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Discrimination at the margins: perceived discrimination and the role of social support in mental health service use for youth experiencing homelessness
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Discrimination at the margins: perceived discrimination and the role of social support in mental health service use for youth experiencing homelessness
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Content
DISCRIMINATION AT THE MARGINS: PERCEIVED DISCRIMINATION AND THE
ROLE OF SOCIAL SUPPORT IN MENTAL HEALTH SERVICE USE FOR YOUTH
EXPERIENCING HOMELESSNESS
by
Monique Holguin
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 2021
Copyright 2021 Monique Holguin
ii
Dedication
This dissertation is dedicated to the people whose love and support made it possible for
me to thrive in my academic career. First, this dissertation is dedicated to my husband and
daughter. I am beyond grateful for your unconditional love and patience. To my husband, you
have rooted me on from day one and there is no one else I would rather ride this journey with
than you. I am humbled by and forever grateful for your love. To my daughter, you have given
me more purpose and joy than I ever dreamt possible. I love you always sunshine. To my mom,
Nina, and two brothers (Bobby and Arthur), thank you for always believing that this little girl
from Rose Hills could create a positive impact in this world and instilling core family and
community values that solidified my purpose. This dissertation is specifically dedicated to the
memory of my grandmother and hero, Eulalia Ibarra. Your unwavering love and commitment to
community has been the inspiration for all of it. I am eternally grateful for the foundation of love
and commitment to service you provided. Lastly, to the countless other people who I have had
the good fortune to cross paths with and for whose support, inspiration, guidance, and
encouragement helped to make my academic dreams possible...thank you, thank you, thank you.
This dissertation is also dedicated to you.
iii
Acknowledgments
I would like to express my deepest appreciation to my committee members, Dr. Eric
Rice, Dr. Monica Perez Jolles, and Dr. Michael Cousineau for their unwavering support,
constructive feedback, and ongoing guidance. Their investment in my academic growth provided
the foundation I needed to think more critically about my research ideas, conceptual frameworks,
analysis plan and interpretation of findings. Ultimately, it was this investment that served as
motivation for me to take this dissertation to the next level. I am incredibly grateful to all of you.
I would also like to extend my deepest gratitude to all of the youth experiencing homelessness
who participated in our study. Your resilience is remarkable and remarkably rich and complex.
This dissertation would not be possible without your participation and I am truly thankful. Last
but not least, I would like to extend my gratitude to my fellow student colleagues, faculty, and
staff at USC Suzanne Dworak-Peck School of Social Work for their encouragement and support.
Thank you for believing in the value of my work and contributions to academia and community
iv
Table of Contents
Dedication ....................................................................................................................................... ii
Acknowledgments.......................................................................................................................... iii
List of Tables ................................................................................................................................. vi
List of Figures .............................................................................................................................. viii
Abstract .......................................................................................................................................... ix
Chapter 1: Overview of Dissertation Topic and Research.............................................................. 1
Overview of the Chapters ............................................................................................. 4
Prevalence ..................................................................................................................... 5
Demographic Profile ..................................................................................................... 5
Challenges Facing Youth Experiencing Homelessness ................................................ 7
Intersectionality........................................................................................................... 14
The Risk Amplification and Abatement Model .......................................................... 17
An Intersectional-based RAAM Framework .............................................................. 20
Chapter 2: Prevalence of Discrimination Among Youth Experiencing Homelessness ................ 25
Discrimination and Other Related Populations........................................................... 26
Discrimination and Youth Experiencing Homelessness ............................................. 27
Serious Consequences of Discrimination ................................................................... 29
An Intersectional-Based RAAM Framework ............................................................. 30
Current Study .............................................................................................................. 31
Methods....................................................................................................................... 32
Measures ..................................................................................................................... 33
Data Analysis .............................................................................................................. 37
Results ......................................................................................................................... 38
Discussion ................................................................................................................... 54
Limitations .................................................................................................................. 58
Chapter 3: Prevalence of Supportive Staff Among Youth Experiencing Homelessness .............. 63
Social Support ............................................................................................................. 63
Current Study .............................................................................................................. 66
Methods....................................................................................................................... 67
Data Analysis .............................................................................................................. 72
Results ......................................................................................................................... 72
Discussion ................................................................................................................... 80
Limitations .................................................................................................................. 83
Implications................................................................................................................. 84
v
Chapter 4: Discriminatory Experiences, Staff Support, and Service Engagement
Among Youth Experiencing Homelessness................................................................ 86
Mental Health Service Needs...................................................................................... 86
Staff Support in Drop-In Centers ................................................................................ 87
Perceived Discrimination in Community and Service Settings .................................. 89
Current Study .............................................................................................................. 90
Methods....................................................................................................................... 91
Measures ..................................................................................................................... 92
Data Analysis .............................................................................................................. 96
Results ......................................................................................................................... 97
Discussion ................................................................................................................. 111
Limitations ................................................................................................................ 115
Conclusion ................................................................................................................ 116
Chapter 5: Discussion ................................................................................................................. 117
Resilience and Positive Staff Support ....................................................................... 122
Multiple Marginalized LGB and Non-Cisgender Youth Experiencing
Homelessness ............................................................................................................ 126
Intersectional-Based RAAM Framework ................................................................. 129
Conclusion ................................................................................................................ 135
References ................................................................................................................................... 137
vi
List of Tables
Table 2.1. Descriptivetatistics For Youth Experiencing Homelessness (n = 198) ..................... 39
Table 2.2. Descriptive Statistics for Marginalized and Multiple Marginalized Youth
Experiencing Homelessness........................................................................................ 40
Table 2.3. Prevalence of Discrimination Experiences Among Youth Experiencing
Homelessness (n = 198) .............................................................................................. 42
Table 2.4. Prevalence of Discrimination Experiences Among Marginalized and Multiple-
Marginalized Youth Experiencing Homelessness (n = 198) ...................................... 46
Table 2.5. Main Reason for Perceived Discrimination Among all Youth Experiencing
Homelessness .............................................................................................................. 50
Table 2.6. Main Reason For Perceived Discrimination Among Multiple-Marginalized
Youth Experiencing Homelessness............................................................................. 53
Table 3.1. Descriptive Statistics of Youth Experiencing Homelessness (n = 198) ..................... 74
Table 3.2. Positive Staff Relationships of Youth Experiencing Homelessness (n = 198) ........... 76
Table 3.3. Positive Staff Relationships of Marginalized and Multiple Marginalized
Youth Experiencing Homelessness (n = 198) ............................................................. 77
Table 3.4. Bivariate Logistic Regressions of Positive Staff Support ........................................... 78
Table 3.5. Multivariate Logistic Regression of Positive Staff Relationship Given
Drop-In Center Discrimination (n = 198) ................................................................... 79
Table 3.6. Multivariate Logistic Regression of Positive Staff Relationship Given
Health Services Center Discrimination (n = 198) ....................................................... 80
Table 4.1. Descriptive Statistics of Youth Experiencing Homelessness (n =198) ...................... 99
Table 4.2. Mental Health Service Use of Youth Experiencing Homelessness (n = 35) ............ 101
Table 4.3. Mental Health Service Use Among Multiple-Marginalized Youth
Experiencing Homelessness (n = 35) ........................................................................ 103
Table 4.4. Bivariate Logistic Regressions of Mental Health Service Use ................................. 104
Table 4.5. Multivariate Logistic Regression of Mental Health Service Use Among
Youth Experiencing Homelessness (n = 198) ........................................................... 105
Table 4.6. Multivariate Logistic Regression of Mental Health Service Use Among
Youth Experiencing Homelessness (n = 198) ........................................................... 106
vii
Table 4.7. Frequency of Drop-In Center Attendance Among Youth Experiencing
Homelessness (n = 198) ........................................................................................... 108
Table 4.8. Bivariate Logistic Regressions of Daily Drop-In Center Attendance ...................... 109
Table 4.9. Multivariate Logistic Regression of Daily Drop-In Center
Attendance (n = 198) ................................................................................................ 110
Table 4.10. Multivariate Logistic Regression of Daily Drop-In Center
Attendance (n = 198) ............................................................................................... 111
viii
List of Figures
Figure 1.1. An Intersectional-Based RAAM Framework for Youth Experiencing
Homelessness ............................................................................................................ 24
Figure 2.1. Demographics on Marginalized and Multiple Marginalized Youth
Experiencing Homelessness (n = 198) ...................................................................... 41
Figure 2.2. Main Reason for Perceived Discrimination Among All Youth
Experiencing Homelessness ...................................................................................... 51
ix
Abstract
Youth who identify with marginalization and multiple marginalization comprise a substantial
and disproportionate portion of the population experiencing homelessness and yet little is known
about their perceived discriminatory experiences across settings fundamental to their health and
housing stability. This dissertation built upon the Risk Amplification and Abatement Model (to
incorporate an Intersectionality lens in an effort to understand the specific and varied
discriminatory experiences MM-YEH face and its association with social support and mental
health service use. Chapter 2 results revealed that the majority of Heterosexual, Non-Cisgender
YEH (60%, X
2
= 12.48, p < .01) were more likely to report drop-in center discrimination than any
other MM-YEH groups. Race was reported as the main factor for discrimination (N = 66; 51.9%)
among all YEH participants who endorsed perceived discrimination of any type. Chapter 3
results found that in regard to gender, non-cisgender youth (OR = 3.31, 95%CI = 1.05, 10.43, p
<.05) were more likely to have a positive staff relationship, compared to cisgender youth.
Chapter 4 results found that youth who endorsed a positive staff relationship (OR = 3.57, 95%CI
= 1.52, 8.43, p <.003) were more likely to frequent the drop-in center daily, compared to youth
without a positive staff relationship. Youth who reported community settings only discrimination
were more likely (OR = 2.53, 95% CI = 1.03, 6.16, p <.03) to frequent the drop-in center daily
compared to youth who did not report community settings only discrimination. The findings
demonstrate a need to expand focus from deficit-based narratives to resilience and adaptive
coping among youth experiencing homelessness. Future research should incorporate
Intersectional-lens RAAM framework and incorporate Critical Race theory (CRT) to understand
and explore how to comprehensively measure discrimination and structural racism among MM-
YEH.
1
Chapter 1: Overview of Dissertation Topic and Research
Marginalized and multiple marginalized youth experiencing homelessness (MM-YEH)
are tasked daily with managing compounding stressors associated with their intersecting
racial/ethnic, sexual minority and homelessness identities distinct from their White, heterosexual
YEH peers. Moreover, youth experiencing homelessness (YEH) who endorse one or more of
these marginalized identities report higher rates of depressive symptoms and suicidality (Gattis
& Larson, 2016), with a substantial body of research suggesting that discrimination targeted at
one or more identities contributes to poor mental health outcomes
(Almeida et al., 2009; Brody et
al., 2006; Thoma & Huebner, 2013). YEH are disproportionately at risk for serious physical and
behavioral health consequences while simultaneously being one of the most medically
underserved (Hudson et al., 2010; Christiani et al., 2008). Furthermore, YEH have previously
reported perceived discrimination as a barrier in choosing not to seek or maintain health service
use (Rew, 2000; Hudson, 2010; Gattis, 2013). Although researchers are increasingly interested in
how discrimination impacts YEH mental health symptoms and access to care
(Milburn et al,
2006, 2009; Gattis, 2013, 2016), we continue to lack clarity on the prevalence of discrimination
amongst YEH, including: which YEH may be more likely at risk and types of service and
community settings more prone to exhibit discrimination. To our knowledge, there is limited
research specifically focused on the prevalence of multiple marginalized YEH who identify as
both LGBT and with a racial/ethnic minority group. Of the few studies that have addressed
racial/ethnic prevalence amongst LGBT YEH, YEH who identified as LGBT were also found to
disproportionately identify as a person of color (Gattis & Larson, 2017; Reck, 2009). Youth who
are Black and LGBT, particularly young men, report the highest rates of homelessness (Morton,
2
Samuels, Dworsky & Patel, 2018). Unfortunately, few studies focused on the health service use
of LGBT youth of color experiencing homelessness.
Focusing on MM-YEH, this dissertation will build upon the Risk Amplification and
Abatement Model (RAAM) (Milburn et al., 2006) to incorporate an Intersectionality lens
(Crenshaw, 1990) in an effort to understand the specific and varied discriminatory experiences
MM-YEH face and its association with social support and mental health service use. Elucidating
a deeper understanding of YEH’s discriminatory experiences will offer a path toward culturally
tailored interventions to address the impact of discrimination and enhance social support and
mental health service use for this population. To our knowledge, no study has yet to examine if
positive adult support can mitigate the damaging effects of discrimination and promote
behavioral service use for YEH.
The present cross-sectional study will use an Intersectional-based Risk Amplification and
Abatement framework, to explore the prevalence of discrimination and its potential association
with positive adult support and mental health service use for YEH. Expanding the RAAM model
to include an Intersectional lens will allow for a more in-depth focus of the interconnected role of
race/ethnicity, sexual orientation and homelessness, that may show a more complex side of
discrimination and how it potentially shapes the adults and systems that these youth come in
contact with. For the purposes of the analysis, this model will be used to evaluate YEH’ unique
discriminatory experiences interactions with supports, e.g., formal adults and systems, e.g., drop-
in center mental health service utilization, given the youth’s constellation of interrelated and
intersecting social roles. Thus, the overarching goal of the proposed study is to examine the
prevalence of discrimination and to identify the potential differences in supportive staff relations
and drop-in center and mental health service utilization among MM-YEH compared to their
3
White, heterosexual YEH counterparts within an Intersectional-based RAAM framework.
Relying upon Intersectionality and RAAM key domains, we will meet this goal by completing
the following specific aims:
1. To identify and understand perceived discrimination prevalence of intersecting youth
experiencing homelessness, including: which sub-groups are most at risk and types of
service and community settings, e.g., law enforcement, drop-in centers, health and
behavioral services, employer and community, perceived as discriminatory.
2. To identify and understand the main reason for perceived discrimination among YEH
intersecting sub-groups.
3. To identify which YEH subgroups are more likely to have a positive formal (staff)
support.
4. To examine potential main effects between perceived discrimination and positive formal
(staff) support.
5. To examine potential main effects between the following independent variables:
perceived discrimination in community services settings, discrimination in drop-in
centers, positive staff support and the following outcome variable: frequency of drop-in
attendance among MM-YEH.
6. To examine potential main effects between the following independent variables:
perceived discrimination in community services settings only, drop-in centers, positive
staff support and the following outcome variable: mental health service use, among MM-
YEH.
This is the first known study to utilize an Intersectional and RAAM framework to
investigate the prevalence of discrimination and its association with social support and mental
4
health service use for YEH. This study fits with the NIMHD vision to prioritize the prevalence
and impact of health disparities and disseminate effective individual-, community-, and
population-level interventions to reduce and encourage elimination of health disparities
(Alvidrez
et al., 2018) Research that provides a deeper understanding of the associated factors involved in
YEH’ mental health service use is necessary considering the rapidly evolving social, service and
housing landscape that has disproportionately impacted MM-YEH. By addressing the unique
stressors experienced by MM-YEH, this study is able to draw a greater emphasis of public and
population health concerns. Using Intersectionality as a framework lends to a greater focus on
intersecting marginalized stressors involved in the social determinants of health and need to
address YEH mental health as a larger public and population health issue.
Overview of the Chapters
This dissertation is divided into five chapters: (1) Introduction, Literature Review, and
Conceptual Framework, (2) Perceived Discrimination Prevalence among MM-YEH, (3)
Perceived Discrimination and Positive Adult Support Among MM-YEH, (4) Perceived
Discrimination, Staff Support, and Service Engagement among MM-YEH, (5) Discussion. This
introduction chapter (Chapter 1) provides an overview of the prevalence and health demographic
profile of YEH with particular attention paid to MM-YEH, an overview of the literature focused
on specific issues facing YEH, including: mental health, service utilization, and discrimination.
The literature review presents a case as to why it is critical to examine discriminatory
experiences among YEH sub-groups and why it may be necessary to explore positive adult
support among MM-YEH to support mental health service use pathways. The conceptual
framework illustrates the two conceptual models (Risk Amplification and Abatement Model and
Intersectionality) used to conceptualize and frame the examination of the three aims in this study.
5
Prevalence
A society must be measured by how it treats its most vulnerable and valuable members
which undoubtedly includes youth experiencing homelessness (YEH). The national prevalence
of youth homelessness in the U.S. makes it abundantly clear that as a nation we are falling
shamefully short (Morton et al., 2018). Morton and colleagues (2018) found that approximately
one in thirty adolescents (13-17 years) and one in ten young adults (18-25 years) experienced
some form of homelessness during a 12-month period. This study also found disparities in regard
to race/ethnicity and sexual orientation; Black, Latinx, and America Indian and Alaska Native as
well as lesbian, gay, bisexual, transgender and questioning youth were more likely to experience
homelessness than their White and heterosexual identifying counterparts (Morton et al., 2018).
Furthermore, YEH experience a disproportionate health burden in comparison to their housed
peers (Edidin, Ganim, Hunter, & Karnik, 2012) and face barriers when seeking health services
(Pedersen, Tucker, & Kovalchik, 2016). Simply put, homelessness among youth is a dire social
and health concern, particularly for marginalized and multiple marginalized youth experiencing
homelessness (MM-YEH).
Demographic Profile
LGBTQ individuals are disproportionately represented in the overall homeless population
compared to the general population. It is estimated that 20-40% of YEH identify as LGBT
(Corliss, Goodenow, Nichols, & Austin, 2011; Durso & Gates, 2012; Keuroghlian, Shtasel, &
Bassuk, 2014; Ray, 2006; Morton et al., 2018). These figures may not be fully representative
due to underreporting and possible sampling bias stemming from the stigma associated with
coming out and identifying as a sexual minority as well as the elusiveness of the LGBT
definition for researchers (Meyer & Wilson, 2009). Nonetheless, the fact remains that LGBT
6
youth experience homelessness more frequently than their heterosexual peers (Morton et al.,
2018; Rice et al., 2013). National estimates suggest the risk of youth reporting homelessness is
up to 120% higher for LGBT youth compared to their peers who identify as heterosexual or
cisgender (Morton, Dworsky, & Samuels, 2017). Racial and sexual minority disparities are also
present in Los Angeles county. While Black youth only represent 7.9% of the population in Los
Angeles, Black YEH account for 38.2% of youth homelessness in Los Angeles (Los Angeles
Homeless Services Authority (2020)). Furthermore, one in five Los Angeles YEH reported being
lesbian, gay, bisexual or sexual orientation nonconforming (Los Angeles Homeless Services
Authority (2020). Moreover, LGBT youth experiencing homelessness are at increased risk of
negative mental health outcomes when compared to their housed sexual minority peers (Rosario,
Schrimshaw, & Hunter, 2012; Walls, Hancock, & Wisneski, 2007) and heterosexual peers
experiencing homelessness (Gattis, 2013; Gattis, 2009; Whitbeck, et al., 2004; Grafsky, Letcher,
Slesnik, & Serovich, 2011).
People of color are dramatically more likely to become homeless in the United States
compared to their White counterparts. Blacks make up more than 40% of the homeless
population, but represent only 13% of the population (National Alliance to End Homelessnes,
2018). Of particular note, Black and Latino youth are overrepresented among the U.S.
population experiencing homelessness (Morton et al., 2018). As such, Black and Latino YEH
occupying multiple positions of marginalization, may likely face a myriad of unique stressors not
experienced by their white peers experiencing homelessness, which can be linked to increased
rates of depressive symptoms compared to their white unhoused counterparts (Adkins, et al.,
2009; Gore & Aseltine, 2003).
7
Challenges Facing Youth Experiencing Homelessness
Mental Health Needs
Among the housed population, persons identifying with marginalized identities have been
empirically linked to mental health outcomes with a preponderance of evidence suggesting that
marginalized and multiple marginalized youth are at serious risk for mental health challenges
(Russel & Fish, 2016; Mereish, Sheskir, Hawthorne, & Goldbach, 2019). In other words, YEH
identifying with multiple marginalized identities may be experiencing particular external
circumstances prone to producing more stress, which then affects the probability of mental health
problems. For example, a particular Black LGB male YEH may experience unique stressors
based on the experience of racism, homophobia, etc. in this particular environment which may
associate with risk for mental health issues that may likely be altogether different for White LGB
YEH and Black hetero YEH. Of note, mental health issues associated by a social position is not
in and of itself predictive of any given circumstance or outcome but rather creates particular
discrepancies between the demands and treatment of the external systems in one’s environment
and the attributes of the individual carrying marginalized identities. Therefore, while some
circumstances of identity and status hierarchies many not reliably affect mental health outcomes,
other marginalized circumstances may be more threatening and damaging (Nyamanthi et al.,
2012; Bender et al., 2012).
The experience of homelessness leaves youth more susceptible for serious health and
mental health consequences (Asante, Meyer-Weitz, & Petersen, 2016; Ensign, 2004; Edidin,
Garnik, Hunter, & Garnik, 2012; Pedersen, Tucker, Klein, & Parast, 2018). In fact, one of the
defining characteristics of YEH that distinguishes them from their housed peers is their high
vulnerability to serious mental illness. YEH are a heterogeneous population but share in common
8
precarious and often highly dangerous living conditions coupled with extreme disadvantage and
alienation (Bender et al., 2014; Thrane , Hoyt & Whitbeck, 2006; Davies & Allen, 2017; Kidd &
Carroll, 2007), particularly for those who experience poor mental health. Histories of childhood
maltreatment and highly conflicted family relationships are commonly noted among YEH and
considered to be a key factor to youth leaving or being kicked out of their home (Brook,
Milburn, Rotheram-Borus, & Witkin, 2004; Hyde, 2005). The psychological harm from previous
trauma and abuse amplifies when youth leave home and are now left to fend for themselves on
the streets (Whitbeck, Hoyt, & Yoder, 1999; Stewart et al., 2004). Being unaccompanied and
with few means of financial support, YEH are vulnerable to being exploited and victimized
(Rew, 2008; Taylor-Seehafer, 2004, Whitbeck, Chen, & Johnson, 2006; Stewart et al., 2004).
Experiences of victimization and the daily toll of life on the streets, can exacerbate a youth’s
prior trauma, and ultimately contribute to a greater risk of serious mental illness (Rohde et al.,
2001; Bender, Ferguson, Thompson, & Langenderfer, 2014, Thompson et al., 2010).
Whitbeck, Hoyt, & Bao (2000) found street victimization (e.g., verbal, physical, or sexual
assault while homeless) to be positively associated with depressive symptoms above the clinical
threshold, even after controlling from contributing family risk factors, such as abuse and
rejection. An abundance of literature has demonstrated disproportionately higher rates of mental
illness among YEH compared to the general adolescent and young adult population (Edidin et
al., 2012; Kidd, 2006; Burt, Pearson, & Montgomery, 2007; Solorio et al., 2006). At least 50% of
YEH are thought to have serious mental health and/or substance abuse problems (Ensign & Bell,
2004). Moreover, sexual minority youth experiencing homelessness (SM-YEH) have particularly
high rates of mental health and substance use problems and suicidality (Tyler, 2013; Whitbeck et
al., 2004). Among housed youth in general, sexual minority youth are more vulnerable to
9
psychological problems that their heterosexual counterparts (Ahuja et al., 2015; Becerra-Culqui
et al., 2018). Many are victims of family rejection, parental abuse and have mental health issues.
These problems are amplified for sexual minority youth who become homeless (Rhoades
et al., 2018; Keuroughlin, Shtasel, & Bassuk, 2014). SM-YEH report that one of the main
reasons for running away or being forced out of their home is family rejection and parental abuse
(Keuroughlin, Shtasel, & Bassuk, 2014; Durso & Gates, 2012). Negative experiences in the
families of origin of SM-YEH are associated with greater mental health challenges and poor
coping skills (Moskowitz, Stein & Lightfoot, 2012). In comparison with heterosexual YEH, SM-
YEH report greater rates of mental illness, including depression, anxiety, posttraumatic stress
disorder (PTSD), substance use disorder, and suicidal ideation (Substance Abuse and Mental
Health Services [SAMHSA], 2011; Whitbeck et al., 2004).
The association between race/ethnicity and mental health may not be as clear for youth
experiencing homelessness. Although the research remains sparse in addressing racial
differences in mental health symptoms among YEH, one recent study (Gattis & Larson, 2016)
found that depressive symptoms and suicidality are prevalent among Black YEH, and that
depressive symptoms are particularly associated with racial discrimination and homelessness
status. Moreover, perceived racial discrimination showed the most consistent pattern of
association with poor mental health outcomes Black YEH, compared to other forms of
discrimination (Gattis & Larson, 2016). A lack of attention to various and unique forms of
marginalization, and their accompanying multiple forms of discrimination, may undercut attempt
to adequately identify, prevent, and treat mental health issues among MM-YEH.
