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Couch-surfing among youth experiencing homelessness: an examination of HIV risk

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Couch-surfing among youth experiencing homelessness: an examination of HIV risk

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Content COUCH-SURFING AMONG YOUTH EXPERIENCING HOMELESSNESS:
AN EXAMINATION OF HIV RISK
by
Laura Petry
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(SOCIAL WORK)
August 2024
Copyright 2024 Laura Petry

ii
DEDICATION
For every young person who was ever told
they weren’t “homeless enough”

iii
ACKNOWLEDGMENTS
To my mentor, Dr. Eric Rice: It will be impossible for me to ever adequately express how
profoundly grateful I am for you—and never will I escape an attempt with a dry eye.1 I first
encountered your work twelve years ago while I was sitting behind my desk as a case manager in
a transitional housing program, barely older than the youth who lived there. I never would have
imagined you would take me under your wing and forever change how I see myself in this world
and in this work. Thank you for believing in me, and for showing up for me even when I had
trouble showing up for myself. Thank you for your boundless support and the tremendous grace
you afforded me in this journey; without it, I simply would not have made it.
To my dissertation committee members, Dr. Benjamin Henwood and Dr. Phebe Vayanos:
Thank you for always providing such thoughtful, incisive guidance and for helping to push me
and this work just that much further. And to Dr. Jordan Davis, a key collaborator in this study:
Thank you for being patient with me while I found my sea legs.
To the young people who participated in this research: I will be forever indebted to you.
Thank you for entrusting me with your stories; I promise they will, in some way, move the
needle forward. I am deeply grateful for the community partners who enabled me to hear you.
Erin Casey and Danielle Rutledge at My Friend’s Place and Orville Ranglin and Jermaine
Strickland at the Los Angeles LGBT Center were integral to coordinating the qualitative arm of
this research and I appreciate you all so much. I must also give very special thanks to Heather
Carmichael at My Friend’s Place and Kris Nameth at the Los Angeles LGBT Center for
supporting me since my days as civil servant ablaze over our local youth counts, and for now
making this research happen.
1 Not even this one!

iv
I am also incredibly grateful to the National Institute of Mental Health for the predoctoral
fellowship award that supported this dissertation and sent the message that these young people
very much do count in our work to address youth homelessness. In addition to my dissertation
committee and study collaborators, I am beholden to many others who so graciously supported a
submission that nearly didn’t happen (but that I am very glad did). To Dr. Larry Palinkas, Dr.
Michael Hurlburt, Dr. Suzanne Wenzel, and Dr. Norweeta Milburn: Thank you for riding the
wave with me and remaining steadfast in your support of me and this work.
There were many interactions with fellow doctoral students throughout this endeavor, big
and small, that brought much-needed reprieve, camaraderie, and hope. To Dr. Sara Semborski,
Dr. Graham DiGuiseppi, Shaddy Saba, Ronna Bañada, and Corinne Zachry: Thank you for the
time, generosity, and support you all offered me. To Rory O’Brien: Thank you for your belly-fire,
for your encouragement, and for always reminding me to center what truly matters. And to Olga
Koumoundouros: Thank you for helping to reignite a flame, and for giving me such a precious
space to wrestle with messy ideas and even messier feelings.
To Dr. Coco Auerswald: Thank you for so radically altering my trajectory over a decade
ago, and for continuing to pour such unbridled support into me. I cannot begin to tell you what it
means to me that our paths ever crossed.
To my dearest friend, Dan: Our friendship is the most sacred relationship in my life. Or at
least, it is second only to the one I share with the cat. Thank you for keeping me laughing
throughout this herculean undertaking. And for serving as the dutiful recipient of (too) many
neurotic texts and Simpsons memes. Your love and support mean the world to me, and I would
move mountains to return a sliver of the kindness and care you have extended my way. Thank
you for everything.

v
Finally, to my beloved cat, Zora: Thank you for bounding into my world as the most
wonderfully instant ‘foster fail’ that ever foster failed. You were a powerful source of comfort
and light amidst very difficult times, and I simply cannot imagine being here without you. Thank
you for filling my days with meows, mrraps, purrs, and trills, and for the immeasurable joy you
bring.

vi
TABLE OF CONTENTS
Dedication....................................................................................................................................... ii
Acknowledgments..........................................................................................................................iii
List of Tables................................................................................................................................viii
Abbreviations.................................................................................................................................. x
Abstract........................................................................................................................................... x
Chapter 1. An Introduction to Couch-surfing Among Youth Experiencing Homelessness.......... 1
Overview of the Dissertation ........................................................................... 21
Chapter 2. Associations Between Couch-surfing, Social Support, and HIV Risk:
An Egocentric Network Analysis................................................................................. 24
Introduction...................................................................................................... 24
Methods............................................................................................................ 32
Results.............................................................................................................. 38
Discussion ........................................................................................................ 47
Chapter 3. Couch-surfing and Social Support Typologies Associated with HIV-related
Behavior: A Latent Class Analysis.............................................................................. 54
Introduction...................................................................................................... 54
Methods............................................................................................................ 60
Results.............................................................................................................. 68

vii
Discussion ........................................................................................................ 79
Chapter 4. At the Intersection of Couch-surfing, Social Support, and Transactional Sex:
A Qualitative Study..................................................................................................... 86
Introduction...................................................................................................... 86
Methods............................................................................................................ 91
Results.............................................................................................................. 94
Discussion .......................................................................................................111
Chapter 5. A Discussion of Implications for Youth Who Are Couch-surfing: Practice,
Policy, and Research .................................................................................................. 120
References................................................................................................................................... 130

viii
LIST OF TABLES
Table 1.1 Definitions of homelessness used by federal agencies in addressing youth
homelessness................................................................................................................... 7
Table 1.2 Categories of homelessness used by HUD ................................................................... 16
Table 2.1 Characteristics of youth experiencing homelessness, by living situation..................... 40
Table 2.2 HIV risk and prevention behaviors and sources of social support among youth
experiencing homelessness, by current living situation................................................ 42
Table 2.3 Bivariate analysis of odds of engaging in HIV-related behaviors................................. 44
Table 2.4 Interaction effects between social support and living situation and their association
with condomless sex ..................................................................................................... 45
Table 2.5 Interaction effects between social support and living situation and their association
with transactional sex.................................................................................................... 46
Table 2.6 Multivariable logistic regression model of factors associated with
transactional sex............................................................................................................ 47
Table 3.1 Sample characteristics of youth experiencing homelessness........................................ 69
Table 3.2 Fit indices for latent class models................................................................................. 71
Table 3.3 Demographic characteristics of class membership ....................................................... 74
Table 3 4 Correlates of class membership .................................................................................... 75
Table 3.5 Relationship between class membership and engagement in HIV-related
behaviors....................................................................................................................... 76
Table 3.6 Odds of engagement in HIV risk and prevention behaviors in the past 30 days
based on class membership........................................................................................... 78
Table 4.1 Interview participant characteristics ............................................................................. 95

ix
LIST OF FIGURES
Figure 3.1 Model for latent class analysis .................................................................................... 67
Figure 3.2 Conditional probabilities of class membership ........................................................... 73
Figure 4.1 A conceptual model of the relationship between couch-surfing, social support, and
transactional sex among youth experiencing homelessness ........................................ 98

x
ABBREVIATIONS
aBIC Adjusted Bayesian Information Criteria
BIC Bayesian Information Criteria
BLRT Bootstrapped Likelihood Ratio Test
CDC Centers for Disease Control and Prevention
CoC Continuum of Care
ED U.S. Department of Education
EHCY Education for Homeless Children and Youth
HAP Homeless Assistance Programs
HCYA Homeless Children and Youth Act
HEARTH Homeless Emergency Assistance and Rapid Transition to Housing Act
HIV Human Immunodeficiency Virus
HHS U.S. Department of Health and Human Services
HUD U.S. Department of Housing and Urban Development
HYH Have You Heard?
LCA Latent Class Analysis
LGBTQ+ Lesbian, Gay, Bisexual, Transgender, Queer, and other sexual and gender
minorities
LGBQ+ Lesbian, Gay, Bisexual, Queer, and other sexual minorities
LMR Lo-Mendell-Rubin Adjusted Likelihood Ratio Test
PIT Point-in-Time Count
PrEP Pre-exposure Prophylaxis
PSH Permanent Supportive Housing

xi
RRH Rapid Re-housing
RHYA Runaway and Homeless Youth Act
TLFB Timeline Follow-back
VLRT Vuong-Lo-Mendell-Rubin Likelihood Ratio Test
YEH Youth Experiencing Homelessness
YHDP Youth Homelessness Demonstration Program

x
ABSTRACT
“Couch-surfing” is nearly four times more prevalent than living on the streets or residing in
temporary shelter programs among youth experiencing homelessness (YEH). Yet there persists a
lack of research on couch-surfing YEH, who are precluded from accessing many resources
through current homeless services systems simply because of their living situation. Examining
how couch-surfing may relate to specific vulnerabilities, including HIV risk, is critical to better
understanding this phenomenon and to improving U.S. policy responses to youth homelessness.
Key to this examination is the role of young people’s social support networks, given their
particular importance in facilitating couch-surfing arrangements and in influencing various
sexual health behaviors. This dissertation endeavors to explore the relationships between couchsurfing, social support, and HIV risk through three separate studies corresponding to three
specific aims. Aim 1 uses egocentric social network analysis to investigate whether couchsurfing and social support are associated with specific HIV-related behaviors, including
transactional sex, condomless sex, sex under the influence, concurrent sex partners, HIV testing,
and PrEP awareness and use. Aim 2 uses latent class analysis to explore the heterogeneity of
YEH based on their living situation and social support networks to examine (a) whether
minoritized identities and duration of homelessness relate to emergent subgroups and (b) whether
HIV-related behaviors vary across these same subgroups. Finally, Aim 3 uses qualitative methods
to investigate the relationships between couch-surfing, social support, and sexual risk among a
sample of 25 YEH. This study will expand knowledge regarding HIV-related behaviors among
YEH, provide new insights into couch-surfing among YEH, and pave the way for the
development of more tailored health interventions and more impactful homelessness policy.

1
CHAPTER 1. AN INTRODUCTION TO COUCH-SURFING AMONG YOUTH
EXPERIENCING HOMELESSNESS
INTRODUCTION
Each year, an estimated 3.5 million youth between the ages of 18 and 25 experience
homelessness in the U.S. (Morton et al., 2018). Among these young people, “couch-surfing,” or
temporarily staying with other people, occurs at three to four times the rate of other forms of
homelessness, including living on the streets or residing in shelter programs (Curry et al., 2017).
However, couch-surfing is frequently excluded from definitions of homelessness utilized by the
U.S. Department of Housing and Urban Development (HUD) (2015), which administers funding
for most of the housing resources available for youth experiencing homelessness. This exclusion
has plagued efforts to effectively address youth homelessness, including impacting communities’
ability to collect and report accurate data that inform critical funding and planning decisions
(Auerswald & Adams, 2018; Dworsky, 2020). Concurrently, the research literature has paid little
attention to couch-surfing. Despite its prevalence and its implications for policy and practice,
few studies specifically examine couch-surfing among youth experiencing homelessness.
Instead, studies often define homelessness in broad terms or else focus only on street- or shelterbased youth. Still, the emergent literature on couch-surfing indicates that these youth contend
with similar risk factors as their street-based counterparts while also facing their own distinct
vulnerabilities related to mental health (Hail-Jares et al., 2023; Petry et al., 2022; Rhoades et al.,
2024), substance use (Suchting et al., 2020; Tyler, Olson, & Ray, 2020), service utilization
(Tyler, Olson, & Ray, 2020), and victimization (Petry et al., 2022; Tyler & Schmitz, 2018).
Further, Black and lesbian, gay, bisexual, queer, and other sexual minority (LGBQ+) youth have
been found to be significantly more likely to be couch-surfing compared to their White and

2
heterosexual peers, underscoring potential disparities in experiences of homelessness and access
to resources among minoritized youth (Petry et al., 2022). In laying the foundation for the
importance and relevance of this dissertation research, which examines sexual risk behavior
among young adults who are couch-surfing, the current chapter provides an overview of the
emergent literature on couch-surfing and the shortcomings of U.S. policy responses to youth
homelessness.
Couch-surfing and the volatility of youth homelessness
In the context of homelessness and housing instability, “couch-surfing” generally refers
to temporarily staying in the homes of others without a ‘secure place to be’ (Curry et al., 2017;
McLoughlin, 2013). This is admittedly a broad conceptualization of a nuanced phenomenon that,
while highly prevalent among youth, remains far less understood than street homelessness. Of
the estimated 3.5 million youth experiencing in the U.S. on an annual basis, approximately 1.6
million report exclusively couch-surfing—and over half of those remaining report couch-surfing
in addition to experiencing other forms of homelessness, including sleeping on the streets or
staying in temporary shelter programs (Curry et al., 2017; Morton et al., 2018). The precursors to
couch-surfing are similar to those preceding youth living on the streets, and include ruptured
family relationships, interpersonal and community violence, behavioral health issues, and
poverty (Hail-Jares et al., 2021; Krause et al., 2016; McLoughlin, 2013; Tyler & Melander,
2010). In the face of a housing loss, youth often turn to couch-surfing to avoid both the streets
and the shelter system, leveraging their social connections to arrange a temporary place to stay
(Hail-Jares, 2023; McLoughlin, 2013; Perez & Romo, 2011). Although this is an experience
distinct from—and often intersecting with—other forms of homelessness, the dominant trend in

3
youth homelessness research has been to fold couch-surfing under broad definitions of
homelessness that encompass a range of settings. This is at least partially attributed to the
recognition that the way in which youth experience homelessness is not static but variable,
spanning multiple venues.
It is generally understood that youth homelessness often entails cycling in and out of
different settings (Coates & McKenzie-Mohr, 2010; Kidd et al., 2016; Toro et al., 2011; Tyler et
al., 2012), but studies indicate that even when there are near-daily changes to a young person’s
living situation, specific settings are associated with specific behaviors and risk factors that affect
their health and well-being. In two Midwestern cities, Tyler and colleagues (2020) measured the
daily sleeping locations of 150 youth experiencing homelessness over the course of 30 days.
Even among those predominantly residing in more stable environments like transitional housing
programs, youth were highly mobile. Over a two-week period, youth reported moving between
an average of three different location types, with significant differences emerging based on
where youth stayed most frequently. Those who most commonly stayed with a friend or romantic
partner reported fewer days feeling depressed, more frequent marijuana use, and less engagement
in services.
In Texas, Suchting and colleagues (2020) traced the daily sleeping locations of 66 youth
experiencing homelessness over 21 days. Youth in this sample most frequently reported residing
in unstable housing situations, including staying with family, friends, or a romantic or sexual
partner. However, over one-quarter of these youth also reported cycling through unsheltered
locations and shelter programs during the same timeframe, and over one-third reported staying in
at least one of these other location types in addition to unstable housing arrangements. In contrast
to Tyler and colleagues (2020), Suchting and colleagues examined the odds of youth staying in

4
each location type based on a range of experiences from the preceding day, including sexual
activity, substance use, assault, sources of stress, and discrimination. Being arrested, having sex
with an ‘unspecified other,’ being physically assaulted, and being stressed about parenting were
all associated with increased odds of staying with someone relative to staying in a shelter. Being
verbally assaulted, experiencing racial discrimination, and being discriminated against by a
friend were all negatively associated with spending the night with someone else.
Together, the studies by Tyler and colleagues (2020) and Suchting and colleagues (2020)
not only underscore the volatility of homelessness experienced among young people, but indicate
that even amid this instability, different forms of homelessness are associated with specific health
behaviors, risk factors, and adverse experiences. This is reinforced by an emergent body of
research examining these differences more broadly. In a study of over 9,400 youth experiencing
homelessness across 16 communities in the U.S., Petry and colleagues (2022) reported that youth
who had threatened harm to themselves or others were significantly more likely to be couchsurfing than residing in a shelter, and those who were able to meet their basic needs were less
likely to be couch-surfing. Using a nationally representative sample of sexual minority
adolescents, Rhoades and colleagues (2024) have suggested that youth who couch-surf
exclusively and youth who experience multiple forms of homelessness are no different in their
anxiety or depression symptomatology, but each are associated with large increases in symptoms
of anxiety, depression, suicidal ideation, and suicide attempt relative to their stably housed peers.
Additionally, Hail-Jares and colleagues (2020) have reported that relative to other forms of
homelessness, couch-surfing is associated with lower perceptions of social support, poorer
mental health, and greater severity of self-harm among youth in Australia.

5
These findings call into question the homogenization of young people’s homelessness
experiences in research, as this practice effectively obscures our understanding of couch-surfing
despite the critical implications for policy and practice. Couch-surfing youth are often treated as
less vulnerable, and as less of a concern by gatekeepers within social services systems and by
policymakers that prioritize ‘rooflessness’ above other risk factors (Hail-Jares et al., 2021;
Holtschneider, 2021; McLoughlin, 2013). In the U.S., couch-surfing has long been embroiled in
policy debates over what constitutes homelessness and who deserves access to housing.
U.S. policy responses to youth homelessness
Across the three main agencies tasked with addressing youth homelessness in the U.S.—
the Department of Education (ED), the Department of Health and Human Services (HHS), and
the Department of Housing and Urban Development (HUD)—are a multitude of definitions of
and responses to youth homelessness. Adapted from summary documentation from HHS (2020),
Table 1.1 provides an overview of the definitions used in the administration of core federal
programs serving youth experiencing homelessness. The definitions used by ED and HHS both
include youth who are staying in unsheltered locations (e.g., on the streets or in a vehicle,
abandoned building, or other place not meant for human habitation), emergency shelter or
transitional housing, motels or hotels, or with others if there is no viable alternative (also referred
to as “doubled-up” or couch-surfing). However, although ED and HHS definitions are closely
aligned and accurately reflect the ways in which youth experience homelessness, the supports
their programs offer are severely limited in scope and neither provide permanent housing. The
Education for Homeless Children and Youth (EHCY) program administered by ED is chiefly
concerned with protecting the educational rights of students experiencing homelessness (ED,

6
2018). EHCY aims to reduce barriers to attending and succeeding in school by providing
students and their families information about support services and linkages to community-based
resources. Meanwhile, HHS is responsible for the implementation of programs authorized by the
Runaway and Homeless Youth Act (RHYA), which funds street outreach programs, short-term
shelters for youth under the age of 18, and transitional housing programs for youth between the
ages of 16 and 22. But these resources are not available in every community, let alone every state
(HHS, 2023a). In 2023, there were just 35 street outreach programs, 119 emergency shelter
programs, and 84 transitional housing programs nationwide (HHS, 2023b).

7
Table 1.1 Definitions of homelessness used by federal agencies in addressing youth homelessness
Department of Housing and
Urban Development
Homeless Emergency
Assistance and Rapid
Transition to Housing
(HEARTH) Act of 2009
Homeless Assistance
Programs (HAP)
$2.8 billionb (serving all
homeless populations)
Yes
50,256 unaccompanied
youtha (age 25 and under)
on a single night in January
2023 out of a total 653,104
persons experiencing
homelessness
Adapted from U.S. Department of Health and Human Services (2020). Definitions of homelessness for federal programs serving children,
youth, and families https://www.acf.hhs.gov/sites/default/files/documents/ecd/homelessness_definition.pdf
a Students identified by ED counts include those enrolled in public education programs and consist of students in pre-Kindergarten through
grade 12, and high school graduates participating in bridge to higher education programs (National Center for Homeless Education, 2023).
a The point-in-time count only enumerates individuals who are living in unsheltered locations, emergency shelter, transitional housing, or a
motel/hotel funded by a government or charity program. Those who are couch-surfing or doubled-up are not included (HUD, 2023a).
b Includes only the Continuum of Care ($2.8 billion) program under HAP (HUD, 2023b).
Department of Health and
Human Services
Runaway and Homeless
Youth Act (RHYA)
Runaway and Homeless
Youth (RHY) Program
$146 million
No, emergency shelter and
transitional housing only
No estimate available
Department of Education
McKinney-Vento Homeless
Assistance Act
Education for Homeless
Children and Youth (EHCY)
Program
$129 million
No, support services only
1.2 million students
identified during the 2021-22
school year, including
100,664 unaccompanied
youth
Defining legislation
Program
Funding (FY 2023)
Funds permanent housing
For youth
Estimated number of youth
experiencing homelessness

8
Table 1.1 Definitions of homelessness used by federal agencies in addressing youth homelessness (continued)
Department of Housing and
Urban Development
No, with the following
exceptions:
• facing imminent
housing loss with
credible evidence that
owner or renter of
housing will not permit
them to stay >14 days
and no other residence
identified and lacks
resources or support
networks to obtain
other permanent
housing
• fleeing or attempting
to flee domestic
violence or other
dangerous conditions
within a housing
situation and no other
residence identified
and lacks resources or
support networks to
obtain other permanent
housing
Department of Health and
Human Services
Yes, if youth is unable to live
with a relative and has no
other safe alternative
Department of Education
Yes, if youth lacks a “fixed,
regular, and adequate
nighttime residence” due to
loss of housing, economic
hardship, or similar situation
Couch-surfing, “doubledup,” or staying with others

9
Table 1.1 Definitions of homelessness used by federal agencies in addressing youth homelessness (continued)
Department of Housing and
Urban Development
No, with the following
exceptions (continued):
• unaccompanied youth or
family considered family
under other federal
statutes who have (1)
been without permanent
housing for a long period
of time, and (2)
experienced persistent
instability defined by
frequent moves over a
long period of time, and
(3) can be expected to
continue to experience
instability for an
extended period because
of chronic physical or
mental health conditions
or disabilities, substance
addiction, histories of
domestic violence or
child abuse, the presence
of a child with a
disability, or multiple
barriers to employment
Department of Health and
Human Services
Department of Education
Couch-surfing, “doubledup,” or staying with others
(continued)

10
Table 1.1 Definitions of homelessness used by federal agencies in addressing youth homelessness (continued)
Department of Housing and
Urban Development
No, with the following
exceptions:
• paid for by a
government program
or charity
• lacks resources to stay
>14 days and no other
residence identified
and lacks resources or
support networks to
obtain other permanent
housing
• fleeing or attempting
to flee domestic
violence or other
dangerous conditions
within a housing
situation and no other
residence identified
and lacks resources or
support networks to
obtain other
permanent housing
Department of Health and
Human Services
Department of Education
Motels or hotels

11
Table 1.1 Definitions of homelessness used by federal agencies in addressing youth homelessness (continued)
Department of Housing and
Urban Development
No, with the following
exceptions (continued):
• unaccompanied youth
or family considered
family under other
federal statutes who
have (1) been without
permanent housing for
a long period of time;
(2) experienced
persistent instability
defined by frequent
moves over a long
period of time; and
(3) can be expected to
continue to experience
instability for an
extended period
because of chronic
physical or mental
health conditions or
disabilities, substance
addiction, histories of
domestic violence or
child abuse, the
presence of a child with
a disability, or multiple
barriers to employment
Department of Health and
Human Services
Department of Education
Motels or hotels (continued)

12
Table 1.1 Definitions of homelessness used by federal agencies in addressing youth homelessness (continued)
Department of Housing and
Urban Development
Yes
Yes
Defined so as to include all
families with children and
youth who are defined as
homeless under other federal
statutes.
Department of Health and
Human Services
Yes, if youth is unable to live
with a relative and has no
other safe alternative
Yes, if youth is unable to live
with a relative and has no
other safe alternative
N/A
Department of Education
Yes
Yes
N/A
Emergency shelter or
transitional housing
Unsheltered locations
“At risk of homelessness”

13
Meanwhile, as the largest funder of housing and support services for people experiencing
homelessness in the U.S., HUD holds the greatest potential—and influence—in addressing youth
homelessness. While HUD has made significant investments over the past decade in dedicating
resources specifically to youth experiencing homelessness, their use of more restrictive
definitions and eligibility criteria ultimately hinders the ability of communities to effectively
serve this unique population, and it starts with who gets counted as homeless. Every year,
communities receiving HUD funding for homeless services are required to conduct a point-intime (PIT) count of the individuals and families experiencing homelessness within their
jurisdiction (HUD, 2023a). Generally occurring on a single night within the last 10 days of
January, these enumerations are limited to those who are living on the streets or residing in
emergency shelter or transitional housing programs. In turn, not only are these estimates used by
Congress to drive policy and funding decisions concerning homelessness, but they are used to
this same end by state and local governments. The limitations of the PIT count in estimating
youth homelessness have long been lamented by researchers, service providers, and advocates.
Critiques often emphasize the fact that these enumerations were originally designed around
experiences of more visible street homelessness, while the ways in which youth experience
homelessness are often invisible—and include couch-surfing (Auerswald & Adams 2018;
Dworsky, 2020; Holtschneider, 2021; Metcalf, 2020; Richard et al., 2024; Smith & CastañedaTinoco, 2019). This has resulted in estimates that are considered severe undercounts of the true
population, which subsequently curtail investments in effectively addressing youth homelessness
that disproportionately impact certain communities. Previous research examining how different
definitions affect resources for students experiencing homelessness suggests that youth and
families who are doubled-up or couch-surfing are more likely to reside in communities with high

14
rates of poverty and greater concentrations of Black or Hispanic students (Sullivan, 2023). These
findings underscore the disparate impacts that exclusionary homelessness definitions may have
on socioeconomically disadvantaged populations and raise concerns that racial, ethnic, and
economic inequities may be embedded within and perpetuated by more restrictive definitions of
homelessness.
Beyond the definition used for the PIT count, Table 1.1 indicates some of the specific
exceptions HUD proposes in serving those who may be couch-surfing. In the administration of
its programs, HUD employs four separate “categories” of homelessness that determine eligibility
criteria for those seeking assistance. Table 1.2 outlines these different categories based on HUD’s
own guidance for applying its definitions specifically to youth (2015), and elucidates the
exceptions noted in Table 1.1. A distilled summary of these categories is provided below:
• Category 1: Literal Homelessness includes individuals who are living in unsheltered
locations, in emergency shelter or transitional housing, in a motel or hotel paid for by a
government or charity program, or who are exiting from an institutional setting if certain
other conditions are met.
• Category 2: Imminent Risk of Homelessness includes those facing eviction, those
unable to continue paying for their own hotel or motel room, and those who are staying
with friends or family but are being asked to leave within 14 days.
• Category 3: Homeless Under Other Federal Statutes includes unaccompanied youth
who are not included in the other three categories but are considered homeless by other
federal statutes, including the aforementioned RHYA. However, HUD appends additional
criteria that must be met to be considered under Category 3, including not having a lease
agreement in the past 60 days, having two or more moves in the last 60 days, and being
expected to continue experiencing housing instability because of specific barriers.
• Category 4: Fleeing Domestic Violence includes individuals fleeing or attempting to
flee dangerous conditions within their current living situation, including domestic
violence, sexual assault, and physical abuse.

