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Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66921, first published .
The American Transformative HIV Study: Protocol for a US National Cohort of Sexual and Gender Minority Individuals With HIV

The American Transformative HIV Study: Protocol for a US National Cohort of Sexual and Gender Minority Individuals With HIV

The American Transformative HIV Study: Protocol for a US National Cohort of Sexual and Gender Minority Individuals With HIV

Authors of this article:

Christian Grov1 Author Orcid Image ;   Alexa B D'Angelo1 Author Orcid Image ;   Chloe Mirzayi1 Author Orcid Image ;   Michelle Dearolf1 Author Orcid Image ;   Elena Hoeppner1 Author Orcid Image ;   Yan Guo1 Author Orcid Image ;   Nicole Richards1 Author Orcid Image ;   Rifa Ehsan1 Author Orcid Image ;   Sarah Kulkarni1 Author Orcid Image ;   Denis Nash1 Author Orcid Image ;   Viraj V Patel2 Author Orcid Image ;   Dustin T Duncan3 Author Orcid Image ;   Meredith Ray4 Author Orcid Image ;   Tyler Bartholomew5 Author Orcid Image ;   Jennifer Manuzak6 Author Orcid Image ;   Jennifer Manuel7 Author Orcid Image ;   Kathryn McCollister5 Author Orcid Image ;   Drew Westmoreland8 Author Orcid Image ;   Adam W Carrico9 Author Orcid Image
Article Authors Cited by Tweetations Metrics

    1City University of New York Graduate School of Public Health and Health Policy, 55 West 125 Street, New York, NY, United States

    2Albert Einstein College of Medicine, Montefiore Health System, New York, NY, United States

    3Columbia University, New York, NY, United States

    4The University of Memphis, Memphis, TN, United States

    5University of Miami, Coral Gables, FL, United States

    6Tulane University, New Orleans, LA, United States

    7University of California San Francisco, San Francisco, CA, United States

    8University of Florida, Gainesville, FL, United States

    9Florida International University, Miami, FL, United States

    Corresponding Author:

    Christian Grov, MPH, PhD


    Background: Sexual and gender minority (SGM) individuals represent 2%‐5% of the US population, yet continue to account for more than two-thirds of new HIV infections annually.

    Objective: This study seeks to identify multilevel (ie, structural, psychological, and social) and biobehavioral (ie, rectal cytokines or chemokines) determinants of amplified HIV seroconversion risk for SGM individuals, including those who use methamphetamine.

    Methods: The American Transformative HIV Study is an ongoing web-based cohort study of 5364 SGM individuals from all 50 US states and Puerto Rico, enrolled in 2022 and 2023, and will be followed through 2027. We oversampled persons who use methamphetamine (2846/5364, 53.1%). We used established web-based strategies to enroll individuals aged 16‐49 years at high risk of HIV acquisition via sexual networking apps. To be eligible, participants had to report meeting objective criteria for HIV pre-exposure prophylaxis (PrEP) care, but not be taking PrEP. Participants complete annual web-based surveys (baseline, 12, 24, and 36 months) and are asked to provide self-collected oral fluid samples for HIV testing and 2 rectal swabs (the Aptima Multitest Swab and the Zymo DNA/RNA Shield swab) following each assessment. Oral fluid samples are analyzed immediately, while rectal swabs are banked for a future nested case-cohort analysis to assess changes in inflammatory markers following a new infection.

    Results: Nearly all participants (4542/5364, 84.7%) were cisgender men, 3.7% (201/5364) were transgender women, and 1.1% (61/5364) were transgender men who have sex with men. There were also 560 (10.4%) individuals who self-identified outside of the gender binary—all reported being assigned male sex at birth. In total, 56.5% (3031/5364) were persons of color, and 31.8% (1714/5365) were aged 16 to 29 years. In total, 4054 baseline HIV test kits were returned, including 371 HIV reactive samples—3.3% (69/2210) were HIV-positive among those who did not report methamphetamine use, and 15.5% (302/1944) were HIV-positive among those reporting methamphetamine use. Based on participant’s HIV results as well as self-reporting when their most recent prior HIV-negative test was, we estimated that the incidence rate in this cohort in the 12-month period leading up to study enrollment was 10.06 (95% CI 8.65‐11.64) per 100 person-years among those reporting methamphetamine use compared with 2.04 (95% CI 1.49‐2.73) among those not reporting methamphetamine use per 100 person-years.

    Conclusions: A large, US national, and racially diverse web-based cohort of SGM individuals at high risk for HIV has been successfully enrolled and will be followed through 2027. Persons who use methamphetamine have been oversampled and demonstrated an exceptionally greater risk for HIV. Our study will offer insight into the development and implementation of new interventions, which aim to have a meaningful impact on HIV transmission.

    JMIR Public Health Surveill 2025;11:e66921

    doi:10.2196/66921

    Keywords

    HIV testing; rectal cytokines or chemokines; cohort research; nested case-cohort designs; American Transformative HIV Study; AMETHST; United States; sexual and gender minority; methamphetamine; web-based survey; oral fluid; rectal swab 


    Background

    Sexual and gender minority (SGM) individuals represent 2%‐5% of the US population, yet continue to account for more than two-thirds of new HIV infections annually [1-4]. The Centers for Disease Control and Prevention has estimated that 1 in 6 sexual minority men will acquire HIV in their lifetime, including half of Black sexual minority men and one-quarter of Latino sexual minority men [2,5]. Meanwhile, gender minority individuals (transgender men and transgender women) accounted for 2% of new HIV infections in 2019 (while representing ~1% of the US population) [6-8], with transwomen of color most impacted [8]. A Centers for Disease Control and Prevention survey of transgender women across 7 US cities found that 42% of respondents were living with HIV, with 65% of American Indian or Alaska Natives, 62% of Black transwomen, and 35% of Latinx transwomen living with HIV [9]. Our ability to avert new infections may be further challenged by racial disparities in pre-exposure prophylaxis (PrEP) uptake [10].

    Methamphetamine use is an enduring and resurgent epidemic in SGM communities [11-15]. Rates of methamphetamine use are high among SGM individuals, ranging from 7.4% to 30%. Although methamphetamine use may have declined somewhat after significant public health attention in the early- and mid-2000s [16,17], it is again on the rise [16,18-22]. Findings from our team and others [23,24] demonstrate that methamphetamine use is disproportionately impacting SGM individuals who are from racial and ethnic minority groups and accounts for one-in-three new HIV infections in SGM individuals [25]. There are behavioral, structural, psychosocial, and biological pathways through which methamphetamine increases the risk for HIV transmission.

    Mechanisms That Increase HIV Vulnerability

    Behavioral

    Methamphetamine increases sexual libido while decreasing inhibitions [26-28]. Because it is a stimulant, sexual minority men using methamphetamine will often engage in condomless anal sex (CAS) with multiple partners for prolonged periods (1‐3 days) [28-30], with less regard to HIV prevention modalities.

    Structural

    High rates of methamphetamine use and its social acceptability in sexual minority men communities potentiate exposure risk through social or sexual networks [31-34]. Many sexual minority men are also highly likely to reside in concentrated neighborhoods within urban centers where the public health impact of methamphetamine use is amplified. Meanwhile, institutionalized and cultural stigma, homophobia, and discrimination affect the health of SGM individuals [35-41], which can keep them from seeking HIV prevention services and substance use disorder treatment [42]. These can include individualized minority stress exposures (eg, being subject to a homophobic slur) and structural determinants (eg, living in an area with unfavorable SGM policies or laws).

