Factors associated with human papillomavirus (HPV) non-vaccination among 14-year-old children in Canada
Bibliographic record
Abstract
Objective The purpose of this study is to identify factors associated with HPV non-vaccination among 14-year-olds in Canada. Methods This study employed data from the 2021 Childhood National Immunization Coverage Survey. Data were collected between January and June 2022 across Canada's 10 provinces and three territories. Multivariate logistic regression analysis was conducted, to identify factors linked to HPV non-vaccination among 14-year-olds. Results HPV non-vaccination was found to be independently and significantly associated with the child being born outside of Canada (aOR = 2.61, 95 % CI: 1.20,5.70) and having a history of parental refusal, reluctance, or delay of at least one routine childhood vaccine other than HPV vaccine for their child (aOR = 3.26, 95 % CI: 1.87,5.66). Socioeconomic status-related factors such as household income, parent/guardian education, and the child's visible minority status were not found to be associated with HPV non-vaccination. Conclusions Future research is needed to better understand the barriers to HPV vaccination among non-Canadian-born adolescents and to gain insight into the complex intersecting factors at the individual, interpersonal, organizational, and societal levels that contribute to HPV non-vaccination in this population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".