Findings are somewhat more consistent among housed youth; several studies have found
that depressive symptoms are more pronounced among Black youth in comparison to their White
10
counterparts (Adkins et al., 2009; Boardman & Alexander, 2011; Gore & Aseltine, 2003). Other
studies investigating housed youth, found that racial and ethnic groups indicated higher levels of
acute and chronic stress than their White peers (Boardman & Alexander, 2011). Conversely,
additional research investigating housed youth indicated that the prevalence of mental health
problems, particularly depressive symptoms and depressive disorders, is greater among Whites
than Blacks (Kessler et al., 1999; Riolo, Nguyen, Greden, & King, 2005), and yet other studies
found the opposite (Pratt & Brody, 2008; Tayler & Turner, 2002; Gonzalez, Tarraf, Whitfield &
Vega, 2010).
Low Service Utilization
Despite the increased burden of mental illness, YEH frequently underutilize available
services intended to alleviate some of these stressors. In regard to mental health service
utilization, YEH who live with mental health problems are even less likely to receive treatment
(Solorio et al., 2006; Holmes et al., 2005; Klein et al., 2007). Historically, YEH report barriers in
accessing care (Slesnick, Zhang, & Brakenhoff, 2017; Barman-Adhikari et al., 2016; Edidin,
Ganim, Hunter, & Karnik, 2012), particularly in connecting to behavioral health, health and
substance use treatment (Edidin, Ganim,Hunter & Karnik, 2012; Christiani et al., 2008;
Chelvakumar et al., 2017; ). Literature suggests YEH are more inclined to use services that meet
their basic day-to-day needs, e.g., food, clothing, shower, etc., rather than participate in targeted
services to address their health, behavioral health and/or trauma related issues (Slesnick et al.,
2008; Pederson, Tucker & Kolvachik, 2016). The inability for healthcare services to engage
these youth contributes to additive deleterious health consequences such as increased risk of
substance use disorders, victimization, mood disorders, sexually transmitted diseases, and
suicidality (Christiani, 2008; Kushel, Yen, Gee, & Courtney, 2007; Kryda & Compton, 2009).
11
Combined, these consequences contribute to the vicious cycle of chronic homelessness and
poverty for many youth. Youth not accessing behavioral health services are those most likely in
need of outreach and engagement; Kryda and Compton (2009) found that unengaged youth have
more severe risk factors, including higher substance use, mental health problems, and decreased
likelihood of exiting homelessness. There are several reasons why YEH may not receive regular
health care; these include fear of social service agency notification, fear of legal intervention,
lack of familiarity with respect to how to access health care resources, and lack of affordable
health insurance (Klein, 2000).
Barriers to health care access also suggest there are factors related to service, including:
feeling discriminated against (Christiani et al., 2008; Hudson et al., 2010), distrust or dislike of
service providers (Solorio et al., 2006), and knowledge of what services are available and where
to go (Solorio et al., 2006; Stewart et al.,2014). Three concurrent studies examined barriers to
health and behavioral health care for YEH in Los Angeles (Christiani et al., 2008), Santa Monica
(Hudson et al., 2010), and Ontario (Kozloff et al., 2913) identified personal barriers, including,
stigma and fear or discrimination as well as structural barriers, such as, knowledge on how to
access services. Similarly, Martins (2008) found stigmatization and the sense of disrespect
toward homelessness as a reported barrier to health care delivery and suggest there exists two
separate yet unequal health care delivery systems, one for the housed and one sub-par system for
those experiencing homelessness. There is a growing investment from both providers and
researchers to address discriminatory barriers to care; however, given the current gap in the
literature there is still unanswered questions as to the magnitude of this barrier and the YEH
subgroups most vulnerable to discrimination.
12
Discrimination
There is a well-established association between both overt as well as subtle forms of
discrimination (e.g., microaggressions) and deleterious emotional, physical and behavioral health
outcomes among the housed youth population (Nadal e.g., 2014; Brondolo, Rieppi, Kelly &
Gerin, 2003). Chronic and persistent stress from stigmatization and discrimination can lead to
wear and tear on the body (Williams et al., 1997; Geronimus et al., 1996); McEwen, 2004;
Troxel et al., 2003), contributing to a host of physical and psychological health risks (Williams et
al., 2003; Gee, 2008; Krieger, 2014). The impact of discrimination can also contribute to feelings
of helplessness and reduced levels of trust among victims (Nnawulezi & Sullivan, 2014). Both
subtle and explicit forms of discrimination negatively affects victims’ trust in service providers
and caregivers and has been a factor in poor treatment adherence (Cuffee et al, 2013; Gonzales,
Davidoff, DeLuca, & Yanos, 2015; Jones et al., 2017). Although research has overwhelmingly
focused on perceived discrimination among housed adults, housed youth and young adults face
discrimination in an array of community and service settings including: primary care (Shearer et
al., 2016), mental health (Grollman, 2012, in employment and the workplace, interactions with
law enforcement, in community, and in school settings (Brody et al., 2006; Gee and Walseman,
2009; Leaper and Brown, 2008).
Currently there is a dearth in the literature; however, a few studies have found a
relationship between discrimination and negative mental health outcomes for this population.
Gattis and Larson (2016) examined discriminatory experiences for YEH and found that YEH
who reported discrimination have higher levels of suicidality and depression. Similarly, in a
series of studies on YEH, an association was found between homelessness stigma and higher
13
levels of suicidal ideation, depressive symptoms, and loneliness (Kidd, 2004, 2006). Milburn
and colleagues (2006) found that sexual minority YEH reported higher rates of discrimination.
Discrimination due to race/ethnicity, sexual orientation, gender identity and/or
homelessness, is thought to be particularly deleterious to emerging housed adults (Hurd, Varner,
Caldwell, & Zimmerman, 2014; Neblett, Donte, & Banks Hudson, 2016). Experiences of
discrimination can pose significant challenges to MM-YEH’ mental health during this process
(Thoma & Huebner, 2013), when young people might be exploring their intersecting minority
identities for the first time (Morgan, 2013). In addition, YEH transitioning into adulthood may be
more susceptible to discriminatory experiences given that they are tasked with adult
responsibilities, such as, applying for jobs, securing housing or health services, which often
occur via drop-in centers. In addition, discriminatory experiences may be particularly salient and
detrimental to a youth’s sense of self during emerging adulthood (Benner & Graham, 2014),
given that this stage is marked by self-exploration and identity exploration (Arnett, 2000;
Erikson, 1968). These risks are compounded by the fact that the onset for several mental health
disorders often present themselves before the age of 25 (Kessler et al., 2005) with research
suggesting that up to 50% of YEH meet criteria for a psychiatric disorder, such as PTSD,
depression, or anxiety (Edidin et al., 2012). The presence of mental illness setbacks during this
period can contribute to negative consequences in housing attainment and stability (Kidd et al.,
2016; Slesnik et al., 2017), occupational and educational attainment (Ferguson, 2013), as well as
increased risk for chronic homelessness (Edidin, 2012; Farrell, 2012).
Discrimination is particularly treacherous as it can lead to a lack of trust in others who
may fully understand, minimize or invalidate the experience (Harrel, 2000; Clement et al., 2015).
The risk may be especially consequential for YEH given that their primary adult source of
14
support are often service providers relied upon to gain access to basic needs and yet who may
simultaneously be perpetrators of discrimination. MM-YEH may be particularly vulnerable to
experiencing discrimination by health care providers. Geber (1997) found that racial/ethnic YEH
reported barriers to health care service utilization based on racial/ethnic discrimination with the
fear of racism and racist behaviors by health care workers was a major disincentive to seek
services. Unfortunately, research on racial/ethnic minority YEH barriers to health care service
use continues to be limited, the findings from the Geber study (1997) implicate a need to not
only further explore these mental health service barriers for racial/ethnic YEH, but to do so with
MM-YEH given the heterogeneity of this population. Although researchers have become
increasingly interested in how discrimination impacts YEH mental health symptoms and access
to care (Slesnik & Brakenhoff, 2017; Milburn et al., 2009; Gattis, 2013), we continue to lack
clarity regarding the prevalence of discrimination amongst YEH. The complexities in the
literature highlight the need for an intersectional approach that allows for a more thorough
examination of these patterns and for more nuanced theorizing of the interactions
Intersectionality
The roots of Intersectionality theory are drawn from the writings of Black feminists who
challenged the notion of a universal gendered experience and argued that Black women’s
experiences were also shaped by race and class (Crenshaw, 1990; Collins, 1990; Davis, 1981).
Contrary to articulating gender, race, and class as distinct social categories, intersectionality
postulates that these systems of oppression are mutually constituted and work together to
produce inequality (Cole, 2009; Collins, 1990; Crenshaw, 1990; Schulz & Mullings, 2006). As
such, analyses that focus on gender, race, or class independently are insufficient because these
social positions are experienced simultaneously. Intersectionality proposes that the convergence
15
of oppressed identities, such as race, sexual orientation, gender, creates unique experiences that
traditional theories fail to accurately explain.
Therefore, it is assumed that the identities of race, sexual orientation and homelessness
status are immutable, inseparable traits, meaning that MM-YEH do not just identify as Black or
lesbian or non-cisgender for example, but instead see themselves as Black, lesbian, non-
cisgender identifying YEH. Their identities as an individual are not categorized solely on the
basis on race, gender, or sexual preference, but instead is a collection of all those identities.
Intersectionality as a framework can be used to analyze the experiences of discrimination faced
by individuals with multiple minority identities that simply cannot be addressed by a single-axis
approach (Crenshaw, 1990; Collins, 2009). Incorporating an Intersectional framework will not
only provide clarity on the prevalence of MM-YEH’s discriminatory experiences but also allow
for a thorough investigation of its potential association with positive adult support and mental
health service use. As such, it is imperative to examine discriminatory experiences of YEH
identifying with various and multiple race/ethnicity, sexual orientation, gender identities, who
are more likely at risk and the types of service and community settings more prone to exhibit
discrimination.
For the purposes of this study, we will operate on three common assumptions shared by
intersectionality scholars (Crenshaw, 1990; Collins, 2000; Cho, Crenshaw and McCall, 2013):
(1) a recognition that all YEH are characterized simultaneously by multiple social categories,
including but not limited to: race, gender, and sexual orientation, and that these multiple social
categories are interconnected, such that the experiences of such that the experience of each social
category is linked to the other categories. (2) Embedded within each of these socially constructed
categories lies a dimension of inequity, and the recognition that this inequity is essential in
16
intersectional analysis. (3) These categories are characteristics of the social context experienced
by those YEH. In other words, the social structures, institutions, and interpersonal interactions
construct the categories and enforce the power inequities and as such, these categories and their
significance may be unique, fluid and dynamic. This last assumption is particular important
given that one of the main foci is centered on examining the association MM-YEH experiences
across a range of health and community service settings.
MM-YEH may experience unique discriminatory barriers to receiving adequate mental
health services that other non-marginalized YEH do not face (Moore, Camacho, & Munson,
2020). The research is scarce in regard to MM-YEH’ experiences of discrimination; however, we
can gain some insight from the extensive literature documenting the specific discriminatory
barriers that sexual minority YEH and racial/ethnic minority adults experiencing homelessness
(AEH). For example, sexual minority YEH reported discrimination based on gay, lesbian or
bisexual status more frequently than their heterosexual YEH counterparts (Milburn et al., 2006;
Milburn et al., 2009; Gattis et al., 2013). Racial/ethnic minority-AEH also have a history of
mistreatment and continuously experience discrimination, particularly in accessing and utilizing
health services, based on their race (Skosireva et al., 2014; Zerger et al., 2014; Wen, Hudak, &
Hwang, 2007). In addition, there is ample literature demonstrating that marginalized and
multiple marginalized housed youth disproportionately experience discrimination more
frequently than their White, heterosexual, housed counterparts (Seaton et al., 2008; Assari &
Caldwell, 2018; Seaton et al., 2013; Almeida et al., 2009; Raifman, 2018).
MM-YEH may face emotional tasks that non-MM YEH youth do not face. They may
wrestle with: (1) developing and defining both a sexual minority identity and a racial/ethnic
identity; (2) potential conflicts in allegiance within their sexual minority and/or racial/ethnic
17
community; and (3) experiencing both homophobic and race-related discrimination. Thus, it is
hypothesized that MM-YEH and in particular, Black, sexual minority and gender minority
identifying YEH may be experiencing unique, undue discriminatory barriers and emotional
distress when compared to White, heterosexual, cisgender YEH because they may be subjected
to particular forms of discrimination and hardship. Dealing with multiple layers of oppression
may likely complicate social relations, with adults and systems. The social stressors faced by
racial minority, sexual and gender minority identifying YEH brave every day are exacerbated by
the constant perilous state of homelessness. Incorporating an Intersectional framework will
provide clarity on the prevalence of MM-YEH’ discriminatory experiences and its potential
association with positive adult support and mental health service use. Intersectionality theory
challenges us to consider discrimination amongst YEH not in terms of single factors (eg, gender
or race), but in terms of multiple, interacting factors. Intersectionality is also a lens through
which one can examine and critique social interactions and drop-in center and mental health
service use.
The Risk Amplification and Abatement Model
In order to identify interventions that could mitigate negative mental health outcomes for
YEH, researchers have moved away from traditional deficit-based frameworks to focus more on
identifying protective factors that may buffer against poor health outcomes (Milburn et al., 2008;
Rice, Stein, & Milburn, 2008; Kidd & Shahar, 2008). One particular focus is in the area of social
support (Rice, Stein, & Milburn, 2008; Barman-Adhikari, et al., 2016; McCay et al., 2011).
Although some studies have utilized a social network framework to investigate service use
patterns among YEH (Barman-Adhikari & Rice, 2014; Barman-Adhikari et al., 2016; Kolzoff et
al., 2013), a majority of this research has solely investigated the mechanisms through which
18
social networks and social supports, particularly family and peer-based support, have both
positive and negative effects on physical and mental health outcomes (Rice, Milburn, & Monro,
2011; Wenzel et a., 2010). There has been some promising findings among the adult
experiencing homelessness (AEH) population. Hatton (2001) found that health care use was
facilitated when AEH had service providers in their social networks. In order to reduce the gap
between need and healthcare service access for MM-YEH, it is critical to understand how adult
social support may potentially influence service use for this group.
The Risk Amplification and Abatement Model (Milburn et al., 2009) builds on the Risk
Amplification Model (Whitbeck, Hoyt, & Yoder, 1999) and posits that contact with positive
social supports including supportive family members, prosocial peers, and early contact with
social services can alleviate risk behaviors associated with continued homelessness (Milburn et
al., 2009). Grounded in a socio-ecological perspective, the RAAM model suggests that dynamics
occurring at a interpersonal level, e.g., formal and informal adult relationships are linked to
levels of higher social services, e.g., mental health services. RAAM contends that YEH
encounter both positive and negative contact with socializing agents at four levels of social
organization: family, peers, social services and formal institutions (Milburn et al., 2009). A
RAAM framework, with its emphasis on the positive and negative socializing influences of YEH
within the family, peer, social service and institutional environment, may be useful in
conceptualizing and examining the potential similarities and differences between MM-YEH and
their White, heterosexual, cisgender identifying counterparts in relation to positive adult supports
and mental health services.
Research on other high risk adolescent populations, aside from youth experiencing
homelessness, has repeatedly demonstrated that engagement with positive adults, be they formal
19
supports or informal supports can do much to improve youth outcomes (Gavin, Catalano, &
Markham, 2010; Richman, Rosenfeld, & Bowen 1998). YEH social network studies have found
that these youth have heterogenous networks comprising of both formal and informal sources of
social supports, including non-parental adults (Rice, 2010; Wenzel et al., 2012; De la Haye et al.,
2012). Non-parental adults as potential sources of positive support may be a promising source of
intervention. However, we currently have limited understanding regarding non-parental adult
support as a potential source of support in health care access and utilization for YEH. One study,
found that YEH who received emotional support from adult staff were more likely to engage in
health, behavioral health, and shelter services (Barman-Adhikari et al., 2016). However, there
still is a lack of understanding of how adult supports may influence health service use for MM-
YEH.
The findings from the Barman-Adhikari et al., study (2016) are promising and suggest
that staff and non-staff adult relationships may promote health service engagement for YEH.
Thus far, much of the work driven by this perspective has demonstrated that positive behavioral
health outcomes are positively associated with family member or home-based peer engagement
(i.e. informal supports) (Milburn et al., 2009). The potential positive role of social service
providers (i.e. staff supports) and non-parental adult support (i.e., non-staff support) has been
acknowledged in this work, but rarely empirically investigated (Milburn et al., 2009; Rice,
Milburn, & Monro, 2011) and to our knowledge, has never been studied among MM-YEH .
Despite the growing interest in understanding racial/ethnic, sexual and gender minority
differences in YEH, gaps in knowledge still remain. It is unknown how MM-YEH compare to
their White, heterosexual, cisgender counterparts regarding informal and formal adult
relationships and use of mental health services. Although RAAM has served to move the field
20
for YEH forward with its emphasis on protective factors that can mitigate the negative stressors
and traumatic experiences that arise from YEH interactions with these systems, it has not
accounted for the potential differences and similarities MM-YEH in supportive adult
relationships and mental health service use.
An Intersectional-based RAAM Framework
Many YEH occupy multiple marginalized identities and thus are subject to multiple
forms of discrimination that may shape their likelihood of engaging with adults and mental
health services. Thus, the purpose of this dissertation is to expand upon the existing RAAM
model by utilizing an intersectional-based RAAM framework that will help to 1) identify
potential disparities in discriminatory experiences for marginalized YEH and 2) allow for a
deeper understanding as to why and how discrimination may contribute to unique and
complicated socialization process for MM-YEH in regard to forming adult relationships and
utilizing mental health services. For example, although it is hypothesized that MM-YEH may
experience discrimination at greater frequency, this may not necessarily negatively influence
their engagement with formal adults or mental health services. An intersectional-based RAAM
framework emphasizes the need to attend to the complex and compounding ways that YEH with
multiple marginalized identities interact with adults and systems, e.g., mental health services.
MM-YEH, in the face of previous and current discriminatory exposure, may have had to learn to
adapt in order to continue getting their needs met.
Focusing on MM-YEH, this dissertation will build upon the Risk Amplification and
Abatement Model (RAAM) (Milburn et al., 2006) to incorporate an Intersectionality lens
(Crenshaw, 1990) in an effort to understand the specific and varied discriminatory experiences
MM-YEH face and its association with social support and mental health service use. Elucidating
21
a deeper understanding of YEH’ discriminatory experiences will offer a path toward culturally
tailored interventions to address the impact of discrimination and enhance social support and
mental health service use for this population. This dissertation contends to use an intersectional
approach to understand the varied risk amplification and abatement processes for MM-YEH with
adult support networks and mental health service utilization.
To this end, we describe potential challenges and opportunities that arise when
incorporating an intersectional-based RAAM framework to better understand MM-YEH. Some
scholars have argued that qualitative methods are more compatible with intersectional
approaches than are quantitative methods (Bowleg, 2008; Syed, 2010). The application of
intersectional approaches using quantitative methods has been increasingly recognized in some
related disciplines, including sociology (Choo & Feree, 2010), gender studies (Spierings, 2012),
and family studies (Few-Demo, 2014) as well as in social work (Sterzing et al., 2017). One
common challenge to using an intersectional approach with quantitative research is additive
analytic approaches which consider social identities, e.g., race/ethnicity, gender, sexual
orientation, etc. as entirely independent, distinct and mutually exclusive and thus, antithetical to
the assumptions of intersectionality.
This dissertation recognizes this critique and will address it by using both additive
effects, to isolate the meaning and importance of each social category (e.g., main effects) and
multiplicative effects (e.g., interaction effects). Collins (2000) acknowledged the possibility of
additive effects and described how, “on certain dimensions Black women may more closely
resemble Black men; on others, White women, and on still others, Black women may stand apart
from both groups. Additive approaches alone may promote a ranking of oppressions. Using a
quantitative intersectional approach to explore MM-YEH, will include an examination and
22
comparison of additive and multiplicative effects. YEH social categories will be analyzed
separately such that for example, race/ethnicity may be construed as having effects that can be
partitioned statistically from the effects of sexual orientation and that such effects could be
additive. For example, a Black, sexual minority YEH, then could experience discrimination
based on racism as well as heterosexism in an additive manner as demonstrated through an
independent main effects analysis. The effects of multiple group memberships will also include
interaction effects to examine a potential multiplicative impact, such that the effects of
discrimination based on race might exacerbate the effects of discrimination based on
heterosexism. This approach is consistent with Bowleg (2008) and Shields (2008), who each
advocated for a “both/and” strategy to intersectional approaches.
This intersectional approach comprised of both additive and multiplicative effects will
foster a deeper understanding of the nuanced ways in which YEH social categories are
systematically interlocked and linked to power and oppression. Incorporating an intersectional-
lens to quantitative YEH data will ultimately promote implication for future intersectional-based
critical empirical research and foster a change in the mainstream of research on YEH, giving a
greater voice to those youth who lie at the margins of society. Moreover, future work that
engages both quantitative and qualitative methods, will extend a further reach and platform for
MM-YEH.
The pillars of the RAAM framework that expand beyond interpersonal relations and
explicitly account for the relationships have with institutions and social services is ripe for this
intersectional analysis. It has been suggested that intersectional-based research should aim to
understand how power, privilege and oppression are embedded in social categories and may vary
across social locations (Cole, 2009). As such, this study will examine MM-YEH discriminatory
23
experience across several social locations, e.g., law enforcement, drop-in centers, health services
(including medical, mental health, substance use treatment, and HIV/STI treatment services),
employer, businesses, and in community. The incorporation of these social structures will
provide more clarity on how privilege and power, particularly in institutions and service settings,
influence disadvantage and oppression for MM-YEH and offer insight into which specific MM-
YEH may be in need of more directed support. Figure 1.1 presents a conceptual model for an
Intersectional-based RAAM framework.
24
Figure 1.1
An Intersectional-Based RAAM Framework for Youth Experiencing Homelessness
Population Characteristics
Demographic
Profile
Race/Ethnicity
Sexual
Orientation
Gender
Homelessness
Characteristics
Duration
Positive
Staff
Support
Perceived
Discrimination
Mental Health
Service
Utilization
Drop-in Center
Attendance
Chapter 3 Chapter 4
Chapter 4 Chapter 2
Chapter 3
25
Chapter 2: Prevalence of Discrimination Among Youth Experiencing Homelessness
Youth who identify with minority and multiple minority status make up a substantial and
disproportionate portion (particularly in the case of Black, sexual minority, and gender non-
conforming youth) of the population experiencing homelessness and yet little is known about
their perceived discriminatory experiences across settings fundamental to their health and
housing stability. For the purpose of this dissertation, perceived discriminatory experiences can
be understood as a behavioral manifestation of a negative attitude, judgment, or unfair treatment
based on groups membership (Pascoe & Smart Richman, 2009). Morton et al. (2018) estimated
that Black youth have an 83% heightened risk of homelessness and LGBTQ youth have a 120%
heightened risk. Morton et al. (2018) further asserts that Black or multiracial LGBTQ youth have
the highest prevalence of homelessness, with one in four LGBTQ young adults of color having
reported homelessness in the previous 12 months (Morton et al., 2018). The negative impact of
discrimination on health has been documented extensively (Banks, Kohn-Wood, & Spender,
2006; Klonoff, Landrine, & Campbell, 2000; Mays, Cochran & Barnes, 2007; Pascoe & Smart
Richman, 2009; Williams & Mohammed, 2009). Specifically, discrimination has been well
established as a key factor contributing to minority health disparities (Williams and Mohammed,
2013; Williams and Mohammed, 2009; Colen, Ramey, Cooksey, & Williams, 2018).
It is especially critical to understand the prevalence rates of discrimination for YEH given
that they over represent the very marginalized social identities often the target of discrimination
(Pedersen, Tucker, & Kovalchik, 2016, Hudson et al., 2010). As such, marginalized and multiple
marginalized youth experiencing homelessness (MM-YEH) are vulnerable to less desirable
treatment in systems they depend on for services necessary to their health and well-being
(Milburn et al., 2006; Slesnick, Zhang, & Brakenhoff, 2017). This study will incorporate an
26
Intersectional lens RAAM framework to identify and understand perceived discrimination
prevalence of youth experiencing homelessness, including: which sub-groups are most at risk
and types of service and community systems, e.g., law enforcement, drop-in centers, health and
behavioral services, employer and community, perceived as discriminatory. It is hypothesized
that YEH who carry marginalized and multiple marginalized identities will have different and
unique discriminatory experiences when engaging with various systems: law enforcement, drop-
in centers, health services, employers, small businesses, and the community – than their non-
marginalized unhoused counterparts.
Discrimination and Other Related Populations
The literature is still sparse in regard to discriminatory experiences among YEH (Milburn
et al., 2006, 2010; Gattis & Larson, 2016), but we can look toward adults experiencing
homelessness (AEH) to understand the gravity of the matter and the seriousness of the
consequences. A growing body of research has increasingly focused on the pervasive role of
discrimination in the lives of AEH. AEH report regularly facing discrimination in a variety of
settings including: private businesses, law enforcement, medical services, social services, and
society as a whole (Wen, Hudan, & Hwang, 2007; Writing et al., 2019). Moreover, Lynch and
Stagoll (2002) found that discrimination is especially pronounced in the area of housing and
health service access, thus adding an additional barrier to a group disproportionately at risk and
in dire need of these services. Writing et al., (2019) found that Black AEH were more likely to
report discriminatory experiences due to race compared to their White unhoused adult peers.