    Psychosocial

    There are known psychosocial determinants that increase the risk for methamphetamine use and HIV. Syndemic theory posits that multiple co-occurring epidemics work synergistically to increase—for instance—HIV vulnerability in SGM individuals [43-48]. In syndemic theory, “epidemics” refers both to epidemics of disease [49] (eg, mental health issues, methamphetamine use, and HIV) and social epidemics (eg, poverty, racism, and homophobia). Among SGM individuals—especially SGM persons of color—simultaneous and synergistic epidemics increase HIV vulnerability [43,47,48,50,51]. For example, studies of Black and Latino sexual minority men draw associations among methamphetamine use, mental health outcomes, and condomless sex, all of which could amplify HIV vulnerability [51].

    Biological

    Methamphetamine potentiates rectal immune dysregulation in SGM individuals, which could amplify the biological risk for HIV. Approximately 70% of HIV infections in sexual minority men occur during receptive CAS [52-54], but little is known about the correlates and consequences of rectal immune dysregulation relevant to HIV [55]. Methamphetamine directly decreases parasympathetic tone [56], increasing intestinal permeability and altering rectal immune responses by changing the gut microbiome [57]. Methamphetamine also directly damages gut barrier integrity, which could amplify rectal immune dysregulation [58].

    Study Objective and Hypothesis

    The objective of this study is to identify multilevel (ie, structural, psychological, and social) and biological (ie, rectal cytokines or chemokines) determinants of amplified HIV seroconversion risk for SGM individuals who use methamphetamine to guide targeted, combination interventions to reduce HIV incidence. We hypothesize that those reporting methamphetamine use would have higher HIV prevalence as well as higher recent HIV incidence than those not reporting methamphetamine use.


    Overview

    We sought to recruit, via sexual networking apps, a racially and geographically diverse sample of HIV-negative SGM individuals who are not on PrEP, to better inform the design, implementation, scale-up, and evaluation of HIV prevention programs. Moreover, to understand the multilevel biobehavioral pathways through which methamphetamine amplifies HIV risk, we sought to overenroll persons who use methamphetamine. We describe the protocol and baseline participant characteristics for the American Transformative HIV Study (AMETHST).

    Target Population

    The AMETHST cohort study used established [59,60], web-based strategies to enroll a large sample of HIV-negative men, transmen, and transwomen who have sex with men, aged 16 to 49 years, and who are at high risk of HIV acquisition—defined as meeting objective criteria for PrEP care but not being on PrEP at the time of enrollment. The cohort will be followed prospectively for 36 months to examine outcomes including PrEP uptake or discontinuation, HIV acquisition, changing patterns of methamphetamine use, and rectal immune dysregulation. We aimed to enroll a cohort of participants at high risk for HIV that was geographically diverse (ie, with representation from every US state), racially and ethnically diverse (n=3031, 56.5% are participants of color), and young (n=1704, 31.8% aged 16‐29 years). We overenrolled persons who reported recent (<3 months) methamphetamine use (n=2518). All study procedures were approved by the City University of New York institutional review board, and we obtained a waiver of parental consent for those aged 16 and 17 years. Those aged 16 or 17 years were presented with additional multiple-choice questions about their comprehension of the study consent form (that they were required to answer correctly) as part of the assent process. We include those aged 16 and 17 years because data suggest that this is about the age when many men who have sex with men begin to become sexually active with other men [61], and thus vulnerable to HIV. We obtained a waiver of parental consent, given the minimal risk posed by the study and that requiring parental consent could potentially endanger participants who may not be “out” to their parents [62].

    Cohort Eligibility and Recruitment

    Enrollment for AMETHST began in August 2022 and concluded in August 2023. Participants were recruited via advertisements on men-for-men geosocial sexual networking mobile phone apps. Some advertisements were more generic in nature, while others used imagery (eg, smoke exhaled from methamphetamine use) and textual cues that would suggest the study was seeking to enroll those who use methamphetamine (see Multimedia Appendix 1 for example advertisements). Of note, app developers forbid both its user base as well as advertisers from mentioning drug use directly. To subvert this, users have developed evolving coded language or emojis to communicate interest in finding meth-using partners without setting off automatic filters or censors [63,64]. Our advertisements were geotargeted to individuals using apps inside the United States. Eligibility criteria are shown in Table 1; however, once we reached saturation of individuals who do not use methamphetamine, we limited enrollment to just those who met these criteria and reported recent methamphetamine use (defined as at least 1 instance of use in the past 3 months). Apps themselves require users to indicate that they are older than 18 years of age. Individuals younger than 18 years of age are known to bypass this by saying that they are older than 18 years when they join. It is for this reason we allowed for individuals aged 16 and 17 years of age to enroll in our study (n=123).

    Potential participants were directed to a secure screening survey in their device’s web browser and presented with a screen describing study participation and eliciting informed consent. The screening survey took approximately 5‐10 minutes to complete and included core eligibility criteria for the study. As the mpox outbreak was peaking in the United States at the time recruitment launched, the survey also included questions on mpox, the results of which have been published elsewhere [65]. There was no incentive for completing the screening survey. However, those who were eligible were sent a baseline survey, for which they received an incentive. Upon completion of the baseline survey, participants were mailed at-home collection kits for HIV testing (ie, oral fluid sample) and rectal swabs—all to be returned via mail to a laboratory for testing or storage. Upon receipt at the laboratory, participants received an incentive for their HIV test kit and a second incentive for returning the rectal swabs (described below).

    Table 1. Eligibility criteria for the American Transformative HIV Study.
    Eligibility criteriaParticipants who used methamphetamine in the last 3 months (n=2846), n (%)Participants who had not used methamphetamine in the last 3 months (n=2518), n (%)Chi-square (df)P value
    Core eligibility criteria (all participants must meet these criteria)—a
    Aged 16 to 49 years2846 (100)2518 (100)—
    At least 2 men sex partners in the past 90 days2846 (100)2518 (100)—
    Not currently participating in a clinical trial for an HIV vaccine or pre-exposure prophylaxis2846 (100)2518 (100)—
    Not currently on pre-exposure prophylaxis2846 (100)2518 (100)—
    Never diagnosed with HIV (self-report)2846 (100)2518 (100)—
    Currently residing in the United States or territories2846 (100)2518 (100)—
    Not cisgender woman2846 (100)2518 (100)—
    Additional eligibility criteria (participants must meet at least 1)
    ≥1 receptive condomless anal sex acts with a men partner in the last 6 months2384 (83.8)2102 (83.5)0.1 (1).78
    ≥3 insertive condomless anal sex acts with a men partner in the last 6 months1913 (67.2)1277 (50.7)150.9 (1)<.001
    Used methamphetamine in the last 3 months2846 (100)0 (0)——
    Syphilis diagnosis in the last 6 months149 (5.2)55 (2.2)34.0 (1)<.001
    Shared injection drug needles in the last 12 months236 (8.3)3 (0.1)209.6 (1)<.001

    aNot applicable.

    Preventing Fraudulent Participation

    We enacted multiple measures to minimize repeat participation and fraudulent participants, including recording IP addresses and using cookies to block repeated attempts. Our databases flagged duplicate contact information. Mailing addresses were validated with the US postal service, and participants were required to provide a unique valid phone number (ie, text verification). Multiple entries were identified by email addresses, mailing addresses, or phone numbers. In addition, the data manager manually checked for duplicate entries during baseline data collection. We also assessed the time to completion of our web-based surveys and checked for variability in response sets.

