High rates of HIV testing despite low perceived HIV risk among African-American sexually transmitted disease patients.
Bibliographic record
Abstract
PURPOSE: In the current diagnosis-based, human immunodeficiency virus (HIV) prevention climate, previous testing among persons at elevated HIV risk has cost and efficacy implications, as it signals continued behavioral risk, limited HIV knowledge or overuse of services. This study sought to determine the proportion of African Americans newly seeking sexually transmitted disease (STD) diagnosis who previously had obtained HIV counseling and testing. METHODS: This was a clinic-based, cross-sectional survey of African-American adults (N=408) seeking STO diagnosis at a public STD clinic located in a high-HIV and STD prevalence city in the U.S. south. MAIN FINDINGS: Eighty-four percent of respondents had previously obtained HIV counseling and testing: 68% had previously obtained care at the clinic. Sixty-five percent of respondents perceived themselves as having low or no HIV risk. Seventy-two percent correctly answered > or = 3 of 4 HIV knowledge items. CONCLUSIONS: Although diagnosis-based HIV prevention initiatives promote HIV counseling and testing for both primary and secondary HIV prevention, these findings suggest that many African-American STD patients remain at risk following testing. Future research should explore how the counseling portion of standard HIV counseling and testing influences subsequent knowledge, attitudes, risk perceptions and behaviors.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".