A survey of healthcare workers’ recommendations about human papillomavirus vaccination
Bibliographic record
Abstract
Purpose: The human papillomavirus (HPV) vaccine is safe and effective for preventing HPV-related diseases. However, HPV vaccination rates in Japan are low because the "Ministry of Health, Labour and Welfare" had stopped recommending vaccination. We assessed healthcare workers' (HCWs) current recommendations regarding the HPV vaccine and how the provision of information about HPV vaccination affected their recommendations. Materials and Methods: A survey was conducted among nurses and physicians in Nara prefecture from March 2021 to July 2021. The questionnaire asked about their understanding, recommendations, and opinions regarding HPV vaccination. Before answering the last two questions (optional), the HCWs read evidence-based information quantifying the risks and benefits of HPV vaccination. Results: A total of 441 HCWs completed the questionnaire. Only 19% of HCWs always recommended HPV vaccination for girls aged 12-16 years. The evidence-based information significantly improved the percentage of HCWs who would "always recommend" vaccination. Conclusion: This study showed that the proportion of HCWs who recommend HPV vaccination to adolescent girls remains low in Japan. However, we found that evidence-based information describing the causal relationship between adverse events and vaccination, quantifying the risks and benefits, noting the importance of HCW communications with families, and reporting the recommendations of national societies, might increase HCWs' recommendations for HPV vaccination.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".