    Baseline Web-Based Survey

    Participants were emailed and texted a unique link to a baseline survey. The web-based survey assessed psychosocial, demographic, social network, and behavioral characteristics (behaviors including sexual behavior and substance use). The full measures for the screening survey and baseline survey are included in Multimedia Appendix 2. The survey took approximately 45 minutes to complete, and participants were compensated US $40 for completing the survey.

    Biomarkers

    Upon completing the baseline survey, participants were sent at-home specimen collection kits. This kit included the OraSure HIV-1 specimen collection device and 2 rectal swabs (the Aptima Multitest Swab and the Zymo DNA/RNA Shield swab). Participants were also provided access to a study video along with printed instructions on collecting their specimens. Upon receipt at the laboratory, oral fluid samples were used for HIV antibody testing using the Avioq HIV-1 enzyme immunoassay [66]. Any samples testing positive with this assay were subsequently tested with the Food and Drug Administration–cleared BioRad Geenius HIV-1/2 as a supplemental antibody test, which has been shown to reliably detect HIV-1 antibodies in oral fluid specimens with mean enzyme immunoassay signal-to-cutoff greater than or equal to 3.00 [66]. The laboratory returned all results to our team, and we in turn informed the participants. Those with HIV-negative results were informed by email, and those with HIV-reactive results were informed via phone following a published protocol [67].

    Rectal swabs received by the laboratory are being banked or frozen until all follow-up assessments are complete, at which point we will be conducting a nested case-cohort study [68] to examine biological vulnerability to HIV. This is described in greater detail below. Participants were compensated US $25 for returning their HIV test kit and US $25 for returning rectal swabs.

    Participants With Unknown Baseline HIV Status

    Participants who screened eligible and completed a baseline questionnaire, but did not return an HIV test kit (baseline serostatus not confirmed with a biomarker), will continue to be followed and asked at regular intervals to submit an oral fluid sample for HIV testing using the at-home sampling kit. For the purposes of prospectively estimating HIV incidence in the AMETHST cohort, these individuals will be excluded. However, we will conduct post hoc sensitivity analyses that make assumptions about having similar, lower, or higher HIV risk profiles than the AMETHST participants for whom baseline HIV status was determined. Key questions answered by including these participants will include identifying psychosocial and demographic factors associated with a timeline to sample return (for those who return a sample at a future wave) as well as how these factors differentiate those who do not return a sample going forward.

    HIV Incidence in the 12 Months Before Cohort Enrollment

    We estimated pre-enrollment HIV incidence using baseline data on HIV serostatus and HIV testing history prior to joining the study. Using these data, we reconstructed a cohort of individuals who could all be classified as HIV-negative as of 12 months before cohort enrollment. For those HIV-positive at enrollment, we estimated the time of seroconversion using self-reported data on the timing of their last HIV-negative test. Specifically, those self-reporting a negative HIV test within 6 months of AMETHST enrollment were classified as being HIV-negative as of 6 months before enrollment, with seroconversion timing assumed to be distributed evenly during the 6 months leading up to study enrollment. Similarly, participants self-reporting a negative HIV test 7 to 12 months before AMETHST enrollment were classified as being HIV-negative as of 12 months before enrollment, with seroconversion timing assumed to be distributed evenly during the 12 months leading up to study enrollment. We also estimated HIV incidence for the 6-month period leading up to cohort enrollment. For the purposes of identifying boundaries around minimum and maximum incidence rates, we conducted sensitivity analyses representing assumptions for the timing of seroconversion at both extremes.

    All participants are provided information on where they can access free and low-cost HIV testing outside of the study as well as information on PrEP and where they can get access to PrEP for no or low cost. Participants are also welcome to reach out to our team if they need assistance getting connected to HIV prevention resources or HIV care.

    Statistical Power

    This study is sufficiently powered for all future analyses assessing the main aims of the cohort (ie, impact of methamphetamine on HIV seroconversion and PrEP uptake) considering expected HIV seroconversion rates, PrEP uptake rates, methamphetamine use, and response rates based on our prior work [69].

    Ethical Considerations

    All participants provided informed consent. The AMETHST study protocol was approved by the Institutional Review Board of the City University of New York (approval 2022-0378-PHHP). Participant contact information is stored separately from their data or responses and linked only by a unique ID. At enrollment, participants were compensated US $40 for completing the survey, US $25 for returning their HIV test kit, and US $25 for returning rectal swabs.


    Overview

    In total, 71,205 individuals began our screening survey, and 42,132 (59%) completed it. Of the noncompleters, most closed their browser window on the informed consent page (ie, immediately). Of the 42,132 who completed the screening survey, 9115 appeared to be eligible and were sent a baseline computer-assisted self-interview (CASI) survey, 88.3% (n=8049) of whom completed that survey. However, among those completing this baseline CASI (n=8049), 2716 were removed from further consideration (1675/2716, 61.7% of these were explicitly removed because the participant did not verify a working phone number with the study team; a measure in place to prevent fraudulent or duplicate participants).

    Of the participants who completed the baseline CASI and verified a phone number, 5364 were eligible to receive and were mailed HIV and rectal test kits. We consider these 5364 individuals to be enrolled in the cohort. Participants resided in all 50 states and Puerto Rico (Figures 1 and 2).

    Of those 5364 who were sent a kit, 78.2% returned at least 1 of the specimens (be it an HIV test kit or at least 1 rectal sample). The majority of those sent kits returned their HIV test kit (n=4054, 76%). Throughout the course of enrollment, we had to resend packages to participants a total of 1720 times (this includes 920 participants who had to have a package resent once and 800 participants who had to have a package resent more than once). Of these resent packages, 469 were partial kits (eg, an HIV test kit or a rectal swab). Reasons for resent kits varied and included participants reporting a package not having arrived to them (n=505), packages not received by the laboratory (n=71), some issue with the kit itself requiring the participant to resample (eg, insufficient sample and sample damaged in transit; n=524), the participant misplacing the kit (n=224), the participant moving or asking to send the kit to a different address (n=275), or other factors or a combination of the aforementioned (n=196). Of the participants who returned kits (n=4191), 4085 (97.5%) returned their HIV test kit and at least 1 rectal sample, 73 (1.7%) participants returned just their HIV test kits, and 33 (0.8%) participants returned at least 1 rectal sample but no HIV test kit.

    As shown in Table 1, those reporting methamphetamine use were significantly more likely to report nearly all the “additional eligibility” criteria, including 3 or more insertive CAS acts with a man in the last 3 months (67.2% vs 50.7%), a syphilis diagnosis in the last 6 months (5.2% vs 2.2%), and sharing injection drug needles in the last 12 months (8.3% vs 0.1%).

    ‎
    Figure 1. Geographic distribution of participants. Those in green had HIV-positive test results.
    ‎
    Figure 2. Participant flow through study procedures at enrollment. CASI: computer-assisted self-interview; STI: sexually transmitted infection.

    Baseline Characteristics of the AMETHST Cohort

    Nearly all (4542/5364, 84.7%) were cisgender men, 3.7% (201/5364) were transgender women, and 1.1% (61/5364) were transgender men who have sex with men (Table 2). There were also 560 (10.4%) individuals who self-identified outside of the gender binary—all reported being assigned male sex at birth. In total, 56.5% (3031/5364) were persons of color, and 31.8% (1714/5364) were younger individuals aged 16 to 29 years.

