Assessing HIV Risk, Syndemics, Resilience and Engagement in Care in a Large National Cohort of Gay, Bisexual and Other Men Who Have Sex with Men in the United States

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6-1-2021

Assessing HIV Risk, Syndemics, Resilience and Engagement in Care in a Large National Cohort of Gay, Bisexual and Other Men Who Have Sex With Men in the United States

Javier Lopez-Rios CUNY School of Public Health, [email protected]

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This work is made publicly available by the City University of New York (CUNY). Contact: [email protected] ASSESSING HIV RISK, SYNDEMICS, RESILIENCE AND ENGAGEMENT IN CARE IN A LARGE NATIONAL COHORT OF GAY, BISEXUAL AND OTHER MEN WHO HAVE SEX WITH MEN IN THE UNITED STATES

A DISSERTATION

JAVIER LOPEZ-RIOS, MPH

Concentration: COMMUNITY HEALTH AND HEALTH POLICY

Presented to the Faculty at the Graduate School of Public Health and Health Policy in partial

fulfillment of the requirements for the degree of Doctor of Philosophy

Graduate School of Public Health and Health Policy City University of New York New York, New York April 2021

Dissertation Committee: Christian Grov, PhD, MPH (Chair) Nicholas A. Grosskopf, EdD, MCHES Ivan C. Balan, PhD ii

Copyrighted By

JAVIER LOPEZ-RIOS, MPH

2021

iii

ABSTRACT

Assessing HIV Risk, Syndemics, Resilience and Engagement in Care in a Large National Cohort

of Gay, Bisexual and Other Men Who Have Sex with Men in The United States

Javier Lopez-Rios, MPH

Advisor: Christian Grov, PhD

Committee Members: Nicholas Grosskopf, EdD, MCHES

Ivan C. Balan, PhD

Background: HIV continues to be a pervasive public health issue in the United States with more

than 1.2 million people living with HIV (PLWHIV) across the nation. Gay, bisexual and other

men who have sex with men (GBM) account for over two-thirds of all new HIV diagnoses with

racial and ethnic minorities shouldering a large proportion of the burden of disease. Although

HIV transmission is predominantly driven by sexual behaviors, there are underlying complex

individual, behavioral, and structural factors that contribute to high rates of sexual behavior and

subsequent HIV acquisition. Moreover, difficulties remain in maximizing linkage to care and

viral suppression for PLWHIV. Despite the wealth of research showing the importance of viral

suppression as a tool for controlling the HIV epidemic, over one-quarter of HIV-positive GBM

are not fully engaged in HIV primary medical care; Sexual minority populations of color

experience starkly worse rates of engagement in HIV care. This multi-method dissertation aimed iv to understand how multi-level factors compound HIV risk in a U.S. national sample of GBM and to describe engagement in HIV care among those newly diagnosed with HIV. The following specific aims were addressed:

Aim 1: Measure exposure to syndemic conditions, describe the conditions most likely to co- occur and examine their association to HIV risk.

Aim 2: Describe the levels of resilience and identify associations with HIV risk and conduct comparisons by race/ethnicity, region, age and other socio-demographic characteristics.

Aim 3: Describe the barriers and facilitators to engagement in prompt HIV care 3-months after the delivery of an HIV-positive result.

Methods: Data for this study was collected as part of the Together 5,000 study, a U.S. national, internet-based cohort study of men, transgender men, and transgender women who have sex with men. For Aims 1 and 2, we conducted secondary analysis of quantitative survey data from a cohort of 6,118 GBM ages 16-49 at high risk for HIV transmission. The surveys gathered data on demographics, HIV risk behaviors, HIV and STI testing history, mental health, and interpersonal factors. For Aim 1, we evaluated the prevalence of syndemic conditions and explored their associations with HIV risk. Descriptive statistics were used to describe the sample and the prevalence of syndemic conditions. The associations were determined using adjusted multiple linear regressions. For Aim 2, we measured and described the sociodemographic differences in levels of resilience and explored the association between resilience and HIV risk. The associations were determined using adjusted multiple linear regressions. For aim 3, we conducted secondary analysis of qualitative in-depth interviews from 50 GBM diagnosed HIV- positive during their participation in Together 5,000. The goal of Aim 3 was to described v participants experiences getting linked-to-care and identify barriers and facilitators to engagement in HIV care using thematic analysis.

Results: In Aim 1 we found a high prevalence of intimate partner violence (IPV), experiences of childhood sexual abuse, homelessness and mental health issues. Further, IPV, depression, polydrug use, incarceration history and homelessness were positively associated with HIV risk.

We also demonstrated that increasing cumulative syndemic conditions were associated with higher HIV risk. Those who reported 3 or more co-occurring conditions had the highest risk for

HIV. In Aim 2, we found higher mean resilience scores among those identifying as black, with higher education, having full-time employment, higher incomes, and those who have health insurance. Although we found no statistically significant association between resilience and our composite measure of HIV risk, we did find a significant association between higher resilience and lower condomless receptive anal sex acts in the last 3 months. In Aim 3, we found that the majority of participants reported being linked-to-care, while only 74.5% of those reported initiating ART. Thematic analysis identified 4 major themes related to participants’ engagement in care: 1) Reasons for HIV testing (e.g., HIV self-testing and expectation of positivity), 2)

Linkage-to-care (e.g., appointment/logistic issues and social support as encouragement), 3)

Barriers (e.g., financial burden, competing priorities and fear/stigma) and facilitators (e.g., financial assistance, patient-provider relationships, auxiliary support services and health agency) to engagement in HIV care, and 4) PrEP as a missed prevention opportunity.

Conclusion: Overall, the findings from this multi-method dissertation suggest that the HIV epidemic is complex, and therefore an effective response requires an understanding of the diversity and dynamic nature of individuals, communities, and our socio-political environment.

We demonstrated that environmental and behavioral factors such as homelessness, incarceration vi are prevalent among GBM in the U.S. and contribute to HIV acquisition, thus offering compelling evidence for the adoption of these variables in future syndemic models. Further, there needs to be a more comprehensive investigation of the unique risk factors in this population, particularly those that may impact uptake and adoption of preventive HIV health behaviors, such as pre-exposure prophylaxis (PrEP). For instance, larger structural factors like societal racial discrimination, anti-immigration laws, lack of health insurance coverage and unemployment can significantly impact adherence to biomedical tools and use of testing services. Future research should explore these social and structural determinants within the context of HIV prevention. There is a need for targeted interventions for those at the highest risk, particularly racial and ethnic minorities and those from impoverished communities to increase

HIV testing frequency and facilitate better engagement in care. Further, as seen in our study findings, HIV prevention is a multi-faceted process. As such, there is a need for a more holistic approach to prevention, wherein HIV prevention is conceptualized as more than just HIV testing and PrEP initiation but that takes into account intrapersonal (e.g,, resilience) and interpersonal factors (e.g., social support). Finally, addressing policy-, social- and individual-level barriers could improve GBM’s engagement in HIV care. Capitalizing on GBM’s health agency through partnerships with local agencies and fostering better patient-provider relationships could optimize continuity of HIV care. We possess the tools needed to end the HIV epidemic in the

U.S., particularly by advocating for a new federal policy which streamlines HIV testing, linkage- to-care and ART initiation.

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TABLE OF CONTENTS

TABLE OF CONTENTS ...... VII

LIST OF TABLES ...... X

LIST OF FIGURES ...... XI

AWKNOWLEDGEMENTS ...... XII

DEDICATION ...... XIII

CHAPTER 1 – INTRODUCTION ...... 1

Background ...... 1

Rationale for the Dissertation ...... 9

Specific Aims ...... 10

Theoretical Frameworks ...... 11

Organization of the Dissertation ...... 12

Data Sources ...... 13

Application of Findings ...... 15

References ...... ERROR! BOOKMARK NOT DEFINED.

CHAPTER 2: THE ASSOCIATION BETWEEN SYNDEMIC CONDITIONS AND HIV

RISK IN AN U.S. NATIONAL COHORT OF GAY, BISEXUAL AND OTHER MEN

WHO HAVE SEX WITH MEN (GBM) ...... 27

Abstract ...... ERROR! BOOKMARK NOT DEFINED.

Introduction ...... 28 viii

Methods ...... 30

Results ...... 34

Discussion ...... 36

References ...... 40

CHAPTER 3: EXPLORATION OF THE ASSOCIATION BETWEEN RESILIENCE

AND HIV RISK BEHAVIORS AMONG GAY, BISEXUAL AND OTHER MEN WHO

HAVE SEX WITH MEN (GBM) ACROSS THE UNITED STATES...... 51

Abstract ...... 51

Introduction ...... 52

Methods ...... 54

Results ...... 57

Discussion ...... 58

References ...... 63

CHAPTER 4 – ENGAGEMENT IN CARE AMONG NEWLY DIAGNOSED HIV-

POSITIVE GAY, BISEXUAL AND OTHER MEN WHO HAVE SEX WITH MEN IN

THE UNITED STATES: RESULTS FROM THE TOGETHER 5,000 STUDY ...... 71

Abstract ...... 71

Introduction ...... 72

Methods ...... 74

Results ...... 77 ix

Discussion ...... 89

References ...... 94

CHAPTER 5: CONCLUSION ...... 101

Overview ...... 101

Summary of Findings ...... 102

Policy Implications ...... 105

Future Directions ...... 107

Limitations ...... 108

Conclusions ...... 109

References ...... 111

APPENDICES ...... 115

Appendix A: Enrollment Survey ...... 116

Appendix B: Secondary Survey ...... 126

Appendix C: Interview Guide ...... 153

LIST OF TABLES

Table 2.1: Demographic characteristics of the Together 5,000 study, and number of participants above the Median number of Syndemic Conditions, n = 6,118 ...... 46

Table 2.2. Syndemic Prevalence in the Together 5,000 Cohort ...... 48

Table 2.3. Bivariate Associations among Syndemic Conditions and HIV Risk ...... 49

Table 2.4 Linear Regressions of HIV Risk by Individual and Cumulative Syndemics ...... 50

Table 3.1. Socio-Demographic and Health Behavior Characteristics of the Together 5,000 cohort by Mean Resilience, n = 6,118 ...... 66

Table 3.2. Correlation Matrix between Psychosocial variables, Resilience and HIV Risk ...... 68

Table 3.3. Multiple Linear Regression of HIV Risk and Resilience (CD-Risc) ...... 69

Table 4.1. Socio-Demographic characteristics, HIV-positive GBM, n = 50 ...... 99

LIST OF FIGURES

Figure 1.1 - CDC Estimated HIV Prevalence and Incidence,1980-2012 ...... 23

Figure 1.2 - HIV Diagnoses among GBM, 2006-2017 ...... 24

Figure 1.3 - HIV Incidence in NYC, GBM, 2012-2016 ...... 25

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AWKNOWLEDGEMENTS

My sincerest gratitude to Dr. Christian Grov, my dissertation chair, supervisor and mentor who without his help this dissertation would not be possible. Thank you for the invaluable guidance throughout my doctoral training and for always giving me the chance to shine. Thank you to the rest of my committee members, Drs. Nicholas Grosskopf and Ivan Balan for their input, feedback, and advice on this body of work and my career. Your contributions and kindness will never be forgotten. Special thanks to additional members of the Together 5,000 study team for their scientific contributions: Sarit Golub, Gregorio Millett, Don Hoover, Sarah

Kulkarni, Matthew Stief, Drew Westmoreland, Alexa D’Angelo, Gloria Perez, Corey Morrison and Pedro Carneiro. To my HIV Center colleagues, Dr. Robert Remien and Rebecca Giguere: thank you for being my cheerleaders and always believing in me. I would be remiss if I did not my fellow CUNY SPH colleagues and students for their support throughout this adventure.

Thank you all for lifting me up when I needed it and for the healthy dose of competition.

I am forever grateful to my siblings, Mairyn Lopez-Rios, Orlando Lopez-Rios and

Nashali Lopez-Santiago, and my parents, Orlando Lopez-Huertas and Myriam Rios-Blas, for their love and support throughout the years. Special thank you to Dr. Ciara A. Torres and

Jonathan Lopez-Matos who believed in me from day one and encouraged me to apply to a PhD. I would also like to thank my partner, Cody Lentz, whose love, unwavering support and limitless encouragement enabled me to stay on track. Last but not least, for those who believed in me and those who did not, thank you.

Disclosure Statement: Work on this dissertation was not funded. The Together 5,000 study was funded by the National Institutes for Health (UG3AI133675 – PI: Grov). xiii

DEDICATION

I dedicate this dissertation to my grandparents, Mamá Generosa ‘Gene’ Blás and my Papá

Alfredo “Fello” Rios, my late grandparents, Blanca Iris Huertas and Loreto Lopez, and my parents, Myriam Rios-Blas and Orlando Lopez-Huertas. You taught me to persevere, to work hard, to be grateful and, most importantly, to be humble. I would not be the person I am today without you—I love and miss you dearly.

CHAPTER 1 – INTRODUCTION

Background

HIV continues to be a pervasive public health issue in the United States.1,2 To date, there are more than 1.2 million people living with HIV (PLWHIV) a)cross the nation (Figure 1.1).3-5

Since the beginning of the epidemic, more than 700,000 people have died from HIV-related complications.3-6 As of 2015, the U.S. accounted for about 3.5% of the global burden of

HIV.1,3,7,8 According to the UNAIDS definition, the HIV epidemic in the U.S. is classified as a concentrated epidemic given that the majority of infections occur in high-risk subpopulations.7,8

As such, incidence rates have been adopted as the primary measure for the nation’s HIV response because they reflect the concentration of HIV diagnoses, accounting for population size across geographic boundaries, and are adequate for determining pockets of infectiousness.2,3,6,9,10

Nationally, there are around 40,000 incident cases per year; gay, bisexual and other men who have sex with men (GBM) account for over two-thirds of all HIV diagnoses.1,3,11,12

Technological advances in the efficacy of antiretroviral treatment (ART) have transformed the management of HIV from an emergency response to a devastating epidemic to efforts at chronic disease management.13-16 Given this, more people continue to live longer, healthier lives, and, therefore, the overall prevalence of HIV continues on an upward trajectory.1,3,4

HIV and Gay, Bisexual and other Men who have sex with Men in the U.S. The first cases of HIV/AIDS were identified among young gay men in the 1980s.17

Although new infections peaked at about 130,000 cases per year in the late 80’s, the Centers for

Disease Control and Prevention (CDC) recently estimated stabilizing incidence rates of about

40,000 new annual HIV infections.11,12,18 In 1983, almost three-quarters (71%) of HIV transmissions were attributed to male-to-male sexual behavior. 6,10,19,20 The proportion of incident HIV among GBM declined to 44% in 1996, but later rebounded to a staggering 72% of 2 total transmissions in 2006.6,10,19,20 From 2012 to 2016, the number of new HIV infections remained relatively stable across the U.S. Nonetheless, the rate of HIV diagnoses varied geographically and across subpopulations, thus pointing to several risk pools.2,3,6,10 According to

CDC surveillance data, the rate of HIV diagnoses was highest in the South (16.1 per 100,000 people), followed by U.S. territories (12.3), including Guam and Puerto Rico, the Northeast

(10.6), the West (9.4) and the Midwest (7.4).1,3,4,12,18 Young adults were found to be at concerning risk for HIV; individuals under the age of 35 accounted for 56% of all new HIV diagnoses in 2017 and those aged between 25 and 34 years accounted for 35%.3,4,12,18 Although new HIV diagnoses have been declining over the last decade, the number of incident cases of

HIV among GBM has remained relatively stable (Figure 1.2).1,3,4,12,13,18,20 Notably, the proportion of HIV cases among GBM has been increasing slightly since 2011.1,3,4,12,13,18,20

Strikingly, the number of new infections among young GBM aged 13-24, increased 22% in 2010,1,3,18 and similar trends have been reported among young GBM living in urban centers, such as New York City (Figure 1.3).8,11,21 Although recent data points towards stabilizing HIV rates among black GBM, 1,3,18 they still remain the only at-risk group in the U.S. for which new

HIV infections rates have resurged and shown few signs of reduction over the past decade.

Furthermore, black and Latino GBM have a 1 in 2 and 1 in 4 chance, respectively, of becoming infected with HIV in their lifetime, thus warranting continued and concerted efforts for prevention and intervention in these populations.1,3,18

Racial and ethnic minorities were found to be disproportionately affected by the epidemic and represented a large proportion of new cases.3,4,6,10,12,18,22,23 Particularly, the HIV epidemic has been heavily concentrated among black and Latino GBM.24 Incident rates for African-American individuals were as high as 41.1 per 100,000 persons in 2016; comparable rates were 16.1 for 3

Hispanic/Latinos and 5.1 for Whites.1,3,4,13,25 Although initially an epidemic affecting predominantly white GBM, the racial, ethnic, and economic composition of PLWHIV has shifted dramatically over the last 30 years to one largely affecting economically disadvantaged sexual minorities of color.20,26-29

HIV Risk Factors for GBM Although HIV transmission is predominantly a factor of sexual behavior, there are underlying complex social, economic, and environmental factors that contribute to high rates of sexual behavior and HIV acquisition,22,30,31 particularly, stigma, discrimination, and poverty.22,30,31 Most of the literature has focused on condomless anal sex (CAS) as a risk factor for HIV. Moreover, attention has been paid to correlates of CAS, such as drug use (e.g., methamphetamines, cocaine, etc.), alcohol abuse, and poor mental health as important mediators of HIV transmission.32,33 Transmission risk behaviors among dyads or couples is of particular importance. Relationship characteristics, such as increased intimacy, inadequate communication skills and unstable power dynamics, have been found to lead higher rates of condom discontinuation (or lack of use) during couple’s sexual relationships.34-36

Sexual networks have been found to be an underlying driver of the epidemic. Larger sexual networks give GBM more opportunities for exposure. Studies have found a positive association between larger sexual networks and total number of sexual partners, CAS, substance use, and STI prevalence.37-40 Notably, homophily in sexual networks is presumed to be an important underlying and understudied factor impacting HIV rates among black GBM, particularly given this group’s already elevated risk.39 Further, rates of homelessness are especially high for young GBM and other gender non-conforming youth;41,42 in fact, such youth are at a heightened risk for engaging in survival sex work and, as such, are more likely to exhibit

HIV risk behaviors with clients.42 4

Stigma, racism, and marginalization have been identified as drivers of the epidemic.

Research regarding the role of stigma on HIV risk in GBM has found that discrimination is often compounded with other sources of stigma, including stigma around gender identity and racism.43-

52 Gender roles have been shown to influence the perception that one male partner is “womanly” or “weak”, which in turn facilitates problematic power dynamics, such as when the more

”manly” partner exerts undue influence over decisions surrounding condom use.43,44,52,53 This stigma produces marginalization in GBM and, in turn, strongly influences an individual’s vulnerability for HIV infection through engagement in higher risk sexual behaviors.44,46,47,53-55

This is particularly true for individuals in disadvantaged social positions, who are likely to go through psychologically straining life experiences (stressors) due to their intersecting identities

(e.g., being gay and black in a racist and sexist social environment).44,46,56-58

Legislation contributing to unequal access to preventive programming may act as a barrier to the HIV response. In particular, geographic disparities in HIV infection are not uncommon in the U.S., with the South having twice as many young adults diagnosed with an

AIDS-related infection when compared to the northeast.59 Despite the expansion of Medicaid and the advent of the Affordable Care Act, the South is one of the more restrictive regions in the

U.S. when it comes to Medicaid eligibility.59-61 This restrictiveness results in many PLWHIV being un- or under-insured, less likely to be virally suppressed, and more likely to contribute to forward transmission. Moreover, a recent CDC analysis found that black GBM living in the

South are undertested despite being at higher risk for HIV, therefore pointing to a gap in service delivery.62 These multi-level mechanisms contribute and play a pivotal role in how GBM of color engage in, or fail to engage in, preventative services. These factors also highlight the need 5 to understand the intersecting nature of HIV risk, particularly among those from disadvantaged communities.

Resilience as a buffer for HIV Risk

Resilience is a multi-dimensional intrapersonal characteristic that positively influences self-efficacy and adaptive coping and has been thought to contribute to better health and decreased HIV risk through behavioral, psychological and physiological mechanisms.57,63 There is a growing body of literature that documents cross-sectional associations among greater levels of resilience, protective sexual behaviors (e.g., consistent condom use), and a lower HIV prevalence. A study of Black GBM in Texas found that social support, a resilience psychosocial factor, was positively associated with more frequent HIV testing and higher rates of consistent condom use during anal sex.64 Another study of Black GBM in southern states found that individuals with higher resilience scores had a lower prevalence of condomless sex.65 Another study saw a negative correlation between higher resilience and heavy substance use and mental health issues, and prevalent HIV infection.66

A resilience framework implies a departure from deficit-based research and could denote an opportunity to build on strength-based approaches to the public health response to HIV/AIDS.

Resilience theory focuses on protective factors that originate at the individual level, such as coping, and translates to factual resources at the community level, such as social support. Herrick et al., describe how social support and high community involvement are associated with decreased risk behaviors and conclude that harnessing the strengths and resilience of GBM may enhance HIV prevention programs and, thus, reverse trends in infection.67-69 Nevertheless, most of the published literature on resilience remains largely theoretical and widely understudied in the HIV literature. 6

Ending the HIV Epidemic across the Nation

The United States Department of Health and Human Services established The Ending the

HIV Epidemic: A Plan for America (EHE) to reduce the number of new HIV infections by 75% by 2025 through combination efforts, including treatment as prevention, pre-exposure prophylaxis (PrEP), post-exposure prophylaxis (PEP), and HIV testing with timely linkage to care.9,70-72 Further, the UNAIDS “90-90-90” strategy calls for 90% of people living with HIV to be diagnosed, with 90% initiating ART, and 90% of people initiating ART to achieve and sustain viral suppression through adherence to the treatment and engagement in medical care.15

Successful and prolonged engagement in HIV care, including ART, not only reduces HIV transmission and risk behaviors, but also leads to improvements in the morbidity and mortality of

HIV- and AIDS-related illnesses, thus facilitating improvements in overall health.21,28,29

Undetectable = Untransmittable In 2015, the World Health Organization (WHO) revised its guidelines and recommended that anyone infected with HIV should begin antiretroviral therapy (ART) as soon after diagnosis as possible.73 This test-and-treat approach removes all limitations on ART eligibility based on

CD4+ counts – where patients were previously recommended to start ART when found to have less than 250 CD4+ cells/mm3 by a healthcare provider.73 Current treatment goals aim to suppress viral loads (typically defined as 50 copies of HIV RNA per milliliter) in all HIV- infected patients. PLWHIV who maintain durable viral suppression are unable to transmit the virus to sexual partners and, as such, gave way to the Undetectable = Untrasmittable (U=U) campaign.74,75

Achieving U=U can have profound public health significance. A 2017 epidemiological study estimated that 1 in 6 GBM in the U.S. will be diagnosed with HIV in their lifetime if current incidence trends remain stable.76 Hess et al. found that, although inflated when compared 7 to other subgroups, the lifetime risk estimate for GBM was lower, largely due to current combination prevention efforts such as highly-active ART for treatment and PrEP for prevention.76 Analyses on the cost-effectiveness of preventing HIV through these methods found that interventions aimed at diagnosing and treating HIV were highly cost-effective, particularly when aimed at GBM.77 Moreover, Shackman et al.’s analysis found that the medical cost saved by avoiding one HIV infection was $229,800 and concluded that the economic value of prevention is substantial when compared to the high cost of HIV treatment.78

Despite the current cost of HIV disease management, ensuring timely linkage to care remains a high priority in all prevention efforts given the potential to eradicate forward transmission among undetectable PLWHIV.79 Although the quality and efficacy of HIV treatment continues to advance, racial\ethnic disparities still persist with regards to retention in HIV care, adherence to

ART, and viral load suppression.10,22 As such, monitoring the effectiveness of test and treat strategies is of utmost importance and necessary for identifying areas of improvement.

HIV Care Continuum in the United States The HIV treatment cascade – often referred to as the HIV care continuum – can be an effective tool for monitoring the progress of HIV intervention strategies by outlining and modeling the sequential stages of HIV care from diagnosis to viral suppression.80 Advances in biomedical strategies to prevent HIV and recent worldwide EHE initiatives, such as the UNAIDS

90-90-90 goals and U=U, have also led to concerted efforts to monitor HIV testing and PrEP uptake.71

Status Neutral Engagement in Care The New York City Department of Health and Mental Hygiene (DOHMH) proposed the status-neutral prevention and treatment cycle, which puts forth a continuum of care irrespective of HIV status, for tracking the progress of HIV prevention and care efforts.70,71 This status 8 neutral approach to HIV care is a multidirectional and dynamic model that centers around HIV testing and diverges depending on the individual’s status; those who test HIV-negative fall into the “HIV Primary Prevention” continuum while those who test positive fall into the traditional treatment engagement arm.71 The primary component of the status neutral approach is HIV testing, and, as such, concerted efforts have been made to expand access to and use of testing services.31,71,81 These efforts have manifested in various ways, such as the incorporation of rapid

4th generation HIV tests that are able to detect acute HIV in sexual health clinics (e.g., the Alere

Determine HIV Ab/Ag combo test), and the distribution of free at-home HIV testing kits to

GBM (e.g., the FDA approved OraQuick in-home rapid HIV test).82,83

Point-of-care HIV testing, both in community and medical settings, allows for widespread detection of HIV.84 Although we are increasingly able to diagnose HIV at higher rates, there is a continued need to understand determinants of seroconversion among GBM and to identify the potential barriers to linkage to medical services. Difficulties remain in maximizing linkage to care and viral suppression, especially in hard-to-reach sexual minority populations who are HIV-positive.9,16,70,71,85 Over one-third of all PLWHIV are not fully engaged in HIV primary medical care, and sexual minority populations of color experience starkly worse rates of engagement when compared to their white counterparts.9,16,22,70,71,85,86

Barriers and Facilitators to Engagement in HIV Care for GBM Consistent use of ART is necessary to achieve viral suppression.21,74 Inconsistent use of

ART may be fueled by individual-level challenges, such as depression, as well as policy-related factors such as the high cost of treatment and inadequate insurance status (particularly, whether or not an individual is covered by private or government-provided insurance).87 Considering the high cost of ART, the barriers to accessing health insurance, and the limited financial resources of many PLWHIV, the AIDS Drug Assistance Program (ADAP), a part of Ryan White Part B 9 funding, acts as a last resort provider for ART and other essential HIV-related medications free of charge to low-income PLWHIV who qualify for the program.88 Unfortunately, this program has been found to be under-utilized by PLWHIV.88

Further, engagement in care is heavily dependent on provider-patient relationships.

Studies have documented the important role providers play in getting patients to come back for follow-up visits.48,89-91 Particularly for GBM, providers who are open to discussing matters of sexual health and are inclusive have been most successful in retaining patients.87,90,91 In a study about PrEP use among GBM in NYC, Jaiswal et al. found that with less concerns about having to talk to providers about their sex life and less concerns about paying for PrEP, the higher the odds to be on PrEP.92 Further, using the National Survey on HIV in the Black community survey, Ojikutu et al. found that those with higher knowledge about PrEP and higher use of medical services were more willing to initiate and use PrEP.93 Particularly, both studies found lower willingness and actual use of PrEP when perceived stigma was high, and trust in the healthcare system was low.92,93 These findings are in line with the literature on structural barriers specific to sexual minority populations, such as stigma and medical mistrust. Further, homelessness, lack of healthcare access, and low availability of PrEP-prescribers have also been found to significantly limit PrEP uptake and engagement in HIV care, once diagnosed.26,31,94

Finally, financial issues, limited insurance coverage, lack of information, and self-perceived low risk of HIV exposure were found to be significant barriers to PrEP uptake.95-97

Rationale for the Dissertation

There is an urgent need for continued understanding of unique factors affecting HIV risk and engagement in HIV care for GBM. Biological, behavioral and structural factors make the dynamics of the epidemic in the U.S. complex.98 Aside from sexuality-related stigma, GBM 10 experience high levels of victimization including intimate partner violence, stress, depression and substance use which puts them at a heightened risk for HIV infection.50,87,99 There are little recent data on the prevalence of homelessness and incarceration among GBM from across the nation. Although we understand that multiple factors may work in tandem to increase HIV risk, there are few national studies looking at the additive effect of all these on HIV risk. Further, prevention research has largely studied HIV risk through a deficit-based, risk focused approach.