15
These categories appear to capture the different forms of homelessness experienced by
youth but in practice, youth who are couch-surfing remain systematically excluded from most
HUD-funded programs. The exceptions noted in the preceding table are rarely made. To begin to
understand why, it is important to examine the regulations surrounding the programs that HUD
funds. In 2022, HUD administered over $2.7 billion to over 6,600 projects across all U.S. states
and territories as part of its Continuum of Care (CoC) program (HUD, 2023b). The CoC program
is the largest program under HUD’s Homeless Assistance Programs (HAP) and serves as the
primary mechanism for coordinating community-level responses to homelessness and for
funding mainstream programs serving youth, families, and adults. The majority of CoC program
funding is dedicated to permanent housing solutions, including permanent supportive housing
(PSH) and rapid re-housing (RRH). PSH consists of non-time limited affordable housing
assistance paired with voluntary support services for chronically homeless individuals and
families—those who have experienced prolonged or recurrent homelessness (in either
unsheltered locations or in an emergency shelter) while also living with a chronic and
debilitating health condition. RRH consists of short- to medium-term rental assistance alongside
support services. Although RRH eligibility criteria do not require individuals to have a disability,
only certain categories of HUD’s homeless definitions qualify for these programs.

16
Table 1.2 Categories of homelessness used by HUD
Category Living situation Documentation required
Category 1 – Literal
Homelessness
• Emergency shelter
• Transitional housing
• Hotel or motel paid by
government or charity
• Unsheltered locations
• Institution (e.g., jail or
hospital), if the youth
resided there for 90 days
AND resided in an
emergency shelter or
unsheltered location prior
to entering institution
• Third party documentationa or
• Direct observation by intake
worker, or
• Self-certification by youthb
AND documented attempts
by intake worker to verify, or
• (If exiting institution)
Discharge paperwork or
statement from institution
verifying dates OR selfcertification AND
documented attempts by
intake worker to verify. AND
documentation of shelter or
unsheltered situation prior to
entering institution.
Category 2 –
Imminent Risk of
Homelessness
• Being evicted from own
housing within 14 days
• Hotel or motel paid by
youth or family or friend
where youth cannot stay for
more than 14 days
• Staying with family or
friends and being asked to
leave within 14 days
Additionally, youth must have no
safe alternative housing, resources,
or support networks to maintain or
obtain permanent housing
• Notice of eviction or
equivalent, or
• Proof of inability to continue
to pay for hotel or motel, or
• Self-certification by youth
that they cannot stay where
they have been AND
verification from owner or
renter of housing OR
documented attempts by
intake worker to verify, AND
• Documentation that youth has
no safe alternative housing,
no financial or other
resources, or support
networks (youth may selfcertify).
Category 3 –
Homeless Under
Other Federal
Statutes
NOTE: HUD must
approve CoC Program
funded projects to serve
youth under this
category.
Youth who are not homeless under
the other categories but who:
• Are homeless under other
federal statutes (including
RHYA), AND
• Have not had their own
place with a lease or
occupancy agreement in
the last 60 days, AND
• Have moved at least twice
in the last 60 days, AND
• Can be expected to
experience continued
housing instability due to a
• Certification of homeless
status by the entity
responsible for administering
homeless assistance under
other federal statutes, AND
• Self-certification by youth
that they have not had a lease
or similar agreement for the
last 60 days with written
documentation OR
documented attempts by
intake worker to verify, AND
• Self-certification by youth
they have moved at least

17
Category Living situation Documentation required
Category 3 –
Homeless Under
Other Federal
Statutes (continued)
disability, substance use
addiction, history of
domestic violence or child
abuse, or two or more
barriers to employment
twice in the last 60 days with
written documentation OR
documented attempts by
intake worker to verify, AND
• Documentation of special
needs (e.g., a copy of SSI
check, third party
verification, direct
observation) or at least two
barriers to employment
Category 4 – Fleeing
Domestic Violence
Youth fleeing or attempting to flee
living situation because of domestic
violence, dating violence, sexual
assault, stalking, or other dangerous
conditions related to violence
occurring within the house or has
made them afraid to return to the
house, including:
• Trading sex for housing
• Trafficking
• Physical abuse
• Violence (or perceived
threat of violence) because
of their sexual orientation
Additionally, youth must have no
safe alternative housing, resources,
or support networks to maintain or
obtain permanent housing
For providers that are NOT victim
service providers:
• Statement by youth that they
are fleeing because of
domestic or other violence
AND
• If the safety of the youth is
not jeopardized, verification
of the statement through
written observation by intake
worker or staff at other
organizations from whom
youth has sought assistance
OR documented attempts by
intake worker to verify
information
For victim service providers
• Statement by youth that they
are fleeing because of
domestic or other violence
AND
• Certification of statement by
the youth or intake worker
All providers must have youth selfcertify that they have no safe
alternative housing, no financial or
other resources, or support networks,
and intake worker should obtain any
available documentation supporting
this information.
Adapted from U.S. Department of Housing and Urban Development. (2015). Determining homeless
status of youth. https://files.hudexchange.info/resources/documents/Determining-Homeless-Status-ofYouth.pdf
a Third party documentation includes records from administrative databases, written observations by a
street outreach worker or referral from an external housing or service provider, and signed documentation
from institutional settings that include records regarding length of stay.
b Self-certification refers to a process by which the youth provides a written description of how they meet
the definition, which must then have documented attempts by the intake worker to verify this information.

18
PSH programs generally require that youth meet the Category 1 definition and live with a
chronic health condition (HUD, 2023c), the latter of which creates an additional wrinkle for
youth seeking housing assistance as they are less likely than their adult counterparts to report a
chronic health issue (Van Dongen et al., 2019; Winetrobe et al., 2016). While youth under
Category 2 may be eligible for some RRH programs according to HUD, local CoC prioritization
and eligibility policies decide who is eligible for RRH (HUD, 2023c). Many communities
prioritize or altogether reserve RRH programs for non-chronically homeless individuals under
Category 1 and sometimes Category 4 (DuBois, 2024; Wagner et al., 2020). This practice is
influenced by HUD scoring criteria for annual CoC funding competitions that reward
communities for reporting a decrease in their PIT count (HUD, 2023c) and by policies that
require communities to develop and implement coordinated entry systems that rank individuals
for limited resources (HUD, 2023c). This ranking is based on vulnerability measures that
deprioritize couch-surfing, and that have since come under scrutiny for their bias against
minoritized groups that in turn perpetuate disparities in housing outcomes (Cronley, 2022;
Kithulgoda et al., 2022; Petry et al., 2021; Shinn & Richard, 2022; Wilkey et al., 2019).
Considering Black and LGBQ+ youth are more likely to be couch-surfing than residing in shelter
programs (Petry et al., 2022), these intersecting and compounding biases within homeless
services systems ultimately reinscribe the marginality of minoritized youth experiencing
homelessness.
Although Category 3 exists to accommodate definitions of homelessness under other
federal statutes, HUD appends four additional criteria that must be met and requires communities
to gain written approval. Communities must demonstrate why serving youth under Category 3 is
of greater or equal priority than serving those under other categories, how doing so will be more

19
cost-effective in meeting their performance goals, and that they have the resources to house
everyone in their community who is considered homeless under Categories 1 and 4 (HUD,
2023c). If approved, these youth would still remain ineligible for all PSH programs and the
amount of funding that could be used to serve youth under Category 3 is capped at 10 percent.
Not a single community has ever been granted this exception (National Alliance to End
Homelessness, 2018; National Network for Youth, 2019).
Under Category 4, youth escaping domestic violence and other dangerous living
situations may be considered eligible for certain RRH resources if they do not meet criteria for
PSH, though this is again variable depending on local prioritization policies (DuBois, 2024;
Wagner et al., 2020). Notably, while HUD considers youth trading sex for housing as eligible
under Category 4, this distinct scenario is only found in the supplemental reference guide for
youth homelessness adapted for Table 1.2. Trading sex is not mentioned in the defining
legislation (HEARTH Act of 2009), nor in HUD’s funding regulations for CoC programs
(2023c), nor in their standard criteria and recordkeeping guidance (2012). Instead, these sources
only reference domestic violence more broadly, or specify “domestic violence, dating violence,
sexual assault, stalking, or other dangerous, traumatic, or life-threatening conditions.” The
omission of transactional sex in these primary sources places the onus on individual service
providers to decide whether youth engaged in transactional sex meet the criteria of Category 4.
Further, while there is a degree of flexibility afforded by HUD in defining “dangerous,
traumatic, or life-threatening,” documentation requirements associated with Category 4 require
youth to state that they are fleeing due to violence—and transactional sex is not always perceived
by youth to be dangerous, traumatic, or life-threatening (Hail-Jares, 2023; Tyler & Johnson,
2010).

20
The definitional constraints that HUD imposes on the most powerful data we have on
homelessness and on the largest portfolio of housing programs at our disposal ultimately prevent
us from addressing youth homelessness. According to the PIT count, there are just over 50,000
youth experiencing homelessness on any given night, representing less than 8% of the total
estimated population of people experiencing homelessness in the U.S. (HUD, 2023a). Of the
approximately 600,000 permanent housing beds and 450,000 emergency shelter and transitional
housing beds in our national inventory, only 3% and 4%, respectively, are dedicated to youth—
and that includes beds not funded by HUD programs (2023a; 2023d). HUD’s policies are
effectively rooted in conceptualizations of youth homelessness that defy empirical evidence,
obscure our understanding of the nature and scope of youth homelessness, and lead to a grave
misalignment between resources and need. Youth experiencing homelessness do not fall neatly
along a continuum of risk based solely on their living situation (Fowler et al., 2019), but the
existing eligibility thresholds set for this population assume that couch-surfing falls squarely on
the end of least risk. Consequently, further research on the potential relationships between couchsurfing and certain risk behaviors may help shift the prevailing paradigms around youth
homelessness that undergird current public policy and reorient the distribution of current
resources. Exploring the connection between couch-surfing and transactional sex in particular
may provide an opportunity for communities to extend critical housing resources to a segment of
couch-surfing youth under HUD’s Category 4 definition of homelessness.

21
OVERVIEW OF THE DISSERTATION
The current dissertation aims to make a novel contribution to the literature on couch-surfing
among youth experiencing homelessness through an examination of the relationships between
couch-surfing, social support networks, and sexual risk behavior. Relative to their stably housed
peers, youth experiencing homelessness are at significantly higher risk for HIV (Caccamo et al.,
2017; Logan et al., 2013; Ober et al., 2012), yet the differential impact that their specific living
situation might have on their engagement in risky sexual behaviors remains unknown. Key to
this analysis will be the examination of young people’s social support networks, given that
couch-surfing is fundamentally a survival strategy dependent upon social connections and that
these connections are known to influence sexual health behaviors (Barman-Adhikari et al., 2018;
Hsu et al., 2018; Rice et al., 2008). Following this chapter are three distinct studies structured
around the following aims:
• Aim 1 (Chapter 2): Investigate whether couch-surfing and social support are associated
with specific HIV risk or prevention behaviors among youth experiencing homelessness.
• Aim 2 (Chapter 3): Examine the heterogeneity of youth experiencing homelessness
based on their living situation and social support networks and their association with
HIV-related behaviors.
• Aim 3 (Chapter 4): Qualitatively explore how couch-surfing and social support intersect
to influence engagement in HIV-related behaviors among youth experiencing
homelessness.
Findings from these three chapters are summarized in Chapter 5 and discussed in relation to
implications for practice, policy, and future research.

22
The conceptualization and operationalization of couch-surfing
Despite the prevalence of couch-surfing observed among youth experiencing
homelessness, no consistent research definition or formal policy definition currently exists for
this phenomenon. Further complicating efforts to define couch-surfing, the term itself is often
used interchangeably with doubled-up, unstably housed, precariously housed, marginally
housed, and others. Drawing from previous research concerning couch-surfing and unstable
housing among youth experiencing homelessness (Curry et al., 2020; Hail-Jares et al.,
2021; McLoughlin, 2013; Slesnick et al., 2018; Suchting et al., 2020; Tyler et al., 2020), the
current study defines couch-surfing as an unstable or otherwise temporary and informal housing
arrangement wherein a young person spends the night at the private residence of another person.
While couch-surfing ‘hosts’ generally include friends, relatives, romantic or sexual partners,
strangers, or people met online or through a mutual connection (e.g., a friend of a friend), the
temporal dimension of couch-surfing is far less understood and seldom quantified. Consequently,
in hopes of informing the future development of couch-surfing definitions and measures, the
current study adopts a broader conceptualization that may encompass shorter stays of one or two
nights at a time and longer stays amounting to several weeks or even a few months. Additionally,
the current study uses the term “couch-surfing” to better align with how youth, service providers,
and advocates most commonly reference this form of homelessness (National Network for
Youth, 2019) and to improve the accessibility of this work.
That said, there are limitations to the measure of couch-surfing used in the quantitative
arm of this study (Aims 1 and 2) that warrant acknowledgment here. Data come from a parent
study that recruited participants from community-based organizations who chiefly serve youth
experiencing homelessness. In assessing their living situation, youth responded to a survey item

23
prompting them to indicate the type of location they had spent most of their nights in the
preceding two weeks. Response options included Home of someone I know (family, friend,
partner, etc.) and Stranger’s home/residence, both of which were used in the operationalization
of couch-surfing in this dissertation study. The relative stability—real or perceived—of these
specific living situations is unknown. It is therefore possible that some youth who reported
staying with someone they knew were in more stable housing situations but still accessing
services for other support. However, responses to additional survey items indicate that these
young people’s connections to the drop-in center where surveys took place largely aligned with
the duration of their most recent episode of homelessness. This study acknowledges the
limitations of this couch-surfing measure throughout and underscores the importance of more
nuanced measures of couch-surfing arrangements in future research on youth homelessness.

24
CHAPTER 2. ASSOCIATIONS BETWEEN COUCH-SURFING, SOCIAL SUPPORT,
AND HIV RISK: AN EGOCENTRIC NETWORK ANALYSIS
INTRODUCTION
Youth experiencing homelessness face increased risk for multiple adverse health
outcomes due to histories of abuse and victimization, unstable and frequently dangerous living
situations, and engagement in behaviors often related to young people’s efforts to survive,
including substance use and risky sexual activity (Edidin et al., 2012; Smith-Grant et al., 2022).
Youth experiencing homelessness are at especially high risk for sexually transmitted infections;
prior studies have reported an overall prevalence of sexually transmitted infections among this
population between 6% and 32% (Caccamo et al., 2017) and an HIV prevalence between 5% and
16% (Logan et al., 2013). Yet even at its lowest estimate, the prevalence of HIV among youth
experiencing homelessness is at least twice as high as their stably housed peers (Ober et al.,
2012). HIV risk among youth experiencing homelessness has appeared to predominantly be the
consequence of risky sexual behaviors over illicit drug use (Barman-Adhikari et al., 2018; Linton
et al., 2013), including inconsistent condom use, sex under the influence of drugs or alcohol,
multiple concurrent sex partners, and engagement in transactional sex (i.e., exchanging sex in
return for money, drugs, shelter, or food). Social networks, or the interpersonal relationships with
whom an individual is connected (Lin, 1999), have been demonstrated to exert key influences on
HIV risk behaviors among youth experiencing homelessness (Barman-Adhikari et al., 2018; Hsu
et al., 2018; Rice et al., 2008). However, the bearing that social support might have with young
people’s sexual risk-taking—and how it might intersect with their living situation—warrants
further investigation.

25
HIV risk behaviors among youth experiencing homelessness
Decades of research have demonstrated that consistent and correct condom use is
effective in reducing the risk of HIV transmission (Centers for Disease Control and Prevention
[CDC], 2023). However, studies report that upwards of between 60% and 70% of youth
experiencing homelessness engage in condomless sex (Barman Adhikari et al., 2018; Santa
Maria et al., 2018). Sex under the influence of drugs or alcohol has also been identified as a risk
factor for HIV due to its association with condomless sex (Dang et al., 2019; Madden et al.,
2021) and multiple sexual partners (Madden et al., 2021). One study using a probability sample
of youth experiencing homelessness reported that sex under the influence occurred in one-third
of sexual encounters reported by participants; hard drug use or heavier drinking prior to sex was
associated with a decreased likelihood of condom use (Tucker et al., 2012).
Rates of transactional sex among youth experiencing homelessness in the U.S. have been
reported between 11% and 41%, depending in part on geographic contexts (Gwadz et al., 2009;
Walls & Bell, 2011). Prior work suggests that most young people do not engage in transactional
sex prior to their housing loss; in a nationally representative study of adolescents and young
adults, those who reported ever being homeless were nearly three times more likely to engage in
transactional sex compared to their stably housed peers (Ulloa et al., 2016). Further, the
likelihood of engaging in transactional sex significantly increases as young people’s length of
time homeless or number of homeless episodes increases (Heerde & Hemphill, 2016). Youth of
color, transgender and gender-expansive youth, and LGBQ+ youth experiencing homelessness
have all been reported to be significantly more likely to engage in transactional sex relative to
their White, cisgender, and heterosexual counterparts (Kattari & Begun, 2017; Walls & Bell,

26
2011). Concurrently, these populations also carry an overall disproportionate risk for HIV (CDC,
2022).
HIV prevention behaviors among youth experiencing homelessness
Routine HIV testing is a core strategy for helping to reduce transmission rates and
facilitate early detection and treatment (CDC, 2022). Overall HIV testing rates are higher among
youth experiencing homelessness than youth in the general population (Gwadz et al., 2010; Tyler
& Melander, 2010; Young & Rice, 2011; Balaji et al., 2012), with one representative sample of
sexually active youth in Los Angeles reporting an 85% lifetime test rate (Ober et al., 2012).
However, evidence suggests that HIV testing may vary across different subgroups, contexts, and
risk behaviors. Demographic characteristics reported as being associated with HIV testing among
youth experiencing homelessness have included being Black or multiracial (Solorio et al., 2006);
Hispanic/Latinx (Ober et al., 2012); LGBQ+ (Johnson De Rosa et al., 2001; Santa Maria et al.,
2020; Solorio et al., 2006); female (Solorio et al., 2006; Tyler & Melander, 2010); and older in
age (Myles et al. 2020; Solario et al., 2006). Accessing shelter and drop-in services has also been
noted as being significantly associated with an increased likelihood of HIV testing among this
population (Gwadz et al., 2010; Ober et al., 2012). Notably, findings on the relationship between
sexual risk behaviors and HIV testing have been somewhat mixed, though the selection and
definition of sexual risk variables in these studies have varied considerably (Solorio et al., 2006;
Myers et al., 2020; Ober et al., 2012). Most recently, in their study of youth experiencing
homelessness in Atlanta, Myers and colleagues (2020) reported that while transactional sex was
significantly associated with ever testing for HIV, condomless sex and having four or more
sexual partners in the past year were not.

