‘It is scary to pause treatment’: perspectives on HIV cure-related research and analytical treatment interruptions from women diagnosed during acute HIV in Durban, South Africa
Bibliographic record
Abstract
BACKGROUND: HIV remains a major challenge in KwaZulu-Natal, South Africa, particularly for young women who face disproportionate risks and barriers to prevention and treatment. Most HIV cure trials, however, occur in high-income countries. OBJECTIVE: To examine the perspectives of young women diagnosed with acute HIV in a longitudinal study, focusing on their perceptions on ATI-inclusive HIV cure trials and the barriers and facilitators to participation. MATERIALS AND METHODS: Between October 2022 and February 2024, we conducted closed-ended surveys and in-depth interviews with 20 women aged 19-33 living with HIV, who were willing but ineligible or unable to participate in an HIV cure trial. RESULTS: Many participants reported mental health challenges, including major depression (40%), moderate to severe anxiety (35%), and low self-esteem (35%). While women diagnosed during acute HIV supported pausing antiretroviral treatment (ART) during analytical treatment interruption (ATI) to advance HIV cure research, concerns about health risks and HIV-related stigma were significant barriers to enrollment. Trust in the research team and close monitoring were seen as positive factors, while fears around sharing of HIV/ATI status and transmission to sex partners complicated decision-making. Participants expressed a need for psychological counseling and access to community resources to manage ATI-related stressors. CONCLUSIONS: Understanding women's perspectives on HIV cure research, especially ATI trials, is vital. Building trust and addressing psychosocial challenges through a healing-centered approach can facilitate trial participation. Socio-behavioral research before and during HIV cure trials will be essential to inform participant-centered protocol design.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.009 |
| 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".