    As shown in Table 2, those reporting methamphetamine use were more likely to be White, transgender women or nonbinary, nongay identified, older, and to have never heard of PrEP. They were less likely to have health insurance, have a primary care provider, and were significantly more likely to have tested for HIV more than a year ago or had never been tested for HIV in their lives.

    Table 2. Demographic characteristics for the American Transformative HIV Study cohort study.
    Participants who used methamphetamine in the last 3 months (n=2846), n (%)Participants who had not used methamphetamine in the last 3 months (n=2518), n (%)Chi-square (df)P value
    Race or ethnicity242.8 (4)<.001
    Asian or Pacific Islander37 (1.3)153 (6.1)
    Hispanic or Latinx649 (22.8)829 (32.9)
    Non-Hispanic Black350 (12.3)416 (16.5)
    Non-Hispanic White1452 (51)881 (35)  
    Multiracial or other358 (12.6)239 (9.5)  
    Gender40.5 (3)<.001
    Cisgender male2342 (82.3)2200 (87.4)  
    Transgender woman137 (4.8)64 (2.5)  
    Transgender man25 (0.9)36 (1.4)  
    Nonbinary or other342 (12)218 (8.7)  
    Sexual identity123.8 (2)<.001
    Gay1760 (61.9)1912 (75.9)  
    Bisexual664 (23.3)355 (14.1)  
    Other422 (14.8)251 (10)  
    Age (years)240.3 (6)<.001
    16‐1931 (1.1)92 (3.7)  
    20‐24179 (6.3)369 (14.7)  
    25‐29467 (16.4)566 (22.5)  
    30‐34731 (25.7)613 (24.3)  
    35‐39630 (22.1)438 (17.4)  
    40‐44505 (17.7)273 (10.8)  
    45‐49303 (10.6)167 (6.6)  
    Has health insurance1947 (68.4)1989 (79)76.5 (1)<.001
    Has a primary care provider1174 (41.3)1505 (59.8)183.3 (1)<.001
    Never heard of PrEPa83 (2.9)41 (1.6)9.8 (1).001
    HIV testing history175.9 (3)<.001
    In the last 6 months882 (31)1017 (40.4)  
    In the last 7‐12 months862 (30.3)940 (37.3)  
    More than a year ago882 (31)417 (16.6)  
    Never been tested for HIV220 (7.7)144 (5.7)  

    aPrEP: pre-exposure prophylaxis.

    Completion of Baseline HIV Testing and Returning Rectal Swabs

    All 5364 participants enrolled in the cohort were mailed specimen collection kits (oral fluid for HIV testing and 2 rectal swabs) via United States Postal Service, of which 74.5% (3998/5364) returned both their HIV test kit and at least 1 rectal sample. An additional 3.6% (194/5364) partially returned their samples (either an HIV test kit or at least 1 rectal sample). The remaining did not return their kits, and failure to return kits was higher among those who reported methamphetamine use (28.6% vs 14.3%) despite being sent multiple reminders to do so. Among those having returned an HIV test kit, 3.3% were HIV-positive among those who did not report methamphetamine use, and 15.5% were HIV-positive among those reporting methamphetamine use. Among those with HIV-negative results (n=3683), those reporting methamphetamine use were significantly more likely to report their last HIV test was either more than a year ago (27% vs 15.5%) or having either never tested for HIV or not knowing the results of their last test (6.5% vs 3.9%). In contrast, among those with HIV-positive results (n=371), there were no significant differences in how long ago they previously tested HIV-negative (Table 3).

    Table 3. Biomarkers and HIV results for the American Transformative HIV Study.
    Participants who used methamphetamine in the last 3 months (n=2846), n (%)Participants who had not used methamphetamine in the last 3 months (n=2518), n (%)Chi-square (df)P value
    Returned sampling kits to the laboratory185.2 (2)<.001
     Did not return either kit813 (28.6)359 (14.3)
     Partial kit return (HIV or rectal)128 (4.5)66 (2.6)
     Returned all kits (HIV and at least 1 rectal)1905 (66.9)2093 (83.1)
    HIV test kit result (only those with valid HIV test kit results, n=4054)183.1 (1)<.001
     HIV-negative1642 (84.5)2041 (96.7)
     HIV-positive302 (15.5)69 (3.3)
    Date of most recent HIV test (only those with valid HIV-negative results, n=3683)95.4 (3)<.001
     Self-reported HIV-negative test <6 months ago585 (35.6)843 (41.3)
     Self-reported HIV-negative test 7‐12 months ago507 (30.9)801 (39.2)
     Self-reported HIV-negative test >12 months ago443 (27)317 (15.5)
     No previous HIV test, indeterminate result, or do not know or do not remember107 (6.5)80 (3.9)
    Date of most recent HIV test (only those with valid HIV-positive results, n=371)4.7 (3).19
     Self-reported HIV-negative test<6 months ago54 (17.9)13 (18.8)
     Self-reported HIV-negative test 7‐12 months ago86 (28.5)23 (33.3)
     Self-reported HIV-negative test >12 months ago137 (45.4)23 (33.3)
     No previous HIV test, indeterminate result, or do not know or do not remember25 (8.3)10 (14.5)

    HIV Status and Estimating the Cohort HIV Incidence Rate Before AMETHST Enrollment

    Based on participants’ HIV results as well as self-reporting when their most recent HIV-negative test was, we estimated that the incidence rate in this cohort in the 12-month period leading up to study enrollment was 10.06 (95% CI 8.65‐11.64) per 100 person-years among those reporting methamphetamine use compared with 2.04 (95% CI 1.49‐2.73) among those not reporting methamphetamine use per 100 person-years. The estimate for the 6-month period leading up to enrollment was 8.85 (95% CI 7.02‐11.01) per 100 person-years among those reporting methamphetamine use compared with 1.85 (95% CI 1.14‐2.83) among those not reporting methamphetamine use per 100 person-years (Table 4).

    Table 4. HIV incidence among American Transformative HIV Study participants in the 12- and 6-month periods before study enrollment.
    Participants who used methamphetamine in the last 3 months (n=2820)Participants who had not used methamphetamine in the last 3 months (n=2584)Incidence rate ratio
    12-month period before enrollment
    Presumed recent seroconversions, na17442—b
    Person-years at risk among people who seroconvertedc, n8721—
    Person-years at risk among persons with HIV-negative test results, n16422041—
    Incidence rate per 100 person-years (95% CI)d10.06 (8.65-11.64)2.04 (1.49-2.73)4.93 (3.55-6.99)
    6-month period before enrollment
    Presumed recent seroconversions, ne7619—
    Person-years at risk among people who seroconvertedc, n389.5—
    Person-years at risk among persons with HIV-negative test results, n8211020.5—
    Incidence rate per 100 person-years (95% CI)d8.85 (7.02-11.01)1.85 (1.14-2.83)4.78 (2.94-8.12)

    aTo accurately approximate the number of recent seroconversions for the 12-month incidence calculation, we first totaled the number of HIV-positive results for testing categories ≤6 months and 7‐12 months (Table 3). Then, we added 25% of the adjacent category of those who reported last testing >12 months ago.

    bNot applicable.

    cPerson-years calculated as (1) mid-year estimates for those presumed to have seroconverted in the last year (12-month incidence rate), (2) full-year estimates for people who did not seroconvert (12-month incidence rate), (3) quarter-year estimates for those presumed to have seroconverted in the last 6 months (6-month incidence rate), and (4) half year estimates for those who did not seroconvert (6-month incidence rate).

    dMid-P exact test 95% CIs calculated using OpenEpi software.

    eTo accurately approximate the number of recent seroconversions for the 6-month incidence calculation, we used the number of HIV-positive results for the ≤6 months category. Then, we added 25% of those who reported the last testing 7-12 months ago.