27
In addition to condom use and HIV testing, the use of pre-exposure prophylaxis (PrEP) is
a key strategy for reducing transmission among high-risk groups (CDC, 2022). However,
awareness and use of PrEP among youth experiencing homelessness are low. Results from a
cross-sectional survey of young adults experiencing homelessness across seven U.S. cities
indicated that while 84% of young people were eligible for PrEP based on their risk behaviors,
only 29% had any knowledge or awareness of the HIV prevention medication. Even still, 59%
reported that they would be likely to take PrEP if they knew it could reduce their HIV risk (Santa
Maria et al., 2019a). Related qualitative work has pointed toward a variety of factors impacting
these young people’s use of PrEP, including low PrEP awareness, low perceived HIV risk, and
medical mistrust (Santa Maria et al., 2019b).
Social support and sexual health
The influence of social networks in various aspects of the lives of youth experiencing
homelessness is well-documented in the literature, including how sexual risk behaviors can be
exacerbated or mitigated by key social connections (Barman-Adhikari et al., 2016; Kattari et al.,
2017; Kennedy et al., 2012; Rice et al., 2011; Rice et al., 2007; Tyler, 2013). Perceptions of peer
condom use and communication with sexual partners have been significantly associated with
youth not engaging in condomless sex (Barman-Adhikari et al., 2018). Relationships with
supportive adults has been connected to a reduced likelihood of condomless sex (Kennedy et al.,
2012; Tevendale et al., 2009) and connections to stably housed peers have been associated with
increased condom use (Valente & Auerswald, 2013). Additionally, youth experiencing
homelessness affiliated with network members who either engage in condomless sex or have
concurrent sexual partners have been reported to be significantly more likely to have concurrent

28
partners themselves (Hsu et al., 2018). Meanwhile, connections to family members and homebased peers have been linked to an increased likelihood of HIV testing among youth
experiencing homelessness (Craddock et al., 2016; Rice et al., 2010). Family relationships have
also been associated with decreased odds of engagement in transactional sex among youth
experiencing homelessness (Rice et al., 2010), while peers appear to have the opposite effect
among young women experiencing homelessness (Warf et al., 2013).
What is less well-known with respects to the relationship between social networks and
HIV-related behavior among youth experiencing homelessness concerns the functional aspects of
networks—such as social support. Social support refers to either the perceived or actual
resources available from the relationships surrounding a given individual (Barrera, 1986; Heller
et al., 1986). Social support can take a variety of forms, of which the most common include
emotional (affect, concern); instrumental (practical or material aid); informational (counsel,
knowledge); and appraisal (feedback, affirmation). These various forms of social support are all
intimately linked to an individual’s health and well-being (Fleury et al., 2009; Heaney & Israel,
2008), and evidence among high-risk populations suggests that the presence and source of social
support within an individual’s social network are associated with both sexual risk behaviors and
safer sex practices (Cohen, 2004; Gass et al., 2021; Qiao et al., 2014).
Meanwhile, although social support has been associated with other health-related
outcomes among youth experiencing homelessness, including mental health symptomatology
(Wright et al., 2017), suicide attempts (Fulginiti et al., 2022), and substance use (Brown et al.,
2020; Green et el., 2013; Ferguson & Xie, 2012), fewer have examined its effect on sexual risk
behavior. Among those that have, supportive relationships with peers and family have been
negatively associated with condomless sex and multiple concurrent partners (Rice et al., 2008;

29
Whitbeck et al., 2001), and family support has been observed to be negatively associated with
engagement in transactional sex (Rice et al., 2010; Stein et al., 2009). However, more recent
studies investigating the effects of social networks on the sexual risk-taking of youth
experiencing homelessness have remained more focused on network structure and composition
(Barman-Adhikari et al., 2016; Craddock et al., 2016; Hsu et al., 2018) and social norms
(Barman-Adhikari et al., 2017; Kattari et al., 2017; Tyler & Melander, 2012).
The relationship between living situation and sexual risk behavior
In the nascent literature exploring the relationship between living situation and different
risk behaviors among youth experiencing homelessness, only a select few have examined sexual
risk. Although transactional sex in particular has long been recognized as part of the survival
strategies deployed by youth experiencing homelessness (Halcón & Lifson, 2004; Showden &
Majc, 2018; Srvivastava et al., 2019), it has seldom been investigated within the more specific
socioenvironmental contexts of young people’s living situations. Young women engaged in
transactional sex have overwhelmingly reported that they do so in exchange for a place to stay
(Warf et al., 2013), while transactional sex has been noted to occur at a lower rate for youth
overall in shelters compared to those on the streets (Walls & Bell, 2011). A study of transgender
and gender-expansive adults indicated that those who were couch-surfing or in other temporary
living arrangements were twice as likely to report engaging in transactional sex compared to
those who had not sought a temporary place to stay (Kattari & Begun, 2017).
Only two other studies to-date appear to have examined associations between different
living situations and other HIV risk behaviors among youth experiencing homelessness, neither
of which included couch-surfing as a distinct group. Marshall and colleagues (2009) indicated

30
that youth on the streets were less likely to use condoms while those in emergency shelters were
more likely to report a greater number of sexual partners. In their longitudinal study of youth
who were newly homeless in Los Angeles, Solorio and colleagues (2008) reported that male
youth living in non-family settings—which included places like staying with friends, in a
hotel/motel, or on the streets—had more sexual partners compared to those living with family
members or in a service or institutional setting (e.g., shelter, group home, or jail). While these
studies point toward how specific living situations may have distinct associations with sexual
risk behaviors among youth, couch-surfing remains an underexplored setting.
The impact of social support on the relationship between living situation and risk-taking
As young people draw upon various social connections for temporary living
arrangements (McLoughlin, 2013; Perez & Romo, 2011), couch-surfing is fundamentally
intertwined with social networks that can also influence behavior. Prior research suggests that
while the heterogeneity of the social networks of couch-surfing youth is similar to street- and
shelter-based youth, they are significantly more likely to report connections to home-based peers
(Petry et al., in revisions). Additionally, different forms and sources of social support are
distinctly associated with couch-surfing, as receiving emotional support from home-based peers
is associated with couch-surfing (Petry et al., in revisions). While this points toward the
differential impact of social support on living situation for youth experiencing homelessness, it
remains unclear the extent to which these social support networks might also influence sexual
risk behavior within the unique contexts of couch-surfing. It is possible that couch-surfing can, at
times, include exposure to supportive adults and peers who might mitigate certain risk behaviors,
while couch-surfing in other environments could include engagement with network relationships

31
that facilitate or otherwise influence youth engagement in riskier behavior (e.g., exchanging sex
in return for a place to stay). Therefore, the potential impact of couch-surfing on young people’s
sexual risk-taking may in part depend on the composition of their social support networks.
CURRENT STUDY
Despite extensive research on HIV risk among youth experiencing homelessness, scant
studies have examined the extent to which the socioenvironmental contexts of young people’s
living situations may be associated with risk behavior. Similarly, while social network influences
on the sexual risk-taking of youth experiencing homelessness have been widely explored, fewer
studies investigate how the functional aspects of these networks (e.g., the provision of social
support) may be associated with risk among this population. To help address these gaps in the
literature, the current study will conduct an egocentric social network analysis to determine
associations between living situation, sources of social support, and HIV risk and prevention
behaviors. Additionally, given that couch-surfing is a temporary housing strategy that hinges on a
young person’s ability to leverage their social networks, the current study also aims to examine
how different sources of social support may moderate the association between living situation
and sexual risk. The current study is guided by the following hypotheses:
Hypothesis 1: Couch-surfing will be significantly associated with specific HIV risk
behaviors. In particular, youth who are couch-surfing will be at significantly greater odds
of engaging in transactional sex relative to youth in shelter.

32
Hypothesis 2: Social support provided to youth will be significantly associated with HIV
risk and prevention behaviors. In particular, youth receiving social support from family
members will be at significantly lesser odds of engaging in sexual risk behaviors and
those receiving social support from staff will be at significantly greater odds of reporting
recent HIV testing.
Hypothesis 3: The association between couch-surfing and HIV-related behaviors will be
moderated by social support, such that supportive connections to family and home-based
peers will weaken the relationship between housing status and HIV risk behavior and
strengthen the relationship between housing status and HIV prevention behavior. In
particular, it is hypothesized that supportive family relationships will weaken the
relationship between couch-surfing and transactional sex.
METHODS
PARTICIPANTS AND PROCEDURES
This study utilized baseline data from Have You Heard? (HYH), a longitudinal study of a
peer-led social network intervention to prevent HIV among youth experiencing homelessness
(see Rice et al., 2021). Data were collected via convenience sampling methods across three dropin centers in Los Angeles, California, between September 2016 and October 2018. Drop-in
centers are an integral part of the continuum of services for youth experiencing homelessness,
providing young people with basic needs like food, clothing, and hygiene, to more intensive
services like case management, housing linkages, and mental health support (Pedersen et al.,
2016; Slesnick et al. 2016; Rice et al., 2023). All youth accessing drop-in services at one of the

33
partnering agencies were eligible for the study and were approached by research staff with the
opportunity to participate upon entering a given drop-in center. At the time of study enrollment,
each youth provided informed consent and completed an anonymous, computerized, selfadministered survey approximately 60 minutes in length. The study survey included an
assessment of the young person’s sociodemographic characteristics, personal social networks,
HIV risk behaviors, and sexual health communication behavior. Youth were compensated with a
$20 gift card for their time and participation. Survey items and study procedures were approved
by the University of Southern California Institutional Review Board.
A total of 731 youth between the ages of 14 and 26 participated in the HYH study at
baseline. Given the focus of the current analysis, youth younger than 18 (n = 14) or older than 25
(n = 6) were removed from the dataset. Additionally, youth who reported spending most of their
nights somewhere other than in a shelter program, on the streets, or “couch-surfing” were also
removed. This included youth staying in their own place (n = 73), in a hotel or motel (n = 37), in
an institutional setting (e.g., foster care, jail or prison, or inpatient facility; n = 4), or someplace
else (n = 35). While these living situations may also have unique bearings on young people’s
social support networks and subsequent risk behaviors, they are distinct experiences outside the
scope of the current study. These exclusions resulted in 556 youth between the ages of 18 and 25
in the final analytic dataset.
MEASURES
Control variables
Demographic characteristics. Age, gender identity, sexual orientation, and race or
ethnicity were included as control variables in this analysis. Age was a continuous variable

34
inclusive of ages between 18 and 25. Gender identity was a nominal variable that included male,
female, transgender, and gender-expansive youth. Due to the relatively small numbers in the
latter group, youth who were non-binary, genderqueer, gender non-conforming, or another
gender-diverse identity (n = 23) were combined with transgender youth into a single category for
this analysis. Male youth were used as the referent group. Sexual orientation was a dichotomous
variable in which a value of zero represented youth identifying as heterosexual and one
represented youth identifying as lesbian, gay, bisexual, questioning, asexual, or another nonheterosexual orientation. Race or ethnicity was a nominal variable with four categories: Black,
Hispanic/Latinx, White, and either multiracial or some other race. Due to their relatively small
numbers, youth reporting some other race were combined with those identifying as multiracial.
This included youth who were American Indian or Alaska Native (n = 18), Asian (n = 8), and
Native Hawaiian or Other Pacific Islander (n = 1). White youth were used as the referent group.
Main independent variables
Current living situation. The present study sought to examine associations between
living situation and social support networks and their relationship to different HIV-related
behaviors. Current living situation was a nominal variable that distinguished between couchsurfing, unsheltered, and shelter youth. These living situations were originally assessed by
asking youth to identify the type of location they spent most of their nights in the preceding two
weeks. Youth who reported staying at the home of someone they knew (e.g., family member,
friend, or romantic partner) or with a stranger were coded as couch-surfing. Those who indicated
living outside or in a vehicle, abandoned building or similar location were coded as being
unsheltered. Youth who reported residing in either an emergency shelter or transitional housing

35
program were coded as being in shelter. Shelter youth were used as the referent group, providing
a point of comparison between youth temporarily residing inside private residences and youth
temporarily residing inside social service facilities.
Sources of social support. Social support variables were derived from social network
questions designed to identify the different types of support provided by different types of people
within a young person’s network (Agneessens et al., 2006; Wellman & Wortley, 1990) and
adhered to recommendations by Rice & Yoshioka-Maxwell (2015) for incorporating egocentric
network analysis into social work research. Youth were asked to name up to five individuals with
whom they had the most contact in the past month, and to then identify which individuals held
specific characteristics, provided particular kinds of support, or with whom they communicated
about various sexual health topics. For the current study, five key types of social network
members were examined: family, home-based peers, romantic or sexual partners, homeless
peers, and service provider staff. Family included biological, adopted, or foster family members,
and excluded street or other chosen family members. Home-based peers included other young
people between the ages of 14 and 25 who the participant knew prior to becoming homeless.
Romantic or sexual partners included individuals with whom participants reported being
romantically or sexually involved. Homeless peers included other young people between the
ages of 14 and 25 who were also currently experiencing homelessness. Service provider staff
included individuals the participant identified as a case manager, agency staff, or volunteer.
Social support was measured by asking participants to identify which individuals in their
named network provided either emotional, instrumental, informational, or appraisal support in
the past month. Emotional support was assessed by asking who participants had turned to for
help or advice when they were feeling depressed or dealing with major issues. Instrumental

36
support was assessed by asking who participants were able to borrow money or other material
aid from when needed. Informational support was assessed by asking who participants had
spoken with about where to get social services. Appraisal support was assessed by asking who
encouraged participants in meeting their goals. The endorsement of at least one form of support
was used to create a dichotomous variable representing whether a given network member
provided social support. Together with the network member variables, this broader social support
variable was used to construct a series of dichotomous variables indicating the presence of
specific supportive relationships within a young person’s network. For example, youth who
reported having at least one family member who provided social support were coded as having
social support from family. These variables were subsequently integrated with each participant’s
individual-level survey data.
Main dependent variables
HIV risk and prevention behaviors. Participants were asked a series of questions about
their sexual behavior over the past 30 days based on whether they indicated having at least one
sexual partner during that time. Similar to how their broader social networks were assessed,
participants identified up to five recent sexual partners and were asked whether they engaged in
specific sexual practices with a given partner. Condomless anal sex, condomless vaginal sex,
multiple concurrent partners, sex under the influence, and transactional sex were created as
dichotomous variables for inclusion in the current analysis. Participants were coded as having
condomless anal sex if they identified at least one sexual partner with whom they had anal sex
without a condom; condomless vaginal sex was coded similarly. Multiple concurrent partners
was coded to indicate whether participants reported having two or more sexual partners in the

37
past 30 days. Sex under the influence was coded according to whether participants identified at
least one sexual partner with whom they had sex while either they themselves or their partner
were under the influence of drugs or alcohol. Finally, transactional sex was derived from items
measuring both recent exchange and survival sex. Exchange sex was defined as trading sex or
sexual content (i.e., videos or photos) in exchange for money, while survival sex was defined as
trading sex or sexual content in exchange for things other than money, including a place to stay.
Youth who reported being sexually inactive were coded as not engaging in any of these HIVrelated risk behaviors.
All participants, regardless of whether they were sexually active, were asked about their
HIV prevention behaviors. HIV testing, PrEP knowledge, and ever being prescribed PrEP were
created as dichotomous variables for inclusion in the current analysis. HIV testing was coded to
reflect participants who reported getting an HIV test within the previous six months. PrEP
knowledge was assessed using a Likert scale to measure how much participants knew about
PrEP; participants who expressed having at least “a little bit” of knowledge about the HIV
prevention medication were coded as having PrEP knowledge. Ever being prescribed PrEP was
coded to indicate participants who reported ever having a PrEP prescription.
ANALYSIS
Egocentric network analysis facilitates the statistical examination of social connections
surrounding a single individual (the “ego”) (Wasserman & Faust, 1994). This type of analysis is
well suited to capture how certain facets of social relationships between youth experiencing
homelessness and the people they interact with can influence specific behaviors (Rice &
Yoshioka-Maxwell, 2015). More specifically, egocentric network analysis enables the current

38
study to explore how different living situations and sources of social support may be
differentially associated with engagement in particular HIV-related behaviors.
Descriptive statistics of HIV-related behaviors and sources of social support by living
situation were first run to examine their prevalence among the current sample of youth
experiencing homelessness. Chi-square tests were then performed to assess differences between
living situations across various HIV-related behaviors and sources of social support. Behaviors
identified as statistically significant were carried forward into a series of bivariate logistic
regressions to examine their associations with living situation and sources of social support.
Sources of social support that were statistically significant at a p-value threshold of 0.1 were then
included in logistic regressions testing the potential moderating effect of social support on the
association between living situation and sexual risk behavior. In these bivariate analyses, a pvalue threshold of 0.1 was used to determine which variables were candidates for further
investigation and for inclusion in multivariable models. Final multivariable models included
HIV-related behaviors that were significant among couch-surfing youth, along with demographic
control variables and sources of social support that were significant in relationship to those
specific behaviors.
RESULTS
Table 2.1 presents the demographic characteristics of the current sample overall and by
living situation. The average age of participants was 21.9 years old. Youth of color were in the
majority—31.5% were Black, 14.5% were Hispanic/Latinx, and 30.9% were multiracial or
another non-White race. Over half (66.9%) of youth were male, 21.4% were female, and 11.7%
were either transgender or gender-expansive. A sizeable minority (42.6%) identified as LGBQ+.

39
Most youth reported currently living unsheltered (53.6%), while 16.0% were couch-surfing and
30.4% were residing in an emergency shelter or transitional housing program. Across the
different living situations, youth differed significantly with respects to age (F(2,553) = 5.21, p <
0.01), race (X2 = 17.96, p<.01), and sexual orientation (X2 = 7.0, p = 0.03). Post hoc analyses
indicated that youth who were couch-surfing had a significantly lower average age compared to
youth who were unsheltered (p < 0.01). Meanwhile, higher rates of Black youth were observed
among those couch-surfing or in shelter (37.1% and 39.5%, respectively) compared to those who
were unsheltered (29.0%). Higher rates of White youth were observed among the unsheltered
(29.0%) compared to those couch-surfing (19.1%) or in shelter (15.0%). Youth did not
significantly differ in gender identity with respects to their current living situation.

40
Table 2.1 Characteristics of youth experiencing homelessness, by living situation (n = 556)
Unsheltered
(n = 298)
n (%)
Couchsurfing
(n = 89)
n (%)
Shelter
(n = 169)
n (%)
Total
(n = 556)
n (%)
F or
X2
Demographics
Age, mean (SD) 22.1 (2.0) 21.4 (2.1) 21.9 (1.9) 21.9 (2.0) 5.21*
Race (n = 553) 17.96*
Black 75 (29.0) 33 (37.1) 66 (39.5) 174 (31.5)
Hispanic/Latinx 44 (14.8) 13 (14.6) 23 (13.8) 80 (14.5)
White 86 (29.0) 17 (19.1) 25 (15.0) 128 (23.2)
Multiracial or another
race
92 (31.0) 26 (29.2) 53 (31.7) 171 (30.9)
Gender identity 3.37
Male 203 (68.1) 61 (68.5) 108 (63.9) 372 (66.9)
Female 64 (21.5) 20 (22.5) 35 (20.7) 119 (21.4)
Transgender or
gender-expansive
31 (10.4) 8 (9.0) 26 (15.4) 65 (11.7)
LGBQ+ (n = 550) 116 (39.5) 33 (37.1) 85 (50.9) 234 (42.6) 7.00*
* p < .05
Table 2.2 provides the frequencies of specific HIV risk and prevention behaviors and
sources of social support by living situation. At 18.0%, couch-surfing youth reported the highest
rate of recent transactional sex, compared to 9.5% of shelter youth and 15.4% of unsheltered
youth. The results of a chi-square test indicated that youth engaging in transactional sex and
those who did not differed significantly with respect to their living situation (X2 = 4.56, p<.10).
The rate of multiple concurrent sexual partners was also highest among couch-surfing youth,
with 38.2% reporting multiple partners compared to 32.0% of shelter youth and 34.9% of
unsheltered youth. Couch-surfing youth reported the lowest rate of condomless anal sex (13.5%)
compared to unsheltered youth (26.5%) and youth in shelter (23.7%). Results of a chi-square test
indicated that youth who reported condomless anal sex and those who did not differed

41
significantly with respects to their living situation (X2 = 6.46, p<.05). Rates of condomless
vaginal sex among couch-surfing youth were higher than youth in shelter (29.2% compared to
23.7%), but lower than unsheltered youth (34.6%). Sex under the influence occurred at similar
rates among couch-surfing youth and youth in shelter (18.0% compared to 16.6%) and was
highest among unsheltered youth (30.9%). The results of a chi-square test indicated that youth
having sex under the influence and those who did not differed significantly with respect to their
living situation (X2 = 14.35, p<.05).
While the overall majority of youth reported having an HIV test within the past six
months, the rate was highest among youth in shelter (77.7%), followed by couch-surfing youth
(75.0%) and unsheltered youth (68.9%). Knowledge of PrEP followed a similar pattern, though
overall rates were lower than for HIV testing, as 51.8% of youth in shelter reported having at
least some knowledge of the HIV prevention medication, followed by 47.2% of couch-surfing
youth and 39.9% of unsheltered youth. The results of a chi-square test also indicated that youth
reporting knowledge of PrEP and those who did not differed significantly with respect to their
living situation (X2 = 6.31, p<.05). Rates of ever being prescribed PrEP were low across the
board, with 11.2% of couch-surfing youth, 8.9% of shelter youth, and 8.4% of unsheltered youth
reporting ever having a prescription to the HIV prevention medication.
Sources of social support also differed across living situations. Couch-surfing youth most
frequently reported receiving social support from family (46.1%) and home-based peers (33.7%).
Meanwhile, support from homeless peers was most frequently cited by youth in shelter and
unsheltered youth (47.7% and 50.3%, respectively). Couch-surfing and unsheltered youth
reported similar rates of receiving support from a romantic or sexual partner (37.1% compared to
38.3%) and youth in shelter reported the highest rate of support from service provider staff

42
(29.0%). Chi-square tests indicated that youth who had supportive homeless peers and those who
did not differed significantly based on their living situation (X2 = 8.86, p<.05), as did those who
indicated support from home-based peers and those who did not (X2 = 9.99, p<.05).
Table 2.2 HIV risk and prevention behaviors and sources of social support among youth
experiencing homelessness, by current living situation (n = 556)
Unsheltered
(n = 298)
Couchsurfing
(n = 89)
Shelter
(n = 169)
n (%) n (%) n (%) X2
HIV risk behavior (past 30 days)
Condomless anal sex 79 (26.5) 12 (13.5) 40 (23.7) 6.46
Condomless vaginal sex 103 (34.6) 26 (29.2) 40 (23.7) 6.12
Multiple partners 104 (34.9) 34 (38.2) 54 (32.0) 1.05
Sex under the influence 92 (30.9) 16 (18.0) 28 (16.6) 14.35
Transactional sex 46 (15.4) 16 (18.0) 16 (9.5) 4.56
HIV prevention behavior
HIV test in past 6 months (n = 550) 204 (68.9) 66 (75.0) 129 (77.7) 4.44
PrEP knowledge (n = 548) 117 (39.9) 42 (47.2) 86 (51.8) 6.31
Ever prescribed PrEP 25 (8.4) 10 (11.2) 15 (8.9) 0.68
Sources of social support
Homeless peer 142 (47.7) 31 (34.8) 85 (50.3) 6.01
Home-based peer 54 (18.1) 30 (33.7) 41 (24.3) 9.99
Romantic/sexual partner 114 (38.3) 33 (37.1) 54 (32.0) 1.90
Family 118 (39.6) 41 (46.1) 61 (36.1) 2.43
Service provider staff 61 (20.5) 21 (23.6) 49 (29.0) 4.35
Note: Numbers in bold type indicate significance at p <.10
Table 2.3 displays the bivariate associations between current living situation, sources of
social support, and HIV risk and prevention behaviors that were significant in the preceding
analysis: condomless anal sex, condomless vaginal sex, sex under the influence, transactional

43
sex, and PrEP knowledge. Relative to youth in shelter, couch-surfing was significantly
associated with decreased odds of condomless anal sex and increased odds of recent
transactional sex. Living unsheltered was significantly associated with increased odds of
condomless vaginal sex, sex under the influence, and transactional sex, as well as decreased odds
of knowledge about PrEP. Supportive ties to homeless peers and romantic or sexual partners
were associated with increased odds of condomless anal sex and knowledge about PrEP, and
decreased odds of recent transactional sex. Support from a romantic or sexual partner was also
associated with increased odds of condomless vaginal sex. Support from home-based peers or
family was associated with decreased odds of recent transactional sex, while support from staff
was associated with increased odds of reporting any knowledge of PrEP.

44
Table 2.3 Bivariate analysis of odds of engaging in HIV-related behaviors
PrEP
knowledge
OR (95% CI)
0.62
(0.42 – 0.91)
0.83
(0.50 – 1.39)
1.39
(0.99 – 1.94)
0.81
(0.54 – 1.22)
1.38
(0.97 – 1.95)
1.05
(0.74 – 1.48)
1.62
(1.09 – 2.41)
Note: Numbers in bold type indicate significance at p <.10
Transactional
sex
OR (95% CI)
1.75
0.95 – 3.19
2.10
(0.99 – 4.42)
0.64
(0.39 – 1.05)
0.59
(0.31 – 1.13)
0.99
(0.60 – 1.63)
0.64
(0.38 – 1.07)
0.81
(0.45 – 1.47)
Sex under
the influence
OR (95% CI)
2.25
(1.40 – 3.61)
1.10
(0.56 – 2.17)
1.59
(1.08 – 2.35)
1.34
(0.86 – 2.09)
2.34
(1.58 – 3.47)
1.05
(0.71 – 1.56)
1.30
(0.83 – 2.02)
Condomless
vaginal sex
OR (95% CI)
1.70
(1.11 – 2.61)
1.33
(0.75 – 2.37)
0.95
(0.66 – 1.37)
1.21
(0.79 – 1.85)
2.54
(1.75 – 3.69)
1.16
(0.80 – 1.67)
0.87
(0.57 – 1.35)
Condomless
anal sex
OR (95% CI)
1.16
(0.75 – 1.80)
0.50
(0.25 – 1.02)
1.57
(1.06 – 2.33)
1.09
(0.69 – 1.74)
3.94
(2.62 – 5.94)
0.97
(0.65 – 1.44)
1.32
(0.84 – 2.06)
Current living situation (ref: Shelter)
Unsheltered
Couch-surfing
Sources of support
Homeless peer
Home-based peer
Romantic or sexual partner
Family
Service provider staff

45
Tables 2.4 and 2.5 explore whether sources of social support moderate the association
between living situation and HIV-related behavior. From the preceding bivariate analysis, only
behaviors that were significant at the p < 0.1 level among couch-surfing youth were examined, as
were sources of social support that were significant at p < 0.1 for these behaviors. Results
indicate no significant interaction effect between living situation and social support with respects
to either condomless anal sex or recent transactional sex. Consequently, interaction terms were
excluded from the final multivariable models.
Table 2.4 Interaction effects between social support and living situation and their association
with condomless sex
Condomless anal sex
OR (95% CI)
Support from homeless peer
Unsheltered (ref: Shelter) 1.23 (0.63 – 2.38)
Couch-surfing (ref: Shelter) 0.68 (0.27 – 1.71)
Homeless peer support 1.67 (0.81 – 3.43)
Unsheltered x Homeless peer support 0.93 (0.38 – 2.25)
Couch-surfing x Homeless peer support 0.55 (0.13 – 2.42)
Support from romantic or sexual partner
Unsheltered (ref: Shelter) 1.16 (0.60 – 2.24)
Couch-surfing (ref: Shelter) 0.74 (0.27 – 2.01)
Romantic or sexual partner support 4.95 (2.33 – 10.51)
Unsheltered x Romantic or sexual partner support 0.84 (0.33 – 2.13)
Couch-surfing x Romantic or sexual partner support 0.37 (0.09 – 1.58)

46
Table 2.5 Interaction effects between social support and living situation and their association
with transactional sex
Transactional sex
OR (95% CI)
Support from homeless peer
Unsheltered (ref: Shelter) 1.62 (0.74 – 3.52)
Couch-surfing (ref: Shelter) 1.73 (0.68 – 4.39)
Homeless peer support 0.56 (0.19 – 1.62)
Unsheltered x Homeless peer support 1.18 (0.34 – 4.08)
Couch-surfing x Homeless peer support 1.46 (0.30 – 7.04)
Support from home-based peer
Unsheltered (ref: Shelter) 1.73 (0.89 – 3.38)
Couch-surfing (ref: Shelter) 2.50 (1.08 – 5.80)
Home-based peer support 0.70 (0.19 – 5.80)
Unsheltered x Home-based peer support 0.91 (0.19 – 4.50)
Couch-surfing x Home-based peer support 0.56 (0.09 – 3.67)
Support from family
Unsheltered (ref: Shelter) 1.91 (0.92 – 3.96)
Couch-surfing (ref: Shelter) 2.62 (1.05 – 6.56)
Family support 0.79 (0.26 – 2.38)
Unsheltered x Family support 0.79 (0.26 – 2.38)
Couch-surfing x Family support 0.59 (0.12 – 2.93)
Table 2.6 features the final model that contained significant results for couch-surfing
youth. Couch-surfing was associated with over twice the odds of reporting recent transactional
sex relative to youth in shelter (OR = 2.52, 95% CI = 1.13 – 5.62), as was living unsheltered (OR
= 2.06, 95% CI = 1.08 – 3.95). Relative to being White, being Hispanic/Latinx was also
associated with over twice the odds of reporting recent transactional sex (OR = 2.35, 95% CI =
1.11 – 4.98), as was being LGBQ+ relative to being heterosexual (OR = 2.18, 95% CI = 1.26 –
3.76). None of the social support variables—support from a homeless peer, home-based peer, or
family member—were statistically significant in the final model.

