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Psychological distress behavioral patterns and mental health service use among Latinos in the 2012 National Health Interview Survey: a latent class analysis

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Psychological distress behavioral patterns and mental health service use among Latinos in the 2012 National Health Interview Survey: a latent class analysis

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PSYCHOLOGICAL DISTRESS BEHAVIORAL PATTERNS AND MENTAL HEALTH SERVICE USE AMONG
LATINOS IN THE 2012 NATIONAL HEALTH INTERVIEW SURVEY: A LATENT CLASS ANALYSIS

ARMANDO BARRAGÁN, JR.

❧

A Dissertation Presented to the

FACULTY AT THE SCHOOL OF SOCIAL WORK
UNIVERSITY OF SOUTHERN CALIFORNIA

In Partial Fulfillment of the
Requirements for the Degree of

DOCTOR OF PHILOSOPHY

August 2015

ii

DEDICATION
Para mis padres, Armando and Carmen, que han sacrificado tanto para ayudarme a ser el
hombre que soy hoy. Sin su amor y apoyo, yo no habría superado los obstáculos que enfrenté en
mi educación. Los quiero.
To my beautiful wife, Sandra, whose love, patience and understanding were a blessing
throughout my studies. Thank you so much for your support. I love you.

iii

ACKNOWLEDGEMENTS
I would like to thank my committee members, Ann Marie Yamada, Tamika Gilreath, and
Robert Rueda, for their support, feedback and knowledge throughout my dissertation. I
especially like to thank Dr. Gilreath in supporting me through many aspects of my dissertation
process, both at the academic and personal level. Your guidance and interest in my success have
been critical in completing this dissertation. I would also like to acknowledge the faculty who
have advised me throughout my studies and the School of Social Work for all of their support.
I would like to acknowledge the Council on Social Work Education’s Minority
Fellowship Program for their guidance and financial support throughout most of my doctoral
studies. I have met great people in MFP who I will continue to have as colleagues and friends.
Finally, I would like to acknowledge my family and friends who have supported me long
before my doctoral studies: my parents, Armando and Carmen Barragán; my siblings, Virginia
and Isaí Barragán; my closest friends (aka “groomsmen”) Aaron Allen, Luis Acosta, and Andy
Acosta; and my tíos, Noel and Gina Carrillo. And to the one I met during my doctoral studies
and will continue to share life’s journey, my wife Sandra Alvarez. Thank you all for your
encouragement, support, advice and friendship.

iv

TABLE OF CONTENTS
Dedication ii

Acknowledgements iii

List of Tables and Figures v

Abstract vi

Overview and Background: Psychological Distress and Mental Health Service
Use among Latino Subgroups 1
Rationale 4
Dissertation Layout 11

Study One: Comorbidity and Psychological Distress Outcomes among Latinos 14
Methods 18
Results 22
Discussion 25

Study Two: Psychological Distress Behavioral Patterns Among Latinos:
We Don’t See Ourselves As Worthless 31
Methods 32
Results 36
Discussion 39

Study Three: Psychological Distress Behavioral Patterns and Mental Health
Service Use Among Latinos: A Post Hoc Analysis 44
Methods 45
Results 50
Discussion 51

Conclusion 55
Summary of Findings 56
Research and Practice Implications 58

References 61

Appendices
Appendix A: SAS Syntax for Multiple Linear Regression Analyses 94
Appendix B: Mplus Syntax for Latent Class Analyses 99
Appendix C: Mplus Syntax for Latent Class Analyses w/ Binary Distal Outcome 102
v

LIST OF TABLES AND FIGURES
Table 1. Correlation Matrix of Mental Health Disorder Comorbidity 79

Table 2. Correlation Matrix of Physical and Mental Health Disorder Comorbidity 80

Table 3. Sample Characteristics 81

Table 4. Standardized Regression Models of Mental Health Disorder Comorbidity 82
as a Predictor of Psychological Distress

Table 5. Standardized Regression Models of Physical and Mental Health Disorder 83
Comorbidity as a Predictor of Psychological Distress

Table 6. Sample Characteristics and Psychological Distress, NHIS, 2012 84

Table 7. Fit Statistic Comparisons of Latent Class Analysis Models 85
of Psychological Distress

Table 8. Conditional Probabilities of Psychological Distress (n = 4,912) 86

Table 9. Multinomial Logistic Regression Results of Psychological Distress (n = 4,912) 87

Table 10. Sample Characteristics, Mental Health Treatment, & Psychological Distress, 88
NHIS, 2012

Table 11. Fit Statistic Comparisons of Latent Class Analysis Models of 89
Mental Health Treatment & Psychological Distress

Table 12. Conditional Probabilities of Mental Health Treatment 90
& Psychological Distress (n = 4,920)

Table 13. Multinomial Logistic Regression Results of Mental Health Treatment 91
& Psychological Distress (n = 4,920)

Figure 1. Adapted Ecological Systems Theory Model 92

Figure 2. Odds Ratios of Mental Health Service Use Predicted by 93
Psychological Distress Behavioral Profiles

vi

ABSTRACT
Psychological distress, generally defined as a state of emotional suffering and
characterized by symptoms of depression and anxiety, affects Latinos at higher rates and severity
than the general population. Previous studies have focused on identifying the risk and protective
factors associated with distress, but few studies have accounted for comorbid health illnesses,
which affect Latinos at higher rates and could account for increased distress levels. Furthermore,
our understanding of psychological distress among Latinos in epidemiological studies are based
on a Western medical construct that may be incongruent with conceptualizations of distress
among Latinos, thus calling into question the comprehensiveness of distress among Latinos.
Using data from the 2012 National Health Interview Survey, the focus of this dissertation was to
answer the following questions: (a) What differential effects does the number of lifetime health
disorders have on the severity of psychological distress among Latinos? (b) How are protective
and risk factors associated with psychological distress among Latinos? (c) Do Latinos exhibit
psychological distress behavioral profiles that are ethnically unique and if so, what are they? (d)
What is the association between psychological distress behavioral patterns and mental health
service use during the previous year? Findings indicated an increased exacerbation of symptoms
for comorbid health problems, yet some covariate effects indicated that some Latino groups are
at risk of increased distress whereas the same covariates represent protective factors for other
Latino groups. Furthermore, feelings of worthlessness, identified in literature as one of the major
domains of psychological distress, did not characterize manifestations of distress among Latinos.
Despite the inherent buffering effect of not endorsing feelings of low worth for some mental
health problems, Latinos who report high levels of distress may still require outside mental
health services. In the three studies conducted in this dissertation, Puerto Ricans were at greatest
vii

risk of psychiatric morbidity. Implications of these findings on research and practice are
discussed, as are directions for future studies.

1
OVERVIEW AND BACKGROUND:
PSYCHOLOGICAL DISTRESS AND MENTAL HEALTH SERVICE USE AMONG LATINO SUBGROUPS
During the previous 40 years, the growth of the Latino population in the United States
has reshaped American demographics (Alegría, Mulvaney-Day, Torres, et al., 2007), with
estimates that more than 20% of the country’s population will be Latino by 2050 (U.S. Census
Bureau, 2004). Compared to Anglo Americans, Latinos with a mental illness are at risk of
underutilizing mental health services (Barrio, Yamada, Atuel, et al., 2003; Barrio, Yamada,
Hough, et al., 2003), with fewer than 1 in 11 contacting a mental health specialist and even fewer
seeking mental health treatment when they are immigrants (U.S. Department of Health and
Human Services [USDHHS], 2001). Failure to receive mental health treatment places Latinos at
greater risk of poor health outcomes, such as homelessness, hospitalization, and worsening of
psychiatric symptoms (Dixon et al., 2009; Fischer et al., 2008; Kreyenbuhl, Nossel, & Dixon,
2009).
A challenge in the process of engaging Latino consumers living with a mental illness is
that Latino culture is not homogeneous, even based on the standard definition of Latino seen in
various studies (Alegría, Vila, et al., 2004). How needs and concepts are understood across the
Latino paradigm in a myriad of sociocultural contexts influences the unique needs faced by each
subgroup
1
(Alegría, Atkins, Farmer, Slaton, & Stelk, 2010; Alegría, Vila, et al., 2004). Mexican-
born families, for example, may move to the United States as undocumented immigrants and
thus may have difficulty obtaining health insurance and be averse to reaching out to government-
employed authorities for fear of incarceration or deportation. In contrast, Puerto Ricans are
natural-born U.S. citizens entitled to many benefits that state-born individuals have and are

1
Latino subgroups (also referred to as Latino groups) refers to ethnic groups originating from a Latin American
country. Those born in the United States are identified as their own Latino subgroup to distinguish them from
foreign-born groups (e.g., Mexican Americans vs. Mexicans).

