Factors associated with parental intentions to vaccinate 0-4-year-old children against COVID-19 in Canada: a cross-sectional study using the Childhood COVID-19 Immunization Coverage Survey (CCICS)
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to determine the factors associated with low or no parental intention to vaccinate children of 0-4-years in Canada with a COVID-19 vaccine through the 2022 Childhood COVID-19 Immunization Coverage Survey (CCICS). The CCICS was conducted prior to the introduction of a COVID-19 vaccine and a vaccine recommendation for this age group. METHODS: Simple and multiple logistic regression models were used to determine associations between sociodemographic factors as well as knowledge, attitudes and beliefs and low/no intentions to vaccinate against COVID-19 among parents of children 0-4 years. RESULTS: Factors associated with low intentions to vaccinate children against COVID-19 included being male (aOR: 2.0; 95% CI: 2.0‒2.1) compared to female; being 30-39 (aOR 1.1; 95% CI: 1.1‒1.2) compared to 40+; being Black (aOR: 2.3, 95% CI: 2.2‒2.5), East/Southeast Asian (aOR: 3.6, 95% CI: 3.3‒3.8), or having multiple ethnicities (aOR: 1.3, 95% CI: 1.1‒1.6) compared to White European ethnicity; living in a rural (aOR: 2.0, 95% CI: 1.9‒2.1) compared to urban community; having a total 2021 household income of $60,000‒$79,999 CAD (aOR: 1.4, 95% CI: 1.3‒1.5) compared to $150,000 CAD and above; and trusting government bodies (aOR: 2.4; 95% CI: 1.1‒1.2), international bodies (aOR: 2.4; 95% CI: 2.2‒2.5), or media (aOR: 2.0, 95% CI: 1.9‒2.2) for information about COVID-19 vaccines compared to health care providers. CONCLUSIONS: The findings of this study demonstrate that several sociodemographic factors and parental beliefs impact the decision to vaccinate children 0-4 years of age against COVID-19. Future research should focus on sociodemographic barriers to vaccination and how to most appropriately tailor the delivery of vaccination programs to specific groups, in an effort to narrow the gap between intentions and uptake of COVID-19 vaccination in younger children. As well, messaging should specifically be targeted to parents who have lower confidence in the COVID-19 vaccine and the government to provide correct information and build trust.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".