Research has begun to emerge with a focus on the strengths and resilience of GBM but, overall, remains widely understudied. More empirical studies are needed to understand how resilience may impact HIV risk. Finally, the U.S. is failing to meet viral suppression targets and there are large gaps in the HIV continuum of care for GBM. Over one-third of all PLWHIV are not fully engaged in HIV primary medical care, and sexual minority populations of color experience starkly worse rates of engagement when compared to their white counterparts.9,16,22,70,71,85,86

Notably, the largest drop-offs in the prevention engagement continuum occur in provider- initiated discussions for PrEP eligibility and actual PrEP initiation, pointing towards potential disparities and barriers to PrEP initiation.71 As such, there is continued need to understand the barriers and facilitators to HIV testing, prompt linkage-to-care and retention in care.

Specific aims

This dissertation uses a multi-method approach to understand factors influencing HIV risk and engagement in HIV care among a U.S. national sample of GBM. This study examined the individual and contextual factors influencing GBM’s risk and identified potential missed prevention and intervention opportunities. The following specific aims were addressed:

Aim 1: Measure exposure to syndemic conditions, describe the conditions most likely to co- occur and examine their association to HIV risk. 11

Aim 2: Describe the levels of resilience and identify associations with HIV risk and conduct comparisons by race/ethnicity, region, age and other socio-demographic characteristics.

Aim 3: Describe the barriers and facilitators to engagement in prompt HIV care 3-months after the delivery of an HIV-positive result.

Theoretical Frameworks

Despite the large body of literature on correlates of HIV risk among GBM, few longitudinal studies have been implemented to examine the way these factors are compounded for GBM. Aim 1 made use of the Syndemic Theory, which posits that two or more vulnerability factors (e.g., depression, anxiety, etc.) work together to diminish health. Syndemic conditions can be defined as co-occurring epidemics that have an additive effect on risk, and range from physiological (i.e., co-morbities) or psycho-social (i.e., behavioral, social and/or structural) factors (Figure 2).100,101 In particular, research has shown a positive association between number of syndemic conditions and HIV risk behavior and prevalence but no syndemic studies have included homelessness and history of incarceration into its models. Aim 2 was structured through a resilience framework in which resilience is conceptualized as a multi-dimensional intrapersonal characteristic influencing HIV risk behaviors and protective behaviors.65,102 Resilience appears to have an important role in shaping whether or not people recover from adversity and sustain healthy growth and functioning.102,103 High levels of well-being protect against elevated levels of inflammation, decrease the likelihood of disability and early mortality, and helps people manage the negative impact of health changes.57,102,103 Given the continued high numbers of new HIV infections among GBM, there is a need to understand the protective role of resilience on HIV to develop strength-based prevention interventions that capitalizes on the assets, and resources unique to GBM. Finally, Aim 3 was structured through the social ecological model (SEM) to 12 explore the complex interplay of individual, relationship, community, health care system and policy factors which influence engagement in HIV care.104 The SEM recognizes that an individual’s health may be influenced by individual, interpersonal, social and structural factors.104,105

Organization of the dissertation

Following this introduction, the dissertation contains four additional chapters. In chapter

2, we addressed specific aim 1 in which we used the Syndemic Theory framework to assess the prevalence of syndemic conditions and explored its associations with HIV risk. Notably, our syndemic model incorporates homelessness and history of incarceration into the assessment of cumulative risk for HIV given the heightened HIV vulnerability among GBM experiencing homelessness and incarceration. We hypothesized that a syndemic of psychosocial and behavioral conditions would be associated with greater HIV risk. Our hypothesis was largely supported by the data and provide a compelling case towards the adoption of these new variables into future syndemic analyses.

In chapter 3, we addressed specific aim 2 using a resilience framework. Using this strength-based approach to HIV prevention, we hypothesized that resilience buffered HIV risk.

Our hypothesis was not fully supported by our analyses, in which we found no statistically significant association between resilience and our composite measure of HIV risk. Nonetheless, when disaggregating our measure of HIV risk into its behavioral components, we found a significant negative association between resilience and condomless receptive anal sex. This led us to conclude that resilience may be better conceptualized and measured as a multi-dimensional factor, and that future studies should ensure to assess its relationship to specific HIV risk behaviors. 13

Chapter 4 addresses specific aim 3 in which we explored linkage, engagement and retention in HIV care among participants newly diagnosed with HIV through qualitative in-depth interviews. We explored the barriers and facilitators to engagement in care using the socioecological framework. Through thematic analyses, we identified four major themes related to participants’ engagement in care: 1) Reasons for HIV testing (e.g., HIV self-testing and expectation of positivity), 2) Linkage-to-care (e.g., appointment/logistic issues and social support as encouragement), 3) Barriers (e.g., financial burden, competing priorities and fear/stigma) and facilitators (e.g., financial assistance, patient-provider relationships, auxiliary support services and health agency) to engagement in HIV care, and 4) PrEP as a missed prevention opportunity.

In chapter 5, we summarize the findings from our specific aims. We also discuss the strengths and limitations of our methods and analyses. Finally, we conclude with policy implications and directions for future research.

Data Sources

This dissertation uses data collected as part of the Together 5,000 study, a U.S. national, internet-based cohort study of men, transgender men, and transgender women who have sex with men. The overall goal of the study was to identify modifiable individual and structural factors associated with HIV seroconversion and pre-exposure prophylaxis (PrEP) uptake. Enrollment began in 2017 using advertisements on geosocial networking phone applications and concluded in 2018. This dissertation is a secondary analysis of quantitative data from a cohort of 6,118

GBM ages 16-49 at high risk for HIV transmission (defined as meeting CDC guidance for PrEP use), and qualitative data from 50 GBM diagnosed HIV-positive during their participation in

Together 5,000.

Eligible participants were men, transgender men, and transgender women; aged 16–49 14 years; had at least two male sex partners in the past 3 months; were not currently participating in a HIV vaccine or PrEP clinical trial; were not on PrEP at the time of enrollment; lived in the

United States or its territories; self-reported HIV status as HIV negative or unknown.

Additionally, eligible participants met at least one of the following criteria: diagnosed (within past 12 months) with syphilis, rectal gonorrhea or chlamydia, shared injection drug use in the last

12 months, self-reported more than one receptive CAS acts with a man in the past 3 months, self- reported greater than two insertive CAS acts with a man in the past 3 months, took postexposure prophylaxis (PEP) in the past 12 months, and/or self-reported methamphetamine use in the past 3 months.

Parent Study Procedures

Interested participants completed an initial web-based screening survey collecting data on sexual behavior, substance use, demographic characteristics, history of PrEP use, and history of post-exposure prophylaxis (PEP) use. Eligible participants were asked to complete a secondary web-based baseline survey that further assessed psychosocial and network characteristics. Out of the 8,777 eligible participants, 6,283 completed the secondary baseline survey and were asked to provide a valid mailing address. Participants were then sent an at-home HIV test kit via mail and were asked to mail oral fluid samples to the study laboratory for analysis. A full description of the Together 5,000 study, recruitment methods and enrollment numbers (Figure 1.4) have been previously published.106,107

Further, a trained staff member contacted participants to deliver their HIV results over the phone. A total of 196 participants tested preliminary HIV-positive at enrollment; results were successfully delivered to 132 (67%) of participants. Those who received preliminary HIV- positive results were provided with a list of clinic referrals for linkage-to-care and support. Three 15 months afterwards, the 132 participants were invited to undergo a qualitative interview about their experiences accessing care following results delivery.108 Fifty-four participants agreed to participate in the qualitative sub-study. Interviews were conducted by two study staff members and the principal investigator. All interviews were conducted over the phone, recorded using a call recording earphone device and transcribed verbatim. Transcripts were verified against their corresponding audio recording by three study staff members for quality assurance. The Together

5,000 study protocol was approved by the Institutional Review Board in the Human Research

Protection Program (HRPP) of the City University of New York (CUNY) Graduate School of

Public Health and Health Policy.

Application of Findings

The findings of this dissertation may be useful in that it expands the application of

Syndemic Theory by incorporating a unique set of social condition variables, such as incarceration and homelessness history, often left out in traditional syndemic analyses. This dissertation also explores both deficit- and strength-based approaches to HIV prevention through a syndemic framework and a resilience framework. Further, the qualitative data from recently diagnosed individual’s experience accessing HIV care provides valuable insights into barriers and facilitators to engagement in care across the U.S. As such, this research provides new information on the state of the HIV policies and hard to reach populations in the US and contribute toward the goal of ending AIDS in the US by 2030.109

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Figure 1.1 - CDC Estimated HIV Prevalence and Incidence,1980-2012

Figure 2.1 - CDC Estimated HIV Prevalence and Incidence,1980-2012

*Obtained from the CDC Fact Sheet: Today’s HIV Epidemic 1

Figure 1.4 - HIV Diagnoses among GBM, 2006-2017

Figure 1.5 - HIV Diagnoses among GBM, 2006-2017

*Line graph created using data from the CDC HIV Surveillance Reports Vols. 17-19, 29.

Figure 1.3 - HIV Diagnoses among GBM, 2006-2017*Line graph created using data from the CDC HIV Surveillance Reports Vols. 17-19, 29. 25

Figure 1.7 - HIV Incidence in NYC, GBM, 2012-2016

*Obtained from the CUNY Institute for Implementation Science in Population Health’s End the Epidemic Dashboard.

Figure 1.6 - HIV Incidence in NYC, GBM, 2012-2016*Obtained from the CUNY Institute for Implementation Science in Population Health’s End the Epidemic Dashboard.

Figure 1.4 - Together 5,000 Enrollment Flowchart 27

CHAPTER 2: THE ASSOCIATION BETWEEN SYNDEMIC CONDITIONS AND HIV RISK IN AN U.S. NATIONAL COHORT OF GAY, BISEXUAL AND OTHER MEN WHO HAVE SEX WITH MEN (GBM)

ABSTRACT

Background: Gay, bisexual and other men who have sex with men (GBM) continue to be at disproportionate risk for HIV. Nonetheless, few studies have looked at the role of psycho-social syndemics on HIV risk in large national samples of MSM.

Methods: 6,118 MSM completed a cross-sectional survey on socio-demographics, HIV risk behaviors, mental health and substance use as part of the Together 5,000 study, an U.S. national cohort of men, transgender women and transgender men who have sex with men. We evaluated the prevalence of syndemic conditions and explored its associations with HIV risk.

Results: Participants’ mean age was 30.6 years (SD=7.9); 52.2% identified as white, 24.6% as Hispanic/Latino and 11% as Black. Half of participants (50.4%) reported some intimate partner violence (IPV), while one-quarter reported symptoms of anxiety (30.6%), depression (28.8%), and experiences of childhood sexual abuse (CSA, 24.3%). Moreover, 21.2 % and 11.9% reported hazard alcohol and polydrug use, respectively. One-fifth (20.3%) reported at least two co- occurring syndemics. In multiple linear regressions, IPV (β = 1.07, p < 0.001), childhood sexual abuse (β = 0.54, p < 0.05), polydrug use (β = 5.62, p < 0.001), incarceration history (β = 1.91, p < 0.001) and homelessness (β = 2.31, p < 0.001) were positively associated with HIV risk. Further, increasing cumulative syndemic conditions were associated with higher HIV risk (F(14, 6103) = 62.7, p < 0.001). For instance, HIV risk increased with one (β = 1.06, p < 0.001), two (β = 1.54, p < 0.001), three (β = 2.88, p < 0.001), four (β = 4.16, p < 0.001) and more than four (β = 7.04, p < 0.001) co-occurring syndemics.

Conclusions: We found further evidence of psychosocial and substance use problems among MSM our cohort. Increasing syndemic burden was associated with greater HIV risk. Our findings highlight the need for interventions that address psychosocial health outcomes, within the context of HIV prevention.

INTRODUCTION

HIV continues to be a pervasive public health issue in the United States.1,2 Although new

HIV diagnoses have been declining over the last decade, the number of incident cases of HIV among Gay, Bisexual and other men who have sex with me (GBM) has remained relatively stable.2-8 Notably, the proportion of HIV cases among GBM has been increasing slightly since

2011.2-8 In 2017, there were 38,739 new HIV diagnoses in the U.S.; GBM accounted for over two-thirds (27,000, 70%) of all new HIV diagnoses.2,3,5,9 Particularly, young GBM (under the age of 35 years) accounted for 64% of all new HIV diagnoses among all GBM in 2017.3-6 The rate of diagnoses for those aged 25 to 34 increased by 26% from 2010 to 2016.3-6 At this rate, one in six GBM will acquire HIV in their lifetime, including one in two Black GBM and one in for Latino GBM, thus warranting continued and concerted efforts for prevention and intervention in sexual minority populations.2,3,6

GBM experience high levels of adverse psychosocial conditions such as depression,10,11 problematic alcohol consumption and substance use,12,13 exposure to violence (e.g., intimate partner violence)14,15 and homelessness16-18 that puts them at heightened risk for HIV infection.19-

21 In fact, analyzing HIV risk through a syndemic framework can provide a nuanced understanding of how behavioral and psychosocial factors can compound HIV vulnerability.13,22-

25 The Substance Abuse, Violence and HIV/AIDS (SAVA) model of syndemics describes how the confluence of substance use, violence, and sexual risk behaviors interact to exacerbate HIV burden among vulnerable populations.14,22,23,26 Other models expanded on the SAVA model to incorporate psychosocial variables (e.g., depression, childhood sexual abuse, sexual compulsivity, etc.) that have provided a more complex view of the unique risk factors affecting

GBM in the U.S.23,26 Past research has demonstrated the additive risk these psychosocial 29 conditions can have on an individual’s health. 13,19,24,26 One study of 1,033 HIV-negative GBM from across the U.S. found that at least 62% of men reported at least one syndemic condition and found that HIV transmission risk behaviors were highest among those reporting three or more syndemic conditions.23,26 Another study of 464 Latino GBM in Philadelphia, PA, found participants with two or more factors reported more male partners and more CAS with casual male partners than those with none.27 Further, Martinez et al. led a study of 176 Hispanic men and transgender women in New York City and found that those who reported three or four syndemic factors were significantly more likely to report heavy drinking, and found an association between heavy binge drinking, and having multiple sexual partners.13 Another study of 100 gay male couples living in the U.S. found that syndemics contribute to HIV transmission risk between main sexual partners.28 Notably, these studies highlight the need for extended research with larger geographically diverse samples that incorporate other social condition variables, such as homelessness and incarceration, that have also been found to be prevalent and important for understanding risk among GBM but often left out of the syndemic analyses.8,14,16-

19,23,24,26,29

Research indicates that sexual minority adults make up a significant proportion of the homeless adult populations in the United States; about 20 to 40% of the homeless population despite being about 5% of the general population.30-33 Young adults are 8 times more likely to experience homelessness.30,32 In fact, the Ali Forney Center reports that 42% of the homeless youth in New York City are sexual minorities; 49% male and 90% persons of color.34 Further, those experiencing homelessness are at risk of a plethora of risk behaviors and negative health outcomes, such as engaging in high-risk sexual behaviors and commercial sex work, contracting

HIV and other STIs, and at higher risk of victimization.30-32,34 Further, incarceration is a concern 30 among GBM. In a 2017 study, Meyer et al. found that about 9% of men in prison and 6% of men in jail self-identify as gay or bisexual; they estimate that the incarceration rate of sexual minority adults was 1882 per 100 000, more than 3 times that of the US adult population.35

Similarly, those with a history of incarceration have been found to have a higher risk for HIV.35-

39 Given the heightened HIV vulnerability among those experiencing lifetime homelessness and incarceration, these variables should be explored in syndemic analyses.

The present study extends the recent work on syndemics and HIV risk by exploring eight syndemic conditions (intimate partner violence, depression, anxiety, childhood sexual abuse, polydrug use, hazard alcohol use, incarceration history and homelessness) among a national sample of GBM in the U.S. Using a syndemic framework, we hypothesized that a syndemic of psychosocial and behavioral conditions would be associated with greater HIV risk.

METHODS

Cohort recruitment, enrollment, and surveys

This study uses data collected as part of the Together 5000 study, a U.S. national, internet-based cohort study of men, transgender men, and transgender women who have sex with men. The overall goal of the study is to identify modifiable individual and structural factors associated with HIV seroconversion and PrEP uptake. Enrollment began October 2017 using ads on men-for-men geosocial networking phone applications and concluded in June 2018.

Participants were eligible if they identified as cisgender men, transgender men, or transgender women; were between the ages of 16 and 49 years; had at least 2 male sexual partners in the last

3 months; were not currently participating in a HIV vaccine or PrEP clinical trial; were not on 31

PrEP at the time of enrollment; lived in the US or its territories; self-reported HIV status as HIV- negative or unknown; and met at least one of the following additional criteria: diagnosed with syphilis, or rectal gonorrhea/chlamydia in the last 12 months, shared injection drug use needles in the past 12 months, self-reported more than one receptive CAS acts with a man in the past 3 months, self-reported greater than two insertive CAS acts with a man in the past 3 months, took post-exposure prophylaxis (PEP) in the past 12 months, and/or self-reported methamphetamine use in the past 3 months. Notably, the recruitment strategies were targeted to reach GBM, but our enrollment criteria did not exclude transgender men and transgender women who otherwise met study criteria. Nonetheless, transgender individuals were excluded in the present analysis because they are faced with a complex interplay of multi-level psychosocial stressors that may differentially impact HIV compared to GBM.40 Participants were directed to a secured informed consent and enrollment survey webpage that presented questions about demographic characteristics, sexual behavior, and substance use. Eligible participants who consented and completed the enrollment survey (Appendix A) were later sent a link (email and text) to complete a secondary survey (Appendix B) that collected additional behavioral data. Participants completing this secondary survey received a $15 gift card by email.

HIV testing

Participants who completed the second survey were subsequently mailed an OraSure

HIV-1 oral specimen collection device to assess current HIV status. Using a self-addressed and stamped envelope, participants mailed oral fluid samples to the study lab for analysis.

Participants who returned a sample to the lab received another $15 gift card by e-mail. A full description of the recruitment methods and of the Together 5,000 cohort have been previously published.41,42 32

Study Measures

Variables of interest for the current study included demographic characteristics, sexual heath factors related to HIV risk and HIV testing, and HIV vulnerability factors (syndemics):

Polydrug use, hazard alcohol use, Depression, Anxiety, Childhood sexual abuse, Intimate partner violence, Incarceration history and housing instability. Demographic characteristics measured in the enrollment survey included age, race/ethnicity, sexual identity (e.g., gay, bisexual), employment status, highest level of education, annual income, health insurance status, and having performed sex work in the past 3 months. Sexual health variables included perceived HIV status at enrollment (negative vs. unknown), HIV testing history, experience with PrEP and PEP, as well as the number of times participants had insertive and/or receptive CAS in the past 3 months.

HIV risk was measured using the MSM Risk Index43,44, a tool for systematically determining risk for HIV acquisition with a sensitivity of 84% and a specificity of 45% for predicting incident HIV infection in the next six months.43,44 The MSM-Risk index is a validated screening tool for calculating HIV risk among GBM that incorporates age, number of male partners, number of HIV-positive male partners, frequency of condomless receptive anal sex, frequency of condomless insertive anal sex with HIV-positive partners and use of amyl nitrate

(“poppers”) and methamphetamines.43,44 Risk scores ranged from 0 to 45; higher scores point towards higher HIV risk.43,44

We identified the following as HIV vulnerability factors based on an expanded Syndemic framework. Polydrug use was determined based participants reported use of cocaine, crack, crystal methamphetamine, marijuana, ecstasy, gamma-hydroxybutyrate (GHB), ketamine, heroin, and poppers in the last 90 days. Participants reporting use of three or more will be coded 33 as having engaged in polydrug use. Hazard alcohol use was assessed using the alcohol use disorders identification test (AUDIT), a 10-item questionnaire to screen for hazardous alcohol use. The scores can range from 0 to 40, with a score between 8 and 14 depicting hazard alcohol use (1, yes or 0, no). An indication for depression was measured using the Patient Health

Questionnaire (PHQ-2), which screens for depression with a sensitivity of 86% and specificity of

78%.45 PHQ-2 score ranges from 0-6, with a score of 3 of greater as the optimal cut off point to screen for major depressive disorder.45 An indication for anxiety was measured using the

General Anxiety Disorder scale (GAD-2), which screens for anxiety with a sensitivity of 86% and specificity of 83%.46 GAD-2 score ranges from 0-6, with a score of 3 of greater as the optimal cut off point to screen for general anxiety disorder.46 Childhood sexual abuse was determined by asking participants if they had experienced sexual activity, into which they felt forced or scared by someone who was older than them, and whether they were aged 16 or younger at the time (0, no; 1, yes).47 Intimate partner violence was assessed through an adaptation of the Revised Conflict Tactics Scale, a 12-item questionnaire that measured unwanted physical or emotional abuse.48 Participants who responded yes to any of the items were coded as a yes on a dichotomous variable indicating intimate partner violence (0, no; 1, yes). Incarceration history was determined by asking participants whether or not they had ever been incarcerated. Answers will be coded as a dichotomous variable (0, no; 1, yes). Finally, housing instability was determined by asking participants if they had unstably housed (e.g., couch surfing, homeless) in the last five years (0, no; 1, yes).

Analysis Plan

Our objective was to: 1) assess the prevalence of syndemic conditions in a large geographically diverse sample of GBM; 2) to explore the associations between individual and 34 cumulative syndemics, and HIV risk. Descriptive statistics were used to describe the sample (n =

6,118). The median number of syndemic conditions was compared across demographic characteristics using a median test. Frequencies were used to determine the prevalence of individual and cumulative syndemic conditions reported by participants. Bivariate associations between the presence of each syndemic condition and HIV risk were calculated as odds ratios.

Further, we assessed the association of each individual syndemic factor on HIV risk using multiple linear regression. Finally, a multiple linear regression was used to test the additive effect of the syndemic factors (presence of multiple factors) and HIV risk. Linear regressions were adjusted for age, race, sexuality, employment status, current health insurance status, and income.

Statistical significance was set at the 0.05 level. All analyses were conducted using SPSS 26.

These procedures were reviewed and approved by the Institutional Review Board at The City

University of New York’s Graduate School of Public Health and Health Policy.

RESULTS

Descriptive statistics for demographic characteristics and comparisons of the number of participants within each demographic characteristic reporting more than the median number of syndemic conditions are presented in Table 2.1. Participants (n = 6,118) had a mean age of 30.6 years (SD = 7.9). The majority identified as Gay, Queer or Homosexual (85%) and did not have a main sexual partner (73.3%). Participants identified as white (52.2%), Hispanic/Latino

(24.6%), black (11%), multiracial (8.7%) and Asian/Pacific Islander (3.5%). Nearly two-thirds

(62.6%) reported being fully employed, 45% reported having some college education, 41.7% reported an annual income between $20,000 and $49,999, and 48.4% lived in southern states of the U.S. A quarter (27.4%) reported that they did not have/were unsure if they had health 35 insurance and 14.6% reported engaging in transactional sex in the past 3 months. Finally, over half self-reported as HIV-negative (58.2%), and one-quarter (26.3%) reported that their last HIV test was more than a year ago. Using median analyses, a higher proportion of syndemics was found among participants who identified as Latino and multiracial, reported lower levels of education and income, were unsure of their HIV status and had most recently tested more than a year ago, and who had engaged in sex work in the last 12 months.

The prevalence of syndemic conditions are presented in Table 2.2. Half of participants

(50.4%) reported intimate partner violence (IPV), while roughly one-quarter reported symptoms of anxiety (30.6%), depression (28.8%), and childhood sexual abuse (CSA, 24.3%); one-fifth

(20.3%) reported unstable housing within the last 5 years, and 14.5% reported having been incarcerated at least once in their lives. Moreover, 21.2 % and 11.9% reported hazard alcohol and polydrug use, respectively. One-quarter (24.7%) of participants reported one syndemic condition, 20.3% reported two co-occurring syndemics, 15.8% reported three, 10.3% reported four, and 8.8% reported more than four co-occurring syndemics.

The bivariate associations between syndemic conditions, expressed as odds ratios (ORs), are presented in Table 2.3. The majority of the syndemic conditions were associated with each other and with HIV risk. Nonetheless, there were no statistically significant associations between: polydrug use and depression, and polydrug use and CSA. There were no statistically significant association between hazard alcohol use, and depression, anxiety and CSA. Further, no association was found between incarceration and anxiety, homelessness and anxiety, and homelessness and alcohol use.

Table 2.4 displays the unadjusted and adjusted linear regression models of HIV risk and individual syndemic conditions (model 1), as well as cumulative syndemics (model 2). In the 36 unadjusted multiple linear regression for Model 1 (F(8, 6109) = 115.99, p < 0.001), IPV (β =

1.20, p < 0.001), depression (β = 0.55, p < 0.05), polydrug use (β = 5.78, p < 0.001), incarceration history (β = 1.36, p < 0.001) and homelessness (β = 2.79, p < 0.001) were positively associated with HIV risk. After adjusting for control variables, the relationship between depression and HIV risk was not statistically significant; conversely, the relationship between CSA and HIV risk became statistically significant (β = 0.53, p < 0.05). Finally, in the adjusted multiple linear regressions for Model 2, increasing cumulative syndemic conditions were associated with higher HIV risk (F(14, 6103) = 66.32, p < 0.001). For instance, HIV risk increased with one (β = 1.23, p < 0.001), two (β = 1.46, p < 0.001), three (β = 3.06, p < 0.001), four (β = 4.40, p < 0.001) and more than four (β = 7.40, p < 0.001) co-occurring syndemics.

DISCUSSION

We examined the association between eight syndemic conditions (IPV, depression, anxiety, CSA, polydrug use, hazard alcohol use, incarceration history and homelessness) and

HIV risk in a national sample of HIV-negative cis-gender gay and bisexual men. We found additional evidence that these social conditions intersect to exacerbate HIV risk. This study also underlines the importance of including syndemics beyond substance use and violence in syndemic research. We demonstrate that environmental and behavioral factors such as homelessness, incarceration are prevalent among GBM in the U.S. and contribute to HIV acquisition. Consistent with the literature and current trends in the HIV epidemic, syndemics were particularly common among populations most at risk for HIV, including those identifying as Latino/Multiracial, with lower income and educational attainment, who engage in commercial sex work, who were unsure of their HIV status and those who had not tested for HIV in the last 37 year. Overall, our analyses provided evidence that increasing syndemic burden was associated with greater HIV risk.

Our study provides valuable insights on the prevalence of homelessness and incarceration among sexual minority men. Past studies have estimated the rates of recent homelessness and history of incarceration among sexual minority individuals across the U.S. but there is a dearth of recent data from geographically diverse samples of GBM. Although studies support the association between incarceration and HIV risk,37,39,49 a 2010 meta-analysis by Gough et al. does not support this relationship.50 Our data illustrate that, not only are they both prevalent among

GBM, but they are significantly associated to increasing HIV Risk. In fact, public health practitioners recognize housing instability and incarceration as important social determinants of health and as catalysts for worsening health outcomes.51-53 Further, those with a history of incarceration are much more likely to become homeless.54,55 As such, there is compelling evidence to justify their adoption in future syndemic models.

Given the shift to a biomedical paradigm of prevention, understanding the complexities of men’s lives is pivotal. This warrants a more comprehensive investigation of the unique risk factors in this population, particularly those that may impact uptake and adoption of preventive

HIV health behaviors, such as pre-exposure prophylaxis (PrEP). For instance, larger structural factors like societal racial discrimination, anti-immigration laws, lack of health insurance coverage and unemployment can significantly impact adherence to biomedical tools and use of testing services.56,57 Future research should explore these social and structural determinants within the context of HIV prevention.

