Assessing sociodemographic disparities in HPV vaccine uptake among grade 6 and 9 students in the Vancouver Coastal Health region
Bibliographic record
Abstract
PURPOSE: To identify sociodemographic factors associated with HPV vaccine uptake in a universal, in-school HPV vaccination program, among grade 6 and 9 students in the regional health authority of Vancouver Coastal Health (VCH), British Columbia (BC), Canada during the 2021/22 school year. VCH operates within the southwest corner of the province of BC serving a mix of urban and rural regions. HPV vaccine is offered in school to all grade 6 students using a two-dose series, with catch up immunizations offered to students in grade 9. METHODS: We conducted a cross-sectional study of grade 6 and 9 students enrolled in VCH schools for the 2021/22 school year, who also resided within the VCH region. We modelled the associations between sociodemographic explanatory variables (individual-level and group-level) and fully vaccinated outcome using a cross-classified (non-nested) multilevel model. RESULTS: Among the 17,939 students eligible, 74 % were fully vaccinated for HPV. Immunization coverage was associated with grade, geographic area of residence, school category, social and material deprivation. We demonstrated that grade modified the association between material deprivation and being fully vaccinated. Grade 9 students, including those residing in more materially deprived neighbourhoods, had substantially higher odds (OR 2.01 [95 % CI 1.08, 3.75]) of being fully vaccinated relative to grade 6 students in the least materially deprived neighbourhoods. CONCLUSIONS: Though publicly funded HPV vaccine is offered to all students in grade 6 and 9, in a space that maximizes programmatic access, sociodemographic factors associated with under-immunized populations were identified. This information can be leveraged for strategic targeting of resources to underimmunized schools or students to mitigate impacts. The repeat offering of HPV vaccine in an older grade (grade 9 in BC) is a key programmatic strategy to reach under-immunized populations and should be complemented by other creative approaches.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".