47
Table 2.6 Multivariable logistic regression model of factors associated with transactional sex
Transactional sex
OR (95% CI)
Current living situation (ref: Shelter)
Unsheltered 2.06 (1.08 – 3.95)*
Couch-surfing 2.52 (1.13 – 5.62)*
Source of social support
Homeless peer 0.62 (0.36 – 1.05)
Home-based peer 0.61 (0.30 – 1.22)
Family 0.76 (0.43 – 1.32)
Demographics
Age 1.05 (0.93 – 1.20)
Race (ref. White)
Black 1.11 (0.54 – 2.28)
Hispanic/Latinx 2.35 (1.11 – 4.98)*
Multiracial or another race 0.82 (0.40 – 1.69)
Gender identity (ref. Male)
Female 1.09 (0.58 – 2.04)
Transgender or gender-expansive 1.65 (0.78 – 3.48)
LGBQ+ 2.18 (1.26 – 3.76)*
* p < .05
DISCUSSION
Current study findings provide new evidence for the risks involved in couch-surfing, as
transactional sex places young people not only at increased risk for HIV, but for sexual coercion
and exploitation (Tyler & Schmitz, 2018). Relative to those in shelter, couch-surfing youth were
over twice as likely to engage in recent transactional sex (OR = 2.52, 95% CI = 1.13 – 5.62), as
were unsheltered youth (OR = 2.06, 95% CI = 1.08 – 3.95). These findings suggest a specific
association between young people’s living situation and their recent engagement in transactional
sex, and that the magnitude of this relationship is similar between couch-surfers and unsheltered

48
youth. Although the degree to which couch-surfing youth in this sample are living with the
people with whom they are transacting sex is unclear, 20.0% (n = 11) reported residing with a
stranger while the remainder indicated that they were staying with someone they knew, including
friends, family members, and romantic or sexual partners. Prior work has suggested that
transactional sex with a casual partner is associated with housing instability (Bauermeister et al.,
2017) and that trading sex with strangers for a place to stay is common among young women
(Warf et al., 2013) and LGBTQ+ youth (Dank et al., 2015) experiencing homelessness. While we
are unable to disaggregate the different types of couch-surfing hosts in this dataset, it is possible
that some young people’s couch-surfing arrangements are intertwined with and contingent upon
transactional sex, particularly in scenarios where strangers or romantic or sexual partners are
hosting. Considering the relatively high percentage of couch-surfing youth in this sample staying
with familiar connections, we must also consider that transactional sex may be a tactic employed
by youth to avoid overstaying their welcome with a given host while also avoiding the streets.
Notably, Hispanic/Latinx youth were over twice as likely to report engaging in recent
transactional sex relative to their White peers (OR = 2.35, 95% CI = 1.11 – 4.98). While one
previous study on transgender and gender-diverse adults experiencing homelessness indicated
that Black, Hispanic/Latinx, and multiracial adults were more likely to report engaging in
transactional sex (Kattari & Begun, 2017), studies drawing from nationwide samples of either
youth experiencing homelessness (Walls & Bell, 2011) or youth and young adults more broadly
(Ulloa et al., 2016) have only reported Black youth as being more likely to engage in
transactional sex. However, these studies also contrasted with earlier work, which often produced
mixed findings on the association between race and transactional sex. Many of these studies
worked with comparatively smaller, more localized samples of homeless youth populations

49
(Ennett et al., 1999; Green et al., 1999; Hickler & Auerswald, 2009; Rotheram-Borus et al.,
1992), and current study findings could be considered within the context of rising
Hispanic/Latinx homelessness in Los Angeles (Chinchilla & Gabrielian, 2021; Los Angeles
Homeless Services Authority, 2023). This general inconsistency in the literature warrants further
investigation into potential qualitative differences that may vary across different geographic
contexts, intersecting social identities, and structural factors affecting engagement in
transactional sex among youth experiencing homelessness (Alessi et al., 2021; Hickler &
Auerswald, 2009; Walls & Bell, 2011). In contrast, study findings that LGBQ+ youth were
significantly more likely to report recent transactional sex relative to their heterosexual
counterparts (OR = 2.18, 95% CI = 1.26 – 3.76) is consistent with previous literature establishing
that sexual minority youth are at increased risk of engaging in transactional sex (Kattari &
Begun, 2017; Walls & Bell, 2011; Srivastava et al., 2019). This may be attributed in part to the
increased prevalence of other correlates of transactional sex observed among LGBQ+ youth,
including discrimination (Tyler, 2009) and prior sexual victimization (Baams et al., 2019), as
well as less family support and more connections to peers who trade sex (Tyler, 2008).
In addition to the relationship between couch-surfing and HIV risk behavior among youth
experiencing homelessness, the extent to which social support may impact the likelihood of
sexual risk-taking—and whether social support moderates the relationship between couchsurfing and risk behavior—was of key interest. However, social support alone was only
significant in the bivariate analysis; there was no significant interaction effect and no significant
main effect of social support on risk observed in the multivariable models for transactional sex.
These findings suggest that while living situation and social support may be individually
associated with transactional sex, the effect of living situation on transactional sex ultimately

50
eclipses that of social support and that broad social support may have no bearing on the
relationship between living situation and transactional sex. However, prior work has indicated
that it is not only the source of social support but the type of support provided that can vary
across different network members and affect health outcomes (Agneessens et al., 2006), and that
emotional support in particular might be pertinent to young people’s engagement in risk
behaviors (Brown et al., 2020).
Beyond transactional sex, study findings provide important insights into several other
HIV risk and prevention behaviors among couch-surfing youth. Across the five HIV risk
behaviors under study—condomless anal and vaginal sex, sex under the influence of drugs or
alcohol, multiple concurrent sex partners, and engaging in transactional sex—couch-surfing
youth reported the highest rates of both transactional sex (18.0%) and multiple sex partners
(38.2%). While couch-surfing youth reported the lowest rate of condomless anal sex across all
living situations (13.5%), their rates of condomless vaginal sex (29.2%) and sex under the
influence (18.0%) were generally higher than those of youth in shelter and lower than those of
unsheltered youth. The prevalence of these sexual risk behaviors among couch-surfing youth
relative to shelter- and street-based youth highlights that even when youth experiencing
homelessness are temporarily residing with others, they contend with similar HIV risks.
While most youth across living situations reported HIV testing within the preceding six
months, the prevalence of testing among couch-surfing youth (75.0%) was on par with those
reported by youth in shelter (77.7%) and higher than the rates reported by unsheltered youth
(68.9%). PrEP knowledge followed a similar pattern, though rates were markedly lower than
those for HIV testing. The high rates of HIV testing in the overall sample are consistent with
prior research (Ober et al., 2012), and the particularly high rate among shelter youth echoes

51
earlier work finding shelter use to be associated with increased HIV testing among youth
experiencing homelessness due to their more immediate proximity to services and linkages
(Gwadz et al., 2010). The lower rates of PrEP knowledge across the board are also consistent
with research on the low awareness of PrEP among this population (Hsu & Rakhmanina, 2022;
Santa Maria et al., 2018; Santa Maria et al., 2019a) but once more, youth in shelter reported the
highest rates of PrEP knowledge (51.8%), followed by couch-surfing (47.2%) and unsheltered
(39.9%) youth, again likely due to their proximity to social services.
LIMITATIONS
A number of limitations to the current study warrant acknowledgment. The crosssectional data utilized in this analysis preclude the study from drawing any causal interpretations;
longitudinal work is needed to examine how the relative stability of a young person’s living
situation and social support networks over time may impact their engagement in HIV risk and
prevention behaviors. Of particular interest is whether specific changes in a young person’s
couch-surfing status or sources of social support result in changes to the likelihood that they
engage in transactional sex over time. As couch-surfing was not an intended focus of the parent
study, the current study is also limited by its measure of living situation. Future studies might
capture greater detail concerning with whom youth are residing and the nature of these specific
relationships in tandem with details concerning their sexual partners. This additional information
would enable a clearer examination of more complex relational dynamics involved with
engagement in transactional sex than what the current analysis allows.
The sites from which participants were recruited into the parent study must also be
considered, as the couch-surfing youth in the current sample likely represent a narrower range of

52
experiences. Youth were recruited from drop-in centers located in the two primary hubs for
homeless youth services in Los Angeles: Hollywood and Venice. While drop-in centers serve as
critical safe havens helping to meet the basic needs of youth experiencing homelessness (Rice et
al., 2023; Slesnick et al., 2016), couch-surfing youth may be more disconnected from the
homeless services system than street-involved youth (Tyler et al., 2020; Vichta-Ohlsen et al.,
2017). This may be attributed to couch-surfers’ lack of knowledge of available resources,
negative experiences with or perceptions of social services, and/or being considered lower
priority by both the homeless services system and themselves (Beekman et al., 2021; Hail-Jares,
et al., 2021; McLoughlin, 2013). Additionally, urbanicity may be a factor in the prevalence of
couch-surfing among this population (Curry et al., 2017) and such youth may have been less
likely to be encountered in Hollywood and Venice than in more suburban or rural communities.
CONCLUSION
This study provides new empirical evidence that among youth experiencing
homelessness, couch-surfing is significantly associated with transactional sex. These findings
challenge notions regarding the relative safety of couch-surfing and underscore the need for
more nuanced and responsive policies regarding how these youth are prioritized for housing
resources. Service providers need to be able to recognize and respond to young people whose
couch-surfing may be intertwined with some form of transactional sex, as these youth are at
increased risk for HIV as well as sexual victimization. Engaging couch-surfing youth in
assessing their level of risk and helping to identify potential resources to reduce their risk are
vital to promoting their sexual health and their overall safety and well-being. While these
strategies may include easy access to condoms, HIV testing, and PrEP, some young people may

53
also require an alternative housing arrangement. However, without increased housing resources
for couch-surfing youth, service providers may be limited in facilitating these young people’s
access to safe and stable housing.

54
CHAPTER 3. COUCH-SURFING AND SOCIAL SUPPORT TYPOLOGIES
ASSOCIATED WITH HIV-RELATED BEHAVIOR: A LATENT CLASS ANALYSIS
INTRODUCTION
Homelessness and connections to risky peer networks have long been established as
increasing the likelihood of engagement in HIV risk behavior among youth (Barman-Adhikari et
al., 2018; Hsu et al., 2018; Kattari et al., 2017; Kennedy et al., 2012; Rice et al., 2011; Rice et al.,
2008; Rice et al., 2007; Tyler, 2013). However, further work is needed to disentangle the types of
homelessness situations and sources of social support that may affect HIV risk. While the
previous chapter outlined the importance of recognizing couch-surfing as a distinct context
impacting young people’s sexual behavior and the role social support networks play in affecting
HIV risk, the current chapter seeks to examine the heterogeneity of couch-surfing youth with
respects to their social support networks and how variations in these networks may correlate with
HIV-related behaviors.
The heterogeneity of couch-surfing and its impact on risk behavior
Although couch-surfing youth are seldom investigated as their own distinct subgroup
within the population of youth experiencing homelessness, there is evidence that the experience
of couch-surfing is not monolithic. A handful of researchers describe contexts in which couchsurfing can provide important social and emotional supports to youth experiencing homelessness.
In their qualitative study of nine Midwestern couch-surfing youth between the ages of 17 and 23
and their hosts, Curry and colleagues (2021) describe relationships that extend beyond meeting a
housing need to provide emotional support and help youth connect to services and obtain
resources. In qualitative work with fourteen couch-surfing youth in Australia, McLoughlin

55
(2013) notes that youth who found themselves couch-surfing in supportive environments were
able to reconnect with resources that positively altered their housing trajectories—however, these
youth were part of a scant few. Interviewing a sample of 32 Latino foster care alumni in Texas,
Perez & Romo (2011) highlight the importance of supportive peer networks in helping youth
avoid the streets, connect to social services, and buffer against the psychological distress of
unstable and precarious housing.
Other studies detail couch-surfing in unsupportive and risky environments, with some
researchers positing that couch-surfing can be intertwined with youth engaging in substance
abuse and transactional sex. In another qualitative study of 41 youth living in a rural Washington
community conducted by Curry and colleagues (2019), youth frequently reported couch-surfing
at trap houses—homes where young people sell and use drugs (Nichols & Braimoh, 2018)—that
initiated or exacerbated their own substance abuse. Curry and colleagues noted that these trap
houses were predominantly provided by peers and sometimes family, key network members
youth turned to when trying to avoid the streets in a community with few formal supports.
Additionally, as discussed in preceding chapters, transactional sex has been linked to couchsurfing, particularly among sexual and gender minority youth (Arrington-Sanders et al., 2022;
Dank et al., 2015). Most recently, qualitative interviews with 31 LGBTQ+ couch-surfing youth
in Australia relayed several queer young people’s experiences with trading sex to obtain or
maintain a place to stay (Hail-Jares, 2023). While some of these experiences aligned with
common depictions of transactional sex as an exploitive quid pro quo arrangement, several
young people in the study distinguished between sexual exchange and sex work, describing the
latter as an empowering opportunity to make money for securing other temporary
accommodations. Altogether, these qualitative studies illustrate the diversity of couch-surfing

56
experiences among youth experiencing homelessness and suggest that the relational facets of
young people’s couch-surfing arrangements can impact their risk-taking behavior. However,
these dynamics have yet to be explored quantitatively within a larger population of couch-surfing
youth or situated in relation to other homeless experiences.
Variation in the social support networks of youth experiencing homelessness
The social networks of youth experiencing homelessness are relatively diverse in their
composition and often include home-based peers (i.e., friends known prior to experiencing
homelessness), romantic and sexual partners, family members, service provider staff, and
homeless peers (Barman-Adhikari et al., 2016; De La Haye et al., 2012; Tyler & Melander, 2011;
Wenzel et al., 2012). Unfortunately, despite the heterogeneity of their composition, the networks
of youth experiencing homelessness are frequently resource poor (Nevard et al., 2021; Wenzel et
al., 2012) and these young people report lower rates of perceived social support from network
members relative to their housed peers (Brown et al., 2020; Menke, 2000). Rates of social
support reported among youth experiencing homelessness vary across studies, which may be due
in part to the myriad measures of social support employed. In their study of 1,046 youth
experiencing homelessness in Los Angeles, Barman-Adhikari et al. (2016) measured social
support to include people youth could rely on to lend them money, give them food, or provide a
play to stay (instrumental support), and people youth confided in or who made them feel cared
for (emotional support). Only 25% of youth in the study indicated receiving social support from
their network. In contrast, a survey of 693 youth experiencing homelessness in Atlanta by Wright
and colleagues (2017) measured social support by asking youth to identify network members in

57
whom they could confide or turn to for help; 65% of youth indicated at least one source of social
support.
Even in studies with youth reporting lower overall rates of social support, differences in
types and sources of support have emerged. Relative to their White peers, Black youth indicate
significantly more family and home-based peers in their social support networks (Brown et al.,
2020)—connections they are also more likely than White youth to draw upon for temporary
housing arrangements in addition to maintaining more regular contact (Hickler & Auerswald,
2009). LGBQ+ youth have been reported to be less likely to get instrumental support from homebased peers (Barman-Adhikari et al., 2016) and more likely to have little to no social support
(Brown et al., 2020). Meanwhile, findings on gender have been inconsistent. Some studies report
female youth experiencing homelessness as more likely to be entrenched in street networks and
detached from family and home-based peers (Rice et al., 2012; Valente & Auerswald, 2013;
Wright et al., 2017), while others have indicated female youth as highly connected to family and
home-based peer supports (Brown et al., 2020)—or found no significant gender differences at all
(Barman-Adhikari et al., 2017). Studies have also observed that the longer youth experience
homelessness, the less likely they are to report receiving social support (Barman-Adhikari et al.,
2016; Rice et al., 2008; Wright et al., 2017). In regards to living situation, studies have noted that
youth living on the streets are at increased odds of reporting little to no social supports (BarmanAdhikari et al., 2016; Brown et al., 2020) and recent work suggests that emotional support from
home-based peers is associated with increased odds of couch-surfing (Petry et al., in revisions).
What remains unclear is whether there is greater diversity in the social support networks of
couch-surfing youth that differ significantly along demographic characteristics and influence
HIV-related behaviors.

58
Typologies of youth experiencing homelessness
Identifying subgroups of individuals based on a given set of characteristics can have
important implications for service provision through informing more targeted intervention and
prevention efforts (Barlie et al., 2018). Latent class analysis (LCA) is a statistical technique for
detecting otherwise unobserved heterogeneity within a sample (Hagenaars & McCutcheon,
2002) and identifying “qualitatively different subgroups within populations who often share
certain outward characteristics” (Weller et al., 2020). In the research on youth homelessness,
LCA has been used to identify subgroups based on victimization experiences (Bender et al.,
2014; Tyler & Ray, 2019), risk and protective factors (Altena et al., 2018; Milburn et al., 2009),
and substance use (Bender et al., 2014; Brown et al., 2024; DiGuiseppi et al., 2020). LCA has
also previously been employed to identify sexual risk classes among youth experiencing
homelessness, as Santa Maria and colleagues (2020) identified two distinct sexual risk classes,
“lower risk” and “higher risk,” based on a set of sexual risk behavior and sexual assault
variables. Female youth and LGBQ+ youth were significantly more likely to be in the “higher
risk” group, but there were no significant differences observed based on living situation.
Meanwhile, to date, only one study appears to have identified subgroups of youth
experiencing homelessness based on their social support networks. Brown and colleagues (2020)
examined a sample of 1,046 youth experiencing homelessness in Los Angeles and identified five
subgroups based on both the type (emotional, instrumental, and service, the latter of which was
analogous to informational support) and composition (family, service provider, home-based peer,
and street-based peer) of young people’s support networks. These five emergent subgroups
included: (1) high emotional and service support from staff; (2) high emotional, service, and
instrumental support from home-based peers and family members; (3) moderate emotional

59
support from street- and home-based peers; (4) low or no support; and (5) high emotional and
instrumental support from home-based peers and family. In exploring associations with class
membership and demographic characteristics, Brown and colleagues reported that Black youth
and female youth were significantly more likely to be in the high emotional and instrumental
support from home-based peers and family class than the low or no support class. Meanwhile,
LGBQ+ youth were significantly more likely to be in the low or no support class than in a class
with social supports. In relationship to substance use, youth reporting recent heroin use were
significantly more likely to be in the low or no support class than the high staff emotional and
service support class. Youth reporting recent marijuana use were significantly more likely to be
in the high home-based peer and family emotional and instrumental support class.
Findings from the Brown and colleagues (2020) study suggest the existence of key
differences in the social support networks of youth experiencing homelessness and point toward
how health behaviors may be correlated with certain support networks. Considering the role
social networks play in how young people experience homelessness (Curry et al., 2021;
McLoughlin, 2013; Petry et al., in revisions), how living situation might factor into clustering
youth experiencing homelessness based on their social support networks—and how these
resultant subgroups may be associated with HIV-related behaviors—warrants further study.
CURRENT STUDY
Building upon the previous chapter, the current study continues to address gaps in the
current literature on couch-surfing, social support, and HIV risk among youth experiencing
homelessness. This study features a closer examination of the socioenvironmental contexts
surrounding young people’s experiences of homelessness and their effect on sexual risk behavior,

60
and will conduct a latent class analysis to explore the heterogeneity of youth experiencing
homelessness based on their living situation and sources of social support. Following the
identification of emergent subgroups, this study will examine whether (a) minoritized identities
or prolonged homelessness relate to belonging to certain subgroups and (b) specific HIV and
prevention behaviors vary across specific subgroups. It is anticipated that profiles will emerge in
which one subset of couch-surfing youth will report social support from family members and
home-based peers, while another subset of couch-surfing youth will be less likely to report these
same sources of social support and may instead report little to no social support. We might
expect that youth in the former group will be less likely to engage in sexual risk-taking and those
in the latter will be more likely. Additionally, given prior work suggesting that Black youth and
LBGQ+ youth are more likely to couch-surf (Petry et al., 2022) and that these groups of youth
report different levels of social support (Brown et al., 2020), it is expected that being Black will
be associated with a more family-connected subgroup while being LGBQ+ will be associated
with a less supportive network.
METHODS
PARTICIPANTS AND PROCEDURES
The current analysis used baseline data from Have You Heard? (HYH), an HIV
prevention intervention study of youth experiencing homelessness (see Rice et al., 2021).
Between September 2016 and October 2018, participants were recruited across three of the most
frequented drop-in centers for youth experiencing homelessness in Los Angeles. Every youth
who accessed these drop-in services during the study period was eligible to participate in the
study and approached by research staff upon entry. Study participants provided informed consent

61
prior to completing an anonymous, computerized, self-administered survey. Approximately 60
minutes in length, the survey assessed young people’s sociodemographic characteristics, personal
social networks, HIV risk behaviors, and sexual health communication behavior. Youth received
a $20 gift card as compensation for their time and participation. Survey items and study
procedures were approved by the University of Southern California Institutional Review Board.
At baseline, a total of 731 youth between the ages of 14 and 26 participated in the HYH
study. For the current study, youth younger than 18 (n = 14), older than 25 (n = 4), or of
unknown age (n = 1) were removed from the dataset. Given the concerns of the current study,
those who indicated residing somewhere other than a shelter program, on the streets, or “couchsurfing” were also removed. These other living situations included stable housing (n = 70);
hotels or motels (n = 36); institutional settings such as foster care, jail or prison, or inpatient
facilities (n = 11); or some other non-specified location (n = 40). These exclusions resulted in a
final analytic dataset comprised of 556 youth.
MEASURES
Current living situation. Current living situation was used as a latent class indicator
variable in the present analysis and assessed by asking youth to identify the type of location they
spent most of their nights in the preceding two weeks. In the current study, living situation was
recoded to include only three categories: couch-surfing, unsheltered, and shelter. Couch-surfing
included youth who reported staying at the home of someone they knew (e.g., family member,
friend, or romantic partner) or with a stranger. Unsheltered included youth who reported living
outside or in a vehicle, abandoned building, or similar location not meant for human habitation.