    Longitudinal Follow-Up and Measurement

    Prospective closed follow-up of AMETHST participants includes completion of web-based surveys beginning 12 months after the baseline survey, again at 24 months, and finally at 36 months, as well as annual self-administered at-home HIV test and rectal swabs. However, at follow-up, participants who self-report being on PrEP (ie, PrEP adoption outside of the study) are asked to provide proof in the form of a photo of the medication bottle with their prescription information or other medical documentation of their prescription. Likewise, those who report having been diagnosed with HIV between study assessments are asked to provide proof in the form of a picture of a document or medication bottle with their prescription information. Those known to be HIV-positive (either via testing HIV-positive during a prior wave of assessments or documented proof of HIV seroconversion between study assessments) will not be asked to test for HIV within the study again. Our reason for not asking those on PrEP to test with us is because our test is a third-generation HIV test, and those on PrEP should be receiving a fourth-generation HIV test (blood) from their medical provider, and we do not want participants to inadvertently use our test in lieu of their providers. Should participants report discontinuing PrEP at a follow-up assessment, they will be asked to test with us again.

    A comprehensive list of key study measurements by study wave is included in Multimedia Appendix 3. We will follow the cohort of 5364 individuals to characterize methamphetamine use or uptake or discontinuation and its role in the following: the rate of PrEP uptake or discontinuation, individual or network or contextual-level determinants of PrEP uptake or discontinuation, patterns of PrEP use (eg, daily or on-demand), the rate of new HIV seroconversions and other missed HIV prevention opportunities (ie, sexually transmitted infections while not on PrEP), individual or network or contextual-level determinants of HIV seroconversion and missed HIV prevention opportunities, racial or ethnic disparities in HIV incidence and their trends over time, and the influence of PrEP uptake on racial or ethnic disparities in HIV incidence.

    Given the nature of this web-based US nationwide cohort, we elected to longitudinally follow all participants who mailed an HIV test kit at baseline rather than only those who completed HIV testing. Participants who did not complete HIV testing will have the opportunity to provide those data or samples at future assessments, and this will enable us to learn more about differential rates of participation and attrition in the cohort moving forward.

    Biological Vulnerability to HIV—Nested Case-Cohort Study

    At the completion of all follow-up assessments, we will conduct a nested case-cohort study [68] to examine biological vulnerability to HIV. We anticipate that upward of 450 individuals will have seroconverted to HIV-positive, and we will match their samples against 450 HIV-negative participants (similar in age and race). The rectal swabs for these 900 participants will be retrieved from the biospecimen repository. For those who are HIV seroconvert, swabs preceding seroconversion will be selected. One swab (the Aptima Multitest Swab) will be tested for rectal gonorrhea and chlamydia. The second swab (the Zymo DNA/RNA Shield swab) will be examined using the LEGENDPlex assays to quantify rectal cytokine or chemokine levels. We will use the Human Inflammation Panel, which allows for the measurement of 13 cytokines or chemokines [70]. This will allow to determine changes in cytokine or chemokine profiles before and after HIV seroconversion—matched against those of HIV-negative participants—and to determine if methamphetamine use is associated with any immune changes in the rectal mucosa among those who acquire HIV as well as in the comparison group.


    Principal Findings

    The AMETHST cohort study enrolled an entirely web-based US national cohort of cisgender men, transgender men, and transgender men who have sex with men and are at very high risk for HIV, into longitudinal follow-up. Greater than half of the participants were persons of color, and 53.1% had recently used methamphetamine. Importantly, none of the AMETHST participants were on PrEP at enrollment, but all met the clinical criteria for PrEP use. This will allow our study to fill critical knowledge gaps that can improve our understanding of the role that methamphetamine plays in (barriers to) PrEP uptake or discontinuation among those most in need of HIV prevention interventions—and at a time in which PrEP has been Food and Drug Administration–approved for more than a decade.

    Although all participants were similar in their having met clinical criteria for PrEP, we observed several characteristics that distinguished people who used methamphetamine at baseline from those who did not in ways that put them at greater risk for HIV. People who used methamphetamine were more likely to report greater than 3 recent insertive CAS acts with men, to have been diagnosed recently with syphilis, to report sharing injection drug needles in the past year, trended toward being older, having never tested for HIV, and to not have health insurance, nor a primary care provider, or have heard of PrEP. These facets all compound to elevate HIV risk. This is perhaps evidenced best through the staggering number of HIV infections (baseline prevalence) identified among those who use methamphetamine (n=302, 15.5% vs n=69, 3.3% among those not using). This high number was despite lower HIV kit return among those who use methamphetamine. Our baseline data highlight the challenges people who use methamphetamine face as well as the challenges we as researchers may have in engaging and retaining this population longitudinally. Our estimates of HIV incidence in the 12-month period leading up to enrollment (2.04% per year among those who do not use methamphetamine and 10.06% per year among those who use methamphetamine) suggest that, without significant PrEP uptake as the cohort moves forward, the risk of HIV acquisition that we will observe prospectively will also be quite high. As noted, per enrollment criteria, no participants were taking PrEP at the time of enrollment; however, we provide participants information and resources on how to access PrEP and will be monitoring that outcome going forward.

    Strengths

    Major strengths of the AMETHST cohort include its large sample size, geographic diversity, self-reported data related to substance use, HIV risk and PrEP, biomarkers for direct measurement of HIV status and seroconversion and inflammation, recruitment of participants independent of their access to or engagement with the health care system, and inclusion of large numbers of racial or ethnic minority SGM individuals as well as those younger than the age of 29 years. Having overrepresented persons who use methamphetamine uniquely positions this cohort to answer key causal questions about the role that methamphetamine plays in disrupting HIV prevention. As well, our future nested case-cohort study will enable our team to answer key questions regarding the biological role that methamphetamine plays in HIV seroconversion.

    Importantly, the AMETHST cohort study design, with its infrequent (ie, annual) surveys, reduces the potential for participation and questionnaire-response bias introduced by the Hawthorne effect. Studies involving frequent contact can cause participants to adopt behaviors that make them less representative of the vulnerable populations from which they were drawn. For example, McCambridge et al [71] discussed how research participant effects—an expansion on the Hawthorne effect [72]—can introduce bias, including demand characteristics [73]. Studies involving high levels of staff contact with participants may induce behavior change by repeatedly engaging participants outside of their natural context, artificially impacting results and reducing generalizability [74,75]. That being said, we recognize that any self-reporting of a behavior introduces some potential for a participant to reflect upon, and thus modify, their behavior.