This study also identified that AEH experienced discrimination while interacting with various
systems with the most commonly reported perceived discrimination experiences being attributed
27
to law enforcement, employer based settings, and higher education institutions (Writing et al.,
2019).
Other research confirms that experiences with discrimination for AEH reduces trust in
service providers and treatment compliance (Boulware et al., 2003; Cuffee et al., 2013; Mohseni
& Lindstrom, € 2008). Additionally, there is a well-established link between experiences with
stigmatization and discrimination and a host of negative emotional, physical and behavioral
outcomes (Brondolo et al., 2009; Clark et al., 1999; Nadal et al., 2014). Persistent discrimination
is associated with fewer group memberships and subsequent lesser well-being (Johnstone et al.,
2015), physiological stress responses (McEwen, 2004), which contribute to behavioral health
consequences, such as depressive and anxiety symptoms (Banks et al., 2006), high blood
pressure and hypertension (Clark & Gotchett, 2006; Davis et al., 2010), homelessness (Skosireva
et al., 2014), and early mortality (Williams et al., 2003; Krieger et al., 1999).
Given that both minority and multiple marginalized housed youth, defined as youth who
have stable housing, report more discriminatory experiences in comparison to non-minority
housed youth (Scott & House, 2005; Hurd et al., 2014; Livingston et al., 2017) and minority and
multiple minority adults experiencing homelessness report more discriminatory experiences than
their White, heterosexual homeless peers (Bogart et al., 2011; Writing et al., 2013; Zerger et al.,
2014 ), it is imperative to gain a better understanding of the prevalence of discrimination by
various YEH sub-groups.
Discrimination and Youth Experiencing Homelessness
Although research on the discriminatory experiences of YEH is especially scarce,
Milburn et al., (2006) found that YEH that were new to homelessness, particularly those who
identify as Lesbian, Gay, Bisexual and transgender (LGBT), experience discrimination in the
28
form of harassment from peers, family, or police. Sexual minority youth experiencing
homelessness may face discrimination when seeking needed services, and programs specifically
designed for this population are often lacking (Durso & Gates, 2012, Abramovich, 2016). In
addition, Gattis and Larson (2016) reported that Black YEH (ages 16–24) regularly experience
discrimination based on their race, homeless status, and sexual identity. Gattis and Larson (2016)
also found that depressive symptoms and suicidality are prevalent among Black YEH and that
depressive symptoms are particularly associated with racial discrimination and indicators of
homelessness. These findings shed light on the need to account for race and other minority
identities when investigating how discriminatory experiences may vary across YEH subgroups.
Service access and acquisition are often complex and sometimes dangerous for
transgender and gender expansive young people. This community frequently experiences stigma
and discrimination and face systemic barriers including sex segregated programs and
institutional practices that deny their own understanding and articulation of their gender. Recent
attention has been drawn to the overrepresentation of transgender and non-cisgender young
people within the population of youth experiencing homelessness, as well as the issue of
homelessness among transgender and non-cisgender people in general (Quintana et al., 2010;
Yu, 2010; Bolas, 2007; Ray, 2006; Mottet & Ohle, 2006; Xavier, 2000). Transgender and non-
cisgender youth are often forced to live outside of mainstream society, due to prejudice and
discrimination in employment, housing, health care, and education. Though the literature
suggests that transgender and non-cisgender young people are disproportionately represented in
the population of unstably housed young people (Whitbeck et al., 2014; Bolas, 2007), little is
known about their specific experiences, challenges, and needs accessing housing related services
and supports.
29
Serious Consequences of Discrimination
Although the literature focused on YEH discrimination remains sparse, the current
findings present a strong case that discrimination is both a real and serious problem and its
associated consequences are detrimental to both the service access and health of YEH. Drop-in
centers are often an initial entry point to vital resources for YEH, which places drop-in center
staff in the unique position to facilitate YEH’ knowledge of and linkage to formal services to
meet their health and behavioral health needs. These centers are typically funded by private
donations, charitable organizations, and federal and state grants to fund staff and resources
(Slesnick et al.,2008; Pedersen, Tucker, & Kaolvachik, 2016). Drop-in centers typically try to
break down barriers and take a “come as you are” approach to engaging youth in services
(Slesnick et al., 2008). As such, drop-in center staff serve as an invaluable conduit in connecting
YEH to health, economic, and housing stability.
Identifying which YEH subgroups are more prone to experience discrimination in drop-in
centers could help address drop-in provider bias and thus enhance access to drop-in access
services for YEH sub-groups. Perceived discrimination is shown to have a negative impact on
help seeking, access to care, poverty, and social marginalization (Thornicroft et al., 2007).
Within healthcare settings, discrimination by healthcare providers can function as a key barrier to
obtaining needed services, resulting in avoidance or delays in treatment seeking, under-diagnosis
and mistreatment, non-adherence with or discontinuation of treatment, and poor treatment
outcomes (Martins, 2008; Wen, Hudak, & Hwang, 2007; Thornicroft, Rose, & Kassam, 2007).
To our knowledge, no study has yet to account for the prevalence of discrimination
among YEH who identify with intersecting identities. Discrimination, whether it be on the basis
of race, gender, and/or sexual orientation, is thought to be harmful to emerging adults (Hurd,
30
Varner, Caldwell, & Zimmerman, 2014; Neblett, Donte, & Banks Hudson, 2016). Individuals in
this age range may experience discrimination in greater frequency than at earlier ages when they
apply for jobs for the first time or, in the case of homeless youth, attempt to secure benefits such
as financial and housing support without the support of their family or a caseworker.
An Intersectional-Based RAAM Framework
The Risk Amplification and Abatement Model (RAAM), with its emphasis on both the
positive and negative socializing influences of YEH within the family, peer, social service and
institutional environment, will be useful in conceptualizing and examining discrimination across
social service and institutional settings (Milburn et al., 2009) Yet, RAAM does not explore
which YEH sub-groups are experiencing greater positive or negative contact with social services
and formal institutions. An Intersectional-based RAAM framework advocates studying the
mutual and simultaneous construction of various YEH social categories, such as race, class,
gender and sexual orientation in order to identify the unique patterns of discriminatory
experiences that might stem from the various intersections of YEH social identities and contact
with RAAM’s four levels of social organization: family, peers, social services and formal
institutions. This is consistent with an intersectionality approach, which examines the ways in
which various socially constructed categories interact on multiple levels that result in perceptions
of unequal treatment (Andersen & Collins, 2009).
A primary assumption of the intersectional approach is that specific types of
discrimination are related such that discrimination may be based on the “intersection” of multiple
social categories such as race, ethnicity and gender (Andersen & Collins, 2009). Examining
differences in perceived discrimination based on race or sexual orientation or gender alone is
insufficient. More specifically, an Intersectional RAAM framework can address whether there
31
are subgroups of Black youth for whom perceived discrimination is more harmful.
Unfortunately, there persists a substantial gap in the current literature that explores the
intersectionality of race/ethnicity, sexual orientation and gender identities among YEH.
Narrowing this gap is essential to protect marginalized YEH subgroups and promote better
outcomes, given the growing research showing that discrimination is negatively linked to health
(Williams & Mohammed, 2009).
Current Study
MM-YEH may be simultaneously contending with unique discriminatory experiences
that may contribute to difficulty in accessing and utilizing services. To our knowledge no prior
study has examined the prevalence of multiple discriminatory structural settings among MM-
YEH sub groups. The present cross-sectional study will use an Intersectional-based Risk
Amplification and Abatement framework, to explore the prevalence of discrimination across the
following service and community settings: law enforcement, drop-in centers, health services,
employer, businesses, and community for various intersecting YEH sub-groups. Expanding the
RAAM model to include an Intersectional lens will allow for a more in-depth focus of the
interconnected role of race/ethnicity, sexual orientation and gender, that may show a more
complex side of discrimination and how it potentially shapes the adults and systems that these
youth come in contact with. Relying upon Intersectionality and RAAM key domains, we will
meet this goal by completing the following specific aims:
1. To identify and understand perceived discrimination prevalence of intersecting youth
experiencing homelessness, including: which sub-groups are most at risk and types of
service and community settings, e.g., law enforcement, drop-in centers, health and
behavioral services, employer and community, perceived as discriminatory.
32
2. To identify and understand the main reason for perceived discrimination among YEH
intersecting sub-groups.
Methods
Sample
Data was derived from a longitudinal social network study of youth experiencing
homelessness utilizing drop-in centers in Los Angeles, CA. A sample of 418 youth ages 16-24
were surveyed between June 2018 and February 2019. Participants were recruited from 3 drop-in
centers servicing YEH across 4 different waves at each of the centers. A total of 198 participants
recruited from the 3 drop-in centers from the third wave of this study comprised the analytical
sample for this study. The refusal rate for the study was 5.8%. Two of the centers are located in
area in Los Angeles County in which many YEH are concentrated (Rabinovitz, Desai, Schneir,
& Clark, 2010). In comparison, the third recruitment site is located in Venice, a location that has
increasingly become an area where youth congregate but does not have access to the array of
services in Hollywood (Brooks et al., 2004). Each wave of data occurred approximately 6
months apart. All youth accessing services at the recruitment sites during the periods of data
collection were invited to participate in the study. All three drop-in centers structure operates
such that any youth who self-identifies as homeless, e.g., sleeping on the streets, in an emergency
shelter, couch surfing, or at immediate risk of being homeless) and is between the ages of 16-24
is deemed eligible for services. Youth were invited to participate in multiple waves, but only the
fourth wave survey data was used in the current study. The fourth wave was the only wave that
included measures for discrimination. As such, it was the only wave used in the data.
33
Procedures
Recruitment was conducted for 14 days at each site during Wave 3 of data collection (3
months after baseline data was collected). During these periods, recruiters were present at the
agency to approach you for the duration of service provision hours. A consistent set of two
research staff members at each site were responsible for recruitment, in order to prevent youth
from completing the survey multiple times within each data collection period. Signed voluntary
consent was obtained from youth 18 years of age and older and informed assent was obtained
from youth 16-17 years old. The Institutional Review Board at the University waived parental
consent, as YEH under 18 years old are considered unaccompanied minors who may not have a
parent or adult guardian from whom to consent. The 60-minute survey was a computer
administered self-interview, completed at the site. Participants received $25 in gift cards as a
compensation for their time. The Institutional Review Board approved all survey items and
procedures.
Measures
Gender, Racial Identity, and Sexual Orientation
Gender identity and race/ethnicity questions allowed students to mark more than one
category. For the present study, gender identity was recategorized into: 1) Male (if a student
marked only “male”), 2) Female (if a participant marked only “female”), and 3) Non-cisgender
(if a participant marked “trans male/trans man”, “trans female/ trans woman”, “Gender
queer/Gender non-conforming” or “Different identity” in which the written response was
indicative of non-cisgender and as such this category was also included in the third category:
“Non-cisgender”) (Srivestava et al., 2019).
34
The sexual orientation item, which limited participants to one response among the
following categories: 1) Gay or Lesbian, 2) Bisexual, 3) Heterosexual or Straight, 4) Questioning
or Unsure, 5) Asexual, or 6) Another Sexual Orientation. Sexual orientation was re-coded into:
1) heterosexual (if a participant marked “heterosexual”) and 2) LGBQ (if a participant marked
any response other than “heterosexual”), to maintain consistency with previous studies (e.g.,
Rice et al., Milburn et al., ). Participants were given several race/ethnicity options and instructed
to “pick the one that describes you best”. Race was re-coded into: 1) Black (if a participant
identified as Black), 2) White (if a participant identified as White), 3) Latinx (if a participant
identified as Latinx) and 4) Other Race(if marked American Indian or Alaska Native, or Asian,
or Mixed Race as a category). Of note, White Non-Hispanic was not a response option and thus,
there was no overlap of Latinx and White. Finally, intersecting stigmatized identities was
operationalized as two or more stigmatized identities across gender (i.e., cisgender girl, gender
expansive), race (i.e., youth of Color), and sexual orientation (i.e., LGBQ).
Intersecting identities were created by the incorporation of interaction terms. The
following variables were recoded: race/ethnicity, gender, and sexual orientation into the
following: race x sexual orientation, race x gender, and gender x sexual orientation. Lastly, an
intersectional variable that accounts for three social identities: race/ethnicity, gender and sexual
orientation was created into the following: race x gender x sexual orientation to explore the main
reason for discrimination.
Other Socio-Demographic Variables
Current housing status for the sample was recoded as: literal homelessness (youth
experiencing literal homelessness were defined as those who indicated that they were currently
staying in a shelter (emergency or temporary), hotel, motel, trailer, street, beach, tent or
35
campsite, abandoned building, car or bus vs. youth living with biological family, foster family,
relative, friend, group home, sober living facility, transitional living program). Foster care
involvement was assessed with dichotomous responses. Age was collected as a continuous
variable and dichotomized for analysis using the mean age (22.1) to determine the categories.
Discrimination Variables
Participant’s perceived provider discriminatory experiences was measured using the
Everyday Discrimination scale (EDS) which has been widely used in studies of discrimination
and health (Williams et al. 1997; Deitch et al. 2003). The EDS was developed as a subjective
measure to capture self-reported frequency of routine, relatively subtle discriminatory
experiences in everyday social situations. The EDS has been found to be strongly associated with
institutional and interpersonal discrimination (Hughes 2003; Krieger et al. 2005) and is accepted
as a valid measure that accounts for discriminatory experiences among youth and adults who
identify with minority status (Seaton et al. 2008; Goosby et al., 2015; ). First, participants are
asked: “Can you tell me if any of the following ever happen to you?” The original scale consists
of 11 items assessing the frequency of participants’ experiences of everyday discrimination. For
the purposes of Aim 1 and based on prior studies modification for use in health care settings
(Bird et al., 2009; Peek et al., 2011), a methodological decision was made to slightly modify the
EDS to focus on 6 types of everyday discrimination experiences pertinent to YEH. This included
YEH experiencing discrimination in law enforcement, drop-in centers, health services (including
medical, mental health, substance use treatment, and HIV/STI treatment services), employer,
businesses, and in community settings. The slight modification occurred with the change of:
‘people’ to ‘staff’ for the drop-in center and health service variable and ‘people’ to ‘police’ for
the law enforcement variable, and ‘people’ to ‘employer’ for the employer variable – to better
36
reflect the setting . Examples include: “ People act as if they think you are not smart”, “People
act as if they are afraid of you” to “Staff act as if they think you are not smart” and “Staff act as
if they are afraid of you”.
Situation-based coding, a common approaches to coding the EDS (Schulz et al., 2006;
Lewis et al., 2009; Moody et al., 2006), will be used for this study. In situation-based coding,
each survey item is dichotomized: ‘never’ = 0 and ‘ever’ = 1. Situation-based category coding
collapses everyone who experience any discrimination into one category. Responses are summed
across the items to generate a score ranging from 0-6, capturing the number of different
situations ever experienced. For this study, we will dichotomize each EDS item to ‘never’=0 and
‘ever’=1. Items will be summed (range: 0-10) to reflect the total number of discriminatory
situations ‘ever’ experienced per type: law enforcement, drop-in center, health service, employer,
business, and community. In addition, items across all 6 types of settings will be summed range:
0-60) to reflect the total number of situations ‘ever’ experienced across all settings. The
Everyday Discrimination Scale has demonstrated good reliability and validity (Taylor, Kamarck,
& Shiffman, 2004; Williams et al., 2012; Williams, Neighbors, & Jackson, 2003). In sample of
LGBT participants, Cronbach’s alpha for the discrimination scale was 0.94, and discrimination
scores were correlated positively with depressive symptoms, anxiety, and substance use
(Gamarel, Reisner, Laurenceau, Nemoto, & Operario, 2014; Gamarel, Reisner, Parsons, &
Golub, 2012; Gordon & Meyer, 2008; S. L. Reisner, White, Bradford, & Mimiaga, 2014). Main
reason for discrimination will be captured by asking respondents a follow-up question to
determine the main reason for their perceived discriminatory experiences. The stem question is:
“What do you think the main reason for these experiences?” Respondents were asked to select
37
one of the following reasons: gender, race, sexual orientation, age, religion, education or income
level, prior involvement with police, prior involvement with foster care, or other.
Data Analysis
The descriptive and multivariate analysis for this paper was generated using SAS version
9.4. For this study, a descriptive and bi-variate analysis of perceived discrimination by type, e.g.,
law enforcement, drop-in center, health service, employer, business, and community was run to
examine prevalence in YEH. Cross-tabs and chi-squares were generated to compare the
distributions of covariates between the following discrimination settings: law enforcement, drop-
in center, health service, employer, business, and community and the following main effects:
race/ethnicity (Black, White, Latinx, and Mixed/Other), sexual orientation (Heterosexual, Non-
Heterosexual), and gender (Male, Female, Non-Cisgender). All statistical levels of significance
at P≤0.05 were considered significant. Next, we used a Chi-square test to compare the
distribution of covariates between the four intersecting interaction effects: race x sexual
orientation, race x gender, and gender x sexual orientation by the same discrimination settings:
law enforcement, drop-in center, health service, employer, business, and community.
Furthermore, cross-tabs and group comparisons using chi-squares were generated to examine the
main reason identified for perceived discrimination, e.g., gender, race, sexual orientation, age,
religion, education or income level, prior involvement with police, prior involvement with foster
care, or other by main effects: racial/ethnicity (Black, White, Latinx, and Mixed/Other), sexual
orientation (Heterosexual/Non-Heterosexual, and gender (Male, Female, Non-Cisgender) as well
as by intersecting interaction effects: race x sexual orientation, race x gender, and gender x
sexual orientation. Ps≤.05 were considered significant. Given that this is an exploratory study
38
with an understudied population, it was decided to not handle missing data with techniques such
as imputation. Instead, the missing data was simply reported.
Results
A summary of the demographic characteristics for the current sample is presented in
Table 1. The sample is heterogeneous with minority identities representing a large proportion of
the sample. Specifically, the modal of youth identify as Black (N = 73, 37.06 %) and LGBT (N =
105, 70.48%). A substantial proportion of the sample identify as Non-Cisgender (N = 29,
14.66%). The average age for the sample is 22.1 years old (SD = 2.1) with slightly over one-third
(35.8%) of the sample reporting their current housing situation as literally homeless. Lastly,
Table 2.1 presents frequencies for everyday discrimination reported by the entire non-intersected
YEH sample. First, most respondents (64.14%) indicated that they had experienced some form of
discrimination.
39
Table 2.1
Descriptive Statistics For Youth Experiencing Homelessness (n = 198)
Demographics n or M % or SD
Race/ethnicity (missing = 6)
Black 73 37.06
Latinx 21 10.66
Mixed 50 25.38
White 41 20.81
Other 12 6.09
Gender (missing = 6)
Female 45 22.73
Male 124 62.63
Non-cisgender 29 14.66
Sexual orientation (missing = 0)
LGB 105 53.03
Heterosexual 93 46.97
Age 22.1 2.1
Demographics N %
Current housing situation (missing = 22)
Literal homelessness 58 35.8
Unstable housing 118 67
No 71 35.86
Yes 127 64.14
Note. LGB = Lesbian, Gay, Bisexual
Table 2.2 presents the prevalence of MM-YEH subgroups (Gender x Race x Sexual
Orientation) in our sample. YEH identifying as Male, Black, and Heterosexual represent the
largest intersected subgroup (N = 26; 13.2%) followed by YEH identifying as Male, Other Race,
40
and Heterosexual (N = 25, 12.69%) and YEH identifying as Male, Other Race, and LGBQ (N =
21, 10.66%).
Table 2.2
Descriptive Statistics for Marginalized and Multiple Marginalized Youth Experiencing
Homelessness
Demographics N %
Male x Black x heterosexual 26 13.2
Male x White x heterosexual 12 6.09
Male x Latinx x heterosexual 8 4.06
Male x other x heterosexual 25 12.69
Female x Black x heterosexual 7 3.55
Female x White x heterosexual 7 3.55
Female x Latinx x heterosexual 1 0.51
Female x other x heterosexual 2 1.02
Other x Black x heterosexual 1 0.51
Other x White x heterosexual 2 1.02
Other x Latinx x heterosexual 2 1.02
Other x other x heterosexual 0 0
Male x Black x LGBQ 19 9.64
Male x White x LGBQ 6 3.05
Male x Latinx x LGBQ 7 3.55
Male x other x LGBQ 21 10.66
Female x Black x LGBQ 15 7.61
Female x White x LGBQ 5 2.54
Female x Latinx x LGBQ 3 1.52
Female x other x LGBQ 4 2.03
Other x Black x LGBQ 5 2.54
Other x White x LGBQ 9 4.57
Other x Latinx x LGBQ 2 1.02
Other x other x LGBQ 8 4.06
Note. LGBQ = Lesbian, Gay, Bisexual, Queer
41
Figure 2.1
Demographics on Marginalized and Multiple Marginalized Youth Experiencing Homelessness (n
= 198)
As shown in Table 2.3, among the YEH sample, significant differences were found when
comparing discriminatory experiences between heterosexual YEH and sexual minority YEH.
Specifically, LGBT YEH were significantly more likely to endorse discrimination with: law
enforcement staff (police) (70.48% vs. 56.99%, X
2
= 3.90, p < .05), drop-in center staff (41.9%
vs. 24.73%, X
2
= 6.49, p < .01), employers (44.76% vs. 24.73, X
2
= 8.66, p < .01), business staff
(51.43 vs. 32.26%, X
2
= 7.42, p < .01), and with the community (51.43% vs. 25%, X
2
= 12.39, p <
.001). As shown in Table 3., discrimination was not significantly related to race/ethnicity or
gender as a main effect.
0
5
10
15
20
25
30
Table 2. Demographics on Marginalized and Multiple Marginalized Youth Experiencing Homelessness
(MM-YEH) N=198 N
Table 2. Demographics on Marginalized and Multiple Marginalized Youth Experiencing Homelessness
(MM-YEH) N=198 %
42
Table 2.3
Prevalence of Discrimination Experiences Among Youth Experiencing Homelessness (n = 198)
Demographics
Law enforcement Drop-in center Health services
N % N % N %
Race/ethnicity
(missing = 6)
Black 51 69.86 22 30.14 21 28.77
Latinx 11 52.38 4 19.05 3 14.29
Mixed 31 62 21 42 19 38
White 27 65.85 18 43.9 15 36.59
Other 7 51.59 2 28.57 3 30.95
Gender (missing = 6)
Female 28 62.22 12 26.67 12 26.67
Male 82 66.13 41 33.06 39 31.45
Non-cisgender 17 58.62 14 48.28 10 34.48
Sexual orientation
(missing = 7)
LGB 105 70.48* 44 41.9** 35 33.33
Heterosexual 93 56.99 23 24.73 26 27.96
Foster care history
Yes 34 57.63 12 20.34 12 20.34
No 75 63.56 44 37.29 35 29.66
Demographics
Employer Businesses Community
N % N % N %
Race/Ethnicity
(missing = 6)
Black 31 42.47 32 43.84 31 42.47
Latinx 4 19.5 5 23.81 2 9.52
Mixed 18 36 23 46 24 48
White 14 34.15 21 51.22 17 41.46
Other 3 30.95 3 30.95 5 45.24
43
Demographics
Employer Businesses Community
N % N % N %
Gender (missing = 6)
Female
19 42.22 21 46.67 19 42.22
Male
43 34.68 49 39.52 46 37.1
Non-cisgender
8 27.59 14 48.28 14 48.28
Sexual orientation
(missing = 7)
LGB
47 44.76** 54 51.43** 54 51.43***
Heterosexual
23 24.73 30 32.26 25 26.88
Foster care history
Yes
14 23.73 17 28.81 18 30.51
No
43 36.44 51 43.22 46 38.98
Note. LGB = Lesbian, Gay, Bisexual
*p < .05. **p< .01. ***p<.001.
Table 2.4 presents findings for discriminatory experiences across the six settings among
MM-YEH. In regard to law enforcement settings, there was a significant difference when
examining the intersection of sexual orientation and gender. Specifically, YEH who identify as
LGBQ and Male were more likely than their heterosexual peers (77.36 vs. 57.75%, X
2
= 15.50,, p
< .01) and YEH who identify as LGBQ and female were more likely than their heterosexual
female counterparts (75 vs. 41.18%, X
2
= 15.50, p < .01) to report perceived discrimination from
law enforcement. Although there were no significant differences among other intersected YEH
subgroups specific to law enforcement discrimination, it is worth noting that both the majority of
Black heterosexual YEH and Black LGBQ YEH (67.65% and 71.79% X
2
= 8.81, p < .27)
similarly reported law enforcement discrimination. For drop-in center settings, significant
differences were found among intersected YEH in regard to: sexual orientation and race and
sexual orientation and gender. Specifically, YEH who identified as Other Race and LGBT were
44
more likely than their Other Race Heterosexual peers (51.52 vs. 20.69%, X
2
= 14.74, p < .01) to
report drop-in center discrimination. It is worth noting that both Black LGBQ YEH and Black
Heterosexual YEH endorsed drop-in center discrimination at relatively similar rates (33.33% vs
26.47%, X
2
= 14.74, p < .01). In addition YEH who identified as LGB and Male were more likely
than their heterosexual peers (47.16 vs. 22.54%, X
2
= 12.48, p < .01) to report drop-in center
discrimination. YEH who identify as Heterosexual and Non-cisgender were the intersected group
most likely to report discrimination in drop-in centers. In fact, the majority of Heterosexual,
Non-Cisgender YEH (60%, X
2
= 12.48, p < .01) were more likely to report drop-in center
discrimination than other intersected YEH peers.
