Digital Epidemiologic Research on Multilevel Risks for HIV Acquisition and Other Health Outcomes Among Transgender Women in Eastern and Southern United States: Protocol for an Online Cohort.

HIV HIV infection HIV testing United States cohort studies digital research online health public health transgender transgender persons

Journal

JMIR research protocols
ISSN: 1929-0748
Titre abrégé: JMIR Res Protoc
Pays: Canada
ID NLM: 101599504

Informations de publication

Date de publication:
26 Apr 2021
Historique:
received: 28 03 2021
accepted: 31 03 2021
entrez: 26 4 2021
pubmed: 27 4 2021
medline: 27 4 2021
Statut: epublish

Résumé

The HIV epidemic disproportionately impacts transgender women in the United States. Cohort studies identify unique risks for affected populations, but use of facility-based methods may bias findings towards individuals living in research catchment areas, more engaged in health services, or, in the case of transgender populations, those who are open about their transgender identity. Digital clinical trials and other online research methods are increasingly common, providing opportunity to reach those not commonly engaged in research. Simultaneously, there is a need to understand potential biases associated with digital research, how these methods perform, and whether they are accepted across populations. This study aims to assess the feasibility of developing and implementing an online cohort of transgender women to assess risks for HIV acquisition and other health experiences. Further, this study aims to evaluate how an online cohort compares to a site-based, technology-enhanced cohort for epidemiologic research. The overarching goal is to estimate incidence of HIV and other health outcomes among transgender women in eastern and southern United States. This substudy is part of a larger multisite prospective cohort (LITE) conducted among transgender women, which also includes a site-based, technology-enhanced cohort in 6 eastern and southern US cities. The online cohort was launched to enroll and follow participants across 72 cities in the same region and with similar demographic characteristics as the site-based cohort. Participants are followed for 24 months. Adult transgender women are recruited via convenience sampling (eg, peer referrals, social media, and dating apps). Participants reporting negative or unknown HIV status are enrolled in a baseline study visit, complete a sociobehavioral survey, and provide oral fluid specimens to test for HIV. Participants not living with HIV (lab-confirmed) at baseline are offered enrollment into the cohort; follow-up assessments occur every 6 months. Enrollment into the online cohort launched in January 2019. Active recruitment stopped in May 2019, and enrollment officially closed in August 2020. A total of 580 participants enrolled into and are followed in the cohort. A recruitment-enrollment cascade was observed across screening, consent, and completion of study activities. Implementation experiences with HIV test kits highlight the need for heavy staff engagement to support participant engagement, visit completion, and retention, even with automated digital procedures. This study is responsive to increasing research interest in digital observational and intervention research, particularly for populations who are most affected by the HIV epidemic and for those who may otherwise not participate in person. The progression across stages of the recruitment-enrollment cascade provides useful insight for implementation of cohort studies in the online environment. DERR1-10.2196/29152.

