Understanding the Acceptability of Broadly Neutralizing Antibodies for HIV Prevention Among At-Risk Populations and Feasibility Considerations for Product Introduction in India: Protocol for a Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Acceptability and preference research play a crucial role in the design, evaluation, and implementation of any new prevention product in any geographical setting. They also play a critical role in the development of clinical guidelines and policies. A wide range of acceptability studies have been conducted in diverse general and key populations for various new HIV prevention products worldwide. As clinical development strategies are being developed for clinical studies of broadly neutralizing antibodies (bNAbs) as potential HIV prevention products, appropriately tailoring them to address the type of HIV epidemic at hand would be critical for efficient uptake within in-country public health systems and decrease adoption and adherence challenges. Accomplishing this will require comprehensive acceptability and feasibility studies to inform multisectoral efforts that increase access to these products and national policies supportive of access to health care for those in most need. Thus, it is both opportune and important to undertake focused efforts toward informing product development strategies. OBJECTIVE: This study aims to understand preferences for product attributes and key behavioral factors influencing adoption and uptake of bNAb prevention products among end-users including female sex workers, men who have sex with men, transgender women, people who inject drugs, and adolescent girls and young women in India and understand the key health system and programmatic perspectives toward the introduction of bNAb prevention products from health service providers and policy makers in India. METHODS: A multisite study will be conducted in Delhi, Mumbai, and Chennai to capture the differences in perspectives among diverse end-users and key informants across the country. The study will use a multimethods design using focus group discussions, in-depth interviews, simulated behavioral experiments, and key informant interviews. A total of 30 focus group discussions, 45 in-depth interviews, 15 simulated behavioral experiments sessions, and 15 key informant interviews will be conducted across 3 sites. RESULTS: The data collected and analyzed will enable insights on which specific product attributes matter the most to the populations and why some attributes are less preferred; contextual drivers of preferences and choices at individual, interpersonal, social, and structural levels; and relative positioning of bNAb products among other potential HIV prevention products. Insights from the health service providers and policy makers will provide a critical understanding of the need perception of the potential product in the existing product landscape and what additional efforts and resources are required for potential introduction, delivery, and uptake of the bNAb products in the Indian context. CONCLUSIONS: Insights generated from the abovementioned objectives will represent perspectives of populations of interest across geographies in India, will provide an overview of the acceptability of bNAb products and the feasibility of their introduction in this region, and will inform product development strategies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47700.
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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 | 0.064 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.032 | 0.006 |
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".