Significant differences were found when examining employer based discrimination for a
number of MM-YEH groups. Specifically, Black LGBT YEH (51.28 vs. 32.35%, X
2
= 14.57, p <
.01), Other Race LGBT YEH (48.48 vs. 17.24%, X
2
= 14.57, p < .01), and White LGBT YEH (40
vs. 28.57%, X
2
= 14.57, p < .01) were more likely to report discrimination in employer settings
than their heterosexual YEH counterparts. Similarly YEH who identify as LGBT and Male,
(47.17 vs. 25.35%, X
2
= 12.37, p < .01) and LGBQ and Female (53.57 vs. 25.53%, X
2
= 12.37, p <
.01) were more likely to report employer based discrimination than their heterosexual YEH
peers, with 53.57% of LGBT Female YEH reporting perceived discrimination by employers. In
regard to discrimination in small business settings, significant differences were found when
examining the intersection between sexual orientation and race. Specifically, LGBT YEH who
identify as Black (56.41 vs. 29.41%, X
2
= 15.39, p < .01) or other race (50 vs. 27.59%, X
2
=
15.39, p < .01), were more likely to report perceived small business discrimination than their
heterosexual peers. In regard to discrimination in community settings, significant differences
were also found when examining the intersection of sexual orientation and race with sexual
45
minority YEH who identify as Black (56.21 vs. 26.47%, X
2
= 24.92, p < .01), White (55 vs.
28.57%, X
2
= 24.92, p < .01), or other race (60.61 vs. 31.03%, X
2
=, 24.92 p < .01), were more
likely to report perceived community discrimination than their heterosexual peers.
46
Table 2.4
Prevalence of Discrimination Experiences Among Marginalized and Multiple-Marginalized
Youth Experiencing Homelessness (n = 198)
Demographics
Law enforcement Drop-in center Health services
N % N % N %
Sexual
orientation x
race (missing =
1)
Heterosexual
x Black
23 67.65 9 26.47* 8 25.53
Heterosexual
x White
12 57.14 8 38.1 10 47.62
Heterosexual
x Latinx
3 33.33 0 0 1 11.11
Heterosexual
x other
15 51.72 6 20.69 7 24.14
LGBQ x
Black
28 71.79 13 33.33 13 33.33
LGBQ x
White
15 75 10 50 5 25
LGBQ x
Latinx
8 66.67 4 33.33 2 16.67
LGBQ x
other
23 69.7 17 51.52 15 45.45
Sexual
orientation x
gender
(missing = 1)
Heterosexual
x male
41 57.75** 16 22.54* 19 26.76
Heterosexual
x female
7 41.18 4 25.53 5 29.41
Heterosexual
x non-
cisgender/
other
5 100 3 60 2 40
47
Demographics
Law enforcement Drop-in center Health services
N % N % N %
LGBQ x
male
41 77.36 25 47.17 20 37.74
LGBQ x
female
21 75 8 28.57 7 25
LGBQ x
non-
cisgender/
other
12 50 11 45.83 8 33.33
Gender x race
(missing = 1)
Male x
Black
33 73.33 14 31.11 14 31.11
Male x
White
11 61.11 7 38.89 7 38.89
Male x
Latinx
8 53.33 4 26.67 2 13.33
Male x other 30 65.22 16 34.78 16 34.78
Female x
Black
15 68.18 5 22.73 5 22.73
Female x
White
8 66.67 5 41.67 4 33.33
Female x
Latinx
1 25 0 0 1 25
Female x
other
4 66.67 2 33.33 2 33.33
Non-
cis/other x
Black
3 50 3 50 2 33.33
Non-
cis/other x
White
8 72.73 6 54.55 4 36.36
Non-cis x
Latinx
2 100 0 0 0 0
Non-
cis/other x
other race
4 40 5 50 4 40
48
Demographics
Employer Businesses Community
N % N % N %
Sexual
orientation x
race (missing =
1)
Heterosexual
x Black
11 32.25* 10 29.41* 9 26.47**
Heterosexual
x White
6 28.57 11 52.38 6 28.57
Heterosexual
x Latinx
1 11.11 1 11.11 1 11.11
Heterosexual
x other
5 17.24 8 27.59 9 31.03
LGBQ x
Black
20 51.28 22 56.41 22 56.41
LGBQ x
White
8 40 10 50 11 55
LGBQ x
Latinx
3 25 4 33.33 1 8.33
LGBQ x other 16 48.48 18 54.55 20 60.61
Sexual
orientation x
gender (missing
= 6)
Heterosexual
x male
18 25.35* 12 26.67 12 26.67
Heterosexual
x female
4 25.53 41 33.06 39 31.45
Heterosexual
x non-
cisgender/
other
1 20 14 48.28 10 34.48
LGBQ x male 25 47.17 12 26.67 12 26.67
LGBQ x
female
15 53.57 41 33.06 39 31.45
49
Demographics
Employer Businesses Community
N % N % N %
LGBQ x non-
cisgender/
other
7 29.97 14 48.28 10 34.48
Gender x race
(missing = 7)
Male x
Black
21 46.67 18 40 18 40
Male x
White
5 27.78 9 50 7 38.89
Male x
Latinx
2 13.33 3 20 2 13.33
Male x other 15 32.61 19 41.3 19 41.3
Female x
Black
8 36.36 11 50 10 45.45
Female x
White
6 50 5 41.67 5 41.67
Female x
Latinx
1 25 1 25 0 0
Female x
other
4 66.67 4 66.67 4 66.67
Non-
cis/other x
Black
2 33.33 3 50 3 50
Non-
cis/other x
White
3 27.27 7 63.34 5 45.45
Non-
cis/other x
Latinx
1 50 1 50 0 0
Non-
cis/other x
other race
2 20 3 30 6 60
Note. LGBQ = Lesbian, Gay, Bisexual, Queer
*p < .05. **p < .01. ***p < .001.
50
Table 2.5 presents that main reason for perceived discrimination among the entire YEH
sample. Race was reported as the main factor for discrimination (N = 66; 51.9%) among all YEH
participants who endorsed perceived discrimination of any type. Sexual Orientation (N = 49,
38.58%) and Gender (N = 45, 35.43%) were also listed among the top five reasons for perceived
discrimination among YEH who reported discrimination of any type.
Table 2.5
Main Reason for Perceived Discrimination Among all Youth Experiencing Homelessness
Demographics N %
Race 66
51.9
Homeless/housing status 56
44.09
Sexual orientation 49
38.58
Financial/employment status 49
38.58
Gender 45
35.43
Education status/problems 30
23.62
Mental health status/symptoms 27
21.26
Colorism (dark skinned) 26
20.47
Colorism (brown/medium skinned) 22
17.32
Substance use status/symptoms 19
14.96
Colorism (light skinned) 16
12.59
Immigration status 10
7.87
51
Figure 2.2
Main Reason for Perceived Discrimination Among All Youth Experiencing Homelessness
Table 2.6 presents that main reason for perceived discrimination among MM-YEH. Of
note, LGBQ YEH who identify as Black (N = 23, 82.1%) or Latinx (N = 6, 75%), were more
likely to report Race as the main reason for discrimination than their White, LGBQ peers (N = 6,
40%). Moreover, In contrary, almost three-fourth of White YEH who identify as LGBQ (N = 11,
73.3%) listed sexual orientation as the main source for their discrimination. YEH who identify as
female and Black (N = 13, 86.6%), Non-Cisgender and Black (N = 2, 66.7%) and Non-
Cisgender and Latinx (N = 2, 100%) reported race as the main factor for their discriminatory
experiences. In comparison, the majority of Non-Cisgender YEH who identify as White (N = 6,
0
10
20
30
40
50
60
70
Table 5. Main Reason for Perceived Discrimination Among all YEH N
Table 5. Main Reason for Perceived Discrimination Among all YEH %
52
75%) reported gender as the main source for their discriminatory experiences. Non-cisgender
YEH who identify as LGBQ (N = 9, 75%) or Heterosexual (N = 3 ,60%) were more likely to
report gender as the main reason for discriminatory experiences in comparison to heterosexual
YEH who identify either as male (N = 7; 17.1%) or female (N = 1, 14.3%) or LGBQ YEH who
identify as either male (N = 17, 41.5%) or female (N = 8; 38.1%).
53
Table 2.6
Main Reason For Perceived Discrimination Among Multiple-Marginalized Youth Experiencing
Homelessness
Intersectional IVs
Race Sexual orientation Gender
N % N % N %
Sexual orientation x race
(missing = 1)
Heterosexual x Black 8 34.7 3 0.09
Heterosexual x White 3 25 2 0.16
Heterosexual x Latinx 3 100 0 0
Heterosexual x other 5 33.33 2 0.13
LGBQ x Black 23 82.1 14 50
LGBQ x White 6 40 11 73.3
LGBQ x Latinx 6 75 5 62.5
LGBQ x other 12 52.1 12 52.2
Gender x race (missing = 1)
Male x Black 16 48.4
10 30..3
Male x White 4 36.3
1 9.1
Male x Latinx 6 75
3 37.5
Male x other 11 36.6
10 33.3
Female x Black 13 86.6
6 40
Female x White 1 0.12
2 25
Female x Latinx 1 100
0 0
Female x other
1 25
1 25
Non-cis/other x Black 2 66.7
2 66.7
Non-cis/Other x White 4 50
6 75
Non-cis x Latinx 2 100
2 100
Non-cis/other x other race 4 100
2 50
54
Intersectional IVs
Race Sexual orientation Gender
N % N % N %
Sexual orientation x gender
(missing = 6)
Heterosexual x male
5 12.2 7 17.1
Heterosexual x female
1 14.3 1 14.3
Heterosexual x non-
cisgender/other
1 20 3 60
LGBQx male
20 48.8 17 41.5
LGBQx female
10 47.6 8 38.1
LGBQx non-cisgender/other
12 100 9 75
Note. IV = Independent Variables , LGBQ = Lesbian, Gay, Bisexual, Queer
Discussion
The present chapter incorporated an Intersectional-based Risk Amplification and
Abatement framework, to examine the perceived discriminatory prevalence among MM-YEH
when interacting with: law enforcement, drop-in centers, health services, employer, businesses,
and community. The findings underscore that discrimination is a serious problem facing the
YEH population particularly in light of the fact that more than half (64%) of YEH endorsed
some form of discrimination.
The main effect findings are consistent with previous studies (Milburn et al., 2009;
Gattis, 2013) and suggest that that sexual minority YEH display heightened risk for
discrimination compared to their heterosexual counterparts. The fact that LGBQ YEH,
particularly LGBQ YEH of color, were more likely to endorse discrimination across all settings
(with the only exception being health services) than their heterosexual peers illustrates that as a
society we still have a lot of work to do to eradicate homophobia and prejudice. This finding
points to a need to develop further platforms for the LGBQ community and LGB YEH of color
to become actively involved in leading, re-imagining, and redesigning drop-in center, law
55
enforcement, employer, and community policies and practice to be both race and sexual minority
affirming and inclusive. More specifically, LGB YEH of color should help design and
implement sensitivity training and training for both drop-in staff and the community at large on
discriminatory practices and the emotional consequences of verbal, physical, and sexual abuse
based on race, gender, sexual orientation, and the intersection of all three for MM-YEH. In
practice, some training areas would focus on informing providers and the community of the
importance of using preferred pronouns, identifying and challenging racial, heterosexual, and
gender bias, when interacting with MM-YEH. In addition, the fact that youth reported
experiences of discrimination across sectors (policy, community, drop-in center) calls for inter-
agency collaboration and leadership action. We encourage enhanced cross-system collaboration
and partnerships between drop-in centers and community sectors, e.g., law enforcement, small
businesses, to more effectively address the discrimination.
Suggested areas for collaboration between drop-in center providers and law enforcement,
small businesses, employers, and community sectors should be established with the goal of
creating a strong working relationship to address and dismantle discriminatory practices.
Common areas of collaboration might include: training community partners on anti-
discrimination policy and cross-learning conversations on best practices to engage with YEH. In
regard to the trainings, we suggest that MM-YEH are actively involved in both the planning and
facilitation of these trainings. In regard to cross-learning discussions, we recommend that MM-
YEH provide critical feedback on current best practices for YEH, such as positive youth
development and trauma informed care (Taylor-Seehafer, 2004; Bransford & Cole, 2019).
Further data should be collected on MM-YEH’ experience of these implementation practices and
56
the findings should be utilized to enhance inclusivity, affirmation, and support in service and
community settings.
Our current findings shed light on the complex interplay between intersecting identities
and experiences of oppression has allowed us to begin to gain insight to the particular and unique
salience that the LGBQ social identity has for LGBQ YEH who identify as Black and Other
Race in comparison to their heterosexual and White LGBQ peers. Specifically, LGBTQ YEH
identifying as Black or other Race experienced significantly more discrimination in law
enforcement, drop-in centers, employers, small businesses, and in the community relative to both
Heterosexual YEH identifying as Black or Other Race, which mirrors past research on racial
disparities in the victimization of LGBQ housed youth (Whitfield, Walls, Langenderfer-
Magruder, & Clark, 2014). These preliminary findings suggest that being both Black or other
race and LGBQ is an entirely distinct experience that may place this YEH subgroup at particular
risk for discrimination across multiple settings.
Although not measured specifically in this chapter, structural determinants that
specifically target the Black LGB community need to be accounted for in light of these findings.
Specifically structural racism and LGBT stigma that places LGB youth of color at greater risk
for overrepresentation in the child welfare, juvenile justice and homeless systems, as well as for
greater risk of entering the school-to-prison pipeline and a higher likelihood of being detained for
non-serious offenses (Glennon, 2016). Future research should incorporate qualitative data to
expand on this empirical gap and explore how Black LGB YEH discriminatory experiences may
differ from white LGBTQ YEH and heterosexual Black YEH. Researchers might also study
individual and collective strategies, potentially alternative support structures and resource
sharing, that Black LGB YEH of color deploy to manage the challenges of discrimination.
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It is important to keep in mind, the sample are all drop-in center serving youth. We do not
have data on YEH who currently do not access drop-in centers. One can imagine that
discrimination may be a barrier to drop-in center access for this group and thus further
exploration is needed here. It is promising that there were no significant findings in regard to
health service discrimination; however, discrimination may likely serve as a barrier to critical
health services given that drop-in centers are oftentimes the main entry point for YEH to access
services and drop-in center discrimination was endorsed by several YEH sub-groups. The
endorsement of discrimination with drop-in center staff is an alarming concern specifically
because our sample only included drop-in center serviced YEH. Given that drop-in centers
provide a range of services that this population needs, it is important to understand the
discriminatory experiences of both drop-in center serviced YEH as well as drop-in center
disconnected YEH, such that this information can help inform the decision-making of these
agencies regarding communication, outreach, and involvement with these youth.
Heterosexual YEH who identify with expansive and non-conforming expressions of
gender were more likely to experience discrimination at drop-in centers (60%) compared to all
other intersected YEH subgroups. In U.S. society, there has often been a conflation of gender
expression with sexuality, for if a person does not enact and embody gender expressions that are
in line with stereotypical expectations for the gender they were assigned at birth, one is seen as
challenging both heteronormativity and the gender binary. Drop-in centers need to revisit their
policies and practices to find ways to dismantle the gender binary, create equity for both
heteronormativity and non-heteronormativity, whereby youth who are both heterosexual and
non-cisgender can feel welcomed, supported, and included. For example, gender affirming drop-
in center policies should ensure staff shall not engage in formal or informal attempts to censor,
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suppress, or change a youth’s gender identity or gender expression and affirm the gender identity
and expression of all YEH.
Above all, race was identified as the main reason for any type of discrimination among
all YEH. This finding points to the salience of race for the YEH community and provides
evidence to incorporate a critical race focused lens to the Intersectional-based RAAM model for
future studies. This may be particularly true for Black YEH considering that Black YEH
subgroups were more likely to identify race as the main reason for discrimination irrespective of
their sexual orientation and gender. Given that both sexual orientation and gender were also
reported among the top five main reasons for discrimination lends further support for an
intersectional-based RAAM model. The fact that homelessness status and financial/employment
status were also identified among the top five suggests a need to further explore if housing and
employment should be viewed as additional potentially socialized identities at risk for
discrimination.
Limitations
This study has limitations that are worth emphasizing. First, data for this study are cross-
sectional thereby limiting our ability to make any causal claims between the variables and
discrimination. Therefore, only an association can be concluded. Second, operationalizing
intersectionality through quantitative research alone is difficult because it is a social phenomenon
operating at multiple levels. Future studies would greatly benefit from incorporating a mixed
methods approach to move beyond the mathematical multiplicative approach and begin to try
capturing the complex and nuanced ways in which social identities intersect and
relative weights given to each identity within a particular social service or institutional setting.
For example, A Black LGBQ YEH with a strong African American cultural heritage may be
59
more resilient than some of her White LGBQ counterparts; however, the current analysis falls
short in allowing us to examine strengths specific to certain MM-YEH groups.
Qualitative research would allow us to begin teasing the interplay between resilience and
oppression apart. Lastly, although YEH were able to check all that apply in regard to the
question depicting the main reason for discrimination, the social identity options were still
categorical. Future research should expand on the present study’s work by incorporating a main
reason question that accounts for YEH’ intersected identities. For example, qualitative studies
should not only ask Black LGBQ YEH about race or sexual orientation as a main reason, but
also inquire about the intersection of their socialized Black LGBQ experience is the main reason
for discrimination. Lastly, the lack of significance when exploring interactions effects among
certain MM-YEH groups, for example Latinx LGB or Latinx non-cisgender MM-YEH may have
been a result of small cell size and not simply because they do not exist. Future research should
seek to include a larger sample of these specific MM-YEH groups.
Implications
The results of this study also demonstrate the nuanced ways in which racial/ethnic, sexual
minority and gender non-conforming statuses intersect at the individual level to produce different
forms of privilege and adversity at the structural level thus creating unique discriminatory
experiences across social services and formal institutions among MM-YEH. These findings
create a strong implications in favor of utilizing the emerging Intersectional-lens RAAM model
to better understand the specific experiences of the MM-YEH population. In fact, these results
show that failure to attend to diversity within marginalized groups of YEH can obscure important
distinctions in regard to discriminatory experiences among YEH with multiple marginalized
identities.
60
More specifically, although both race and gender is not significantly associated to
discrimination alone, if we only tested main effects we would have missed the significant
findings regarding the intersection of both race and sexual orientation and gender and sexual
orientation. To our knowledge, there are only a few studies (Gattis & Larson, 2017), that have
included interactions effects to explore the intersection of race and gender for YEH and its
association with discriminatory experiences. This dissertation is unique in its explicit focus on
the prevalence of discrimination experiences among MM-YEH. As such, our interaction findings
strongly emphasize the critical importance of an intersectional approach for this community. We
advocate for further research, policy and program efforts to dismantle the homogenization of the
clearly heterogenous community of MM-YEH. Homogenizing MM-YEH facilitates their
dehumanization, erasing not only their diverse intersecting identities, but also obscuring their
diverse experiences of discrimination.
There is a growing investment from both providers and researchers to address
discriminatory barriers experienced by YEH; however, given the current gap in the literature
there is still unanswered questions as to the magnitude of this barrier and the YEH subgroups
most vulnerable to discrimination. The present study offers some initial intersectional findings
and makes a strong case to utilize an intersectional based RAAM model to examine and address
the staggering prevalence among MM-YEH. There are three main implications for practice and
future research from this study. First, supports are needed for YEH who identify with
intersecting sexual, gender, and racial/ethnic minority social identities and may be at particular
risk for discrimination, policy implications to target discrimination prevention and interventions
in social services and institutions, and examining the role of strengths-based assets for MM-
YEH. First, to our knowledge, this is the first study to underscore the specific risk faced by
61
LGBQ youth who identify as Black or Other Race with respect to discrimination across multiple
settings. Thus, there is a need to focus on ways to specifically support these YEH subgroups who
is overrepresented in the YEH community and to understand how to specific supports Black and
other race LGBQ YEH need that may be unique from both White LGBQ and Black or other race
heterosexual peers. Despite an increased awareness of “safe zones” and other social service
initiatives to promote LGBQ inclusivity (Wood et al., 2016), the results of this study identify an
ongoing need to continue to address specific Black and other race LGBQ disparities and design
policies that are responsive the unique Black or other Race LGBQ YEH experience.
Second, in parallel to increased risk for discrimination among heterosexual, non-
cisgender YEH, anti-discriminatory campaigns and policies should target and eliminate dated
and degrading gender binary and heteronormative practices. Thus, campaigns and policies could
also incorporate a strong ally approach and provide strategies to encourage intervention, by
providers and peers, when they observe situations of discrimination toward their sexual, gender,
and racial minority YEH peers. The intersection of race/ethnicity and sexual minority might
further exacerbate distal and proximal stressors on LGBQ adolescents of color. In addition to
relative risk, future research could also examine potential protective factors that might mitigate
the impact of discrimination for these YEH subgroups.
Our effort to incorporate intersectionality to more fully examine the YEH experience is
offered in the spirit of continuing a dialogue among researchers focused on YEH to move toward
a less partial, less categorical estimation of the adverse impact of discrimination among MM-
YEH across multiple social service and institutional settings. Several of the shortcomings of this
analysis could be easily addressed with minimal effort at the data collection phase by
augmenting the initial study to include more qualitative data with questions that draw on the
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YEH experience of belonging to multiple marginalized minority groups and other potential
social identities, e.g., colorism, housing, employment not accounted for in the current study. A
next step would be to ask participants to indicate the relative positive or negative salience of each
identity and to weigh or rank the perceived importance of each identity as well as the intersection
of identities relative to the others. The addition of attention to contextual, interpersonal-level, and
other potential socially constructed variables could inform future YEH research. Ultimately the
goal of producing such knowledge would be to affect social change within and across this
service systems and institutions to improve the health of YEH who experience marginalization at
many levels.
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Chapter 3: Prevalence of Supportive Staff Among Youth Experiencing Homelessness
Given the well documented risks associated with youth homelessness, studies have
focused on protective factors that may mitigate adverse health outcomes for this populations
(Lightfoot, Stein, Tevendale, & Preston, 2011; Barman-Adhikari et al., 2016; Craddock, Rice,
Rhodes, & Winetrobe, 2016; Dang et al., 2014). Research suggests that youth experiencing
homelessness (YEH) who are able to engage with supportive social networks – which often
include service providers, such as drop-in center and health service providers – are associated
with lower rates of substance use and other high health risk behaviors (De la Haye et al., 2012;
Rice, 2011; Ferguson and Xie, 2012). Despite emerging research linking positive staff support to
positive outcomes for homeless youth, less attention has been paid to understanding which YEH
subgroups, particularly YEH who are prone to discrimination based on race/ethnicity, gender,
and/or sexual orientation status, are most likely to develop such positive staff support. A better
understanding of this issue is critical to designing targeted interventions that can facilitate
building more robust social support systems among MM-YEH given the critical role drop-in and
service providers play in connecting YEH to services coupled with the disproportionate risk of
discrimination in service settings. Adopting an Intersectional-based Risk Amplification and
Abatement Model, this study therefore aimed: (1) to examine the presence of positive staff
support among marginalized and multiple marginalized YEH subgroups; and (2) to identify
salient correlates - including the presence of drop-in center discrimination and health service
center discrimination - of positive staff support among M-YEH and MM-YEH subgroups.
Social Support
Researchers have moved away from traditional deficit-based frameworks to focus more
on identifying protective factors that may buffer against poor health outcomes for YEH (Milburn
64
et al., 2009; Rice, Stein, & Milburn, 2008; Kidd & Shahar, 2008). One particular focus is in the
area of social support (Rice, Stein, & Milburn, 2008; Barman-Adhikari, 2014, 2016; McCay et
al., 2011). The majority of this research on “prosocial” support has focused on other youth who
are in school or employed or supportive family ties and found that these social ties are associated
with lower rates of high-risk behaviors (Rice et al. 2007). Additional studies have documented
that having access to social support is associated with fewer negative mental health symptoms
and maladaptive behaviors among YEH (Castro et al. 2014; Fulginiti et al. 2016; Irwin et al.
2008; Moskowitz et al. 2013; Unger et al. 1998). Social support from personal networks can also
offer critical instrumental coping assistance in finding employment and being successful in
finding housing (Barman-Adhikari and Rice 2014; Holtschneider 2016).
The literature also suggests that ties to supportive professionals may be particularly
influential in increasing the likelihood that YEH access services when available (Tyler et al.
