Assessing awareness and use of HIV self-testing kits after the introduction of a community-based HIV self-testing programme among men who have sex with men in Kenya
Bibliographic record
Abstract
Men who have sex with men (MSM) bear a disproportionate burden of new HIV infections in Kenya, while experiencing discrimination, leading to suboptimal levels of HIV care. HIV self-testing (HIVST) is a tool to increase HIV screening and earlier diagnosis; however, questions remain regarding how best to scale-up HIVST to MSM in Kenya. The main objective of this study was to examine changes in knowledge and use of HIVST after implementation of a community-led HIVST project. Participants were MSM recruited from Kisumu, Mombasa, and Kiambu counties. Data were collected from two rounds (Round 1: 2019; Round 2: 2020) of serial cross-sectional integrated biological and behavioural assessments (IBBA), pre-, and post-project implementation. Two main outcomes were measured: 1) whether the respondent had ever heard of HIVST; and 2) whether they had ever used HIVST kits. Changes in outcomes between IBBA rounds were examined using modified multivariable Poisson regression models; adjusted prevalence ratios (aPR) and 95% confidence intervals (95% CI) are reported. A total of 2,328 respondents were included in main analyses. The proportion of respondents who had heard of HIVST increased from 75% in Round 1 to 94% in Round 2 (aPR: 1.2, 95% CI: 1.2-1.3), while those reporting using an HIVST kit increased from 20% to 53% (aPR: 2.3, 95% CI: 2.0-2.6). Higher levels of education and HIV programme awareness were associated with both outcomes. Awareness and use of HIVST kits increased after implementation of a community-led HIVST implementation project, demonstrating the importance of integration with existing community groups.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".