2
generally more proficient at speaking English than recently immigrated Mexicans. Consequently,
these unique experiences shape the etiology of illnesses and the pathways toward obtaining
treatment (Cook, Alegría, Lin, & Guo, 2009). For example, studies have shown that rates of
mental health service use are higher among Puerto Ricans and U.S.-born Latinos than among
non-Puerto Ricans and foreign-born Latinos (Alegría, Mulvaney-Day, Woo, et al., 2007). Similar
studies have found that nativity, language proficiency, and years of residence in the United States
are among factors that differentially affect use of mental health services by Latino subgroups (Ai,
Appel, Huang, & Lee, 2012; Ai, Nöel, Appel, Huang, & Hefley, 2013; Alegría, Mulvaney-Day,
Woo, et al., 2007; Keyes et al., 2012). The general principle of Latino subgroup amalgamation
thus undermines targeted efforts to unravel subgroup differences in treatment use and overall
mental health. Few studies have focused their efforts on untangling the subtle yet significant
differences in treatment use and the phenomena of mental illnesses among Latino subgroups
(Guerrero, Marsh, Khachikian, Amaro, & Vega, 2013).
Identifying the factors associated with treatment use has helped public health efforts in
targeting the needs of the Latino population. Ever since the U.S. Surgeon General’s call for more
studies on the discrepancies in mental health among Latinos (USDHHS, 2001), studies like the
National Latino and Asian American Study (Alegría, Takeuchi, et al., 2004) and the National
Epidemiological Survey on Alcohol and Related Conditions (Grant et al., 2004) have highlighted
the unique needs of each Latino group for effective and efficient mental health services (López,
Barrio, Kopelowicz, & Vega, 2012). However, studies examining heterogeneity among Latino
subgroups have been limited to examining questions related to prevalence of mental illnesses and
use of services, with few studies examining the impact of psychological distress on levels of
functioning between subgroups. Of the studies that have examined psychological distress, even

3
fewer studies emphasized differences between subgroups with regard to factors that either buffer
against or increase risk of distress. Furthermore, studies assessing distress among Latinos have
explored distress in the context of Western medicine, which may be incongruent with the
subjective interpretations of symptoms unique to Latino culture. Studying differences in how
Latino subgroups manifest distress can help mental health professionals: (a) target groups at
highest risk of experiencing significant psychological distress and (b) adjust mental health
services based on the sociocultural needs of clients.
In light of the need to address these issues, this dissertation focused on the following
questions:
1. What differential effects does the number of lifetime health disorders have on the
severity of psychological distress among Latinos?
2. How are protective and risk factors associated with psychological distress among
Latinos?
3. Do Latinos exhibit psychological distress behavioral profiles that are ethnically
unique and if so, what are they?
4. What is the association between psychological distress behavioral patterns and mental
health service use during the previous year?
Results from this study will increase understanding of the differential effects that
psychological distress may have among Latinos who also report experiencing a mental illness
during their lifetime. Additionally, these findings will provide insight for mental health providers
and policy makers regarding how to target and prioritize treatment for groups that are more at
risk of psychological distress. Studies such as these can guide efforts to tailor treatments to the

4
unique needs of each subgroup with the goal of providing quality mental health treatment for all
Latinos.
Rationale
Psychological Distress
Psychological distress (also referred to as distress) is generally defined as a state of
emotional suffering, characterized by symptoms of depression (e.g., anhedonia, hopelessness,
and sadness) and anxiety (e.g., restlessness and feeling tense; Mirowsky & Ross, 2002). The
principles associated with psychological distress are rooted in the stress-distress model,
postulating that exposure to a stressful event threatens an individual’s physical or mental health
(Drapeau, Marchand, & Beaulieu-Prévost, 2012; Horwitz, 2007; Ridner, 2004). Consequently,
the inability to adequately cope with the stressor can eventually result in emotional turmoil.
Despite the generally agreed-on definition, the psychiatric nosology of psychological distress has
been debated in scientific literature (see Drapeau et al., 2012). Wheaton (2007) viewed
psychological distress as an emotional disturbance that affects social functioning and activities of
daily living. However, other researchers have viewed psychological distress as a diagnostic
criterion for mental disorders and a marker of symptom severity (Kessler et al., 2003; Phillips,
2009; Watson, 2009). Despite the position of mental health professionals on the nosology of
psychological distress, distress itself is a useful indicator of psychological functioning and
prominent in the evaluation of public health.
Psychological distress had been studied in epidemiological surveys as a general
assessment of mental health dating back to the baby boomer era (Kessler et al., 2002; MacMillan,
1957). However, the method used to study psychological distress did not evaluate rates of
specific psychiatric disorders, preventing epidemiologists and public health authorities from

5
developing an accurate picture of the nation’s public mental health profiles. Consequently,
psychological distress measurements fell out of favor after the Epidemiological Catchment Area
Study (Robins & Regier, 1991). Subsequently, the use of psychometrically reliable diagnostic
tools administered by lay interviewers has been the standard approach to measure
psychopathology in current epidemiological studies (Kessler et al., 2002; Robins, Helzer,
Croughan, & Ratcliff, 1981; Robins, Wing, et al., 1988).
Despite the advantages of sophisticated diagnostic tools, clinical reappraisal studies have
demonstrated that many community cases have significantly less serious disorders than those in
clinical settings (Kessler et al., 2002; Kessler et al., 2001). Consequently, with a high proportion
of individuals meeting criteria for a psychiatric disorder, policy makers and other health officials
needed to differentiate between individuals with severe or less severe psychiatric disorders, with
the ultimate goal of defining medical necessity (Kessler et al., 2002). As a result, psychological
distress nonspecific to psychiatric disorders saw resurgence in use following a shift toward
studying mental illnesses based more on severity and less on diagnosis (Kessler et al., 2002).
The call for psychiatric epidemiological studies to include psychological distress has
been heeded in general population studies. Community and regional surveys have revealed rates
ranging between 5% and 12% of individuals reporting significant psychological distress
(Benzeval & Judge, 2001; Chittleborough, Winefield, Gill, Koster, & Taylor, 2011; Gispert,
Rajmil, Schiaffino, & Herdman, 2003; Kuriyama et al., 2009; Phongsavan, Chey, Bauman,
Brooks, & Silove, 2006). Rates may be even higher for the Latino segment of the population,
because exposure to acculturative stress (i.e., the process of adapting to the host country’s
culture), language barriers, and other socioeconomic factors are credible risk factors for

6
increased psychological distress (Centers for Disease Control and Prevention [CDC], 2014;
Drapeau et al., 2012).
Psychological Distress among Latinos
According to the CDC (2014), 4.1% of Latinos report serious psychological distress,
higher than Anglo Americans (3.6%) and African Americans (3.0%). Given the increased risk of
mental health morbidity associated with high psychological distress (Hendricks, Thorne, Clark,
Coombs, & Johnson, 2015; Kessler et al., 2003; McKelvey, Davies, Pfaff, Acres, & Edwards,
1998), studies during the previous 10 years have focused on identifying factors that could
explain higher rates of psychological distress among Latinos. Several sociocultural factors and
intergroup dynamics have been consistently shown to be a risk factor for psychological distress
(Molina & Alcántara, 2013; Rivera et al., 2008; J. M. Torres & Wallace, 2013; L. Torres,
Driscoll, & Voell, 2012; Zhang, Hong, Takeuchi, & Mossakowski, 2012). Zhang et al. (2012)
illustrated that unlike Asian Americans—among whom limited English proficiency is associated
with psychological distress—sociodemographic factors (e.g., employment, gender, education)
and discrimination have a stronger association with psychological distress than limited English
proficiency among Latinos. Other factors such as nativity status (Molina & Alcántara, 2013),
acculturation (J. M. Torres & Wallace, 2013; L. Torres et al., 2012), social cohesion (Rivera et
al., 2008), and immigration and migration background (Molina & Alcántara, 2013; J. M. Torres
& Wallace, 2013) have also been shown to influence levels of psychological distress among
Latinos.
However, observations have varied greatly both in the rates of distress and risk factors
among Latino subgroups. Bratter and Eschbach (2005) used data from the National Health
Interview Survey (NHIS) to investigate the association between ethnicity and psychological

7
distress. According to their findings, Puerto Ricans had the highest levels of psychological
distress compared to Anglo Americans. Psychological distress levels were lower among
Mexicans, whereas Cubans reported no difference in psychological distress levels compared to
Anglo Americans. Rivera et al.’s (2008) assessment of family cohesion (i.e., emotional bonding
that family members have toward one another; Olson, Russell, & Sprenkle, 1983) and its
buffering effects on psychological distress illustrated the complex nature of relationships among
family members across Latino subgroups. Among Latinos as a whole, family cohesion was
associated with lower psychological distress. However, among Cubans, increased family
cohesion was associated with increased psychological distress. Among Puerto Ricans and
Mexicans, family cohesion had no impact on psychological distress. Rivera et al. (2008)
demonstrated that certain factors commonly thought to buffer distress may actually be risk
factors for certain Latinos. What is unclear, however, is whether these complex relationships
extend beyond social dynamics assessed by Rivera et al. (2008). Although sociodemographic
factors affect distress among Latinos, the literature has yet to identify both the magnitude and
type of effect of sociodemographic factors on distress among Latino groups.
Evaluation of Latino heterogeneity with regard to psychological distress has focused on
identifying risk factors and describing the etiology of various mental health problems. However,
research efforts examining Latino psychological distress have not focused on exploring and
identifying how psychological distress manifests among Latinos. A study funded by the World
Health Organization (Draguns, 1990) identified common symptoms of depression across various
countries, including anxiety, tension, sadness, and lack of energy. However, respondents from
Western countries reported additional feelings of guilt, whereas participants from non-Western
countries reported somatic complaints. Nervios, a term for psychological distress prominent

