Effect of race/ethnicity on participation in HIV vaccine trials and comparison to other trials of biomedical prevention
Bibliographic record
Abstract
INTRODUCTION: Racial/ethnic minorities are underrepresented in actual HIV vaccine trials in North America, and willingness to participate (WTP) and retention in an HIV vaccine trial may differ from that in Whites. METHODS: In this review, the authors identified HIV vaccine preparedness studies (VPS) in North America in high-risk populations that examined the relationship between race/ethnicity and WTP in a preventive phase 3 HIV vaccine trial, and the relationship to retention. Studies were categorized by risk group, and comparison group (Whites vs. non-Whites). Other types of trials of biomedical prevention were also identified, and WTP and retention rates were compared and contrasted to actual HIV vaccine trials. RESULTS: In the studies identified, WTP in a hypothetical trial HIV vaccine trial did not differ by race/ethnicity. In contrast, actual HIV vaccine trials, an HIV acquisition trial, and a phase 2B preexposure prophylaxis (PrEP) trial have enrolled a large percentage of White men. Human papilloma virus (HPV) privately-funded trials have also enrolled a large number of Whites, due to convenience sampling. Retention in the HIV acquisition trial was lower in African-Americans compared with Whites. CONCLUSION: Strategies to increase WTP and enhanced retention (ER) strategies may help in recruiting and retaining minority participants in actual HIV vaccine trials and other trials of biomedical prevention.
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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 | 0.025 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".