2012; Wright and Connoley 2002). Professional staff have been found to be both instrumentally
resourceful (Barman-Adhikari and Rice, 2014) as well as provide secure models of attachment
and a sense of belonging for YEH (Oliver and Cheff 2014). While research has started to
acknowledge the advantages of YEH establishing and securing positive staff relationships
(Barman-Adhikari and Rice, 2014; Oliver and Cheff, 2014; Holguin et al., (in press)), literature
on the intersections of race, sexual orientation, gender and staff relationships remains non-
existent. In this paper, we focus on the prevalence of positive staff support among YEH with
marginalized and multiple marginalized identities.
Among homeless youth, there has been very limited focus on race-based differences in
network characteristics. The findings among these few studies suggest that social relationship
differences do exist particularly when comparing Black YEH to White YEH (Wenzel et al., cite,
65
Hickler and Auerswald, 2009); however, much of the work here has only focused on affiliations
with family and peers (Giordano et al., 1993; Rice et al., 2007, 2011). To our knowledge, only
one study to date (Johnson et al. 2005) has explicitly explored quantitatively the factors
associated with differences in social support composition among YEH who identify as LGBT.
This study found that lesbian, gay, or bisexual identity and childhood abuse history were two of
the factors associated with reporting a greater proportion of street peers among their social
supports. The same study found that YEH who identify as LGBT also accessed social support
from staff. It is critical to understand the prevalence of staff support, particularly given how
instrumental they are to service access, among MM-YEH. Specifically, drop-in centers are often
a key location to deliver higher level services to YEH that may not seek services elsewhere. A
better understanding of the of service-level factors (e.g., staff relationships) that could potentially
facilitate MM-YEH engagement in drop-in centers as well as other service settings will help
inform research and outreach efforts.
An Intersectional-Based RAAM Framework
An Intersectional-based RAAM framework builds on the RAAM model by supporting
the argument that negative contact with socializing agents amplifies risk, while positive contact
with socializing agents, including providers, abates risk for YEH (Milburn et al., 2009). The
Intersectional-based RAAM framework extends the work of RAAM by incorporating an
intersectional perspective of YEH. From this perspective, RAAM suggests that positive and
negative contact with socializing agents are encountered by YEH in at least four levels of social
organization: family, peers, social services, and formal institutions. Using this model, we focus
on a specific RAAM level of social organization: social services and seek to examine if there are
differences in the presence of supportive staff relations among YEH with multiple marginalized
66
experiences. Furthermore, we seek to investigate these staff relations within the context of
perceived drop-in center and health service discrimination amongst MM-YEH. Addressing this is
essential to promoting stronger support networks marginalized YEH subgroups.
Current Study
The YEH population is remarkably heterogeneous and represent a plethora of
marginalized identities with regard to race/ethnicity, sexual orientation, gender identity, and
many other identities and experiences. However, our understanding of how MM-YEH organize
their social lives and networks is extremely limited. Consequently, at the most basic level, we
seek to contribute to growing literature by probing the relationship between race/ethnicity,
gender identity, sexual identity, and time homeless and the prevalence of service provider
supports among MM-YEH. Because discrimination is emerging as a serious barrier to much
needed services for this population, we go further and investigate the association between service
provider support, race/ethnicity, gender identities and having experienced drop-in center or
health service discrimination. The present cross-sectional study will use an Intersectional-based
Risk Amplification and Abatement framework, to explore the prevalence of discrimination and
its potential association with positive adult support among MM-YEH. Relying upon
Intersectionality and RAAM key domains, we will meet this goal by completing the following
specific aims:
1. To identify which YEH subgroups are more likely to have a positive adult (formal (staff)
and informal (non-staff)) support
2. To examine potential main effects between perceived discrimination and positive adult
(formal (staff) and informal (non-staff)) support.
67
Methods
Sample
Data was derived from a longitudinal social network study of youth experiencing
homelessness utilizing drop-in centers in Los Angeles, CA. A sample of 418 youth ages 16-24
were surveyed between October 2018 and June 2019. Participants were recruited from 3 drop-in
centers servicing YEH across 4 different waves at each of the centers. 198 participants recruited
from the 3 drop-in centers from the fourth wave of this study comprised the total sample for this
study. The refusal rate for the study was X%; only X youth that were approached refused to
participate in the study. Two of the centers are located in area in Los Angeles County in which
many YEH are concentrated (Rabinovitz, Desai, Schneir, & Clark, 2010). In comparison, the
third recruitment site is located in Venice, a location that has increasingly become an area where
youth congregate but does not have access to the array of services in Hollywood (Brooks et al.,
2004). Each wave of data occurred approximately 6 months apart. All youth accessing services at
the recruitment sites during the periods of data collection were invited to participate in the study.
All three drop-in centers structure operates such that any youth who self-identifies as homeless,
e.g., sleeping on the streets, in an emergency shelter, couch surfing, or at immediate risk of being
homeless) and is between the ages of 16-24 is deemed eligible for services. Youth were invited
to participate in multiple waves, but only the fourth wave survey data was used in the current
study.
Procedures
Recruitment was conducted for 14 days at each site during Wave 3 of data collection (3
months after baseline data was collected). During these periods, recruiters were present at the
agency to approach you for the duration of service provision hours. A consistent set of two
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research staff members at each site were responsible for recruitment, in order to prevent youth
from completing the survey multiple times within each data collection period. Signed voluntary
consent was obtained from youth 18 years of age and older and informed assent was obtained
from youth 16-17 years old. The Institutional Review Board at the University waived parental
consent, as YEH under 18 years old are considered unaccompanied minors who may not have a
parent or adult guardian from whom to consent. The 60-minute survey was a computer
administered self-interview, completed at the site. Participants received $25 in gift cards as a
compensation for their time. The Institutional Review Board approved all survey items and
procedures.
Measures
Outcome Variable: Positive Staff Relationships
For positive, supportive formal support, participants were asked: (1) During my time in
youth services, I have developed at least one relationship with a supportive and positive staff at
an agency that I attend. Participants were asked to select one of the following responses: “yes”,
“no”, or “I don’t know”. Response items were coded dichotomously into a “yes” or “no” format.
Gender, Sexual Orientation, and Race/Ethnicity
Gender identity and race/ethnicity questions allowed students to mark more than one
category. For the present study, gender identity was recategorized into: 1) Male (if a participant
marked only “male”), 2) Female (if a participant marked only “female”), and 3) Non-cisgender
(if a participant marked “trans male/trans man”, “trans female/ trans woman”, “Gender
queer/Gender non-conforming” or “Different identity” in which the written response was
indicative of non-cisgender and as such this category was also included in the third category:
“Non-cisgender”). A second gender identity category was created to compare cisgender
69
participants (participants who endorsed 1) Male (if a participant marked “Male”) or 2) Female (if
a participant marked “Female”) to non-cisgender participants (if a participant marked “trans
male/trans man”, “trans female/ trans woman”, “Gender queer/Gender non-conforming” or
“Different identity” in which the written response was indicative of non-cisgender and as such
this category was also included in the third category: “Non-cisgender”).
The sexual orientation item, which limited participants to one response among the
following categories: 1) Gay or Lesbian, 2) Bisexual, 3) Heterosexual or Straight, 4) Questioning
or Unsure, 5) Asexual, or 6) Another Sexual Orientation. Sexual orientation was re-coded into:
1) heterosexual (if a participant marked “heterosexual”) and 2) LGB (if a participant marked any
response other than “heterosexual”), to maintain consistency with previous studies (e.g., Rice et
al. 2013, Milburn et al., 2009). Participants were given several race/ethnicity options and
instructed to “pick the one that describes you best”. Race was re-coded into: 1) Black (if a
participant identified as Black), 2) White (if a participant identified as White), 3) Latinx (if a
participant identified as Latinx) and 4) Other Race(if marked American Indian or Alaska Native,
or Asian, or Mixed Race as a category). Finally, intersecting stigmatized identities was
operationalized as two or more stigmatized identities across gender (i.e., cisgender, non-
cisgender), race (i.e., Black, White, Latinx, Other), and sexual orientation (i.e., LGB).
Intersecting identities were created by recoding the following variables: race/ethnicity, gender,
and sexual orientation into the following: race x sexual orientation, race x gender, and gender x
sexual orientation.
Other Socio-Demographic Variables
Length of homelessness was recoded dichotomously as: less than two years for all
participants who indicated: less than 1 month, 1-3 months, 4-6 months, 7-9 months, 10-11
70
months or 1-2 years and chronic/two or more years for participants who indicated: 3-4 years, 5-6
years, 7-8 years, or 9 or more years. Current housing status for the sample was recoded as: literal
homelessness (youth experiencing literal homelessness were defined as those who indicated that
they were currently staying in a shelter (emergency or temporary), hotel, motel, trailer, street,
beach, tent or campsite, abandoned building, car or bus vs. youth living with biological family,
foster family, relative, friend, group home, sober living facility, transitional living program).
Foster care involvement was assessed with dichotomous responses. Age was collected as a
continuous variable and dichotomized for analysis using the mean age (22.1) to determine the
categories. All other demographic variables were categorical.
Discrimination Variables
Participant’s perceived provider discriminatory experiences was measured using the
Everyday Discrimination scale (EDS) which has been widely used in studies of discrimination
and health (Williams et al. 1997; Deitch et al. 2003). The EDS was developed as a subjective
measure to capture self-reported frequency of routine, relatively subtle discriminatory
experiences in everyday social situations. The EDS has been found to be strongly associated with
institutional and interpersonal discrimination (Hughes 2003; Krieger et al. 2005) and is accepted
as a valid measure that accounts for discriminatory experiences among youth and adults who
identify with minority status (Seaton et al. 2008; Goosby et al., 2015; ). First, participants are
asked: “Can you tell me if any of the following ever happen to you?” The original scale consists
of 11 items assessing the frequency of participants’ experiences of everyday discrimination. For
the purposes of Aim 2 and based on prior studies modification for use in health care settings
(Bird et al., 2009; Peek et al., 2011), a methodological decision was made to modify the EDS to
focus on 2 types of everyday discrimination experiences: drop-in centers and health services
71
(including medical, mental health, substance use treatment, and HIV/STI treatment services) and
subsequently changed ‘people’ to ‘staff’ for the drop-in center and health service variable.
Examples include: “ People act as if they think you are not smart”, “People act as if they are
afraid of you” to “Staff act as if they think you are not smart” and “Staff act as if they are afraid
of you”.
Situation-based coding, a common approaches to coding the EDS (Schulz et al., 2006;
Lewis et al., 2009; Moody et al., 2006), will be used for this study. In situation-based coding,
each survey item is dichotomized: ‘never’ = 0 and ‘ever’ = 1. Situation-based category coding
collapses everyone who experience any discrimination into one category. Responses are summed
across the items to generate a score ranging from 0-6, capturing the number of different
situations ever experienced. For this study, we will dichotomize each EDS item to ‘never’=0 and
‘ever’=1. Items will be summed (range: 0-10) to reflect the total number of discriminatory
situations ‘ever’ experienced per type: law enforcement, drop-in center, health service, employer,
business, and community. In addition, items across all 6 types of settings will be summed range:
0-60) to reflect the total number of situations ‘ever’ experienced across all settings. The
Everyday Discrimination Scale has demonstrated good reliability and validity (Taylor, Kamarck,
& Shiffman, 2004; Williams et al., 2012; Williams, Neighbors, & Jackson, 2003). In sample of
LGBT participants, Cronbach’s alpha for the discrimination scale was 0.94, and discrimination
scores were correlated positively with depressive symptoms, anxiety, and substance use
(Gamarel, Reisner, Laurenceau, Nemoto, & Operario, 2014; Gamarel, Reisner, Parsons, &
Golub, 2012; Gordon & Meyer, 2008; S. L. Reisner, White, Bradford, & Mimiaga, 2014).
72
Data Analysis
Statistical analyses were conducted using SAS software (SAS version 9.4). Descriptive
analyses were used to describe the sample’s demographic characteristics, homelessness
experiences, and presence of positive staff relationships. Crosstabs and chi-squares were used to
present the association between participants’ main demographic identities, i.e., race/ethnicity,
sexual orientation, and gender and positive staff relationships. Next, a series of bivariate logistic
regressions were run to determine significant associations (p<.05) between the independent
variables and the outcome variable, positive staff relationships. Prevalence ratios, their 95%
confidence intervals and their respective P-values were calculated. These bivariate associations
were examined in a pair-wise approach, which is logically equivalent to the examination of a
correlation matrix. Any independent variable that was found to be significantly associated (i.e., p
< .05 level) with any dependent variable was retained in the final multivariate logistic regression
models presented in Table 5-6 (Hosmer & Lemeshow, 1989). A multivariate regression model
was run to determine significant associations (p <.05) between all independent variables (i.e.,
demographic characteristics, perceived discriminatory experiences, predisposing characteristics,
and the outcome variable, positive staff relationships.
Results
Descriptive statistics are presented in Table 3.1. The sample is heterogeneous with many
youth identifying with diverse minority statuses. Specifically, Black (N = 73, 37.06 %) was
endorsed more than any other race/ethnicity and slightly over half of the sample identified as
LGBT (N = 105, 53.03%). A substantial proportion of the sample identify as Non-Cisgender (N
= 29, 14.66%). The average age for the sample is 22.1 years old (SD = 2.1) with a little over one-
third (33.68%) of the sample reporting they have been homeless for two or more years. Slightly
73
over one-third (33.6%) of youth reported discrimination in drop-in centers. Similarly, a little less
than one-third (30.81%) of youth reported discrimination in health, mental health, and substance
use treatment center settings. Although the majority of youth reported a positive staff
relationship (62.69%), over one-third (37.31%) reported the absence of a positive staff
relationship.
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Table 3.1
Descriptive Statistics of Youth Experiencing Homelessness (n = 198)
Demographics N %
Race/ethnicity (missing = 6)
Black 73 37.06
Latinx 21 10.66
Mixed 50 25.38
White 41 20.81
Other 12 6.09
Gender (missing = 6)
Female 45 22.73
Male 124 62.63
Non-cisgender 29 14.66
Sexual orientation (missing = 7)
LGB 105 53.03
Heterosexual 93 46.97
Foster Care History
Yes 118 66.67
No 59 33.33
Demographics M SD
Age 22.1 2.1
Demographics N %
Time homeless (missing = 5)
Less than two years
128 66.32
Two or more years
65 33.68
Drop-in center discrimination
No 131 66.16
Yes 67 33.84
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Demographics N %
Health service discrimination
No 137 69.19
Yes 61 30.81
Positive staff relationship
No 72 37.31
Yes 121 62.69
Note. LGBT = Lesbian, Gay, Bisexual
Among the YEH sample (as shown in Table 3.2), significant differences were found
when comparing the presence of positive staff relationships between cisgender YEH and non-
cisgender YEH. Specifically, YEH who identify as male or female were significantly less likely
to have a positive staff relationship (58.2% vs. 60.47%% vs. 85.71%, X
2
= 7.49, p < .02). Given
the similar percentage rates among male and female youth, we recoded the gender variable to
compare cisgender youth and non-cisgender youth. In comparison to non-cisgender youth,
cisgender youth were less likely to have a positive staff relationship (58.79% vs. 85.71%, X
2
=
7.42, p < .01). As shown in Table 3.2., positive staff relationship was not significantly related to
race/ethnicity or sexual orientation as a main effect.
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Table 3.2
Positive Staff Relationships of Youth Experiencing Homelessness (n = 198)
Demographics N % Chi squared
Race/ethnicity (missing = 6)
Black 43 59.72 0
White 28 68.29 2.6
Latinx 15 75
Other 35 58.33
Sexual orientation (missing = 7)
LGB 69 67.65 2.27
Heterosexual 52 57.14
Gender (missing = 6)
Male 71 58.2
Female 26 60.47 7.49*
Non-cisgender 24 85.71
Gender binary (missing = 6)
Cisgender 97 58.79
Non-cisgender 24 85.71 7.42*
Note. LGB = Lesbian, Gay, Bisexual
Table 3.3 presents findings for the presence of a positive staff relationship among MM-
YEH. In regard to positive staff relationships, no significant differences were found when
examining the intersection of sexual orientation and the intersection of race and sexual and the
intersection of gender and gender and race.
77
Table 3.3
Positive Staff Relationships of Marginalized and Multiple Marginalized Youth Experiencing
Homelessness (n = 198)
Demographics N % Chi Squared
Sexual orientation x race
(missing = 1)
Heterosexual x Black 17 51.52
Heterosexual x White 12 57.14 8.51
Heterosexual x Latinx 8 88.89
Heterosexual x other 15 53.57
LGBQ x Black 26 66.67
LGBQ x White 16 80
LGBQ x Latinx 7 63.64
LGBQ x other 20 62.5
Sexual orientation x gender
(missing = 1)
Heterosexual x male 40 57.97
Heterosexual x female 8 47.06 9.74
Heterosexual x non-
cisgender/other
4 80
LGBQ x male 31 58.49
LGBQ x female 18 69.23
LGBQ x non-cisgender/other 20 89.96
Gender x race (missing = 1)
Male x Black 26 59.09
Male x White 11 61.11 13.52
Male x Latinx 11 73.33
Male x other 23 51.11
Female x Black 12 54.55
Female x White 9 75
Female x Latinx 2 66.67
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Demographics N % Chi Squared
Female x other 3 50
Non-cis/other x Black 5 83.33
Non-cis/other x White 8 72.73
Non-cis x Latinx 2 100
Non-cis/other x other race 9 100
Note. LGBQ = Lesbian, Gay, Bisexual, Queer
The bivariate logistic regression for positive staff relationship is presented in Table 3.4.
The following independent variables: drop-in center discrimination and gender as well as health
service discrimination and gender were significantly associated with positive staff relationship
outcomes in the bivariate analysis. Specifically, youth who identify as non-cisgender were more
likely (OR = 4.14 95%CI = 1.37, 12.54, p <.05) to have a positive staff relationship than youth
who identify as cisgender. In addition, youth who identify as non-cisgender were more likely
(OR = 4.19, 95%CI =1.39, 12.65, p <.05) to have a positive staff relationship than cisgender
youth.
Table 3.4
Bivariate Logistic Regressions of Positive Staff Support
Discrimination OR
95% CI
Drop-in center
Non-cisgender 4.14 * [1.37, 12.54]
Drop-in center discrimination 1.09
[.58, 2.06]
-2 log likelihood
Health service
Non-cisgender 4.19 * [1.39, 12.65]
Health service discrimination 1.05
[.55, 1.99]
-2 log likelihood
Note. *p <. 05. **p < .01. ***p < .001.
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The multivariate model presented in Table 3.5. revealed that gender identity was
significantly associated with a positive staff relationship. In regard to gender, non-cisgender
youth (OR = 3.33, 95%CI = 1.08, 10.50, p <.05) were more likely to have a positive staff
relationship, compared to cisgender youth. The model showed no significant associations for the
following covariates: drop-in center discrimination, sexual orientation, foster care history,
race/ethnicity.
Table 3.5
Multivariate Logistic Regression of Positive Staff Relationship Given Drop-In Center
Discrimination (n = 198)
OR 95% CI
Non-cisgender 3.33 * [1.05, 10.50]
Drop in center discrimination 0.95 [0.47, 1.93]
LGB 1.36
[0.71, 2.62]
Foster care 0.77
[0.39, 1.51]
Black 0.84
[0.44, 1.60]
-2 log likelihood 221.62
Note. LGB = Lesbian, Gay, Bisexual
*p < .05. **p < .01. ***p < .001.
The multivariate model in Table 3.6. shows that gender identity was significantly
associated with the presence of positive staff relationships. In regard to gender, non-cisgender
youth (OR = 3.31, 95%CI = 1.05, 10.43, p <.05) were more likely to have a positive staff
relationship, compared to cisgender youth. The model showed no significant associations for the
following covariates: health service discrimination, sexual orientation, foster care history,
race/ethnicity.
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Table 3.6
Multivariate Logistic Regression of Positive Staff Relationship Given Health Services Center
Discrimination (n = 198)
OR 95% CI
Non-cisgender 3.31 * [1.05, 10.43]
No drop-in center discrimination 0.82 [0.40, 1.66]
LGB 1.37
[0.72, 2.60]
Foster care 0.76
[0.39, 1.48]
Black 0.84
[0.44, 1.59]
-2 log likelihood 221.32
Note. LGB = Lesbian, Gay, Bisexual
*p < .05. **p < .01. ***p < .001.
Discussion
Our study aligns with a growing body of work focused on examining the heterogeneity of
YEH’ social relationships, (De La Haye et al. 2012; Falci et al. 2011; Johnson, Whitbeck, and
Hoyt 2005; Milburn et al. 2005; Rice, Milburn, and Rotheram-Borus 2007; Rice, Milburn, and
Monro 2011; Tyler and Melander 2011; Wenzel et al. 2010; Wenzel et al. 2012). The findings
provide preliminary empirical evidence for the Intersectional-based RAAM model and points to
the critical importance of accounting for and honoring YEH’ diverse marginalized experience to
better understand YEH staff support social networks. We sought to expand on the literature by
focusing on service provider relationships among YEH who identify with marginalized and
multiple marginalized identities. There are several important findings that can be conceptualized
through an Intersectional-based RAAM framework which emerge from these data and as such,
we suggest promising points of interventions.
First, it is encouraging to note that the majority of youth identified a supportive staff in
their life (62.69%); however, we still found that slightly over one in three (37.31%) drop-in
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center participants did not identify a support staff. These findings shed light on the social support
gaps that still remain within service settings and the potential need to rethink and reshape
provider engagement efforts with YEH. Previous qualitative studies have found that
characteristics of drop-in staff can both facilitate and discourage YEH engagement at drop-in
centers (Petersen, Tucker, & Kovalchik, 2016; Slesnick et al., 2008). Researchers have found
that YEH report non-engagement with service providers who demonstrate authoritative
communication styles (e.g., judgmental, hurried manner), convey disrespect, do not take the
youth seriously, and appear untrustworthy (Hudson, Nyamanthi, & Sweat, 2008). Drop-in center
services should be individually tailored on engagement efforts with MM-YEH who are
disconnected from staff. For example, efforts can be made to hire staff members that possess the
qualities to which youth respond positively. Service providers themselves must be self-aware of
their own implicit and explicit biases. Anti-discrimination policies should create spaces in which
both YEH and supportive staff can call out staffs’ biases and actively support YEH who identify
and report staffs’ discriminatory behaviors without fear of repercussion.
Second, the prevalence findings underscore that discrimination in service settings is a
serious problem facing the YEH population particularly in light of the fact that slightly more
than one-third face drop-in center discrimination (33.84%) and health services discrimination
(30.81%). Although a few studies have explored discriminatory experiences among YEH
(Miburn et al., 2006; 2010; Gattis & Larson, 2017), to our knowledge our study is the first to
explicitly examine drop-in center and health service discrimination among YEH. As underscored
in the previous study, discrimination against MM-YEH is pervasive across a myriad of
community and service settings. Drop-in center and health service discriminatory prevalence
rates are particularly alarming given the grave circumstances (e.g., homelessness) that these
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youth find themselves in coupled with the fact that drop-in and service providers often serve as
the access point to additional social supports and services. Social support engagement efforts
should carefully consider how to alleviate the deleterious impact of chronic stressors endemic to
experiences of marginalization and multiple marginalization in outreach and engagement
planning.
Third, and perhaps most interesting, more non-cisgender than cisgender YEH endorsed
the presence of supportive staff relationship. This is particularly interesting given that in our
previous study we found that heterosexual YEH who identify with expansive and non-
conforming expressions of gender were more likely to experience discrimination at drop-in
centers (60%) compared to all other intersected YEH subgroups as found in the previous chapter.
This finding highlights the resilience of non-cisgender YEH who are able to establish and
maintain positive staff relations while simultaneously enduring discrimination in the very same
setting. It may also suggest that non-cisgender are likely to be among the most discriminated
against and marginalized in community settings as indicated in the previous study. Though it is
promising that professionals are perceived as positive and supportive, perhaps drop-in or
behavioral health service providers should invest greater efforts to connect these youth to home-
based peers or mentors who may be able to provide sustained support.
Our results should be considered within the settings in which the data was collected. An
initial consideration is that one of the drop-in centers included in the study is primarily focused
on the LGBT community which may contribute to this promising finding. However, no
significant differences were found when we examined drop-in site effects and compared drop-in
center discrimination across all three settings. Alternatively, it could be that gender minority
YEH feel more secure in establishing a relationship with a staff member within these types of
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settings despite experiencing drop-in center discrimination. It could be that non-cisgender YEH
seek certain drop-in staff who have been gender affirming and supportive while simultaneously
having to contend with discriminatory experiences by other staff. Our findings indicate a need to
move beyond individual-focused interventions that foster MM-YEH resilience toward systemic
approaches to combat drop-in center discrimination. This preliminary finding enhances our
strong endorsement for drop-in centers to revisit their policies and practices and find ways to
dismantle the gender binary, create equity for both heteronormativity and non-heteronormativity,
whereby all MM-YEH can feel welcomed, supported, and included.
