SARS-CoV-2 vaccine acceptance among caregivers of children younger than five years of age: A cross-sectional survey in Toronto
Bibliographic record
Abstract
Background: Despite severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine approval in Canada for children six months to five years old, vaccine acceptance for this age group remains low compared with other age groups. This study aimed to assess vaccine acceptance among caregivers of children younger than five years old and to identify factors associated with SARS-CoV-2 vaccine hesitancy in Toronto. Methods: A multi-language self-administered survey was sent to caregivers of children attending 660 Toronto schools and two community health centres between April 5 to July 4, 2022. Data on socio-demographic characteristics, acceptance of routine childhood and influenza vaccines and current SARS-CoV-2 vaccine status for parents and older siblings were collected. Results: A total of 253 caregivers of children younger than five years old answered the survey. Although 234 (94%) of the responding caregivers were fully vaccinated against SARS-CoV-2 and more than 90% had their children older than five years receiving one dose of the vaccine, only 148 (59%) had intentions to vaccinate their child younger than five years old. Conclusion: These findings highlight the importance of interventions to increase vaccine confidence among caregivers of children aged younger than five years old.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".