Understanding Men’s Perceptions of Human Papillomavirus and Cervical Cancer Screening in Kampala, Uganda
Bibliographic record
Abstract
PURPOSE: This preliminary study explores Ugandan men's knowledge and attitudes about human papillomavirus (HPV), cervical cancer, and screening. METHODS: A local physician led an education session about cervical cancer for 62 men in Kisenyi, Kampala in Uganda. Trained nurse midwives administered surveys to assess knowledge and attitudes before and after the education session. RESULTS: From the pre-education survey, only 24.6% of men had heard of HPV previously, and 59% of men had heard of cervical cancer. Posteducation, 54.5% of men believed only women could be infected with HPV and 32.7% of men believed antibiotics could cure HPV. Despite their limited knowledge, 98.2% of men stated they would support their partners to receive screening for cervical cancer, and 100% of men surveyed stated they would encourage their daughter to get the HPV vaccine if available. CONCLUSIONS: Knowledge of HPV and cervical cancer among Ugandan men is low. Even after targeted education, confusion remained about disease transmission and treatment. Ongoing education programs geared toward men and interventions to encourage spousal communication about reproductive health and shared decision making may improve awareness of cervical cancer prevention strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".