A Skills-Based HIV Serostatus Disclosure Intervention for Sexual Minority Men in South Africa: Protocol for Intervention Adaptation and a Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Gay, bisexual, and other men who have sex with men (GBMSM) living with HIV have low antiretroviral treatment adherence in South Africa due to limited skills in managing disclosure and prevention behaviors with sexual and romantic partners. As a result, there is a high HIV transmission risk within HIV-discordant partnerships, but an existing intervention may address these outcomes, if adapted effectively. Healthy Relationships (HR) is a behavioral intervention that was originally delivered in groups and in person over 5 sessions to develop coping skills for managing HIV-related stress and sexually risky situations, enhance decision-making skills for HIV disclosure to partners, and establish and maintain safer sex practices with partners. HR effectively improves prevention behaviors but has yet to be tailored to a non-US context. OBJECTIVE: We aim to adapt HR into a new culturally grounded intervention entitled Speaking Out & Allying Relationships for GBMSM and then assess its feasibility in Eastern Cape, South Africa. METHODS: The study will have 2 aims. For aim 1-adaptation-we will use a human-centered design approach. Initial intervention tailoring will involve integrating Undetectable=Untransmittable and pre-exposure prophylaxis education, developing intervention content for a videoconference format, and designing role-plays and movies for skill building based on preliminary data. Afterward, interviews and surveys will be administered to GBMSM to assess intervention preferences, and a focus group will be conducted with health care providers and information technology experts to assess the intervention's design. Finally, a usability test will be performed to determine functionality and content understanding. Participants will be GBMSM living with HIV (n=15) who are in a relationship and health care providers and information technology (n=7) experts working in HIV care and programming with this population. For aim 2, we will examine the feasibility of the adapted intervention by using a pilot randomized control design. There will be 60 individuals per arm. Feasibility surveys and interviews will be conducted with the intervention arm, and behavioral and biomedical assessments for relationship and treatment adherence outcomes will be collected for both arms. All participants will be GBMSM living with HIV who are in a relationship with an HIV-negative or unknown status partner. RESULTS: Intervention adaptation began in August 2021. Initial tailoring and the refining of GBMSM intervention preferences were completed in December 2021. Usability and feasibility assessments are due to be completed by March 2022 and February 2024, respectively. CONCLUSIONS: GBMSM need efficacious interventions that tackle partnership dynamics, HIV prevention, and treatment outcomes for antiretroviral treatment adherence and viral suppression in South Africa. Harnessing everyday technology use for social networking (eg, videoconferences), Undetectable=Untransmittable education, and pre-exposure prophylaxis to update an existing intervention for South African GBMSM has the potential to strengthen relationship communication about HIV treatment and prevention and, in turn, improve outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36845.
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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 | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.060 | 0.007 |
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".