    Limitations

    Recruiting participants and gathering data on the web are a less controlled research environment than face-to-face studies. Web-based recruitment increases vulnerability to repeat participation and fraudulent manipulation of HIV testing procedures. We took several measures to avoid this, including requiring all participants to have a unique email address, a unique and valid phone number (with text verification), and a valid mailing address (verified with the US postal service). We tracked IP addresses and blocked responses from outside the United States on our screening survey. Our advertising materials did not indicate full eligibility criteria (eg, age 16 to 49 years, cannot be HIV-positive, and meeting criteria for PrEP care but not being on PrEP), and the screening survey included additional items not related to study eligibility such as cannabis use, mpox infection or vaccination, health insurance status, and doxycycline postexposure prophylaxis. However, no method is entirely infallible. At future waves of follow-up, data will be compared to responses at baseline for consistency (eg, age and race).

    Next, participants were recruited via sexual networking apps and are thus not representative of all SGM individuals highly vulnerable to HIV. These apps have emerged as the modal means through which SGM individuals meet sex partners and have become an essential tool for researchers and providers to reach this population.

    Finally, HIV seroconversions and PrEP uptake may be incompletely ascertained, and the timing of HIV seroconversions must be estimated using a midpoint approach with broad intervals, potentially introducing bias in our baseline HIV incidence estimates. For example, our study eligibility or inclusion criterion of never diagnosed with HIV (self-report) effectively excludes frequent HIV testers who seroconverted and were diagnosed in the period immediately before the study launch.

    Conclusions

    The AMETHST cohort is a large racially and geographically diverse group of SGM individuals who report high vulnerability to HIV. Its focus to identify multilevel (ie, structural, psychological, and social) and biobehavioral (ie, rectal cytokines or chemokines) determinants of amplified HIV seroconversion risk for SGM individuals, including those who use methamphetamine, will serve to guide targeted, combination interventions to reduce HIV incidence and increase PrEP uptake. Its added nested case-cohort study [68] will determine changes in cytokine or chemokine profiles before and after HIV seroconversion as well as the role that methamphetamine plays in that process. Our team welcomes new collaborations both in secondary analysis of the data generated as well as proposals for new measures or data to be gathered from participants in future waves of follow-up. Instructions and a concept proposal form are available by emailing the principal investigators (CG and AWC). Submitted concept proposals will be reviewed by the principal investigators (CG and AWC) and a core group of AMETHST investigators with rapid turnaround.

    Acknowledgments

    American Transformative HIV Study was funded by the National Institutes of Health (NIH; UG3 AI169652—CG or AWC). Other forms of support include the City University of New York (CUNY) Institute for Implementation Science in Population Health, the Einstein, Rockefeller, and CUNY Center for AIDS Research (P30 AI124414). DW was supported in part by K01 AA029047. JM is supported in part by the Tulane National Primate Research Center NIH Core Grant (P51OD011104). The authors especially thank Matthew Stief as well as NIH program staff: Gerald Sharp, Lori Zimand, Richard Jenkins, Michael Stirratt, and Sonia Lee. Although NIH funded this research, they do not necessarily endorse these findings.

    Conflicts of Interest

    None declared.

    Multimedia Appendix 1

    Sample recruitment advertisements.

    DOCX File, 1887 KB
    Multimedia Appendix 2

    Baseline survey.

    DOCX File, 150 KB
    Multimedia Appendix 3

    Screening survey.