There is a need for targeted interventions for those at the highest risk, particularly racial and ethnic minorities and those from impoverished communities to increase HIV testing 38 frequency and facilitate better engagement in care. Further, as seen in our study findings, HIV prevention is a multi-faceted process. As such, there is a need for a more holistic approach to prevention, wherein HIV prevention is conceptualized as more than just HIV testing and PrEP initiation. Literature on adherence to antiretrovirals and viral suppression has found that housing assistance, and mental health and substance use counselling is pivotal towards maximizing health outcomes that, if not addressed in tandem, may reduce the effectiveness of U=U goals.18,57-60 As such, there are grounds for adopting similar models in the HIV-negative continuum of care. For instance, community-based case management and patient navigators could be successful at helping patients manage their financial, social, and provider-related barriers to HIV prevention.61,62

Limitations

Our findings should be interpreted through careful consideration of its limitations. First, the cross-sectional design of this study prevents making any conclusive causal claims about the temporality and directionality of the relationships we observed. This study was not designed to prove causation, only to assess associations, and therefore causal inferences should be interpreted with caution.63 Although this fully online study allowed for increased geographical reach, it also increased the potential for fraudulent participants.61,62 This study relied exclusively on data from self-reported surveys and, while measures to increase the validity of the data were put into place, social desirability and recall bias may have affected the study findings.64 Further, our surveys were only delivered in English, as such, our findings may not reflect the experiences of GBM who speak other languages. Additionally, the study population was recruited via sexual networking apps and represented a sample of those at highest risk for HIV, who are not on PrEP at enrollment. Given the non-probability sampling, we are unable to generalize these results to 39 other GBM. Finally, our findings are limited to a sample of HIV-negative cis-gender men and we cannot rule out that there may be unique syndemics impacting other gender non-conforming participants and those who are HIV-negative.

Conclusion

To our knowledge, this is the first study to assess syndemics among a large, geographically diverse group of GBM in the U.S. This is particularly important given the relative invisibility of data from GBM outside of larger urban centers and a rapidly evolving epidemic.65-69 Our study underlines the socioeconomic vulnerabilities impacting GBM across the U.S., particularly among racial/ethnic minorities. Our syndemic models showed that the presence of multiple co-ocurring factors, including psychosocial variables such as homelessness and incarceration, were significantly impacting HIV risk. Future studies should further explore the impact of additional structural factors, including racial and ethnic discrimination on HIV prevention and care.

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54. Couloute L. Nowhere to Go: Homelessness among formerly incarcerated people: Prison Policy Initiative;2018. 55. Remster B. A Life Course Analysis of Homeless Shelter Use among the Formerly Incarcerated. Justice Quarterly. 2019/04/16 2019;36(3):437-465. 56. Horn T, Sherwood J, Remien RH, Nash D, Auerbach JD. Towards an integrated primary and secondary HIV prevention continuum for the United States: a cyclical process model. Journal of the International AIDS Society. 2016;19(1):21263. 57. Remien RH, Bauman LJ, Mantell JE, et al. Barriers and facilitators to engagement of vulnerable populations in HIV primary care in New York City. Journal of acquired immune deficiency syndromes (1999). May 01 2015;69 Suppl 1:S16-24. 58. S. TB, Laura F, Jesse T, et al. Improving HIV Care Engagement in the South from the Patient and Provider Perspective: The Role of Stigma, Social Support, and Shared Decision-Making. AIDS patient care and STDs. 2018;32(9):368-378. 59. HUD Exchange. Connection Between Housing and Improved Outcomes Along the HIV Care Continuum 2014. 60. Dandachi D, May SB, Davila JA, et al. The Association of Unmet Needs With Subsequent Retention in Care and HIV Suppression Among Hospitalized Patients With HIV Who Are Out of Care. Journal of acquired immune deficiency syndromes (1999). Jan 1 2019;80(1):64-72. 61. Doblecki-Lewis S, Butts S, Botero V, Klose K, Cardenas G, Feaster D. A Randomized Study of Passive versus Active PrEP Patient Navigation for a Heterogeneous Population at Risk for HIV in South Florida. Journal of the International Association of Providers of AIDS Care (JIAPAC). 2019;18:2325958219848848. 62. Blashill AJ, Brady JP, Rooney BM, et al. Syndemics and the PrEP Cascade: Results from a Sample of Young Latino Men Who Have Sex with Men. Archives of sexual behavior. Jan 2020;49(1):125-135. 63. Morabia A. A history of epidemiologic methods and concepts: Birkhäuser; 2013. 64. Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plastic and reconstructive surgery. Aug 2010;126(2):619-625. 65. Bell D, Valentine G. Queer country: rural lesbian and gay lives. Journal of Rural Studies. 1995;11(2):113-122. 66. D'Augelli AR, Hart MM. Gay women, men, and families in rural settings: Toward the development of helping communities. American Journal of Community Psychology. 1987;15(1):79-93. 67. Williams ML, Bowen AM, Horvath KJ. The social/sexual environment of gay men residing in a rural frontier state: implications for the development of HIV prevention programs. The Journal of Rural Health. 2005;21(1):48-55. 45

68. Preston DB, D'Augelli AR. The challenges of being a rural gay man: coping with stigma. New York: Routledge; 2013. 69. Mustanski B. Getting wired: Exploiting the Internet for the collection of valid sexuality data. J. Sex Res. 2001;38(4):292-301. 46 Table 2.1: Demographic characteristics of the Together 5,000 study, and number of participants above the median number of syndemic conditions, n = 6,118

Characteristic Frequency % Freq above median % Median Test χ² Race/Ethnicity White 3191 52.2 1028 32.2 49.03* Black 674 11.0 206 30.6 Latino 1505 24.6 490 32.6 Asian/Pacific Islander 217 3.5 30 13.8 All Other Multi 531 8.7 212 39.9 Sexual Orientation Gay, Queer, Homosexual 5198 85.0 1647 31.7 14.9* Bisexual 864 14.1 288 33.3 Other 56 0.9 31 55.4 Education < High school diploma 139 2.3 68 48.9 164.6* High school diploma or GED 869 14.2 350 40.3 Some college or technical school training 2752 45.0 1010 36.7 College graduate + 2358 38.5 538 22.8 Employment Status Full-time (40 hours per week) 3831 62.6 1038 27.1 163.8* Part-time (less than 40 hours per week) 785 12.8 313 39.9 Working- or full-time student 492 8.0 145 29.5 Unemployed/Other 1010 16.5 470 46.5 Annual Income Less than $20,000 2014 32.9 842 41.8 207.3* $20,000-$49,999 2554 41.7 828 32.4 $50,000+ 1550 25.3 296 19.1 Has a main partner Yes 1634 26.7 476 29.1 9.03* No 4484 73.3 1490 33.2 Health Insurance Yes 4443 72.6 1236 27.8 137.9* No/do not know 1675 27.4 730 43.6 47 Engaged in sex work (past 12 months) Yes 895 14.6 355 39.7 222.7* No 5223 85.4 1476 28.3 Self-reported HIV Status HIV-negative 3559 58.2 969 27.2 93.9* I don't know; I am unsure 2559 41.8 997 39.0 Have you ever been tested for HIV? In the past 12 months 3746 61.2 1130 30.2 18.2* More than a year ago 1612 26.3 579 35.9 Never 760 12.4 257 33.8 Region Northeast 911 14.9 243 26.7 19.2* South 2950 48.4 993 33.7 Midwest 887 14.5 272 30.7 West 1323 21.7 446 33.7 Pacific, US Territories, Others 47 0.8 6 12.8 M SD Age 30.6 7.9

*p < 0.05 48

Table 2.2. Syndemic prevalence in the Together 5,000 cohort

Frequency (%)

IPV 3081 50.4 Depression 1763 28.8 Anxiety 1873 30.6 CSA 1485 24.3 Polydrug use 731 11.9 Hazard Alcohol Use 1300 21.2 Incarceration History 886 14.5 Homelessness 1243 20.3 Cumulative Syndemics Frequency (%) One Syndemic 1512 24.7 Two Syndemics 1241 20.3 Three Syndemics 967 15.8 Four Syndemics 630 10.3 More than Four 539 8.8 49 Table 2.3. Bivariate associations among syndemic conditions and HIV risk

Hazard Alcohol Depression Anxiety CSA Polydrug use Incarceration Homelessness Use OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)

IPV 2.06* (1.8, 2.3) 1.53* (1.3, 1.8) 1.97* (1.7, 2.3) 1.712* (1.4, 2.1) 1.2* (1.04, 1.34) 1.88* (1.6, 2.20) 1.96* (1.7, 2.3)

Depression - 18.01* (15.7, 20.7) 1.36* (1.2, 1.6) 1.1 (0.9, 1.4) 0.87 (0.73, 1.03) 1.28* (1.05, 1.56) 1.7* (1.4, 2.03)

Anxiety - 1.49 *(1.3, 1.7) 1.4* (1.1, 1.7) 1.14 (0.97, 1.35) 1.03 (0.84, 1.25) 1.16 (0.97, 1.4)

CSA - 0.99 (0.83, 1.2) 1.05 (0.90, 1.21) 1.65* (1.4, 1.9) 1.61* (1.4, 1.9)

1.55* (1.29, Polydrug use - 2.33* (1.92, 2.82) 1.64* (1.4, 1.98) 1.86) Hazard Alcohol - 0.78* (0.64, 0.94) 0.85 (0.72, 1.01) Use

Incarceration - 2.91* (2.5, 3.4)

Homelessness -

* p < 0.05

50 Table 2.4 Linear Regressions of HIV Risk by Individual and Cumulative Syndemics

Model 1: Individual Syndemics b SE P-Val F(df) Adj-R2 Adjusted b* SE P-Val F(df) Adj-R2

IPV 1.21 0.20 0.00 116.3 (8, 6109) 0.131 1.068 0.194 0.00 77.5 (17, 6100) 0.175

Depression 0.55 0.26 0.04 - - 0.248 0.258 0.34 - -

Anxiety 0.49 0.26 0.06 - - 0.346 0.252 0.17 - -

CSA 0.36 0.23 0.11 - - 0.538 0.222 0.02 - -

Polydrug use 5.81 0.30 0.00 - - 5.622 0.295 0.00 - -

Hazard Alcohol Use -0.32 0.23 0.17 - - -0.512 0.227 0.02 - -

Incarceration History 1.35 0.28 0.00 - - 1.908 0.28 0.00 - -

Homelessness 2.78 0.25 0.00 - - 2.307 0.25 0.00 - - Model 2: Cumulative Syndemics^ b SE P-Val F(df) Adj- R2 Adjusted b* SE P-Val F(df) Adj- R2

One 0.18 0.18 0.50 88.6 (5, 6112) 0.067 1.06 0.29 0.00 62.70 (14, 6103) 0.124

Two 0.64 0.27 0.02 - - 1.54 0.30 0.00 - -

Three 1.61 0.28 0.00 - - 2.88 0.32 0.00 - -

Four 3.24 0.35 0.00 - - 4.16 0.37 0.00 - -

More than Four 6.81 0.38 0.00 - - 7.04 0.39 0.00 - - ^Reference group: 0 factors *b coefficients are adjusted for age, race, sexuality, employment status, current health insurance status, and income

CHAPTER 3: EXPLORATION OF THE ASSOCIATION BETWEEN RESILIENCE AND HIV RISK BEHAVIORS AMONG GAY, BISEXUAL AND OTHER MEN WHO HAVE SEX WITH MEN (GBM) ACROSS THE UNITED STATES.

ABSTRACT

Background: Gay, bisexual and other men who have sex with men (GBM) continue to be at disproportionate risk for HIV, predominantly those from racial/ethnic minority populations. Further, minority GBM experience higher rates of mental health issues and substance use that put them at higher risk for HIV. Resilience is an intrapersonal factor among GBM that has been hypothesized to buffer syndemic factors and HIV risk yet remains widely understudied among sexually active GBM. As such, we examined patterns of resilience among a U.S. national cohort of GBM.

Methods: 6,118 cisgender men completed a cross-sectional survey on demographics, HIV risk behaviors, HIV and STI testing history, and mental health as part of the Together 5,000 study, an U.S. national, internet-based cohort of men, transgender women and transwomen who have sex with men. We explored racial and ethnic differences in resilience (using the Connor-Davidson Resiliency Scale CD-Risc-10), and its associations with HIV risk behaviors.

Results: Mean age of participants was 30.6 years (SD = 7.9); 52.2% identified as White, 24.6% as Hispanic/Latino, 11.1% as Black and 8.7% as Asian/Pacific Islander. Over one- third of participants (38.5%) had at least a college degree, and over half (62.6%) worked full- time. Over half self-reported as HIV-negative (58.2%), one-quarter (26.3%) reported that their last HIV test was more than a year ago. Mean CD-Risc-10 score was 28.97 (SD = 6.07, Median = 29, Inter-quartile range = 25, 33). There was a significantly higher mean resilience among those identifying as black, with higher education, having full-time employment, having an annual income of $50,000, having health insurance, being HIV-negative, and having tested in the last year. Moreover, there was a significantly lower mean resilience among those engaging in transactional sex in the last 12 months and among those having been diagnosed with an STD in the last 12 months. We found no statistically significant association between resilience and our composite measure of HIV risk (β = 0.02 [95% CI: 0.02, 0.06]) in adjusted multiple linear regression analyses. Nonetheless, we found a significant association between higher resilience and lower condomless receptive anal sex acts in the last 3 months (β = 0.10 [95% CI: -0.17, -0.04], p < 0.001).

Discussion: Our study may have been limited in its ability to fully measure resilience and could have accounted for our non-significant findings. The CD-Risc only measures adaptability and coping, and although this is an acceptable construct to measure, resilience may be better conceptualized as a multi-dimensional factor. It may also be more appropriate to measure the association between resilience and HIV risk by focusing on specific sexual behaviors rather than a composite measure of sexual risk. Our findings highlight gaps and the need to promote health-enhancing positive factors in HIV intervention work. 52

INTRODUCTION

HIV continues to be a pervasive public health issue in the United States.1,2 Although new HIV diagnoses have been declining over the last decade, the number of incident cases of

HIV among Gay, Bisexual and other men who have sex with me (GBM) has remained relatively stable.2-8 Notably, the proportion of HIV cases among GBM has been increasing slightly since 2011.2-8 In 2017, there were 38,739 new HIV diagnoses in the U.S.; GBM accounted for over two-thirds (27,000, 70%) of all new HIV diagnoses.2,3,5,9 Young GBM

(under the age of 35 years) accounted for 64% of all new HIV diagnoses among all GBM in

2017.3-6 The rate of diagnoses for those aged 25 to 34 increased by 26% from 2010 to 2016.3-

6 At this rate, one in six GBM will acquire HIV in their lifetime, including one in two Black

GBM and one in four Latino GBM, thus warranting continued and concerted efforts for prevention and intervention in sexual minority populations.2,3,6 A concerted response to the

HIV epidemic requires contextualized and multi-level research and prevention for GBM. As such, there is dire need to fully understand the contexts that shape men’s HIV risk.

Intrapersonal traits, such as resilience, may mitigate HIV among GBM, particularly those from racial minority groups.10

HIV testing and higher rates of consistent condom use during anal sex.16 Another study of

Black GBM in southern states found that individuals with higher resilience scores had a 53 lower prevalence of condomless sex.17 Another study saw a negative correlation between higher resilience and heavy substance use and mental health issues, and prevalent HIV infection.18

A resilience framework posits that GBM possess resilience that enables them to process experiences with homophobia and heteronormativity and, as such, thrive through the adversity brought on by HIV/AIDS.19,20 This framework implies a departure from deficit- based research and could denote an opportunity to build on strength-based approaches to the public health response to HIV/AIDS. Further, it focuses on protective factors that originate at the individual level, such as coping, and translates to factual resources at the community level, such as social support. Herrick et al. describe how social support and high community involvement are associated with decreased risk behaviors and conclude that harnessing the strengths and resilience of GBM may enhance HIV prevention programs and, thus, reverse trends in infection.19-21 Nevertheless, the majority of the published literature on resilience remains largely theoretical.

Resilience also remains widely understudied in the HIV literature. Only one published study has specifically looked at the direct relationship between resilience and HIV risk behaviors.17 However, this study focused solely on Black GBM from Atlanta, Georgia and

Jackson, Mississippi.17 To our knowledge, there have been no published national studies looking at the relationship between resilience and HIV risk behaviors in large geographically diverse samples of sexually active GBM. Given this, the present study fills this gap in knowledge by determining the geographic, racial and socio-demographic differences in resilience among a U.S. national sample of GBM in the U.S. Further, this study explores the association between HIV risk and resilience; hypothesizing that resilience is associated with lower HIV risk.

METHODS

Cohort recruitment, enrollment, and surveys

2017 using ads on men-for-men geosocial networking phone applications and concluded in

June 2018. Participants were eligible if they identified as men, transgender men, or transgender women; were between the ages of 16 and 49; had at least 2 male sexual partners in the last 3 months; were not currently participating in a HIV vaccine or PrEP clinical trial; were not on PrEP at the time of enrollment; lived in the US or its territories; self-reported

HIV status as HIV-negative or unknown; and met at least one of the following additional criteria: diagnosed with syphilis, or rectal gonorrhea/chlamydia in the last 12 months, shared injection drug use needles in the past 12 months, self-reported more than one receptive CAS acts with a man in the past 3 months, self-reported greater than two insertive CAS acts with a man in the past 3 months, took post-exposure prophylaxis (PEP) in the past 12 months, and/or self-reported methamphetamine use in the past 3 months. Notably, the recruitment strategies were targeted to reach GBM, but our enrollment criteria did not exclude transgender men and transgender women who otherwise met study criteria. Nonetheless, transgender men and women were excluded in the present analysis because they are faced with unique psychosocial stressors and buffers that may differentiate them from GBM.22

Participants were directed to a secured informed consent and enrollment survey webpage that presented questions about demographic characteristics, sexual behavior, and substance use. Eligible participants who consented and completed the enrollment survey

(Appendix A) were later sent a link (email and text) to complete a secondary survey 55

(Appendix B) that collected additional behavioral data. Participants completing this secondary survey received a $15 gift card by email. Participants who completed the second were subsequently mailed an OraSure HIV-1 oral specimen collection device. Using a self- addressed and stamped envelope, participants mailed oral fluid samples to the study lab for analysis. Participants who returned a sample to the lab received another $15 gift card by e- mail. A full description of the recruitment methods and of the Together 5,000 cohort have been previously published.23,24

Study measures

The outcome of interest in this study is HIV risk; measured using the MSM Risk

Index25,26, a tool for systematically determining risk for HIV acquisition with a sensitivity of

84% and a specificity of 45% for predicting incident HIV infection in the next six months.25,26 The MSM-Risk index is a validated screening tool for calculating HIV risk among MSM that incorporates age, number of male partners, number of HIV-positive male partners, frequency of condomless receptive anal sex, frequency of condomless insertive anal sex with HIV-positive partners and use of amyl nitrate (“poppers”) and methamphetamines.25,26 Risk scores ranged from 0 to 45; higher scores point towards higher

HIV risk.25,26

The predictor under investigation is resilience; measured using the Connor-Davidson

Resilience Scale (CD-RISC-10), a 10-item Likert scale that measures a person’s ability to cope with adversity, and may promote better health outcomes and serve as a protective factor against HIV.13,17 Items included: “I am able to adapt to change”, “I tend to bounce back after illness or hardship”, and “I think of myself as a strong person”. Study participants were asked to rate their agreement with each item on a 5-point scale ranging from “not true at all” to

“true all the time”. Answers were coded 0 to 4 and summed to obtain total CD-RISC score, 56 ranging from 0 to 40, with higher scores depicting higher resilience. The Cronbach’s alpha for the CD-RISC in the current sample was 0.87, suggesting high internal reliability.27

Other variables of interest for the current study included demographic characteristics, sexual heath factors related to HIV risk and HIV testing, and other psychosocial factors, such as internalized homophobia and social support. Demographic characteristics measured in the enrollment survey included age, race/ethnicity, sexual identity (e.g., gay, bisexual), employment status, highest level of education, annual income, health insurance status, and having performed sex work in the past 3 months. Sexual health variables included HIV testing frequency, prior use of PrEP, insurance status, and STI diagnosis in the past year. internalized homophobia (IH) assessed using the internalized homophobia 14-item scale. The

IH scale answers ranged from Strongly disagree (1) to Strongly agree (4), with higher scores indicating higher internalization of homophobia. Perceived social support was scored using the 12-item Multidimensional Scale of Perceived Social Support.28 The perceived social support scale answers ranged from Very strongly disagree (1) to Very strongly agree (6), with higher scores indicating higher perceived support. The Cronbach’s alpha for the IHP and perceived social support scales in the current sample were 0.88 and 0.94, respectively, suggesting high internal reliability.27

Analysis

Our objective was to explore the association between resilience and HIV risk among our sample of MSM. Descriptive statistics were used to describe the sample (n = 6,118).

Socio-demographic differences in mean resilience were calculated using ANOVA. Bivariate associations between resilience and HIV risk, and other psychosocial variables were determined using the Pearson’s correlation (r). Finally, we assessed the association between resilience and HIV risk using multiple linear regression, adjusted for age, race, sexuality, income employment status, current health insurance status, HIV testing frequency, PrEP 57 status, STD diagnosis, IH and Social support. Statistical significance was set at the 0.05 level. All analyses were conducted using SPSS 26.

RESULTS

Descriptive statistics for socio-demographic characteristics are presented in Table 3.1.

Participants (n = 6,118) had a mean age of 30.6 years (SD = 7.9). Participants identified as white (52.2%), Hispanic/Latino (24.6%), Black (11%), multiracial (8.7%) and Asian/Pacific

Islander (3.5%). The majority identified as Gay, Queer or Homosexual (85%) and did not have a main sexual partner (73.3%). Nearly two-thirds (62.6%) reported being fully employed, 45% reported having some college education, 41.7% reported an annual income between $20,000 and $49,999, and 48.4% lived in southern states of the U.S. A quarter

(27.4%) reported that they did not have/were unsure if they had health insurance, 14.6% reported engaging in transactional sex in the past 3 months, and 14.2% reported prior, but not current, use of PrEP. Finally, over half self-reported as HIV-negative (58.2%), one-quarter

(26.3%) reported that their last HIV test was more than a year ago.

The mean resilience score in this sample was 28.97 (SD = 6.07, Median = 29, Inter- quartile range = 25, 33). Socio-demographic differences in mean resilience are also presented in Table 3.1. There was a significantly higher mean resilience (p < 0.001) among those identifying as black, with higher education, having full-time employment, having an annual income of $50,000, having health insurance, being HIV-negative, and having tested in the last year. Moreover, there was a significantly lower mean resilience (p < 0.001) among those engaging in transactional sex in the last 12 months and among those having been diagnosed with an STD in the last 12 months.

Table 3.2 displays the correlation matrix between the predictor, outcome and variables of interest. The mean score on the IH and perceived social support scales were 58

26.65 (SD = 7.9) and 50.45 (SD = 14.02), respectively. Although weak, there was a statistically significant negative correlation between resilience and IH (r = −0.16, p < 0.001).

We found a moderate and statistically significant positive correlation between resilience and social support (r = 0.30, p < 0.001). Nonetheless, there was no statistically significant relationship between resilience and our measure of HIV risk (MSM risk Index, r = -0.024).

There was a statistically significant negative correlation between IH and social support (r = -

0.23, p < 0.001). Moreover, there were weak but significant negative correlations between IH and HIV risk (r = -0.04, p <0.01), and between social support and HIV risk (r = -0.09, p <

0.001).

Table 3.3 displays the results of the adjusted multiple linear regression between resilience and three models of HIV risk; Model 1 using the composite MSM risk Index measure, Model 2 using only a measure of condomless receptive anal sex, and Model 3 using a measure of condomless insertive anal sex. In model 1, there was no statistically significant association between resilience and HIV risk (β = 0.02 [95% CI: 0.02, 0.06]) after adjusting for age, race/ethnicity, sexual identity, education, income, employment, insurance status, HIV testing frequency, PrEP status, Internalized homophobia and perceived social support. In model 2, there was a statistically significant association between resilience and condomless receptive anal sex (β = -0.10 [95% CI: -0.17, -0.04], p < 0.001). Finally, in model 3, there was no statistically significant association between resilience and condomless insertive anal sex (β = -0.01 [95% CI: -0.05, 0.03]).

DISCUSSION

In this study of geographically and racially diverse GBM, we did not find a significant association between resilience and our composite measure of HIV risk. We did, on the other hand, find a statistically significant negative association between resilience and reported 59 number of condomless receptive anal sex acts with male partners. We found higher resilience scores among younger participants, those identifying as black, with higher levels of education and income, and among those employed full-time. We also found statistically significant association between mean resilience and several health seeking behaviors such as testing for

HIV in the last year and having health insurance. The average resilience score in our sample was lower than the average scores in U.S. community samples29-31 but slightly higher than those from sexual minority samples using the same resilience measure (CD-Risc-10).32,33

To our knowledge, this study is one of few studies assessing the relationship between resilience and HIV risk in a national sample of GBM. Other studies focusing on resilience frameworks in this population have found conflicting evidence between reduced HIV risk behaviors and resilience. McNair et al. in their 2017 study of resilience and HIV risk behaviors among black GBM, found that participants with higher resilience scores had a lower prevalence of condomless anal sex with main and casual sexual partners.17 In a 2016 study of GBM using sexual networking websites, White Hughto et al. found that HIV-risk resilience was common and may manifest in safer sex intentions, such as sero-sorting and/or insisting on condom use.34 Meanwhile, Dawson et al.’s study on black GBM found no association between greater resilience and fewer instances of condomless anal sex.35

Our findings do not confirm the proposed protective benefit of resilience on HIV risk as measured by the MSM risk index.

There are several factors explaining why our findings differ from those of the literature. First, the conceptualization of resilience as a unidimensional construct may be inadequate for this population. The Connor-Davidson Resilience scale only measures adaptability and coping, and although this is an acceptable construct to measure, resilience may be better conceptualized as a multi-dimensional factor, vis-à-vis syndemics. For instance, Wilson et al. conceptualized resilience as self-efficacy, hardiness/adaptive coping, 60 and social support, and found that self-efficacy and hardiness/adaptive coping may play a more important role in protecting young GBM from risks compared to social support.36 They found resilience to be associated with better psychological functioning factors (i.e., attachment, internalized homophobia, familism) that contribute to lower HIV risk among

GBM.36 In their study of Tanzanian GBM, Adeboye et al. conceptualized resilience as structural and functional social support, age of sexual debut and social visibility, and were found to directly associated with lower odds of contracting HIV infection.37 Particularly, they conclude that participants with high social visibility had lower odds of HIV infection, even under the effect of multiple syndemics.37 Moreover, Dacus re-conceptualized resilience theory for black GBM as the intersection of self-agency, social support, and behaviors of avoidance of sero-conversion.38

Given this, our study may have been limited in its ability to fully measure resilience and could have accounted for our non-significant findings. Future research may benefit from assessing HIV risk through the presence of resilience-promoting (e.g., social support, hardiness and coping, etc.) or resilience-diminishing (e.g., internalized homophobia) factors.

For example, we found a negative association between social support and HIV risk, and it may be more reliable to assess the presence of factors associated with resilience (e.g., social support) and look at the association between the numbers of factors present and HIV risk.

Thus, offering a more comprehensive assessment of resilience.

Second, although the MSM risk index is a validated tool used to determine risk, it may have oversimplified men’s risk. The scoring schema for this tool requires assigning a number for each risk category that the participant has displayed. For instance, if a participant has engaged in condomless receptive anal sex more than once in the last six months, they are assigned a 10, regardless if they only had one occasion or five.26 As such, any variability in risk may have been masked by the grouping of HIV risk factors into one score. Our findings 61 reflect this issue; when looking at the relationship between resilience and condomless receptive anal sex occasions (specific behavior), we found a significant negative association.

Thus, it may be more appropriate to assess these relationships through the specific risk behaviors than a composite risk profile.

Although our main findings showed no significant association, there was a significant positive association between resiliency and social support, and negative association between resiliency and internalized homophobia. Formative research on the role of social support has

Highlighted the need for strategies that enhance social support networks and address the social-psychological, emotional, and interpersonal factors, such as internalized and perceived homophobia that contribute to HIV risk.12,35,39 Future research is pivotal towards understanding how these interpersonal factors affect risk behaviors. Our findings highlight a need to identify and promote health-enhancing positive factors in HIV intervention work.

Limitations

Our findings should be interpreted through careful consideration of its limitations.

First, the cross-sectional design of this study prevents making any conclusive causal claims about the temporality and directionality of the relationships we observed. This study was not designed to prove causation, only to correlate, and therefore causal inferences should be interpreted with caution.27 Although this fully online study allowed for increased geographical reach, it also increased the potential for fraudulent participants.40,41 Further, this study relied exclusively on data from self-reported surveys and, while measures to increase the validity of the data were put into place, social desirability and recall bias may have affected the study findings.42 Further, the study population was recruited via sexual networking apps and represented a sample of those at highest risk for HIV, who are not on

PrEP at enrollment. Given the non-probability sampling, we are unable to generalize these results to other GBM. Our findings are limited to a sample of HIV-negative cis-gender GBM 62 and we cannot rule out that there may be unique differences in resilience profiles for individuals who are gender non-conforming and those who are HIV-positive. In fact, future research could benefit from exploring the role of resilience among HIV-positive individuals and in identifying resilience enhancing factors.