62
Shelter included youth who reported residing in either an emergency shelter or transitional
housing program.
Social support. Along with current living situation, social support variables were used as
latent class indicators. These variables were derived from social network questions designed to
identify different types of support provided by different types of social connections within a
young person’s network (Agneessens et al., 2006; Wellman & Wortley, 1990). Youth were asked
to name up to five individuals with whom they had the most contact in the past month, an
approach based on recall patterns observed in egocentric network surveys whereby respondents
tend to name social network members in descending order of tie strength (i.e., relationship
closeness) and frequency of contact (Burt, 1984; Marsden & Hollstein, 2023; Töpfer &
Hollstein, 2021). Following the identification of these five network members, youth were then
prompted to indicate which of these network members, if any, provided specific types of social
support. The current study examined five key types of social network members: family, homebased peers, romantic or sexual partners, homeless peers, and service provider staff. Family
included biological, adopted, or foster family members and excluded street or other chosen
family. Home-based peers included other young people between the ages of 14 and 25 who the
participant knew prior to becoming homeless and who were also not currently experiencing
homelessness. Romantic or sexual partners included individuals with whom youth reported
being romantically or sexually involved. Homeless peers included other youth between the ages
of 14 and 25 who were also currently experiencing homelessness. Service provider staff included
individuals the participant identified as a case manager, agency staff member, or volunteer.
Social support was measured by asking participants to indicate which of their identified
=network members provided either emotional, instrumental, informational, or appraisal support.

63
Network members to whom youth felt they could turn to when feeling depressed or dealing with
major issues were coded as providing emotional support. Network members from whom youth
could borrow money or other material things when needed were coded as providing instrumental
support. Network members with whom youth talked about where to get social services were
coded as providing informational support. Finally, network members from whom youth received
encouragement in meeting their goals were coded as providing appraisal support. For the current
study, the endorsement of at least one form of social support was used to create a dichotomous
variable representing whether a given network member was a source of social support. Together
with the network member variables, this broader social support variable was used to construct a
series of dichotomous variables indicating the presence of specific supportive relationships
within a young person’s network. For example, a youth who identified a family member in their
network who was a source of social support was coded as “1,” indicating the presence of family
support. Meanwhile, a youth who either did not identify a family member in their network at all
or who identified a family member who did not provide them with social support was coded as
“0,” indicating the absence of family support.
HIV risk and prevention behavior. Specific HIV risk and prevention behaviors under
study were included as distal outcomes in the present analysis. Risk behaviors included
condomless anal sex, condomless vaginal sex, multiple concurrent partners, sex under the
influence, and transactional sex. Youth were asked to identify up to five sexual partners in the
preceding 30 days. If youth identified at least one sexual partner, they were asked a series of
questions about their sexual behaviors with each sexual partner identified. Like the construction
of the social support variables, the endorsement of a given HIV-related behavior with at least one
sexual partner was used to create a dichotomous variable indicating whether youth engaged in a

64
specific behavior. Condomless anal sex was coded as “1” if youth reported at least one sexual
partner wherein a condom was not used during anal sex and “0” if youth reported only having
anal sex with a condom or not having any anal sex. Condomless vaginal sex was similarly coded.
Multiple concurrent partners was coded as “1” if youth reported two or more sexual partners in
the past 30 days and “0” if youth reported one sexual partner or none. Sex under the influence
was coded as “1” if youth reported that either themselves or their partner were under the
influence of drugs or alcohol while having sex and “0” if youth did not. Lastly, transactional sex
was coded as “1” if youth reported trading sex or sexual content (i.e., videos or photos) in
exchange for money, a place to stay, food, or other non-monetary items, and “0” if youth did not
report engaging in transactional sex.
HIV prevention behaviors under study included HIV testing, PrEP knowledge, and ever
prescribed PrEP, and were each created as dichotomous variables. HIV testing was coded as “1”
if youth reported getting an HIV test within the previous six months and “0” if youth reported
getting tested more than six months ago or having never been tested. PrEP knowledge was
assessed using a four-point Likert scale to measure how much youth knew about the HIV
prevention medication. PrEP knowledge was coded as “1” if youth knew “a little bit about it” or
“a lot about it” and “0” if youth “never heard of it” or “heard of it, but don’t know what it is.”
Ever prescribed PrEP was coded as “1” if youth indicated ever having a PrEP prescription and
“0” if not.
Demographic characteristics. Gender identity, sexual orientation, and race or ethnicity
were included as auxiliary predictors in the current analysis. Gender identity was a nominal
variable that included male, female, transgender, and gender-expansive youth, with male youth
used as the referent group. For the present analysis, non-binary, genderqueer, gender non-

65
conforming, or other gender-diverse youth were combined into a single category with
transgender youth due to their relatively small numbers (n = 23). Sexual orientation was also
collected as a nominal variable in which participants identified their sexuality as either lesbian,
gay, bisexual, questioning, asexual, heterosexual, or with another sexual identity. This variable
was recoded as a dichotomous variable in which non-heterosexual youth were coded as “1” and
heterosexual youth were coded as “0.” Race or ethnicity was coded as a nominal variable with
four categories: (1) Black, (2) Hispanic/Latinx, (3) White, and (4) multiracial or some other race,
with White youth selected as the referent group. Given their smaller numbers, youth identifying
with ‘some other race’ were combined with multiracial youth and included American Indian or
Alaska Native (n = 18), Asian (n = 8), and Native Hawaiian or Other Pacific Islander (n = 1)
youth.
Duration of homelessness. Duration of homelessness was also included as an auxiliary
predictor and collected as a categorical variable assessing the length of the young person’s most
recent episode of homelessness. Original response categories included less than one week, one
week to one month, one to six months, six months to one year, one to three years, and more than
three years. This variable was recoded as a dichotomous variable in which youth who reported
currently experiencing homelessness for six months to one year, one to three years, or more than
three years were coded as “1” and youth who selected shorter lengths of time were coded as “0.”
ANALYSIS
Latent class analysis (LCA) identifies subgroups within a sample and highlights the
profiles and conditional probabilities of behaviors within a given profile (McCutcheon, 1987;
Lanza & Rhoades, 2013). In the current study, LCA will be conducted in Mplus 8.1 (Munthén &

66
Munthén, 2017) to identify profiles of youth experiencing homelessness based on their living
situation (i.e., living unsheltered, couch-surfing, or residing in a shelter program) and social
support networks (i.e., emotional, instrumental, informational, or appraisal support from family,
home-based peers, romantic or sexual partners, homeless peers, or service provider staff). This
person-centered approach allows for identification of subgroups of youth who are similar to each
other but different from those in other classes based on their current living situation and sources
of social support (Oberski, 2016).
Model fit will be assessed using decreases in Bayesian Information Criteria (BIC) and the
sample size adjusted Bayesian Information Criteria (aBIC). Class selection will be based on BIC
or aBIC values increasing from the prior model to determine which class is a better fit to the data
(Sclove, 1987). Further, the Lo-Mendell-Rubin adjusted likelihood ratio test (LMR), Vuong-LoMendell-Rubin Likelihood Ratio Test (VLRT), and bootstrapped likelihood ratio test (BLRT)
will be used to evaluate the increase in model fit between k – 1 and k class models (Nylund et al.,
2007; Nylund-Gibson & Choi, 2018). Inclusion of any small emergent classes representing less
than 5% of the sample will be assessed based on model fit statistics and whether the small class
makes conceptual sense and is distinct from other classes (Weller et al., 2020).
To understand how race or ethnicity, gender, sexual identity, and duration of
homelessness are related to class membership, latent class regression will be utilized wherein
these characteristics will be entered into the model to predict membership in the emergent
classes. Latent class regression uses a variable represented by the posterior probability of class
assignment as the outcome variable (Lanza et al., 2013). The final model in this step results in a
multinomial logistic regression using one of the classes as the reference category.

67
Finally, to better understand how HIV risk and prevention behaviors—including
condomless sex, multiple concurrent partners, sex under the influence, transactional sex, recent
HIV testing, and PrEP awareness—vary across emergent classes, the DCAT option in Mplus will
be used to obtain pairwise comparisons of HIV-related behavior probability. This method is
based on the Lanza, Tan, and Bray (LTB) approach, which follows three steps: (1) the LCA is
estimated using only latent class indicator variables, (2) the highest probability of class
membership is used to assign classes, and (3) associations between class membership and
outcomes are estimated with an adjustment based on classification uncertainty (Lanza et al.,
2013). Figure 3.1 provides a visual representation of the proposed latent class analysis.
Figure 3.1 Model for latent class analysis

68
RESULTS
Sample characteristics for the current study are displayed in Table 3.1. On average, youth
were 21.9 years old at the time of the survey. Youth of color were in the majority, with 31.5%
identifying as Black ,14.5% as Hispanic/Latinx, and 30.9% as multiracial or with another race
other than White. Most youth were male (66.9%), followed by 21.4% who were female and
11.7% who were transgender or gender-expansive. A sizeable minority (42.6%) identified as
LGBQ+. With respects to their current homelessness, 43.8% of youth reported that their current
episode had lasted longer than six months. Over half (53.6%) indicated living on the streets,
30.4% reported residing in a shelter program, and 16.0% were couch-surfing.
Of the five different sources of social support under study, youth most frequently
endorsed receiving support from homeless peers (46.4%), followed by family (39.6%), a
romantic or sexual partner (36.2%), service provider staff (23.6%), and home-based peers
(22.5%).
Over one-third of youth (34.5%) reported multiple sexual partners in the last 30 days. In
regards to other HIV risk behaviors, 30.4% reported having condomless vaginal sex, 23.6%
reported condomless anal sex, 24.5% reported having sex under the influence, and 14% reported
engaging in transactional sex. Most youth (72.6%) reported being tested for HIV within the past
six months, but less than half (44.6%) indicated knowledge of PrEP and 9.0% reported ever
being prescribed PrEP.

69
Table 3.1 Sample characteristics of youth experiencing homelessness (n = 556)
n (%) mean (SD)
Demographics
Age 21.9 (2.0)
Race (n = 553)
Black 174 (31.5)
Hispanic/Latinx 80 (14.5)
White 128 (23.2)
Multiracial or another race 171 (30.9)
Gender identity
Male 372 (66.9)
Female 119 (21.4)
Transgender or gender-expansive 65 (11.7)
LGBQ+ (n = 550) 234 (42.6)
Current homelessness
Duration of >6 months (n = 544) 238 (43.8)
Living situation
Unsheltered 298 (53.6)
Couch-surfing 89 (16.0)
Shelter 169 (30.4)
Sources of social support
Family 220 (39.6)
Home-based peer 125 (22.5)
Romantic or sexual partner 201 (36.2)
Homeless peer 258 (46.4)
Service provider staff 131 (23.6)
HIV risk and prevention behaviors
Condomless anal sex* 131 (23.6)
Condomless vaginal sex* 169 (30.4)
Multiple concurrent partners* 192 (34.5)
Sex under the influence* 136 (24.5)
Transactional sex* 78 (14.0)
HIV test in past 6 months (n = 550) 339 (72.6)
Know about PrEP (n = 548) 245 (44.7)
Ever prescribed PrEP 50 (9.0)
* past 30 days

70
Fit indices for latent class models based on living situation and sources of social support
are displayed in Table 3.2. While the BIC pointed toward a three-class solution, the adjusted-BIC
suggested a four-class solution as the best fit for the data. Given the marked drops in the LRT,
VLRT, and BLRT observed in the four-class solution, a three-class solution was selected wherein
BIC = 4545.89; adjusted-BIC = 4472.87; LRT = 54.98 (p < .05); VLRT = 56.07 (p < .05); and
BLRT = 56.07 (p < .001).

71
Table 3.2 Fit indices for latent class models
7-class
0.72
-2161.93
4323.85
4671.85
4671.50
4496.90
10.60, p>.05
10.81, p>.05
10.81, p>.05
* Tests not applicable to 1-class solution.
Note. AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; LRT = Lo-Mendell Rubin Adjusted Likelihood Ratio Test; -
VLRT = Vuong-Lo-Mendell Rubin Likelihood Ratio Test; BLRT = Bootstrapped Likelihood Ratio Test -
6-class
0.75
-2167.33
4428.67
4428.67
4631.74
4482.54
12.62, p>.05
12.87, p>.05
12.87, p>.05
5-class
0.73
-2173.77
4425.53
4425.53
4594.04
4470.24
22.73, p > .05
23.18, p > .05
23.18, p < .001
4-class
0.69
-2185.36
4370.71
4432.71
4566.66
4468.25
29.22, p > .05
29.80, p > .05
29.80, p < .001
3-class
0.64
-2200.25
4400.51
4446.51
4545.89
4472.87
54.98, p < .05
56.07, p < .05
56.07, p <. 001
2-class
0.66
-2228.29
4456.58
4486.58
4551.39
4503.77
83.72, p < .01
85.38, p < .01
85.38, p < .001
1-class
*
-2270.98
4541.95
4555.95
4586.20
4563.98
*
*
*
Entropy
Log-likelihood
Negative 2 loglikelihood
AIC
BIC
Adjusted BIC -
LRT, p-value
VLRT, p-value
BLRT, p-value

72
Figure 3.2 depicts the conditional probabilities by class based on living situation and
social support. Classes were largely differentiated based on social support networks and, with the
exception of Class 3, living situation probabilities were reflective of the overall sample
distribution and referred to as heterogeneous homelessness in the subsequent class names. Class
1 (n = 293; 52.7%) was labeled Family support and heterogenous homelessness as youth in this
class had a higher probability of reporting social support from a family member and more
moderate probabilities of reporting social support from other types of network connections;
living situation probabilities were similar to the sample distribution overall. Class 2 (n = 139;
25.0%) was labeled Very little support and heterogeneous homelessness, as youth in this class
indicated very low probabilities of reporting any sources of social support, including zero
probability of reporting support from either home-based peers or homeless peers; living situation
probabilities were similar to the sample distribution overall. Finally, Class 3 (n = 124; 22.3%)
was labelled Homeless peer support and no couch-surfing due to youth in this class having a
high probability of reporting social support from homeless peers and zero probability of couchsurfing.

73
Figure 3.2 Conditional probabilities of class membership
Descriptive statistics of demographic and homelessness characteristics by class are
displayed in Table 3.3. Results of chi-square tests indicate that class membership differed
significantly with respects to race and ethnicity (X2 = 15.42, p = .02), gender identity (X2 =
15.67, p < .01), and sexuality (X2 = 11.50, p = .02). Youth of color remained a consistent majority
across classes, with Hispanic/Latinx youth found at a higher rate (20.1% vs. 14.5%) and Black
youth at a slightly lower rate (26.6% vs. 31.5%) in the Very little support and heterogeneous
homelessness class than seen in the overall sample. Transgender and gender-expansive youth
were present at a much lower rate (5.8%) in the Very little support and heterogeneous
homelessness class and markedly higher rate (20.2%) in the Homeless peer support and no
couch-surfing class compared to 11.7% in the overall sample. Age and duration of homelessness
were not significantly associated with class membership and thus not retained in subsequent
analyses.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Unsheltered
Couch-surfing
Shelter
Family
Home-based peer
Homeless peer
Intimate partner
Provider staff
Class 1: Family support and heterogenous homelessness
Class 2: Very little support and heterogenous homelessness
Class 3: Homeless peer support and no couch-surfing

74
Table 3.3 Demographic characteristics of class membership
Family
support and
heterogeneous
homelessness
(n = 293)
n (%)
Very little
support and
heterogeneous
homelessness
(n = 139)
n (%)
Homeless peer
support and
no couchsurfing
(n = 124)
n (%)
X2 or F
Demographics
Age, mean (SD) 21.8 (2.0) 21.9 (2.1) 22.2 (1.7) 15.65
Race/ethnicity 15.42*
Black 96 (32.8) 45 (32.4) 33 (26.6)
Hispanic/Latinx 40 (13.7) 28 (20.1) 12 (9.7)
White 59 (20.1) 30 (21.6) 42 (33.9)
Multiracial or another race 98 (33.4) 36 (25.9) 37 (29.8)
Gender identity 15.67**
Male 204 (69.6) 98 (70.5) 70 (56.4)
Female 57 (19.5) 33 (23.7) 29 (23.4)
Transgender or gender-
expansive
32 (10.9) 8 (5.8) 25 (20.2)
LGBQ+ 124 (42.6) 48 (35.6) 62 (50.0) 11.50*
Current homelessness
Duration of >6 months 116 (40.1) 66 (49.6) 56 (45.9) 3.63
* p < .05; ** p < .01
To explore associations between demographic characteristics and class membership, a
series of latent class regressions were performed; results are displayed in Table 3.4. Relative to
White youth, Black youth (OR = 2.73; 95% CI = 1.23 – 6.19) and youth categorized as
multiracial or another race (OR = 2.60; 95% CI = 1.12 – 5.42) were significantly more likely to
be in the Family support and heterogeneous homelessness class than the Homeless peer support
and no couch-surfing class. Transgender and gender-expansive youth were at significantly
decreased odds of being in the Family support and heterogeneous homelessness class compared
to the Homeless peer support and no couch-surfing class, relative to their male counterparts (OR
= 0.32; 95% CI = 0.14 – 0.78). Transgender and gender-expansive youth were also at decreased
odds of being in the Very little support and heterogeneous homelessness class compared to the

75
Homeless peer support and no couch-surfing class relative to male youth (OR = 0.16; 95% CI =
0.05 – 0.52), as were LGBQ+ youth relative to heterosexual youth (OR = 0.49; 95% CI = 0.27 –
0.90).
Table 3 4 Correlates of class membership
Ref. Homeless peer
support and no couchsurfing
(n = 124)
Family support and
heterogeneous homelessness
(n = 293)
Very little support and
heterogeneous homelessness
(n = 139)
Odds Ratio 95% Confidence
Interval
Odds Ratio 95% Confidence
Interval
Demographics
Age 0.86 0.75 – 1.00 0.89 0.77 – 1.03
Race/ethnicity (ref.
White)
Black 2.73 1.23 – 6.19* 2.18 1.0 – 4.75
Hispanic/Latinx 3.96 1.07 – 9.66 4.08 1.49 – 11.16
Multiracial or another
race
2.60 1.12 – 5.42* 1.44 0.65 – 3.19
Gender (ref. Male)
Female 0.56 0.27 – 1.20 0.76 0.38 – 1.53
Transgender or gender-
expansive
0.32 0.14 – 0.78* 0.16 0.05 – 0.52*
LGBQ+ 1.02 0.38 – 1.23 0.49 0.27 – 0.90*
Current homelessness
Homeless >6 months 0.85 0.39 – 1.28 1.18 0.65 – 2.13
* p < .05
The relationship between class membership and engagement in specific HIV risk and
prevention behaviors was first assessed through a series of chi-square tests, displayed in Table
3.5. Results indicated that youth belonging to either the Very little support and heterogeneous
homelessness class or Homeless peer support and no couch-surfing class differed significantly in
reporting sex under the influence in the past 30 days (X2 = 7.14, p =.01). Additionally, youth

76
belonging to the Family support and heterogeneous homelessness and Very little support and
heterogeneous homelessness classes differed significantly in reporting recent transactional sex
(X2 = 5.89, p <.05). Youth in the Family support and heterogeneous homelessness and Homeless
peer support and no couch-surfing classes also differed significantly with respects to reporting
knowledge of PrEP (X2 = 4.62, p <.05), as did youth in either the Very little support and
heterogeneous homelessness or Homeless peer support and no couch-surfing classes (X2 = 9.38,
p <.01).
Table 3.5 Relationship between class membership and engagement in HIV-related behaviors
Family support
and heterogenous
homelessness
vs.
Very little support
and heterogeneous
homelessness
X2 (p-value)
Family support and
heterogenous
homelessness
vs.
Homeless peer
support and no
couch-surfing
X2 (p-value)
Very little support
and heterogenous
homelessness
vs.
Homeless peer
support and no
couch-surfing
X2 (p-value)
HIV Risk Behavior
(past 30 days)
Condomless anal sex 1.79 (p = .18) 0.56 (p = .45) 3.81 (p = .05)
Condomless vaginal sex 1.89 (p =.17) 3.51 (p =.06) 0.39 (p = .53)
Multiple concurrent
partners
2.72 (p = .09) 0.01 (p = .95) 2.09 (p = .15)
Sex under the influence 2.56 (p = .11) 1.51 (p = .22) 7.14 (p =.01)*
Transactional sex 5.89 (p =.02)* 0.37 (p =.54) 2.85 (p = .09)
HIV Prevention
Behavior
HIV testing (past 6
months)
2.88 (p = .09) 0.11 (p = .74) 1.38 (p =.24)
PrEP knowledge 0.97 (p =.33) 4.62 (p = .04)* 9.38 (p < .01)**
Ever prescribed PrEP 0.26 (p =.61) .83 (p =.362) 0.19 (p = .66)
* p < .05; ** p < .01
Statistically significant relationships (p < .05) between class membership and HIV-related
behaviors observed in the preceding analysis were then carried forward into a series of bivariate

77
logistic regressions to assess the directionality of these associations. The results of this regression
analysis are displayed in Table 3.6. Relative to youth in the Homeless peer support and no
couch-surfing class, those in the Very little support and heterogeneous homelessness class were
significantly less likely to report having sex under the influence in the past 30 days (OR = 0.38;
95% CI = 0.19 – 0.79). Compared to youth in the Very little support and heterogeneous
homelessness class, youth in the Family support and heterogeneous homelessness class were
significantly less likely to report recently engaging in transactional sex (OR = 0.40; 95% CI =
0.19 – 0.82). Relative to youth in the Homeless peer support and no couch-surfing class, youth in
either the Family support and heterogeneous homelessness (OR = 0.52; 95% OR = 0.29 – 0.95)
or Very little support and heterogeneous homelessness (OR = 0.40, 95% CI = 0.22 – 0.73) classes
were significantly less likely to report knowledge of PrEP.

