Resolving Challenges in HIV Cure–Related Research: Protocol for a Modified Delphi Consensus-Building Process
Bibliographic record
Abstract
BACKGROUND: HIV cure-related research is expanding rapidly, bringing both new opportunities and ethical challenges. Historically, clinical trials for novel HIV treatments have underrepresented populations most affected by HIV, such as Black gay men and transgender women. This disparity is compounded by medical mistrust and historical mistreatment of racially and ethnically diverse individuals in the United States. Addressing these issues is crucial as we plan HIV cure-related clinical trials. We aim to build consensus on how to increase representation of groups most affected by HIV in cure-related trials in the United States. OBJECTIVE: We aimed to describe a protocol using a hybrid Delphi consensus-building methodology to build consensus on 3 key research questions: how to better engage populations in HIV cure research who carry the greatest burden of HIV (ie, racial, ethnic, sex, and gender minority groups); how to enhance trust and diminish mistrust in health care and scientific settings that influence willingness to participate; and how to design HIV cure research and analytical treatment interruption protocols that do not limit participation of working adults. METHODS: We used a hybrid Delphi method, involving 4 iterative survey rounds. Initial surveys were open-ended and broad, refining over subsequent rounds into more specific, closed-ended questions based on previous feedback. Between rounds, an independent stakeholder group reviewed interim findings, incorporating a nominal group technique to enhance the process. Panelists represented diverse racial, ethnic, sex, and gender perspectives, including an intentional oversampling of experts on racial and ethnic minority issues. Recruitment was facilitated through partnerships with community-based organizations, such as The Well Project, National Minority AIDS Council, and TruEvolution. RESULTS: As of December 2024, all 4 Delphi survey rounds and 3 nominal group technique discussions have been completed. The process progressed from broad, open-ended questions in round 1 to structured ranking and rating in rounds 3 and 4. Iterative feedback informed survey refinement between rounds. The final data analysis and synthesis of consensus recommendations are underway and will be reported in a forthcoming results paper. CONCLUSIONS: The hybrid Delphi methodology effectively refined responses and built consensus on engaging priority populations in HIV cure research. Oversampling of diverse participants and the inclusion of independent stakeholder feedback added robustness and inclusivity to the findings. Future steps include detailed data analysis and data dissemination. Consensus recommendations will be reported in subsequent manuscripts to inform more inclusive, trust-centered, and accessible HIV cure trial design. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/67123.
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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 | 0.057 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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; both teacher heads 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".