Barriers and Facilitators to HIV and Viral Hepatitis Testing in Primary Health Care Settings in the Kyrgyz Republic (BarTest): Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: In the Kyrgyz Republic, it is estimated that 18% of people living with HIV are undiagnosed and more than half are diagnosed late (CD4 lymphocyte count of <350 cells/μL). For viral hepatitis, before 2023, free testing was only available to people living with HIV, which led to a low testing uptake. A new national program on the elimination of HIV and viral hepatitis infection for the years 2023-2027 recognizes the need to scale up testing to reduce the gap in undiagnosed people in the country. OBJECTIVE: This study aimed to identify and describe the most important barriers and facilitators to HIV and viral hepatitis B, C, and D testing from the perspective of health care workers working in primary health care settings in the Kyrgyz Republic. METHODS: A cross-sectional, mixed methods study was conducted in 2 phases. A purposive sampling approach was applied to recruit health care workers in primary health care settings. In phase I, in-depth, semistructured interviews were conducted with 22 participants to gather detailed information about the key barriers and facilitators for testing. We applied a thematic approach for qualitative analysis. The themes identified informed the development of a questionnaire with the main barriers and facilitators for phase II. The questionnaire was distributed electronically, and the target sample size was 400 participants. We performed descriptive analyses of the questionnaire data, reporting the most frequently mentioned barriers and facilitators for HIV and viral hepatitis testing. RESULTS: The study received financial support in the framework of the Global Health Protection Programme by the Federal Government of Germany. Data collection took place in June 2024 for phase I and in November 2024 for phase II. Data analyses and writing up of results will be done in early 2025 and results are expected to be published in spring 2025. CONCLUSIONS: The results of the study will improve the understanding of existing barriers and facilitators to HIV and viral hepatitis testing in order to increase testing offers and uptake in primary health care settings in the Kyrgyz Republic. Importantly, the findings will inform steps to improve the implementation of the new testing strategy and, ultimately, increase the number of people diagnosed and treated in the Kyrgyz Republic. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/62929.
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 | 0.048 | 0.022 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".