    DOCX File, 47 KB
    1. HIV in the United States: at a glance. Centers for Disease Control and Prevention. 2015. URL: http://www.cdc.gov/hiv/statistics/basics/ataglance.html [Accessed 2025-07-22]
    2. HIV among gay and bisexual men. Centers for Disease Control and Prevention. 2016. URL: http://www.cdc.gov/hiv/group/msm [Accessed 2016-08-22]
    3. Diagnoses of HIV infection among adolescents and young adults in the United States and 6 dependant areas 2010-2014. HIV surveillance supplemental report. Centers for Disease Control and Prevention; 2016.
    4. HIV and gay and bisexual men. Centers for Disease Control and Prevention. 2018. URL: https://www.cdc.gov/hiv/group/msm/index.html [Accessed 2018-10-17]
    5. Half of Black gay men and a quarter of Latino gay men projected to be diagnosed within their lifetime. Centers for Disease Control and Prevention. 2016. URL: http://www.cdc.gov/nchhstp/newsroom/2016/croi-press-release-risk.html [Accessed 2016-04-26]
    6. What percentage of the US population is transgender? USA Facts. 2023. URL: https://usafacts.org/articles/what-percentage-of-the-us-population-is-transgender [Accessed 2025-04-29]
    7. How many adults and youth identify as transgender in the United States? The Williams Institute. 2022. URL: https://williamsinstitute.law.ucla.edu/publications/trans-adults-united-states [Accessed 2025-04-29]
    8. HIV surveillance report 2019. Centers for Disease Control and Prevention. 2021. URL: http://www.cdc.gov/hiv/library/reports/hiv-surveillance.html [Accessed 2022-08-04]
    9. HIV infection, risk, prevention, and testing behaviors among transgender women. Centers for Disease Control and Prevention; 2021.
    10. Bush S, Magnuson D, Rawlings MK, Hawkins T, McCallister S, Mera Giler R. Racial characteristics of FTC/TDF for pre-exposure prophylaxis (PrEP) users in the US #2651. Presented at: American Society for Microbiology: ICAAC; Jun 16-20, 2016; Boston, MA, United States.
    11. Carrico AW, Zepf R, Meanley S, Batchelder A, Stall R. Critical review: when the party is over: a systematic review of behavioral interventions for substance-using men who have sex with men. J Acquir Immune Defic Syndr. Nov 1, 2016;73(3):299-306. [CrossRef] [Medline]
    12. Thiede H, Valleroy LA, MacKellar DA, et al. Regional patterns and correlates of substance use among young men who have sex with men in 7 US urban areas. Am J Public Health. Nov 2003;93(11):1915-1921. [CrossRef] [Medline]
    13. Das M, Santos D, Matheson T, et al. Feasibility and acceptability of a phase II randomized pharmacologic intervention for methamphetamine dependence in high-risk men who have sex with men. AIDS. Apr 24, 2010;24(7):991-1000. [CrossRef] [Medline]
    14. Colfax G, Shoptaw S. The methamphetamine epidemic: implications for HIV prevention and treatment. Curr HIV/AIDS Rep. Nov 2005;2(4):194-199. [CrossRef] [Medline]
    15. Compton WM, Jones CM. Substance use among men who have sex with men. N Engl J Med. Jul 22, 2021;385(4):352-356. [CrossRef] [Medline]
    16. Pantalone DW, Bimbi DS, Holder CA, Golub SA, Parsons JT. Consistency and change in club drug use by sexual minority men in New York City, 2002 to 2007. Am J Public Health. Oct 2010;100(10):1892-1895. [CrossRef] [Medline]
    17. Grov C, Parsons JT, Bimbi DS, Sex and Love v3.0 Research Team. In the shadows of a prevention campaign: sexual risk behavior in the absence of crystal methamphetamine. AIDS Educ Prev. Feb 2008;20(1):42-55. [CrossRef] [Medline]
    18. Reback CJ, Shoptaw S, Grella CE. Methamphetamine use trends among street-recruited gay and bisexual males, from 1999 to 2007. J Urban Health. Nov 2008;85(6):874-879. [CrossRef] [Medline]
    19. Reback CJ, Fletcher JB, Shoptaw S, Grella CE. Methamphetamine and other substance use trends among street-recruited men who have sex with men, from 2008 to 2011. Drug Alcohol Depend. Nov 1, 2013;133(1):262-265. [CrossRef] [Medline]
    20. Kuo I, Patrick R, Opoku J, Rawls A, Magnus M, Peterson J, editors. Changing pattern of crystal meth use in Black & White MSM, Washington, DC, 2008–2014. Presented at: Conference on Retroviruses and Opportunistic Infections; Feb 13-16, 2017; Seattle, WA, United States.
    21. Hood JE, Buskin SE, Golden MR, Glick SN, Banta-Green C, Dombrowski JC. The changing burden of HIV attributable to methamphetamine among men who have sex with men in King County, Washington. AIDS Patient Care STDS. Jun 2018;32(6):223-233. [CrossRef] [Medline]
    22. HIV infection risk, prevention, and testing behaviors among men who have sex with men—national HIV behavioral surveillance, 20 U.S. cities 2014. Centers for Disease Control and Prevention; 2016.
    23. Hoenigl M, Chaillon A, Moore DJ, Morris SR, Smith DM, Little SJ. Clear links between starting methamphetamine and increasing sexual risk behavior: a cohort study among men who have sex with men. J Acquir Immune Defic Syndr. Apr 15, 2016;71(5):551-557. [CrossRef] [Medline]
    24. Rivera AV, Harriman G, Carrillo SA, Braunstein SL. Trends in methamphetamine use among men who have sex with men in New York City, 2004-2017. AIDS Behav. Apr 2021;25(4):1210-1218. [CrossRef] [Medline]
    25. Grov C, Westmoreland D, Morrison C, Carrico AW, Nash D. The crisis we are not talking about: one-in-three annual HIV seroconversions among sexual and gender minorities were persistent methamphetamine users. J Acquir Immune Defic Syndr. Nov 1, 2020;85(3):272-279. [CrossRef] [Medline]
    26. Halkitis PN, Parsons JT, Stirratt MJ. A double epidemic: crystal methamphetamine drug use in relation to HIV transmission among gay men. J Homosex. 2001;41(2):17-35. [CrossRef] [Medline]
    27. Isaiah Green A, Halkitis PN. Crystal methamphetamine and sexual sociality in an urban gay subculture: an elective affinity. Cult Health Sex. Jul 1, 2006;8(4):317-333. [CrossRef]
    28. Baskin-Sommers A, Sommers I. The co-occurrence of substance use and high-risk behaviors. J Adolesc Health. May 2006;38(5):609-611. [CrossRef] [Medline]
    29. Semple SJ, Zians J, Strathdee SA, Patterson TL. Sexual marathons and methamphetamine use among HIV-positive men who have sex with men. Arch Sex Behav. Aug 2009;38(4):583-590. [CrossRef] [Medline]
    30. Semple SJ, Patterson TL, Grant I. Binge use of methamphetamine among HIV-positive men who have sex with men: pilot data and HIV prevention implications. AIDS Educ Prev. Apr 2003;15(2):133-147. [CrossRef] [Medline]
    31. Halkitis PN, Fischgrund BN, Parsons JT. Explanations for methamphetamine use among gay and bisexual men in New York City. Subst Use Misuse. 2005;40(9-10):1331-1345. [CrossRef] [Medline]
    32. Braine N, Acker CJ, van Sluytman L, Friedman S, Des Jarlais DC. Drug use, community action, and public health: gay men and crystal meth in NYC. Subst Use Misuse. 2011;46(4):368-380. [CrossRef] [Medline]
    33. Treloar C, Hopwood M, Drysdale K, et al. Stigma as understood by key informants: a social ecological approach to gay and bisexual men’s use of crystal methamphetamine for sex. Int J Drug Policy. Aug 2021;94:103229. [CrossRef] [Medline]
    34. Aguilar JP, Sen S. The culture of methamphetamine: reframing gay men’s methamphetamine use. J Hum Behav Soc Environ. Apr 2013;23(3):370-382. [CrossRef]
    35. Bostwick WB, Boyd CJ, Hughes TL, West BT, McCabe SE. Discrimination and mental health among lesbian, gay, and bisexual adults in the United States. Am J Orthopsychiatry. 2014;84(1):35-45. [CrossRef] [Medline]
    36. Balaji AB, Bowles KE, Hess KL, Smith JC, Paz-Bailey G, Taussig J. Association between enacted stigma and HIV-related risk behavior among MSM, National HIV Behavioral Surveillance System, 2011. AIDS Behav. Jan 2017;21(1):227-237. [CrossRef] [Medline]
    37. Lee JH, Gamarel KE, Bryant KJ, Zaller ND, Operario D. Discrimination, mental health, and substance use disorders among sexual minority populations. LGBT Health. Aug 2016;3(4):258-265. [CrossRef] [Medline]
    38. Mays VM, Cochran SD. Mental health correlates of perceived discrimination among lesbian, gay, and bisexual adults in the United States. Am J Public Health. Nov 2001;91(11):1869-1876. [CrossRef] [Medline]
    39. Meyer IH. Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence. Psychol Bull. Sep 2003;129(5):674-697. [CrossRef] [Medline]
    40. Meyer IH, Schwartz S, Frost DM. Social patterning of stress and coping: does disadvantaged social statuses confer more stress and fewer coping resources? Soc Sci Med. Aug 2008;67(3):368-379. [CrossRef] [Medline]