78
Table 3.6 Odds of engagement in HIV risk and prevention behaviors in the past 30 days based on
class membership
Sex under the
influence
Transactional sex PrEP knowledge
OR (95% CI) OR (95% CI) OR (95% CI)
Class comparison
Family support and
heterogenous
homelessness
vs.
Very little support
and heterogeneous
homelessness
1.72 (0.85 – 3.49) 0.40 (0.19 – 0.82)* 1.32 (0.76 – 2.30)
Family support and
heterogeneous
homelessness
vs.
Homeless peer
support and no
couch-surfing
0.66 (0.35 – 1.26) 0.75 (0.30 – 1.86) 0.52 (0.29 – 0.95)*
Very little social
support and
heterogeneous
homelessness
vs.
Homeless peer
support and no
couch-surfing
0.38 (0.19 – 0.79)* 1.89 (0.88 – 4.08) 0.40 (0.22 – 0.73)*
* p < .05

79
DISCUSSION
The current study represents the first known investigation of whether profiles of youth
experiencing homelessness based on current living situation and sources of social support differ
significantly with respects to HIV risk and prevention behavior. Results of a latent class analysis
identified three subgroups of youth: (1) the Family support and heterogeneous homelessness
class (n = 293; 52.7%), (2) the Very little support and heterogeneous homelessness class (n =
139; 25.0%), and (3) the Homeless peer support and no couch-surfing class (n = 124; 22.3%).
Couch-surfing youth had zero probability of being in the class dominated by social support from
homeless peers and modest probabilities of belonging to classes characterized by either family
support or very little support overall (23% and 18%, respectively). These results suggest both the
heterogeneity of social support among couch-surfing youth and the relative isolation of couchsurfing youth from homeless peer networks. It has long been established that the longer a young
person remains homeless, the more detached they become from ‘pro-social’ peers and the more
entrenched they become with risky peer networks and increasingly engaged in sexual risk
behavior (Rice et al., 2007; Rice et al., 2008; Rice et al., 2011). However, duration of
homelessness in the current study was not correlated with class membership and alternative
explanations must be considered. Even among couch-surfing youth who are accessing homeless
services and interacting with other youth in spaces like drop-in centers, it is possible that these
young people are less reliant on homeless peers in part because of the social support networks
surrounding their temporary housing arrangements. Independent of their duration of
homelessness, couch-surfing youth may simply be less exposed to homeless peer networks,
spending less time congregating with other youth in shelters or on the streets as they navigate
securing and maintaining a short-term place to stay. However, even with the social support

80
structures facilitating their couch-surfing, these youth still vary in their perceptions of social
support. McLoughlin (2013) documented that while the pursuit of social support and
connectedness was a key factor in youth leveraging their contacts for a place to stay, many of
these youth grappled with the loss of support leading to their homelessness and struggled with
the precarity, instability, and psychological burdens associated with couch-surfing. This
observation is echoed in current study findings of a subgroup inclusive of couch-surfing youth
reporting very little support, challenging more prevalent notions of youth engaging in largely
supportive couch-surfing arrangements.
In examining demographic associations with emergent classes, several minoritized
identities were significant predictors of class membership. Black, multiracial, and other nonHispanic/Latinx youth of color were significantly more likely to be in the Family support and
heterogeneous homelessness class than the Homeless peer support and no couch-surfing class.
These findings reinforce those of prior studies reporting that Black youth are more likely than
their White peers to indicate supportive ties to family (Hickler & Auerswald, 2009; Brown et al.,
2020) while also newly suggesting that other racially minoritized youth experiencing
homelessness report more supportive family connections and that these youth may be uniquely
positioned to leverage certain networks for couch-surfing. While the current study is unable to
disaggregate the ‘multiracial and other race’ category, future work with a larger sample size
might investigate whether specific racial or ethnic identities are correlated with different types of
social support networks given the implications for more culturally-grounded HIV interventions
for minoritized youth populations (Craddock et al., 2016; Evans et al., 2020; Lauricella et al.,
2016). Additionally, these findings provide further insight on prior work indicating that Black
and non-Hispanic/Latinx youth of color were more likely to couch-surf (Petry et al., 2022),

81
pointing toward the role that supportive family connections may play in these young people’s
ability to broker temporary housing arrangements.
Meanwhile, LGBQ+ youth as well as transgender and gender-expansive youth were
significantly less likely to be in the Family support and heterogeneous homelessness class than
in the Homeless peer support and no couch-surfing class. Additionally, sexual and gender
minority youth were less likely to be in the Very little support and heterogeneous homelessness
class than the Homeless peer support and no couch-surfing class. This stands in contrast with the
Brown and colleagues (2020) study, which suggested that LGBQ+ youth were more likely to be
found in a latent class characterized by little to no social support than any other class with social
supports. Although Brown and colleagues also drew from a sample of youth experiencing
homelessness in Los Angeles, data were collected between 2011 and 2013. Since then, there have
been increased investments among homeless youth service providers in promoting and adopting
more LGBTQ+- affirming practices and programming given the prevalence of LGBTQ+ youth
within the population (Maccio & Ferguson, 2016; Shelton et al., 2018). As data from the current
study were collected from drop-in centers, which serve as safe havens for youth experiencing
homelessness (Rice et al., 2023; Slesnick, 2016), it is possible that these spaces can function as
places where LGBTQ+ youth can connect and form supportive relationships with one another. In
one study of drop-in center utilization among youth experiencing homelessness in Los Angeles,
youth were more likely to attend the drop-in if their friends also attended, and positive
perceptions of the drop-in environment were more strongly related to drop-in center use for
LGBQ+ youth than for their heterosexual peers (Tucker et al., 2018). We can also consider
current findings in the context of previous work indicating that LGBQ+ youth are more likely to
couch-surf (Petry et al., 2022). Although this study finds that sexual and gender minority youth

82
were less likely to be found in subgroups with couch-surfing youth, it is worth underscoring that
the Petry and colleagues study drew from a 16-community sample—the social support dynamics
in a youth homelessness hub like Los Angeles may be unique among the LGBTQ+ youth
accessing services at the agencies participating in the parent study.
In relationship to HIV risk and prevention behaviors, study findings indicate that youth in
the Family support and heterogeneous homelessness class were significantly less likely to
engage in transactional sex compared to youth in the Very little support and heterogeneous
homelessness class. This is consistent with earlier research reporting the effect of family
connections (Heerde & Hemphill, 2017; Rice et al., 2010) and positive maternal relationships
(Stein et al., 2009) among youth experiencing homelessness on decreasing the odds of engaging
in transactional sex. These findings also point toward a subset of couch-surfing youth—those
with very little support—who may be particularly vulnerable to engaging in transactional sex.
Additionally, youth in the Very little support and heterogeneous homelessness class were
significantly less likely to engage in sex under the influence compared to those in the Homeless
peer support and no couch-surfing class. Prior work examining with whom youth experiencing
homelessness engage in substance use has indicated that both shared drinking and shared drug
use were significantly more likely to occur with recent sex partners, network members who
engaged in risky sex, and network members who provided youth with either emotional or
instrumental support (Green et al., 2013). Findings from the current study underscore the
complex relational dynamics present among homeless peer groups that can both provide young
people with support and increase their engagement in risky behavior.
Finally, youth in the Family support and heterogeneous homelessness or Very little
support and heterogeneous homelessness classes were each significantly less likely to report

83
knowledge of PrEP compared to the Homeless peer support and no couch-surfing class. Over the
past decade, PrEP has emerged as an important HIV prevention strategy, yet levels of awareness
vary among youth experiencing homelessness and uptake remains low despite their elevated HIV
risk (Santa Maria et al., 2019a; Storholm et al., 2023). Network-based interventions have been
effective in preventing HIV among various populations (Yang et al., 2020) and peer-based
interventions targeting youth experiencing homelessness demonstrate promise (Medley et al.,
2009; Yadav et al., 2017; Young et al., 2020), including the peer-led HIV prevention intervention
conducted by the parent study (Rice et al., 2021). Current study findings contribute additional
insights to the nascent literature on PrEP among this population, as conversations about PrEP
among supportive homeless peer groups may already be occurring and could be a targeted focus
of peer-based network HIV prevention interventions. Conversely, findings also point toward
opportunities to explore the potential of increasing PrEP awareness through family-based
interventions, as recent research on PrEP awareness and use among adolescents suggest that
family engagement may facilitate PrEP uptake and adherence (Jackson-Gibson et al., 2021;
Ndimande-Khoza et al., 2023).
LIMITATIONS
The current study is limited in its generalizability due to its non-probability sample of
youth experiencing homelessness accessing a few select drop-in centers in Los Angeles. Other
limitations posed by the sample meant that social support could not be disaggregated into its
distinct types (emotional, instrumental, informational, appraisal) along with its sources due to
small cell sizes among couch-surfing youth. Prior research indicates that it is not only the mere
presence of social support within a young person’s network, but who it comes from and what
type of support is provided that is important, as patterns of support and influence vary across

84
network members (Agneessens et al., 2006; Brown et al., 2020; Petry et al., in revisions). Future
research might examine sources of social support among youth experiencing homelessness in
greater detail to include different types of support and to assess how HIV risk and prevention
behaviors may be implicated in a more nuanced set of emergent subgroups.
Additionally, due to the limitations of the living situation measure and the sample of
couch-surfing youth discussed in the preceding chapter, it is worth revisiting the identification of
subgroups of couch-surfing youth based on network characteristics in future research. While the
current study points toward variations in the social support networks among couch-surfing youth,
the youth in this sample were less distinguished by their living situation; this could be an artifact
of the lack of specificity in the current measure of couch-surfing regarding. Additional
qualitative work may provide further insights into the classes identified in the present study and
future studies might capture greater detail concerning the perceived stability of these temporary
housing arrangements and with whom youth are residing. Further, the cross-sectional nature of
this analysis precludes any causal interpretations. Alongside more detailed information regarding
couch-surfing arrangements, longitudinal research would enable a clearer examination of
variations in couch-surfing trajectories, the multifaceted relational dynamics present within these
contexts, and their effect on HIV risk.
CONCLUSION
This study reveals three distinct subgroups of youth experiencing homelessness based on
their living situation and social support networks: Family support and heterogeneous
homelessness, Very little support and heterogenous homelessness, and Homeless peer support
and no couch-surfing. Results indicate varying levels of support among youth who are couch-

85
surfing and their relative isolation from homeless peer networks. Youth with supportive family
connections were less likely to engage in transactional sex compared to those with very little
support, but less knowledgeable about PrEP relative to those connected to homeless peer
networks. Black, multiracial, and other non-Hispanic/Latinx youth of color were more likely to
have family support, while LGBTQ+ youth were more likely to receive support from homeless
peers. These findings underscore the varied social support systems among youth who are couchsurfing and among youth experiencing homelessness more broadly, and highlight the need for
more culturally nuanced and grounded interventions that consider the distinct impacts of family
and peer influence on HIV-related behaviors.

86
CHAPTER 4. AT THE INTERSECTION OF COUCH-SURFING, SOCIAL SUPPORT,
AND TRANSACTIONAL SEX: A QUALITATIVE STUDY
INTRODUCTION
The preceding chapters yield important insights into the relationship between living
situation, social support, and HIV risk and prevention behaviors among youth who are couchsurfing. Arguably the most prominent findings have underscored the relationship between couchsurfing and transactional sex and the potential influence of certain social support networks on
young people’s engagement in this survival behavior. Results of Aim 1 suggest that youth who
are couch-surfing are significantly more likely to engage in transactional sex relative to those in
shelter, and at a magnitude greater than those living on the streets. In Aim 2, couch-surfing youth
were found across two classes distinguished by either the presence of supportive family
relationships or the relative lack of any social support—and entirely absent from a third class
characterized by supportive connections to other youth experiencing homelessness. Youth in the
class marked by family support were significantly less likely to report recent transactional sex
relative to those with very little support. Together, these studies point toward a distinct
connection between couch-surfing and transactional sex and highlight the heterogeneity of social
support networks among couch-surfing youth that may influence their engagement in
transactional sex. However, questions remain regarding what social support looks like for youth
within their couch-surfing arrangements and the circumstances influencing transactional sex
encounters in these living situations. Drawing from qualitative interviews conducted with youth
experiencing homelessness, the present study seeks to explore the dynamic socioenvironmental
contexts of couch-surfing arrangements and their relationship to engagement in transactional sex.

87
Social support among couch-surfing youth
To date, only a handful of studies have specifically explored the social networks of
couch-surfing youth. A recent social network analysis suggests that youth with a higher
proportion of peers from home in their network are more likely to be couch-surfing relative to
living on the streets, and that emotional support from these particular peers is associated with
couch-surfing (Petry et al., under revisions). In earlier case studies of couch-surfing among
Latino former foster youth, Perez & Romo (2011) observe that youth frequently leverage peer
networks after failed attempts to reconnect with family members. Friends and romantic partners
are noted to extend emotional, cultural, informational, and instrumental supports that young
people’s biological families are unable or unwilling to provide. Similarly, McLoughlin (2013)
details how young people’s pathways into couch-surfing commonly originate with the loss of
vital personal and economic supports from family; the loss of these supports is further
exacerbated by a lack of support from system gatekeepers who fail to recognize the severity of a
young person’s housing crisis. A decade later, Hail-Jares and colleagues (2023) continue to
remark upon the de-prioritization of couch-surfing youth in formal support systems that center
‘rooflessness’ over other risk factors. Meanwhile, these youth turn to informal sources of support
to arrange temporary housing, including friends, extended family members, romantic partners,
acquaintances, and strangers (Hail-Jares & Vichta-Ohlsen, 2023; McLoughlin, 2013; Perez &
Romo, 2011).
While it is broadly understood that couch-surfing youth draw from a range of different
social connections, less is known about how couch-surfing experiences might differ across these
connections, how different types and sources of social support may impact couch-surfing
arrangements, and how these contexts might promote risk or resilience. Curry and colleagues

88
(2020) interviewed nine couch-surfing youth and ten adult couch-surfing hosts in a Midwestern
state. Their findings indicate that youth in these temporary living arrangements often receive
support beyond meeting basic housing needs, including other material resources like food and
clothing, information related to accessing social services, and emotional support from developing
‘family-like ties’ with their hosts. Drawing from this same sample of couch-surfing youth and
hosts, VanMeeter and colleagues (2022) underscore that these supportive couch-surfing
arrangements are often threatened by material challenges, including increased household costs
such as food and utilities and restrictions on long-term guests imposed by lease agreements and
public housing benefits. While these two studies provide important insights into the relational
and structural dynamics surrounding couch-surfing, they are limited by the type of couch-surfing
experiences under study. The hosts who participated were at least ten years older than the youth,
did not have a romantic or sexual relationship with the youth, and had hosted the youth for at
least three weeks. Only one host was an extended family member; the remainder were
connections made through others, most commonly via friends or romantic partners. How social
support might differ for youth couch-surfing in other types of arrangements and environments—
and the relationship of these contexts to engagement in transactional sex—remains an area
warranting further study.
Transactional sex among youth experiencing homelessness
In a nationally representative sample of adolescents and young adults in the U.S., 4.9%
indicated ever engaging in transactional sex, or exchanging sex for money or other material
support; youth who ever reported experiencing homelessness were nearly three times as likely to
exchange sex relative to their stably housed peers (Ulloa et al., 2016). Transactional sex has long

89
been associated with an increased risk of HIV (Marshall et al., 2009; Mgbako et al., 2019;
Nerlander et al., 2020; Oldenburg et al., 2015; Wamoyi et al., 2016). Engagement with multiple
concurrent sexual partners, lack of condom use, and the higher prevalence of sexually
transmitted infections more broadly are among the factors associated with transactional sex that
contribute to its relationship with HIV risk (Krisch et al., 2019; Nerlander et al., 2017; Ward &
Rönn, 2010). Consequently, youth engagement in transactional sex is of particular concern given
that young people between the ages of 13 and 24 accounted for over half of new HIV diagnoses
in 2021, the most recent data available as of this writing (CDC, 2023).
Transactional sex among youth experiencing homelessness is a survival strategy—a way
to meet basic needs and a way to cope with the stressors of homelessness (Madden et al., 2021;
Santa Maria et al., 2015; Walls & Bell, 2011)—and prior work indicates that these young
people’s engagement in transactional sex is correlated with a range of adverse outcomes. In their
analysis of 1,625 youth experiencing homelessness in 28 states across the U.S., Walls & Bell
(2011) examined a broad range of demographic, substance use, mental health, and physical
health variables in relationship to lifetime engagement in transactional sex. A history of suicide
attempts, familial substance abuse, and recently testing for HIV were all associated with an
increased likelihood of engaging in transactional sex. Additionally, Black and sexual minority
youth were each found to be significantly more likely to report lifetime transactional sex relative
to their White and heterosexual peers, respectively. In a more recent study of 253 youth
experiencing homelessness in Los Angeles undertaken by Srivastava and colleagues (2019),
sexual and gender minority youth were significantly more likely to engage in transactional sex,
as were youth who indicated recent sex with someone who was HIV positive.

90
While neither the Walls & Bell (2011) nor the Srivastava and colleagues (2019) studies
made a distinction between young people’s living situations, others have called for further
investigation into the specific social, environmental, and structural factors influencing youth
engagement in transactional sex (Showden & Majic, 2018). Ulloa and colleagues (2016), in their
study of a nationally representative sample of adolescents and young adults in the U.S.,
emphasized the need for qualitative work to understand the distinct contexts and motivations
surrounding sexual exchange between those experiencing homelessness and those who are stably
housed. While this is certainly an important distinction to make among youth more broadly, these
same factors are just as pertinent in understanding transactional sex among youth experiencing
homelessness. A handful of studies have parsed between young people living on the streets and
those residing in shelters (Green et al., 1999; Marshall et al., 2009; Tucker et al., 2012), but
couch-surfing as a distinct context in relationship to transactional sex has largely remained
absent from the literature.
Recent qualitative work by Hail-Jares (2023) among sexual and gender minority youth
couch-surfing in Australia indicates considerable variation in their experiences with transactional
sex. Notably, young people made a clear distinction between sex work and sexual exchange, and
the level of agency they felt able to exercise in these encounters. However, youth across these
scenarios remained acutely aware of the power imbalance presented by their housing precarity
and their vulnerability to coercion and assault. Hail-Jares also noted that contrary to popular
conceptions of young people exchanging sex with older, predatory adults, many youth engaged
in transactional sex with other young people similar in age. While these findings underscore the
variety of circumstances in which couch-surfing youth engage in transactional sex, additional

91
research is needed to further understand the contexts of young people’s couch-surfing trajectories
and their relationship to engagement in transactional sex.
CURRENT STUDY
The current study seeks to provide additional insights into key findings observed in the
preceding two chapters, particularly those pertaining to the relationship between couch-surfing,
social support, and transactional sex. Using in-depth interviews conducted with 25 youth
accessing services at local drop-in centers, this study offers a qualitative examination of the
socioenvironmental contexts of young people’s couch-surfing arrangements and their
experiences with transactional sex.
METHODS
PARTICIPANTS AND PROCEDURES
In June and July of 2023, a convenience sample of 25 young adults was recruited via inperson methods at two major drop-in centers serving youth experiencing homelessness in the
Hollywood area of Los Angeles, California. All young people accessing drop-in services were
approached individually by research staff upon entry, and those interested in the opportunity to
participate in the study completed an eligibility screener. The screener consisted of four
questions assessing the following criteria: (1) aged 18 to 25; (2) in the past 12 months, spent at
least one night temporarily residing at another person’s home or residence because they had no
place else to stay; and (3) in the past 12 months, engaged in oral, vaginal, or anal sex. Regardless
of whether they met eligibility criteria, youth who completed the screener were compensated $3
cash for their time. Fifty-five youth completed the eligibility screener; 24 were ineligible due to

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either their age (n = 3), no couch-surfing experience (n = 18), or sexual inactivity (n = 3). An
additional six youth were eligible for the study but were lost to follow-up.
Interview participants provided verbal informed consent, were assigned a unique
participant ID, and completed an anonymous, self-administered survey on a tablet. This brief
survey collected basic demographic information along with homelessness history and recent
sexual behavior. The survey also included the participant’s study ID number so that responses
could later be linked to interview data. Following the completion of the survey, participants were
engaged in a one-on-one, in-depth interview that lasted an average of 60 minutes. Youth were
compensated $40 cash for their time.
Qualitative interviews were structured around a timeline follow-back (TLFB) method
adapted for the current study and focused on young people’s experiences with couch-surfing,
their social support networks, and their sexual behaviors. TLFB uses key calendar events or dates
to prompt respondents in providing retrospective details over a specific period of time (Sobell &
Sobell, 1992). While TLFB has its roots in substance use research (Hjorthøj et al., 2012; MartinWillett et al., 2019; Sobell et al., 1996), the method has also been used to trace events related to
housing instability (Tsemberis et al., 2007) and sexual behavior (Carey et al., 2001). The current
study implemented a physical calendar drawn on a large piece of lightweight poster board and
adhered to the following protocol: 1) explanation of TLFB; 2) identification and recording of
“anchor dates” representing key events to assist in recall; 3) identification and recording of
milestones related to living situation; 4) discussion of identified domains related to couchsurfing, social support networks, and HIV-related behaviors. In addition to the use of anchor
dates to facilitate retrieval, the current study utilized other recommended methods for TLFB,
including giving participants more time to remember and recalling events in reverse

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chronological order (Tourangeau, 2000; Tsemberis et al., 2007). After annotating the calendar,
participants were engaged in a discussion regarding the specific circumstances surrounding a
given living situation, with special emphasis afforded to episodes of couch-surfing, as well as
their social support networks and sexual activity during the time under discussion. Interviews
followed a flexible interview structure whereby different domains were explored at different
depths depending on each participant’s experiences and willingness to engage. Calendars were
jointly annotated by both the interviewer and the participant over the course of the interview, and
labeled with the participant’s study ID number so that calendar data could later be linked to
survey and transcript data.
Interviews were conducted by the lead author, a doctoral candidate in social work with 11
years of experience working with youth experiencing homelessness at the time of data collection.
Interviews were audio recorded and transcribed verbatim; transcripts were then entered into
ATLAS.ti (Version 23.4.0) for data management and analysis. Annotated TLFB calendars were
photographed, uploaded to a protected server, and transcribed; original copies were subsequently
destroyed. All study procedures were approved by the Institutional Review Board at the
University of Southern California.
ANALYSIS
A thematic approach was used to code and analyze interview transcripts (Braun & Clarke,
2006; 2023). An initial set of codes was generated deductively from domains outlined in the
interview guide. The author and another PhD student in social work then independently read and
coded two initial transcripts and met to compare results, address any discrepancies, and discuss
the refinement of the codebook. This process was repeated twice, resulting in a final set of

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agreed-upon codes. A final round of co-coding was done with two additional transcripts, for a
total of eight, to ensure that codes were being applied consistently before the author solo coded
the remaining transcripts. Next, in order to qualitatively explore associations observed in the
quantitative arm of the larger study, preliminary themes were identified across two key
categories, social support and transactional sex, by examining the text across relevant codes.
Once themes were identified, quotes that were consistent with each theme were highlighted and
reviewed across all transcripts to verify that themes were common across participant
experiences. Throughout this process, the author engaged in memo-writing to document patterns
observed across the text and across the housing trajectories solicited through TLFB to aid in
refining the emergent themes.
RESULTS
PARTICIPANT CHARACTERISTICS
Characteristics of the 25 interview participants are presented in Table 4.1. On average,
participants were 22.5 years old at the time of the interview. The majority were youth of color (n
= 22) and most youth identified as LGBQ+ (n = 16). Over one-third were either transgender (n =
4) or non-binary (n = 5). While all participants reported couch-surfing in the previous 12 months,
most youth at the time of the interview were residing in either emergency shelter or transitional
housing programs (n = 17). Over half (n = 16) reported their current episode of homelessness
lasting for six months or longer. When asked about their recent sexual activity, the majority (n =
22) reported having at least one sexual partner in the past three months, with nearly half (n = 12)
reporting multiple concurrent partners. Most youth reported testing for HIV in the past month (n

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= 15), but youth were split on their knowledge of PrEP—just under half (n = 12) indicated that
they knew something about the HIV prevention medication.
Table 4.1 Interview participant characteristics
Total (n = 25)
n (%) mean (SD)
Demographics
Age 22.5 (1.7)
Race
Black 6 (24.0)
Hispanic/Latinx 8 (32.0)
White 3 (12.0)
Multiracial or another race 8 (32.0)
Gender identity
Male 10 (40.0)
Female 6 (24.0)
Transgender 4 (16.0)
Non-binary 5 (20.0)
LGBQ+ 16 (64.0)
Lesbian 5 (20.0)
Gay 2 (8.0)
Bisexual 5 (20.0)
Asexual 3 (12.0)
Pansexual 1 (4.0)
Ever in foster care 9 (36.0)
Education and employment
Educational attainment
Less than a high school diploma 10 (40.0)
High school diploma or GED 7 (28.0)
Some college, but no degree 8 (32.0)
Bachelor’s degree 1 (4.0)
Currently in school 5 (20.0)
Currently earn income from a job 15 (60.0)
Homelessness history
Age first experienced homelessness 18.0 (3.7)
Current living situation
Unsheltered 1 (4.0)
Couch-surfing 5 (20.0)
Emergency shelter or transitional housing 17 (68.0)
Stably housed 2 (8.0)
Number of homeless episodes (lifetime)
1 episode 4 (16.0)
2 episodes 2 (8.0)
3 episodes 6 (24.0)

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4 or more episodes 13 (52.0)
Duration of current homelessness
Less than 1 month 2 (8.0)
1 to 2 months 4 (16.0)
3 to 5 months 3 (12.0)
6 to 11 months 6 (24.0)
12 months or longer 10 (40.0)
Number of couch-surfing hosts (12 months)
1 host 5 (20.0)
2 to 3 hosts 10 (40.0)
4 to 5 hosts 5 (20.0)
6 or more hosts 5 (20.0)
Reason for most recent homelessness
Kicked out or asked to leave by family 14 (56.0)
Lost job or could no longer afford rent 10 (40.0)
Family no longer had room at their place 7 (28.0)
Family violence 6 (24.0)
Own mental health or substance use issues 6 (24.0)
Family mental health or substance use issues 5 (20.0)
Family lost housing or did not have stable housing 5 (20.0)
Break-up with romantic partner 5 (20.0)
Intimate partner violence 5 (20.0)
Gang or neighborhood violence 4 (16.0)
Exited a system (e.g., foster care, jail/prison) 4 (16.0)
Sexual health
Number of sexual partners in past 3 months
None 3 (12.0)
1 partner 10 (40.0)
2 partners 2 (8.0)
3 or more partners 10 (40.0)
Last HIV test
In the past month 15 (60.0)
Two to six months ago 6 (24.0)
More than six months ago 2 (8.0)
Never been tested 2 (8.0)
Knowledge of PrEP
Know a lot about it 6 (24.0)
Know a little bit about it 6 (24.0)
Heard of it, but don’t know what it is 5 (20.0)
Never heard of it 8 (32.0)

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A CONCEPTUAL MODEL
Results of the thematic analysis culminated in a model (depicted in Figure 4.1) of the
relationship between couch-surfing, social support, and transactional sex among youth
experiencing homelessness. Young people’s experiences with couch-surfing over the preceding
12 months were generally characterized by their level of volatility, or the frequency with which
youth moved from one temporary housing arrangement to the next. Low volatility couch-surfing
was identified by longer-term arrangements lasting longer than two months in combination with
fewer instances of couch-surfing overall. High volatility couch-surfing was distinguished by
more transient living arrangements marked by staying with multiple different hosts within a short
period of time or shorter couch-surfing stays occurring in the midst of cycling in and out of other
forms of homelessness.
Young people’s perceptions of social support often impacted the level of volatility in their
couch-surfing. Youth expressing difficulties in navigating relationships while couch-surfing often
described efforts to limit stays with supportive hosts in order to preserve important relationships
(Theme 1: Negotiating support), leading to increased instability. For others, the volatility of their
couch-surfing impacted their perceptions of social support, as youth experiencing higher
instability indicated feeling disconnected and misunderstood by others and emphasized the need
for more emotional support (Theme 2: Lonely and isolated). Family relationships also emerged
as a key theme (Theme 3: Family connections), particularly among those with lower volatility
couch-surfing experiences. These youth were more frequently hosted by family members and
more likely to remain connected to family even if relationships were complicated or contentious.
Independent of the level of volatility in their housing arrangements, youth with connections to
family were less likely to report direct experience with transactional sex while couch-surfing.

