PA-206 Breaking the silence of female genital schistosomiasis in Ghana’s health system: a case of health workers within the FAST project
Bibliographic record
Abstract
Background Female Genital Schistosomiasis (FGS) remains one of the most critical and neglected topics in Neglected Tropical Diseases (NTDs) and the health of women and girls worldwide. Health workers’ knowledge of FGS is vital to the prevention and management of the disease. This study, therefore, conducted implementation research to identify and address the FGS knowledge gap among health workers in Ghana. Methods This study was a 3-year (2020 -2022) implementation research study applying a pragmatic uncontrolled quasi-experimental study design. The study involved a baseline assessment, an intervention phase involving the training of health workers about FGS and an endline assessment. A mixed-method approach was applied to data collection. The qualitative data involved 20 In-depth Interviews while the quantitative data involved 116 health workers. NVIVO 12 and STATA 14 were used for qualitative and quantitative data analysis, respectively. Results Before the intervention, there was little knowledge about FGS among health workers as most participants only understood FGS as merely urogenital schistosomiasis in females. Based on the baseline assessments, an FGS education intervention in the form of training of health workers and distribution of FGS educational materials was carried out. The impact of this intervention enhanced health workers’ awareness and management of FGS. However, access (availability and affordability) to praziquantel (the main drug used in treating and preventing schistosomiasis) was cited as a challenge. Conclusion The FGS intervention has improved health workers’ awareness and understanding of FGS. However, there is a need to improve access to praziquantel to facilitate FGS management. In addition, a holistic strategy encompassing all stakeholders at the individual, community, and health-system levels is required to improve the general knowledge and management of FGS.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".