8
among Latinos, is an example of a syndrome whose manifestations are shaped by culture over
many generations (Guarnaccia, 1997; San Miguel et al., 2006). Consequently, mental health
professionals have limited knowledge regarding the expressions of psychological distress that
distinguish Latino subgroups from one another, and thus may overlook behaviors that are
uniquely indicative of distress in a given subgroup. Furthermore, mental health professionals are
forced to conflate the otherwise unique nature of Latino heterogeneity.
If unique psychological distress profiles that characterize and distinguish Latino groups
do exist, how are these distinct profiles associated with mental health treatment use during the
previous year? Previous studies assessing treatment use have focused on identifying correlates of
service use (e.g., Dallo, Kindratt, & Snell, 2013; Lo, Cheng, & Howell, 2014), providing mental
health professionals with a greater understanding of potential risk factors associated with
treatment use. A study by Constatine, Wilton, and Caldwell (2003) provided more in-depth
evaluation of psychological distress and treatment use, observing that social support did not
moderate access to treatment among Latinos. However, these studies did not account for
treatment use based on psychological distress profiles of Latino subgroups, and thus have been
limited in terms of providing a sociocontextually accurate assessment of service use. Assessing
treatment use that is context specific, both with regard to psychological distress and Latino
subgroups, can provide mental health professionals with a more comprehensive understanding of
behavior patterns associated with treatment use among Latinos.
Framework of Latino Heterogeneity, Psychological Distress, and Service Use
The basic framework used to contextualize Latino heterogeneity and psychological
distress is best understood via the ethnic-culture perspective (Mirowsky & Ross, 1980). This
perspective assumes that psychological well-being varies based on cultural practices and values

9
that distinguish various ethnic groups. This differs from the minority status perspective
hypothesized by other researchers (see Mirowsky & Ross, 1980), which asserts that ethnic
minorities are subject to distress due to (a) prejudice and discriminatory actions or (b) low social
class. In support of the ethnic-culture perspective, Mirowsky and Ross (1980) assessed studies in
which psychological distress was examined among ethnic groups. Similar to the results presented
by Bratter and Eschbach (2005), Puerto Ricans had the highest distress levels of any group when
controlling for socioeconomic factors (Dohrenwend & Dohrenwend, 1969; Srole, Langner,
Michael, Opler, & Rennie, 1962). In contrast, Antunes, Gordon, Gaitz, and Scott (1974) and
Gaitz and Scott (1972) found that Mexicans had less distress than other ethnic groups when
controlling for socioeconomic factors. These findings and those of Mirowsky and Ross (1980)
demonstrated that sociocultural factors specific to each ethnic group are better able to account for
the variability of psychological distress than either prejudice and discrimination or social class.
Considering the versatility of the ethnic-culture perspective in terms of explaining the
heterogeneity of mental health between ethnic groups, Mirowsky and Ross (1980) acknowledged
that Latino subgroups are distinct enough to vary substantially in their mental health.
Furthermore, the theoretical framework structuring the sociocultural processes is
Bronfenbrenner’s ecological systems theory (EST). Bronfenbrenner’s model posits that
environmental forces interact with individuals, thus affecting outcomes in an individual’s
behavior and pathology (Bronfenbrenner, 1974, 1986; Bronfenbrenner & Evans, 2000;
Bronfenbrenner & Morris, 1998; Jensen, 2007). This system is composed of five subsystems that
affect individual outcomes, with each subsystem depending on the nature of the individual. The
most proximal subsystem affecting the individual is the microsystem, which consists of face-to-
face interactions with others (Bronfenbrenner, 1989). Second, the mesosystem refers to

10
bidirectional influences between two or more settings that also affect the individual
(Bronfenbrenner, 1989). Third, the exosystem refers to the larger social system that does not
directly affect the individual (Bronfenbrenner, 1989). The most distal of subsystems in EST is
the macrosystem, which is commonly known as a society’s general or mainstream culture
(Jensen, 2007). Critical components include belief systems, patterns of social interaction,
lifestyles, and life course development (Bronfenbrenner, 1989). Finally, the chronosystem refers
to the dimension of time, because the dynamic processes in these subsystems can only occur as a
function of time.
Understanding the risk and protective factors for psychological distress among Latinos,
along with the nature of psychological distress manifestation and treatment use, requires
assessment of individuals in their context. Thus, use of EST is able to assess individuals in
context while illustrating factors that mediate the psychological well-being of Latinos in terms of
their particular environmental level (Jensen, 2007). According to Jensen (2007), mediating
factors and processes should be viewed as bidirectional, push–pull forces that place an individual
at varying levels of psychological well-being. Consistent with Bronfenbrenner’s perspective,
mediating processes at various environmental levels are not independent from one another, but
rather influence one another in complex ways to create ecological conditions in which an
individual ranges from susceptible to resilient in terms of psychiatric morbidity (Aronowitz,
1984; Jensen, 2007).
This dissertation adapted Jensen’s (2007) model for immigrants and psychological well-
being (Figure 1). At the individual level, factors affecting psychological well-being include
demographics, immigration and migration background, mental and physical illnesses, and
employment status. Each of these factors is inherent within individuals, directly affecting their

11
worldview and needs. The first of Bronfenbrenner’s levels, the microsystem consists of family,
coworkers, friends, neighbors, and church members, all of whom have the potential to affect the
trajectory of psychological well-being among individual Latinos. At the exosystem level,
processes that influence the individual’s environment occur outside his or her presence (Jensen,
2007). These include workplace dynamics, neighborhood resources, local politics, media, and
access to services. Consequently, any incongruences found between the individual, microsystem,
and exosystem levels or beyond may lead to conflict between systems and are therefore unique
in the context of the mesosystem. Conflicts may include discrepant practices, values, beliefs,
language, and culture, thus representing a risk factor for individuals for whom such conflicts are
possible. At the most distal environmental level, the macrosystem generally forms the general
cultural framework in which a society functions (Jensen, 2007). In the context of this dissertation,
this includes the economy, laws, U.S. culture, and attitudes toward Latinos.
Dissertation Layout
The following dissertation is organized as a three-paper manuscript focusing on
psychological distress outcomes among Latinos reporting a mental illness using 2012 NHIS data.
Study 1 addressed the first and second question of the dissertation (i.e., What differential effects
does the number of lifetime health disorders have on the severity of psychological distress
among Latinos? How are protective and risk factors associated with psychological distress
among Latinos?). Previous studies have provided an up-to-date assessment of psychological
distress among Latinos but fell short in assessing other important areas. First, several studies did
not account for mental disorders as covariates, which may have confounded their research.
Considering that features characterizing psychological distress are also associated with
depressive and anxiety illnesses (Drapeau et al., 2012; Payton, 2009), mental disorders should be

12
assessed when evaluating psychological distress. Furthermore, fewer studies have accounted for
physical illnesses that occur alongside mental health problems. Mood and anxiety disorders are
often associated with increased risk of coronary artery disease, diabetes, and various
cardiovascular diseases (Golden et al., 2008; Muskin, 2010; Shen et al., 2008). Lastly, research
has shown that the relationship between protective and risk factors can differ between Latino
groups in relation to psychological distress (e.g., Rivera et al., 2008). However, it is unclear
whether these complex relationships extend beyond the social dynamics assessed by Rivera et al.
(2008), leaving an incomplete picture of risk and protective factors among Latinos. Based on
current understanding of Latino mental health, Study 1 addressed the following specific
questions:
1. Do comorbid mental illnesses result in increased severity of psychological distress
and vary among Latino subgroups?
2. Are comorbid chronic physical health problems and mental illnesses associated with
increased psychological distress and do they vary among Latino subgroups?
3. How are protective and risk factors associated with psychological distress among
Latinos?
Furthermore, the behavioral profile of psychological distress that may distinguish Latinos
and Latino subgroups is not well understood, despite evidence suggesting the influence of culture
on manifestation of psychological distress (e.g., Guarnaccia, 1997; Mirowsky & Ross, 1980; San
Miguel et al., 2006). Study 2 addressed the third question of this dissertation: Do Latinos exhibit
psychological distress behavioral profiles that are ethnically unique and if so, what are they?
Based on the first two studies regarding psychological distress behavioral profiles that
distinguish Latino groups, Study 3 addressed the fourth question (i.e., What is the association

13
between psychological distress behavioral patterns and mental health service use during the
previous year?). This final study assessed treatment use using the same models aimed at
identifying psychological distress behavioral patterns among Latinos in the previous study.
Conducting this study with the previously used models provided a contextually accurate
assessment of service use beyond that of previous studies. Based on evidence provided in Study
1, Study 2, and current understanding of the literature, it was hypothesized that:
1. Higher distress would be associated with increased use of mental health services.
2. Puerto Ricans would be most likely to seek mental health services compared to other
Latino groups.
The final chapter summarizes these studies, discussing the common themes found in
these inquiries. Additionally, this chapter elaborates on the implications of these studies for the
overall mental health of Latinos, addresses the impact of findings on the mental health treatment
infrastructure, and informs mental health treatment professionals about the effectiveness of
contemporary treatment protocols.

