Factors Associated with Not Testing For HIV and Consistent Condom Use among Men in Soweto, South Africa
Bibliographic record
Abstract
BACKGROUND: Besides access to medical male circumcision, HIV testing, access to condoms and consistent condom use are additional strategies men can use to prevent HIV acquisition. We examine male behavior toward testing and condom use. OBJECTIVE: To determine factors associated with never testing for HIV and consistent condom use among men who never test in Soweto. METHODS: A cross-sectional survey in Soweto was conducted in 1539 men aged 18-32 years in 2007. Data were collected on socio-demographic and behavioral characteristics to determine factors associated with not testing and consistent condom use. RESULTS: Over two thirds (71%) of men had not had an HIV test and the majority (55%, n = 602) were young (18-23). Of those not testing, condom use was poor (44%, n = 304). Men who were 18-23 years (aOR: 2.261, CI: 1.534-3.331), with primary (aOR: 2.096, CI: 1.058-4.153) or high school (aOR: 1.622, CI: 1.078-2.439) education, had sex in the last 6 months (aOR: 1.703, CI: 1.055-2.751), and had ≥1 sexual partner (aOR: 1.749, CI: 1.196-2.557) were more likely not to test. Of those reporting condom use (n = 1036, 67%), consistent condom use was 43% (n = 451). HIV testing did not correlate with condom use. CONCLUSION: Low rates of both condom use and HIV testing among men in a high HIV prevalence setting are worrisome and indicate an urgent need to develop innovative behavioral strategies to address this shortfall. Condom use is poor in this population whether tested or not tested for HIV, indicating no association between condom use and HIV testing.
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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 | 0.000 | 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".