Factors influencing human papillomavirus school-based immunization in Alberta: A mixed-methods study protocol
Bibliographic record
Abstract
More than 1,300 Canadians are diagnosed with cervical cancer annually, which is nearly preventable through human papillomavirus (HPV) immunization. Across Canada, coverage rates remain below the 90% target set out by the Action Plan for the Elimination of Cervical Cancer in Canada (2020-2030). To support this Plan, the Canadian Partnership Against Cancer has commissioned the Urban Public Health Network (UPHN) to coordinate a quality improvement project with Canada's school-based HPV immunization programs. In Alberta, the UPHN partnered with Alberta Health Services (AHS) for this work. This study has one overarching research question: what are parent/guardian and program stakeholder perceived barriers, enablers and opportunities to immunization for youth as part of the school-based HPV immunization program in Alberta? This study uses a mixed-methods sequential explanatory design. A survey will be emailed to a sample of Albertans with children aged 11-17 years. Questions will be based on a Conceptual Framework of Access to Health Care. Subsequent qualitative work will explore the survey's findings. Parents/guardians identifying as vaccine hesitant in the survey will be invited to participate in virtual, semi-structured, in-depth interviews. Stakeholders of the school-based immunization program will be purposively sampled from AHS' five health zones for virtual focus groups. Quantitative data will be analyzed using SAS Studio 3.6 to carry out descriptive statistics and, using logistic regression, investigate if Framework constructs are associated with parents'/guardians' decision to immunize their children. Qualitative data will be analyzed using NVivo 12 to conduct template thematic analysis guided by the Framework. Study results will provide insights for Alberta's public health practitioners to make evidence-informed decisions when tailoring the school-based HPV immunization program to increase uptake in vaccine hesitant populations. Findings will contribute to the national study, which will culminate in recommendations to increase HPV immunization uptake nationally and progress towards the 90% coverage target.
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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 | 0.021 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.035 | 0.004 |
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".