Advancing community stakeholder engagement in biomedical HIV prevention trials: principles, practices and evidence
Bibliographic record
Abstract
Community stakeholder engagement is foundational to fair and ethically conducted biomedical HIV prevention trials. Concerns regarding the ethical engagement of community stakeholders in HIV vaccine trials and early terminations of several international pre-exposure prophylaxis trials have fueled the development of international guidelines, such as UNAIDS' good participatory practice (GPP). GPP aims to ensure that stakeholders are effectively involved in all phases of biomedical HIV prevention trials. We provide an overview of the six guiding principles in the GPP and critically examine them in relation to existing social and behavioral science research. In particular, we highlight the challenges involved in operationalizing these principles on the ground in various global contexts, with a focus on low-income country settings. Increasing integration of social science in biomedical HIV prevention trials will provide evidence to advance a science of community stakeholder engagement to support ethical and effective practices informed by local realities and sociocultural differences.
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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 | 0.348 | 0.368 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".