Evidence map›Paper›PMID 42842829›Full record

ArticleJMIR research protocols2026

A US-Based National Virtual Cohort of People Living With HIV at Risk for Viral Nonsuppression: Protocol for the EPI-LoVE Prospective Cohort Study.

Marjan Javanbakht, Lisa B Hightow-Weidman, Sean D Young, Nora E Rosenberg, Kathryn E Muessig, Sarah Schoetz Dean, Aimee Rochelle, Warren Scott Comulada, Pamina M Gorbach

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Marjan JavanbakhtDepartment of Epidemiology, Fielding School of Public Health, University of California Los Angeles, 650 Charles Young Drive, CHS 21-293, Los Angeles, CA, 90095, United States, 1 310-825-3234.ORCID http://orcid.org/0000-0003-0088-3803
Lisa B Hightow-WeidmanInstitute on Digital Health and Innovation, College of Nursing, Florida State University, Tallahassee, FL, United States.ORCID http://orcid.org/0000-0002-2421-923X
Sean D YoungDepartment of Emergency Medicine, UCI School of Medicine, University of California, Irvine, Irvine, CA, United States.ORCID http://orcid.org/0000-0001-6052-4875
Nora E RosenbergDepartment of Health Behavior, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID http://orcid.org/0000-0002-9759-9966
Kathryn E MuessigInstitute on Digital Health and Innovation, College of Nursing, Florida State University, Tallahassee, FL, United States.ORCID http://orcid.org/0000-0002-8522-3240
Sarah Schoetz DeanDepartment of Epidemiology, Fielding School of Public Health, University of California Los Angeles, 650 Charles Young Drive, CHS 21-293, Los Angeles, CA, 90095, United States, 1 310-825-3234.ORCID http://orcid.org/0009-0002-3993-1526
Aimee RochelleInstitute on Digital Health and Innovation, College of Nursing, Florida State University, Tallahassee, FL, United States.ORCID http://orcid.org/0000-0002-1229-9594
Warren Scott ComuladaDepartment of Epidemiology, Fielding School of Public Health, University of California Los Angeles, 650 Charles Young Drive, CHS 21-293, Los Angeles, CA, 90095, United States, 1 310-825-3234.ORCID http://orcid.org/0000-0002-1340-6371
Pamina M GorbachDepartment of Epidemiology, Fielding School of Public Health, University of California Los Angeles, 650 Charles Young Drive, CHS 21-293, Los Angeles, CA, 90095, United States, 1 310-825-3234.ORCID http://orcid.org/0000-0003-2100-7765

Funding

Exploring, Predicting, and Intervening on Long-term Viral suppression Electronically (EPI-LoVE)UG3AI176592 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GORBACH, PAMINA MAE, HIGHTOW-WEIDMAN, LISA B · 2023 to 2024
$4.3M
Big Data Digital Outreach and Epidemiology Methods for HIV Care among Communities of ColorR01MD018548 · NIMHD · UNIVERSITY OF CALIFORNIA-IRVINE · PI Sean Young · 2022 to 2026
$3.9M
NIAID NIH HHS UG3 AI176592NIMHD NIH HHS R01 MD018548
6 · The paper itself

Abstract

Background: Despite advances in HIV treatment, many people living with HIV fail to achieve or maintain viral suppression. Individuals who experience interruptions in HIV care, adherence challenges, and viral nonsuppression are often underrepresented in clinic-based cohort studies. Virtual cohort methodologies offer opportunities to recruit, engage, and retain these populations while integrating longitudinal behavioral, biomarker, and digital engagement data needed to characterize dynamic changes in HIV care engagement and viral suppression. Objective: The Exploring, Predicting, and Intervening on Long-Term Viral Suppression Electronically (EPI-LoVE) study was developed to establish a national virtual cohort of people living with HIV with current viral nonsuppression or at an elevated risk of future viral nonsuppression. We describe the study design, recruitment, data collection methods, retention strategies, and baseline cohort characteristics. Methods: Participants were recruited through digital advertising, a national HIV care provider network, and referrals from previous research studies. Eligible participants were adults living with HIV who were currently virally unsuppressed or considered at elevated risk of future viral nonsuppression based on a history of detectable HIV viral load, recent missed HIV care appointments, or a qualifying mental health diagnosis. Following online screening, participant eligibility was confirmed through telephone verification and supporting documentation. Participants completed online surveys every 3 months and HIV viral load assessments every 6 months over 24 months. Data were collected through a study-specific mobile health platform integrating longitudinal behavioral surveys, remote biomarker collection, app engagement metrics, and frequent "Speak Up" microassessments of time-varying behavioral and psychosocial factors associated with HIV care engagement and viral suppression. Results: The study was funded in May 2023. Participant recruitment occurred between February 2024 and June 2025, and longitudinal data collection is ongoing, with study findings anticipated in spring 2028. A total of 4789 individuals expressed interest in the study, 2739 completed screening, and 2262 met eligibility criteria. A total of 1109 consented, and 1051 enrolled. Among the 2262 eligible participants, 63.4% (n=1435) qualified based on a detectable viral load during the previous 12 months, whereas the remainder qualified based on recent missed HIV care appointments or a qualifying mental health diagnosis. Among the 1051 participants, the cohort was predominantly Black or African American (n=677, 64.4%), with a median age of 36 (IQR 31-43) years; 70.8% (n=744) reported recent substance use, and 63.7% (n=669) screened positive for moderate-to-severe depressive symptoms. Baseline HIV viral load data were obtained from 863 (82.1%) participants. Conclusions: EPI-LoVE demonstrates the feasibility of recruiting, verifying, and engaging a geographically diverse national virtual cohort of people living with HIV at elevated risk of viral nonsuppression. By integrating longitudinal behavioral assessments, biomarker collection, and digital engagement data within a single platform, EPI-LoVE provides a scalable framework for studying the dynamic determinants of HIV care engagement and informing future personalized digital interventions.

Indexed as

HIV InfectionsViral LoadAdultCohort StudiesFemaleHumansMaleMiddle AgedProspective StudiesUnited Statesdigital cohortHIVmHealthmobile healthviral suppressionvirtual cohort

Identifiers

PMID42842829
PMCPMC13645198

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.