“ <i>It takes time to build trust</i> ”: a survey Ontario’s school-based HPV immunization program ten years post-implementation
Bibliographic record
Abstract
OBJECTIVES: Describe Ontario's school-based human papillomavirus (HPV) vaccination program from the perspective of local public health units (PHUs). METHODS: In 2018, Vaccine Preventable Diseases (VPD) managers at each of Ontario's 35 PHUs were invited to participate in an online survey regarding the organization and delivery of their HPV vaccination program. Questions were asked on the school-based program, training and support of vaccine providers, communication and promotion, assessing coverage rates and perceptions of the program's strengths and challenges. Descriptive statistics were generated for close-ended items. A thematic content analysis was performed for open-ended items. RESULTS: Eighteen PHUs (54%, n = 19/35) responded. All responding PHUs provided the HPV vaccine in publicly funded schools but only 6 reported being permitted to provide HPV vaccine in private schools. Fact sheets, Q&As or other written information locally developed by the PHUs were the main tools used to communicate with parents (n = 17), students (n = 13), school personnel (n = 13) and school board officials (n = 9). The most frequently reported barriers were: limited program resources, negative perceptions held by parents and/or school staff regarding the HPV vaccine, logistical issues (e.g., getting the consents forms returned, collaboration with schools for vaccine delivery) and the fact that HPV vaccination is not mandatory under Ontario legislation. CONCLUSION: Local public health units that implement HPV vaccine programs in schools identified logistical barriers, public perceptions about the HPV vaccine and the voluntary nature of the program as the main barriers.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".