Limitations
The results of this study need to be considered in the context of its limitations. The
study’s cross-sectional design limits causal conclusions. Using longitudinal strategies in future
studies will help to clarify the causal mechanisms that underlie the relationships between
marginalized identities, discriminatory experiences, and types of social support. Future studies
would be wise to incorporate a mixed-methods design and utilize qualitative data to further
unlock the rich complexity of support networks through the lens of MM-YEH who are
particularly targeted for discrimination and marginalization. In-depth interviews and focus
groups with transgender and gender-expansive YEH is necessary to further investigate how these
marginalized groups are navigating oppressive service and community settings that use
discriminatory cisgender policies and practices such as, gendered bathrooms, sex-segregated
facilities, and exclusionary paperwork, thereby dishonoring their self-designated gender.
Qualitative data may also begin to unlock if and how pro-social, gender-affirming staff can
provide support for non-cisgender YEH in community environments. Several researchers have
demonstrated the promise of using qualitative data to begin to explore some of the nuances of
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these youth’s dynamic lives, as well as their changing social networks (Toolis and Hammack
2015; Tyler and Melander, 2011). We relied on a simple measure to identify the presence of
supportive staff relationships rather than a formal network roster. Future studies may benefit by
incorporating modified network roster approaches (Tucker et al. 2012; Tyler 2008), as well as
global measures of perceived support and/or the number of ties based on role relationships (Rice
et al. 2007; Unger et al. 1998) to further examine MM-YEH’ staff relations. In addition,
supportive staff relationships were only examined from the perspective of YEH. As such, we do
not have data from staff themselves to corroborate. Our methodological decision to only use data
that was self-reported by YEH is aligned with the focus of the study to better understand the
lived experiences of YEH.
Implications
While more research is needed to fully elucidate the composition and roles within MM-
YEH’ personal support networks, our study and related research point to the need to consider
marginalized experiences more carefully in our efforts to help these groups. Policy makers and
homeless service providers would be wise to consider ways in which they could adopt and
incorporate more network-centered engagement and intervention strategies to improve the care
available to youth who runaway or find themselves homeless.
Specifically, we call on researchers and providers to shift their focus from assisting MM-
YEH tasked with overwhelming amounts of stress to manage their distress and instead focus on
systems-level interventions that target the root determinants of these discriminatory stressors.
Gender-affirming policies and anti-discrimination efforts, particularly in the form of policies that
expand non-conforming gender rights in both service and community settings at large, are
worthy of new and sustained investment. In regard to direct practice, providers have
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demonstrated non-affirming, biased approaches with non-cisgender youth (Blumer et al., 2012).
It is critical for both researchers and clinicians to adopt an intersectional lens to: 1) recognize that
non-cisgender YEH have specific issues related to their unique discriminatory experiences,
social support, and homelessness status in different moments of gender affirmation and 2)
develop interventions to promote a strong, gender-affirming relationships between non-cisgender
YEH and other social supports in service and community settings.
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Chapter 4: Discriminatory Experiences, Staff Support, and Service Engagement Among
Youth Experiencing Homelessness
Many youth experiencing homelessness (YEH) occupy multiple marginalized identities
and thus are subject to multiple forms of discrimination that may shape their likelihood of
engaging in drop-in center and mental health services. Staff in these centers may be able to play
a pivotal role in facilitating YEH’s attendance and connection to critical services, such as mental
health. Although our previous study found that multiple marginalized youth experiencing
homeless (MM-YEH) experience discrimination across various community and service settings
at greater frequency, this may not necessarily negatively influence their engagement with drop-in
center and mental health services.
Our contribution to the RAAM framework is to incorporate an Intersectionality lens to
attend to the complex and compounding ways that YEH with multiple marginalized identities
interact with adults and systems, e.g., drop-in centers, mental health services. MM-YEH, in the
face of previous and current discriminatory exposure, may have had to learn to adapt in order to
continue getting their needs met. Thus, the purpose of this study is to expand upon the existing
RAAM model by utilizing an intersectional-based RAAM framework that allow for a deeper
understanding of how discrimination and positive staff relationships may contribute to unique
and complicated socialization process for multiple marginalized youth experiencing
homelessness (MM-YEH) engaging in drop-in center and mental health service use.
Mental Health Service Needs
An estimated 1 in 30 US adolescents experience some type of unaccompanied
homelessness annually (Morton, Dworsky, & Matjasko, 2018). Once they are out on the streets
on their own, most of these YEH are in immediate need of basic services such as food, showers,
and clean clothes, while simultaneously facing a host of other challenges. While youth facing
87
homelessness demonstrate resilience, adaptability, and many other strengths (Bender, Thompson,
McManus, Lantry, & Flynn, 2007), they also face significant risks, including violence,
transactional/exchange sex, incarceration, exacerbation of mental and physical health conditions,
and early mortality (Aratani, 2009; Cleverley & Kidd, 2011; Tucker, Edelen, Ellickson, & Klein,
2011). Rates of traumatic experiences among YEH are high and can occur during both childhood
and adolescence and as a result of homelessness (Wong, Clark, & Merlotte, 2016; Tyler &
Smitz, 2018; Bender et al., 2014; Bender et al., 2015).
Mental health risks associated with homelessness are well documented (Edidin, Ganim,
Hunter, & Garnik, 2012; Bender, Ferguson, Thompson, & Langendefer, 2014; Beharry, 2012;
Wong, Clark, & Merlotte, 2016; Kulik, Gaetz, Crowe, & Ford-Jones, 2011). It is estimated that
more than half of homeless youth have one or more mental health disorders, with depression
being the most common (Bender et al., 2015; Edidin, Ganim, Hunter, & Garnik, 2012). YEH are
clearly among the greatest in need of mental health services; however, being part of a
marginalized and underserved population often makes it much more difficult to advocate for and
obtain these essential behavioral health services (Black et al., 2018; Chevalkumar et al., 2017;
Krausz et a., 2013). It is therefore imperative to focus on factors that either amplify or abate
service engagement and mental health use.
Staff Support in Drop-In Centers
Drop-in centers provide an invaluable safety net for YEH by helping them meet both
basic needs (e.g., food, hygiene, clothing), as well as “higher-level” needs such as mental health
care, individual and group counseling, and other vital health resources (Pedersen, Tucker, Klein,
& Parast, 2016; Slesnik et al., 2016; Rice et al., (under review)). Drop-in centers are used more
often than other service settings for medical, substance use treatment, and mental health service
88
needs (Pedersen, Tucker, & Kolvachik, 2016; De Rosa et al., 1999). Unlike shelters with
restrictive rules that youth must follow (e.g., curfews, abstinence from substances), drop-in
centers are designed to alleviate barriers and take a “come as you are” approach to engaging
youth in services (Pedersen, Tucker, Klein, & Parast, 2018; Slesnick et al., 2016). Furthermore,
YEH who are able to access behavioral health and case management services at drop-in centers
demonstrate significant improvement in mental health and greater housing stability over time
compared to YEH who do not use these services (Slesnick et al., 2008). Therefore, drop-in center
staff are in the unique position to help youth transition to more higher intensity services, such as
mental health, to meet their needs, given that drop-in centers are often YEH’s main resource for
services.
To date, research on drop-in center service use among marginalized YEH groups is
extremely limited. For instance, there may be specific factors involved in sexual minority YEH’s
decision to use drop-in center services given that: they are over-represented in the YEH
population (Corliss, Goodenow, Nichols, & Austin, 2011), are at greater risk for poor mental
health, substance use, and other problems (Cochran, Stewart, Ginzler, & Cauce, 2002; Gattis,
2013); and face significant discrimination in comparison to heterosexual YEH (Gattis, 2013).
Pedersen and colleagues (2016) found that sexual minority YEH use drop-in center services at
greater rates compared to heterosexual YEH. Another study found that service use among
homeless youth generally did not differ by sexual orientation after controlling for demographics
and other factors (Tyler, Akinyemi, & Kort-Butler, 2012), it did not specifically examine the use
of drop-in centers.
Sexual minority YEH may face unique factors that influence the frequency of drop-in
center utilization or mental health service use. As such, perceptions of drop-in center
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discrimination and staff support may be particularly important determinants of utilization among
sexual minority YEH. Such knowledge would allow providers and researchers to develop
methods to better target sexual minority YEH and help them access needed care at drop-in
centers. A better understanding of who uses services, how often, and if staff relationships
influence use, would greatly help outreach and intervention efforts among the MM-YEH
population.
Perceived Discrimination in Community and Service Settings
Despite the weighty, negative impacts of discrimination in healthcare and community
settings among adults experiencing homelessness (AEH) (Writing et al., 2019; Wen, Hudan, &
Hwang, 2007), surprisingly little is known about how specific MM-YEH discriminatory
experience may influence drop-in frequency and mental health service use. MM-YEH who
belong to several disadvantaged groups may suffer aggravated and specific forms of
discrimination in consequence. Furthermore, researchers have noted the potential additive effects
of stigma and discrimination, though this is less frequently explored (Zerger et al., 2014).
Persons experiencing homelessness are among the most marginalized patient groups. Adults
experiencing homelessness tend to report high levels of unmet behavioral health needs (Krausz
et al., 2013; Rae & Reese, 2015) due in part to numerous access barriers, including perceived
discrimination in healthcare settings (Skosireva et al., 2014; Zerger et al., 2014). While the
relationship between adult homelessness, discrimination, and service use is expanding (Mejia-
Lancheros et al., 2021), the experiences of discrimination among MM-YEH and drop-in
frequency and mental health service use is not presently known or understood.
90
Current Study
This study aims to address some of these gaps in the literature by exploring if there is an
association between discrimination in service and community settings, positive staff support and
drop-in center frequency and mental health service use among MM-YEH. A key purpose of this
current study is to explore how YEH who bear multiple marginalized identities including, racial,
sexual, and gender marginalized, navigate discrimination and staff relationships when deciding
to engage and use drop-in and mental health services. We adopted the Intersectional-based Risk
Amplification and Abatement Framework to guide this work (Milburn et al., 2006). This
framework allows for a deeper understanding as to why and how discrimination (amplification)
and staff support (abatement) may contribute to unique and complicated socialization processes
for MM-YEH when engaging in drop-in center and mental health service use. Specifically, this
study addresses the following research aims:
1. To examine potential main effects between the following independent variables:
perceived discrimination in community services settings, discrimination in drop-in
centers, positive staff support and the following outcome variable: frequency of drop-in
attendance among MM-YEH.
2. To examine potential main effects between the following independent variables:
perceived discrimination in community services settings only, drop-in centers, positive
staff support and the following outcome variable: mental health service use, among MM-
YEH.
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Methods
Sample
Data was derived from a longitudinal social network study of youth experiencing
homelessness utilizing drop-in centers in Los Angeles, CA. A sample of 418 youth ages 16-24
were surveyed between October 2018 and June 2019. Participants were recruited from 3 drop-in
centers servicing YEH across 4 different waves at each of the centers. 198 participants recruited
from the 3 drop-in centers from the third wave of this study comprised the total sample for this
study. Eleven youth that were approached refused to participate in the study. Two of the centers
are located in area in Los Angeles County in which many YEH are concentrated (Rabinovitz,
Desai, Schneir, & Clark, 2010). In comparison, the third recruitment site is located in Venice, a
location that has increasingly become an area where youth congregate but does not have access
to the array of services in Hollywood (Brooks et al., 2004). Each wave of data occurred
approximately 6 months apart. All youth accessing services at the recruitment sites during the
periods of data collection were invited to participate in the study. All three drop-in centers
structure operates such that any youth who self-identifies as homeless, e.g., sleeping on the
streets, in an emergency shelter, couch surfing, or at immediate risk of being homeless) and is
between the ages of 16-24 is deemed eligible for services. Youth were invited to participate in
multiple waves, but only the fourth wave survey data was used in the current study.
Procedures
Recruitment was conducted for 14 days at each site during Wave 3 of data collection (3
months after baseline data was collected). During these periods, recruiters were present at the
agency to approach you for the duration of service provision hours. A consistent set of two
research staff members at each site were responsible for recruitment, in order to prevent youth
92
from completing the survey multiple times within each data collection period. Signed voluntary
consent was obtained from youth 18 years of age and older and informed assent was obtained
from youth 16-17 years old. The Institutional Review Board at the University waived parental
consent, as YEH under 18 years old are considered unaccompanied minors who may not have a
parent or adult guardian from whom to consent. The 60-minute survey was a computer
administered self-interview, completed at the site. Participants received $25 in gift cards as a
compensation for their time. The Institutional Review Board approved all survey items and
procedures.
Measures
Outcome Variable: Mental Health Service Use
Participants were asked, “During my time in youth services, I participated in one or more
meaningful activities, such as those listed below” and asked to check any that they participated
in. Counseling and support groups were among the listed activities. The mental health service
use dichotomous variable was created: “yes” for participants who marked counseling and support
groups among the listed activities and “no” for participants who did not.
Outcome Variable: Frequency of Drop-In Center Attendance
Participants were asked, “How often do you frequent the drop-in center?” and asked to
check one of the following responses: 1) every day 2) couple times a week 3) once a week 4)
couple times a month 5) once a month 6) when I need to 7) this is my first time. Response items
were coded dichotomously into a “daily use” for participants who responded: 1) every day or
“Weekly or less” for participants who responded: 2) couple times a week 3) once a week 4)
couple times a month 5) once a month 6) when I need to 7) this is my first time.
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Gender, Sexual Orientation, and Race/Ethnicity
Gender identity and race/ethnicity questions allowed students to mark more than one
category. For the present study, gender identity was recategorized into: 1) Male (if a participant
marked only “male”), 2) Female (if a participant marked only “female”), and 3) Non-cisgender
(if a participant marked “trans male/trans man”, “trans female/ trans woman”, “Gender
queer/Gender non-conforming” or “Different identity” in which the written response was
indicative of non-cisgender and as such this category was also included in the third category:
“Non-cisgender”). A second gender identity category was created to compare cisgender
participants (participants who endorsed 1) Male (if a participant marked “Male”) or 2) Female (if
a participant marked “Female”) to non-cisgender participants (if a participant marked “trans
male/trans man”, “trans female/ trans woman”, “Gender queer/Gender non-conforming” or
“Different identity” in which the written response was indicative of non-cisgender and as such
this category was also included in the third category: “Non-cisgender”).
The sexual orientation item, which limited participants to one response among the
following categories: 1) Gay or Lesbian, 2) Bisexual, 3) Heterosexual or Straight, 4) Questioning
or Unsure, 5) Asexual, or 6) Another Sexual Orientation. Sexual orientation was re-coded into:
1) heterosexual (if a participant marked “heterosexual”) and 2) LGB (if a participant marked any
response other than “heterosexual”), to maintain consistency with previous studies (e.g., Rice et
al. 2013, Milburn et al., 2009). Participants were given several race/ethnicity options and
instructed to “pick the one that describes you best”. Race was re-coded into: 1) Black (if a
participant identified as Black), 2) White (if a participant identified as White), 3) Latinx (if a
participant identified as Latinx) and 4) Other Race(if marked American Indian or Alaska Native,
or Asian, or Mixed Race as a category). Finally, intersecting stigmatized identities was
94
operationalized as two or more stigmatized identities across gender (i.e., cisgender, non-
cisgender), race (i.e., Black, White, Latinx, Other), and sexual orientation (i.e., LGB).
Intersecting identities were created by recoding the following variables: race/ethnicity, gender,
and sexual orientation into the following: race x sexual orientation, race x gender, and gender x
sexual orientation.
Other Socio-Demographic Variables
Length of homelessness was recoded dichotomously as: less than two years for all
participants who indicated: less than 1 month, 1-3 months, 4-6 months, 7-9 months, 10-11
months or 1-2 years and chronic/two or more years for participants who indicated: 3-4 years, 5-6
years, 7-8 years, or 9 or more years. Current housing status for the sample was recoded as: literal
homelessness (youth experiencing literal homelessness were defined as those who indicated that
they were currently staying in a shelter (emergency or temporary), hotel, motel, trailer, street,
beach, tent or campsite, abandoned building, car or bus vs. youth living with biological family,
foster family, relative, friend, group home, sober living facility, transitional living program).
Foster care involvement was assessed with dichotomous responses. Age was collected as a
continuous variable and dichotomized for analysis using the mean age (22.1) to determine the
categories. All other demographic variables were categorical.
Positive Staff Relationships
The aspect of the RAAM (Milburn et al., 2009) model targeting abatement included
whether participants identified the presence of positive and supportive (formal, e.g., staff)
relationships. This RAAM data were collected via the following variable. For positive,
supportive formal support, participants were asked: (1) During my time in youth services, I have
developed at least one relationship with a supportive and positive staff at an agency that I attend.
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Participants were asked to select one of the following responses: “yes”, “no”, or “I don’t know”.
Response items were coded dichotomously into a “yes” or “no” format.
Discrimination Variables
Participant’s perceived health service and drop-in center discriminatory experiences was
measured using the Everyday Discrimination scale (EDS) which has been widely used in studies
of discrimination and health (Williams et al. 1997; Deitch et al. 2003). The EDS was developed
as a subjective measure to capture self-reported frequency of routine, relatively subtle
discriminatory experiences in everyday social situations. The EDS has been found to be strongly
associated with institutional and interpersonal discrimination (Hughes 2003; Krieger et al. 2005)
and is accepted as a valid measure that accounts for discriminatory experiences among youth and
adults who identify with minority status (Seaton et al. 2008; Goosby et al., 2015; ). First,
participants are asked: “Can you tell me if any of the following ever happen to you?” The
original scale consists of 11 items assessing the frequency of participants’ experiences of
everyday discrimination. For the purposes of this study and based on prior studies modification
for use in health care settings (Bird et al., 2009; Peek et al., 2011), a methodological decision
was made to modify the EDS to focus on service discrimination experiences: drop-in centers and
health services (including medical, mental health, substance use treatment, and HIV/STI
treatment services) and subsequently changed ‘people’ to ‘staff’ for the drop-in center and health
service variable. Examples include: “ People act as if they think you are not smart”, “People act
as if they are afraid of you” to “Staff act as if they think you are not smart” and “Staff act as if
they are afraid of you”. For the purpose of the descriptive analyses, a community setting only
discrimination variable was created into a dichotomous variable: “yes” for participants who
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endorsed law enforcement discrimination, small business discrimination, employer
discrimination, or community discrimination only and “no” for participants who did not.
Situation-based coding, a common approaches to coding the EDS (Schulz et al., 2006;
Lewis et al., 2009; Moody et al., 2006), will be used for this study. In situation-based coding,
each survey item is dichotomized: ‘never’ = 0 and ‘ever’ = 1. Situation-based category coding
collapses everyone who experience any discrimination into one category. Responses are summed
across the items to generate a score ranging from 0-6, capturing the number of different
situations ever experienced. For this study, we will dichotomize each EDS item to ‘never’=0 and
‘ever’=1. Items will be summed (range: 0-10) to reflect the total number of discriminatory
situations ‘ever’ experienced per type: law enforcement, drop-in center, health service, employer,
business, and community. In addition, items across all 6 types of settings will be summed range:
0-60) to reflect the total number of situations ‘ever’ experienced across all settings. The
Everyday Discrimination Scale has demonstrated good reliability and validity (Taylor, Kamarck,
& Shiffman, 2004; Williams et al., 2012; Williams, Neighbors, & Jackson, 2003). In sample of
LGBT participants, Cronbach’s alpha for the discrimination scale was 0.94, and discrimination
scores were correlated positively with depressive symptoms, anxiety, and substance use
(Gamarel, Reisner, Laurenceau, Nemoto, & Operario, 2014; Gamarel, Reisner, Parsons, &
Golub, 2012; Gordon & Meyer, 2008; S. L. Reisner, White, Bradford, & Mimiaga, 2014).
Data Analysis
Data analyses was conducted using SAS software (SAS version 9.4). A statistically
accepted two-step strategy (Hosmer & Lemeshow, 2004) was used to reduce the number of
variables included in the final multivariate models in order to preserve statistical power and
degrees of freedom. Crosstabs and chi-squares were used to present the association between
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participants’ independent variables, i.e., race/ethnicity, sexual orientation, gender, positive staff
relationships, drop-in center discrimination, health service discrimination and the two outcome
variables: mental health service use and drop-in center frequency. Next, a series of bivariate
logistic regressions were run to determine significant associations (p<.10) between the
independent variables and the two outcome variables, mental health service use and drop-in
center frequency. Prevalence ratios, their 95% confidence intervals and their respective P-values
were calculated. These bivariate associations were examined in a pair-wise approach, which is
logically equivalent to the examination of a correlation matrix. Any independent variable that
was found to be significantly associated (i.e., p < .10 level) with the specific dependent variable
was retained in the final multivariate logistic regression models (Hosmer & Lemeshow, 2004).
Although the standard threshold is p < .05, the Hosmer & Lemeshow strategy (2004) allows for
it to be increased to p < .10 following the pair-wise approach.
Results
Table 4.1 presents descriptive statistics. The sample is diverse; YEH endorsed various
marginalized identities. The majority of youth identified as racial/ethnic marginalized and about
one in five youth (20.81%) identified as White. Both youth identifying with a sexual minority or
gender minority status were well represented in the study. A little over half of the sample
identified as LGB (N = 105, 53.03%) and a substantial proportion of the sample identified as
Non-Cisgender (N = 29, 14.66%). The average age for the sample is 22.1 years old (SD = 2.1).
Slightly over one-third (33.68%) of the sample reported they have been homeless for two or
more years. In regard to discrimination experiences, a little more than one-third (33.6%) of youth
reported discrimination in drop-in centers and slightly less than one-third (30.81%) of youth
reported discrimination in health, mental health, and substance use treatment center settings. A
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strong majority (69.19%) of YEH reported experiencing discrimination in community settings
only (law enforcement, community, small business, and employer settings). More than half of
youth reported a positive staff relationship (62.69%). Roughly one in four participants (25.26%)
indicated frequenting the drop-in center daily and 17.68% of youth reported using mental health
services.
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Table 4.1
Descriptive Statistics of Youth Experiencing Homelessness (n =198)
Demographics N %
Race/ethnicity (missing 6)
Black 73 37.06
Latinx 21 10.66
Mixed 50 25.38
White 41 20.81
Other 12 6.09
Gender (missing 6)
Female 45 22.73
Male 124 62.63
Non-cisgender 29 14.66
Sexual orientation (missing 7)
LGB 105 70.48
Heterosexual 93 56.99
Foster care history
Yes 118 66.67
No 59 33.33
Demographics M SD
Age 22.1 2.1
Demographics N %
Time homeless
Less than two years 128 66.32
Two or more years 65 33.68
Drop-in center discrimination
No 131 66.16
Yes 67 33.84
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Demographics N %
Health Service Discrimination
No 137 69.19
Yes 61 30.81
Community settings only discrimination
No 61 30.81
Yes 137 69.19
Positive staff relationship
No
72 37.31
Yes
121 62.69
Drop-in frequency
Daily use
48 25.26
Weekly or less
142 74.74
Mental health service use
No
163 82.32
Yes
35 17.68
Note. LGB = Lesbian, Gay, Bisexual
Mental Health Service Use
Table 4.2 presents the chi-squares for mental health service use. Significant differences
were found when comparing mental health service use between LGB YEH and heterosexual
YEH. Specifically, YEH who identify as LGB were significantly more likely to use mental
health services (23.8% vs. 10.8% vs. 85.71%, X
2
= 5.78, p < .01). Significant differences were
also found in regard to staff support. In comparison to YEH who did not endorse a positive staff
relationship, youth who reported a positive staff in their life were more likely to use mental
health services (23.9% vs. 8.3%, X
2
= 7.43, p < .002). As shown in Table 2., mental health
service use was not significantly related to race/ethnicity, gender, or whether or not youth
endorsed drop-in center or health service discrimination.
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Table 4.2
Mental Health Service Use of Youth Experiencing Homelessness (n = 35)
N % Chi Squared
Staff support (missing = 6)
Yes 29 23.97** 7.43
No 6 8.33
Drop in center discrimination
(missing = 7)
Yes 16 23.88 2.68
No 19 14.5
Health service discrimination
(missing = 6)
Yes 8 13.11 1.26
No 27 19.71
Race/ethnicity (missing = 6)
Black 11 15.07
White 10 24.39 1.65
Latinx 4 19.05
Other 10 16.13
Sexual orientation (missing = 7)
LGB 25 23.82*
Heterosexual 10 10.75 5.78
Gender (missing = 6)
Male 22 17.74
Female 4 8.89 5.94
Non-cisgender 9 31.03
Note. LGB = Lesbian, Gay, Bisexual
Table 4.3. presents findings for mental health service use among MM-YEH. Significant
differences were found at the intersection of sexual orientation and race. Specifically, youth
identifying as both White and LGB were more likely to use mental health services than youth
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identifying as Black and LGB, Latinx and LGB, and Mixed and LGB (45% vs. 15.4% vs. 25%
vs. 21.2% X
2
= 15.02, p < .03). No significant differences were found when examining the
intersection of sexual orientation and gender and the intersection of gender and race.
