COVID-19 vaccine acceptance and uptake among caregivers of children aged 5–11 years in Ontario, Canada: A cross-sectional survey
Bibliographic record
Abstract
INTRODUCTION: Although COVID-19 vaccine safety in 5-11-year-old children has been documented, half of Ontarian children this age remain unvaccinated. This study aimed to assess caregivers' vaccine acceptance for 5-11-year-old children and identify factors associated with vaccine non-acceptance. METHODS: A multi-language self-administered survey was sent to caregivers of 5-11-year-old children through schools and community health centers within the Greater Toronto Area from April-July 2022. Sociodemographic characteristics and immunization behaviours were collected for caregivers, their 5-11-year-old children, and any older siblings. The primary outcome, COVID-19 vaccine acceptance, was previous uptake of COVID-19 vaccine or caregiver intent to vaccinate for their 5-11-year-old child. Data were analyzed using descriptive statistics and multivariable logistic regression. RESULTS: In total, 807 caregivers were included in analysis. Although 93 % of caregivers had received two doses of COVID-19 vaccine, 77 % had a 5-11-year-old child who received at least one dose of vaccine. Caregivers age was associated with vaccine acceptance (vs. < 40 years; adjusted odds ratio [aOR] 2.1, 95 % confidence interval [CI] 1.4-3.1 for ages 40-49; aOR 2.8, 95 % CI 1.1-7.1 for ages ≥50 years). Immunization factors associated with vaccine acceptance included caregiver COVID-19 vaccination (aOR 38.1 vs. unvaccinated caregivers; 95 % CI 15.8-92.3), older siblings COVID-19 vaccination (aOR 49.2 vs. unvaccinated siblings; 95 % CI 18.3-132.3), and recent influenza vaccination for the child (aOR 6.9 vs. no influenza vaccine; 95 % CI 4.6-10.5). Among 189 caregivers with unvaccinated 5-11-year-old children, the most common reasons for non-acceptance were concerns about long-term side effects (59 %), lack of experience vaccinating children (41 %), and concerns that vaccines were developed too quickly (39 %). CONCLUSION: Acceptance of COVID-19 vaccination for 5-11-year-old children were associated with caregiver vaccine behaviors and sociodemographic factors. These findings highlight groups of caregivers that can be targeted for educational interventions and concerns that may be addressed to increase vaccine confidence.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".