Adaptation of a Health Education Program for Improving the Uptake of HIV Self-Testing by Men in Rwanda: A Study Protocol
Bibliographic record
Abstract
Background and objectives: Available evidence shows a low uptake of HIV services among men in Rwanda. HIV self-testing (HIVST), a new intervention, may have the potential to improve the uptake of HIV testing services among men. The current study aims to adapt a health education program (HEP) for improving the uptake of HIVST among men in Rwanda. Materials and Methods: We propose a mixed method study, which will be conducted in four phases. In Phase 1, we will conduct a scoping review to map the available evidence on health education programs for men in low- and middle-income countries (LMICs). In Phase 2, we will conduct interviews with stakeholders in the Rwanda HIV response and healthcare providers to determine their perspectives on implementation of HIVST in Rwanda. In Phase 3, a cross-sectional survey will be used to assess HIVST awareness and acceptability among men in Rwanda. Guided by findings from Phases 1, 2, and 3, we will employ the nominal group technique to develop and optimize the HEP for improving the uptake of HIVST among men in Rwanda. In Phase 4, we will use a pragmatic pilot randomized controlled trial to assess the preliminary impact of the HEP for men in Rwanda and assess the feasibility of a later, larger study. We will employ the Stata version 16 statistical package and NVivo version 12 for the analysis of quantitative and qualitative data, respectively. We anticipate that the findings of this study will inform implementers and policy makers to guide strategies on the implementation of HIVST in Rwanda and ultimately accomplish goals set forth in the Rwanda 2019–2024 Fourth Health Sector Strategic Plan on scaling up the number of men who know their HIV status. Conclusion: It is anticipated that this study will proffer solutions and strategies that are applicable not only in Rwanda but also in similar settings of LMICs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".