Confidence and barriers: Analysis of factors associated with timely routine childhood vaccination in Canada during the COVID-19 pandemic
Bibliographic record
Abstract
Routine childhood vaccination is a crucial component of public health in Canada and worldwide. To facilitate catch-up from the global decline in routine vaccination caused by the COVID-19 pandemic, and toward the ongoing pursuit of coverage goals, vaccination programs must understand barriers to vaccine access imposed or exacerbated by the pandemic. We conducted a regionally representative online survey in January 2023 including 2036 Canadian parents with children under the age of 18. We used the COM-B model of behaviour to examine factors influencing vaccination timeliness during the pandemic. We assessed Capability with measures of vaccine understanding and decision difficulty, and Motivation with a measure of vaccine confidence. Opportunity was assessed through parents' self-reported experience with barriers to vaccination. Twenty-four percent of surveyed parents reported having missed or delayed one of their children's scheduled routine vaccinations since the beginning of the pandemic, though most parents reported having either caught up or the intention to catch up soon. In the absence of opportunity barriers, motivation was associated with timely vaccination for children aged 0-4 years (aOR = 1.81, 95 % CI: 1.14-2.84). However, experience with one or more opportunity barriers, particularly clinic closures and difficulties getting an appointment, eliminated this relationship, suggesting perennial and new pandemic-associated barriers are a critical challenge to vaccine coverage goals in Canada.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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".