Prevalence and Determinants of Genital Infection with Papillomavirus, in Female and Male University Students in Busan, South Korea
Bibliographic record
Abstract
BACKGROUND: Little is known about the prevalence of human papillomavirus (HPV) infection in young adults in Asia. METHODS: We invited female and male students in Busan, South Korea, to participate in a survey that included, for females, self-collection of vaginal cells and, for males, physician-performed collection of exfoliated genital cells. The prevalences of 25 HPV types were evaluated, by a polymerase chain reaction-based assay, in 672 female students (median age, 19 years) and in 381 male students (median age, 22 years). RESULTS: HPV DNA was detected more frequently in female students (15.2%) than in male students (8.7%); in both sexes, high-risk HPV types were predominant. Among sexually active students, HPV prevalence was 38.8% in females and 10.6% in males. In female students, currently smoking cigarettes and having multiple lifetime sex partners were the strongest risk factors for HPV infection; in male students, associations between HPV prevalence and sexual habits were similar to those in female students but never attained statistical significance. CONCLUSIONS: Young women in South Korea start having penetrative sexual intercourse relatively late (median age, 18 years), but, once they begin, HPV prevalence quickly rises to levels comparable with those found in university students in the United States and in northern Europe. The high rate of participation in our study suggests that trials of new vaccines against HPV may be feasible among university students in South Korea.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".