Not provided
| ID | Type | Description | Link |
|---|---|---|---|
| 1R01MH114891-01A1 | U.S. NIH Grant/Contract | View source |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| National Institute of Mental Health (NIMH) | NIH |
| University of Southern California | OTHER |
| The Miriam Hospital | OTHER |
| University of Mississippi Medical Center |
Not provided
Not provided
Not provided
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.
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.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control | No Intervention | Participants will receive SMS text message reminders to get tested for HIV in a clinic. | |
| Standard Self-Testing | Active Comparator | Participants will receive an HIV self-test kit in the mail with no standardized follow-up from counselors. |
|
| Enhanced Self-Testing | Experimental | Participants will receive an HIV self-test kit and will be contacted via telephone for counseling within 24 hours of opening their test. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| HIV self-test | Diagnostic Test | Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) |
|
| Measure | Description | Time Frame |
|---|---|---|
| Model Adjusted Probability of Any HIV Testing | 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. | 12 month study period |
| Model Adjusted Probabilities of Repeat HIV Testing (>1) | 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. | 12 months |
| HIV Diagnoses | count of participants who were ultimately diagnosed with HIV during the course of the study |
| Measure | Description | Time Frame |
|---|---|---|
| Model Predicted Probability of Receipt of a Prescription for Pre-exposure Prophylaxis (PrEP) | We used logistic regression with dummy-coded condition assignment as a predictor to test differences in outcomes across experimental conditions. A binary variable reflecting whether participants had ever had a PrEP prescription in the past was included for the PrEP prescription model. We specified two-way interactions between these covariates and condition assignment in all models, but none were significant and were excluded. |
| Measure | Description | Time Frame |
|---|---|---|
| Average Predicted Number of High-risk Casual Anal Sex (CAS) Events With Partners of Unknown HIV and PrEP Status | We used logistic regression with dummy-coded condition assignment as a predictor to test differences in outcomes across experimental conditions. We specified two-way interactions between these covariates and condition assignment in all models, but none were significant and were excluded. 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. |
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Tyler B Wray, PhD | Brown University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Brown University School of Public Health | Providence | Rhode Island | 02906 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32677999 | Derived | Wray TB, Chan PA, Klausner JD, Mena LA, Brock JB, Simpanen EM, Ward LM, Chrysovalantis S. eTest: a limited-interaction, longitudinal randomized controlled trial of a mobile health platform that enables real-time phone counseling after HIV self-testing among high-risk men who have sex with men. Trials. 2020 Jul 16;21(1):654. doi: 10.1186/s13063-020-04554-1. |
Not provided
Not provided
Once the final dataset for this research has been assembled, the Project Coordinator will create an archival copy (which will contain no personally identifying information) to store, along with an electronic version of the codebooks of the study. Versions will be available in English, and outside investigators will be able to utilize the data by contacting the PIs and describing their purpose for using the data.
Data will become available after the publication of primary analyses. Data will be available for as long as requests are made.
De-identified individual participant data will be available to outside investigators after the primary analyses have been conducted and are published.
Not provided
Not provided
Not provided
Not provided
| ID | Title | Description |
|---|---|---|
| FG000 | Control | Participants will receive SMS text message reminders to get tested for HIV in a clinic. |
| FG001 | Standard Self-Testing | Participants will receive an HIV self-test kit in the mail with no standardized follow-up from counselors. HIV self-test: Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) |
| FG002 | Enhanced Self-Testing | Participants will receive an HIV self-test kit and will be contacted via telephone for counseling within 24 hours of opening their test. HIV self-test: Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) Counseling: Post-Test HIV Risk ReductionCounseling |
| Title | Milestones | Reasons Not Completed | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
|
Not provided
Not provided
| ID | Title | Description |
|---|---|---|
| BG000 | Control | Participants will receive SMS text message reminders to get tested for HIV in a clinic. |
| BG001 | Standard Self-Testing | Participants will receive an HIV self-test kit in the mail with no standardized follow-up from counselors. HIV self-test: Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Mean |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Model Adjusted Probability of Any HIV Testing | 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. | Posted | Mean | 95% Confidence Interval | percent probability | 12 month study period |
|
12 months
Not provided
Not provided
| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Control | Participants will receive SMS text message reminders to get tested for HIV in a clinic. |
Not provided
Not provided
Not provided
| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Dr. Tyler Wray | Brown University | 4018636659 | tyler_wray@brown.edu |
Not provided
| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Oct 1, 2018 | Feb 5, 2025 | Prot_SAP_002.pdf |
| ICF | No | No | Yes | Informed Consent Form | Sep 1, 2021 | Feb 5, 2025 | ICF_003.pdf |
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D015658 | HIV Infections |
| ID | Term |
|---|---|
| D000086982 | Blood-Borne Infections |
| D003141 | Communicable Diseases |
| D007239 | Infections |
| D015229 | Sexually Transmitted Diseases, Viral |
Not provided
Not provided
| ID | Term |
|---|---|
| D003376 | Counseling |
| ID | Term |
|---|---|
| D008605 | Mental Health Services |
| D004191 | Behavioral Disciplines and Activities |
| D003153 | Community Health Services |
| D006296 | Health Services |
Not provided
Not provided
| OTHER |
Not provided
Not provided
Not provided
Participants are not informed of their condition assignment, but may infer it via the procedures they are provided. Both investigators and staff assessing outcomes are blinded to participants' group assignments.