14
STUDY ONE: COMORBIDITY AND PSYCHOLOGICAL DISTRESS OUTCOMES AMONG LATINOS
Psychological distress is generally defined as a state of emotional suffering, characterized
by symptoms of depression (e.g., anhedonia, hopelessness, and sadness) and anxiety (e.g.,
restlessness and feeling tense; Mirowsky & Ross, 2002). Psychological distress is thus an
emotional disturbance that affects social functioning and other aspects of day-to-day activities
(Wheaton, 2007). When distress is severe enough, individuals become at risk of living with a
serious psychological disorder or experiencing unemployment and require greater assistance to
function (Bratter & Eschbach, 2005; Kessler et al., 2003).
The current literature has indicated that 5% to 12% of the general population reports
significant psychological distress (Benzeval & Judge, 2001; Chittleborough et al., 2011; Gispert
et al., 2003; Kuriyama et al., 2009; Phongsavan et al., 2006). However, prevalence rates can be
higher in some segments of the population, such as immigrants who must adapt to a host country
while being responsible for the care of their relatives (Drapeau et al., 2012). In these populations,
the prevalence of distress is greater, ranging from 13% to 39% (Levecque, Lodewyckx, &
Bracke, 2009; Ritsner, Ponizovsky, & Ginath, 1999; Sundquest, Burfield-Bayard, Johansson, &
Johansson, 2000). This is especially a concern in the United States, because Latinos account for
the largest immigrant population. Compared to Anglo Americans and African Americans, the
prevalence of affective disorders, a proxy for distress, is highest among Latinos (Kessler et al.,
1994; Robins & Regier, 1991; Williams, Costa, & Leavell, 2009).
According to the CDC (2014), 4.1% of Latinos report serious psychological distress,
higher than Anglo Americans (3.6%) and African Americans (3.0%). Given the increased risk of
mental health morbidity associated with high psychological distress (Hendricks et al., 2015;
Kessler et al., 2003; McKelvey et al., 1998), studies during the previous 10 years have focused

15
on identifying factors that could explain the higher rates of psychological distress among Latinos.
Several sociocultural factors and intergroup dynamics have been consistently shown to be a risk
factor for psychological distress (Molina & Alcántara, 2013; Rivera et al., 2008; J. M. Torres &
Wallace, 2013; L. Torres et al., 2012; Zhang et al., 2012). Zhang et al. (2012) illustrated that
unlike Asian Americans, among whom limited English proficiency is associated with
psychological distress, sociodemographic factors (e.g., employment, gender, education) and
discrimination have a stronger association with psychological distress than limited English
proficiency among Latinos. Other factors such as nativity status (Molina & Alcántara, 2013),
acculturation (J. M. Torres & Wallace, 2013; L. Torres et al., 2012), social cohesion (Rivera et
al., 2008), and immigration and migration background (Molina & Alcántara, 2013; J. M. Torres
& Wallace, 2013) have also been shown to affect levels of psychological distress among Latinos.
However, observations have varied greatly both in the rates of distress and risk factors
among Latino subgroups. Bratter and Eschbach (2005) used data from the NHIS to investigate
the association between ethnicity and psychological distress. Based on their findings, Puerto
Ricans had the highest levels of psychological distress compared to Anglo Americans. Among
other Latinos, psychological distress levels were lower among Mexicans, whereas Cubans
reported no difference in psychological distress levels compared to Anglo Americans. Rivera et
al.’s (2008) assessment of the buffering effects of family cohesion (i.e., emotional bonding
among family members; Olson et al., 1983) on psychological distress illustrated the complex
nature of relationships among family members across Latino subgroups. When observing Latinos
as a whole, family cohesion was associated with lower psychological distress. However, when
considering Cubans, increased family cohesion was associated with increased psychological
distress. Among Puerto Ricans and Mexicans, family cohesion had no impact on psychological

16
distress. Rivera et al. (2008) demonstrated that certain factors commonly thought of as buffering
distress may actually increase risk for certain Latinos. What is unclear, however, is whether these
complex relationships extend beyond social dynamics assessed by Rivera et al. (2008). Although
sociodemographic factors affect distress among Latinos, the literature has yet to identify both the
magnitude and type of relationship between sociodemographic factors and distress among Latino
groups.
The risk of psychological distress among Latinos isn’t limited to social and mental health
factors. The CDC’s (2013) Health Disparities and Inequalities Report, a comprehensive
assessment highlighting health disparities and inequalities across a wide range of diseases, found
various physical health problems affect Latinos at greater rates compared to the general
population. The prevalence of obesity among Mexican American women was higher than among
non-Latino White adults. Similarly, diabetes is more prevalent among Latinos compared to
Anglo American and Asian adults. Despite various other health problems facing Latinos, there
have been surprisingly few studies on the impact of health problems on psychological distress
among Latinos.
Although previous studies have made efforts to assess psychological distress among
Latinos, various questions related to the severity of psychological distress among Latinos have
remained unanswered. First, few studies have assessed the influence of comorbid physical health
and mental health illnesses on the presentation of psychological distress. Second, many
community-based studies have assessed Latino groups as a homogenous culture. The principle of
subgroup amalgamation undermines distinct sociocultural elements, such as immigration
experiences, social class, etc., that differentially affect the mental health needs of subgroups
(Alegría et al., 2010; Alegría, Vila, et al., 2004). Lastly, research has shown that the relationship

17
between protective and risk factors can differ among Latino groups in relation to psychological
distress (e.g., Rivera et al., 2008). However, it is unclear whether these complex relationships
extend beyond the social dynamics assessed by Rivera et al. (2008), creating an incomplete
picture of risk and protective factors among Latinos.
Mirowsky and Ross (1980) contextualized Latino heterogeneity and psychological
distress using the ethnic-culture perspective, stating that psychological well-being varies based
on cultural practices and values that distinguish various ethnic groups. In the case of Latino
heterogeneity, Latinos are distinct enough to vary substantially in their mental health (Alegría et
al., 2010; Alegría, Vila, et al., 2004; Mirowsky & Ross, 1980). Understanding the risk and
protective factors for psychological distress among Latinos requires assessment of individuals in
context. Thus, the theoretical framework structuring the sociocultural processes in this study is
EST. Bronfenbrenner’s model posits that environmental forces interact with the individual, thus
affecting outcomes in an individual’s behavior and pathology (Bronfenbrenner, 1974, 1986;
Bronfenbrenner & Evans, 2000; Bronfenbrenner & Morris, 1998; Jensen, 2007). EST is able to
assess individuals in context while illustrating factors that mediate the psychological well-being
of Latinos in terms of their particular environmental level (Jensen, 2007). This dissertation
adapted Jensen’s (2007) model for immigrants and psychological well-being (Figure 1).
This study aimed to answer the following questions: (a) Do comorbid mental illnesses
result in increased severity of psychological distress and vary among Latino subgroups? (b) Are
comorbid chronic physical health problems and mental illnesses associated with increased
psychological distress and do they vary among Latino subgroups? (c) How are protective and
risk factors associated with psychological distress among Latinos?

18
Methods
Data Source
The NHIS is an annual, cross-sectional survey designed to report nationally
representative estimates on a variety of health issues, including health status and treatment uses.
Since 1960, the National Center for Health Statistics and CDC have used the NHIS to monitor
trends in illnesses and treatment use and progress toward achieving national health objectives
(CDC, 2012). The NHIS excludes individuals in long-term care institutions, active-duty armed
forces personnel, U.S. nationals living in foreign countries, and individuals in correctional
facilities.
To accomplish sampling efficiency for a nationwide survey occurring throughout the year,
multistage sampling techniques were implemented to identify potential participants (CDC, 2012).
Since 2006, this method has been used to partition the target population into various strata and
clusters. The target universe was individuals living in dwelling units that were either households
or noninstitutional quarters (e.g., collegiate dormitories). The first stage involved partitioning the
target universe into primary sampling units (PSUs), generating approximately 1,900
geographically defined PSUs in every state and the District of Columbia. A PSU is composed of
single counties, various adjacent counties, or a metropolitan area. Subsequently, a PSU may vary
in population size. Smaller PSUs are identified as non-self-representing PSUs, which are
stratified geographically (e.g., by state) using criteria consistent with NHIS goals. Once the strata
have been identified, a sample of PSUs was selected. Among several non-self-representing strata,
two PSUs were chosen without replacement with probability proportional to sample size and
self-representing PSUs were selected with certainty. In non-self-representing strata with smaller
populations, one PSU was drawn (CDC, 2012).