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However, a subset of youth experiencing higher housing instability and more tenuous or fewer
social supports were more likely to encounter situations where they felt obligated to have sex
with their host (Theme 4: Coercive romantic relationships), were driven to transactional sex by a
desire for emotional support (Theme 5: Seeking emotional connection), or were asked by hosts to
perform sexual favors in return for a place to stay (Theme 6: Propositioned by hosts).
In the following sections, themes are described in greater detail and supported by direct
quotes from the youth interviewed. Themes are grouped into two categories, Social support
among couch-surfing youth and Transactional sex and couch-surfing, with the latter representing
a subset of twelve youth who discussed experiences with transactional sex. Additionally, while
all but three of the participants identified as a racial or ethnic minority, these identities—along
with age and gender identity—are underscored in the presentation of direct quotes given the
importance of these characteristics observed in the preceding chapters.
Figure 4.1 A conceptual model of the relationship between couch-surfing, social support, and
transactional sex among youth experiencing homelessness

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SOCIAL SUPPORT AMONG COUCH-SURFING YOUTH
THEME 1. NEGOTIATING SUPPORT: “I DIDN’T WANT TO RUIN OUR
RELATIONSHIP”
Although the level of volatility in their living arrangements varied, most youth
interviewed indicated staying with multiple different hosts. While some young people’s couchsurfing trajectories were characterized by longer stays with a given host or by rotating among a
few different family members or friends, many indicated staying with people they knew less well
(or not at all) in combination with people with whom they had a direct relationship. For youth in
this latter group, this frequently meant cycling between supportive environments with trusted
family or friends and unsupportive environments where they felt misunderstood, unwanted, or
even unsafe. Valerie, a 24-year-old multiracial woman, contrasted her experiences cycling
between couch-surfing with high school friends, people from her neighborhood, and a trap
house:
“With my friends, we watching TV or going to the mall when I’m sleeping over their
house. It was peaceful. I was always welcome. People in the neighborhood, it was way
different. It was stressed out and tired…[and] when I had to go do my grown man stuff, it
was different. The whole mood was just a different atmosphere. People get into fights.
People get too high and start tripping in the trap. You’re staring at the monitor for hours,
make sure police don’t ride by, just paranoid all the time.”
For Valerie and others, even when there were safe and trusted places for them to stay,
youth were worried about overstaying their welcome and felt strongly about protecting

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relationships that were important to them. Several youth stated that couch-surfing often “ruined”
relationships with friends and family, and some described leaving couch-surfing arrangements in
order to preempt any perceived damage that might be caused by their stay. This often coincided
with desires to be independent and self-sufficient, and to forge their own path forward. As Julian,
a 24-year-old Latino, described leaving one couch-surfing arrangement:
“I just decided to leave because I didn’t want to ruin our relationship. I just told them I’d
go to a shelter so that they wouldn’t have to expend the effort. And it’s not that I didn’t
want them looking out for me, it’s just that I thought I should handle things on my own.”
Sierra, a 22-year-old multiracial woman, similarly reflected on her feelings about
reaching out to a family member:
“I just wanted to see if I would get any support from them. I guess that’s probably not the
nicest thing, but I needed support from someone other than myself. And I guess that’s also
a problem with young people. It’s hard to ask for support. You always feel like you have
to do it yourself or make it happen for yourself.”
THEME 2. FAMILY CONNECTIONS: “I FEEL LIKE I NEED MORE SUPPORT FROM
FAMILY”
Support from family was a recurring theme throughout interviews and over half of youth
said that they felt supported by a family member. While some youth mentioned receiving
instrumental support from family, including money or a temporary place to stay, many

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emphasized emotional support. David, a 24-year-old Black trans man, described the support he
received from his brother, who would occasionally host him while couch-surfing or pay for hotel
rooms: “[He gives] emotional support and mental support, at times when I need someone to talk
to, when I need someone to just sit there.” Youth also described receiving motivation and
encouragement from family members, and those naming siblings or cousins sometimes cited
them as role models. Even with positive, supportive connections to family, circumstances were
often complicated or not conducive to helping young people get stable. For David, while his
brother served as a reliable host and supportive ear, his gang involvement precluded David from
trying to broker a more stable housing arrangement. For Isaiah, a 25-year-old Black man whose
grandmother raised him and was his “number one” supporter, rules associated with subsidized
housing meant Isaiah was on his own.
Others were connected to family but emphasized a distinct lack of support. Amiya, a 22-
year-old multiracial woman, noted the difference between the support she got from family and
the support she received from those at the drop-in center where her interview took place: “I know
my family loves me, but they can’t always be there. And I know if I come here, somebody’s always
here. Somebody that cares about me is always here... [but] I feel like I need more support from
family.” Amiya and others whose families were largely absent or unsupportive often desired
more family support, but struggled to reconcile that desire with various relational traumas.
Gabriel, a 24-year-old Latino, grappled with family rejection of his sexual identity: “Sometimes
the culture and the people, they’re not there yet. Obviously, I’m always welcome to go [to their
home], but I don’t feel welcome anymore…It’s really hard to forgive, especially the people
who’ve hurt you.” Nia, a 24-year-old multiracial woman, spoke about her mom:

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“She’s been there for me a lot of times when I needed her and wasn’t expecting her to be
because of just how she is…But I can’t go to her all the time. When I do go to her, it’s like,
‘Why did I come to you?’…We’ve been through a lot and it’s like we’ve went our separate
ways. Sometimes we keep in touch and sometimes we don’t really want to talk to each
other.”
Including Nia with her mother, most youth interviewed indicated couch-surfing at the
home of at least one family member—and this often included those with whom they had a more
fraught relationship. Asking family for a temporary place to stay would often yield arrangements
that started out welcoming and supportive but would quickly become complicated by other
factors. While this included material strains on households that were already struggling, youth
more commonly pointed toward shifting (even mercurial) relational dynamics with hosts and
other household members. Jasmine, an 18-year-old Latina, stated that in her couch-surfing
experience with family, “People tell you so much how they’re going to be there for you, but
things start to get uncomfortable and unravel and you know you really can’t stay.” Julian, a 24-
year-old Latino, summed up his experience with family as such:
“If you go stay with family, you’re going to be in a mindset where you’re going to be like,
‘Well, my family’s going to help me even if it’s a long time to get me out of here.’ But
literally within a week you can have a problem with that same family member you
thought was so nice and helpful and you could be on the street again.”

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THEME 3. LONELY AND ISOLATED: “I FELT ALONE EVERYWHERE”
Youth often expressed feeling isolated while couch-surfing and many described a lack of
empathy and understanding from people in their lives, including hosts. Sebastian, a 24-year-old
Latino, spoke about couch-surfing hosts who couldn’t understand the challenges he faced in
getting stable, stating that “some people just don’t understand that you need a lot of time to
recuperate from any fall [into homelessness]… It’s not something you’re going to get out of
quickly unless you really have support, which I didn’t.” Isaiah, a 25-year-old Black man,
described couch-surfing with friends who were eager to host him but who he felt largely
disconnected from:
“After a while, [couch-surfing] fucks you up mentally. Like damn, start feeling like you’re
kind of losing bits of yourself… and I literally have people that hit me up every day, they
want me to come over. And I get it, they are being helpful and I’m very grateful. But
sometimes you’re just like, ‘that’s not the kind of support that I need right now.’ Instead I
got to kind of comfortably be uncomfortable. I got to act like everything’s cool.”
Others talked about removing themselves from negative relationships and influences.
Oscar, a 23-year-old Latino, discussed stepping away from peer relationships at the drop-in
center he had been attending for the past two years: “I’m here to work and get myself back to my
own apartment so that I can live my life again, not to be involved in their life and what they’re
doing out in the street.”
A number of youth reported feeling supported by no one other than their therapist. Sierra,
a 22-year-old multiracial woman, stated: “I prefer therapy before inviting in anyone that I know,

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just because a lot of people…I don’t feel like they have a lot of space to understand. Especially if
they have had their own problems.” Others relayed similar sentiments of relying on therapists
because they did not want to take up space with people in their personal lives. Drew, a 23-yearold non-binary person, said: “No one has ever been very significantly invested in my life enough
because I’m just... I’m too much. I am a lot.”
Many youth who expressed having very few, if any, people to draw upon for support
attributed their increased reliance on only themselves to tumultuous or traumatic couch-surfing
experiences. Marco, a 21-year-old Latino trans man, was sexually assaulted while couch-surfing
with a friend’s father and described struggling to trust people ever since:
“I’ve become wired to fight everything…I can’t trust you and I can’t trust my judgment
either…I guess that’s what couch-surfing does. It takes away your trust. You can’t trust
the water; you can’t trust anything in it.”
TRANSACTIONAL SEX AND COUCH-SURFING
Of the 25 youth interviewed, twelve discussed direct experiences with transactional sex.
Compared to youth who did not indicate any experience with transactional sex, these youth were
more likely to report more volatile couch-surfing trajectories that involved more transitory stays
across multiple hosts and amid multiple forms of homelessness. These youth were more likely to
be concerned about damaging supportive relationships (Theme 1), to be less connected to family
members (Theme 2), and to express feeling unsupported and alone (Theme 3). The following set
of themes describe these young people’s varied experiences with transactional sex and consider
these experiences within the context of their perceptions of social support.

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THEME 4. COERCIVE ROMANTIC RELATIONSHIPS: “MAYBE IT WOULD MAKE
HIM COMFORTABLE WITH ME STAYING HERE”
Often, sexual favors were not initially or even explicitly part of young people’s couchsurfing arrangements, but at some point would become a condition of maintaining a given living
situation. This commonly occurred among young people temporarily residing with a current or
former intimate partner, where power differentials effectively pressured young people into
performing emotional and sexual labor to maintain both their relationship and their housing.
Alex, a 21-year-old Latinx person, characterized having sex while couch-surfing with their
boyfriend to “keep the peace” in a mercurial relationship:
“They would get angry or start arguments and I would have to give them that attention,
that sexual attention in order to be like, ‘Oh, don’t kick me out.’ I wouldn’t have anywhere
to stay. There definitely was a power dynamic.”
Alex expressed that this power dynamic made them feel like they were living
“underneath someone’s control, [which] wasn’t good, mentally.” This sentiment was emblematic
of other young people’s experiences of coming to stay with someone they believed cared for
them, only to find themselves negotiating against their own well-being in order to keep a roof
over their head. As Alex came to realize: “You care for this person, but you’re not so sure they
care enough for you.” Mismatched desires to give and receive support within a romantic
relationship while also navigating the precarity of a young person’s housing situation often set
the stage for coercive sexual exchange.

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Even in situations where youth felt they were consenting to a sexual encounter, there was
an undercurrent of feeling pressured to concede to the desires and expectations of their host in
order to maintain their living situation. Sierra, a 22-year-old multiracial woman, was upfront in
expressing her desire to remain platonic and establish her independence while couch-surfing with
her ex-boyfriend. However, he quickly started to “play house,” tending after her, sending her
money, and calling her pet names. Sierra felt pressured to play along: “I have nowhere to go and
I thought maybe that would make him comfortable with me staying there.” About a week into the
month-long arrangement, the two started having sex:
“He probably felt more confident that he could buy me things and make sure that I was in
a safe environment where I was comfortable and it felt like the sexual encounters were
okay. But they definitely weren’t what I feel like a sexual encounter should be…I felt like I
knew what it felt like to be completely cared for [and] I just knew that this wasn’t how it
was supposed to feel…But I can’t say that I didn’t want it. I can’t say that I said no or
anything. But after it happened, I kind of felt sick with myself, and I felt sad and had a cry
afterwards. It wasn’t what I thought was good for me.”
Young people in these situations were often not just economically vulnerable but
emotionally vulnerable and isolated from other sources of support. Alex had supportive
relationships with their mother and grandparents, but during their time couch-surfing with their
boyfriend, described keeping their distance: “I didn’t want to tell them much about it… [they]
are very involved and I didn’t want them to be at the time.” Meanwhile, Sierra’s stay with her exboyfriend came on the heels of couch-surfing alongside her mother at the home of a family

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friend. Sierra felt she was more concerned about getting stable than her mother was, which
became a point of contention between the two as she sought to escape the pressures of providing
for her family—“I ended up purchasing my first car. I worked very hard for it, and I got up and
left. I was like, ‘Okay, I’m totally about to go on my own with this.’ And my ex, he was very
stable.”
THEME 5. SEEKING EMOTIONAL CONNECTION: “I’M TRYING TO FILL A VOID”
For young people involved in more upfront and straightforward exchanges of sex, the
desire for an emotional connection often went in tandem with the desire for a place to stay. This
was exemplified by Amiya, a 22-year-old multiracial woman whose pathway into transactional
sex followed tumultuous attempts to seek support from family. In her current episode of
homelessness, Amiya had lost her housing following a break-up with a boyfriend. After four
months of bouncing between the streets and emergency shelters, she attempted to stay with an
older sister: “I had explained to her…I was feeling depressed or suicidal and I couldn’t really
stay on the streets anymore. So she let me stay for a little bit.” The arrangement was short-lived,
in part due to a historically contentious relationship between the two. After another several
weeks on the street and failed efforts to stay with her mom, Amiya turned to Tinder:
“I slept with a stranger for somewhere to stay. I think it was also because I was
lonely…So I got all dressed up and got on Tinder and looked for somebody. And it felt
nice. He bought me flowers and it wasn’t like he was a weirdo. He took me on a nice
dinner…It was just sort of like, ‘I’m going on a date, I’m going to hook up with this guy
and I’m going to have a place to crash for at least tonight.’I felt bad about it, but then at

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least I’m not a hooker on the street, you know what I mean? At least I’m not having sex
with people multiple times a day.”
This was the first time that Amiya had engaged in transactional sex, but it would become
part of her strategy for both getting off the streets and forging an emotional connection: “It’s like
I’m trying to fill a void. I don’t feel loved enough, so sex is one way to get close to somebody.” At
the same time, these interactions were ephemeral, lasting for a single night. While Amiya
described her first time as “risqué, but not risky,” she later expressed concern about her
willingness to go off with strangers: “I can’t be putting myself out in danger like that...I need to
be careful about what I do.” At the time of the interview, Amiya was stable in an emergency
shelter but still hooking up with strangers she met online and on the streets. While she would
occasionally still spend the night, she was protective over not jeopardizing her spot in the shelter:
“Sometimes I’ll stay, but that’s when I want to. I never expect it because I already have
somewhere to lay my head. I’m not going to risk it for dick.”
For others, the pursuit of “getting close to somebody” entailed paying strangers for
sexual encounters. Kai, a 23-year-old multiracial non-binary person, had been couch-surfing with
friends and occasionally sleeping in a church library for several months. In describing their stay
with high school friends still living with their parents, Kai noted that “the only ones I was able to
stay at were basically the friends that had problems with their parents. So it almost always ended
up that the parent didn’t want me there.” Amid this instability and lack of support in their living
situation, Kai turned to Grindr and started arranging to pay men for sex. Like many of the
instances of transactional sex detailed by other youth, these encounters were absent of any
condom use or conversations about HIV or STIs. For Kai, condoms were never considered and

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they expressed a lack of knowledge about HIV and STIs, stating: “I don’t have any knowledge
and haven’t looked into anything about that stuff. I don’t know anything about it.”
THEME 6. PROPOSITIONED BY HOSTS: “ANYWHERE I GO, IT’S ALWAYS A
POSSIBILITY”
Several youth detailed situations in which they were explicitly propositioned by couchsurfing hosts to exchange sex for a place to stay. Expectations of sexual activity made at the
outset were especially common in online interactions with strangers. Youth mentioned seeking
out couch-surfing opportunities on websites like Craigslist and Reddit, as well as on the
Couchsurfing app geared toward travelers, but quickly found that prospective hosts made sex a
condition of their stay. However, in many cases—including those who met strangers from
online—youth did not find themselves being propositioned until they were already in their host’s
company. Drew, a 23-year-old White non-binary person, became homeless on the streets after
needing to leave a couch-surfing arrangement with an ex-girlfriend’s parent. From the streets,
Drew attempted to couch-surf with a prospective host from Reddit. Although Drew made a
concerted effort to vet the host and convince him that they weren’t “some random risky guy,”
Drew still found themselves being groped and propositioned by their host:
“The whole time I was just holding onto this thought that maybe I could just fucking play
the role and just get a night out of this guy without being sexually assaulted or anything
bad occurring. But it was just too much. And he was far too persistent. I went back to his
house and it was literally prescription pill bottles everywhere. House was a mess. And he
wouldn’t allow me to chill. He was trying to get me to smoke stuff and take pills…And

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then he started to belittle my situation. He was making me feel really small about being
homeless and that my fight and my struggle and my story was essentially worthless and
that I wouldn’t get anything better than him paying me to be his houseboy.”
Drew left the house and hopped on a bus, returning to the streets before calling to find an
emergency shelter. This refusal to engage in transactional sex was echoed by others who found
themselves in increasingly vulnerable positions with hosts who sought to exploit their need for
housing. For some young people, this predatory behavior would dovetail with the loss of their
ability to financially contribute to the household. Once jobs were lost or money ran out, youth
described being propositioned by their hosts but remaining steadfast in their refusal. Marco, a 21-
year-old Latino trans man, recalled feeling vulnerable when propositioned by his couch-surfing
host after he lost his job and could no longer chip in financially:
“That’s when I got scared…I knew I was not going to give in and I was not going to let
anyone take. I knew that I was not going to have sex with this person to stay at their
house. I didn’t want to have sex with this person and I wasn’t going to stick around so
that they could try to take it from me.”
Similar to Drew, Marco soon left the house and started sleeping in his car before his mom
suggested he call around to find an emergency shelter. Both Drew and Marco indicated having
very little to no social support during this time; both also disclosed previous sexual assaults and
were keenly aware of their vulnerability to being victimized. Marco stated: “I felt like anywhere
I go, it’s always a possibility.”

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Other youth detailed situations in which they did engage in transactional sex after being
propositioned. As Drew connected their experience being propositioned by a host to the broader
reality of young people in similar situations: “It could have ended a lot of worse, especially if I
was less sure of myself, if I was a more vulnerable individual. That reality exists for people and a
lot of youth…are getting taken advantage of straight up.” But for some young people, it was part
of an effort to navigate out of couch-surfing situations that were unsafe or uncomfortable. Elian,
a 21-year-old non-binary Latinx person, was the only youth interviewed who indicated engaging
in a form of sex work. Elian was couch-surfing with a friend who was living with their parents
when the father made unwanted advances: “[I] left because it didn’t feel comfortable anymore...
So one of my friends offered, I had to trade pictures, photos, stuff like that to be able to get
money from them so I could rent a motel room.” In contrast, Gianna, a 22-year-old Latina trans
woman, described leaving a couch-surfing arrangement to alleviate a perceived burden on her
host:
“I was staying at my friend’s house for a week…everything was fun. And then I wanted to
leave to give them space. I felt like I was crowding them too much. But once I left, I was
at this one guy’s house. He was cute and he did expect some things, so I put up a good
show, but I kind of didn’t want to.”
DISCUSSION
Findings from the current study resulted in a model illustrating the relationship between
couch-surfing, social support, and transactional sex. Couch-surfing experiences varied in their
level of volatility, with lower volatility characterized by longer stays with fewer hosts and higher

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volatility by shorter stays with multiple hosts. The relative instability of young people’s couchsurfing arrangements often impacted their perceptions of social support and vice versa. Youth
concerned with overburdening supportive hosts limited their stays with trusted friends and
family, leading to greater instability, while those who experienced higher couch-surfing volatility
often struggled with increasing feelings of loneliness and isolation. These perceptions regarding
social support appeared to influence young people’s engagement in transactional sex. Youth
involved in coercive romantic relationships were frequently concerned with preserving
relationships not just with their host but with other people in their life they did not want to
burden with their need for housing. Youth who felt lonely and isolated were often driven to
transactional sex by a desire for emotional intimacy, however fleeting. Meanwhile, family
connections emerged as an important factor in young people’s social support systems and couchsurfing trajectories. Youth who maintained connections to family appeared less likely to engage
in transactional sex, regardless of the degree of their couch-surfing volatility.
Social support among youth who are couch-surfing
While the heterogeneity of these young people’s social networks was once again
reinforced, the current study newly illustrates the variability in young people’s relationships with
couch-surfing hosts and their efforts to navigate support. Prior qualitative work with couchsurfing youth has largely characterized host relationships as being supportive, with young people
leveraging close social connections in the wake of losing support from family (McLoughlin,
2013; Perez & Romo, 2011; Curry et al., 2021). Although youth in the current study indicated
couch-surfing in supportive couch-surfing environments, most also described couch-surfing in
unsupportive environments. This was often a result of not wanting to overburden their supportive

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yet resource-poor hosts, echoing concerns expressed by youth in prior studies (Hail-Jares, 2023;
McLoughlin, 2013), but it was also framed as a determination to be independent and self-reliant.
However, these alternatives to supportive couch-surfing environments often increased young
people’s exposure to a range of risks impacting their health, safety, and psychological well-being.
To improve our understanding of how risk and vulnerability manifest within and across couchsurfing arrangements, future research ought to examine the volatility of these arrangements and
how relationships with hosts and other household members affect housing trajectories and other
outcomes for this population.
As young people balanced and negotiated support from others in finding a place to stay,
many emphasized the need for emotional support. Even as youth leveraged various relationships
to facilitate couch-surfing, many described feeling isolated, misunderstood, and unsupported.
These findings resonate with prior observations of youth overwhelmed by ‘the psychological
burdens of couch-surfing’ that could erode young people’s sense of ontological security and lead
to even more precarious situations (McLoughlin, 2013). Notably, several youth in the current
study who described having very little to no support mentioned feeling supported by a therapist.
For most of these youth, the connection to a therapist was relatively recent and often made
through either drop-in services or a shelter program. Given the associations between couchsurfing and poor mental health (Hail-Jares et al., 2021; Petry et al., 2022; Rhoades et al., 2024),
and the traumatic experiences some youth endured while couch-surfing, these findings point
toward the important role that mental health providers can serve in supporting these youth.
Among the most salient observations regarding social support concerned the family
relationships that youth described while couch-surfing. In the preceding twelve months, twothirds of participants indicated at least one couch-surfing arrangement with either an immediate

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or extended family member. This included parents, grandparents, aunts, cousins, and siblings
who agreed to host young people for a finite amount of time. Similar to the predominantly nonfamilial adult hosts under study by VanMeeter and colleagues (2022), many of these family
members were limited in the support they could extend due to material constraints on their own
household. Overcrowding, guest restrictions in subsidized housing, financial burdens, and other
resource limitations were common barriers to providing stable housing for youth. For a number
of youth, hosting family members were themselves involved in high-risk behaviors that they
sought distance from, including substance use and gang activity. But the most cited reason for
leaving these couch-surfing arrangements were shifting and often volatile relational dynamics
with family hosts and other household members. Consequently, youth typically had to leverage
other, often less familiar connections or else resort to the streets. For many young people, this
fostered or otherwise compounded feelings of isolation or abandonment and often signaled
greater destabilization in their housing situation.
Still, family was a central component of young people’s support systems. Even among
youth with fractured family ties, there often persisted a desire to sustain or repair these
relationships, a finding resonant with prior work on the varied and evolving perceptions and
negotiations of family among youth experiencing homelessness (Parker & Mayock, 2019).
However, whether supportive or fraught, young people’s connections to family were seldom
fixed, but dynamic and complex. This fluidity in family relationships underscores unique
opportunities to inform family-based support services and interventions for this population.
While supportive family relationships among youth experiencing homelessness are understood to
serve as a protective factor against risky behaviors and adverse outcomes (Milburn et al., 2023;
Wright et al., 2017), including those related to sexual behavior (Barman-Adhikari et al., 2016;

