Lack of clinician knowledge of human papillomavirus (HPV) vaccination to prevent HPV-related cancers in men: An interview study.
Bibliographic record
Abstract
e18273 Background: Human papillomavirus (HPV) has a well-established link to cervical cancer and anogenital and oropharyngeal malignancies. Recognition of the HPV-caused cancer burden in males has led to expansions of female-only HPV vaccination programs to all genders. This study explored drivers of and barriers to gender-neutral HPV vaccination (GNV) program adoption, implementation, and potential impacts on the HPV-caused cancer burden. Methods: We conducted in-depth interviews with academic oncologists as well as advocacy, public health, infectious disease, and policy experts in six countries (Argentina, Australia, Austria, Brazil, Canada and Italy) from April-August 2018. Using a semi-structured discussion guide, we sought to elicit expert perceptions on factors affecting uptake of HPV vaccination in males and subsequent effects on the incidence of HPV-associated cancer. Data were analyzed for key themes. Results: Eighteen experts participated in the study, including three academic oncologists and two doctoral level oncology researchers. A key theme from the analysis was the critical need to promote education and awareness about GNV across all healthcare providers to facilitate vaccine uptake and high GNV coverage rates. Participants reported a lack of awareness among segments of practitioners about the effectiveness of the HPV vaccine in preventing HPV infection and associated cancers in all genders. They also described strategies to overcome knowledge gaps, such as partnerships with oncologists, cancer advocacy organizations, and professional medical societies, emphasizing the key role that all health care providers can play in raising awareness of the importance of HPV vaccination for all genders. Conclusions: Findings from this study suggest the need to enhance healthcare provider education about GNV, and the importance of a multi-specialty approach to promoting HPV vaccination to prevent infection and HPV associated morbidity and mortality in all genders.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".