Human Papillomavirus Vaccination Uptake and Its Predictors Among Female Adolescents in Gulu Municipality, Northern Uganda
Bibliographic record
Abstract
Background: Human papillomavirus (HPV) is the putative case of cervical cancer. However, uptake of HPV vaccination is reportedly low in Uganda. This study explored the predictors of HPV vaccination uptake among female adolescents aged 15-18 years in Gulu Municipality, in northern Uganda. Methods: This was an analytical cross-sectional survey that was conducted among adolescents aged 15-18 years in Gulu Municipality. A structured questionnaire was used. Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 25. Descriptive statistics and a log binomial model were used to analyze the factors associated with HPV vaccination uptake. Results: Less than a quarter of the female adolescents (22%) aged 15-18 years in Gulu municipality, Gulu district, had been vaccinated with the human papillomavirus vaccine. HPV vaccination uptake was lower by 23% among adolescents who stayed with their mothers only (aPR = 0.769, CI = 0.595-0.995, P = 0.046), and by 14% among adolescents whose parents were unmarried (aPR 0.859, CI = 0.776-0.951, P=0.003). Conclusion: This study reports a low HPV vaccination coverage among adolescents in Gulu Municipality, which is associated with parental perceptions and marital status. Efforts to increase uptake should focus on parents of adolescents.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".