Hepatitis B vaccination status and associated factors among university students in Ghana: A cross-sectional survey
Bibliographic record
Abstract
The World Health Organization (WHO) promotes Hepatitis B vaccination as the most-effective way of controlling HBV infection. However, knowledge regarding general university students’ population vaccination status remains limited in Ghana. Using data from a survey involving 2712 students from three universities, this study aimed to examine Hepatitis B vaccination status and associated factors among university students in Ghana. Results showed that less than half of the participants (38.2%) have been vaccinated and (57.3%) were yet to complete full vaccination (taken the full three doses of the vaccine). Non-compulsory nature of Hepatitis B vaccination (22.7%), lack of awareness of the vaccination (22.7%), high cost of the vaccination (18.1%), no interest/motivation in the vaccination (16.5%) and availability issues (13.8%) were the common reasons cited for non-vaccination. In a multivariate logistic regression analysis, participants who were aged 26 years or above had higher odds of taking Hepatitis B vaccination (AOR: 2.084; CI: 1.530–2.838, p = .001). Also, non-Akans (AOR: 0.746; CI: 0.617–0.902, p = .002), urban residents (AOR: .695; CI: .578-.835, p = .001) and no social support receivers (AOR: .812; CI: .701–1.223, p = .005) had lesser odds of taking Hepatitis B vaccination. This study highlights the urgent need for continued health education on HBV infection and strategies that ensure that students are fully vaccinated. The findings suggest that any interventions design to enhance uptake of Hepatitis B vaccination among students should be sensitive to socio-demographic characteristics especially age, ethnicity, residential status as well as social support.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".