Individual‐ and School‐Level Correlates of HIV Testing among Secondary School Students in Kenya
Bibliographic record
Abstract
The policy framework guiding Kenya's response to the AIDS epidemic identifies voluntary counseling and testing as crucial to risk reduction and HIV-preventive activities. Yet in Kenya, as in most sub-Saharan countries, voluntary testing rates are low, especially among young people. Using hierarchical linear models, we identify both individual- and teacher/school-level factors that affect voluntary HIV testing among secondary school students in Kenya. Results indicate that adolescents are more likely to test for HIV serostatus when they are knowledgeable about testing, have been involved in HIV/AIDS activities in primary school, have been provided with HIV information in secondary school, perceive themselves as at high risk of contracting HIV or know of someone infected with or who has died from HIV/AIDS, and have ever engaged in sexual intercourse. Barriers include fear of going to testing centers and being perceived as HIV-positive. Teacher/school-level characteristics are relevant for explaining rates of HIV testing, especially among girls. To encourage testing, policymakers should attend to teacher/school-level factors as well as individual characteristics of students.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".