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Table 4.3
Mental Health Service Use Among Multiple-Marginalized Youth Experiencing Homelessness (n
= 35)
Demographics N % Chi Squared
Sexual orientation x race
(missing = 1)
Heterosexual x Black 5 14.71*
Heterosexual x White 1 4.76 15.02
Heterosexual x Latinx 1 11.11
Heterosexual x other 3 10.34
LGBQ x Black 6 15.38
LGBQ x White 9 45
LGBQ x Latinx 3 25
LGBQ x other 7 21.21
Sexual orientation x gender
(missing = 1)
Heterosexual x male 9 12.68
Heterosexual x female 0 0 10.86
Heterosexual x non-
cisgender/other
1 20
LGBQ x male 13 24.53
LGBQx female 4 14.29
LGBQ x non-cisgender/other 8 33.33
Gender x race (missing = 1)
Male x Black 8 17.78
Male x White 3 16.67 11.78
Male x Latinx 4 26.67
Male x other 7 15.22
Female x Black 1 4.55
Female x White 2 16.67
Female x Latinx 0 0
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Demographics N % Chi Squared
Female x other 1 16.67
Non-cis/other x Black 2 33.33
Non-cis/other x White 5 45.45
Non-cis x Latinx 0 0
Non-cis/other x other race 2 20
Note. LGBQ = Lesbian, Gay, Bisexual, Queer
Bivariate associations among the main variables and the outcome variable: mental health
service use are presented in Table 4.4. Youth who identify as LGB were more likely (OR = 2.39
95%CI = 1.07, 5.38 p <.02) to use mental health services than heterosexual YEH. In addition,
youth who report a positive staff relationship are more likely (OR = 3.12 95%CI =1.10, 7.42, p
<.05) to use mental health services than YEH who do not hav e a positive staff relationship.
Table 4.4
Bivariate Logistic Regressions of Mental Health Service Use
Discrimination/support OR
95% CI
Drop-in center
LGB
2.39 * [1.07, 5.38]
Drop-in center discrimination
1.60
[.75, 3.42]
-2 log likelihood
Health service
LGB
2.69 * [1.21, 5.98]
Health service discrimination
0.57
[.24, 1.36]
Staff support
Positive staff support
3.12*
[1.10, 7.42]
-2 log likelihood
177.30
Note. *p < .05. **p < .01. ***p < .001.
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Table 4.5 presents the multivariate models for the outcome variable: mental health
service use. In regard to sexual orientation, LGB youth (OR = 2.67, 95%CI = 1.11, 6.45, p <.02)
were more likely to use mental health services, compared to heterosexual youth. In addition,
youth who reported having a positive staff relationship were more likely (OR = 2.98, 95%CI =
1.12, 7.90, p <.02) The model showed no significant associations for the following covariates:
perceived discrimination by drop-in center staff, gender, race/ethnicity, or time homeless.
Table 4.5
Multivariate Logistic Regression of Mental Health Service Use Among Youth
Experiencing Homelessness (n = 198)
OR 95% CI
LGB 2.67 * [1.11, 6.45] 161.85 p = .02
Drop-in center discrimination 1.24 [0.55, 2.79]
Male 0.92
[0.33, 2.61]
Female 0.32
[0.08, 1.23]
White 1.64
[0.57, 4.69]
Mixed 0.99
[.37, 2.68]
Latinx 1.11
[.29, 4.22]
2 or more years homeless 1.33 [.59, 3.01]
Staff support 2.98 * [1.12, 7.90]
-2 log likelihood 221.62
Note. LGB = Lesbian, Gay, Bisexual
*p < .05. **p < .01. ***p < .001.
Table 4.6 presents the multivariate models for the outcome variable: mental health
service use. In regard to sexual orientation, LGB youth (OR = 2.94, 95%CI = 1.23, 7.05, p <.01)
were more likely to use mental health services, compared to heterosexual youth. In addition,
youth who reported having a positive staff relationship were more likely (OR = 3.12, 95%CI =
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1.17, 8.31, p <.01) The model showed no significant associations for the following covariates:
health service discrimination, gender, race/ethnicity, or time homeless.
Table 4.6
Multivariate Logistic Regression of Mental Health Service Use Among Youth Experiencing
Homelessness (n = 198)
OR 95% CI
LGB 2.94 * [1.23, 7.05]
Health service discrimination 0.47
[.19, 1.18]
Male 0.90
[0.31, 2.58]
Female 0.28
[0.07, 1.11]
White 1.71
[0.59, 4.94]
Mixed 1.05
[.39, 2.87]
Latinx 0.97
[.25, 3.73]
2 or more years homeless 1.35
[.59, 3.05]
Staff support 3.12 * [1.17, 8.31]
-2 log likelihood 159.32
Note. LGB = Lesbian, Gay, Bisexual
*p < .05. **p < .01. ***p < .001.
Frequency of Drop-In Attendance
Table 4.7 presents the chi-squares for drop-in frequency. YEH who endorsed a positive
staff relationship were significantly more likely to frequent drop-in centers on a daily basis
compared to participants with no positive staff relationships (33.06% vs. 11.76%, X
2
= 10.42, p <
.01). YEH who reported discrimination at drop-in centers were significantly more likely to
frequent the drop-in center daily (35.4% vs. 20%, X
2
= 5.36, p < .05) compared to YEH who did
not report drop-in center discrimination. YEH who reported discrimination in community
settings only were significantly more likely to frequent the drop-in center daily (77.9% vs.
59.5%, X
2
= 6.09, p < .01) compared to YEH who did not report community settings only
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discrimination. Drop-in frequency was not significantly related to health service discrimination,
race/ethnicity, sexual orientation or gender. However, sexual orientation and gender trended
toward significance (see Table 7). No significant differences were found when examining the
intersection of sexual orientation and race or the intersection of sexual orientation and gender or
the intersection of gender and race.
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Table 4.7
Frequency of Drop-In Center Attendance Among Youth Experiencing Homelessness (n = 198)
Discrimination/support N % Chi Squared
Staff support (missing = 6)
Yes 40 33.06** 10.42
No 8 11.76
Drop in center discrimination (missing
= 7)
Yes 23 35.38* 5.36
No 25 20
Health service discrimination (missing
= 6)
Yes 18 30.51 1.26
No 30 22.9
Community settings only
discrimination (missing = 6)
Yes 40 30.8* 5.43
No 8 14.04
Demographics N % Chi Squared
Race/ethnicity (missing = 6)
Black 16 23.19 2.28
White 14 34.15
Latinx 5 25
Other 13 21.67
Sexual orientation (missing = 7)
LGB 31 30.69 3.37
Heterosexual 17 19.1
Gender (missing = 6)
Male 24 20.17 4.82
Female 13 30.95
Non-cisgender 11 37.93
Note. LGB = Lesbian, Gay, Bisexual
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Bivariate associations among the main variables and the outcome variable: drop-in center
frequency are presented in Table 4.8. Youth who reported a positive staff relationship were
more likely (OR = 3.70 95%CI = 1.14, 6.07 p <.002) to frequent the drop-in center daily than
youth who do not have a positive staff relationship. In addition, youth who report drop-in center
discrimination were more likely (OR = 2.19 95%CI = 1.14, 6.07, p <.02) to frequent the drop-in
center daily than YEH who did not report drop-in center discrimination. Youth who report
discrimination in community settings only were more likely to (OR = 2.63 95%CI = 1.19, 4.88, p
<.01) to frequent the drop-in center daily than YEH who did not report discrimination in
community settings only.
Table 4.8
Bivariate Logistic Regressions of Daily Drop-In Center Attendance
Discrimination/support OR
95% CI
Drop-in center
Drop-in center discrimination 2.19*
[1.12, 4.29]
-2 log likelihood
Community setting
Community settings only discrimination 2.63*
[1.19, 4.88]
Staff support
Positive staff support 3.70**
[1.14, 6.07]
-2 log likelihood 209.57
Note. *p < .05. **p < .01. ***p < .001.
Table 4.9 presents the multivariate model for the outcome variable: drop-in frequency. In
regard to staff support, youth who endorsed a positive staff relationship (OR = 3.57, 95%CI =
1.52, 8.43, p <.003) were more likely to frequent the drop-in center daily, compared to youth
without a positive staff relationship. After controlling for other independent variables, the
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multivariate model found no significant associations for drop-in center discrimination. Similarly,
the model showed no significant associations for the following covariates: race/ethnicity, sexual
orientation, gender, or time homeless.
Table 4.9
Multivariate Logistic Regression of Daily Drop-In Center Attendance (n = 198)
OR 95% CI
White 1.52
[.60, 3.83]
Black 0.99
[.44, 2.26]
Drop-in discrimination 1.97
[.95, 4.09] 0.07
LGB 1.39
[0.66, 2.94]
Male 0.62
[0.29, 1.32]
2 or more years homeless 0.54
[.25, 1.19]
Staff support 3.57 ** [1.52, 8.43]
-2 log likelihood 190.75
Note. LGB = Lesbian, Gay, Bisexual
*p < .05. **p < .01. ***p < .001.
Table 4.10 presents the second multivariate model for the outcome variable: drop-in
center frequency. In regard to staff support, youth who endorsed a positive staff relationship (OR
= 3.47, 95%CI = 1.48, 8.15, p <.004) were more likely to frequent the drop-in center daily,
compared to youth without positive staff support. In addition, youth who reported community
settings only discrimination were more likely (OR = 2.53, 95% CI = 1.03, 6.16, p <.03) to
frequent the drop-in center daily compared to youth who did not report community settings only
discrimination. The model showed no significant associations for the following covariates:
race/ethnicity, sexual orientation, gender, or time homeless.
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Table 4.10
Multivariate Logistic Regression of Daily Drop-In Center Attendance (n = 198)
OR 95% CI
White 1.56
[.60, 3.83]
Black 1.16
[.44, 2.26]
Community discrimination 2.53
[1.03, 6.16] 0.07
LGB 1.39
[0.66, 2.94]
Male 0.62
[0.29, 1.32]
2 or more years homeless 0.54
[.25, 1.19]
Staff support 3.57 ** [1.52, 8.43]
-2 log likelihood 190.75
Note. LGB = Lesbian, Gay, Bisexual
*p < .05. **p < .01. ***p < .001.
Discussion
This study was designed to build on current YEH service engagement literature by
examining the association between positive staff support, experiences of discrimination and
drop-in frequency and mental health service use. The findings build upon preliminary evidence
from the previous studies and offers promise for using an Intersectional-based RAAM model to
understand how both discriminatory experiences and staff support influence YEH service
engagement. Our results highlight key areas for drop-in and mental health service engagement
outreach efforts. As such, we offer specific recommendations for intervention.
It is deeply troubling to discover that YEH experience discrimination in the community,
e.g., law enforcement, small business, employer, and community – at alarmingly high rates
(69.19%). Coupled with our previous studies findings on drop-in center (33.8%) and health
service (30.8%) discrimination prevalence rates, YEH’ resilience is remarkable as indicated by
their openness to continue making connections with supportive staff, as found in our study,
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despite experiencing discrimination across a wide variety of service and community settings. It is
abundantly clear that providers and community stakeholders must all take accountability with
recognizing and mitigating the effects of discrimination. Drop-in staff should develop a deeper
understanding of how discrimination in community and service settings harm YEH subgroups,
so as to take shared responsibility in reducing the effects. As Ross-Sheriff and colleagues
suggested for social workers (2012), we propose that drop-in center staff adopt an action-
oriented, personal accountability approach by examining their own behaviors to mitigate the
debilitating effects and take steps to combat discrimination in drop-in centers. Future research
should examine the specific resilience factors among YEH as they experience a bombardment of
discrimination across community and service settings.
One notable finding is that sexual orientation seems to influence mental health service
use among the YEH population in our study. The fact that sexual minority YEH reported
increased mental health service use compared to their heterosexual counterparts points to LGB
1YEH resilience particularly in light of the fact that this minority YEH subgroup were
significantly more likely to report discrimination in our previous study. One explanation for
these sexual orientation differences may be attributed to the long sought after progress drop-in
centers have adopted to incorporate LGBT affirming policies and practices (Slesnick et al., 2008;
2016; Maccio & Ferguson, 2016). In 2009, a coalition of organizations supporting LGBT
homeless youth published a set of guidelines entitled, “National Recommended Best Practices
for Serving LGBT Homeless Youth” (National Alliance to End Homelessness, 2009). They put
forth LGBT affirming recommendations that employees serving homeless LGBT youth should
incorporate, including: “Support their access to education, medical care, and mental health care”
(National Alliance to End Homelessness, 2009). In addition, it may be that LGB-YEH are
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feeling accepted and supported by specific staff in the center which positively influences mental
health service use.
Another promising finding was that daily drop-in center use did not significantly differ
by sexual minority, gender, race/ethnicity or other demographic characteristics. This is an
encouraging finding in that it suggests that the low barrier, “come as you are” approach typically
taken by drop-in centers is effective in encouraging a diverse cross-section of the YEH
population to engage in services (Slesnick et al., 2016). It is important to note that the study only
sampled drop-in center utilizing YEH. We still do not know about how discrimination
experiences shape drop-in and service engagement for disconnected YEH. It has been suggested
that service-disconnected YEH are likely different from those who already access services
(Kryda and Compton 2009; Sowell et al. 2004) and may have greater need for assistance. For
example, Kryda and Compton (2009) found that service-disconnected YEH have more severe
substance use and mental health problems compared to those service-connected YEH. Similarly,
our findings. Additional qualitative data efforts are needed to identify the specific discriminatory
experiences among MM-YEH that are prone to service-disconnection.
The multivariate finding offers additional evidence for the importance of drop-in center
staff and utilizing these positive relationships to facilitate both drop-in engagement and higher-
level service use for YEH. This result is in keeping with previous studies that have also found a
positive association between service engagement and positive staff relationships (Barman-
Adhikari et al., 2016; Holguin et al., (under review)). Drop-in center staff that demonstrate
respect, empathy, trustworthiness, and are accepting of youth without judgment, enable YEH’
drop-in center and service use (Pedersen et al., 2016). Given high rates of behavioral health
problems among YEH (Huba et al. 2000; Robertson 2004; Wenzel et al. 2010; Nyamathi et al.
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2012; Tucker et al. 2012; Bender et al. 2015), identifying supports that can facilitate drop-in
center and service use is essential. Drop-in center staff are in a key position to establish
meaningful, supportive connections with these youth and honoring their unique marginalized
experiences. Our results suggest that establishing such supportive connections may be an
important component of achieving ongoing engagement of these youth in needed services. It is
important to note that the interaction effect that explored LGB and race was no longer significant
at the multivariate level. This could be attributed to a spurious correlation with staff relationships
only found at the bivariate level. Alternatively, future studies should incorporate a greater sample
that is representative of all MM-YEH groups to account for small cell sizes.
This finding should also be accounted for in conjunction with the previous chapter’s
finding of the high prevalence (60%) of discrimination by drop-in center staff among YEH.
Taken together, these two findings are particularly salient and further supports the use of an
Intersectional-based RAAM framework. Staff support seems to abate risk for YEH as evidenced
by increased drop-in center attendance and mental health service use. The fact that these
supportive relationships are occurring while YEH have to contend with discrimination by drop-in
center staff is in need of further investigation. Specifically, we concur with policymakers and
scholars who emphasize the necessity for more research on marginalized populations at the
intersection of race, gender, and sexual identity (Institute of Medicine, 2019; Mollon, 2012),
particularly with service-disconnected YEH. Future studies should continue to examine how: 1)
discriminatory experiences may amplify risk associated with service engagement and mental
health use, 2) positive staff involvement may abate risk and promote service engagement and
mental health use, and 3) YEH carrying multiple marginalized identities, discriminatory and
service use experiences, may be uniquely shaped across variant community and service
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environments. The use of in-depth interviewing and focus groups can provide insight into
specific resilience factors and unique challenges related to service engagement and mental health
use among MM-YEH. The findings ultimately point to the organizational importance of drop-in
centers and service delivery approaches as key factors in reducing experiences of discrimination
among YEH.
Limitations
The findings of this study should be examined within the context of its limitations. First,
the study is cross-sectional and therefore causality cannot be determined between the
associations between the independent and dependent variables. Second, although an abundance
of evidence pointing to the disproportionate risk of mental health issues among YEH (Edidin,
Hunter, & Karnik, 2012; Wenzel et al. 2010; Nyamathi et al. 2012; Tucker et al. 2012; Bender et
al. 2015), the current study did not measure mental health symptoms among the sample. Our data
was derived from a longitudinal YEH social network study. The larger longitudinal study did
include scales to measure depression and post-traumatic stress symptoms and preliminary data
indicates both high depression (X%) and post-traumatic stress (X%) symptomatic experience
among the total YEH population. Third, the initial incongruent finding that YEH who endorse
drop-in center discrimination is associated with increased drop-in center attendance at the
bivariate level may be indicative of a sample bias. Our sample does not include YEH who
experience discrimination and do not return. It is possible that youth may experience
discrimination at one drop-in center and subsequently choose to attend a different drop-in center
on a daily basis. A related fourth limitation is that daily use at drop-in centers may be associated
with a high need for basic services, e.g., food, clothing, safety; however, this may not necessitate
that YEH are treated well. Again, this underscores the resilience of YEH who attend drop-in
116
centers in spite of discrimination. These findings should be considered with the understanding
that we did not collect data on drop-in center staff reporting. We relied solely on YEH self-
reporting to align with our intent to understand the discriminatory experiences of YEH from their
perspective. Future studies may want to include perceived experiences of discrimination in drop-
in centers from the perspective of staff.
Conclusion
Our study suggests that YEH navigate complex health and social discriminatory
challenges by drawing on their resilience and social connections. As coping and resilience are
shaped by individuals and their cultures and contexts (Ungar, 2008), our findings expose unique,
culturally meaningful ways resilience among MM-YEH, such as relationship-building with staff,
occur even in the face of discrimination. Even in the face of the many and varying complexities
inherent in studying a hidden and discriminated group of multiply marginalized youth
experiencing homelessness, the findings from this current study provides a call to action to
researchers to continue measuring the impact of discriminatory social environments, and the
unique interactions and relationships that exist within these environments, on service
engagement and use. Thus, we advocate for research, policy, and practice that focus on how
drop-in centers as critical gateways to necessary mental health services and serve as primary
prevention environments against pervasive and toxic forms of racism, heterosexism, and
cisgender normativity. Researchers, providers, and other stakeholders should not be satisfied
with YEH simply surviving in our service systems; instead, it is incumbent upon all of us to
target protective factors, such as positive staff support, that may amplify service engagement,
abate further risk, and foster YEH’s resilience and ability to thrive in these systems.
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Chapter 5: Discussion
This discussion will provide: 1) a brief overview of the specific aims and main findings
for the three previous studies, 2) an overview of the overarching themes: a) a strong case to
expand upon resilience and focus on positive staff support among MM-YEH, b) enhanced
support for multiple marginalized LBG and non-cisgender YEH community and, c) evidence in
favor of an Intersectional-based Risk Amplification and Abatement framework (RAAM), - that
arose across all three studies’ findings, 3) research, program, and policy recommendations across
the three overarching themes, and a 4) conclusion.
Chapter 2 Aims
The specific aims for Chapter 2 were as follows: 1. To identify and understand perceived
discrimination prevalence of intersecting youth experiencing homelessness, including: which
sub-groups are most at risk and types of service and community settings, e.g., law enforcement,
drop-in centers, health and behavioral services, employer and community, perceived as
discriminatory. 2. To identify and understand the main reason for perceived discrimination
among YEH intersecting sub-groups.
Main Findings For Chapter 2
The main findings for Chapter 2 are as follows:
1. Law Enforcement - YEH who identify as LGBQ and Male were more likely than
their heterosexual peers (77.36 vs. 57.75%, X
2
= 15.50,, p < .01) and YEH who
identify as LGBQ and female were more likely than their heterosexual female
counterparts (75 vs. 41.18%, X
2
= 15.50, p < .01) to report perceived discrimination
from law enforcement. The majority of Black heterosexual YEH and Black LGBQ
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YEH (67.65% and 71.79% X
2
= 8.81, p < .27) similarly reported law enforcement
discrimination.
2. Drop-In Centers - YEH who identified as Other Race and LGBT were more likely
than their Other Race Heterosexual peers (51.52 vs. 20.69%, X
2
= 14.74, p < .01) to
report drop-in center discrimination. It is worth noting that both Black LGBQ YEH
and Black Heterosexual YEH endorsed drop-in center discrimination at relatively
similar rates (33.33% vs 26.47%, X
2
= 14.74, p < .01). In addition YEH who identified
as LGB and Male were more likely than their heterosexual peers (47.16 vs. 22.54%,
X
2
= 12.48, p < .01) were more likely to report drop-in center discrimination. YEH
who identify as Heterosexual and Non-cisgender were the intersected group most
likely to report discrimination in drop-in centers. In fact, the majority of
Heterosexual, Non-Cisgender YEH (60%, X
2
= 12.48, p < .01) were more likely to
report drop-in center discrimination than other intersected YEH peers.
3. Employment - Black LGBT YEH (51.28 vs. 32.35%, X
2
= 14.57, p < .01), Other Race
LGBT YEH (48.48 vs. 17.24%, X
2
= 14.57, p < .01), and White LGBT YEH (40 vs.
28.57%, X
2
= 14.57, p < .01) were more likely to report discrimination in employer
settings than their heterosexual YEH counterparts. Similarly YEH who identify as
LGBT and Male, (47.17 vs. 25.35%, X
2
= 12.37, p < .01) and LGBQ and Female
(53.57 vs. 25.53%, X
2
= 12.37, p < .01) were more likely to report employer based
discrimination than their heterosexual YEH peers, with 53.57% of LGBT Female
YEH reporting perceived discrimination by employers.
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4. Small Businesses - LGBT YEH who identify as Black (56.41 vs. 29.41%, X
2
= 15.39,
p < .01) or other race (50 vs. 27.59%, X
2
= 15.39, p < .01), were more likely to report
perceived small business discrimination than their heterosexual peers.
5. Community Settings - In regard to discrimination in community settings, significant
differences were also found when examining the intersection of sexual orientation
and race with sexual minority YEH who identify as Black (56.21 vs. 26.47%, X
2
=
24.92, p < .01), White (55 vs. 28.57%, X
2
= 24.92, p < .01), or other race (60.61 vs.
31.03%, X
2
=, 24.92 p < .01), were more likely to report perceived small business
discrimination than their heterosexual peers.
6. Main Reason for Discrimination - Race was reported as the main factor for
discrimination (N = 66; 51.9%) among all YEH participants who endorsed perceived
discrimination of any type. Sexual Orientation (N = 49, 38.58%) and Gender (N = 45,
35.43%) were also listed among the top five reasons for perceived discrimination
among YEH who reported discrimination of any type.
Chapter 3 Aims
Relying upon Intersectionality and RAAM key domains, Chapter 3 focused on the
following specific aims: 1. To identify which YEH subgroups are more likely to have a positive
staff support. 2. To examine potential main effects between perceived discrimination and
positive staff support.
Main Findings for Chapter 3
1. Descriptive findings - a little over one-third (33.68%) of the sample reporting they
have been homeless for two or more years. Slightly over one-third (33.6%) of youth
reported discrimination in drop-in centers. Similarly, a little less than one-third
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(30.81%) of youth reported discrimination in health, mental health, and substance use
treatment center settings. Although the majority of youth reported a positive staff
relationship (62.69%), over one-third (37.31%) reported the absence of a positive
staff relationship.
2. Positive Staff Support - In comparison to non-cisgender youth, cisgender youth were
less likely to have a positive staff relationship (58.79% vs. 85.71%, X
2
= 7.42, p <
.01). Positive staff relationship was not significantly related to race/ethnicity or sexual
orientation as a main effect.
3. Multivariate findings – The first multivariate model presented revealed that gender
identity was significantly associated with a positive staff relationship. In regard to
gender, cisgender youth (OR = .30, 95%CI = .09, .95, p <.05) were less likely to have
a positive staff relationship, compared to non-cisgender youth. The model showed no
significant associations for the following covariates: drop-in center discrimination,
sexual orientation, foster care history, race/ethnicity. The second multivariate model
showed that gender identity was significantly associated with the presence of positive
staff relationships. In regard to gender, cisgender youth (OR = .30, 95%CI = .09, .95,
p <.05) were less likely to have a positive staff relationship, compared to non-
cisgender youth. The model showed no significant associations for the following
covariates: health service discrimination, sexual orientation, foster care history,
race/ethnicity.
Chapter 4 Aims
Chapter 4 addressed the following research aims: 1. To examine potential main effects
between the following independent variables: perceived discrimination in community services
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settings only, drop-in centers, positive staff support and the following outcome variable: drop-in
frequency, among MM-YEH. 2. To examine potential main effects between the following
independent variables: perceived discrimination in community services settings only, drop-in
centers, positive staff support and the following outcome variable: mental health service use,
among MM-YEH.
Main Findings for Chapter 4
1. Descriptive findings - Roughly one in four participants (25.26%) indicated
frequenting the drop-in center daily and 17.68% of youth reported using mental
health services.
