Factors associated with youth vaccine acceptance during the COVID-19 pandemic: Coordinated analyses across 5 Canadian datasets
Bibliographic record
Abstract
Vaccines are essential for preventing infectious diseases, yet vaccine hesitancy—particularly among youth—remains a growing concern. This study investigated factors influencing COVID-19 vaccine acceptance among Canadian youth (aged 12–29 years) across three pandemic stages using data from five rapid-response surveys. Multivariable logistic regression analyses identified sociodemographic, pandemic-related impacts, and mental health factors associated with vaccine acceptance. Results showed increasing vaccine acceptance over time across samples (i.e., Stage 1: 52.3 %–65.4 %; Stage 2: 73.8 %–83.2 %; and, Stage 3: 85.3 %–96.0 %). Although findings varied across samples, overall, parental education (significant adjusted odds ratios [aOR] range across samples and Stages = 0.16 to 2.07), living area (i.e., rural/urban; aORs range = 2.07 to 2.18), and COVID-19 stress (aOR range = 1.06 to 2.34) emerged as consistent factors across time. Other factors, such as being older (Stage 1 aOR = 1.15 to 3.21; Stage 3 aOR = 0.58), White (Stage 1 aOR = 1.55 to 1.69; Stage 2 aOR = 1.48), female (Stage 1 a OR = 0.60 to 0.72) or having a family member diagnosed with COVID-19 (Stage 1 aOR = 1.89; Stage 2 aOR = 0.55; Stage 3 aOR = 0.52) appeared as potential context-specific factors related to vaccine acceptance. Mental health had limited influence. These findings underscore the need for targeted vaccination campaigns addressing stable and dynamic sociodemographic and stress-related factors among youth. • Vaccine acceptance ranged from 52.3 % to 96.0 % across three stages of the pandemic. • Parental education, living area, and COVID-19 stress were key factors in vaccine acceptance. • Anxiety and depressive symptoms generally did not affect vaccine acceptance. • Targeted strategies are needed for youth with lower parental education, those living in rural areas, and those experiencing COVID-19-related distress.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".