The persistent racial disparities in HIV infection warrants the need to collect and examine more data beyond behavioral factors. Particularly, there is a need to understand pervasive social influences and structural determinants of HIV risk among minority GBM.

Our findings provide alternative prospects to pursue regarding the effects of social factors of racial disparities in HIV risk among GBM. 63

References

1. National Center for HIV/AIDS VH, STD, and TB Prevention. HIV Incidence: Estimated Annual Infections in the U.S., 2008-2014: CDC;2017. 2. Centers for Disease Control and Prevention. Today's HIV Epidemic2016. 3. Centers for Disease Control and Prevention. Estimated HIV incidence and prevalence in the United States, 2010–20152018. 4. Centers for Disease Control and Prevention. Monitoring selected national HIV prevention and care objectives by using HIV surveillance data—United States and 6 dependent areas, 20162018. 5. Centers for Disease Control and Prevention (CDC). HIV and AIDS in the United States by Geographic Distribution2015. 6. Centers for Disease Control and Prevention (CDC). HIV in the United States by Region. 2017. 7. Chan M. Ten years in public health, 2007–2017. Geneva2017. 8. Moore RD. Epidemiology of HIV infection in the United States: implications for linkage to care. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. Jan 15 2011;52 Suppl 2:S208-213. 9. Centers for Disease Control and Prevention (CDC). Vital Signs: HIV Prevention Through Care and Treatment - United States. MMWR: Morbidity & Mortality Weekly Report. 2011;60:1618-1623. 10. McCree D, Jones K, Oleary A. African Americans and HIV/AIDS: Understanding and addressing the epidemic2010. 11. Meyer IH. Identity, Stress, and Resilience in Lesbians, Gay Men, and Bisexuals of Color. The Counseling psychologist. 2010;38(3):10.1177/0011000009351601. 12. Herrick AL, Stall R, Chmiel JS, et al. It gets better: resolution of internalized homophobia over time and associations with positive health outcomes among MSM. AIDS and behavior. May 2013;17(4):1423-1430. 13. Gwadz MV, Clatts MC, Yi H, Leonard NR, Goldsamt L, Lankenau S. Resilience Among Young Men Who Have Sex With Men in New York City. Sexuality research & social policy : journal of NSRC : SR & SP. Mar 2006;3(1):13-21. 14. Kurtz SP, Buttram ME, Surratt HL, Stall RD. Resilience, syndemic factors, and serosorting behaviors among HIV-positive and HIV-negative substance-using MSM. AIDS education and prevention : official publication of the International Society for AIDS Education. Jun 2012;24(3):193-205. 15. Mustanski B, Garofalo R, Herrick A, Donenberg G. Psychosocial health problems increase risk for HIV among urban young men who have sex with men: preliminary evidence of a syndemic in need of attention. Annals of behavioral medicine : a publication of the Society of Behavioral Medicine. Aug 2007;34(1):37-45. 64

16. Scott HM, Pollack L, Rebchook GM, Huebner DM, Peterson J, Kegeles SM. Peer social support is associated with recent HIV testing among young black men who have sex with men. AIDS and behavior. May 2014;18(5):913-920. 17. McNair OS, Gipson JA, Denson D, Thompson DV, Sutton MY, Hickson DA. The Associations of Resilience and HIV Risk Behaviors Among Black Gay, Bisexual, Other Men Who Have Sex with Men (MSM) in the Deep South: The MARI Study. AIDS and behavior. May 01 2018;22(5):1679-1687. 18. 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 and behavior. Nov 2014;18(11):2080- 2088. 19. Herrick AL, Stall R, Goldhammer H, Egan JE, Mayer KH. Resilience as a Research Framework and as a Cornerstone of Prevention Research for Gay and Bisexual Men: Theory and Evidence. AIDS and behavior. 2014/01/01 2014;18(1):1-9. 20. Herrick AL, Lim SH, Wei C, et al. Resilience as an untapped resource in behavioral intervention design for gay men. AIDS and behavior. Apr 2011;15 Suppl 1:S25-29. 21. Herrick AL, Egan JE, Coulter RW, Friedman MR, Stall R. Raising sexual minority youths' health levels by incorporating resiliencies into health promotion efforts. Am J Public Health. Feb 2014;104(2):206-210. 22. Wansom T, Guadamuz TE, Vasan S. Transgender populations and HIV: unique risks, challenges and opportunities. J Virus Erad. Apr 1 2016;2(2):87-93. 23. 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 research protocols. Sep 17 2019;8(9):e13715. 24. Grov C, Westmoreland DA, Carneiro PB, et al. Recruiting vulnerable populations to participate in HIV prevention research: findings from the Together 5000 cohort study. Annals of epidemiology. 2019/07/01/ 2019;35:4-11. 25. Smith DK, Pals SL, Herbst JH, Shinde S, Carey JW. Development of a clinical screening index predictive of incident HIV infection among men who have sex with men in the United States. Journal of acquired immune deficiency syndromes (1999). Aug 1 2012;60(4):421-427. 26. Wilton J, Kain T, Fowler S, et al. Use of an HIV-risk screening tool to identify optimal candidates for PrEP scale-up among men who have sex with men in Toronto, Canada: disconnect between objective and subjective HIV risk. Journal of the International AIDS Society. 2016;19(1):20777. 27. Morabia A. A history of epidemiologic methods and concepts: Birkhäuser; 2013. 28. Zimet GD, Dahlem NW, Zimet SG, Farley GK. The Multidimensional Scale of Perceived Social Support. Journal of Personality Assessment. 1988/03/01 1988;52(1):30-41. 29. Campbell-Sills L, Forde DR, Stein MB. Demographic and childhood environmental predictors of resilience in a community sample. J Psychiatr Res. Aug 2009;43(12):1007-1012. 65

30. Campbell-Sills L, Stein MB. Psychometric analysis and refinement of the Connor- davidson Resilience Scale (CD-RISC): Validation of a 10-item measure of resilience. J Trauma Stress. Dec 2007;20(6):1019-1028. 31. Arias González VB, Crespo Sierra MT, Arias Martínez B, Martínez-Molina A, Ponce FP. An in-depth psychometric analysis of the Connor-Davidson Resilience Scale: calibration with Rasch-Andrich model. Health and Quality of Life Outcomes. 2015/09/23 2015;13(1):154. 32. Rodriguez I. Internalized Heteronegativity & Resilience in Relation to the Health of Sexual Minorities of Color: Psychology, University of Rhode Island; 2016. 33. Lyons A, Heywood W. Collective resilience as a protective factor for the mental health and well-being of HIV-positive gay men. Psychology of Sexual Orientation and Gender Diversity. 2016;3(4):473-479. 34. White Hughto JM, Hidalgo AP, Bazzi AR, Reisner SL, Mimiaga MJ. Indicators of HIV-risk resilience among men who have sex with men: a content analysis of online profiles. Sexual health. Jun 2 2016. 35. Dawson EL, Mendoza MCB, Gaul Z, Jeffries Iv WL, Sutton MY, Wilson PA. Resilience, condom use self-efficacy, internalized homophobia, and condomless anal sex among black men who have sex with men, New York City. PLOS ONE. 2019;14(4):e0215455. 36. Wilson PA, Meyer IH, Antebi-Gruszka N, Boone MR, Cook SH, Cherenack EM. Profiles of Resilience and Psychosocial Outcomes among Young Black Gay and Bisexual Men. Am J Community Psychol. Mar 2016;57(1-2):144-157. 37. Adeboye A, Ross M, Wilkerson J, et al. Resilience Factors as a Buffer against the Effects of Syndemic Conditions on HIV Risk and Infection among Tanzanian MSM. Journal of Health Education Research & Development. 01/01 2017;05. 38. Dacus J-D. Strengths and Resiliencies of Black MSM in New York City Who Maintain HIV-Seronegativity [Dissertation]. CUNY Academic Works: Social Work, The Graduate Center; 2018. 39. Saleh LD, van den Berg JJ, Chambers CS, Operario D. Social support, psychological vulnerability, and HIV risk among African American men who have sex with men. Psychol Health. May 2016;31(5):549-564. 40. Doblecki-Lewis S, Butts S, Botero V, Klose K, Cardenas G, Feaster D. A Randomized Study of Passive versus Active PrEP Patient Navigation for a Heterogeneous Population at Risk for HIV in South Florida. Journal of the International Association of Providers of AIDS Care (JIAPAC). 2019;18:2325958219848848. 41. Blashill AJ, Brady JP, Rooney BM, et al. Syndemics and the PrEP Cascade: Results from a Sample of Young Latino Men Who Have Sex with Men. Archives of sexual behavior. Jan 2020;49(1):125-135. 42. Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plastic and reconstructive surgery. Aug 2010;126(2):619-625. 66 Table 3.1. Socio-demographic and health behavior characteristics of the Together 5,000 cohort by mean resilience, n = 6,118

Characteristic M SD Age 30.60 7.90 Resilience (CD-Risc) 28.97 6.07 Frequency % Mean CD-Risc ANOVA (F) p-val* Race/Ethnicity White 3191 52.2 28.9 9.60 < 0.001 Black 674 11.0 30.2 Latino 1505 24.6 28.8 Asian/Pacific Islander 217 3.5 27.8 Multiracial 531 8.7 29.0 Sexual Orientation Gay, Queer, Homosexual 5198 85.0 29.0 0.16 0.851 Bisexual 864 14.1 29.0 Other 56 0.9 28.6 Education < High school diploma 139 2.3 27.7 8.00 < 0.001 High school diploma or GED 869 14.2 28.2 Some college or technical school training 2752 45.0 29.1 College graduate + 2358 38.5 29.2 Employment Status Full-time (40 hours per week) 3831 62.6 29.5 30.78 < 0.001 Part-time (less than 40 hours per week) 785 12.8 28.2 Working- or full-time student 492 8.0 28.8 Unemployed/Other 1010 16.5 27.7 Annual Income Less than $20,000 2014 32.9 28.0 48.38 < 0.001 $20,000-$49,999 2554 41.7 29.2 $50,000+ 1550 25.3 29.9 Has a main partner Yes 1634 26.7 28.9 0.60 0.44 No 4484 73.3 29.0 Health Insurance Yes 4443 72.6 29.1 13.30 < 0.001 No/do not know 1675 27.4 28.5 Engaged in sex work (past 12 months) Yes 895 14.6 28.1 21.80 < 0.001 No 5223 85.4 29.1 Self-reported HIV Status HIV-negative 3559 58.2 29.5 59.71 < 0.001 67 I don't know; I am unsure 2559 41.8 28.3 Have you ever been tested for HIV? In the past 12 months 3746 61.2 29.3 10.64 < 0.001 More than a year ago 1612 26.3 28.5 Never 760 12.4 28.5 Prior PrEP use Yes 871 14.2 29.0 0.003 0.958 No 5247 85.8 29.0 Diagnosed with an STD in the last 12 Months Yes 1087 17.8 28.3 14.22 < 0.001 No 5031 82.2 29.1 Region Northeast 911 14.9 28.5 1.81 0.123 Midwest 887 14.5 29.1 South 2950 48.4 29.1 West 1323 21.7 29.1 Pacific, US Territories, Others 47 0.8 27.7

Table 3.2. Correlation Matrix between Psychosocial variables, Resilience and HIV Risk

Variables Mean SD 1 2 3 4 5 6

† † 1. Internalized Homophobia 26.65 7.90 - -0.23 -0.16 -0.03* -0.002 -0.04** † † 2. Social Support 50.45 14.02 - 0.30 -0.04** -0.03* -0.09 † 3. Resilience (CD-Risc) 28.97 6.07 - -0.06 0.003 -0.024

4. Condomless Receptive Anal Sex Acts with Male 4.20 8.00 - 0.27** 0.26† Partners in the last 3-momths 5. Condomless Insertive Anal Sex Acts with Male 4.30 7.90 - 0.31† Partners in the last 3-momths 6. MSM Risk Index 18.75 7.86 - *p < 0.05; **p < 0.01; †p < 0.001 69 Table 3.3. Multiple Linear Regression of HIV Risk and Resilience (CD-Risc)

Model 2: Condomless Receptive Anal Sex Model 3: Condomless Insertive Anal Sex Model 1: Composite Risk (MSM Risk Index) Acts with Male Partners in last 3-Months Acts with Male Partners in last 3-Months b SE 95% CI b SE 95% CI b SE 95% CI

Age -0.20** 0.02 (-0.23, -0.17) -.003 0.03 (-0.05, 0.05) .09† 0.02 (-0.05, 0.12) Race/Ethnicity White Ref - - Ref - - Ref - -

Black -1.87† 0.38 (-2.61, -1.13) -1.9 0.61 (-3.10, -0.70) -0.79 0.41 (1.58, 0.01) Latino -0.90** 0.28 (-1.44, -0.35) 0.42 0.45 (-0.47, 1.30) -0.11 0.30 (-0.70, 0.47)

Asian/Pacific Islander -1.76** 0.60 (-2.93, 0.59) -0.81 0.96 (-2.70, 1.10) -2.35† 0.64 (-3.60, -1.10) All Other Multi -0.43 0.41 (-1.23, 0.364) -0.56 0.66 (-1.80, 0.73) 0.72 0.44 (-0.14, 1.60) Sexual Identity Not Gay Ref - - Ref - - Ref - -

Gay 1.35† 0.34 (0.69, 2.02) 1.51** 0.55 (0.43, 2.60) -1.61† 0.37 (-2.33, -0.90) Education Less than College Ref - - Ref - - Ref - -

College Graduate -1.16† 0.24 (-1.63, -0.70) -0.33 0.39 (-1.10, 0.43) -0.15 0.26 (0.65, 0.36) Income More than 20,000 a year Ref - - Ref - - Ref - - Less than 20,000 a year .08 0.28 (-0.48, 0.64) 0.06 0.46 (-0.84, 0.95) -0.21 0.30 (-0.80, 0.39) Employment Unemployed Ref - - Ref - - Ref - -

Employed -1.74† 0.33 (-2.40, -1.10) -2.27† 0.54 (-3.32, -1.22) -0.46 0.36 (-1.16, 0.24) 70 Insurance Status Uninsured Ref - - Ref - - Ref - -

Insured -1.77† 0.27 (-2.30, -1.25) -0.44 0.43 (-1.28, 0.40) -0.61* 0.29 (-1.17, -0.05) HIV Testing Frequency Less than every 3 months Ref - - Ref - - Ref - - At least every 3 months 0.59 0.32 (-0.41, 1.23) -0.86 0.52 (-1.90, 0.16) 0.44 0.35 (-0.24, 1.12) PrEP Status Never used PrEP Ref - - Ref - - Ref - -

Used PrEP previously 1.84† 0.30 (1.25, 2.42) 0.98* 0.48 (0.04, 1.92) 0.75** 0.32 (0.13, 1.40) STD Diagnosis More than a year ago Ref - - Ref - - Ref - -

In the last year 1.53† 0.28 (0.98, 2.10) 2.36† 0.45 (1.50, 3.25) 1.14† 0.30 (0.55, 1.73) Internalized Homophobia -0.05** 0.02 (-0.08,-0.02) -0.06* 0.03 (-0.10, -0.01) -0.01 0.02 (-0.05, 0.02)

Social Support -0.05† 0.01 (-0.06, -0.03) -0.02 0.01 (-0.04, -0.01) -0.01 0.01 (-0.03, 0.004)

Resilience (CD-Risc) 0.02 0.02 (0.02, 0.06) -0.10† 0.03 (-0.17, -0.04) -0.01 0.02 (-0.05, 0.03)

*p < 0.05; **p < 0.01; †p < 0.001

CHAPTER 4 – ENGAGEMENT IN CARE AMONG NEWLY DIAGNOSED HIV- POSITIVE GAY, BISEXUAL AND OTHER MEN WHO HAVE SEX WITH MEN IN THE UNITED STATES: RESULTS FROM THE TOGETHER 5,000 STUDY.

ABSTRACT

Background: Despite many efforts, one-quarter of HIV-positive gay, bisexual and other men who have sex with men (GBM) are not engaged in HIV care. Retention in HIV care improves health outcomes and reduces the risk of transmission. As such, it is necessary to understand factors that influence linkage and engagement in HIV care.

Methods: In 2018-2019, 50 GBM completed qualitative interviews 3-months after receiving an HIV-positive result while taking part of Together 5,000, an U.S. national cohort of men, transgender women and transgender men who have sex with men. Interviews explored the barriers and facilitators to engagement with HIV testing and care.

Results: Participants had a mean age of 31.7 years (SD = 8.0). Forty-eight percent were white, 16% were black, 28% were Latino, and 8% were mixed race. Almost half (46%) were uninsured and did not have a primary care provider (48%). The majority (94%) of participants reported being linked-to-care, while only 74.5% of those reported initiating ART. Thematic analysis identified 4 major themes related to participants’ engagement in care: 1) Reasons for HIV testing (e.g., HIV self-testing and expectation of positivity), 2) Linkage-to-care (e.g., appointment/logistic issues and social support as encouragement), 3) Barriers (e.g., financial burden, competing priorities and fear/stigma) and facilitators (e.g., financial assistance, patient- provider relationships, auxiliary support services and health agency) to engagement in HIV care, and 4) PrEP as a missed prevention opportunity.

Conclusion: Addressing policy-, social- and individual-level barriers could improve GBM’s engagement in HIV care. Further, capitalizing on GBM’s health agency through partnerships with local agencies and fostering better patient-provider relationships could optimize continuity of HIV care.

INTRODUCTION

HIV continues to be a pervasive public health issue in the United States (US).1,2 Gay,

Bisexual and other men who have sex with men (GBM) accounted for over two-thirds (27,000,

70%) of all new HIV diagnoses in 2017, thus warranting continued efforts for prevention and intervention.2-6 As such, officials across the US have adopted a concerted commitment towards

Ending the HIV Epidemic (EtE), with an established goal to reduce the number of new HIV infections through combination efforts, including treatment as prevention, Pre-exposure prophylaxis (PrEP), and HIV testing with timely linkage-to-care.7 Successful and prolonged engagement in HIV care, including antiretroviral therapy (ART), not only reduces forward HIV transmission and leads to improvements in morbidity and mortality associated with HIV/AIDS- related illnesses but also improves overall health and quality of life.8-15 Health policies, like the

HIV Continuum of care, can be effective tools for monitoring the progress of HIV prevention and intervention strategies in order to achieve the UNAIDS 90-90-90 goals to end the epidemic.16,17 Moreover, the HIV continuum of care underscores the importance of viewing HIV prevention as a dynamic event requiring ongoing engagement and retention for as long as the individual remains at risk.18 This paradigm shift allows for tracking and understanding missed prevention opportunities; while considerable progress has been made in detecting new HIV cases, difficulties remain in maximizing prevention for those at-risk and in streamlining linkage- to-care for those diagnosed with HIV, especially in hard-to-reach sexual minority populations.16,17,19,20

Particularly, the US is failing to meet viral suppression targets and there are large gaps in the HIV continuum of care for GBM. In 2015, the White House released its National HIV/AIDS

Strategy (NHAS) with a goal to ensure that 90% of all people living with HIV (PLHIV) are 73 retained in care and 80% of all PLHIV are virally suppressed by 2020.21 According to the CDC’s

2016 HIV Surveillance Report, 85% of PLHIV in the US have been diagnosed, 63% have been linked to care, 48% are retained in care, and 49% are virally suppressed.22 Further, they estimate that 5 in 6 (83%) GBM were diagnosed with HIV, 72% were linked to HIV care, 57% were retained in care, and 58% had a suppressed viral load. Studies have also reported racial and ethnic disparities in HIV treatment outcomes. Data from the National HIV Behavioral

Surveillance (NHBS) found that black GBM were faring significantly worse across all steps of the HIV treatment continuum compared to white and Latino GBM, even after controlling for other confounding variables.23,24 For instance, PrEP awareness, willingness, and uptake were significantly lower among racial/ethnic GBM despite their higher HIV incidences compared to white counterparts.25 Therefore, additional research is needed to better understand the barriers and facilitators to successful engagement in HIV care.

Existing research suggests that medical mistrust, stigma, and discrimination due to sexual orientation act as barriers to engagement in care.13,26-28 While these factors impede the adequate formation of a positive patient-provider relationship, which is pivotal for optimal engagement and retention in care, little is known regarding the factors that could facilitate prolonged engagement, especially among disenfranchised communities.11,29-31 Moreover, there are limited qualitative findings regarding where and why fall-outs occur for individuals in resource-limited geographic settings.10,12,29,32 GBM of color are a particularly vulnerable population warranting special attention due to increasing HIV prevalence rates and their susceptibility for fall-outs from care.33,34

This study explored how a sample of 50 recently HIV-diagnosed GBM from across the

US were linked to care and how they continue to be engaged in care through qualitative in-depth 74 interviews. Particular attention was given to the challenges participants faced with their linkage- to-care and initiation of ART. The goal of this study was to identify barriers and facilitators to timely linkage-to-care, as well as missed opportunities for HIV prevention and intervention.

METHODS

Cohort recruitment, enrollment, and surveys

This study used data collected as part of the Together 5000 study, a U.S. national, internet-based cohort study of cisgender men, transgender men, and transgender women who have sex with men in the US. The overall goal of the study was to identify modifiable individual and structural factors associated with HIV seroconversion and PrEP uptake. Enrollment began in

October 2017 using ads on men-for-men geosocial sexual networking phone applications and concluded in June 2018. Participants were eligible if they identified as cisgender men, transgender men, or transgender women; were between the ages of 16 and 49; had at least 2 male sexual partners in the last 3 months; were not currently participating in an HIV vaccine or PrEP clinical trial; were not on PrEP at the time of enrollment; lived in the US or its territories; self- reported their HIV status as HIV-negative or unknown; and met at least one of the following additional criteria: diagnosed with syphilis or rectal gonorrhea/chlamydia in the last 12 months, shared injection drug use needles in the past 12 months, self-reported more than one receptive

CAS acts with a man in the past 3 months, self-reported greater than two insertive CAS acts with a man in the past 3 months, took post-exposure prophylaxis (PEP) in the past 12 months, and/or self-reported methamphetamine use in the past 3 months. While the recruitment strategies were targeted to reach GBM, our enrollment criteria did not exclude transgender men and transgender women who otherwise met study criteria. Nonetheless, transgender men and women were not enrolled in this qualitative study because they experience unique patterns of engagement in HIV 75 care that are distinct to GBM. A full description of the recruitment methods and of the Together

5,000 cohort have been previously published.35,36

Participants completed the informed consent and enrollment survey through a secure webpage. Those eligible were later sent a link (email and text) to complete a secondary survey that collected additional behavioral data. Of those who completed the enrollment survey, 8,755 participants met eligibility criteria. These participants were invited to complete a baseline online survey via email. Of those, 6,267 (71.6%) completed the baseline survey and received a $15 incentive.35,36 Following completion of the survey, participants were mailed an OraSure HIV-1 specimen collection device for self-testing. After completion of the oral swab, participants were instructed to mail the specimen using a prepaid shipping envelope addressed to the New York

State Department of Health (Avioq HIV-1 Microelisa System). We successfully delivered 6,150

HIV test kits to participants, 5,065 of which were returned by the lab, and 195 identified as preliminary positives. Participants were not told in advance how they would be contacted to receive their results. HIV-negative results were sent to participants via email. Preliminary HIV-positive results were delivered to participants via phone. Delivery of HIV-positive results followed an in- house protocol that included provision of referrals to local healthcare resources to facilitate confirmatory testing and linkage-to-care. The protocol and findings of the delivery of positive results over the phone have been previously published.37 Among participants with a preliminary

HIV-positive result, 68% (n = 132/195) were successfully delivered to participants through telephone. Participants who did not receive their results were discreetly contacted multiple times via phone and email. Voicemails and emails from staff indicated our desire to speak with them but did not specify the reason or reference their test results. Participants who successfully received a test result by phone were eligible to participate in the qualitative in-depth interview 76

(IDI).

Qualitative In-depth Interviews

In total, 132 participants were invited to participate in the qualitative IDI. Invitations were sent by email approximately three months after delivery of their preliminary positive test results. Participants were invited to participate, and those who expressed interest were consented and enrolled in the study. MS, JLR and CG conducted one-on-one, semi-structured, audio- recorded phone interviews between March 2018 and January 2019. During data collection, interviewers took notes and met regularly to compare themes to determine saturation. Once the interviewers felt confident that data saturation had been achieved, we ceased recruiting additional participants. In total, 54 participants completed a qualitative interview; however, four interview recordings were lost due to audio file corruption, leaving an analytic sample of 50 interviews. Participants provided verbal informed consent, completed the 60-minute interview, and were given a $40 incentive for their time. These procedures were reviewed and approved by the Institutional Review Board at The City University of New York’s Graduate School of Public

Health and Health Policy.

Measures

Descriptive demographic and behavioral characteristics were derived from data collected as part of the enrollment and secondary survey. The IDIs were conducted via phone and followed a semi-structured interview guide (Appendix C). The interview guide was developed and based on the socio-ecological model in order to identify individual and structural factors to engagement in care. The qualitative interview explored participants’ experiences with linkage to and retention in HIV care, initiation of ART, as well as any barriers and facilitators to their engagement with

HIV testing and care. Further, participants were asked about their recent history of HIV/STI 77 testing and their knowledge of PrEP and PEP prior to their diagnosis. Participants were also asked to provide feedback about their experience receiving a preliminary HIV-positive result by phone, along with any concerns they had about that process. In this paper, we present data on participants’ engagement with HIV testing and care.

Data Analysis

Recordings were transcribed verbatim and transcripts were verified against audio recordings to ensure quality control. The conceptual framework for this analysis was rooted in the socio-ecological model (SEM) which allowed us to explore the complex interplay of multi- level factors influencing engagement in HIV care.38 Further, an inductive, thematic approach was used to analyze participants’ experiences in HIV Care.39 The first author performed an initial close read of 20% of the transcripts, during which initial codes were identified inductively and categorized thematically.40 The first author (JLR) coded all transcripts, and the second author

(CL) independently reviewed the codebook containing coded excerpts from transcripts, highlighting content and noting any overlap or discrepancies between the excerpts and their codes. The first author also reviewed coded transcriptions for overlap and discrepancies.

Throughout the coding process, the first and second author adjusted the codebook to reflect emergent data from the transcripts. Any discrepancies were discussed with the coding team until consensus over the application of each code was reached.

RESULTS

Descriptive statistics for socio-demographic characteristics are presented in Table 4.1.

Participants (n = 50) had a mean age of 31.7 years (SD = 8.0). Forty-eight percent of participants were white (n = 24), 16% were black (n = 8), 28% were Latino (n = 14), and 8% were mixed race (n = 4). All participants identified as cisgender male with most (94%, n = 47) identifying as 78 gay, queer, or homosexual and a minority as bisexual (6%, n = 3). The majority reported having some college education (58%, n = 29) or a college degree (28%, n = 14). About half reported working full-time (54%, n = 27) and an annual income of less than $20,000 USD (44%, n = 22).

At baseline, about half of participants (46%) were uninsured and did not have a primary care provider (48%). Further, almost two-thirds (62%, n = 31) lived in southern states of the US.

Thematic analysis identified four themes and several sub-themes related to participants’ engagement in care: 1) Reasons for HIV testing, 2) Linkage-to-care, 3) Barriers and facilitators to engagement in HIV care, and 4) PrEP as a missed prevention opportunity. Exemplary quotes accompany each theme.

