Socioeconomic and Health-Related Characteristics Associated with Initiation and Completion of Human Papillomavirus Vaccination among Males in the United States: An In-Depth Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Human papillomavirus (HPV) vaccination among males is poorly understood. We systematically reviewed individual socioeconomic/health-related characteristics associated with HPV vaccine initiation and vaccination series completion among males in the United States. We searched for literature up to August 1, 2023, and pooled appropriate multivariable-adjusted results using an inverse variance random effects model, with results expressed as odds ratios. Among pediatric males (<18 years old), we observed moderately increased odds of vaccine initiation in urban residence, with being a Black/Hispanic male versus White male, public versus private health insurance, and visiting a health care provider in the past year. Influenza vaccination in the past year strongly increased the odds. Further, urban residence and having a parent with lower/no education moderately increased the odds of vaccination series completion, whereas influenza vaccination strongly increased the odds. Among adult males (≥18 years old), we observed moderately increased odds of vaccine initiation in the US-born, unemployed, unmarried/separated/divorced/widowed; among the states in the Northern versus Western region; having had a sexually transmitted infection; and being gay/bisexual. Younger age, living in the states in the Northern versus Southern region, having health insurance, and having visited a health care provider in the past year strongly increased the odds. Further, higher education, unmarried/separated/divorced/widowed, being a White male versus Black male, living in the states in the Northern versus Western region, and having a primary care physician moderately increased the odds of vaccination series completion, whereas having health insurance and being gay/bisexual strongly increased the odds. These findings may inform age-targeted future vaccination program planning.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.022 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".