19
To sufficiently recruit racial and ethnic groups, such as African Americans, Latinos, and
Asians, the NHIS also used clustering, stratification, and oversampling techniques. Based on
methods implemented by the U.S. Census Bureau, each non-self-representing and self-
representing PSU was partitioned into substrata of census blocks or combined blocks depending
on the density of African American, Latino, or Asian American individuals. The racial and
ethnic group density substrata were defined according to concentration figures from the 2000
Census. Recently developed housing in a PSU had its own substratum in an effort to produce the
most updated sample of households (CDC, 2012).
Participants
For the purpose of this project, 5,859 Latinos were available for study. The mean age of
participants was 40.31 years (SE = 0.26), with an even distribution of men and women (50.1%
male). Mexicans (38.0%) accounted for the largest majority of Latinos, followed by Mexican
Americans (23.2%), Central or South Americans (16.1%), Puerto Ricans (9.9%), other Latinos
(7.9%), and Cubans and Cuban Americans (5.0%). Due to small subgroup numbers, a separate
category was created that included Dominicans, other Latin Americans, mixed Hispanic
individuals, and other Spanish individuals.
Measures
Psychological distress. The NHIS implemented Kessler’s K6 scale (Kessler et al., 2002)
to measure psychological distress during the previous 30 days. The scale evaluates nervousness,
sadness, helplessness, restlessness, hopelessness, and worthlessness, with each item scored on a
range from 0 (none of the time) to 4 (all of the time). Most studies have confirmed a single-factor
structure of the K6 scale (Drapeau et al., 2010; Green, Gruber, Sampson, Zaslavsky, & Kessler,
2010; Kessler et al., 2002). However, a recent study by Arnaud et al. (2010) provided evidence

20
of a two-factor structure of the K6 scale, in which restlessness and nervousness share a common
latent structure. Additionally, the K6 scale has been demonstrated to reliably predict serious
mental illness (Kessler et al., 2003).
The K6 was designed based on the item response theory model to increase precision and
sensitivity in assessing distress, ensuring consistency across gender and age groups (Drapeau et
al., 2010; Drapeau et al., 2012; Green et al., 2010; Kessler et al., 2002). Furthermore, various
studies have validated K6 for use in Spanish, with an internal consistency satisfactory for
Spanish-speaking participants (α = .87; Kim et al., 2011; National Comorbidity Survey, 2005).
No cultural bias has been identified thus far (Drapeau et al., 2012).
Physical and mental illness. Lifetime mental illness was measured in terms of phobia,
depression, and other mental health disorders. Respondents were asked, “Ever been told you had
phobia or fears?” “Ever been told you had depression?” and “Ever been told you had other
mental health disorders?” Responses were then categorized to include zero mental disorders, one
mental disorder, and two or three mental disorders. To measure for comorbidity of mental and
physical health disorders, individuals were asked various questions regarding chronic health
problems, including whether they had coronary heart disease, hypertension, heart condition or
disease, stroke, cancer, diabetes, or chronic obstructive pulmonary disease.
Covariates. Demographics, socioeconomic status, and acculturation were included in the
analysis of psychological distress. Demographic factors included age, gender, and marital status.
Measures of socioeconomic factors included level of education, employment, and income.
Education responses included never graduated high school, high school graduate or GED, some
college or associate’s degree, college graduate, and postgraduate. Respondents were asked about
their employment status and considered unemployed if they were looking for work. Household

21
income was measured on a continuous scale. Proxy measures for acculturation measures
included language used during the NHIS interview (English or other) and the number of years
that the participant had lived in the United States.
Statistical Analysis
Multiple linear regression was used to answer the questions in this study. Descriptive and
bivariate statistics were calculated to examine the rates of lifetime comorbid mental illnesses,
lifetime comorbid physical and mental illnesses, and level of psychological distress. All
covariates were also analyzed. Use of cross-tabulation statistics accounted for the complications
inherent in the NHIS, which uses large, complex survey methods involving multistage sampling
techniques. All analyses included sampling weights to allow for accurate generalization to the
population of interest. Regression analyses were conducted for each research question while
accounting for covariates. An aggregate model of all Latinos was regressed, followed by a
regression model for each Latino subgroup. The years of residence in the United States variable
was not included in the regression model for Mexican Americans, as these respondents were all
born in the United States. However, the overall regression model for all Latinos included this
variable.
Potential multicollinearity issues were assessed (Table 1 and Table 2). The strongest
linear associations (r = -.59) were between living in the United States for at least 10 years and at
least 15 years. The Variance Inflation Factors (VIFs) of 3.38 for living in the United States for
10 years and 4.80 for 15 years were well below the threshold (VIF = 10) that would demonstrate
a problem of multicollinearity in multivariate regression models (Belsley, Kuh, & Welsch, 2004).
Nativity status, originally included in the analyses, was removed from the model due to

22
collinearity with years of residence in the United States. All analyses were completed using SAS
version 9.4.
Results
Sample Characteristics
Table 3 shows the distributions of all variables by Latino subgroup. The average age of
the sample was 40.31 years (SE = 0.26), with Cubans and Cuban Americans being the oldest on
average among subgroups (M = 48.14, SE = 1.14). The annual income of Cubans and Cuban
Americans, Puerto Ricans, Central and South Americans, and other Latinos ranged between
$50,227 and $53,168. Of note, Mexicans and Mexican Americans had the greatest contrast in
income, $40,527 and $56,961, respectively. Despite higher incomes, Puerto Ricans and Cubans
and Cuban Americans had the highest levels of unemployment (50.9% and 48.8%, respective). It
should be noted, however, that the unemployed category included participants who were not
working or not looking for a job. Mexican participants had with the lowest levels of education,
with more than half reporting less than a high school education. More than 80% of Cubans and
Cuban Americans, on the other hand, had at least a high school education. A majority of Latinos
(61.0%) had lived in the United States for at least 15 years. However, these numbers reflected
both immigrants and native-born participants.
With regard to the health status of Latinos (see Table 3), 13.8% of all Latinos reported
having at least one mental health problem in their lifetime. Puerto Ricans exhibited greater rates
of mental health disorders in their lifetime (more than 20%), whereas less than 11% of Mexicans
reported at least one mental disorder. Similar patterns were found for comorbid health problems;
12.7% of Puerto Ricans and 10.2% of Cubans and Cuban Americans reported comorbid health
and mental health disorders. Mexicans (4.9%) and Central and South Americans (4.7%) reported

23
less mental health and health comorbidity compared to other Latinos. Finally, average
psychological distress among all Latinos was 2.24 (SD = 0.07), with distress being highest
among Puerto Ricans (M = 3.29, SD = 0.20) and lowest among Cubans and Cuban Americans (M
= 1.90, SD = 0.23).
Multivariate Results
Table 4 shows coefficients for the effects of comorbid mental disorders on psychological
distress after adjusting for various socioeconomic factors using multiple linear regression.
Among all Latinos, reporting two or more mental disorders was associated with increased
psychological distress compared to those who reported having no mental disorders (β = .36, p
< .01). Reporting multiple mental disorders was a stronger predictor of increased psychological
distress compared to reporting one mental disorder (β = .31, p < .01). Several covariates also had
a statistically significant association with increased psychological distress, specifically fewer
years of residence in the United States or being a woman, unmarried, or unemployed. Conversely,
fewer years of education was associated with decreased psychological distress.
Mexicans demonstrated similar patterns in mental disorder comorbidity as those among
Latinos as an aggregate; having multiple mental disorders was a stronger predictor of
psychological distress (β = .38, p < .01) than reporting one mental disorder (β = .27, p < .01).
Additionally, speaking Spanish, being unmarried, and female gender were also risk factors for
increased distress. Among Mexican Americans, reporting a mental disorder was associated with
a 0.32 (p < .01) increase in distress compared to reporting no mental disorders. Reporting
multiple mental disorders was a stronger predictor of psychological distress (β = .45, p < .01)
compared to not reporting a mental health disorder. Some covariates for Mexican Americans had

24
an inverse relationship compared to those among Mexicans; speaking Spanish and higher level
of education were associated with decreased distress among Mexican Americans.
Similar patterns in mental disorder comorbidity were found, albeit at varying degrees,
across other Latino groups. Central and South Americans who reported multiple mental disorders
had increased psychological distress (β = .25, p < .01). The severity of reporting one mental
disorder, however, was a stronger predictor of increased distress (β = .28, p < .01). Having
resided for less than 15 years in the United States, being unmarried, speaking Spanish, and
female gender were associated with increased psychological distress. In contrast, having at least
a high school education was associated with decreased distress.
Puerto Ricans reported the highest increase in psychological distress when reporting
multiple mental disorders (β = .48, p < .01). Being a woman, being unemployed, speaking
Spanish, and having lived for less than five years in the United States was associated with
increased distress. Having at least a high school education, however, was associated with
decreased psychological distress. Finally, Cubans and Cuban Americans with one mental
disorder had an increase in distress of .42 (p < .01) compared to those who reported no mental
disorders. Reporting multiple mental disorders, Cubans and Cuban Americans experienced a .30
(p < .01) increase in psychological distress compared to those who did not report a mental
disorder. Having at least a high school education was associated with decreased distress, whereas
having less than 15 years of residence in the United States was associated with increased
psychological distress among Cubans and Cuban Americans.
To assess the effect of comorbid chronic physical health problems and mental disorders
on psychological distress, multiple linear regression models were used across all Latinos and
within each subgroup (Table 5). When modeling across all Latinos, individuals reporting only

