Understanding COVID-19 vaccine hesitancy during parenthood in British Columbia
Bibliographic record
Abstract
INTRODUCTION: COVID-19 vaccine uptake was significantly lower in children under 12 when compared with adults. Vaccine hesitancy was a potential key contributor to the challenges faced in COVID-19 vaccine uptake METHODS: An online cross-sectional survey was conducted across British Columbia, Canada, from October to December 2021 to understand the COVID-19 vaccine perceptions of parents of children under 12 years of age. Participants completed a modified version of the Vaccine Hesitancy Scale (VHS). Logistic regression models were used to identify factors associated with parental vaccine hesitancy and to explore the relationship between parental vaccine intentions and vaccine hesitancy RESULTS: A total of 993 parents participated in the study. One-half of parents (52.1 %) were vaccine hesitant for pediatric COVID-19 vaccines. For every additional child under 12 in a household, parents were more hesitant (adjusted odds ration [aOR] 1.69, 95 % Confidence Interval [CI] 1.28-2.24). Vaccinated parents (aOR 0.01, 95 % CI 0.004-0.02 vs. unvaccinated parents) and parents of children immunized for influenza (aOR 0.18, 95 % CI 0.12-0.29 vs. parents of children not immunized for influenzas) were less likely to be hesitant. Participants who received a COVID-19 vaccine recommendation from their healthcare provider were also less likely to be hesitant (aOR 0.37, 95 % CI 0.18-0.79). Vaccine hesitant parents were less likely to intend to vaccinate their child when compared with a parent who was not vaccine hesitant (aOR 0.001, 95 % CI 0.0004-0.005) CONCLUSION: The findings from this study identify factors influencing COVID-19 vaccine decision-making, supporting the application of the VHS in clinical practice to allow for more strategic implementation of vaccine-promotion resources.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".