Increasing HIV Testing and Viral Suppression via Stigma Reduction in a Social Networking Mobile Health Intervention Among Black and Latinx Young Men and Transgender Women Who Have Sex With Men (HealthMpowerment): Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Stigma and discrimination related to sexuality, race, ethnicity, and HIV status negatively impact HIV testing, engagement in care, and consistent viral suppression (VS) among young Black and Latinx men who have sex with men and transgender women who have sex with men (YBLMT). Few interventions address the effects of intersectional stigma among youth living with HIV and those at risk for HIV within the same virtual space. OBJECTIVE: Building on the success of the HealthMpowerment (HMP) mobile health (mHealth) intervention (HMP 1.0) and with the input of a youth advisory board, HMP 2.0 is an app-based intervention that promotes user-generated content and social support to reduce intersectional stigma and improve HIV-related outcomes among YBLMT. The primary objective of this study is to test whether participants randomized to HMP 2.0 report improvement in HIV prevention and care continuum outcomes compared with an information-only control arm. We will also explore whether participant engagement, as measured by paradata (data collected as users interact with an mHealth intervention, eg, time spent using the intervention), mediates stigma- and HIV care-related outcomes. Finally, we will assess whether changes in intersectional stigma and improvements in HIV care continuum outcomes vary across different types of social networks formed within the intervention study arms. METHODS: We will enroll 1050 YBLMT aged 15 to 29 years affected by HIV across the United States. Using an HIV-status stratified, randomized trial design, participants will be randomly assigned to 1 of the 3 app-based conditions (information-only app-based control arm, a researcher-created network arm of HMP 2.0, or a peer-referred network arm of HMP 2.0). Behavioral assessments will occur at baseline, 3, 6, 9, and 12 months. For participants living with HIV, self-collected biomarkers (viral load) are scheduled for baseline, 6, and 12 months. For HIV-negative participants, up to 3 HIV self-testing kits will be available during the study period. RESULTS: Research activities began in September 2018 and are ongoing. The University of Pennsylvania is the central institutional review board for this study (protocol #829805) with institutional reliance agreements with the University of North Carolina at Chapel Hill, Duke University, and SUNY Downstate Health Sciences University. Study recruitment began on July 20, 2020. A total of 205 participants have been enrolled as of November 20, 2020. CONCLUSIONS: Among a large sample of US-based YBLMT, this study will assess whether HMP 2.0, an app-based intervention designed to ameliorate stigma and its negative sequelae, can increase routine HIV testing among HIV-negative participants and consistent VS among participants living with HIV. If efficacious and brought to scale, this intervention has the potential to significantly impact the disproportionate burden of HIV among YBLMT in the United States. TRIAL REGISTRATION: ClinicalTrials.gov NCT03678181; https://clinicaltrials.gov/ct2/show/study/NCT03678181. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24043.
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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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.092 | 0.013 |
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".