Perceived vulnerability and HIV testing among youth in Cape Town, South Africa
Bibliographic record
Abstract
The importance of perceived vulnerability to risk-reducing behaviors, including HIV testing, is fairly established, especially among youth in sub-Saharan Africa. Yet, the majority of studies that examined this important relationship used cross-sectional data that inherently assume that perceived vulnerability does not change. While these studies have been useful, the assumption of perceived vulnerability as time invariant is a major flaw and has largely limited the practical usefulness of this variable in AIDS prevention and programing. Using longitudinal data and applying random-effects logit models, this study makes a major contribution to scholarship by examining if changes in perceived vulnerability associate with a change to test for HIV among 857 young people in Cape Town, South Africa. Results show that female youth who changed their risk perceptions were more likely to also change to test for HIV, but the effects were completely attenuated after controlling for theoretically relevant variables. No significant relationships were observed for males. Also, females who were virgins at wave 2 but had sex between waves were significantly more likely to have changed to test for HIV. Of most importance was that sexual behavior eliminated the effects of change in risk perceptions suggesting that a change in perception may have occurred as a result of changes in sexual behavior. AIDS prevention programs must pay particular attention to helping youth become aware of their vulnerability to HIV risks, especially as these have implications for risk-reducing behaviors, especially for females who are burdened.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".