eTest: Real-time, Remote Monitoring System for Home-based HIV Testing Among High-risk Men Who Have Sex With Men
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- HIV Infections
- Sponsor
- Brown University
- Enrollment
- 811
- Locations
- 1
- Primary Endpoint
- Model Adjusted Probability of Any HIV Testing
- Status
- Completed
- Last Updated
- last year
Overview
Brief Summary
The proposed research will conduct a fully-powered efficacy trial of this approach in areas with large populations of AA and H/L MSM and high HIV incidence: Jackson, MS, Los Angeles, CA, and Boston, MA. High-risk MSM who have not tested for HIV in the last year will be recruited from MSM-oriented "hook-up" mobile apps, and assigned to receive either (1) HBST with post-test phone counseling/referral ("eTEST" condition), (2) "standard" HBST without active follow-up, or (3) reminders to get tested for HIV at a local clinic ("control" condition) at three month intervals over the course of 12 months. The investigators will explore the impact of the eTEST system on key outcomes, including rates of HIV testing, receipt of additional HIV prevention services, and PrEP initiation, compared with standard HBST or clinic-based testing reminders alone. The investigators will also explore the cost effectiveness of the eTEST system under various scenarios compared with relying on traditional, clinic-based testing alone.
Detailed Description
HIV disproportionately affects men who have sex with men (MSM) in the United States, and new infections continue to increase particularly among African American (AA) and Hispanic/Latino (H/L) MSM. Past studies estimate that up to 50% of these new infections originate from the approximately 20% of MSM who are unaware of their status. Expanded HIV testing can produce reductions in incidence when implemented on a broad scale by facilitating earlier diagnosis and treatment. Rates of HIV testing are particularly low among AA and H/L MSM, and innovative approaches to encourage testing may help address high incidence in these men. Home-based, self-testing (HBST) for HIV offers considerable promise for increasing the number of MSM who are aware of their status by overcoming key barriers to clinic-based testing, such as inconvenience and confidentiality concerns. HBST may also be particularly well-suited for AA and H/L MSM, given that stigma and mistrust of medical care contribute to low testing rates. Despite its promise, however, many are concerned that HBST does not sufficiently connect users with critical post-testing resources, such as confirmatory testing and care among those who test positive, and that these limitations may result in delayed linkage to care. Existing, FDA-approved HBST kits provide a free, 24-hour helpline that offers these services to those who seek it, but few users do, and this "passive" approach may miss critical opportunities to engage with MSM for further prevention services. To address these challenges, the investigators developed a mobile health platform ("eTEST") that uses internet-of-things (IoT) technologies to monitor when HBST users open their tests in real time, allowing the investigators to provide timely, "active" follow-up counseling and referral over the phone after they do so. In a pilot study, the investigators show that providing HBST by mail at regular intervals boosted rates of any/repeat HIV testing among high-risk MSM compared with clinic-based testing reminders. Moreover, those who received follow-up phone counseling after HBST were more likely to receive risk reduction counseling, to consult with a medical provider about PrEP, and to initiate PrEP. Given these promising results, the proposed research will conduct a fully-powered efficacy trial of this approach in areas with large populations of AA and H/L MSM and high HIV incidence: Jackson, MS, Los Angeles, CA, and Boston, MA. High-risk MSM who have not tested for HIV in the last year will be recruited from MSM-oriented "hook-up" mobile apps, and assigned to receive either (1) HBST with post-test phone counseling/referral ("eTEST" condition), (2) "standard" HBST without active follow-up, or (3) reminders to get tested for HIV at a local clinic ("control" condition) at three month intervals over the course of 12 months. The investigators will explore the impact of the eTEST system on key outcomes, including rates of HIV testing, receipt of additional HIV prevention services, and PrEP initiation, compared with standard HBST or clinic-based testing reminders alone. The investigators will also explore the cost effectiveness of the eTEST system under various scenarios compared with relying on traditional, clinic-based testing alone.
Investigators
Eligibility Criteria
Inclusion Criteria
- •report any of the following in the past six months: anal sex without condoms outside of a monogamous partnership with a recently tested, HIV-negative male, having been diagnosed with an STI, or being in an ongoing sexual partnership with an HIV-positive male
- •not tested for HIV in the last 12 months
- •have a stable residence in one of the site metros where they can securely receive packages
- •use an iOS/Android smartphone with a data plan or home wifi
- •fluent in either English or Spanish
Exclusion Criteria
- •currently on PrEP
Outcomes
Primary Outcomes
Model Adjusted Probability of Any HIV Testing
Time Frame: 12 month study period
We used logistic regression with dummy-coded condition assignment as a predictor to test differences in outcomes across experimental conditions. A dummy-coded covariate indicating whether participants reported testing fewer than three times in the 3 years prior to enrolling was included in all models of HIV testing. We fit longitudinal mixed effects models for two outcomes, HIV testing and high-risk CAS events within a given follow-up period, given that these outcomes varied within participants across the study period. We specified distributions appropriate for each outcome (logistic for HIV testing and negative binomial for high-risk CAS events) with suitable link functions, unstructured covariance structures and robust standard errors. Time was included as a continuous covariate. A covariate reflecting pre-enrolment HIV testing and baseline CAS events were included in these models. We used an intent-to-treat approach for all analyses. Missing data were considered missing at random.
Model Adjusted Probabilities of Repeat HIV Testing (>1)
Time Frame: 12 months
We used logistic regression with dummy-coded condition assignment as a predictor to test differences in outcomes across experimental conditions. A dummy-coded covariate indicating whether participants reported testing fewer than three times in the 3 years prior to enrolling was included in all models of HIV testing. We fit longitudinal mixed effects models for two outcomes, HIV testing and high-risk CAS events within a given follow-up period, given that these outcomes varied within participants across the study period. We specified distributions appropriate for each outcome (logistic for HIV testing and negative binomial for high-risk CAS events) with suitable link functions, unstructured covariance structures and robust standard errors. Time was included as a continuous covariate. A covariate reflecting pre-enrolment HIV testing and baseline CAS events were included in these models. We used an intent-to-treat approach for all analyses. Missing data were considered missing at random.
HIV Diagnoses
Time Frame: 12 months
count of participants who were ultimately diagnosed with HIV during the course of the study
Secondary Outcomes
- Model Predicted Probability of Receipt of a Prescription for Pre-exposure Prophylaxis (PrEP)(12 month study period)
- Model Predicted Probability of Receipt of Testing for Other Sexually-transmitted Infections(12 months)