25
physical health problems had slightly increased psychological distress (β = .08, p < .01) whereas
those who report only mental disorders had even higher levels (β = .23, p < .01) when compared
to those with no overall health problems. Comorbid mental and physical health disorders were
associated with increased distress at much higher levels (β = .43, p < .01) compared to reporting
no disorders. Covariate results showed similar patterns as in Table 4, with the exception of
Spanish language being associated with increased distress.
Similar patterns of distress and health and mental health disorder comorbidity were found
across Latino subgroups, although at varying levels. Cubans and Cuban Americans reporting
only mental health disorders had higher distress levels (β = .28, p < .01) compared to those who
indicated having both physical and mental health disorders (β = .47, p < .01). Puerto Ricans
reported having the greatest distress among respondents reporting physical health and mental
disorders, with an average increase in distress of .53 (p < .01). Finally, Central and South
Americans reporting physical health and mental disorders had higher psychological distress (β
= .32, p < .01) than those with only health issues (β = .08, p < .01) or mental disorders (β = .22, p
< .01).
Discussion
The results from these analyses addressed the increased need for studies that examine
Latino heterogeneity in the mental health field. Specifically, this study examined Latino
subgroup differences in level of psychological distress and its association with comorbid mental
health and physical health problems. Findings from this study can be used to identify Latino
subgroups most at risk of high psychological distress and inform public health officials regarding
allocation of resources for groups with the greatest need.

26
Puerto Ricans generally reported the high levels of psychological distress, whereas
Cubans and Cuban Americans, Mexicans, and Mexican Americans reported the lowest distress.
As expected, these observations are concordant with previous studies (Bratter & Eschbach, 2005;
Rivera et al., 2008; Shrout et al., 1992; Zhang et al., 2012), confirming that aggregation of health
outcomes among Latinos, specifically psychological distress, undermines the substantial
variation found across subgroups. The current findings addressed the questions set forth in this
study. First, do comorbid mental illnesses result in increased severity of psychological distress
and vary between Latino subgroups? Are protective and risk factors associated with
psychological distress among Latinos? Latinos, as a whole, had twice as intense psychological
distress when reporting multiple mental disorders compared to those who had only one mental
disorder. Modeling this outcome also suggested potential risk and protective factors for levels of
psychological distress in terms of study covariates. Having less than a high school education,
being unmarried, female gender, residing less than five years in the United States, and speaking
Spanish were associated with increased psychological distress. In contrast, results indicated that
living more than 10 years in the United States, speaking English, being employed, and being
married may protect against increased psychological distress.
Assessment of Latino subgroups demonstrated that some groups were more prone to
increased psychological distress than others with regard to comorbidity. Of note, Puerto Ricans
with comorbid mental disorders were at greatest risk of increased psychological distress among
all Latinos. Although it is difficult to deduce from this study why comorbidity is strongly
associated with increased psychological distress among Puerto Ricans, this finding is congruent
with previous findings (e.g., Alegría, Mulvaney-Day, Torres, et al., 2007; Bratter & Eschbach,

27
2005) regarding increased mental health morbidity among Puerto Ricans compared to all other
Latino groups.
When considering demographic, socioeconomic and acculturation covariates, no single
protective or risk factor affected risk of psychological distress among all Latino subgroups.
Speaking Spanish may be a protective component for Mexican Americans. In contrast, this
aforementioned factor may be a risk factor for Puerto Ricans. Similarly, education was a risk
factor for increased psychological distress among Mexicans but was protective for Puerto Ricans
in this study. Although previous literature (e.g., Alegría, Canino, Stinson, & Grant, 2006; Canino
& Alegría, 2009; Gil, Vega, & Turner, 2002; Vega & Gil, 2005) has identified that the
magnitude of both protective and risk factors vary among Latino subgroups, the results from this
study confirmed findings observed by Rivera et al. (2008), suggesting that protective and risk
factors have an inverse effect among subgroups. Such findings are unique and indicative of the
impact of protective and risk factors on psychiatric morbidity between subgroups. Mirowsky and
Ross’ (1980) ethnic-culture perspective postulates that sociocultural factors affect the nature of
health problems between subgroups, but is limited in terms of identifying specific sociocultural
processes that may explain observations in this study, specifically the inverse effect of protective
and risk factors among subgroups. Several concepts can partially explicate these observations.
The frustrated status hypothesis (Alegría et al., 2006; Burnam, Hough, Karno, Escobar, &
Telles, 1987; Robins & Regier, 1991; Vega, Kolody, et al., 1998) asserts that U.S.-born Latinos
experience higher pressure to attain status and are thus more distressed and at greater risk of
psychiatric morbidity than their foreign-born counterparts. Social status expectations for U.S.-
born Latinos are measured against the standard of perceived status attainment found among their
peers (Alegría et al., 2006). Thus, U.S.-born Latinos subject to the standards of the dominant U.S.

28
culture may adopt the value of higher education as a form of status attainment. However, this
hypothesis does not help explain why increased education was a risk factor for increased
psychological distress among Mexicans in this study. Research assessing intergroup dynamics
among Mexicans is needed to help answer this question. Nevertheless, the frustrated status
hypothesis suggests that expectations of status depend on the network of peers with whom
foreign-born or U.S.-born Latinos identify (Alegría et al., 2006). Individuals in densely
populated Latinos communities may perceive status attainment in the context of their own
network rather than the dominant U.S. culture, which may help Latinos integrate into society
with a sense of accomplishment (Alegría et al., 2006). This view may help explain the decreased
psychological distress found among Mexicans who had lived in the United States for at least
several years.
Grant et al. (2004) also identified traditional cultural retention as a protective factor for
Mexican Americans. Their study found that Mexican Americans’ advantage over Anglo
Americans regarding the risk of psychiatric disorders was related to maintaining traditional
values of strong family cohesion and religiosity. According to Santiago-Rivera, Arredondo, and
Gallardo-Cooper (2002), a survey by the The Washington Post found that “Latinos who retained
dominant use of the Spanish language have a more traditional value structure than those who are
bilingual” (p. 39). Findings from the current study suggest that the safeguarding effect of
speaking Spanish among Mexican Americans buffers psychological distress. However, this
hypothesis is limited to Mexican Americans, because it does not help explain why the remaining
Latino groups were at risk of increased psychological distress related to speaking Spanish.
In sum, these hypotheses are limited in terms of adequately explaining the inverse
relationship of risk and protective factors among Latino groups. Nevertheless, these explanations

29
are illustrative of the complex influence of sociocultural factors on each subgroup and hint at an
underlying mechanism that has yet to be determined. Although Rivera et al. (2008) began to
identify the varied effect of protective and risk factors among Latino subgroups, research is
needed to determine the underlying mechanisms to explain these observations.
Results from the current study also answered the second question (i.e., Are comorbid
chronic physical health problems and mental illnesses associated with increased psychological
distress and do they vary among Latino subgroups?). Findings indicated exacerbation of
psychological distress when participants reported both physical health and mental disorders,
although the intensity of distress varied among subgroups. Similar to the conclusions related to
the first research question, the differences found among subgroups are indicative of sociocultural
factors that distinguish Latino subgroups. Ultimately, the three study questions assessed the
underlying sociocultural patterns that both unify and distinguish Latino subgroups. Overall, the
covariate effects were consistent with those related to the first research question.
The current study has limitations. First, data from this study did not assess the gamut of
various sociocultural factors that influence intergroup dynamics. Risk and protective factors for
the Latino population also include factors such as discrimination, cultural conflict (i.e.,
acculturative stress), social network measures, immigration status, and other sociocontextual
factors not available in the NHIS. Proxy measures for acculturation were used to assess
intergroup dynamics in this study, which is important to account for differences in psychological
distress among subgroups that socioeconomic factors are unable to capture (Williams & Collins,
1995). However, further studies are required that use data rich in sociocultural factors to assess
the complexity of intergroup dynamics. Secondly, lifetime mental and physical health illness was
used as a predictor of psychological distress during the previous 30 days. Respondents may have

30
reported illnesses in the past that did not affect their psychological distress during the previous
month. Furthermore, it was difficult to determine differences in degree of distress among Latino
groups, because these analyses could not adequately determine comparative levels of distress.
Finally, the psychosomatic features associated with nervios, a term for psychological distress
common among Latinos, may confound morbidity of health problems. Thus, it is difficult to
separate whether distress was caused by physical illnesses, increased distress manifested as
physical ailments, or both.
Despite these limitations, these findings can help practitioners and public health officials
identify how to prioritize health programs aimed at Latino populations at greatest risk of negative
outcomes. Targeted efforts can efficiently address Latino health needs in various parts of the
country where certain Latino groups are most prevalent. Ultimately, these efforts will help
achieve the ultimate goal of providing quality services that are congruent with an increased
understanding of the sociocultural dynamics found among Latino groups.
Provided that psychological distress is a manifestation of mental health and influenced by
cultural practices, values, and group experiences that distinguish Latino subgroups, the next step
is to understand how psychological distress manifests among Latinos. Although the K6 scale
used by the NHIS has been validated for use across ethnic groups (Drapeau et al., 2012; Kessler
et al., 2002; Kim et al., 2011), it should not be assumed that the impact of culture can be
removed from subjective interpretations of symptoms (Bratter & Eschbach, 2005). Therefore,
future studies must aim to identify interpretations of psychological distress among Latinos to
better assess behaviors that are unique to Latinos in general and among Latino groups.