Sections du résumé

BACKGROUND BACKGROUND
The HIV epidemic disproportionately impacts transgender women in the United States. Cohort studies identify unique risks for affected populations, but use of facility-based methods may bias findings towards individuals living in research catchment areas, more engaged in health services, or, in the case of transgender populations, those who are open about their transgender identity. Digital clinical trials and other online research methods are increasingly common, providing opportunity to reach those not commonly engaged in research. Simultaneously, there is a need to understand potential biases associated with digital research, how these methods perform, and whether they are accepted across populations.
OBJECTIVE OBJECTIVE
This study aims to assess the feasibility of developing and implementing an online cohort of transgender women to assess risks for HIV acquisition and other health experiences. Further, this study aims to evaluate how an online cohort compares to a site-based, technology-enhanced cohort for epidemiologic research. The overarching goal is to estimate incidence of HIV and other health outcomes among transgender women in eastern and southern United States.
METHODS METHODS
This substudy is part of a larger multisite prospective cohort (LITE) conducted among transgender women, which also includes a site-based, technology-enhanced cohort in 6 eastern and southern US cities. The online cohort was launched to enroll and follow participants across 72 cities in the same region and with similar demographic characteristics as the site-based cohort. Participants are followed for 24 months. Adult transgender women are recruited via convenience sampling (eg, peer referrals, social media, and dating apps). Participants reporting negative or unknown HIV status are enrolled in a baseline study visit, complete a sociobehavioral survey, and provide oral fluid specimens to test for HIV. Participants not living with HIV (lab-confirmed) at baseline are offered enrollment into the cohort; follow-up assessments occur every 6 months.
RESULTS RESULTS
Enrollment into the online cohort launched in January 2019. Active recruitment stopped in May 2019, and enrollment officially closed in August 2020. A total of 580 participants enrolled into and are followed in the cohort. A recruitment-enrollment cascade was observed across screening, consent, and completion of study activities. Implementation experiences with HIV test kits highlight the need for heavy staff engagement to support participant engagement, visit completion, and retention, even with automated digital procedures.
CONCLUSIONS CONCLUSIONS
This study is responsive to increasing research interest in digital observational and intervention research, particularly for populations who are most affected by the HIV epidemic and for those who may otherwise not participate in person. The progression across stages of the recruitment-enrollment cascade provides useful insight for implementation of cohort studies in the online environment.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) UNASSIGNED
DERR1-10.2196/29152.

Identifiants

pubmed: 33900202
pii: v10i4e29152
doi: 10.2196/29152
pmc: PMC8111508
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e29152

Subventions

Organisme : NICHD NIH HHS
ID : P2C HD050924
Pays : United States
Organisme : NIMH NIH HHS
ID : R25 MH067127
Pays : United States
Organisme : NIAID NIH HHS
ID : UG3 AI133669
Pays : United States
Organisme : NIAID NIH HHS
ID : UH3 AI133669
Pays : United States

Informations de copyright

©Andrea L Wirtz, Erin E Cooney, Megan Stevenson, Asa Radix, Tonia Poteat, Andrew J Wawrzyniak, Christopher M Cannon, Jason S Schneider, J Sonya Haw, James Case, Keri N Althoff, Elizabeth Humes, Kenneth H Mayer, Chris Beyrer, Allan E Rodriguez, Sari L Reisner, American Cohort To Study HIV Acquisition Among Transgender Women (LITE) Study Group. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 26.04.2021.

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Auteurs

Andrea L Wirtz (AL)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Erin E Cooney (EE)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Megan Stevenson (M)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Asa Radix (A)

Callen-Lorde Community Health Center, New York, NY, United States.

Tonia Poteat (T)

Center for Health Equity Research, University of North Carolina School of Medicine, Chapel Hill, NC, United States.

Andrew J Wawrzyniak (AJ)

Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, FL, United States.

Christopher M Cannon (CM)

Research and Evaluation, Whitman-Walker Institute, Washington DC, DC, United States.

Jason S Schneider (JS)

Emory University School of Medicine, Atlanta, GA, United States.

J Sonya Haw (JS)

Emory University School of Medicine, Atlanta, GA, United States.

James Case (J)

School of Nursing, Johns Hopkins University, Baltimore, MD, United States.

Keri N Althoff (KN)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Elizabeth Humes (E)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Kenneth H Mayer (KH)

Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University, Boston, MA, United States.
The Fenway Institute, Fenway Health, Boston, MA, United States.

Chris Beyrer (C)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Allan E Rodriguez (AE)

Division of Infectious Diseases, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, United States.

Sari L Reisner (SL)

The Fenway Institute, Fenway Health, Boston, MA, United States.
Division of Endocrinology, Diabetes, and Hypertension, Brigham Women's Hospital, Boston, MA, United States.
Department of Medicine, Harvard Medical School, Harvard University, Boston, MA, United States.
Department of Epidemiology, Harvard TH Chan School of Public Health, Harvard University, Boston, MA, United States.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Classifications MeSH