| Counseling | Behavioral | Post-Test HIV Risk ReductionCounseling |
|
| 12 months |
| 12 month study period |
| Model Predicted Probability of Receipt of Testing for Other Sexually-transmitted Infections | 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. A similar covariate for STI testing was included in the STI testing model. We specified two-way interactions between these covariates and condition assignment in all models, but none were significant and were excluded. | 12 months |
| 12 months |
| BG002 | Enhanced Self-Testing | Participants will receive an HIV self-test kit and will be contacted via telephone for counseling within 24 hours of opening their test. HIV self-test: Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) Counseling: Post-Test HIV Risk ReductionCounseling |
| BG003 | Total | Total of all reporting groups |
| years |
|
| Sex/Gender, Customized | Count of Participants | Participants |
|
| Ethnicity (NIH/OMB) | Count of Participants | Participants |
|
| Race (NIH/OMB) | Count of Participants | Participants |
|
| Region of Enrollment | Number | participants |
|
| OG000 |
| Control |
Participants will receive SMS text message reminders to get tested for HIV in a clinic. |
| OG001 | Standard Self-Testing | Participants will receive an HIV self-test kit in the mail with no standardized follow-up from counselors. HIV self-test: Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) |
| OG002 | Enhanced Self-Testing | Participants will receive an HIV self-test kit and will be contacted via telephone for counseling within 24 hours of opening their test. HIV self-test: Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) Counseling: Post-Test HIV Risk ReductionCounseling |
|
|
| Primary | Model Adjusted Probabilities of Repeat HIV Testing (>1) | 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. | Posted | Mean | 95% Confidence Interval | percent probability | 12 months |
|
|
|
| Primary | HIV Diagnoses | count of participants who were ultimately diagnosed with HIV during the course of the study | Posted | Count of Participants | Participants | 12 months |
|
|
|
| Secondary | Model Predicted Probability of Receipt of a Prescription for Pre-exposure Prophylaxis (PrEP) | We used logistic regression with dummy-coded condition assignment as a predictor to test differences in outcomes across experimental conditions. A binary variable reflecting whether participants had ever had a PrEP prescription in the past was included for the PrEP prescription model. We specified two-way interactions between these covariates and condition assignment in all models, but none were significant and were excluded. | Posted | Mean | 95% Confidence Interval | percent probability | 12 month study period |
|
|
|
| Secondary | Model Predicted Probability of Receipt of Testing for Other Sexually-transmitted Infections | 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. A similar covariate for STI testing was included in the STI testing model. We specified two-way interactions between these covariates and condition assignment in all models, but none were significant and were excluded. | Posted | Mean | 95% Confidence Interval | percent probability | 12 months |
|
|
|
| Other Pre-specified | Average Predicted Number of High-risk Casual Anal Sex (CAS) Events With Partners of Unknown HIV and PrEP Status | We used logistic regression with dummy-coded condition assignment as a predictor to test differences in outcomes across experimental conditions. We specified two-way interactions between these covariates and condition assignment in all models, but none were significant and were excluded. 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. | Posted | Mean | 95% Confidence Interval | events | 12 months |
|
|
|
| 0 |
| 270 |
| 0 |
| 270 |
| 0 |
| 270 |
| EG001 | Standard Self-Testing | Participants will receive an HIV self-test kit in the mail with no standardized follow-up from counselors. HIV self-test: Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) | 0 | 265 | 0 | 265 | 0 | 265 |
| EG002 | Enhanced Self-Testing | Participants will receive an HIV self-test kit and will be contacted via telephone for counseling within 24 hours of opening their test. HIV self-test: Home delivery of HIV self-test kits (OraSure OraQuick Rapid HIV test) Counseling: Post-Test HIV Risk ReductionCounseling | 0 | 275 | 0 | 275 | 0 | 275 |
Not provided
Not provided
| D012749 | Sexually Transmitted Diseases |
| D016180 | Lentivirus Infections |
| D012192 | Retroviridae Infections |
| D012327 | RNA Virus Infections |
| D014777 | Virus Diseases |
| D000091662 | Genital Diseases |
| D000091642 | Urogenital Diseases |
| D007153 | Immunologic Deficiency Syndromes |
| D007154 | Immune System Diseases |
| D005159 | Health Care Facilities Workforce and Services |