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Heerde & Hemphill, 2017; Milburn et al., 2012), current findings warrant further investigation
into the temporal patterning of family connections in relationship to young people’s couchsurfing trajectories and transitions in and out of housing.
Transactional sex and couch-surfing
Nearly half of youth interviewed reported direct experience with transactional sex.
Findings highlight the complex individual, social, and structural factors at play in these
encounters while also challenging popular conceptualizations of transactional sex among this
population. While some youth described relatively straightforward exchanges of sex for a place
to stay, for others it was a byproduct of socioeconomic vulnerability and coercive romantic
relationships. Young people couch-surfing with current or former romantic partners often found
themselves in situations where sex was necessary to maintain their housing; consent was neither
unequivocal nor enthusiastic, but instead driven by psychosocial and economic forces that
diminished their agency (Ranganathan et al., 2017; Sileo et al., 2019; Wamoyi et al., 2019).
Importantly, youth themselves often framed these sexual encounters as a method of maintaining
their housing, as sex was not an initial condition of their stay but became an expectation over
time. It is not apparent that these young people would answer affirmatively to survey questions
like the one used to measure transactional sex in the quantitative arm of the larger study: “Have
you ever traded sex or sexual content for things other than money that you needed, such as a
place to stay, food or meals, or anything else?” Questions such as these evoke a set of
circumstances where young people are engaging in more explicit exchanges of sex for material
support. This may be an arguably riskier form of transactional sex, but it misses out on
understanding the sexual exchanges that can occur in couch-surfing contexts—and that may still

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pose significant risks to young people’s health and well-being. Indeed, the young people
interviewed about these situations were not immune to the health risks associated with more
common notions of transactional sex—they, too, often reported engaging in condomless sex and
contracting other STIs, and many expressed emotional distress in relationship to these sexual
encounters.
Prior work centered around young women has also called for a broader conceptualization
of transactional sex, as narrower definitions have limited the efficacy of more targeted HIV
interventions (Stoebenau et al., 2016) and failed to account for gendered social norms within
informal sexual exchange relationships that increase HIV risk (Stoebenau et al., 2019; Wamoyi et
al., 2019). As others have rightly called for distinguishing between exchange sex and sex work in
recognition of the level of sexual agency a youth possesses in a given encounter (Hail-Jares,
2023), future research must also account for other paradigms of transactional sex. These
paradigms need to reflect the multifactorial forces that influence young people’s engagement in
transactional sex to better inform intervention efforts for this population. As findings from the
current study reinforce, this extends to ‘the emotionality of transactional sex’ (Stoebenau et al.,
2016). Young people’s engagement in transactional sex was often driven by a need for emotional
support and intimacy, where a place to stay was either a secondary benefit or altogether absent
from the exchange. The broader discourse surrounding transactional sex among youth
experiencing homelessness has understandably emphasized the associated physical health risks.
Though a handful of studies have indicated that depression is correlated with youth selling sex
more broadly (Krisch et al., 2019) and that loneliness, anxiety, and psychological distress are
associated with increased odds of transactional sex among other vulnerable populations
(Armstrong et al., 2021; Bauermeister et al., 2017; Folayan et al., 2023), there remains a need to

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disentangle the interplay between couch-surfing, mental health, and transactional sex for youth
experiencing homelessness.
Another key finding around transactional sex concerns young people paying for sexual
encounters. While this occurred among a small subset of youth, it highlights an important area
for further investigation; research tends to focus on those who are on the selling side of the
exchange despite a similarly elevated risk of HIV among those who purchase sex (Bobashev et
al., 2009; Dunne et al., 2019). To the author’s knowledge, there is no study that specifically
examines youth experiencing homelessness who pay for sex. However, studies among other
populations suggest that buying and selling sex are associated with different factors that have
important implications for HIV prevention interventions. In their study of men who have sex
with men (MSM) and transgender women, Dunne and colleagues (2019) indicate that while
buying sex was less frequent among younger MSM and transgender women, buying sex was
significantly associated with living alone or with a friend and with a lack of social support. This
is echoed by the experiences youth shared in the current study, whose purchasing of sex while
couch-surfing was motivated in part by a desire for an emotional connection amid unstable and
unsupportive living situations. Future research is needed to investigate the extent to which youth
experiencing homelessness are purchasing sex and what risks may be associated with this
behavior that differ from other forms of transactional sex.
Structural factors influencing engagement in transactional sex
In the present study, all but three of the participants were youth of color, over half were
LGBQ+, and over one-third were transgender or non-binary. Prior work indicating that youth of
color and sexual minority youth are more likely to be couch-surfing has postulated that the social

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networks of these minoritized youth may be particularly supportive of providing such temporary
housing arrangements (Petry et al., 2022). While findings from the current study lend some
credence to this supposition, they also complicate it. Young people’s experiences of couchsurfing, the support their families do or do not provide, and their engagement in transactional sex
are all situated within broader structures of social and economic inequity. Intergenerational
poverty, structural racism, LGBTQ+ stigma and discrimination, and unfettered capitalism all
invariably create and perpetuate the dislocation and marginality of youth who are couch-surfing.
As we consider individual- and even family-level supports to improve outcomes among these
young people, we must also target structural interventions that address the environmental, social,
cultural, economic, and political factors that ultimately affect individual risk and vulnerability
(Sanders & Ellen, 2010; Showden & Majic, 2018). These structural interventions must invariably
include what many youth in these interviews recommended when asked how we can promote the
sexual health and well-being of youth who are couch-surfing: housing.
LIMITATIONS
Findings from the current study provide important new insights into the social support
networks of couch-surfing youth and their varied experiences with transactional sex, but its
limitations warrant acknowledgment. The same limitations concerning the site of data collection
expressed in previous chapters also applies here; the two drop-in centers where interview
participants were recruited also participated in the parent study that provided the data for the
quantitative arm of this dissertation. While these drop-in centers represent major hubs for youth
experiencing homelessness in Los Angeles, they may only represent a particular perspective
given that couch-surfing youth tend to be more disconnected from the homeless services system

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than youth living on the streets or in shelter programs. Youth recruited more broadly or from
settings outside homeless services may have offered different insights on couch-surfing and
experiences with transactional sex. Additionally, given the sensitive nature of asking about young
people’s sexual behaviors, some participants may have been influenced by social desirability and
been less forthcoming about engaging in certain behaviors. Youth also may not have disclosed
difficult or traumatic experiences related to particular relationships or specific couch-surfing
arrangements. Finally, while interview data were robust enough to develop the proposed
conceptual model, the generalizability of this model to the experiences of other couch-surfing
youth is unknown.
CONCLUSION
This study illustrates the complex interplay between couch-surfing, social support, and
transactional sex among youth experiencing homelessness. Findings not only emphasize the
importance of robust social support systems to mitigate the risk of transactional sex but
underscore the need for safe and stable housing to reduce risk and vulnerability among youth
who are couch-surfing. Higher volatility in couch-surfing arrangements and more tenuous or
fewer ties to social supports often coincided with engagement in transactional sex, while lower
couch-surfing volatility and connections to family appeared to buffer against transactional sex
encounters. The dynamic nature of young people’s family relationships signals opportunities for
interventions to strengthen family ties to reduce sexual risk and to support households whose
only barrier to providing youth more stable housing are their own material constraints. However,
although the family may be an effective intervention point for many youth, it is crucial to tackle
the broader structural issues at the root of youth homelessness in order to improve outcomes.

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CHAPTER 5. A DISCUSSION OF IMPLICATIONS FOR YOUTH WHO ARE
COUCH-SURFING: PRACTICE, POLICY, AND RESEARCH
Simply stated, this dissertation aimed to improve our understanding of youth who are
couch-surfing. Among the 3.5 million young adults who experience homelessness in the U.S.
each year, couch-surfing occurs at three to four times the rate of living on the streets or residing
in temporary shelter programs (Curry et al., 2017; Morton et al., 2018). Yet these young people
remain chronically understudied as a subset of youth experiencing homelessness and rendered
invisible by policy debates that presume couch-surfing is fundamentally less risky than other
forms of homelessness. This dissertation makes significant contributions to an emergent body of
research that challenges this assumption and calls for service providers and broader systems of
care to respond to the risks and vulnerabilities associated with couch-surfing (Hail-Jares et al.,
2021; Petry et al., 2022; Rhoades et al., 2024). This dissertation also calls on researchers to avoid
homogenizing the contexts in which youth experience homelessness and to investigate couchsurfing as a unique and distinct set of experiences.
REVIEW OF KEY FINDINGS
Three specific aims directed this dissertation:
1. Investigate whether couch-surfing and social support are associated with HIV-related
behaviors, including transactional sex, condomless sex, sex under the influence,
concurrent sex partners, HIV testing, and PrEP awareness and use;
2. Explore the heterogeneity of youth experiencing homelessness based on their living
situation and social support networks to determine whether:

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a. Minoritized identities and duration of homelessness are correlated with emergent
subgroups, or
b. HIV-related behaviors vary across these same subgroups; and
3. Qualitatively examine how social support and couch-surfing influence sexual risk
behavior among youth experiencing homelessness.
Aim 1 used egocentric social network analysis to explore facets of the social connections
surrounding youth experiencing homelessness (namely, sources of social support), their
relationship to couch-surfing, and subsequent associations with a range of HIV-related behaviors.
Three hypotheses were generated: (1) youth with supportive family members would be
significantly less likely to engage in sexual risk behaviors; (2) couch-surfing would be
significantly associated with greater odds of engaging in transactional sex; and (3) supportive
family and home-based peer connections would moderate the association between couch-surfing
and HIV-related behaviors, essentially mitigating risk behavior and promoting prevention
behavior. Transactional sex emerged as the only HIV-related behavior significantly associated
with couch-surfing. In the final multivariable model, couch-surfing youth were twice as likely to
report recent transactional sex relative to those residing in shelter. Hispanic/Latinx youth and
LGBQ+ youth were each also significantly more likely to indicate recent transactional sex
relative to their White and heterosexual counterparts. Meanwhile, social support was only
significant in the study’s bivariate analysis. No significant interaction effect between couchsurfing and social support was observed and there was no significant main effect in the final
model for transactional sex.

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Aim 2 employed latent class analysis to identify profiles of youth experiencing
homelessness based on current living situation and sources of social support. Three subgroups
emerged: (1) Family support and heterogeneous homelessness, (2) Very little support and
heterogeneous homelessness, and (3) Homeless peer support and no couch-surfing. Couchsurfing youth had zero probability of belonging to the class characterized by its support from
other youth experiencing homelessness and modest probabilities of belonging to the other two
classes that were commensurate with their distribution in the overall sample. While duration of
homelessness was not correlated with class membership, certain minoritized identities were.
Black, multiracial, and other non-Hispanic/Latinx youth of color were significantly more likely
to belong to the Family support and heterogeneous homelessness class than the Homeless peer
and no-couch-surfing class. Relative to the Homeless peer support and no couch-surfing class,
sexual and gender minority youth were each significantly less likely to belong to the Family
support and heterogeneous homelessness class or Very little support and heterogenous
homelessness class. In relationship to the HIV-related behaviors under study, youth in the Family
support and heterogeneous homelessness class were significantly less likely to engage in recent
transactional sex compared to youth in the Very little support and heterogeneous homelessness
class. Together with those in the Very little support and heterogeneous homelessness class, these
youth were also significantly less likely to report knowledge of PrEP compared to the Homeless
peer support and no couch-surfing class.
Finally, Aim 3 utilized qualitative methods in proposing a conceptual model for
understanding the interplay between couch-surfing, social support, and transactional sex. Based
on interviews with 25 youth experiencing homelessness, three themes pertaining to social
support were identified: (1) negotiating support, (2) family connections, and (3) lonely and

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isolated. An additional three themes related to transactional sex identified included: (4) coercive
romantic relationships, (5) seeking emotional connection, and (6) propositioned by hosts.
Findings highlighted the complex relational dynamics and perceptions of social support within
and surrounding young people’s couch-surfing arrangements, and their relationship to the varied
and nuanced experiences youth had with transactional sex. Youth whose couch-surfing
trajectories were characterized by a high degree of volatility more commonly expressed concern
for “ruining” and overextending important relationships with supportive hosts and more
frequently indicated feeling lonely and isolated while couch-surfing. A subset of these youth was
more likely to engage in some form of transactional sex. Those who were connected to family
and those whose couch-surfing trajectories were less volatile were notably less likely to report
transactional sex encounters.
Together, findings across this study’s three aims indicate a specific association between
couch-surfing and transactional sex among youth experiencing homelessness and the complex
role of social support networks in placing certain young people at greater risk for engaging these
types of sexual encounters. In Aim 1, social support was not statistically significant in the final
model and did not moderate the relationship between couch-surfing and recent transactional sex.
However, social support was significant in the bivariate analysis and the composition of young
people’s social support networks was a substantial differentiator among the emergent subgroups
identified in Aim 2. While the logistic regression employed in Aim 1 examined the unique
contributions of select variables while controlling for the others (Stoltzfus, 2011), the latent class
analysis utilized in Aim 2 grouped young people together based on patterns of responses to
observed variables related to living situation and social support (Weller et al., 2020)—and then
examined their associations with a set of auxiliary predictors and distal outcomes. Consequently,

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while the results of Aim 1 suggest that specific sources of social support may not be significantly
associated with transactional sex or affect the relationship between couch-surfing and
transactional sex, the results of Aim 2 suggest that certain combinations or profiles of social
support may affect young people’s engagement in transactional sex. How the temporal patterning
of couch-surfing might intersect with social support to influence this behavior was precluded by
the cross-sectional nature of the quantitative data under study, but observations derived from the
qualitative arm may form the basis for future work to disentangle the potential causal
mechanisms among these factors. Themes derived from the qualitative analysis performed in
Aim 3 underscore the dynamic interplay between couch-surfing, social support, and transactional
sex, and bring forth a more nuanced understanding of how transactional sex manifests within the
varied contexts of couch-surfing. Findings point toward a potential bidirectional relationship
between the volatility of young people’s couch-surfing arrangements and perceptions of social
support that may influence encounters with and subsequent engagement in transactional sex.
Further, transactional sex often appeared to be less characterized by explicit exchanges of sex for
a place to stay and largely the result of complex negotiations taking place within specific social
and environmental contexts surrounding a given couch-surfing arrangement. These findings
ultimately emphasize how the unique contexts of couch-surfing are specifically associated with
transactional sex—and how more nuanced understandings of transactional sex may be necessary
in structuring our assessment of and responses to youth who are couch-surfing.
PRACTICE IMPLICATIONS
Although transactional sex among youth experiencing homelessness is often connected to
more street-entrenched youth, findings from Aim 1 indicate that youth who are couch-surfing are

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also more likely to engage in recent transactional sex relative to those residing in shelter. These
findings were reinforced by findings derived from Aim 3, as transactional sex was commonly
intertwined with young people’s couch-surfing trajectories. The contexts surrounding these
encounters were often distinct from transactional sex experienced under other forms of
homelessness, highlighting the need for greater intentionality in assessing the social and
environmental factors surrounding young people’s couch-surfing arrangements that may place
them at increased risk. While findings may suggest that couch-surfing in and of itself is
associated with transactional sex, this is not to imply that all couch-surfing is inherently risky.
Others have encouraged a more comprehensive and nuanced approach to understanding how
couch-surfing arrangements can be protective and promote resilience (Curry et al., 2021;
VanMeeter et al., 2023) and findings from this dissertation reinforce those sentiments. In
particular, Aim 2 underscores the heterogeneity of these young people’s social support networks
and their differential impact on sex risk. Couch-surfing youth fell into networks characterized by
either supportive family or very little to no support, with the former appearing to buffer against
engagement in transactional sex, and appeared to be wholly disconnected from homeless peer
networks. Further insights gleaned from Aim 3 suggest that most young people encounter both
supportive and unsupportive couch-surfing environments, and that the volatility of a young
person’s couch-surfing may impact their perceptions of social support. These perceptions can
ultimately influence their engagement with transactional sex, but maintaining connections to
family may serve as a protective factor. These findings hold important implications for helping to
assess a young person’s level of risk while couch-surfing and for developing HIV prevention
interventions that factor in young people’s living situations. Supportive family relationships are
pertinent to network-based interventions seeking to mitigate engagement in transactional sex, as

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are considerations for the cultural contexts in which these relationships occur among minoritized
youth (Craddock et al., 2016; Evans et al., 2020; Lauricella et al., 2016).
Study findings also challenge prevailing paradigms around sexual exchange among this
population and point toward the need for interventions that also address the psychosocial facets
of transactional sex, which for some young people served as a primary motivator above and
beyond any material benefit. Findings underscore the myriad paths by which couch-surfing
youth come to the practice, the varied forms of transactional sex they engage in, and the
structural factors in which these all transpire. It is critical to attend to the multiple social and
economic contexts and motivations surrounding transactional sex (Stoebenau et al., 2018), and
structural interventions for the population need to alleviate their socioeconomic vulnerability.
Among vulnerable populations of young women, direct cash transfers have been demonstrated to
reduce engagement in transactional sex (Baird et al., 2012; Cluver et al., 2014; Dunbar et al.,
2014) and among those experiencing homelessness more broadly, cash transfers have shown to
improve housing stability (Dwyer et al., 2023)—and housing has long been argued as a core
structural intervention in the prevention of HIV (Adimora et al., 2010; Holtgrave et al., 2007;
Kidder et al., 2007).
POLICY IMPLICATIONS
This research is situated within a broader debate over defining youth homelessness in the
U.S. and the systematic exclusion of couch-surfing youth from the homeless services system.
Current homelessness policy dictated by HUD functions on a presumption that a young person
who is couch-surfing is “less homeless” than those on the street or in the shelter system—and
therefore less deserving of help (Holtschneider, 2021). This is codified in policies that require

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communities to institute ranking systems that deprioritize couch-surfing and in funding
regulations that preclude these young people from accessing vital housing opportunities. Study
findings challenge the notion that couch-surfing is inherently less risky or dangerous than other
forms of homelessness and call for policymakers to include couch-surfing in responses to youth
homelessness. The definitions of youth homelessness employed by HUD need to accurately
reflect the realities of youth homelessness, and the systems and interventions funded by HUD
need to be granted the ability to effectively respond to the realities of youth homelessness in
local communities. Excluding these young people from national estimates that drive policy and
funding decisions and excluding them from housing out of scarcity concerns is unacceptable, and
antithetical to their purported mission of ending homelessness. While these exclusionary policies
are deeply rooted in and symptomatic of much broader systemic problems related to poverty and
discrimination, there are still significant if incremental changes that can be made to address the
issues highlighted by this dissertation.
The alignment of federal definitions of youth homelessness to be inclusive of couchsurfing remains a long-standing and worthy goal of advocates and includes last year’s reintroduction of the Homeless Children and Youth Act (HCYA). Still, there are additional paths
we might consider to broaden the scope of youth who get served by HUD programs. While the
HEARTH Act of 2009 makes certain stipulations regarding when communities can serve youth
defined as homeless under other federal statutes (i.e., Category 3), HUD has erected additional
barriers that render Category 3 symbolic. Even in the Youth Homelessness Demonstration
Program (YHDP), HUD’s special initiative to support coordinated community efforts to address
youth homelessness, restrictions around Category 3 persist (HUD, 2023c). However, YHDP
represents an opportunity at the federal level to loosen the restrictions surrounding Category 3—

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even on a pilot basis—to enable communities to coordinate a system of care that is responsive to
the realities of youth homelessness.
Even lower hanging fruit, and in direct relation to the findings of this dissertation study,
is improving the guidance on transactional sex as meeting eligibility requirements under HUD’s
Category 4 homelessness definition. The only place this guidance is currently found is in a
supplemental handout on how to apply HUD’s four categories of homelessness specifically to
youth (HUD, 2015). Trading sex is absent from both HUD’s primary guidance on Category 4 and
their annual Notice of Funding Opportunity, which delineates the eligibility criteria for specific
projects funded through the CoC program. Making this guidance more readily apparent
facilitates an avenue to provide housing support to youth engaged in transactional sex—even if
they are couch-surfing. While findings from this study indicate that identifying youth engaged in
transactional sex is not always so clear, being able to marshal resources once it does is critical.
RESEARCH IMPLICATIONS
Finally, arguably the most direct and far-reaching implication of this dissertation is the
importance of abandoning the research trend of homogenizing the forms of homelessness that
youth experience. While further work is needed to determine how couch-surfing ought to be
conceptualized and subsequently measured, perfection need not be the enemy of good. Often,
youth accessing homeless services or participating in research studies are simply presented with
the option of selecting “couch-surfing” alongside other living situations (as in Hail-Jares et al.,
2021; Morton et al., 2018; Petry et al., 2022; Rhoades et al., 2024). In others, youth broadly
indicate that they are temporarily staying with others (as in Barman-Adhikari et al., 2016; Rice et
al., 2023). In the latter case, sometimes these measures include additional context (e.g., ‘because

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I do not have a safe or stable place to stay’) (as in Morton et al., 2018; Owens et al., 2020) or
assess the perceived stability of the temporary housing arrangement (as in Narendorf et al., 2016;
Santa Maria et al., 2018), particularly when stably housed youth are part of the same study.
While disaggregating living situations among youth experiencing homelessness may not be
feasible for every study, a greater intentionality in collecting data on couch-surfing and in
investigating potential differences across forms of homelessness may have a particularly
profound impact on responses to youth homelessness. Research plays a critical role in arming
youth, advocates, and policymakers with information that moves the needle forward—the policy
implications are too great and the stakes too high for youth who are couch-surfing for us to
render them invisible in our work.

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Abstract (if available)

Abstract “Couch-surfing” is nearly four times more prevalent than living on the streets or residing in temporary shelter programs among youth experiencing homelessness (YEH). Yet there persists a lack of research on couch-surfing YEH, who are precluded from accessing many resources through current homeless services systems simply because of their living situation. Examining how couch-surfing may relate to specific vulnerabilities, including HIV risk, is critical to better understanding this phenomenon and to improving U.S. policy responses to youth homelessness. Key to this examination is the role of young people’s social support networks, given their particular importance in facilitating couch-surfing arrangements and in influencing various sexual health behaviors. This dissertation endeavors to explore the relationships between couch-surfing, social support, and HIV risk through three separate studies corresponding to three specific aims. Aim 1 uses egocentric social network analysis to investigate whether couch-surfing and social support are associated with specific HIV-related behaviors, including transactional sex, condomless sex, sex under the influence, concurrent sex partners, HIV testing, and PrEP awareness and use. Aim 2 uses latent class analysis to explore the heterogeneity of YEH based on their living situation and social support networks to examine (a) whether minoritized identities and duration of homelessness relate to emergent subgroups and (b) whether HIV-related behaviors vary across these same subgroups. Finally, Aim 3 uses qualitative methods to investigate the relationships between couch-surfing, social support, and sexual risk among a sample of 25 YEH. This study will expand knowledge regarding HIV-related behaviors among YEH, provide new insights into couch-surfing among YEH, and pave the way for the development of more tailored health interventions and more impactful homelessness policy.

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Asset Metadata

Creator Petry, Laura (author)

Core Title Couch-surfing among youth experiencing homelessness: an examination of HIV risk

School Suzanne Dworak-Peck School of Social Work

Degree Doctor of Philosophy

Degree Program Social Work

Degree Conferral Date 2024-08

Publication Date 06/25/2024

Defense Date 06/12/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag couch-surfing,HIV risk,OAI-PMH Harvest,social support,transactional sex,Young adults,youth homelessness

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Rice, Eric (committee chair), Henwood, Benjamin (committee member), Vayanos, Phebe (committee member)

Creator Email lkpetry@gmail.com,lpetry@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC1139970N8

Unique identifier UC1139970N8

Identifier etd-PetryLaura-13146.pdf (filename)

Legacy Identifier etd-PetryLaura-13146

Document Type Dissertation

Format theses (aat)

Rights Petry, Laura

Internet Media Type application/pdf

Type texts

Source 20240625-usctheses-batch-1174 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA

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