Engaging Black or African American and Hispanic or Latino Men Who Have Sex With Men for HIV Testing and Prevention Services Through Technology: Protocol for the iSTAMP Comparative Effectiveness Trial
Bibliographic record
Abstract
BACKGROUND: Gay, bisexual, and other men who have sex with men (MSM), particularly Black or African American MSM (BMSM) and Hispanic or Latino MSM (HLMSM), continue to be disproportionately affected by the HIV epidemic in the United States. Previous HIV self-testing programs have yielded high testing rates, although these studies predominantly enrolled White, non-Hispanic MSM. Mobile health tools can support HIV prevention, testing, and treatment. This protocol details an implementation study of mailing free HIV self-tests (HIVSTs) nested within a randomized controlled trial designed to assess the benefit of a mobile phone app for increasing the uptake of HIV prevention and other social services. OBJECTIVE: This study was a comparative effectiveness trial of innovative recruitment and testing promotion strategies intended to effectively reach cisgender BMSM and HLMSM. We evaluated the use of a mobile app for increasing access to care. METHODS: Study development began with individual and group consultations that elicited feedback from 3 core groups: HIV care practitioners and researchers, HIV service organization leaders from study states, and BMSM and HLMSM living in the study states. Upon completion of the formative qualitative work, participants from 11 states, based on the observed areas of highest rate of new HIV diagnoses among Black and Hispanic MSM, were recruited through social networking websites and smartphone apps. After eligibility was verified, participants consented and were randomized to the intervention arm (access to the Know@Home mobile app) or the control arm (referral to web resources). We provided all participants with HIVSTs. The evaluation of the efficacy of a mobile phone app to support linkage to posttest prevention services that included sexually transmitted infection testing, pre-exposure prophylaxis initiation, antiretroviral treatment, and acquisition of condoms and compatible lubricants has been planned. Data on these outcomes were obtained from several sources, including HIVST-reporting surveys, the 4-month follow-up survey, laboratory analyses of dried blood spot cards returned by the participant, and data obtained from the state health department surveillance systems. Where possible, relevant subgroup analyses were performed. RESULTS: During the formative development phase, 9 consultations were conducted: 6 in-depth individual discussions and 3 group consultations. From February 2020 through February 2021, we enrolled 2093 MSM in the randomized controlled trial from 11 states, 1149 BMSM and 944 HLMSM. CONCLUSIONS: This study was designed and implemented to evaluate the effectiveness of recruitment strategies to reach BMSM and HMSM and of a mobile app with regard to linkage to HIV prevention or treatment services. Data were also obtained to allow for the analyses of cost and cost-effectiveness related to study enrollment, HIV testing uptake, identification of previously undiagnosed HIV, sexually transmitted infection testing and treatment, and linkage to HIV prevention or treatment services. TRIAL REGISTRATION: ClinicalTrials.gov (NCT04219878); https://clinicaltrials.gov/ct2/show/NCT04219878. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43414.
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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 | 0.040 | 0.033 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.105 | 0.016 |
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".