31
STUDY TWO: PSYCHOLOGICAL DISTRESS BEHAVIORAL PATTERNS AMONG LATINOS:
WE DON’T SEE OURSELVES AS WORTHLESS
The features of psychological distress include emotional, cognitive, behavioral, and
psychophysiological symptoms that are related to a mental disorder or illness (Dohrenwend,
Shrout, Ergi, & Mendelson, 1980; Kessler et al., 2002; Link & Dohrenwend, 1980). Dohrenwend
et al. (1980) identified psychological distress as inherent in human behavior, independent of
sociocultural background and present across all forms of illnesses. Using Dohrenwend et al.’s
(1980) work to structure the development of a new measure of psychological distress for
epidemiological research, Kessler et al. (2002) developed the K10 and K6 scales. These scales
were also based on various established diagnostic scales, representing a comprehensive set of
domains found in the revised third edition of the Diagnostic and Statistical Manual of Mental
Disorders (American Psychiatric Association, 1987). Kessler et al. (2002) thus determined that
the fundamental features of psychological distress are restlessness, sadness, worthlessness,
nervousness, hopelessness, and helplessness.
Although Kessler et al.’s (2002) behavioral features of psychological distress have been
validated across various sociocultural backgrounds, patterns in the manifestation of
psychological distress may vary between sociocultural groups at the community level. A study
funded by the World Health Organization (Draguns, 1990) identified common symptoms of
depression across various countries: anxiety, tension, sadness, and lack of energy. However,
respondents from Western countries reported additional feelings of guilt whereas non-Western
countries reported somatic complaints. This is especially true among Latinos, who may
experience nervios, a term for psychological distress prominent among Latinos and an example
of a syndrome whose manifestations have been shaped by culture over many generations

32
(Castillo, 1997; Guarnaccia, 1997; Mirowsky & Ross, 1980; Sam & Moreira, 2012; San Miguel
et al., 2006; USDHHS, 2001).
In previous studies (e.g., Bratter & Eschbach, 2005; Dallo et al., 2013; Rivera et al.,
2008), evaluation of Latino heterogeneity with regard to psychological distress has focused on
identifying risk factors and describing the etiology of various mental health problems. However,
research examining Latino psychological distress has not focused on exploring and identifying
how psychological distress manifests among Latinos. Consequently, with limited knowledge
regarding the expression of psychological distress that characterizes Latino groups from one
another, mental health practitioners are at risk of overlooking behaviors that are uniquely
indicative of distress in a given subgroup. Furthermore, mental health professionals are forced to
conflate the otherwise unique nature of Latino heterogeneity. This aim of this study was to
examine patterns of psychological distress among Latino subgroups. Specifically, this study
addressed the following questions: Do Latinos exhibit psychological distress behavioral profiles
that are ethnically unique? If so, what are they?
Methods
Data Source
The NHIS is an annual, cross-sectional survey designed to report nationally
representative estimates related to various health issues, including health status and treatment use.
Since 1960, the National Center for Health Statistics and the CDC have used the NHIS to
monitor trends in illness and treatment use and progress toward achieving national health
objectives (CDC, 2012). The NHIS excludes individuals in long-term care institutions, active-
duty armed forces personnel, U.S. nationals living in foreign countries, and individuals in
correctional facilities.

33
To accomplish sampling efficiency for a nationwide survey occurring throughout the year,
multistage sampling techniques were implemented to identify potential participants (CDC, 2012).
Since 2006, this method has been used to partition the target population into various strata and
clusters. The target universe consisted of individuals living in dwelling units that were either
households or noninstitutional quarters (e.g., collegiate dormitories). The first stage involved
partitioning the target universe into PSUs, generating roughly 1,900 geographically defined
PSUs in every state and the District of Columbia. A PSU is composed of single counties, various
adjacent counties, or a metropolitan area. Subsequently, PSUs may vary in population size.
Smaller PSUs were identified as non-self-representing PSUs, which were stratified
geographically (e.g., by state) using criteria consistent with NHIS goals. Once the strata were
identified, a sample of PSUs was selected. Among several non-self-representing strata, two PSUs
were chosen without replacement with probability proportional to sample size and self-
representing PSUs were selected with certainty. In non-self-representing strata with a smaller
population, one PSU was drawn (CDC, 2012).
To sufficiently recruit racial and ethnic groups, such as African Americans, Latinos, and
Asians, the NHIS also used clustering, stratification, and oversampling techniques. Based on
methods implemented by the U.S. Census Bureau, each non-self-representing and self-
representing PSU was partitioned into substrata of census blocks or combined blocks depending
on the density of African American, Latino, or Asian American individuals. The racial and
ethnic group density substrata were defined according to concentration figures from the 2000
Census. Recently developed housing in a PSU had its own substratum in an effort to produce the
most updated sample of households (CDC, 2012).

34
Participants
For the purpose of this project, 4,921 Latinos were available for study. The mean age of
participants was 40.2 years old (SE = 0.26), with an even distribution of men and women (50.9%
male). Mexicans (38.4%) accounted for the largest majority of Latinos, followed by Mexican
Americans (24.0%), Central or South Americans (16.1%), Puerto Ricans (10.0%), other Latinos
(7.1%), and Cubans and Cuban Americans (4.4%). Due to small subgroup numbers, a separate
category was created that included Dominicans, other Latin Americans, mixed Hispanic
individuals, and other Spanish individuals.
Measures
Psychological distress. The NHIS uses Kessler’s K6 scale (Kessler et al., 2002) to
measure psychological distress during the previous 30 days. The scale evaluates nervousness,
sadness, helplessness, restlessness, hopelessness, and worthlessness, with each item scored on a
range from 0 (none of the time) to 4 (all of the time). Most studies (Drapeau et al., 2010; Green et
al., 2010; Kessler et al., 2002) confirmed a single-factor structure of the K6 scale. However, a
recent study by Arnaud et al. (2010) provided evidence of a two-factor structure of the K6 scale,
in which restlessness and nervousness share a common latent structure.
The K6 was designed based on the item response theory model to increase precision and
sensitivity in assessing distress, ensuring consistency across gender and age groups (Drapeau et
al., 2010; Drapeau et al., 2012; Green et al., 2010; Kessler et al., 2002). Furthermore, various
other studies have validated K6 for use in Spanish, with an internal consistency satisfactory for
Spanish-speaking participants (α = .87; Kim et al., 2011; National Comorbidity Survey, 2005).
No cultural bias has been identified thus far (Drapeau et al., 2012).

35
Covariates. Demographic and socioeconomic covariates were included to identify
patterns of psychological distress among Latino subgroups. Demographic factors included age,
gender, and marital status. Measures of socioeconomic factors included level of education and
employment. Education responses included never graduated high school, high school graduate or
GED, some college or associate’s degree, college graduate, and postgraduate. Due to the ordered
categorical measurement of education, the variable was treated as a Likert scale, using interval-
level measurement for analysis. Respondents were asked about their employment status and
considered unemployed if they were looking for work. Income, which was included in the first
study, was not included in the analysis because it prevented modeling of the latent classes.
Additionally, proxy measures of acculturation, namely language used during the NHIS interview
and number of years of residence in the United States, were not included in the analysis due to a
significant number of missing responses.
Statistical Analysis
Latent class analysis (LCA) is well suited to identify unique psychological distress
profiles among Latinos (McCutcheon, 1987). Using Mplus 7.3, this study performed LCA of
various responses to the K6 related to nervousness, hopelessness, restlessness, worthlessness,
sadness, and helplessness. Two parameters characterize LCA (Agrawal, Lynskey, Madden,
Bucholz, & Heath, 2006): the prevalence of each class and the probability that an individual in a
given class will endorse one of the six items measured by the K6. To identify classes that may be
unique to each Latino subgroup, each group was entered as a covariate. The relationship of
covariates with class membership is ascertained by concurrently estimating multinomial logistic
regression and odds ratios to assess the effect of a covariate on the probability of class
membership relative to the reference class (Auerbach & Collins, 2006; Connell, Gilreath, &