Reasons for HIV testing

Thirty-four percent of participants reported testing for HIV within a year prior to enrollment, 52% more than a year prior, and 14% said they had never tested for HIV. Seventy- two percent of participants self-reported being unsure of their HIV status at the time of enrollment. During IDIs, participants detailed their reasons for testing through the study. Two salient reasons emerged from their accounts:

Increased access through HIV self-testing

Many of the participants noted that they joined the study for the ability to test for HIV in the comfort and privacy of their homes. Most expressed not having tested in a significant amount of time and reported that the study allowed them to test without having to take time off to visit a clinic or a doctor. Some participants preferred this method because they had limited access to testing sites or local clinics were a significant distance from their home. 79

I felt like it was a whole lot better because like I didn't have to, you know to go be around anyone really. I just do it in the comfort of my home, send it off, and then you gonna get the results over the phone and I knew you can't do that, well I mean, I could, usually you have to go in to do that, but I didn't have to come in for the results its all over the phone. So that's, you know, I do like that a whole lot more, you know just be in the comfort of my home and it's either a phone call or I call in to get results. (28 years, black, Mississippi) “I think that what you all are doing is really cool. I think that, you know, doing HIV tests like you all are doing, giving them to people whose thinking, you know, people who might not, maybe wouldn't, wouldn't want to go to an HIV clinic.” (28 years, white, Louisiana) “I live on an island so there’s only one hospital I could go to. The reason why I got a mailed test from you guys is because I was scrolling Facebook, saw the ad, and it had been a while since I had gotten tested… so at the time I didn’t have health insurance so I couldn’t go to the clinic here so that’s why I got the test. It had been a long time, maybe a year that I had been tested prior to that so it was definitely time.” (30 years, multiracial, California) “Part of what was interesting about this study was, I was thinking of going on PrEP. Because here we do testing before you get on PrEP. So I was like well let's just do it. And I really don't wanna walk into a clinic... I don't like going to the doctors offices period.” (28 years, black, Hawaii)

Expectation of Positivity

Another widely cited reason for seeking testing through our study was that participants believed they were HIV-positive but had no confirmation of their status. Many disclosed significant sexual risks over the past year and reported feeling that they were expecting a positive diagnosis at any point. Participants noted that the study afforded them the opportunity to get tested at home on their own time.

“Another reason I was looking at the study was not just out of curiosity, because I actually hooked up with a guy who I then found out was positive. I was much more worried than I thought, so I had a feeling. Uh, I, I had an, it was just weird. I had a feeling, um, that something had changed. That there was a possibility, a higher, uh, possibility suddenly.” (47 years, white, Connecticut) “Most definitely but um, there was always something in the back of my mind. That it would be nice to know. It would be nice to know.” (27 years, white, Nevada)

“But the previous, the year prior to that I did find out that you know there was two people that I had intercourse with that were positive, you know granted I didn’t ask but they did divulge either. Yes, that’s why- that’s why I sent for the test from you guys.” (30 years, multiracial, California) “I kind of had a feeling before your all’s test or whatever, it’s like I figured that now okay let’s figure out now how to deal with it. Just my past, very, not necessarily promiscuous but doing what I had to do to you know survive.” (31 years, white, Alabama)

Linkage-to-care

At the time of the IDI, participants had received their preliminary HIV diagnosis an average of 4 months prior (Range [3, 7]). The majority (94%, n = 47) of participants reported being linked-to-care and had had their HIV diagnosis confirmed by a healthcare provider, while only three-quarters (74.5%, n = 35) of those reported initiating ART. Among those who had not sought care, two avoided making an appointment out of fear of their results and being confronted with the reality of their positivity, and one participant reported many competing priorities like moving, school, and loss of employment.

“I had not really wanted to see that positive test result on paper. Just the reality of it. Ignore it, it goes away.” (44 years, white, Alabama) “Uh, I have not yet. I'm waiting on that. Um, mostly I'd say due to fear.” (29 years, white, Texas) “No, not yet. It's a lot of trouble since then and I'm moving, school, I'm losing my job. So I really just, there's just been a lot going on but I just really haven't been able to.” (28 years, black, Mississippi) Thematic analysis of the data resulted in two salient themes related to linkage to care: issues with appointment scheduling or logistics and social support as encouragement to linkage.

Issues with Appointment Scheduling or Logistics

Although the majority of those in care reported little issues once they had been linked, most expressed difficulties in scheduling their initial appointments, being referred to places 81 outside their county, and only being able to reserve appointments that were scheduled weeks or months after their initial call.

“I called them to set up the appointment, they said that I had to go to the one in the county that I was living in, and so then I called them but they didn't have any appointments because they only do testing on Tuesdays. So they referred me to a different clinic in a different county, and they got me in the same day to do the testing, confirmed everything, and signed me up with one of their doctors to start treatment” (26 years, white, California) “I then called [a doctor that was recommended] and then scheduled an appointment to be seen with that doctor. That took about, maybe two months. Yeah, before I got to be seen by the doctor, the infectious disease doctor.” (35 years, Latino, Texas) “Yeah, it took me a while ‘cause by the time like I had set up an appointment with my doctor, they said that the soonest would have been in about three to four weeks from the day. Um so I did end up going, and I did actually… you know make it to the appointment to get the confirmatory testing and everything, but it just took a while but I did actually go ahead and go through with that.” (24 years, white, California)

Social Support as Encouragement to Linkage

Some participants pointed to family and friends as sources of not only emotional but instrumental support after receiving their diagnosis. They articulated that their support system often offered words of solace during those difficult times, encouraged them to seek care, and at times, took them directly to a health clinic to get confirmatory testing.

“Um, I had somebody that was already, uh, with them, that's a friend of mine… Um, pretty much is just like, "Okay, I need to go get everything taken care of." And he was like, "All right, well, I'll go ahead and make a call, get you an appointment to be seen with the caseworker and get your ... get everything going."” (35 years, white, Texas) “My aunt actually took me to the doctor. Then it came out positive. I was so scared. I was scared at first. I thought my life's going to end. But that afternoon I started talking with the counselors who told me about. Everything was good.” (22 years, black, Florida) “I do have a support team, and I was just like my support team they were just like, "Regardless of whatever happens, whatever you go through, we're still going to be here for you." So it was like, they kinda helped motivate and pushed me a little bit, pushed me 82

towards going, 'cause I was, honestly I was really nervous about it, and I didn't think I was gonna go.” (27 years, black, Georgia)

Barriers to Engagement in HIV Care

Financial Burden

Participants articulated finances as a major barrier to sustained engagement in HIV care.

Participants who did not have insurance were forced to decide whether to hold off attending appointments or initiate ART and risk being billed for it later. In fact, participants often cited feeling uneasy regarding their lack of control over being able to pay for their care as well as all of the bureaucracy related to obtaining public assistance.

“When they told me that, that it was gonna be a little bit expensive, I was like, okay, but I don't have like a really good job, so, basically, you have to have a- You have to be rich to have your medication, that was my first thought. But I seen, I mean, I, I had to find a way.” (29 years, Latino, California) “Two months [to get on ART]. I was kind of like – until I decided [to take it] the doctor recommended like just try right away. I didn’t have any income I didn’t have any – I think other than that my health was fine so that was my reason behind not getting on it immediately.” (40 years, Latino, Texas) “They said that I had to like go through – cause I – you know I’m a college student. I don’t have any money. So they got me, like I had to send off like a whole bunch of paperwork saying that like I don’t have income to pay for this medicine. And then, they said it would take like 6 weeks and that was like in May that they got me to like come back and do that. You know like that’s been the most difficult part is knowing that like I don’t have the medicine right now. Knowing that like it’s like attacking my body and then having to go fill out all these papers to like prove that I’m like poor enough you know. Like it’s, the process just takes so long that you just give up half way through you know.” (22 years, Latino, Texas) “What really got to me or made it difficult for me was my finance. I didn’t have the money to go see a doctor. I didn’t have the funds to actually pay for medication. And, and that scared me. That really scared me. In the sense that, what if I really do need medication and I’m to a point that I need medication now and I can’t afford it?” (29 years, Latino, Florida) 83

Competing Priorities

The majority of participants cited a diverse array of social issues that they had to prioritize over their medical appointments. Specifically, several participants reported periods of unstable housing, which resulted in delays initiating ART or attending appointments.

“I’m actually kind of homeless, my family is kind of there for me, I mean they’re there for me as much as they can be. I haven’t started medication yet, but I have met with my doctor and we’ve been talking about it and I should actually be starting medication for it probably within the next two, three weeks. By the time I get everything situated on my end.” (24 years, white, California)

Others reported that their work or school schedules conflicted with appointments, often feeling a need to choose one over the other. In most cases, they did not attend their appointments and rescheduled them for later times, but for some this resulted in delays to receiving care.

“Um, I think so. He's been trying to meet with me, but I just work a lot and don't really have time for it so he's always trying to speak with me. So I haven’t been able to see them again. I actually had an appointment yesterday, but unfortunately I wasn't able to make it.” (25 years, Latino, New York) “I would say the only thing that was inconvenient was because I had school and most of these doctor's offices or appointments in clinic are open, um, you know, when I get out of school and won’t be open when I could have a school. So I’ve had to take a lot of time at a school.” (18 years, black, Texas) A few participants cited moving as a reason for falling out of care. Participants expressed that their move resulted in concerns over how to re-engage in care, particularly that they did not know where to go and had little time to search for a provider.

“My priorities were just not there. Which I completely regret, but they weren't there at the time. I just opened a business. I just moved. And so, I just had a lot going on and the last thing I had time to do was going to do that.” (29 years, multiracial, Pennsylvania) “I did not have health insurance. I just recently moved from another city. I left my job. I wasn’t feeling good, but I really thought a lot of it was just my job, that I was just really 84

that unhappy and stressed out but… but it wasn’t [getting care].” (39 years, white, Texas) “One of my big concerns when I first found out was just because, like, being in [different city] is just like... I didn't really have the healthcare I have here. And I was worried about getting the medication.” (27 years, Latino, New York)

Fear and Stigma

Some participants expressed feelings of fear and anxiety over visiting their doctors or clinics.

Particularly, some participants were concerned with being recognized and outed for their status and sexuality. Others were concerned about societal stigma for being HIV-positive. Some articulated that a fear of their diagnosis contributed to their delay in getting engaged in care.

“Well, I just have this fear of going to the doctors. So, usually anytime before even, but now it's like even worse. It takes me maybe three appointments before I actually show up. Because I just get such anxiety like the week before and then it just builds and builds and builds. 'Cause like I'm just waiting for them to tell me the next thing I'm dying from.” (29 years, multiracial, Pennsylvania) “Sexuality, for people who are gay, is already such a negative connotation behind it that's there a constant fear. And so nobody runs for help, at least not really openly, especially not where I come from. So, that's one thing within itself.” (25 years, Latino, North Carolina) “So I told myself, "Oh I'll be fine. I'll just, I'll just give myself a little time to think about it, and I'll see where I go from there." That was probably about maybe two months ago? I was just very stupid, I convinced myself that I'll be fine, I'll just let, I'll just let time run its course, and I'll just see what happens. Me thinkin' that way was 'cause I was afraid. Everything was kinda like hittin' me all at once. And then I still have to work, and I had to think about all these other things, it was just, it was just too much. (23 years, black, Texas) “My thoughts were well what if I ran into somebody that I know? It’s not that I don’t want to go but what if I’m just scared or chicken out? Once I got in, it was also just a little nerve wracking. You know to figure out what was going to happen to me then. How bad I was and how bad the situation was going to be or is.” (29 years, Latino, Florida)

Facilitators to Engagement in HIV Care

Financial Assistance

At the time of diagnosis, participants expressed concerns over their ability to pay for HIV care, with many citing financial hardships or lack of insurance. Similarly, participants widely cited financial assistance, either through government sponsored health insurance, drug assistance programs, or co-pay assistance programs, as the main reason they initiated ART and were able to afford care. In turn, some reported feeling relieved that clinic staff helped sign them up for financial assistance during their medical appointments.

“They have a program, the state does, for people that aren’t working that … you get insurance and it’s good for as long as you’re not working. They pay for everything, doctor visits, they pay for one medication a month for like antibiotics stuff like that. It’s a separate program than what is paying for my Genvoya. That, I got a letter from the actual manufacturer saying that because of the situation I’m in, they will not charge me for it.” (39 years, white, Texas) “They signed me up while I was there. Gave me the information to go online to finish signing up, but basically had done all the work for me. They made sure that even my copay is paid. I don't pay a dime and then they contact me every month just to verify my address and make sure that I'm not running out of pills earlier.” (47 years, white, Connecticut) “its called the Ryan White Program here. And luckily enough, the clinic that I go to, they accept and they actually got me enrolled in it and it covered all. ‘Cause you'd have $60 copay with my insurance from work and it covered all that even that copay and then any other things like dealing with care. So, even like my eyesight, like, you know, I'm visually impaired. Um, so I'm in a program, but I mean, just seeing the amount of money that these pills are, um, before the deductible and some like you know, it’s like $2100 for a 30 day supply and I'm on four medications that cost that each. So, its crazy, it's America. And you know the pills that we have from these companies are ridiculous, but I just, I mean, if someone didn't have insurance or the program like I did, there's no way you'd be able to afford these.” (30 years, white, North Carolina)

Kind, Comforting, and Thorough Providers 86

Participant interactions with HIV care providers had a significant impact on engagement in care.

Good communication, kindness, reassurances, and thoroughness in care were essential to consistent engagement, whereas not feeling respected, cared about, or listened to were reasons for disengagement. Participants also cited the importance of providers who were invested in their health and communicated well, preferring providers who thoroughly explained treatment options and addressed their concerns.

“The doctor is very, very nice. For anybody who's going through this, you don't-- obviously I didn't want to tell anybody, it's like something personal, and obviously at the very beginning, it's very hard, you need an outlet but you don't know who to talk to. And so, when I talked to the doctor I felt like, it's somebody that I could- obviously understands my situation. And I had all these questions and he was able to kind of answer them. And then put my ... put my mind at ease, not to be so stressed about it.” (35 years, Latino, Texas) “It was a little bit confusing trying to find the right clinic at the very beginning you know, when you're stressed out and everything. But, um, actually everyone I talked to was super nice, super helpful. Um, the clinic is probably the part that impressed me the most, because they were just like, on top of everything. Trying to make it as quick as possible.” (26 years, white, California) “I was very surprised by how understanding and how nice people were and how helpful it was. It was very kind of shocking. Because you go in you know with this preconceived notion how it might go or whatever. People were super nice, super helpful. They were informative and it made me feel kind of at ease about the whole situation.” (26 years, Latino, Texas)

Auxiliary Support Services

A salient aspect of participants’ narratives was the importance of having available, comprehensive auxiliary social services. Participants reported that these services acted as facilitators to engaging and, more importantly, being retained in care. In most cases, these services included: support groups, mental health services, transportation assistance, medication delivery, and housing assistance. 87

“They're going to try to help me with subsidized rent. Um, also they helped me with transportation, as far as getting back and forth to my appointments so I don't have the worry about stuff like that or if I can’t ever make an appointment. And they was willing to work with me like, just whatever help I needed to make sure I make my appointments so there's never a reason that I'm not able to get my medicine or appointments or stuff like that. And then, I like the fact that sometimes, 'cause I work a lot, so I was like, if I'm not able to pick up my medicine, they do deliver it to me in the mail so that works for me also. So when I get off, I still ... there's no excuse or no reason not to have my medicine.” (27 years, black, Georgia) “I got it pretty easy. I mean, if my car breaks down, they can, um, I can call them and they would actually come pick me up. Um, I have my ... the meds delivered to me by mail. It costs me $5. The clinic, themselves would pick you up [at home] if need be to make your appointment.” (35 years, white, Texas) “There can be some kinda, like, counseling center, that at least someone can go to and talk about things like this, 'cause sometimes people just wanna talk. Or, I know there's numbers and things that people give us, but sometimes people wanna talk to someone face to face. Don't wanna be over the phone, they wanna actually speak to someone, uh, face to face like we get that emotion and that feel from someone else.” (23 years, black, Texas)

Health Agency

Agency was discussed in terms of caring for oneself, and in taking responsibility for one’s own healthcare. Participants often spoke about being strong and doing what needed to be done to access care and remain healthy.

“I’m very anal about things. I have to have all of my paperwork. I have to have all materials ready. I have to have everything. I plan in advance everything… I’m very like the person that’s always ready. They [clinic staff] were kind of surprised and they were glad that I was the kind of person that I am. Because they told me in this case that people have gone through like a duration period in their life where they’re just constantly wallowing on it and like dwelling on it… I’m very like “assess the problem and fix it” and like you know get keep going about my life.” (26 years, Latino, Texas) “I mean I can make up a bunch of excuses, to tell myself but, I mean, there were definitely opportunities when it could have happened, but I just chose to not go through with it just because I wasn’t ready to hear it myself if it were actually a positive result. At some point becomes like a personal responsibility thing as to whether or not you’re going to follow, you know, advice on what people say or do, whether or not you gonna engage 88

and stuff. For me, you know, it was I knew about it, I knew that it was a possibility and I just kind of didn’t care at the time.” (29 years, Latino, Florida)

Participants also maintained that individuals had to find their own way to stay in care and that, ultimately, it was all about the individual’s mindset and own agency towards remaining healthy.

According to participants, if the drive or motivation was not there, then it was foreseeable that individuals would neither seek help nor care for their overall health. These participants often expressed a strong sense of self-reliance.

“It's because people have to take the initiative to wanna prevent things like this from happening… it's our responsibility to make sure that we're protecting ourselves like we need to. And if you don't take the initiative to do that, then there's really not much that you all can do. 'Cause once again, it takes two to tango. If you wanna protect yourself, you have to make sure that you're doin' that. You can't have somebody force you. So not, not necessarily much I don't think.” (23 years, black, Texas)

PrEP as a Missed Prevention Opportunity

Many participants considered starting PrEP prior to their HIV diagnosis but missed the opportunity to start due to a variety of reasons. A few participants considered initiating conversations with their providers about PrEP and their concerns about potential symptoms but either waited too long or had issues scheduling these appointments. Others were unsure where to get PrEP or who they could speak to about it. Two participants initiated PrEP conversations with providers; one provider discouraged the participant from initiating, saying that PrEP was unreliable, and the other admitted they didn’t know enough about PrEP to prescribe it, which frustrated the participant.

“I did think about getting it and you know, taking it as something that would be good for me. I was thinking about taking it, but like I said, I didn’t know where to even get it from. So I was not aware of you know where I would be able to get it, or how much it would be or anything like that.” (24 years, white, California) 89

“I checked it out a couple times out of curiosity online, and- and wasn't sure like, you know, it says how hard it is on your liver, or it was. I think it might have been improved by then. So, I just kind of weighed options, and stalled, and I feel like I waited too long, unfortunately, to get on that.” (47 years, white, Florida) “I did ask my doctor, my previous PCP, who had been my doctor for 15/16 years, I did ask him about going on PrEP. You know “hey I want to go on PrEP” and he gave me this deer in the headlights look like “what is that? I don’t know what that is.” And so like I explained to him. It’s truvada, it’s you know pre exposure prophylaxis, and he’s just like ‘you would need to go, go to the downstairs where they have the communicable diseases department where they might know. And I was just like I was like aggghh.” (43 years, multiracial, Hawaii)

DISCUSSION

Linking and retaining HIV-positive sexual minority men in primary care is critical from both a disease management and epidemiological perspective.8-10,13,19,41,42 Consistent engagement in HIV care plays a pivotal role in improving patient health outcomes as well as controlling incident cases by preventing onward HIV transmission by people with detectable viremia.43-45

Despite a robust and multi-faceted national strategy to end the HIV epidemic, there continues to be fall-outs in care, especially among GBM of color.46 Our findings highlight avenues for improvement in HIV testing and PrEP uptake among HIV-negative men. Moreover, we identified factors that impede swift linkage to and adequate engagement in HIV care, including financial burden, competing priorities, and fear and stigma. Our findings also point to factors that facilitate linkage and engagement, such as financial assistance, positive patient-provider interactions, auxiliary support services, and individual health agency.

Participants identified HIV self-testing (HIVST) as a facilitator to testing, highlighting the ability to test comfortably in the privacy of their homes as an appealing incentive. Studies have shown that HIVST is a highly acceptable alternative to venue-based testing for GBM, facilitates more frequent testing, and could lead to higher risk reduction.47-50 This is a particularly 90 salient finding given the EtE push towards identifying individuals who are unaware of their HIV infection. In fact, widespread adoption and distribution of HIVST kits may increase testing rates among those who are not typically engaged by testing centers but suspect they may be HIV- positive.51,52

Further, participants identified barriers and facilitators to successful engagement in HIV primary care that can guide best practices at not only the policy and organizational level but also at the individual levels. At the policy-level, men echoed the importance of sustaining health policies that help PLHIV cover medical costs and have been found to increase ART adherence as well as retention in care, such as the AIDS Drug Assistance Program (ADAP), the Ryan White

Program, and housing support programs.27,53-56 These findings point towards the need to help

HIV-positive clients have a stable environment where they can prioritize their own health. At the organizational level, participants emphasized how auxiliary support services, such as transportation coverage and mental health care, can make a difference in their retention in care.

Similar findings have been found by Remien et al. in their 2015 qualitative study of PLHIV,57 and by Rooks-Peck et al. in their 2018 meta-analysis study of mental health and retention in care.58

Participants also noted the desire to have medical providers who treated them with kindness and respect, listened to their concerns, were empathic to their diagnosis, and were communicative. Studies have shown that stigma within patient-provider relationships greatly contributes to the lack of trust that GBM have in the medical system; addressing this stigma can maximize patient retention and overall health.59-61 In fact, in their 2016 study on empathic communication, Flickinger et al. found that providers who actively exhibited empathy with their 91 patients promoted emotional connections and encouraged patients’ self-efficacy regarding medication adherence.62,63

Moreover, Many participants noted being interested in PrEP prior to their HIV diagnosis but were not prescribed it in time. Some described not receiving necessary counsel from their primary care doctor, with one participant being discouraged against PrEP use, which represented an unfortunate missed prevention opportunity. These findings are similar to those documented in studies of provider-related barriers to PrEP access.64-67 These provider-related factors suggest that organizations could benefit from more concerted efforts to provide resources to and arrange yearly capacity building for their providers to maximize skills surrounding communication, sexual history taking, and prescribing PrEP.68,69

Health agency, defined as an individual’s inner capacity to overcome obstacles related to their illness, was prevalent in our findings.70-73 At the individual level, men reiterated the need to find inner strength to take charge of their own health care. Many participants spoke about their care in terms of taking responsibility. They emphasized the need for an inner drive or mentality to remain healthy as a facilitator to accessing care. The research on health agency applied to HIV care is scant, making this finding particularly innovative. In their 2015 observational study of patient agency in healthcare settings, Hunter et al. described how patients often struggled to become knowledgeable about their condition and could fail at managing it; as such, the authors denoted health education as a way to enhance patient agency.70-73 Interestingly, in describing the sense of responsibility they felt towards their own health, participants in the present study often alluded to becoming more educated about HIV as a means to engaging in care. Many underscored needing to understand “it was not a death sentence” or that they “can lead normal healthy lives.” These findings suggest that engaging in patient education, either through clinic or 92 other behavioral interventions, may significantly impact patients’ engagement in care. Despite this individualistic approach, many participants simultaneously cited feeling a need to connect with other individuals who shared their experiences as a way of coping with HIV and maintaining themselves in care. In fact, many reported receiving instrumental and emotional support from friends and family when looking to confirm their HIV diagnosis. Establishing a good support system has been documented in several studies as a buffer for negative health consequences and contributes to improved medication adherence and overall care.27-29

Limitations

These findings helped generate insights, themes, and nuances regarding GBM’s experiences accessing health care. However, these findings are not generalizable to the general

GBM population in the US. Our recruitment strategy explicitly emphasized “free at-home HIV testing” as well as compensation for completing study assessments. Those with more severe HIV testing anxiety and those who may be unknowingly living with HIV may not have enrolled in our cohort. Nonetheless, our qualitative findings did highlight some HIV-related anxiety among participants. Further, we only interviewed participants to whom we could successfully deliver an

HIV test result over the phone; as such, their experiences may differ from those who tested HIV- positive but avoided our delivery efforts. In addition, our recruitment strategies led us to interview individuals who were more likely to be engaged in HIV care. Despite many themes being salient across our sample, our study would have benefitted from the perspectives of individuals who were not engaged in care. Further, we cannot rule out that social desirability bias may have influenced study findings, as participants may have softened or minimized negative experiences in care. Finally, these qualitative data are useful for generating theories and hypotheses but by no means signify any causal inferences. 93

Conclusions

As health officials seek strategies to curb the epidemic, they must pay close attention to engaging PLHIV in primary care. By individualizing care to meet the needs of GBM, the public health sector comes much closer to achieving sustainable, undetectable community viral loads.

