Impact of interventions to improve HPV vaccination acceptance and uptake in school-based programs: Findings of a pilot project in Quebec
Bibliographic record
Abstract
CONTEXT: Vaccination coverage against human papillomavirus (HPV) in school-based programs in Quebec, Canada, is suboptimal despite more than a decade of introduction. Three interventions to improve HPV vaccine acceptability and coverage in school-based programs were developed, implemented as part of a multicomponent strategy and evaluated. METHOD: Sixty-four (64) schools were recruited, of which 32 received the interventions (pilot schools), and 32 received usual vaccination activities (control schools). Two approaches were used to assess the impact of the interventions. Pre-post questionnaires were completed by parents in both pilot and control schools. Quantitative analyses of vaccination coverage using the Quebec immunization registry were conducted. RESULTS: Participating parents (n = 989 in the pre-intervention survey and n = 772 in the post-intervention one) were generally aware of HPV and HPV vaccination. Most parents were confident about vaccination, had little or no hesitation and had decided to have their child vaccinated. Parents in the pilot schools were less concerned about vaccine safety than those in the control schools after the interventions. Parents in the pilot schools were also more likely to have decided to have their child vaccinated. A statistically significant difference of 7.4 % in HPV vaccine coverage between pilot and control schools was observed (82.9 % vs 75.5 %, p <0.0001). CONCLUSION: Although school-based programs offer equitable access to vaccination and minimize access barriers, it remains crucial to identify effective interventions to improve vaccine uptake further and reach the WHO cervical cancer elimination goal. Our multicomponent strategy appears to have positively impacted HPV vaccine acceptability and coverage and could be adapted to other contexts where vaccination is delivered in school-based programs.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".