    41. Meyer IH. Minority stress and mental health in gay men. J Health Soc Behav. Mar 1995;36(1):38-56. [Medline]
    42. HIV and gay and bisexual men. Centers for Disease Control and Prevention. 2021. URL: https://www.cdc.gov/hiv/group/msm/index.html [Accessed 2021-07-14]
    43. Parsons JT, Millar BM, Moody RL, Starks TJ, Rendina HJ, Grov C. Syndemic conditions and HIV transmission risk behavior among HIV-negative gay and bisexual men in a U.S. national sample. Health Psychol. Jul 2017;36(7):695-703. [CrossRef] [Medline]
    44. Stall R, Mills TC, Williamson J, et al. Association of co-occurring psychosocial health problems and increased vulnerability to HIV/AIDS among urban men who have sex with men. Am J Public Health. Jun 2003;93(6):939-942. [CrossRef] [Medline]
    45. O’Leary A, Jemmott JB 3rd, Stevens R, Rutledge SE, Icard LD. Optimism and education buffer the effects of syndemic conditions on HIV status among African American men who have sex with men. AIDS Behav. Nov 2014;18(11):2080-2088. [CrossRef] [Medline]
    46. Brennan J, Kuhns LM, Johnson AK, et al. Syndemic theory and HIV-related risk among young transgender women: the role of multiple, co-occurring health problems and social marginalization. Am J Public Health. Sep 2012;102(9):1751-1757. [CrossRef] [Medline]
    47. van den Berg JJ, Isabel Fernández M, Fava JL, et al. Using syndemics theory to investigate risk and protective factors associated with condomless sex among youth living with HIV in 17 U.S. cities. AIDS Behav. Mar 2017;21(3):833-844. [CrossRef] [Medline]
    48. Wim VB, Christiana N, Marie L. Syndemic and other risk factors for unprotected anal intercourse among an online sample of Belgian HIV negative men who have sex with men. AIDS Behav. Jan 2014;18(1):50-58. [CrossRef] [Medline]
    49. Singer M. AIDS and the health crisis of the U.S. urban poor; the perspective of critical medical anthropology. Soc Sci Med. Oct 1994;39(7):931-948. [CrossRef] [Medline]
    50. Halkitis PN, Moeller RW, Siconolfi DE, Storholm ED, Solomon TM, Bub KL. Measurement model exploring a syndemic in emerging adult gay and bisexual men. AIDS Behav. Feb 2013;17(2):662-673. [CrossRef] [Medline]
    51. Wilson PA, Nanin J, Amesty S, Wallace S, Cherenack EM, Fullilove R. Using syndemic theory to understand vulnerability to HIV infection among Black and Latino men in New York City. J Urban Health. Oct 2014;91(5):983-998. [CrossRef] [Medline]
    52. Kelley CF, Kraft CS, de Man TJ, et al. The rectal mucosa and condomless receptive anal intercourse in HIV-negative MSM: implications for HIV transmission and prevention. Mucosal Immunol. Jul 2017;10(4):996-1007. [CrossRef] [Medline]
    53. Hladik F, McElrath MJ. Setting the stage: host invasion by HIV. Nat Rev Immunol. Jun 2008;8(6):447-457. [CrossRef] [Medline]
    54. Sullivan PS, Salazar L, Buchbinder S, Sanchez TH. Estimating the proportion of HIV transmissions from main sex partners among men who have sex with men in five US cities. AIDS. Jun 1, 2009;23(9):1153-1162. [CrossRef] [Medline]
    55. Gonzalez SM, Aguilar-Jimenez W, Su RC, Rugeles MT. Mucosa: key interactions determining sexual transmission of the HIV infection. Front Immunol. 2019;10(144):144. [CrossRef] [Medline]
    56. Henry BL, Minassian A, Perry W. Effect of methamphetamine dependence on heart rate variability. Addict Biol. May 2012;17(3):648-658. [CrossRef] [Medline]
    57. Cook RR, Fulcher JA, Tobin NH, et al. Alterations to the gastrointestinal microbiome associated with methamphetamine use among young men who have sex with men. Sci Rep. Oct 16, 2019;9(1):14840. [CrossRef] [Medline]
    58. Persons AL, Bradaric BD, Dodiya HB, et al. Colon dysregulation in methamphetamine self-administering HIV-1 transgenic rats. PLoS ONE. 2018;13(1):e0190078. [CrossRef] [Medline]
    59. Nash D, Stief M, MacCrate C, et al. A web-based study of HIV prevention in the era of pre-exposure prophylaxis among vulnerable HIV-negative gay and bisexual men, transmen, and transwomen who have sex with men: protocol for an observational cohort study. JMIR Res Protoc. Sep 17, 2019;8(9):e13715. [CrossRef] [Medline]
    60. Grov C, Westmoreland DA, Carneiro PB, et al. Recruiting vulnerable populations to participate in HIV prevention research: findings from the Together 5000 cohort study. Ann Epidemiol. Jul 2019;35:4-11. [CrossRef] [Medline]
    61. Grov C, Bimbi DS, Nanin JE, Parsons JT. Race, ethnicity, gender, and generational factors associated with the coming-out process among lesbian, and bisexual individuals. J Sex Res. May 2006;43(2):115-121. [CrossRef] [Medline]
    62. Mustanski B. Ethical and regulatory issues with conducting sexuality research with LGBT adolescents: a call to action for a scientifically informed approach. Arch Sex Behav. Aug 2011;40(4):673-686. [CrossRef] [Medline]
    63. Lang N. There’s a meth problem on Grindr and Scruff—and no one is doing much about it. MIC. 2016. URL: https:/​/www.​mic.com/​articles/​138644/​there-s-a-meth-problem-on-grindr-and-no-one-is-doing-much-about-it [Accessed 2019-10-01]
    64. Ziegler C. HosTing Now: methamphetamine crisis in the gay community. KTSW 899. URL: https://ktswblog.net/2019/04/25/hosting-now-methamphetamine-crisis-in-the-gay-community [Accessed 2025-04-29]
    65. Grov C, Zohra F, Mirzayi C, et al. Sexual and gender minorities’ vaccine uptake and behavioral change in response to the mpox outbreak in the United States: August 2022 through November 2022. Clin Infect Dis. :ciad793. [CrossRef]
    66. Elma M, Krusel K, Crumpler M, et al. Use of the Bio-Rad Geenius HIV-1/2 supplemental assay for the testing of oral fluids for the presence of HIV antibody. J Clin Virol. Jul 2020;128:104422. [CrossRef] [Medline]
    67. D’Angelo AB, Morrison CA, Lopez-Rios J, et al. Experiences receiving HIV-positive results by phone: acceptability and implications for clinical and behavioral research. AIDS Behav. Mar 2021;25(3):709-720. [CrossRef] [Medline]
    68. Katz DA, Dombrowski JC, Bell TR, Kerani RP, Golden MR. HIV incidence among men who have sex with men after diagnosis with sexually transmitted infections. Sex Transm Dis. Apr 2016;43(4):249-254. [CrossRef] [Medline]
    69. Grov C, Guo Y, Westmoreland DA, et al. Factors associated with PrEP-era HIV seroconversion in a 4-year U.S. national cohort of n = 6059 sexual and gender minority individuals who have sex with men, 2017-2022. J Int AIDS Soc. Jun 2024;27(6):e26312. [CrossRef] [Medline]
    70. McManus K, McGaugh A, Miller C, Manuzak J, Broedlow C. Bio-behavioral correlates of rectal inflammation in HIV-negative sexual minority men. Presented at: Second Annual Mucosal Systems Meeting; May 21-22, 2019; Chicago, IL, United States.
    71. McCambridge J, Kypri K, Elbourne D. Research participation effects: a skeleton in the methodological cupboard. J Clin Epidemiol. Aug 2014;67(8):845-849. [CrossRef] [Medline]
    72. Adair JG. The Hawthorne effect: a reconsideration of the methodological artifact. J Appl Psychol. 1984;69(2):334-345. [CrossRef]
    73. McCambridge J, de Bruin M, Witton J. The effects of demand characteristics on research participant behaviours in non-laboratory settings: a systematic review. PLoS ONE. 2012;7(6):e39116. [CrossRef] [Medline]
    74. Mbulaiteye SM, Mahe C, Ruberantwari A, Whitworth JAG. Generalizability of population-based studies on AIDS: a comparison of newly and continuously surveyed villages in rural southwest Uganda. Int J Epidemiol. Oct 2002;31(5):961-967. [CrossRef] [Medline]
    75. Bouchet C, Guillemin F, Briançon S. Nonspecific effects in longitudinal studies: impact on quality of life measures. J Clin Epidemiol. Jan 1996;49(1):15-20. [CrossRef] [Medline]

    ‎
    AMETHST: American Transformative HIV Study
    CAS: condomless anal sex
    CASI: computer-assisted self-interview
    PrEP: pre-exposure prophylaxis
    SGM: sexual and gender minority

    Edited by Duygu Islek Yaras; submitted 26.09.24; peer-reviewed by Jeb Jones, Rebecca Schnall; final revised version received 19.03.25; accepted 02.04.25; published 22.05.25.

    Copyright

    © Christian Grov, Alexa B D'Angelo, Chloe Mirzayi, Michelle Dearolf, Elena Hoeppner, Yan Guo, Nicole Richards, Rifa Ehsan, Sarah Kulkarni, Denis Nash, Viraj V Patel, Dustin T Duncan, Meredith Ray, Tyler Bartholomew, Jennifer Manuzak, Jennifer Manuel, Kathryn McCollister, Drew Westmoreland, Adam W Carrico. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 22.5.2025.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.