Human papillomavirus (HPV) vaccination in a privately funded program in Ghana: A qualitative case study
Bibliographic record
Abstract
HPV vaccination is one of the safest and most effective interventions against HPV-related cancers. From 2013 to 2018, HPV vaccination was piloted in Ghana in preparation for a national program. Yet, at the time of this study, there was no publicly funded HPV vaccination program in Ghana. We explored an existing privately funded HPV vaccination program in Ghana to identify challenges and gaps and to gather insights to inform vaccination practice and national policy. This study used a qualitative case study research design. We conducted semi-structured interviews on experiences, barriers, and challenges in HPV vaccination at the Greater-Accra Regional Hospital between October 1 and November 26, 2023. Participants (N = 16) included HPV vaccinators (n = 8) and program/policy leaders (n = 8). Our thematic analysis focused on HPV vaccination processes, practice challenges, and policy interests. Four main themes emerged from our analyses. Our findings revealed many challenges faced by the HPV vaccination program. These include a lack of guiding policy/framework for the HPV vaccination program, an emphasis on sexual history, cervical screening, and HPV DNA test in determining vaccination eligibility by vaccinators, and a lack of formal provider and recipient HPV education programs. Although many vaccinators advocated for a universal HPV program, some policy/program leaders were reluctant to prioritize HPV vaccination advocacy due to their focus on acute health concerns. A vaccination program without a policy can be limited in quality and efficiency, as there will be no accountability and sustainability measures. We recommend the need to develop standardized guidelines to support evidence-based HPV vaccination practice.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".