Furthermore, by addressing the root causes behind an individual’s reasons for forestalling or disengaging from care, such as homelessness, poverty, and racial/ethnic disparities, we can move closer to reaching the UNAIDS 90-90-90 targets. Notably, half of our sample identified as people of color. Therefore, the present findings signify perspectives from individuals who are most disenfranchised in the HIV epidemic. Particularly, this vulnerable sector needs support at the individual, organizational, and policy level to overcome the obstacles that hinder their navigation of the healthcare system. Finally, the healthcare system must provide more resources to increase staff capacity building to combat the unique challenges faced by this population. 94

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17. UNAIDS. 90–90–90 - An ambitious treatment target to help end the AIDS epidemic2014. 18. Myers JE, Braunstein SL, Xia Q, et al. Redefining Prevention and Care: A Status-Neutral Approach to HIV. Open forum infectious diseases. Jun 2018;5(6):ofy097. 19. CDC. Vital Signs: HIV Prevention Through Care and Treatment - United States. MMWR: Morbidity & Mortality Weekly Report. 2011;60:1618-1623. 20. Dietz PM, Krueger AL, Wolitski RJ, et al. State HIV Prevention Progress Report2014. 21. Policy TWHNOoA. National HIV/AIDS Strategy for the United States: Updated to 20202015. 22. Centers for Disease Control and Prevention. Estimated HIV incidence and prevalence in the United States, 2010–2016. February 2019 2019. 23. Kelley CF, Rosenberg ES, O'Hara BM, et al. Measuring Population Transmission Risk for HIV: An Alternative Metric of Exposure Risk in Men Who Have Sex with Men (MSM) in the US. PLOS ONE. 2012;7(12):e53284. 24. Hightow-Weidman L, LeGrand S, Choi SK, Egger J, Hurt CB, Muessig KE. Exploring the HIV continuum of care among young black MSM. PLoS One. 2017;12(6):e0179688. 25. Lelutiu-Weinberger C, Golub SA. Enhancing PrEP Access for Black and Latino Men Who Have Sex With Men. Journal of acquired immune deficiency syndromes (1999). Dec 15 2016;73(5):547-555. 26. Eaton LA, Driffin DD, Kegler C, et al. The role of stigma and medical mistrust in the routine health care engagement of black men who have sex with men. American Journal of Public Health. 2015;105(2):e75-82. 27. S. TB, Laura F, Jesse T, et al. Improving HIV Care Engagement in the South from the Patient and Provider Perspective: The Role of Stigma, Social Support, and Shared Decision-Making. AIDS patient care and STDs. 2018;32(9):368-378. 28. Anthony MN, Gardner L, Marks G, et al. Factors associated with use of HIV primary care among persons recently diagnosed with HIV: examination of variables from the behavioural model of health-care utilization. AIDS Care. 2007;19(2):195-202. 29. Genberg BL, Shangani S, Sabatino K, et al. Improving Engagement in the HIV Care Cascade: A Systematic Review of Interventions Involving People Living with HIV/AIDS as Peers. AIDS Behav. Oct 2016;20(10):2452-2463. 30. Mugavero MJ, Amico KR, Horn T, Thompson MA. The State of Engagement in HIV Care in the United States: From Cascade to Continuum to Control. Clinical Infectious Diseases. 2013;57(8):1164-1171. 31. Gelaude DJ, Hart J, Carey JW, et al. HIV Provider Experiences Engaging and Retaining Patients in HIV Care and Treatment: "A Soft Place to Fall". The Journal of the Association of Nurses in AIDS Care : JANAC. Jul - Aug 2017;28(4):491-503. 32. Rosenberg ES, Millett GA, Sullivan PS, Del Rio C, Curran JW. Understanding the HIV disparities between black and white men who have sex with men in the USA using the HIV care continuum: a modeling study. The lancet. HIV. Dec 2014;1(3):e112-e118. 96

33. Halkitis PN. Discrimination and homophobia fuel the HIV epidemic in gay and bisexual men 2012:1. 34. Hill JL. Providing optimal care for your MSM patients2012. 35. 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 research protocols. Sep 17 2019;8(9):e13715. 36. Grov C, Westmoreland DA, Carneiro PB, et al. Recruiting vulnerable populations to participate in HIV prevention research: findings from the Together 5000 cohort study. Annals of epidemiology. 2019/07/01/ 2019;35:4-11. 37. 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 and behavior. 2021/03/01 2021;25(3):709-720. 38. Latkin CA, German D, Vlahov D, Galea S. Neighborhoods and HIV: a social ecological approach to prevention and care. The American psychologist. May-Jun 2013;68(4):210- 224. 39. Power R. The role of qualitative research in HIV/AIDS. Aids. May 07 1998;12(7):687- 695. 40. Ryan GW, Bernard HR. Techniques to Identify Themes. Field Methods. 2003;15(1):85- 109. 41. Rausch D. Promoting engagement in care and timely antiretroviral initiation following HIV diagnosis. 42. Skarbinski J, Rosenberg E, Paz-Bailey G, et al. Human immunodeficiency virus transmission at each step of the care continuum in the united states. JAMA Internal Medicine. 2015;175(4):588-596. 43. Marks G, Crepaz N, Senterfitt JW, Janssen RS. Meta-analysis of high-risk sexual behavior in persons aware and unaware they are infected with HIV in the United States: implications for HIV prevention programs. Journal of acquired immune deficiency syndromes (1999). 2005;39(4):446-453. 44. McNairy ML, Lamb MR, Abrams EJ, et al. Use of a Comprehensive HIV Care Cascade for Evaluating HIV Program Performance: Findings From 4 Sub-Saharan African Countries. Journal of acquired immune deficiency syndromes (1999). 2015;70(2):e44-51. 45. Ulett KB, Willig JH, Hui-Yi L, et al. The Therapeutic Implications of Timely Linkage and Early Retention in HIV Care. AIDS Patient Care & STDs. 2009;23(1):41-49. 46. New York City Department of Health and Mental Hygiene. Care and Clinical Status of People Newly Diagnosed with HIV and People Living with HIV/AIDS in New York City, 2017. 2017. 47. Balán IC, Carballo-Diéguez A, Frasca T, Dolezal C, Ibitoye M. The impact of rapid HIV home test use with sexual partners on subsequent sexual behavior among men who have sex with men. AIDS and behavior. Feb 2014;18(2):254-262. 97

48. Carballo-Diéguez A, Frasca T, Balan I, Ibitoye M, Dolezal C. Use of a rapid HIV home test prevents HIV exposure in a high risk sample of men who have sex with men. AIDS and behavior. Oct 2012;16(7):1753-1760. 49. Lippman SA, Lane T, Rabede O, et al. High Acceptability and Increased HIV-Testing Frequency After Introduction of HIV Self-Testing and Network Distribution Among South African MSM. Journal of acquired immune deficiency syndromes (1999). Mar 1 2018;77(3):279-287. 50. Masters SH, Agot K, Obonyo B, Napierala Mavedzenge S, Maman S, Thirumurthy H. Promoting Partner Testing and Couples Testing through Secondary Distribution of HIV Self-Tests: A Randomized Clinical Trial. PLoS Med. Nov 2016;13(11):e1002166. 51. Ortblad KF, Stekler JD. HIV self-testing: finding its way in the prevention tool box. BMC medicine. 2020/11/30 2020;18(1):373. 52. Johnson CC, Kennedy C, Fonner V, et al. Examining the effects of HIV self-testing compared to standard HIV testing services: a systematic review and meta-analysis. Journal of the International AIDS Society. May 15 2017;20(1):21594. 53. Wohl DA, Kuwahara RK, Javadi K, et al. Financial Barriers and Lapses in Treatment and Care of HIV-Infected Adults in a Southern State in the United States. AIDS patient care and STDs. Nov 2017;31(11):463-469. 54. Amico KR, Konkle-Parker DJ, Cornman DH, et al. Reasons for ART non-adherence in the Deep South: adherence needs of a sample of HIV-positive patients in Mississippi. AIDS Care. Nov 2007;19(10):1210-1218. 55. Fraser B, Pierse N, Chisholm E, Cook H. LGBTIQ+ Homelessness: A Review of the Literature. Int J Environ Res Public Health. Jul 26 2019;16(15). 56. HUD Exchange. Connection Between Housing and Improved Outcomes Along the HIV Care Continuum 2014. 57. Remien RH, Bauman LJ, Mantell JE, et al. Barriers and facilitators to engagement of vulnerable populations in HIV primary care in New York City. Journal of acquired immune deficiency syndromes (1999). May 01 2015;69 Suppl 1:S16-24. 58. Rooks-Peck CR, Adegbite AH, Wichser ME, et al. Mental health and retention in HIV care: A systematic review and meta-analysis. Health psychology : official journal of the Division of Health Psychology, American Psychological Association. Jun 2018;37(6):574-585. 59. Armstrong BJ, Kalmuss D, Franks M, Hecker G, Bell D. Creating teachable moments: a clinic-based intervention to improve young men's sexual health. American journal of men's health. Jun 2010;4(2):135-144. 60. Debra K, Bruce A, Molly F, Gabrielle H, Jessica G. Evaluation of a community-based sexual health intervention for young adult Latino and African-American men. Journal of Men's Health. 2008;5(4):318-326. 61. Hetrick SE, Bailey AP, Smith KE, et al. Integrated (one-stop shop) youth health care: best available evidence and future directions. The Medical journal of Australia. Nov 20 2017;207(10):S5-s18. 98

62. Flickinger TE, Saha S, Roter D, et al. Clinician empathy is associated with differences in patient-clinician communication behaviors and higher medication self-efficacy in HIV care. Patient Educ Couns. Feb 2016;99(2):220-226. 63. Lin C, Li L, Wan D, Wu Z, Yan Z. Empathy and avoidance in treating patients living with HIV/AIDS (PLWHA) among service providers in China. AIDS Care. 2012;24(11):1341-1348. 64. Doblecki-Lewis S, Butts S, Botero V, Klose K, Cardenas G, Feaster D. A Randomized Study of Passive versus Active PrEP Patient Navigation for a Heterogeneous Population at Risk for HIV in South Florida. Journal of the International Association of Providers of AIDS Care (JIAPAC). 2019;18:2325958219848848. 65. Spinelli MA, Laborde N, Kinley P, et al. Missed opportunities to prevent HIV infections among pre-exposure prophylaxis users: a population-based mixed methods study, San Francisco, United States. Journal of the International AIDS Society. 2020;23(4):e25472. 66. Smith DK, Chang MH, Duffus WA, Okoye S, Weissman S. Missed Opportunities to Prescribe Preexposure Prophylaxis in South Carolina, 2013-2016. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. Jan 1 2019;68(1):37-42. 67. Patel RR, Chan PA, Harrison LC, et al. Missed Opportunities to Prescribe HIV Pre- Exposure Prophylaxis by Primary Care Providers in Saint Louis, Missouri. LGBT health. May/Jun 2018;5(4):250-256. 68. Boekeloo BO. Will you ask? Will they tell you? Are you ready to hear and respond?: barriers to physician-adolescent discussion about sexuality. JAMA pediatrics. Feb 2014;168(2):111-113. 69. Ryan KL, Arbuckle-Bernstein V, Smith G, Phillips J. Let‚Äôs Talk About Sex: A Survey of Patients‚Äô Preferences When Addressing Sexual Health Concerns in a Family Medicine Residency Program Office. 2018/10/11;2. 70. Moore JW. What Is the Sense of Agency and Why Does it Matter? Front Psychol. 2016;7:1272. 71. Canoy NA, Ofreneo MAP. Struggling to care: A discursive-material analysis of negotiating agency among HIV-positive MSM. Health. 2017;21(6):575-594. 72. Ocloo J, Goodrich J, Tanaka H, Birchall-Searle J, Dawson D, Farr M. The importance of power, context and agency in improving patient experience through a patient and family centred care approach. Health Research Policy and Systems. 2020/01/23 2020;18(1):10. 73. Hunter J, Franken M, Balmer D. Constructions of patient agency in healthcare settings: Textual and patient perspectives. Discourse, Context & Media. 2015/03/01/ 2015;7:37- 44.

Table 4.1. Socio-demographic characteristics, HIV-positive GBM, n = 50 Characteristic M SD Age 31.70 8.10 Frequency % Race/Ethnicity White 24 48 Black 8 16 Latino 14 28 Multiracial 4 8 Sexual Orientation Gay, Queer, Homosexual 47 94 Bisexual 3 6 Education < High school diploma 2 4 High school diploma or GED 5 10 Some college or technical school training 29 58 College graduate + 14 28 Employment Status Full-time (40 hours per week) 27 54 Part-time (less than 40 hours per week) 7 14 Working- or full-time student 9 18 Unemployed/Other 7 14 Annual Income Less than $20,000 22 44 $20,000-$49,999 20 40 $50,000+ 8 16 Has a main partner Yes 18 36 No 32 64 Health Insurance Yes 27 54 No/do not know 23 46 Has a Primary Care Provider Yes 26 52 No/do not know 24 48 100

Engaged in sex work (past 12 months) Yes 16 32 No 34 68 Housing Instability in past 5 years Yes 20 40 No 30 60 Self-reported HIV Status at Baseline HIV-negative 14 28 I don't know; I am unsure 36 72 Have you ever been tested for HIV? In the past 12 months 17 34 More than a year ago 26 52 Never 7 14 Prior PrEP use Yes 2 4 No 48 92 Diagnosed with an STD in the last 12 Months Yes 10 20 No 40 80 Region Northeast 7 14 South 31 62 Midwest 3 6 West 9 18 Pacific, US Territories, Others - -

101

CHAPTER 5: CONCLUSION

OVERVIEW

This dissertation used a multi-method approach to understand how individual-, contextual- and structural-factors influence HIV risk in an U.S. national sample of GBM and engagement in HIV care among those newly diagnosed with HIV. First, using the syndemic theory framework, we assessed the prevalence of eight syndemic conditions and explored their associations with a composite measure of HIV risk (Aim 1). Second, using a resilience framework, we described the socio-demographic and geographical differences in resilience, and explored whether resilience was associated to a composite measure of HIV risk and to individual sexual risk behaviors (Aim 2). Finally, using the socio-ecological model, we explored linkage and engagement in care for HIV+ GBM and identified multi-level barriers and facilitators to engagement in care (Aim 3). This dissertation used data collected as part of the Together 5,000 study, a U.S. national, internet-based cohort study of men, transgender men, and transgender women who have sex with men. For Aims 1 and 2, we conducted secondary analysis of quantitative survey data from a cohort of 6,118 GBM ages 16-49 at high risk for HIV transmission.1,2 Further, the outcome of interest for Aims 1 and 2 was a compositve measure of

HIV risk. We assessed the relationship between individual and cumulative syndemics, resilience and HIV risk using adjusted multiple linear regressions. For Aim 3, we conducted secondary analysis of qualitative data from 50 GBM diagnosed HIV-positive during their participation in

Together 5,000 using thematic analysis to identify barriers and facilitators to engagement in care.

This dissertation set out to re-conceptualize the application of Syndemic Theory by incorporating a unique set of social condition variables, such as incarceration and homelessness history, often left out in traditional syndemic analyses.3-6 This dissertation also explored both deficit- and 102 strength-based approaches to HIV prevention through a syndemic framework and a resilience framework.7 Further, the qualitative data from recently diagnosed individual’s experience accessing HIV care provides valuable insights into barriers and facilitators to engagement in care across the U.S. As such, this research provides new information on the state of the HIV policies and hard to reach populations in the US and contribute toward the goal of ending AIDS in the US by 2030.8

SUMMARY OF FINDINGS

Aim 1: Syndemics and HIV Risk

Aim 1 extended the recent work on syndemics by exploring the association between eight syndemic conditions (intimate partner violence, depression, anxiety, childhood sexual abuse, polydrug use, hazard alcohol use, incarceration history and homelessness) and HIV risk before and after controlling for selected socio-demographic characteristics. In estimating the prevalence of syndemics among our participants (n = 6,118), half (50.4%) reported previous intimate partner violence (IPV), roughly one-quarter reported symptoms of anxiety (30.6%), depression (28.8%), and childhood sexual abuse (CSA, 24.3%), one-fifth (20.3%) reported unstable housing within the last 5 years, and 14.5% reported having been incarcerated at least once in their lives.

Moreover, 21.2 % and 11.9% reported hazard alcohol and polydrug use, respectively. One- quarter (24.7%) of participants reported one syndemic condition, 20.3% reported two co- occurring syndemics, 15.8% reported three, 10.3% reported four, and 8.8% reported more than four co-occurring syndemics. In adjusted multiple linear regressions, IPV, childhood sexual abuse, polydrug use, incarceration history and homelessness were positively associated with HIV risk. We also found that increasing cumulative syndemic burden was associated with higher HIV risk. Those who reported 3 or more co-occurring conditions had the highest risk for HIV. These 103 findings highlight the need for public health practitioners to recognize housing instability and incarceration as important social determinants of health and as catalysts for worsening health outcomes.9-11 Further, these findings shed light on the socioeconomic vulnerabilities impacting

GBM across the U.S., particularly among racial/ethnic minorities and, as such, future studies should further explore the impact of additional structural factors, including racial and ethnic discrimination on HIV prevention and care.

Aim 2: Resilience and HIV Risk

In Aim 2, we employed a strength-based approach to HIV prevention by describing the levels of resilience in our sample of GBM. We examined the socio-demographic differences in resilience and assessed the relationship between resilience and HIV risk. We found higher mean resilience scores among those identifying as black, with higher education, having full-time employment, higher incomes, and those who have health insurance. There was a lower mean resilience among those engaging in transactional sex in the last 12 months and among those having been diagnosed with an STD in the last 12 months.

We ran three multiple linear regression models between resilience and HIV Risk; Model

1 using the composite MSM risk Index measure, Model 2 using only a measure of condomless receptive anal sex, and Model 3 using a measure of condomless insertive anal sex. After adjusting for psychosocial and demographic characteristics, we found no statistically significant association between resilience and our composite measure of HIV risk and condomless insertive anal sex. However, we found a significant association between higher resilience and lower condomless receptive anal sex acts in the last 3 months. Unfortunately, we may have been limited in its ability to fully measure resilience and could have accounted for our non-significant findings. Our measure of resilience only measures adaptability and coping, and although this is 104 an acceptable construct to measure, resilience may be better conceptualized as a multi- dimensional factor. It may also be more appropriate to measure the association between resilience and HIV risk by focusing on specific sexual behaviors rather than a composite measure of sexual risk. Our findings highlight gaps and the need to promote health-enhancing positive factors in HIV intervention work.

Aim 3: Engagement in Care among newly diagnosed HIV-positive GBM

In Aim 3, we explored linkage, engagement and retention in HIV care through secondary analysis of in-depth interviews with 50 GBM 3-months after delivery of their preliminary HIV- positive test results. Particular attention was given to the challenges participants faced with their linkage-to-care and initiation of ART. Almost half (46%) were uninsured and did not have a primary care provider (48%). The majority (94%) of participants reported being linked-to-care and had their diagnosis confirmed with a healthcare provider, while only 74.5% of those reported initiating ART.

We explored the barriers and facilitators to engagement in care using the socioecological framework. Through thematic analyses, we identified four major themes related to participants’ engagement in care: 1) Reasons for HIV testing (e.g., HIV self-testing and expectation of positivity), 2) Linkage-to-care (e.g., appointment/logistic issues and social support as encouragement), 3) Barriers (e.g., financial burden, competing priorities and fear/stigma) and facilitators (e.g., financial assistance, patient-provider relationships, auxiliary support services and health agency) to engagement in HIV care, and 4) PrEP as a missed prevention opportunity.

These results suggest that addressing policy-, social- and individual-level barriers could improve

GBM’s engagement in HIV care. Further, capitalizing on GBM’s health agency through 105 partnerships with local agencies and fostering better patient-provider relationships could optimize continuity of HIV care.12-15

POLICY IMPLICATIONS

Overall, the findings from this multi-method dissertation suggest that the HIV epidemic is complex and, therefore, an effective prevention and intervention national agenda requires an understanding of the diversity and dynamic nature of individuals, communities, and our socio- political environment. Firstly, our efforts to address HIV disparities will not be successful without careful consideration of the structural and social determinants of health. Housing is an unique social determinant of health that has a significant influence on individual’s lives.16,17 It is also an indicator of broader structural processes of inequality that fuel HIV vulnerability and sustain poor health outcomes.16-20 Particularly, housing is linked to a myriad of economic and social factors. Research has found that a lack of stable and secure housing has a direct negative effect on physical and psychological well-being, socioeconomic attainment, sexual behaviors, and recidivism.16,17,21-23 Our findings demonstrate that environmental and behavioral factors such as homelessness, incarceration are prevalent among GBM in the U.S. In fact, we found that unstable housing not only contributes to HIV risk but was also a barrier to engagement in care.

Past research has established that unstable housing can have a detrimental effect on the HIV continuum of care by delaying linkage to care, increasing the likelihood of discontinuity in care, and decreasing the likelihood of viral suppression.

Health policies that target these structural and social determinants to HIV infection can have a significant impact on the epidemic, particularly those that expand access to prevention services and treatment.13,24,25 The 2019 Ending the HIV Epidemic in America initiative aims to 106 reduce all new HIV infections by 90% in the next 10 years.24 As such, there may be political clout to advocate for evidence-based policies that offer assistance to PLWHIV and eliminate the economical burdens associated to HIV testing and other biomedical interventions. In the last decade, there has been considerable improvement in expanding Medicaid, ADAP eligibility and housing for PLWHIV; however, there is immense eligibility variation between states.26-30 Given this, there needs to be a push towards standardizing eligibility across states in order to reduce

HIV infections across the nation. Some states (e.g., California and New York) have produced policies (e.g., HIV/AIDS Services Administration) or consistently fund programs (e.g., Housing

Works) that have made positive impacts on sexual minority individuals.31,32 Whereas, states like

Texas and Florida, who did not expand access to Medicaid, have some of the most restrictive eligibility criteria for ADAP, and as a result PLHIV in those states face several barriers to care which inhibits their ability to achieve viral suppression and stop the spread of the virus.27,29,33

The shift to a biomedical paradigm of prevention has led to less consideration of individual-level interventions. A resurgence of behavioral interventions that address intra- and inter-personal factors, that promote agency and resilience, and increases health education may be necessary to end the epidemic. Our findings suggest that agency and resilience can have an impact on how GBM understand, seek and interact with HIV prevention tools. Evidence-based behavioral interventions, such as the CDC’s Many Men, Many Voices (3MV), have begun to incorporate resilience building exercises given their understanding that resilience can be learned, developed and influence success in changing behaviors.34 Additionally, incorporating motivational interviewing into field outreach and behavioral interventions can also increase the likelihood of HIV counseling, health education, HIV testing, and, ultimately, improve HIV prevention and care outcomes.35,36 107

Stigma, racism, and marginalization have been identified as drivers of the epidemic.

Studies have found that discrimination is often compounded with other sources of stigma, including stigma around gender identity and racism.15,37-45 Gender roles have been shown to influence the perception that one male partner is “womanly” or “weak”, which in turn facilitates problematic power dynamics, such as when the more ”manly” partner exerts undue influence over decisions surrounding condom use.37,38,45,46 This stigma produces marginalization in MSM and, in turn, strongly influences an individual’s vulnerability for HIV infection through engagement in higher risk sexual behaviors.38,40,41,46-48 This is particularly true for individuals in disadvantaged social positions, who likely to go through psychologically straining life experiences (stressors) due to their intersecting identities (e.g., being gay and black).38,40,49-51

Therefore, interventions that address the management of stigma, enhance social support and health agency continue to be necessary.52

FUTURE DIRECTIONS

This research identified multi-level factors that are associated with HIV risk and engagement in care. Firstly, although our expanded syndemic model offers a more comprehensive understanding of the unique HIV risks for GBM, more research is needed. The way in which we conceptualized our syndemic variables simplifies a large issue into a binary variable. As such, more complex mathematical modelling may be needed to fully understand how syndemics, including housing and incarceration, impact risk. Secondly, while we did not find that resilience was associated to our composite measure of HIV risk, we found a significant association to condomless receptive anal sex. The conceptualization of resilience as a unidimensional construct may be inadequate for this population. Given this, we believe our study 108 was limited in its ability to fully measure resilience. The Connor-Davidson Resilience scale only measures adaptability and coping, and although this is an acceptable construct to measure, resilience may be better conceptualized as a multi-dimensional factor, vis-à-vis syndemics.

Future research may benefit from assessing HIV risk through the presence of resilience- promoting (e.g., social support, hardiness and coping, etc.) or resilience-diminishing (e.g., internalized homophobia) factors. As such, a more nuanced measurement of resilience and expanded research on the ways it impacts HIV prevention and care is needed. Finally, more research is needed on the role of health agency on GBM’s engagement in care. The research on health agency applied to HIV care is scant, making our findings particularly innovative. Given that health agency was a salient theme in our qualitative data, we believe that empirical research should be conducted to quantify and explore its association to HIV care outcomes (e.g., retention in care, viral suppression, etc.).

LIMITATIONS

Our findings should be interpreted through careful consideration of its limitations. In

Aims 1 and 2, we used cross-sectional internet surveys from 6,118 from across the U.S. The cross-sectional design of this study prevents making any conclusive causal claims about the temporality and directionality of the relationships we observed for Aims 1 and 2. This study was not designed to prove causation, only to correlate, and therefore causal inferences should be interpreted with caution.53 Although this fully online study allowed for increased geographical reach, it also increased the potential for fraudulent participants.54,55 Further, this study relied exclusively on data from self-reported surveys and, while measures to increase the validity of the data were put into place, social desirability and recall bias may have affected the study 109 findings.56 Further, the study population was recruited via sexual networking apps and represented a sample of those at highest risk for HIV, who are not on PrEP at enrollment. Given the non-probability sampling, we are unable to generalize the Aim 1 and 2 results to other GBM.

Our findings are limited to a sample of HIV-negative cis-gender GBM and we cannot rule out that there may be unique differences in syndemic prevalence and resilience profiles for individuals who are gender non-conforming and those who are HIV-positive.

Finally, our Aim 3 qualitative findings helped generate insights, themes, and nuances regarding GBM’s experiences accessing health care. However, these findings are not generalizable to the general GBM population in the U.S. Our recruitment strategy explicitly emphasized “free at-home HIV testing” as well as compensation for completing study assessments. Those with more severe HIV testing anxiety and those who may be unknowingly living with HIV may not have enrolled in our cohort. Nonetheless, our qualitative findings did highlight some HIV-related anxiety among participants. Further, we only interviewed participants to whom we could successfully deliver an HIV test result over the phone; as such, their experiences may differ from those who tested HIV-positive but avoided our delivery efforts. In addition, our recruitment strategies led us to interview individuals who were more likely to be engaged in HIV care. Despite many themes being salient across our sample, our study would have benefitted from the perspectives of individuals who were not engaged in care.

CONCLUSIONS

Overall, the findings from this multi-method dissertation suggest that the HIV epidemic is complex, and therefore an effective response requires an understanding of the diversity and dynamic nature of individuals, communities, and our socio-political environment. We 110 demonstrated that environmental and behavioral factors such as homelessness, incarceration are prevalent among GBM in the U.S. and contribute to HIV acquisition, thus offering compelling evidence for the adoption of these variables in future syndemic models. Further, there needs to be a more comprehensive investigation of the unique risk factors in this population, particularly those that may impact uptake and adoption of preventive HIV health behaviors, such as pre- exposure prophylaxis (PrEP). For instance, larger structural factors like societal racial discrimination, anti-immigration laws, lack of health insurance coverage and unemployment can significantly impact adherence to biomedical tools and use of testing services. Future research should explore these social and structural determinants within the context of HIV prevention.

As seen in our study findings, HIV prevention is a multi-faceted process. There is a need for a more holistic approach to prevention, wherein HIV prevention is conceptualized as more than just HIV testing and PrEP initiation but that takes into account intrapersonal (e.g,, resilience) and interpersonal factors (e.g., social support). Finally, addressing policy-, social- and individual-level barriers could improve GBM’s engagement in HIV care. Capitalizing on GBM’s health agency through partnerships with local agencies and fostering better patient-provider relationships could optimize continuity of HIV care. We possess the tools needed to end the HIV epidemic in the U.S., particularly by advocating for a new federal policy which streamlines HIV testing, linkage-to-care and ART initiation. 111

REFERENCES

1. 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 research protocols. Sep 17 2019;8(9):e13715. 2. Grov C, Westmoreland DA, Carneiro PB, et al. Recruiting vulnerable populations to participate in HIV prevention research: findings from the Together 5000 cohort study. Annals of epidemiology. 2019/07/01/ 2019;35:4-11. 3. Scheer JR, Pachankis JE. Psychosocial Syndemic Risks Surrounding Physical Health Conditions Among Sexual and Gender Minority Individuals. LGBT health. Nov/Dec 2019;6(8):377-385. 4. Hirshfield S, Schrimshaw EW, Stall RD, Margolis AD, Jr MJD, Chiasson MA. Drug Use, Sexual Risk, and Syndemic Production Among Men Who Have Sex With Men Who Engage in Group Sexual Encounters. American Journal of Public Health. 2015;105(9):1849-1858. 5. Martinez O, Brady KA, Levine E, et al. Using Syndemics Theory to Examine HIV Sexual Risk Among Latinx Men Who Have Sex with Men in Philadelphia, PA: Findings from the National HIV Behavioral Surveillance. Ehquidad. Jan-Jun 2020;13:217-236. 6. Parsons JT, Antebi-Gruszka N, Millar BM, Cain D, Gurung S. Syndemic Conditions, HIV Transmission Risk Behavior, and Transactional Sex Among Transgender Women. AIDS and behavior. Jul 2018;22(7):2056-2067. 7. Herrick AL, Stall R, Goldhammer H, Egan JE, Mayer KH. Resilience as a Research Framework and as a Cornerstone of Prevention Research for Gay and Bisexual Men: Theory and Evidence. AIDS and behavior. 2014/01/01 2014;18(1):1-9. 8. Bernstein L, Sun LH, Golstein A. Trump is planning campaign to halt transmission of HIV in U.S. by 2030. 2019. 9. Nowotny KM, Kuptsevych-Timmer A. Health and Justice: Framing incarceration as a social determinant of health for Black men in the United States. Sociology Compass. 2018/03/01 2018;12(3):e12566. 10. Brinkley-Rubinstein L, Cloud DH. Mass Incarceration as a Social-Structural Driver of Health Inequities: A Supplement to AJPH. Am J Public Health. Jan 2020;110(S1):S14- s15. 11. Brinkley-Rubinstein L. Incarceration as a catalyst for worsening health. Health & Justice. 2013/10/24 2013;1(1):3. 12. Flickinger TE, Saha S, Roter D, et al. Clinician empathy is associated with differences in patient-clinician communication behaviors and higher medication self-efficacy in HIV care. Patient Educ Couns. Feb 2016;99(2):220-226. 13. Mugavero MJ, Norton WE, Saag MS. Health care system and policy factors influencing engagement in HIV medical care: piecing together the fragments of a fractured health care delivery system. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. Jan 15 2011;52 Suppl 2:S238-246. 14. Kipke MD, Kubicek K, Wong CF, et al. A Focus on the HIV Care Continuum Through the Healthy Young Men's Cohort Study: Protocol for a Mixed-Methods Study. JMIR research protocols. Jan 24 2019;8(1):e10738. 15. Hull MW, Wu Z, Montaner JS. Optimizing the engagement of care cascade: a critical step to maximize the impact of HIV treatment as prevention. Current opinion in HIV and AIDS. 2012;7(6):579-586. 16. Dean HD, Fenton KA. Addressing social determinants of health in the prevention and control of HIV/AIDS, viral hepatitis, sexually transmitted infections, and tuberculosis. 112