2. Multivariate findings for the outcome variable: mental health service use - In regard
to sexual orientation, LGB youth (OR = 2.67, 95%CI = 1.11, 6.45, p <.02) were more
likely to use mental health services, compared to heterosexual youth. In addition,
youth who reported having a positive staff relationship were more likely (OR = 2.98,
95%CI = 1.12, 7.90, p <.02) The model showed no significant associations for the
following covariates: drop-in center discrimination, gender, race/ethnicity, or time
homeless. In regard to sexual orientation, LGB youth (OR = 2.94, 95%CI = 1.23,
7.05, p <.01) were more likely to use mental health services, compared to
heterosexual youth. In addition, youth who reported having a positive staff
relationship were more likely (OR = 3.12, 95%CI = 1.17, 8.31, p <.01) The model
showed no significant associations for the following covariates: health service
discrimination, gender, race/ethnicity, or time homeless.
3. Multivariate findings for the outcome variable: drop-in center frequency - In regard to
staff support, youth who endorsed a positive staff relationship (OR = 3.57, 95%CI =
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1.52, 8.43, p <.003) were more likely to frequent the drop-in center daily, compared
to youth without a positive staff relationship. After controlling for other independent
variables, the multivariate model found no significant associations for drop-in center
discrimination. Similarly, the model showed no significant associations for the
following covariates: race/ethnicity, sexual orientation, gender, or time homeless. In
regard to staff support, youth who endorsed a positive staff relationship (OR = 3.47,
95%CI = 1.48, 8.15, p <.004) were more likely to frequent the drop-in center daily,
compared to youth without positive staff support. In addition, youth who reported
community settings only discrimination were more likely (OR = 2.53, 95% CI = 1.03,
6.16, p <.03) to frequent the drop-in center daily compared to youth who did not
report community settings only discrimination. The model showed no significant
associations for the following covariates: race/ethnicity, sexual orientation, gender, or
time homeless.
Resilience and Positive Staff Support
Research Implications
A large portion of YEH research tends to highlight risk behaviors (Tyler & Smitz, 2018;
Halcon & Lifson, 2018; Solorio et al., 2008; Shillington, Bousman, & Clapp, 2009) and negative
outcomes (Tyler & Melander, 2010; O’Brien, Edinburgh, Barnes, & McRee, 2020; Cauce et al.,
2000), and to a much lesser extent, positive outcomes (Bender et al., 2007; Lee, Liang,
Rotheram-Borus, & Milburn, 2011). A small body of literature has begun to focus on resilience
within this population, and it reveals that many overcome the adversity they face (Kidd &
Shahaar, 2008; Toro, Lesperance, & Baciszewski, 2011). This research offers a paradigm shift
from a deficit- to a strength-based perspective, and several scholars have recommended
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resilience-based policy and service innovations to improve outcomes for these youth (Cronley &
Evans; 2017; Dan, 2014; Bassuk, 2010).
For the purposes of this discussion, resilience is conceptualized as a “a process of
adaptation” rather than a static concept (Ungar, 2015, pg. 4) and this process is commonly
understood within a developmental framework of how youth respond to adverse circumstances
and events over time. Youth resilience consists of both internal and external factors (Luthar,
Cicchetti, & Becker, 2000; Ungar, 2015). Internal resources can include self-compassion (Neff &
McGehee, 2010), self-monitoring/regulating (Buckner, Mezzacappa, & Beardslee, 2003; Herrick
et al., 2011), or spirituality (Cotton, Larkin, Hoopes, Cromer, & Rosenthal, 2005), while external
factors may be positive role models (Yancey, Grant, Kurosky, Kravitz-Wirtz, & Mistry, 2011),
social support (Herrick et al., 2011), and parental monitoring (Fergus & Zimmerman, 2005). For
the purpose of this dissertation, we focused our attention external factors, and more specifically,
social support (positive staff relationships).
Our findings are consistent with a growing body of work focused on the importance of
YEH’ social networks as protective factors (De La Haye et al. 2012; Falci et al. 2011; Johnson,
Whitbeck, and Hoyt 2005; Milburn et al. 2005; Rice, Milburn, and Rotheram-Borus 2007; Rice,
Milburn, and Monro 2011; Tyler and Melander 2011; Wenzel et al. 2010; Wenzel et al. 2012). A
shift toward resilience is critical. The studies conducted in this dissertation provide strong
evidence of resilience among YEH, particularly MM-YEH. Overall, the dissertation indicates
that MM-YEH endorse positive staff relationships and the presence of these relationships is
associated with increased mental health services and drop-in center use. In considering the
importance of formal adult social networks; however, resilience researchers may want to conduct
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more sophisticated network analyses to understand how these relationships help MM-YEH
access and engage in services.
Researchers ought to expand their focus from deficit-based narratives and negative
outcomes to resilience and adaptive coping among youth experiencing homelessness. While a
core set of researchers is carrying out rigorous scholarship in this area, they are limited in
number. It is likely that such a narrow field will be unable to challenge the current knowledge
base, which remains biased toward deviancy. Moreover, this common narrative continues to
marginalize YEH. We call on researchers to confront and challenge their own biases and open
their research agenda to multiple and intersecting ways of understanding the experiences of these
young people, in ways, which are both humanizing and empowering.
In addition, resilience research should advance from exploratory, correlative, and needs
assessment-type methodologies toward more experimental and intervention-oriented research.
Though we have convincing evidence of heterogeneity and resilience among many homeless
youth, we lack a set of evidence-based practices utilizing this knowledge base. Few interventions
have been developed and tested; thus, practitioners are not able to adopt evidence-based practices
that leverage the inherent resilience within many youth.
Program Implications
These findings have important programmatic implications for those working with MM-
YEH. Along with broader efforts to combat discrimination across community and service
settings toward YEH, drop-in services need to be structured to promote inclusion where MM-
YEH are more integrated and connected. Furthermore, program administrators and leaders
should focus on: 1) identifying who the direct service providers are that have positive
relationships with MM-YEH 2) investing both time and funding for these specific providers that
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promote career/leadership pathways and foster their ability to disseminate their cultural
knowledge and skills set.
Such investment will demonstrate a greater commitment toward creating and sustaining a
drop-in center environment that universally upholds anti-discrimination policies. Fostering a
strengths-based MM-YEH centered environment must begin with understanding the unique
experiences, including specific discriminatory experiences of MM-YEH. These MM-YEH
affirming conversations may help to promote empathy and serve as a starting point to help drive
MM-YEH centered drop-in policies in which not only is discrimination addressed but, MM-YEH
specific needs are met. Furthermore, hiring and supporting staff that more accurately reflect the
marginalized identities and lived experiences of MM-YEH may help to build greater trust with
the MM-YEH community and offer a clear signal that equitable diversity and inclusion is a high
priority for drop-in centers.
Policy Implications
Finally, our findings have crucial policy implications that advocate for a need to move
beyond individual-centered resiliency research and programmatic efforts. We call on policy
makers to target the broader systems of inequality that perpetuate the disproportionate rates of
homelessness among MM-YEH. Segregation, police brutality, mass incarceration, inequitable
access to healthcare, and employment, education, health and housing discrimination all
negatively affect multiply marginalized communities, and have throughout American
history. Our discriminatory prevalence findings demonstrated that MM-YEH are no exception.
Understanding and combatting these broad systemic forces underscores the necessity of policy
solutions that create equity across community and service sectors for MM-YEH. We should not
continue to rest our laurels on MM-YEH’ amazing resilience in the face of persistent, ongoing
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discrimination. It is incumbent upon us to acknowledge oppressive systemic forces that create,
perpetuate and permit this discrimination from occurring in the first place and develop policies
that uphold and embrace the rights, protections, and voices of MM-YEH.
Multiple Marginalized LGB and Non-Cisgender Youth Experiencing Homelessness
Research Implications
It is impossible to understand the experience of LGBT and non-cisgender YEH without
first acknowledging the stigmatized status of social deviance historically attributed to both YEH
as well as LGB and transgender and gender expansive people in the U.S. Generally, society still
holds this deficit and deviant-based perception of YEH. As such, societal reforms have
historically centered on mechanisms of control given the authority that law enforcement and
court officials have in controlling these youth (Libertoff, 1980). While being homeless in itself is
not technically a criminal matter today, people experiencing homelessness are criminalized for
conducting activities necessary for daily living and survival. Laws restrict where they can sleep,
camp, ask for money, obtain food, and even sit down (National Law Center on Homelessness
and Poverty, 2016).
Just as YEH have historically been criminalized based on their housing status,
transgender and gender expansive individuals have also been pathologized and criminalized. The
western medical model, with its incessant focus on a binary construction of gender and a binary
constructions of transgender identity, has heavily influenced theoretical conceptualizations of
transgender and gender expansive identities and subsequently the frameworks made available to
the world at large (Sanger, 2008). This inherently oppressive framework reflects society’s
frequent rejection and denial of transgender and gender expansive identities and experiences
(Shelley, 2009).
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Previous literature has demonstrated that LGB and transgender and gender expansive
YEH frequently experience discrimination, and face systemic barriers including institutional
practices that deny their own understanding and expression of their sexual orientation and gender
(Abramovich, 2016; Shelton, 2015; Thaler, Bermudez, & Sommer, 2009). Thus, many service-
oriented systems that should be helpful to LGB and transgender and gender expansive YEH are
informed by these pathological understandings. The consequences are a set of systems that either
deny their existence (Bauer et al., 2009) or are ill equipped to provide safe and affirming care
(Abramovich, 2016; Shelton, 2015). Although it is uplifting to see that non-cisgender YEH were
more likely to report positive staff relationships, the fact that this very same group endorsed
discrimination in drop-in centers at greater rates indicates that there is a lot of work to be done to
fully support this community.
Our findings highlight both the incredible resilience as well as the enormous barriers that
LGB and non-cisgender MM-YEH face when navigating systems at the intersections of multiple
marginalized identities. Future research should adopt an intersectionality-based framework to
examine the specific discriminatory precursors facing non-cisgender MM-YEH and its
association with drop-in center, community, and social service access. Additionally,
experimental research should focus on testing LGB and gender affirming drop-in center
interventions to enhance the safety and well-being for non-cisgender YEH, particularly non-
cisgender YEH of color or who identify as heterosexual, in these spaces.
Due to its cross-sectional design, it was beyond the scope of this dissertation to examine
contextual and identity related variations among the types of resilience strategies utilized by
transgender and gender expansive YYA experiencing homelessness. We suggest future studies
incorporate qualitative research to thoroughly examine the intersections of race/ethnicity, sexual
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orientation and gender identity and expression among non-cisgender YEH. Future research could
examine if and how resilience strategies vary among various MM-YEH groups, and could seek
to identify factors that support the development of resilience strategies among non-cisgender
YEH of multiple marginalized statuses. Similarly, future social network analysis research could
explore the types of supports that non-cisgender YEH find most helpful when accessing and
engaging in services.
Program Implications
Our results align with previous research and demonstrate that despite the increased and
various discriminatory barriers, non-cisgender YEH are finding innovative ways to resist the
multiple and overlapping institutionalized challenges they face. This is evident in their increased
likelihood to have positive staff support. Yet, there is still much work to be done from a
programmatic standpoint. Housing, employment, health care, and social service systems are
often not constructed for nor trained appropriately to meet the specific needs of YEH who have
experienced multiple stigmas related to racism, cisgenderism, transphobia, heterosexism, and
homophobia (Olivet & Dones, 2016). Programmatically, drop-in center providers should operate
from a strengths-based, all-affirming approach and actively challenge oppressive societal
messages about non-cisgender YEH and non-cisgender YEH of multiple marginalized statuses.
A strengths-based perspective will enable providers to identify, partner with, and elevate the
strengths of non-cisgender YEH, rather than focusing solely on their challenges. Such a
perspective broadens the risk paradigm often used to describe this community, and can provide
opportunities to foster the resourcefulness, support networks, and strengths of non-cisgender
YEH (Shelton, 2016).
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Policy Implications
Though some progress for the transgender and gender expansive community has been
made with regards to legal protections and representation in mainstream U.S. culture, advances
are not guaranteed. In fact, these protections are constantly threatened by a conservative backlash
as evidenced through a rise in hetero/ciscentric policies and hetero/cissexist practices (Mertus,
2007). These policies and practices reinforce the systemic oppression of the non-cisgender
community, subsequently impacting the livelihood of non-cisgender YEH when navigating
public and social service spheres. For example, the recent debate over bathroom access in states
such as North Carolina (House Bill 2) has led to the development of anti-trans legislation (House
Bill 142) on state and local levels. This legislation limits the ability of non-cisgender YEH to
fully participate in business, public, and service settings in an equitable way compared to their
cisgender counterparts. We strongly recommend that legislators and policy advocates continue to
monitor anti-trans legislation and push transgender and gender expansive affirming legislation to
dismantle cruel opportunities for further discrimination.
Intersectional-Based RAAM Framework
This dissertation incorporated an Intersectional-based Risk Amplification and Abatement
framework, to explore the prevalence of discrimination and its potential association with positive
adult support, mental health service use, and drop-in center engagement for YEH. Overarching
themes have arisen from the across all three studies. First, we advocate for expanded use of
intersectional-based theoretical frameworks with MM-YEH.
Expanding the RAAM model to include an Intersectional lens has allowed for a more in-
depth focus of the interconnected role of race/ethnicity, sexual orientation and gender, and
offered a profound look at the uniquely complex experiences of YEH with multiple marginalized
130
identities. Across every setting including: law enforcement, drop-in centers, health care services,
small business, employer, and community, MM-YEH endorsed discriminatory experiences by
staff or individuals in these settings, at alarmingly high rates. Marginalized and multiple
marginalized youth experiencing homelessness (MM-YEH) should be at the forefront and
center-stage in the discussion of improving the health and well-being for YEH. Therefore,
centering MM-YEH when thinking about how to address discrimination in service and
community settings is the way forward. We adopted the Intersectional-based Risk Amplification
and Abatement Framework to guide this work to foster a deeper understanding as to why and
how discrimination (amplification) and staff support (abatement) may contribute to unique and
complicated socialization processes for MM-YEH when engaging in drop-in center and mental
health service use. Altogether, the three previous studies offer strong research, program, and
policy implications.
Research Implications
Future research should seek to build from this dissertation and incorporate an
Intersectional-based RAAM framework to account for the diverse array of self-identified statuses
of YEH and how its intersection with various contexts of homelessness. Accounting for
intersecting identities and experiences will offer important insight and provide direction on how
to design service settings that support not just sexual minority youth experiencing homelessness
(SM-YEH) but SM-YEH of marginalized race/ethnicity statuses. Incorporating an intersectional
lens into our data analysis plan allowed us to compare differences in discriminatory experiences
among YEH with various intersecting identities. Our findings suggest that future research
should further investigate discriminatory experiences for SM-YEH of color considering that
LGBQ YEH of color were more likely to endorse discrimination across all settings (with the
131
only exception being health services) than their heterosexual peers. LGBQ YEH identifying as
Black or other Race experienced significantly more discrimination in law enforcement, drop-in
centers, employers, small businesses, and in the community relative to both Heterosexual YEH
identifying as Black or Other Race.
If we continue the status quo of one dimensional demographic data analysis then we will
inevitably miss out on the complex interplay of intersecting identities and how it shapes
particularly unique discriminatory experiences for YEH. Specifically, qualitative research may
be able to more adequately capture the lived experiences of Black or Other Race LGB YEH.
Intersectional-lens RAAM qualitative studies may be better suited to investigate how
discriminatory experiences by service providers or community members impact their access and
engagement in services and society at large as well as the discriminatory barriers associated with
disengagement from services and community.
Structural racism has shown its ugly face in this dissertation. Although race as a main
effect was not found to be significantly associated with discrimination across all three studies,
race was identified as the main reason for discrimination among all YEH in our sample.
Furthermore, Of note, LGBQ YEH who identify as Black (N = 23, 82.1%) or Latinx (N = 6,
75%), were more likely to report race as the main reason for discrimination than their White,
LGBQ peers (N = 6, 40%). These findings alone compel future research to incorporate Critical
Race theory (CRT) to understand the specific discriminatory experiences for Black YEH. CRT
focuses on the critique of how the social construction of race and institutionalized racism
perpetuate a racial caste system that relegates people of color to the bottom tiers (Creshaw,
Gotanda, Peller, & Thomas, 1995). CRT also recognizes that race intersects with other identities,
including sexuality, gender identity, and others (Creshaw, Gotanda, Peller, & Thomas, 1995).
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Importantly, CRT acknowledges that the legacy of slavery, segregation, and the imposition of
second-class citizenship on Black Americans continue to permeate the social fabric of this
nation. As such, CRT is the theoretical lens needed to fully understand racism intersects with
other forms of inequality such as sexism and homophobia for Black YEH.
Future research should further explore how to comprehensively measure discrimination
among MM-YEH. Although unfair treatment and discrimination are both experienced as threats
to fairness and equality (Williams et al. 2012), the former may be based upon characteristics or
behaviors that are unique to the individual victim (e.g., personality), while the latter is based
upon an individual’s identities or social group memberships (Bastos et al. 2017; Chae et al.
2008). We decided on the EDS scale due to its strong association with institutional and
interpersonal discrimination (Hughes 2003; Krieger et al. 2005) as well as its acceptance as a
valid measure that accounts for discriminatory experiences among youth and adults who identify
with minority status (Seaton et al. 2008; Goosby et al., 2015; ). Our choice to use the EDS scale
limits our opportunity to capture positive and negative valences and relative weights of identities.
These may likely be factors that could be better captured at the data collection phase with yet-to-
be-created instruments aiming to measure the intrapersonal level. For example, A Black, non-
cisgender YEH with a strong African American cultural heritage may be more resilient than
some of their YEH counterparts. From this study we cannot know if such intrapersonal-level
factors are independently significant predictors nor if they would explain additional variance. We
propose future research should be aimed at including this level in measurements.
Our effort to operationalize intersectionality is offered in the spirit of continuing a
dialogue among researchers to move toward a greater realization of the adverse impact of social
inequalities on health across multiple service and community settings for YEH. Several of the
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shortcomings of this analysis could be easily addressed with minimal effort at the data collection
phase by augmenting the initial demographic assessment to include more questions about
belonging to marginalized minority groups and other social identities of theoretical interest to the
study. A next step would be to ask participants to indicate the relative positive or negative
valence of each identity and to weigh or rank the perceived importance of each identity relative
to the others. The addition of attention to contextual, interpersonal-level, and intrapersonal-level
variables could inform future implementation research. Ultimately the goal of producing such
knowledge would be to improve access and engagement in needed services and overall health
and well-being all YEH who experience marginalization at many levels.
Program Implications
The incorporation of an Intersectional-based RAAM framework led to the several
program implications. We advocate for the inclusion of an Intersectional-based approach to
evidence-based client-centered frameworks already being implemented with YEH, such as
Positive Youth Development (Taylor-Seenhafer, 2004; Kelly, 2019). Common pillars of the
positive youth development (PYD) framework: include respect, dignity, building relationships,
and developing trust with youth as well as youth leadership/voice, life-goal achievement, and
community service (Taylor-Seenhafer, 2004). In PYD agencies, the focus is on honoring the
dignity and worth of each individual, and as such, staff are expected to create an agency climate
in which all youth and staff are treated with respect. We suggest that an intersectional-based
PYD approach to drop-in center programming can be applied by: 1) developing new programs
and evaluating existing programs centered on the needs of MM-YEH; 2) active participation of
MM-YEH in the evaluation of staff in annual reviews; 5) MM-YEH serving as peer counselors
and peer mentors; 6) forming an advisory council and resident council specific to MM-YEH
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experiences; and 6) MM-YEH contributing to co-authoring agency policies and program
guidelines (e.g., eligibility criteria, rules, and rule-breaking consequences for drop-in centers).
Policy Implications
The Runaway and Homeless Youth Act (RHYA) (Administration for Children and
Families, 2020) is the existing federal legislation that funds street outreach programs, drop-in
centers, basic needs such as food and clothing, and counseling services for YEH. Our policy
implications includes a possible reauthorization of RHYA with nondiscrimination policies for
race, sexual orientation and gender identity, New RHYA non-discrimination policies might
include nondiscrimination initiatives as well as cultural humility training for service providers
focused on sexual and gender identity, and their interaction with ethnicity and race. These
initiatives should be financed under RHYA. We call on state and local leaders to align with
current federal efforts to address LGBT discrimination across social sectors. One example, The
Consumer Financial Protection Bureau announced that it will enforce against discrimination on
the basis of sexual orientation or gender identity in credit and lending services. Local and state
policies that reinforce this federal mandate may be one step toward dismantling small business
discrimination among MM-YEH.
Too often, we see the same story play out. The decision makers in charge of policy
development and implementation practices for YEH do not reflect nor understand the
communities they are intending to serve. This leads to a system that lacks cultural humility and is
rutted in implicit and explicit bias. It’s critical that those decision-maker not only reflect and
represent MM-YEH but are also consistently trained in the history of racism and LGB,
transgender and gender expansive discrimination in social service and other formal systems.
When we are willing to not only have brave conversations about systemic racism and LGBT and
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gender inequality, but also to back MM-YEH centered policy changes, then we will be able to
begin dismantling the formal systems that continue to oppress MM-YEH communities.
Conclusion
This dissertation unveiled the diverse marginalized and multiple marginalized identities
of YEH and their associated discriminatory experiences, social support and service engagement.
This unveiling reveals that MM-YEH are experiencing discriminatory experiences across a
multitude of service and community sectors at alarming rates. The findings across all three
studies are important because it serves to more aptly humanizes the MM-YEH population and
highlight their incredible resilience. These implications are modest suggestions to help address
the discriminatory impact for MM-YEH. Homogenizing youth who are homeless facilitates their
dehumanization, erasing not only their marginalized and multiple marginalized identities, but
also obscuring the diverse experiences they face when navigating services and community.
Homogenization also encourages further acts of discrimination, erroneous negative stereotypes,
assumptions, and prejudices. Consequently, a vicious cycle is created, trapping marginalized
groups in homelessness and other unequal situations.
Even though the picture that is painted for MM-YEH facing discrimination may seem
bleak, these findings should not be taken as evidence that MM-YEH are far from powerless in
the face of pervasive discrimination. Our findings demonstrated how MM-YEH exemplify
resilience and exercise agency in choosing to engage services and establish supportive
relationships in the very environment in which they experience discrimination. Yet, if we are to
call ourselves advocates of YEH, we can not simply rely on MM-YEH remarkable ability to
“bounce back” from discriminatory experiences. It is long overdue for researchers, policy
136
makers, and providers to lift the veil and confront the discriminatory impact on service
engagement for MM-YEH.
137
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Abstract (if available)
Abstract
Youth who identify with marginalization and multiple marginalization comprise a substantial and disproportionate portion of the population experiencing homelessness and yet little is known about their perceived discriminatory experiences across settings fundamental to their health and housing stability. This dissertation built upon the Risk Amplification and Abatement Model (to incorporate an Intersectionality lens in an effort to understand the specific and varied discriminatory experiences MM-YEH face and its association with social support and mental health service use. Chapter 2 results revealed that the majority of Heterosexual, Non-Cisgender YEH (60%, X²= 12.48, p < .01) were more likely to report drop-in center discrimination than any other MM-YEH groups. Race was reported as the main factor for discrimination (N = 66; 51.9%) among all YEH participants who endorsed perceived discrimination of any type. Chapter 3 results found that in regard to gender, non-cisgender youth (OR = 3.31, 95%CI = 1.05, 10.43, p <.05) were more likely to have a positive staff relationship, compared to cisgender youth. Chapter 4 results found that youth who endorsed a positive staff relationship (OR = 3.57, 95%CI = 1.52, 8.43, p <.003) were more likely to frequent the drop-in center daily, compared to youth without a positive staff relationship. Youth who reported community settings only discrimination were more likely (OR = 2.53, 95% CI = 1.03, 6.16, p <.03) to frequent the drop-in center daily compared to youth who did not report community settings only discrimination. The findings demonstrate a need to expand focus from deficit-based narratives to resilience and adaptive coping among youth experiencing homelessness. Future research should incorporate Intersectional-lens RAAM framework and incorporate Critical Race theory (CRT) to understand and explore how to comprehensively measure discrimination and structural racism among MM-YEH.
Linked assets
University of Southern California Dissertations and Theses
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Asset Metadata
Creator
Holguin, Monique M.
(author)
Core Title
Discrimination at the margins: perceived discrimination and the role of social support in mental health service use for youth experiencing homelessness
School
Suzanne Dworak-Peck School of Social Work
Degree
Doctor of Philosophy
Degree Program
Social Work
Degree Conferral Date
2021-08
Publication Date
08/02/2022
Defense Date
08/02/2021
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
Discrimination,Homeless youth,intersectionality,Mental Health,OAI-PMH Harvest,social support
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Rice, Eric (
committee chair
), Cousineau, Michael (
committee member
), Perez Jolles, Monica (
committee member
)
Creator Email
mmholgui@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-oUC15674427
Unique identifier
UC15674427
Legacy Identifier
etd-HolguinMon-9982
Document Type
Dissertation
Format
application/pdf (imt)
Rights
Holguin, Monique M.
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given.
Repository Name
University of Southern California Digital Library
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
Repository Email
cisadmin@lib.usc.edu
Tags
intersectionality
social support