered electronically to maternity patients at a single tertiary metropolitan hospital in Perth, Western Australia. RESULTS: Five hundred and two women participated in the study. Overall, antenatal COVID-19 vaccination rate was 79% [n=398]. One half [51%, n=256] of all the women felt well informed, and information was sourced primarily from their General Practitioner [GP] [60%, n=301], midwives [35%, n=174] and obstetric doctors [13%, n=64]. Women with non-Caucasian ethnicity [34%, n=170 vs. 66%, n=332, p=0.073] and 'country of birth outside Australia' [47%, n=235] reported lower rates of vaccine information provision by hospital staff [34%, n=22 vs 66%, n=42, P = 0.04]. CONCLUSIONS: The COVID-19 vaccine uptake was encouragingly high in our study with favourable attitudes and acceptance for the vaccine from majority of pregnant women. This self-reported study also identified opportunities for enhanced cultural competence and further education and training for hospital staff on COVID-19 vaccine information provision to ethnically diverse women. Further studies examining such interventions are warranted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".