Public health reports (Washington, D.C. : 1974). Jul-Aug 2010;125 Suppl 4(Suppl 4):1- 5. 17. Aidala AA, Wilson MG, Shubert V, et al. Housing Status, Medical Care, and Health Outcomes Among People Living With HIV/AIDS: A Systematic Review. Am J Public Health. Jan 2016;106(1):e1-e23. 18. Dickson-Gomez J, McAuliffe T, Quinn K. The Effects of Housing Status, Stability and the Social Contexts of Housing on Drug and Sexual Risk Behaviors. AIDS and behavior. Jul 2017;21(7):2079-2092. 19. Baral S, Logie CH, Grosso A, Wirtz AL, Beyrer C. Modified social ecological model: a tool to guide the assessment of the risks and risk contexts of HIV epidemics. BMC public health. May 17 2013;13:482. 20. Adimora AA, Ramirez C, Schoenbach VJ, Cohen MS. Policies and politics that promote HIV infection in the Southern United States. Aids. Jun 19 2014;28(10):1393-1397. 21. Couloute L. Nowhere to Go: Homelessness among formerly incarcerated people: Prison Policy Initiative;2018. 22. Remster B. A Life Course Analysis of Homeless Shelter Use among the Formerly Incarcerated. Justice Quarterly. 2019/04/16 2019;36(3):437-465. 23. Kipke MD, Weiss G, Wong CF. Residential status as a risk factor for drug use and HIV risk among young men who have sex with men. AIDS and behavior. Nov 2007;11(6 Suppl):56-69. 24. Office of Infectious Disease and HIV/AIDS Policy. What Is Ending the HIV Epidemic: A Plan for America? 2021; https://www.hiv.gov/federal-response/ending-the-hiv- epidemic/overview. Accessed February 22, 2021. 25. Keuroghlian AS, Shtasel D, Bassuk EL. Out on the street: a public health and policy agenda for lesbian, gay, bisexual, and transgender youth who are homeless. Am J Orthopsychiatry. 2014;84(1):66-72. 26. Wohl DA, Kuwahara RK, Javadi K, et al. Financial Barriers and Lapses in Treatment and Care of HIV-Infected Adults in a Southern State in the United States. AIDS patient care and STDs. Nov 2017;31(11):463-469. 27. Amico KR, Konkle-Parker DJ, Cornman DH, et al. Reasons for ART non-adherence in the Deep South: adherence needs of a sample of HIV-positive patients in Mississippi. AIDS Care. Nov 2007;19(10):1210-1218. 28. Fraser B, Pierse N, Chisholm E, Cook H. LGBTIQ+ Homelessness: A Review of the Literature. Int J Environ Res Public Health. Jul 26 2019;16(15). 29. S. TB, Laura F, Jesse T, et al. Improving HIV Care Engagement in the South from the Patient and Provider Perspective: The Role of Stigma, Social Support, and Shared Decision-Making. AIDS patient care and STDs. 2018;32(9):368-378. 30. HUD Exchange. Connection Between Housing and Improved Outcomes Along the HIV Care Continuum 2014. 31. Shelton J, DeChants J, Bender K, et al. Homelessness and Housing Experiences among LGBTQ Young Adults in Seven U.S. Cities. Cityscape. 2018;20(3):9-34. 32. Remien RH, Bauman LJ, Mantell JE, et al. Barriers and facilitators to engagement of vulnerable populations in HIV primary care in New York City. Journal of acquired immune deficiency syndromes (1999). May 01 2015;69 Suppl 1:S16-24. 33. Smith DK, Chang MH, Duffus WA, Okoye S, Weissman S. Missed Opportunities to Prescribe Preexposure Prophylaxis in South Carolina, 2013-2016. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. Jan 1 2019;68(1):37-42. 113

34. National Center for HIV/AIDS Viral Hepatitis STD and TB Prevention. 3MV - Many Men, Many Voices: A small group intervention for HIV/STI among black gay men. 2018. 35. American Psychological Association. Implementing motivational interviewing to end the youth HIV epidemic: Psychology and AIDS Exchange Newsletter; 2020. 36. Outlaw AY, Naar-King S, Parsons JT, Green-Jones M, Janisse H, Secord E. Using motivational interviewing in HIV field outreach with young African American men who have sex with men: a randomized clinical trial. Am J Public Health. Apr 1 2010;100 Suppl 1(Suppl 1):S146-151. 37. Sun CJ, Garcia M, Mann L, Alonzo J, Eng E, Rhodes SD. Latino Sexual and Gender Identity Minorities Promoting Sexual Health Within Their Social Networks: Process Evaluation Findings From a Lay Health Advisor Intervention. Health promotion practice. 2014. 38. Starks TJ, Rendina HJ, Breslow AS, Parsons JT, Golub SA. The psychological cost of anticipating HIV stigma for HIV-negative gay and bisexual men. AIDS and behavior. 2013;17(8):2732-2741. 39. Smith-Morris C, Morales-Campos D, Alvarez EAC, Turner M. An Anthropology of Familismo: On Narratives and Description of Mexican/Immigrants. Hispanic Journal of Behavioral Sciences. 2012. 40. Rodriguez MM, Madera SR, Diaz NV. Stigma and Homophobia: Persistent Challenges for HIV Prevention Among Young MSM in Puerto Rico. Revista de ciencias sociales. 2013;26:50-59. 41. Overstreet NM, Earnshaw VA, Kalichman SC, Quinn DM. Internalized stigma and HIV status disclosure among HIV-positive black men who have sex with men. AIDS Care. 2013;25(4):466-471. 42. Finlinson HA, Colon HM, Robles RR, Soto M. Sexual identity formation and AIDS prevention: an exploratory study of non-gay-identified Puerto Rican MSM from working class neighborhoods. AIDS and behavior. 2006;10(5):531-539. 43. Douglas-Vail M. Syndemics theory and its applications to HIV/AIDS public health interventions. International Journal of Medical Sociology and Anthropology. 2016;4(1). 44. Diaz NV, Rivera SM, Bou FC. AIDS stigma combinations in a sample of Puerto Rican health professionals: qualitative and quantitative evidence. Puerto Rico health sciences journal. 2008;27(2):147-157. 45. Poppen PJ, Reisen CA, Zea MC, Bianchi FT, Echeverry JJ. Predictors of unprotected anal intercourse among HIV-positive Latino gay and bisexual men. AIDS and behavior. 2004;8(4):379-389. 46. Garcia J, Parker C, Parker RG, Wilson PA, Philbin M, Hirsch JS. Psychosocial Implications of Homophobia and HIV Stigma in Social Support Networks: Insights for High-Impact HIV Prevention Among Black Men Who Have Sex With Men. Health education & behavior : the official publication of the Society for Public Health Education. 2016;43(2):217-225. 47. Frost DM, Meyer IH. Internalized Homophobia and Relationship Quality among Lesbians, Gay Men, and Bisexuals. Journal of counseling psychology. Jan 2009;56(1):97-109. 48. Frost DM, Lehavot K, Meyer IH. Minority stress and physical health among sexual minority individuals. Journal of behavioral medicine. Feb 2015;38(1):1-8. 49. Meyer IH. Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence. Psychological bulletin. Sep 2003;129(5):674-697. 114

50. Meyer IH. Identity, Stress, and Resilience in Lesbians, Gay Men, and Bisexuals of Color. The Counseling psychologist. 2010;38(3):10.1177/0011000009351601. 51. Hatzenbuehler ML, Nolen-Hoeksema S, Erickson SJ. Minority stress predictors of HIV risk behavior, substance use, and depressive symptoms: results from a prospective study of bereaved gay men. Health psychology : official journal of the Division of Health Psychology, American Psychological Association. Jul 2008;27(4):455-462. 52. Hussen SA, Jones M, Moore S, et al. Brothers Building Brothers by Breaking Barriers: development of a resilience-building social capital intervention for young black gay and bisexual men living with HIV. AIDS Care. 2018/07/25 2018;30(sup4):51-58. 53. Morabia A. A history of epidemiologic methods and concepts: Birkhäuser; 2013. 54. Doblecki-Lewis S, Butts S, Botero V, Klose K, Cardenas G, Feaster D. A Randomized Study of Passive versus Active PrEP Patient Navigation for a Heterogeneous Population at Risk for HIV in South Florida. Journal of the International Association of Providers of AIDS Care (JIAPAC). 2019;18:2325958219848848. 55. Blashill AJ, Brady JP, Rooney BM, et al. Syndemics and the PrEP Cascade: Results from a Sample of Young Latino Men Who Have Sex with Men. Archives of sexual behavior. Jan 2020;49(1):125-135. 56. Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plastic and reconstructive surgery. Aug 2010;126(2):619-625.

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APPENDICES 116

APPENDIX A: ENROLLMENT SURVEY

Take care of yourself, take care of your community.

Join Together 5000, a new LGBT-led university research study.

Earn up to $200 by taking surveys online and testing yourself with free at-home HIV test kits.

Earn $15 or more per survey, get free at-home HIV test kits, and earn at least $15 for getting tested. Full participation adds up to $200!

Just take this short 5 minute survey to see if you're eligible.

Age. How old are you? A. Number entry

[IF Age ≤ 15, SKIP TO INELIGIBLE FULL STOP, IF > 49 ALLOW TO FINISH SURVEY BUT END ON INELIGIBLE ASK FOR CONTACT FOR FUTURE RESEARCH] [IF Age < 18, DISPLAY CONSENT1, CONSENT2, CONSENT3]

Consent1. What is this study focused on? A. Sexuality, sexual health, and substance use B. Eating habits C. Sleeping patterns

Consent2. Which of these is a risk of the study? A. Side effects from a treatment being used B. Exercise related fatigue 117

C. Discomfort answering personal questions

Consent3. How long is this survey expected to take? A. 5 minutes B. 20-30 minutes C. 60 minutes

Latino. Do you consider yourself Hispanic or Latino? A. Yes B. No

Race. Which racial or ethnic group do you belong to? (Please select all that apply) A. American Indian or Alaska Native B. Asian C. Black/African American D. Native Hawaiian or Other Pacific Islander E. White F. Other (Please specify): ______

Employ. Which of the following best describes your current employment status? A. Full-time (40 hours per week) B. Part-time (less than 40 hours per week) C. Part-time work - full time student D. Permanent or temporary disabled and NOT working E. Permanent or temporary disabled BUT working “off the books” (or "under the table") F. Unemployed -- Student G. Unemployed – Other

Educ. What's the highest level of education that you have completed? A. 8th Grade or less B. 9th Grade C. 10th Grade D. 11th Grade E. High School Diploma or GED F. Some College or Associates Degree G. Currently enrolled in college H. 4-Year College Degree (BA, BS, BFA) I. Some Graduate School J. Master's Degree K. Doctorate Degree

USAYN. Do you live in the US or one of its territories? 118

A. Yes B. No

[IF USAYN = B INELIGIBLE, ALLOW TO FINISH SURVEY BUT END ON INELIGIBLE ASK FOR CONTACT FOR FUTURE RESEARCH]

Zipcode. What is the Zip code of your home address? A. [5 digits] ______

HIVStatus. What is your HIV status? A. HIV-negative B. HIV-positive C. I don’t know; I am unsure

[IF HIVStatus = B, INELIGIBLE, ALLOW TO FINISH SURVEY BUT END ON INELIGIBLE ASK FOR CONTACT FOR FUTURE RESEARCH, ASK Diagnosis, THEN CONTINUE TO Sex]

Diagnosis. What year were you diagnosed with HIV? A. [validated number entry]

[IF Diagnosis = 2017, ASK LastNegTes]

LastNegTest. When was the last time you received an HIV-negative test prior to being diagnosed HIV-positive? A. I had never been tested for HIV before my diagnosis B. I last tested negative more than 5 years ago C. I last tested negative between 2 and 5 years ago D. I last tested negative between 1 and 2 years ago E. I last tested negative 6 to 12 months ago F. I last tested negative 3 to 6 months ago G. I last tested negative within the past 3 months

[IF HIVStatus = A OR C, ASK LastHIVtest]

LastHIVtest. When was your last HIV Test? A. Within the last month B. 1-3 months ago C. 3-6 months ago D. 7-12 months ago E. [Baseline only] 1 to 2 years ago F. [Baseline only] More than 2 years ago G. [Baseline only] I’ve never been tested

119

[IF LastHIVtest = A, B, C, D, E, ASK TestFreq] TestFreq. How often do you typically get tested for HIV? A. Less than once a year B. Once a year C. Twice a year D. Three times a year E. Four times a year F. Five times a year G. Six times a year H. Seven or more times a year

[IF HIVStatus = A or C, ASK PrEPstatus, PrEPnetwork, NonPrescPrEP, PEPstatus, THEN CONTINUE TO Sex]

PrEPstatus. Have you ever been prescribed HIV medications (e.g., Truvada) for use as PrEP (Pre-Exposure Prophalyxis)? A. I don’t know what PrEP is B. No, never taken PrEP C. Yes, I am currently on PrEP D. Yes, but I am not currently taking PrEP

[IF PrEPstatus = D, ask PrEPdisruption]

[IF PrEPstatus = C, INELIGIBLE, ALLOW TO FINISH SURVEY BUT END ON INELIGIBLE ASK FOR CONTACT FOR FUTURE RESEARCH]

PrEPdisruption. Why did you stop taking PrEP? [Write in] ______

[DISPLAY PrEPnetwork AND NonPrescPrEP IF PrEPstatus = B, C, or D] PrEPnetwork. How many people do you know personally who are taking PrEP (e.g., Truvada)? A. 0 B. 1 C. 2 D. 3 E. 4 F. 5+

NonPrescPrEP. Have you ever taken HIV medications to prevent HIV, without a prescription (e.g., been given PrEP from a friend/partner)? Check all that apply. A. Yes, after an exposure/risk B. Yes, before an exposure/risk C. No

120

PEPstatus. Have you ever been prescribed HIV medications AFTER an exposure to prevent getting HIV (for example, sex without a condom or the condom broke). This is called Post Exposure Prophylaxis, PEP. A. No, never B. Yes, in the last year C. Yes, more than one year ago

ClinicTrial. Are you currently participating in an HIV vaccine or HIV drug prevention clinical trial (e.g. Descovy)? A. Yes B. No

[IF ClinicTrial = A, INELIGIBLE, ALLOW TO FINISH SURVEY BUT END ON INELIGIBLE ASK FOR CONTACT FOR FUTURE RESEARCH]

Sex. What sex were you assigned at birth? A. Male B. Female

Gender. What gender do you currently identify as? A. Male B. Female C. Transgender female D. Transgender male E. Something else (Please specify): _____

[IF Sex = B AND Gender = B (i.e. cisfemales) INELIGIBLE, ALLOW TO FINISH SURVEY BUT END ON INELIGIBLE ASK FOR CONTACT FOR FUTURE RESEARCH]

SexOrientation. Which best describes how you identify your sexual orientation? A. Gay, Queer, Homosexual B. Bisexual C. Straight, Heterosexual D. Other (Please specify): ______

CDC MSM Risk Index

MalePartners. In the last 3 months, how many men have you had anal sex with? A. 0-90+

FemalePartners. In the last 3 months, how many women have you had anal/vaginal sex with? 121

A. 0-90+

[DISPLAY UAVIFemale IF FemalePartners > 0]

UAVIFemale. How many times have you had anal/vaginal sex without a condom with a female partner in the last 3 months? A. 0-90+ drop down

TransmenPartners. In the last 3 months, how many transmen (female-to-male, FTM) have you had anal/vaginal sex with? A. 0-90+

TranswomenPartners. In the last 3 months, how many transwomen have you had anal/vaginal sex with? A. 0-90+

URAI. In the last 3 months, how many times did you have receptive anal sex (you were the bottom) with a man without a condom? A. 0-90+

PozMalePartners. In the last 3 months, how many of your male sex partners were HIV- positive? A. 0-90+

[DISPLAY URAIPos if URAI and PozMalePartners ARE NOT 0] URAIPos. In the last 3 months, how many times did you have receptive anal sex (you were the bottom) with a man without a condom with a man who was HIV-positive? A. 0-90+

UIAI. In the last 3 months, how many times did you have insertive anal sex (you were the top) without a condom with a man? A. 0-90+

UIAIPos. In the last 3 months, how many times did you have insertive anal sex (you were the top) without a condom with a man who was HIV-positive? A. 0-90+

122

The following is a list of sexually transmitted infections. For each infection, please indicate when you were diagnosed.

How long ago was this? In the last 6-12 1-5 Years More than 6 Months Months 5 years STD1. Rectal/Anal Gonorrhea or Chlamydia STD2. Oral/Pharyngeal Gonorrhea or Chlamydia STD3. Genital warts, anal warts, HPV STD4. Herpes, HSV1, HSV2 STD5. Syphilis STD6. Hepatitis C STD7. Hepatitis B STD8. Urethritis

MainPartner. Are you currently in a relationship with someone to whom you feel committed above anyone else and with whom you have had a sexual relationship? A. Yes B. No

Polyamorous. Are you currently in a polyamorous relationship (a committed relationship with more than one person, a thrupple)? A. Yes B. No

[IF MainPartner = A, ASK UAVIMain THROUGH PartnerGender, OTHERWISE SKIP TO Druguse]

UAVIMain. How many times have you had anal/vaginal sex without a condom with your main partner in the last 90 days (since date)? A. 0-90+

PartnerAge. What is your main partner’s age? ______

PartnerStatus. What is your main partner’s HIV status?

A. My partner told me he/she is HIV-positive 123

B. I think my partner is HIV-positive C. I don’t know my partner’s HIV status D. I think my partner is HIV-negative E. My partner told me he/she is HIV-negative

[IF PartnerStatus = A, B, ASK PartnerVL, THEN CONTINUE TO PartnerGender]

PartnerVL. Is your main partner’s HIV viral load undetectable? A. Yes B. No C. I don’t know

[IF PartnerStatus = D, E, ASK PartnerPrEP, THEN CONTINUE TO PartnerGender]

PartnerPrEP. Is your main partner on pre-exposure prophylaxis (PrEP)? A. Yes B. No C. I don’t know

PartnerGender. What is your partner’s gender identity? A. Female B. Male C. Transgender male D. Transgender female

DrugUse. Which of the following drugs have you used in the past 90 days (since mm/dd/yyyy)? Select all that apply. A. Marijuana B. Cocaine C. Crack D. Crystal methamphetamine (meth, crystal, tina) E. Heroin F. MDMA, Ecstasy, Molly G. Ketamine (K) H. GHB I. Prescription pain killers (for fun, to get high) J. Other Prescription drugs (for fun, to get high) K. Poppers L. LSD/Mushrooms/PCP M. Other (specify) N. None of the above

Needles. Have you shared needles to inject drugs (e.g. heroin, steroids, crystal)? A. No, never B. Yes, in the last 12 months C. Yes, more than one year ago

124

AlcoholUse. In the past 3 months, how many days would you say you drank 5 or more alcoholic drinks in one sitting? A. 0-90

CigaretteUse. How often to do you smoke cigarettes? A. Never B. A few times a year C. At least once per month D. 2-3 days per month E. 1-2 days per week F. Almost every day or every day

Housing. What is your current living situation? (Check all that apply) A. Alone B. With Roommates C. With Family D. With Partner (spouse, boyfriend, girlfriend) E. Other (Please specify): ______

Income. Which best describes your total yearly income during the last year? A. Less than $10,000 B. $10,000 to $19,999 C. $20,000 to $29,999 D. $30,000 to $39,999 E. $40,000 to $49,999 F. $50,000 to $74,999 G. $75,000 to $99,999 H. $100,000 to $149,999 I. $150,000 to $199,999 J. $200,000 to $249,999 K. $250,000 or more

HousingInstability. Has there been a period of time in your life where you were unstably housed (e.g., couchsurfing, homeless)? A. No B. Yes, within the last 5 years C. Yes, but more than 5 years ago

SexWork3M. In the last 3 months, were you given anything (money, drugs, a place to stay, etc.) in exchange for sex? A. Yes 125

B. No

DigitalCam. Do you have a digital camera (e.g., a phone with a camera or a device capable of taking digital photos)? A. Yes B. No C. I don’t know

[IF DigitalCam = B or C, INELIGIBLE, ALLOW TO FINISH SURVEY BUT END ON INELIGIBLE ASK FOR CONTACT FOR FUTURE RESEARCH]

HIVMail. Would you be willing to have an HIV test kit (in a plain unmarked envelope) mailed to you? (The envelope won’t say “HIV testing” on it or mention that it is from a research study) A. Yes B. No C. I don’t know

[IF HIVMail = B OR C, ASK MailAlt]

MailAlt. If you are unable to receive mail at your home, what if the package was sent to an alternative address (e.g. a friend, relative, workplace) for you to pick up there? A. Yes, I would be able to pick it up B. No, I would not be able to pick it up

MailContact. If you can’t receive mail at home, and don’t have an alternative address, it will be difficult for us to get you the home HIV testing kit, and for you to participate. If you would still like to participate, we can contact you to try to arrange a way for you to get your testing kit. A. Yes, please contact me B. No, I am not able to receive an HIV home testing kit

Recontact. As part of this study, we will want to reach out to you periodically. Would you be willing to give us your contact information so that we could follow up with you in the future? A. Yes B. No

126

APPENDIX B: SECONDARY SURVEY

INTRODUCTION SCREEN

Welcome back! We look forward to having you as a participant in Together 5,000. Today we will ask you to complete an online survey that will take you about 20-30 minutes. For completing this survey, we will send you a $15 gift certificate. You can take breaks from the survey at any time. If you click the link we emailed you, it will take you right back to where you left off. If you have any questions, feel free to call us at 646-499-CUNY (2869) or email us at [email protected].

Demographics BirthMonth. In what month were you born? A. Drop down list of months

BirthYear. In what year were you born? B. Number entry with validation between 1900 and 2017

SexPos. Which sexual position do you identify most as?

A. Top B. Versatile/Top C. Versatile D. Versatile/Bottom E. Bottom F. Not applicable to me

SexWorkYear. Have you exchanged money for sex in the past 12 months? A. No B. Yes, I’ve been paid for sex 127

C. Yes, I have paid for sex D. Yes, I’ve both been paid and have paid for sex

Incarcerated. Have you ever been incarcerated (prison, jail, or juvenile detention)? A. Yes B. No

[DISPLAY YearOut AND RecIncar IF Incarcerated = A]

YearOut. In what year were you released from incarceration? A. (Drop down year list)

Arrested. Have you been arrested at all in the past 3 months?

A. Yes B. No

OtherStudy. Are you currently participating in another HIV research study (e.g. Unite, Keeping it Lite, or Lite)? A. No B. Yes - Unite C. Yes – Keeping it Lite D. Yes – Lite E. Yes, some other study

FirstOral. How old were you when you first had consensual oral sex with a male? A. Text entry validated to at or below current age

FirstAnal. How old were you when you first had consensual anal sex with a male? A. Drop down 0 to 90+

Connor-Davidson Resilience Scale (10 – item)

Instructions: Please read the following statements and indicate how true they are of you.

128

True Not Nearly True Rarely Sometimes Often all the at all True True True Time Resilience1. I am able to adapt to change 0 1 2 3 4

Resilience2. I can deal with whatever 0 1 2 3 4 comes Resilience3. I see the humorous side of 0 1 2 3 4 things Resilience4. Coping with stress 0 1 2 3 4 strengthens me. Resilience5. I tend to bounce back after 0 1 2 3 4 illness or hardship. Resilience6. I can achieve my goals 0 1 2 3 4

Resilience7. Under pressure, I focus and 0 1 2 3 4 think clearly Resilience8. I am not easily discouraged 0 1 2 3 4 by failure Resilience9. I think of myself as a strong 0 1 2 3 4 person Resilience10. I can handle unpleasant 0 1 2 3 4 feelings

129

Multidimensional Peer-Victimization Scale – Current Student How often during the last school year has another student done these things to you? How often during the last school year has another Not at Once More student done these things to you? all than once PVSCurrent1. Punched me PVSCurrent2. Tried to get me into trouble with my friends PVSCurrent3. Called me names PVSCurrent4. Kicked me PVSCurrent5. Tried to make my friends turn against me PVSCurrent6. Made fun of me because of my appearance PVSCurrent7. Hurt me physically in some way PVSCurrent8. Refused to talk to me PVSCurrent9. Made fun of me for some reason PVSCurrent10. Beat me up PVSCurrent11. Made other people not talk to me PVSCurrent12. Swore at me

MissSchool. How often did you miss school in the last year? A. Not at all B. Once C. More than once

VictOnline. How often did these things happen online? A. Not at all B. Once C. More than once

Multidimensional Peer-Victimization Scale – Former Student Think back to when you were in high school. How Not at Once More often did another student do these things to you? all than once PVS1. Punched me PVS2. Tried to get me into trouble with my friends PVS3. Called me names PVS4. Kicked me PVS5. Tried to make my friends turn against me PVS6. Made fun of me because of my appearance PVS7. Hurt me physically in some way PVS8. Refused to talk to me PVS9. Made fun of me for some reason PVS10. Beat me up 130

PVS11. Made other people not talk to me PVS12. Swore at me

MissSchoolRetro. How often did you miss school in the last year that you were in school? D. Not at all E. Once F. More than once

VictOnlineRetro. How often did these things happen online when you were in high school? D. Not at all E. Once F. More than once

131

ASSIST Interview – ACASI Version

ASSIST1

In your life, which of the following substances have you ever used? For prescription medications, please report nonmedical use only. Yes No ASSIST1a. Cannabis (marijuana, pot, grass, hash, etc.) ASSIST1b. Cocaine (coke, crack, etc.) ASSIST1c. Prescription stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.) ASSIST1d. Methamphetamine (speed, crystal meth, tina, ice, etc.) ASSIST1e. Inhalants (poppers, nitrous, glue, gas, paint thinner, etc.) ASSIST1f. Sedatives or Sleeping Pills (Valium, Ativan, Xanax, Klonopin, Librium, Rohypnol, etc.) ASSIST1g. Gamma Hydroxybutyrate (GHB) ASSIST1h. Ecstasy/MDMA/Molly ASSIST1i. LSD/Acid/Mushrooms/PCP (Angel Dust) ASSIST1j. Special K (Ketamine) ASSIST1k. Street opioids (heroin, opium, etc.) ASSIST1l. Prescription opioids (morphine, codeine, fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine [Suboxone], etc.)

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ASSIST 2

In the past three months, how often have you used the substances you mentioned? [DISPLAY ASSIST2a to ASSIST2l IF ASSIST1a,l,… = A] Never Once Monthly Weekly Daily or or twice almost daily ASSIST2a. Cannabis (marijuana, pot, grass, hash, etc.) ASSIST2b. Cocaine (coke, crack, etc.) ASSIST2c. Prescription stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.) ASSIST2d. Methamphetamine (speed, crystal meth, tina, ice, etc.) ASSIST2e. Inhalants (poppers, nitrous, glue, gas, paint thinner, etc.) ASSIST2f. Sedatives or Sleeping Pills (Valium, Ativan, Xanax, Klonopin, Librium, Rohypnol, etc.) ASSIST2g. Gamma Hydroxybutyrate (GHB) ASSIST2h. Ecstasy/MDMA/Molly ASSIST2i. LSD/Acid/Mushrooms/PCP (Angel Dust) ASSIST2j. Special K (Ketamine) ASSIST2k. Street opioids (heroin, opium, etc.) ASSIST2l. Prescription opioids (morphine, codeine, fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine [Suboxone], etc.)

[DISPLAY ASSIST2Stim IF ASSIST2c = B, C, D, or E] ASSIST2Stim. You mentioned that you've used prescription stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.) in the last 3 months. [DISPLAY ASSIST2Stim1 IF ASSIST2Stim IS DISPLAYED] ASSIST2Stim1. Is this a medication that you can buy in the store without a prescription (over the counter)? A. Yes B. No C. Don’t know 133

[DISPLAY ASSIST2Stim2 IF ASSIST2Stim1 = B or C]

ASSIST2Stim2. Was it prescribed for you? A. Yes B. No C. Don’t know [DISPLAY ASSIST2Stim3 AND ASSIST2Stim4 IF ASSIST2Stim2 = B or C] ASSIST2Stim3. Do you ever use MORE of your stimulant medication, that is, take a higher dosage, than is prescribed for you? A. Yes B. No C. Don’t know ASSIST2Stim4. Do you ever use your stimulant medication MORE OFTEN, that is, shorten the time between dosages, than is prescribed for you? A. Yes B. No C. Don’t know [DISPLAY ASSIST2Sed IF ASSIST2f = B, C, D, or E] ASSIST2Sed. You mentioned that you've used sedatives or sleeping pills (Valium, Ativan, Xanax, Klonopin, Librium, Rohypnol, etc.) in the last 3 months. [DISPLAY ASSIST2Sed1 IF ASSIST2Sed IS DISPLAYED] ASSIST2Sed1. Is this a medication that you can buy in the store without a prescription (over the counter)? A. Yes B. No C. Don’t know [DISPLAY ASSIST2Sed2 IF ASSIST2Sed1 = B or C] ASSIST2Sed2. Was it prescribed for you? A. Yes B. No C. Don’t know [DISPLAY ASSIST2Sed3 AND ASSIST2Sed4 IF ASSIST2Sed2 = B or C] ASSIST2Sed3. Do you ever use MORE of your sedatives or sleeping pills, that is, take a higher dosage, than is prescribed for you? A. Yes 134

B. No C. Don’t know ASSIST2Sed4. Do you ever use your sedatives or sleeping pills MORE OFTEN, that is, shorten the time between dosages, than is prescribed for you? A. Yes B. No C. Don’t know [DISPLAY ASSIST2PrOpi IF ASSIST2l = B, C, D, or E] ASSIST2PrOpi. You mentioned that you've used prescription opioids (morphine, codeine, fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine [Suboxone], etc.) in the last 3 months. [DISPLAY ASSIST2PrOpi1 IF ASSIST2PrOpi IS DISPLAYED] ASSIST2PrOpi1. Is this a medication that you can buy in the store without a prescription (over the counter)? D. Yes E. No F. Don’t know [DISPLAY ASSIST2PrOpi2 IF ASSIST2PrOpi1 = B or C] ASSIST2PrOpi2. Was it prescribed for you? D. Yes E. No F. Don’t know [DISPLAY ASSIST2PrOpi3 AND ASSIST2PrOpi4 IF ASSIST2PrOpi2 = B or C] ASSIST2PrOpi3. Do you ever use MORE of your opioid medication, that is, take a higher dosage, than is prescribed for you? D. Yes E. No F. Don’t know ASSIST2PrOpi4. Do you ever use your opioid medication MORE OFTEN, that is, shorten the time between dosages, than is prescribed for you? D. Yes E. No F. Don’t know

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ASSIST3 During the past three months, how often have you had a strong desire or urge to use the following? [DISPLAY ASSIST3a to ASSIST3l IF ASSIST2a,l,… = B, C, D, or E] Never Once Monthly Weekly Daily or or twice almost daily ASSIST3a. Cannabis (marijuana, pot, grass, hash, etc.) ASSIST3b. Cocaine (coke, crack, etc.) ASSIST3c. Prescription stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.) ASSIST3d. Methamphetamine (speed, crystal meth, tina, ice, etc.) ASSIST3e. Inhalants (poppers, nitrous, glue, gas, paint thinner, etc.) ASSIST3f. Sedatives or Sleeping Pills (Valium, Ativan, Xanax, Klonopin, Librium, Rohypnol, etc.) ASSIST3g. Gamma Hydroxybutyrate (GHB) ASSIST3h. Ecstasy/MDMA/Molly ASSIST3i. LSD/Acid/Mushrooms/PCP (Angel Dust) ASSIST3j. Special K (Ketamine) ASSIST3k. Street opioids (heroin, opium, etc.) ASSIST3l. Prescription opioids (morphine, codeine, fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine [Suboxone], etc.)

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ASSIST4 During the past three months, how often has your use of the following substances led to health, social, legal, or financial problems? [DISPLAY ASSIST4a to ASSIST4l IF ASSIST2a,l,… = B, C, D, or E] Never Once Monthly Weekly Daily or or twice almost daily ASSIST4a. Cannabis (marijuana, pot, grass, hash, etc.) ASSIST4b. Cocaine (coke, crack, etc.) ASSIST4c. Prescription stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.) ASSIST4d. Methamphetamine (speed, crystal meth, tina, ice, etc.) ASSIST4e. Inhalants (poppers, nitrous, glue, gas, paint thinner, etc.) ASSIST4f. Sedatives or Sleeping Pills (Valium, Ativan, Xanax, Klonopin, Librium, Rohypnol, etc.) ASSIST4g. Gamma Hydroxybutyrate (GHB) ASSIST4h. Ecstasy/MDMA/Molly ASSIST4i. LSD/Acid/Mushrooms/PCP (Angel Dust) ASSIST4j. Special K (Ketamine) ASSIST4k. Street opioids (heroin, opium, etc.) ASSIST4l. Prescription opioids (morphine, codeine, fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine [Suboxone], etc.)

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ASSIST 5 During the past three months, how often have you failed to do what was normally expected of you because of your use of the following substances? [DISPLAY ASSIST5a to ASSIST5l IF ASSIST2a,l,… = B, C, D, or E] Never Once Monthly Weekly Daily or or twice almost daily ASSIST5a. Cannabis (marijuana, pot, grass, hash, etc.) ASSIST5b. Cocaine (coke, crack, etc.) ASSIST5c. Prescription stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.) ASSIST5d. Methamphetamine (speed, crystal meth, tina, ice, etc.) ASSIST5e. Inhalants (poppers, nitrous, glue, gas, paint thinner, etc.) ASSIST5f. Sedatives or Sleeping Pills (Valium, Ativan, Xanax, Klonopin, Librium, Rohypnol, etc.) ASSIST5g. Gamma Hydroxybutyrate (GHB) ASSIST5h. Ecstasy/MDMA/Molly ASSIST5i. LSD/Acid/Mushrooms/PCP (Angel Dust) ASSIST5j. Special K (Ketamine) ASSIST5k. Street opioids (heroin, opium, etc.) ASSIST5l. Prescription opioids (morphine, codeine, fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine [Suboxone], etc.)

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ASSIST 6 Has a friend or relative or anyone else ever expressed concern about your use of the following substances? [DISPLAY ASSIST6a to ASSIST6l IF ASSIST1a,l,… = A] No, Yes, in Yes, but never the not in past 3 the past months 3 months ASSIST6a. Cannabis (marijuana, pot, grass, hash, etc.) ASSIST6b. Cocaine (coke, crack, etc.) ASSIST6c. Prescription stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.) ASSIST6d. Methamphetamine (speed, crystal meth, tina, ice, etc.) ASSIST6e. Inhalants (poppers, nitrous, glue, gas, paint thinner, etc.) ASSIST6f. Sedatives or Sleeping Pills (Valium, Ativan, Xanax, Klonopin, Librium, Rohypnol, etc.) ASSIST6g. Gamma Hydroxybutyrate (GHB) ASSIST6h. Ecstasy/MDMA/Molly ASSIST6i. LSD/Acid/Mushrooms/PCP (Angel Dust) ASSIST6j. Special K (Ketamine) ASSIST6k. Street opioids (heroin, opium, etc.) ASSIST6l. Prescription opioids (morphine, codeine, fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine [Suboxone], etc.)

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ASSIST7 Have you ever tried and failed to control, cut down or stop using the following substances? [DISPLAY ASSIST7a to ASSIST7l IF ASSIST1a,l,… = A] No, Yes, in Yes, but never the not in past 3 the past months 3 months ASSIST7a. Cannabis (marijuana, pot, grass, hash, etc.) ASSIST7b. Cocaine (coke, crack, etc.) ASSIST7c. Prescription stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.) ASSIST7d. Methamphetamine (speed, crystal meth, tina, ice, etc.) ASSIST7e. Inhalants (poppers, nitrous, glue, gas, paint thinner, etc.) ASSIST7f. Sedatives or Sleeping Pills (Valium, Ativan, Xanax, Klonopin, Librium, Rohypnol, etc.) ASSIST7g. Gamma Hydroxybutyrate (GHB) ASSIST7h. Ecstasy/MDMA/Molly ASSIST7i. LSD/Acid/Mushrooms/PCP (Angel Dust) ASSIST7j. Special K (Ketamine) ASSIST7k. Street opioids (heroin, opium, etc.) ASSIST7l. Prescription opioids (morphine, codeine, fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine [Suboxone], etc.)

ASSIST 8 Assist8a. Have you ever used any drug by injection (recreational on non-medical use only)? A. No, never B. Yes, in the past 3 months C. Yes, but not in the past 3 months [DISPLAY Assist8b IF Assist8a = B] Assist8b. In the past 3 months, how often have you injected drugs (recreational on nonmedical use only)? A. Once per week or less B. More than once per week

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The Alcohol Use Disorder Identification Test (AUDIT) The following questions will be about alcohol use and a “standard drink.” A standard drink is one 12oz can of beer, one glass of wine, or the equivalent of one shot of hard alcohol. AUDIT1. How often do you have a drink containing alcohol? A. Never B. Monthly or less C. 2-4 times a month D. 2-3 times a week E. 4 or more times a week AUDIT2. How many drinks containing alcohol do you have on a typical day when you are drinking? A. 1 or 2 B. 2 or 4 C. 5 or 6 D. 7 to 9 E. 10 or more AUDIT3. How often do you have six or more drinks on one occasion? A. Never B. Less than monthly C. Monthly D. Weekly E. Daily or almost daily AUDIT4. How often during the last year have you found that you were not able to stop drinking once you had started? A. Never B. Less than monthly C. Monthly D. Weekly E. Daily or almost daily AUDIT5. How often during the lastyear have you failed to do what was normally expected of you because of drinking? A. Never B. Less than monthly C. Monthly D. Weekly E. Daily or almost daily AUDIT6. How often during the last year have you needed a first drink in the morning to get yourself going after a heavy drinking session ? A. Never 141

B. Less than monthly C. Monthly D. Weekly E. Daily or almost daily AUDIT7. How often during the last year have you had a feeling of guilt or remorse after drinking? A. Never B. Less than monthly C. Monthly D. Weekly E. Daily or almost daily AUDIT8. How often during the last year have you been unable to remember what happened the night before because of your drinking? A. Never B. Less than monthly C. Monthly D. Weekly E. Daily or almost daily

AUDIT9. Have you or someone else been injured because of your drinking? A. No B. Yes, but not in the last year C. Yes, during the last year AUDIT10. Has a relative, friend, doctor, or other health care worker been concerned about your drinking or suggested you cut down? A. No B. Yes, but not in the last year C. Yes, during the last year

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GAD/PHQ Over the last 2 weeks, how often were you bothered Not Several More Nearly by… at all days than every half the day days Feeling nervous, anxious, or on edge? Not being able to stop or control worrying? Little interest or pleasure in doing things? Feeling down, depressed or hopeless?

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Internalized Homophobia Scale

Instructions: Please read the following statements about being gay or bisexual and indicate your level of agreement from strongly disagree to strongly agree.

Strongly Strongly

Disagree Disagree Agree Agree IHS1. I often feel it is best to avoid personal or social 1 2 3 4 involvement with other gay/bisexual men IHS2. I have tried to stop being attracted to men in 1 2 3 4 general IHS3. If someone offered me the chance to be 1 2 3 4 completely heterosexual, I would accept the chance IHS4. I wish I weren’t gay/bisexual 1 2 3 4 IHS5. I feel alienated from myself because of being 1 2 3 4 gay/bisexual IHS6. I wish that I could develop more erotic feelings 1 2 3 4 about women IHS7. I feel that being gay/bisexual is a personal 1 2 3 4 shortcoming for me IHS8. I would like to get professional help in order to change my sexual orientation from gay/bisexual to 1 2 3 4 straight IHS9. I have tried to become more sexually attracted 1 2 3 4 to women IHS10. Most gay/bi men are too promiscuous 1 2 3 4 IHS11. I think it’s sad when I see older men who still go to gay events and haven’t “settled down” with 1 2 3 4 someone yet IHS12. I think men who are “effeminate” give a bad 1 2 3 4 name to other gay/bi men IHS13. I like to associate with guys who describe 1 2 3 4 themselves as “straight-acting” IHS14. I think it’s important for different gay “scenes” 1 2 3 4 to all be represented

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Access To- and Use of GLBT-Affirmative Resources and Policies

In the last 6 months, how often did you visit a nearby… Once 3 to 6 to More Never or 5 10 than 10 twice times times times GRPVisit1. LGBT community center? A B C D E GRPVisit2. LGBT “friendly” health care provider or A B C D E facility? GRPVisit3. Gay (LGBT) bar or club? A B C D E GRPVisit4. Gay Bathhouse? A B C D E GRPVisit5. Gay (LGBT) coffee shop or bookstore? A B C D E GRPVisit6. LGBT “friendly” place of worship? A B C D E GRPVisit7. Any other type of LGBT “friendly” space A B C D E (like an ongoing club/meeting/group)?

[DISPLAY GRPVisit7a IF GRPVisit7 = B, C, D, or E] GRPVisit7a. Can you tell me a little bit more about this club/meeting/group? A. ______

HealthInsurance. Do you have health insurance? A. Yes B. No C. I don’t know [IF BYM(Year) > 1991 DISPLAY InsureParent] InsureParent. Do you have health insurance from your parents/guardian? A. Yes B. No C. I don’t know

SamSexMarr. Have you had a same-sex marriage (i.e., marriage license), civil union, or registered domestic partnership? A. Yes B. No C. No, but I have had a commitment ceremony (but there was no official paperwork from a government entity)

PrimCare. Do you have someone that you consider your primary care provider (a doctor)? A. Yes B. No [DISPLAY PrimCareSexMen IF PrimCare = A] 145

PrimCareSexMen. Does she or he know that you have sex with men? A. Yes B. No

PosKnow. How many HIV-positive people do you know? A. Drop down 0-90+

Pre-Exposure Prophylaxis (PrEP)

Instructions: PrEP (pre-exposure prophylaxis) is a new biochemical strategy to prevent HIV infection. PrEP involves HIV-negative guys taking anti-HIV medications (for example, Truvada) once a day, every day to reduce the likelihood of HIV infection if they were exposed to the virus. PrEP is highly effective to reduce the likelihood of HIV infection.

Please note that PrEP is not the same as taking HIV medications for a brief period of time (i.e., 28 days) after a high risk exposure to HIV through encounters such as being stuck by a contaminated needle or having unprotected intercourse. PrEP is intended for regular, long-term use.

HearPrEP. Where did you first hear about PrEP? A. As part of this study B. As part of my participation in a different research study C. Through a news media source D. Through a social media source E. Through a friend F. Through my main partner G. Through a casual sex partner H. Through a family member I. Through a medical provider J. Through a community-based agency K. Other (Please describe): ______L. I don’t remember

PrEPview. What source has had the biggest influence on your current views about PrEP? a. As part of this study b. As part of my participation in a different research study c. Through a news media source d. Through a social media source e. Through a friend f. Through my main partner g. Through a casual sex partner h. Through a family member i. Through a medical provider j. Through a community-based agency k. Other (Please describe): ______l. I don’t remember 146

SpokDocPrEP. Have you ever spoken to a medical provider about starting PrEP?

A. No, I have not ever spoken to a provider about starting PrEP B. Yes, and we both decided it was a good option for me and I should start PrEP C. Yes, and we both decided it might be a good option but to wait before beginning PrEP D. Yes, and we both decided it was not a good option for me E. Yes, and the provider was not comfortable prescribing PrEP for me F. Yes, and the provider thought it was a good option but I chose not to do it

[DISPLAY PrEPNotSpok IF SpokDocPrEP = A]

PrEPNotSpok. What are the reasons you have not yet spoken to a medical provider about PrEP? Check all that apply.

A. I did not know what PrEP was B. I am unsure if I am at high enough risk for HIV C. I don’t have a way to pay for it D. I haven’t don’t have access to a medical provider who will prescribe it E. I haven’t seen my medical provider recently F. I haven’t told my medical provider that I am gay/bi/trans G. I am concerned about talking to my medical provider about my sex life H. I am concerned about PrEP side effects I. I prefer to use condoms. J. Other (Please specify):______

PrEPCand. Do you believe that you are currently an appropriate candidate for PrEP?

A. Yes, I am definitely an appropriate candidate for PrEP B. Yes, I think I am an appropriate candidate for PrEP C. I’m not sure if I am an appropriate candidate for PrEP D. No, I don’t think I am an appropriate candidate for PrEP E. No, I am definitely not an appropriate candidate for PrEP

PrEPFav. In general, I would say the people I am close with:

A. Are in favor of PrEP B. Are opposed to PrEP C. Are split evenly between being in favor of and being opposed to PrEP D. Don’t have strong opinions either way E. Don’t really know what PrEP is

PrEPLike. Research shows that PrEP is at least 90% effective in preventing HIV when taken daily. How likely would you be to take PrEP if it were available for free?

A. I would definitely take it B. I would probably take it 147

C. I might take it D. I would probably not take it E. I would definitely not take it

PrEPPlan. PrEP is currently available with a prescription from your doctor, and research has shown that a majority of insurance companies cover most or all of the costs of PrEP. Do you plan to begin PrEP?

A. Yes, I will definitely begin taking PrEP B. Yes, I will probably begin taking PrEP C. I’m not sure – I might begin taking PrEP D. No, I probably will not begin taking PrEP E. No, I definitely will not begin taking PrEP

[DISPLAY PrEPSoon IF PrEPPlan = A or B] PrEPSoon. How soon do you plan to begin taking PrEP?

A. Within the next month B. Within the next 2-3 months C. Within the next 4-6 months D. Within the next 7 months to a year E. More than a year from now

[DISPLAY PrEPReas if PrEPPlan = C, D, or E]

PrEPReas. What are the reasons you do not intend to begin PrEP? Check all that apply:

A. I’m not at high enough risk for HIV B. I don’t have a way to pay for it C. I don’t have access to a medical provider who will prescribe it D. I don’t believe it works well enough E. I am too concerned about PrEP side effects F. I prefer to use condoms G. I don’t want people to think I am HIV-positive H. I don’t want to risk being stigmatized for taking PrEP I. Other (Please specify): ______

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Instructions: Current guidelines recommend that individuals on PrEP return to a medical provider every 3 months for HIV/STI testing, bloodwork, and a new 3-month prescription. PrEPComPresc. Suppose that you were interested in getting a new prescription for PrEP – do you have or know of a medical provider that you would feel comfortable asking to prescribe it for you? A. Yes, I definitely have or know of a provider B. Yes, I probably have or know of a provider C. No, I probably do not have or know of a provider D. No, I definitely do not have or know of a provider

PrEPComRec. Suppose that you were interested in getting a new prescription for PrEP – where would you feel most comfortable receiving your PrEP-related medical care and prescriptions?

A. My primary care provider (my regular doctor) B. A clinic specializing in HIV-related care (e.g., an HIV clinic) C. A clinic specializing in sexual health (e.g., a Planned Parenthood, an STD clinic) D. A clinic specializing in LGBT health care E. Other (Please specify): ______

AttentionCheck. This question is to check whether you are paying attention. If you are reading this, please select “Strongly agree.”

A. Strongly disagree B. Disagree C. Agree D. Strongly agree

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Barriers to PrEP Uptake Instructions: For the following list of items, please rate how important they are to you in making your decision whether to take, or continue taking, PrEP. When thinking about whether to take/continue Not at all A little Very Concerned PrEP, how concerned are you about… concerned concerned concerned BarrPrEP1. The long-term effects of PrEP on 1 2 3 4 my health? BarrPrEP2. Potential side effects of PrEP? 1 2 3 4 BarrPrEP3. The possibility that if I were to become HIV+, certain medications might no 1 2 3 4 longer work or I might be resistant? BarrPrEP4. The possibility that PrEP might not 1 2 3 4 provide complete protection against HIV? BarrPrEP5. Having to return for medical check- 1 2 3 4 ups every 3 months while I am on PrEP? BarrPrEP6. Bringing up the topic of PrEP with a 1 2 3 4 doctor? BarrPrEP7. Having to talk to a doctor about 1 2 3 4 your sex life? BarrPrEP8. Having to remember to take PrEP 1 2 3 4 every day? BarrPrEP9. Friends finding out that you are on 1 2 3 4 PrEP? BarrPrEP10. Family finding out that you are on 1 2 3 4 PrEP? BarrPrEP11. Sexual partners finding out that 1 2 3 4 you are on PrEP? BarrPrEP12. The way that men on PrEP are 1 2 3 4 portrayed in the media? BarrPrEP13. The way that other gay/bi men talk 1 2 3 4 about guys on PrEP? BarrPrEP14. Listing PrEP as one of your current medications during appointments such as at a 1 2 3 4 dentist’s or specialist’s office?

BarrPrEPOther. Are there any other factors that you think prevent yourself or other guys from getting on PrEP? (Please describe): ______150

Partner Violence Questionnaire

Instructions: Intimate relationships are characterized by many different feelings and behaviors. Sometimes relationships involve unwanted physical or emotional violence.

In the past five years/12 months has a boyfriend or partner... No Yes PartVioRec1. Hit you with fists or an open hand? PartVioRec2. Thrown something at you? PartVioRec3. Verbally threatened you in any way? PartVioRec4. Verbally demeaned you in front of strangers? PartVioRec5. Pushed or shoved you? PartVioRec6. Forced you to get high or drunk? PartVioRec7. Made fun of your appearance? PartVioRec8. Forced you to have sex? PartVioRec9. Kicked you? PartVioRec10. Hit you with an object? PartVioRec11. Damaged or destroyed your property? PartVioRec12. Stalked you?

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Childhood Sexual Abuse ChildForce. When you were age 16 or younger, was there ever a time when you were forced or frightened by another person to do something sexual with them when you didn’t want to? A. Yes B. No [DISPLAY ForcePartAge, AgeFirstTime, ManyTimes, and MorePersons IF ChildForce = A] ForcePartAge. The first time that this happened, how old was this partner? A. 5+ years younger than I was B. Around the same age as I was C. 5-9 years older than me D. 10+ years older than me E. Not sure

AgeFirstTime. How old were you the first time this happened? A. Drop down 1-16 ManyTimes. How many times did this happen before you turned 17? A. Text entry 0-999 MorePersons. Did this ever happen with more than one person? A. Yes B. No HCV Risk Score

Please answer yes or no to the following questions: Yes No HCV1. Have you engaged in condomless receptive anal sex (bareback bottomed) in the last 6 months? HCV2. Have you shared anal sex toys (e.g., dildos) with a partner without washing it first in the last 6 months? HCV3. Have you engaged in fisting without the use of a protective glove (either as a fister or fistee) in the last 6 months? HCV4. Have you recreationally (to get high) injected drugs in the last 12 months? HCV5. Have you shared a straw to snort drugs in the last 12 months? HCV6. Have you had syphilis, genital herpes (outbreak) or lymphogranuloma venereum (LGV) in the last 12 months?

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Multidimensional Scale of Perceived Social Support

Instructions: We are interested in how you feel about the following statements. Read each statement carefully. Indicate how much you agree with each statement.

Very Very Strongly Strongly Mildly Mildly Strongl Strongl Disagree Disagree Disagree Agree y Agree y Agree PerSocSup1. There is a special 1 2 3 4 5 6 person who is around when I am in need. PerSocSup2. There is a special 1 2 3 4 5 6 person with whom I can share my joys and sorrows. PerSocSup3. My family really 1 2 3 4 5 6 tries to help me. PerSocSup4. I get the emotional 1 2 3 4 5 6 help and support I need from my family. PerSocSup5. I have a special 1 2 3 4 5 6 person who is a real source of comfort to me. PerSocSup6. My friends really 1 2 3 4 5 6 try to help me. PerSocSup7. I can count on my 1 2 3 4 5 6 friends when things go wrong. PerSocSup8. I can talk about 1 2 3 4 5 6 my problems with my family. PerSocSup9. I have friends with 1 2 3 4 5 6 whom I can share my joys and sorrows. PerSocSup10. There is a special 1 2 3 4 5 6 person in my life who cares about my feelings. PerSocSup11. My family is 1 2 3 4 5 6 willing to help me make decisions. PerSocSup12. I can talk about 1 2 3 4 5 6 my problems with my friends.

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APPENDIX C: INTERVIEW GUIDE

I want to thank you for taking the time to talk with me today. I really appreciate your willingness to speak with me during what I imagine is a stressful time. Receiving an HIV- positive test result is often a surprise for people, and there are many emotions that you might be experiencing right now—anger, fear, sadness, shame, etc. Everything we discuss today will be confidential. This phone call will be recorded. Later it will be transcribed into text and the recording will be deleted. We’ll probably talk for around 30 to 45 minutes and we’ll send you a $40 Amazon gift card for your time. I’ll send it to you as soon as we get off the phone. I’m legally required to tell you that during our conversation if you tell me that you plan to hurt yourself or someone else, I will have to break confidentiality in order to protect you or someone else.

The goal for this conversation is to learn more about you and your experiences. I know that some of these questions might be difficult to talk about. You don’t have to talk about anything that you don’t want to. You can just say “pass” and we will move on. We can also stop the interview at any time or stop to take a break whenever you need to. I also want to make sure that you’re in a place where you can talk openly, and others won’t be around to hear you.

• Do you have any questions? Can we start the interview?

1. First, I want to talk a little bit about the test results you received. The results indicated a preliminary positive result and we told you that you needed to get confirmatory testing. Have you been able to get that confirmatory testing? a. [Probe for specifics.] b. [If they have been tested] i. Ok great. Can you tell me a little more about it? ii. So where did you go to get tested? iii. Have you been connected to treatment? iv. And how soon after the diagnosis were you able to get connected to a treatment provider? v. And was there a delay in actually getting treated? Starting medications? 1. About how long have you been taking the meds? 2. Has your Dr. scheduled a follow up appointment with you? vi. Can you tell me more about your experience starting up with treatment and care? vii. What has been easy? viii. What has been difficult? c. Do you have a case manager that has been helping you get through this stuff? d. [If they haven’t been tested yet] i. Can you tell me more about why you haven’t been tested yet? ii. Is there someone you could go to get tested? Do you have a doctor? Is there a place nearby? iii. Tell me what you know about them? Do they have a good reputation in the community? Would you feel comfortable going to them? iv. When do you think that you might go, if at all? 154

v. Are the reasons things like the timing of the appointment, or it’s too far, or things like that? vi. [Tell them you can provide some referrals to find a provider.]

2. Have you talked to anyone about your result? a. Is there someone you trust who you could talk to about your test result? b. [If yes] i. Who did you tell? Was it a roommate/friend/partner…? ii. Can you tell me about how that went? c. [If no] i. Do you think you might tell anyone in the future? ii. How do you hope that that conversation might go? d. In your opinion, what makes a person “safe” to talk to about this?

3. Can you tell me how much you knew about HIV prior to joining this study? a. What have you learned since joining the study?

4. Before joining this study, what did you think your HIV status was? a. What experiences did you have that led you to think that?

5. Before you tested for HIV with our study, when was the last time you had an HIV test? a. [If never/more than a year ago] i. Had you thought about getting an HIV test before/since then? ii. What happened to make you consider being tested? iii. What made it difficult for you to get tested? b. When you were last tested, what did the counselor tell you about HIV prevention? What did they tell you about PrEP? c. Where did you get tested? What made you decide to get tested then/there?

6. When was the last time you were tested for STDs other than HIV? a. Where did you get tested? What made you decide to get tested then/there? Do you remember if you tested positive for any of STDs at that time? What type of treatment did you receive, if any? b. If never/more than a year ago: Had you thought about getting tested for STDs before/since then? What happened to make you consider being testing? What made it difficult for you to get tested? c. When you got tested for STDs, What did the provider tell you about HIV prevention? Did they mentioned PrEP? What did they tell you about PrEP?

7. Have you ever taken PrEP – or pre-exposure prophylaxis (Truvada)? a. If yes, can you tell me a little bit about what that was like? When was it, where did you go to get it, how did you decide that you wanted to use PrEP, why/when did you stop taking it? b. If no, have you heard of PrEP before? How much do you know about PrEP? Do you know of any places near you that provide PrEP? 155

c. Have you heard anything about side effects or how effective it is or anything like that?

8. Do you know what PEP - or post-exposure prophylaxis? d. How much do you know about PEP? e. Have you ever taken PEP? f. Do you know of any places near you that provide PEP? g. [If haven’t heard of] PEP is taking pills after being exposed to HIV for a month to prevent an HIV infection. h. [If yes] Can you tell me a little bit about what that was like? When was it, where did you go to get it, how did you decide that you needed to use PEP…

9. Do you have any thoughts about how you might have gotten HIV?

10. So the delivery of HIV test results over the phone is a new thing for the field. How did it go for you? i. Is there anything you think we could have done better? j. Is there anything you’re concerned with about the process?

11. One of the goals of this project is to try to improve HIV prevention and care services. You described XYZ problems, what could have been done to make your experience better? k. What could have been done to solve those problems? l. What do you think would help you and other gay men? m. What do you think are the problems with the system as a whole? n. What do you think would make HIV prevention and care services better or more accessible for people like you?