36
Hansen, 2009; Lanza, Collins, Lemmon, & Schafer, 2007; Magidson & Vermunt, 2002; Nylund,
Asparouhov, & Muthén, 2007).
A preliminary series of models was conducted to determine the adequate number of
classes for psychological distress. First, a single-class model (without covariates) was developed,
after which models with covariates and multiple classes (e.g., two classes, three classes), each
representing different patterns of psychological distress behavior, were developed. Model fit was
compared among freely estimated models. The best model was selected based on suggested
indexes, including low adjusted Bayesian Information Criterion (BIC) relative to other models,
significant Lo-Mendell-Rubin Likelihood Ratio Test (LMR LRT), and adequate quality of
classification (Nylund et al., 2007). After completing these separate analyses, a final combined
LCA model was estimated. Sample weights, clusters, and stratum variables were included in the
analyses to account for the complex sampling design. Because Mplus was unable to incorporate
nonnested cluster and strata variables, PSUs representing more than one stratum were treated as
distinct clustering units (Connell et al., 2009).
Results
Table 6 lists the sample characteristics of respondents and psychological distress
responses. Most respondents were married or cohabitating (61.0%), with close to two thirds
(61.3%) of respondents reporting a high school education or less and being employed (64.7%).
Most respondents reported few to no symptoms on the K6 (85.1% or higher), with most
respondents indicating few to no symptoms of worthlessness (94.4%).
Successive LCA models were run to determine the most parsimonious model to
characterize patterns of psychological distress (Table 7). Unlike previous studies that have used
nonsignificant LMR LRT p-values to determine the best model, use of the BIC has been shown

37
to be one of the best tools to accurately determine the correct number of classes (Jedidi, Jagpal,
& DeSarbo, 1997; Nylund et al., 2007; Roeder & Wasserman, 1997). A five-class model was
determined to have the best overall fit for psychological distress. Using five-class model,
however, would not accurately describe patterns in psychological distress profiles that would be
informative and practical in treatment practice, because two of the five classes shared patterns of
psychological distress that were difficult to distinguish. Consequently, a four-class model was
accepted as the most parsimonious and practical model to characterize psychological distress
patterns. The four classes were titled moderate psychological distress with low worthlessness and
hopelessness; mild sadness, nervousness, and restlessness; high psychological distress; and no
psychological distress (Table 8).
Moderate psychological distress with low worthlessness and hopelessness accounted for
13.6% of the sample. Respondents in this class reported few to no feelings of worthlessness
(75.7%) and hopelessness (60.4%), yet approximately half of these respondents reported some
feelings of sadness, nervousness, restlessness, or helplessness. Mild sadness, nervousness, and
restlessness affected 13.0% of the sample, with more than half of these respondents reporting a
few of the aforementioned feelings. These same respondents, however, reported no feelings of
worthlessness (80.2%), helplessness (53.7%), and hopelessness (66.8%). Respondents indicating
high psychological distress accounted for 2.8% of the sample. Generally, these respondents
reported feelings of every type of distress most if not all of the time. Of note, 20.4% reported no
feelings of worthlessness, representing the least prevalent symptom in the high psychological
distress class. Last, participants indicating no psychological distress accounted for 70.7% of the
sample. Close to if not more than 90% of these respondents reported no feelings of any type of
distress, with a scarce number of responses indicating few to some symptoms.

38
Multinomial logistic regression analyses demonstrated that Latino group association and
demographic and socioeconomic factors influenced class membership (Table 9). Compared to
Mexican respondents, Puerto Rican respondents were more likely to report moderate
psychological distress with low worthlessness and hopelessness (OR = 1.88, 95% CI = 1.21–
2.93) and more than twice as likely to report high psychological distress (OR = 2.36, 95% CI =
1.21–4.57). Mild sadness, nervousness, and restlessness were less likely to be endorsed by Puerto
Rican respondents (OR = 0.40, 95% CI = 0.22–0.72), Cubans and Cuban Americans (OR = 0.49,
95% CI = 0.27–0.87), and other Latinos (OR = 0.55, 95% CI = 0.31–0.96). No statistically
significant associations were observed for Mexican Americans and Central and South Americans.
In terms of demographic and socioeconomic factors, married or cohabitating respondents
were less likely to fall in any of the psychological distress classes (i.e., moderate psychological
distress with low worthlessness and hopelessness; mild sadness, nervousness, and restlessness; or
high psychological distress) compared to the no psychological distress class. Increased education
was associated with being less likely to report high psychological distress compared to the no
psychological distress class (OR = 0.61, 95% CI = 0.48–0.78). Compared to women, men were
less likely to report moderate psychological distress with low worthlessness and hopelessness
(OR = 0.57, 95% CI = 0.44–0.75) or mild sadness, nervousness, and restlessness (OR = 0.62,
95% CI = 0.48–0.80). Finally, employed respondents were less likely than unemployed
respondents to report moderate psychological distress with low worthlessness and hopelessness
(OR = 0.64, 95% CI = 0.49–0.84) or high psychological distress (OR = 0.38, 95% CI = 0.23–
0.64).

39
Discussion
Results indicated variation in the behavioral patterns of psychological distress among
Latinos. Analyses indicated that Latinos who reported mild or moderate levels of distress did not
report similar severity levels across all domains of the psychological distress profile outlined in
the K6 (Kessler et al., 2002), suggesting that these behavioral domains are not characteristic of
Latinos. Respondents with mild psychological distress characterized their experience as having
mild symptoms of sadness, nervousness, and restlessness but not feelings of hopelessness,
helplessness, or worthlessness. With the exception of helplessness, moderate cases of
psychological distress maintained a similar symptom profile, in which worthlessness and
hopelessness were not descriptive of general psychological distress among Latinos. Only in the
high psychological distress class did individuals report increased hopelessness and worthlessness
most or all of the time. In this class, 55.6% of respondents reported feelings of worthlessness
most of the time, a low rate compared to other domains, which ranged from 68.9% for
restlessness to 78.7% for helplessness. Furthermore, 28.6% reported few or no feelings of
worthlessness despite reporting high psychological distress.
Although the K6 has been validated across ethnic groups and adapted internationally for
use in research (Drapeau et al., 2012; Kim et al., 2011; Kessler et al., 2002), results from the
present study suggest that underlying cultural elements affect the subjective interpretations of
symptoms reported by Latinos (Bratter & Eschbach, 2005). Despite these limitations, the
measure was able to indicate which symptoms were more or less relevant for Latinos, and
findings from the present study can advance understanding of Latino health issues currently
being debated. According to the CDC (2014), 4.1% of Latinos report serious psychological

40
distress,
2
higher than rates seen among Anglo Americans (3.6%) and African Americans (3.0%).
Consequently, Latinos may be at increased risk of serious mental disorders, depression, and
suicide, among other negative outcomes (Hendricks et al., 2015; Kessler et al., 2003; McKelvey
et al., 1998). However, the etiology of Latino mental health morbidity is more varied and
complex. Rates of depression vary among Latinos, from rates as low as 2.5% for Cuban
Americans to as high as 6.9% for Puerto Ricans, compared to 3.6% among Anglo Americans
(Oquendo et al., 2001). However, suicide rates among Latinos are more than two times lower
than the rates among Anglo Americans (CDC, 2009; Oquendo et al., 2001). Among several risk
factors associated with suicide and depression, feelings of hopelessness and a low sense of worth
have been consistently validated throughout the literature (McLean, Maxwell, Platt, Harris, &
Jepson, 2008). Findings from the current study indicated that these risk factors are not as
prevalent as among Anglo Americans, which may explain lower rates of suicidal behavior
despite increased prevalence of high psychological distress among Latinos.
The reduced prevalence of worthlessness and hopelessness may be rooted in cultural
values that protect against increased morbidity despite the presence of high psychological
distress among Latinos. Traditional values such as strong family cohesion, religiosity, and
connectedness are common in many Latino families and may have a buffering effect that reduces
mental health morbidity (Alegría et al., 2006; CDC, 2009; Grant et al., 2004; Jimenez, Alegría,
Camino-Gaztambide, & Zayas, 2014; Rivera et al., 2008). The buffering effects of cultural
values vary in impact among Latinos; some subgroups benefit more than others, as illustrated by
previous studies (Alegría et al., 2006; Canino & Alegría, 2009; Gil et al., 2002; Vega & Gil,

2
The current study used the same data as the CDC (2014) but found 2.8% of respondents reported high
psychological distress due to differences in the metrics and analyses used.

41
2005). The sociocultural mechanism that underlies the variation in Latino subgroup morbidity is
thus complex and research is needed to continue to unravel its processes.
The current study determined that Puerto Ricans and Cubans and Cuban Americans were
less likely than Mexicans to report mild sadness, nervousness, and restlessness. With regard to
moderate or high psychological distress profiles, Puerto Ricans were more likely than Mexicans,
including twice as likely regarding high psychological distress, to fall within these classes. These
patterns of increased risk of moderate or high psychological distress among Puerto Ricans are
congruent with previous research reporting high rates of mental health morbidity among Puerto
Ricans (Canino & Alegría, 2009). The mechanisms involved in this higher risk of morbidity are
not well understood (Canino & Alegría, 2009), but there are some possible explanations. Results
from the current study suggest that the underlying sociocultural processes inherent in Puerto
Rican groups differ from other Latino groups and thus play a more central role in increased or
decreased mental health morbidity. Alegría et al. (2006) used the example of discrimination,
whereby Puerto Ricans may be more subject to continuous discrimination than Mexicans or
Cubans by not acculturating into the dominant U.S. culture. The first Puerto Rican migrants were
stigmatized in the United States due to the public perception that their migration was related to a
period of immense unemployment in Puerto Rico and their perceived efforts to obtain
government support (Maldonado-Denis, 1980). Due to this historical context, Puerto Ricans may
have adopted a unique heightened ethnic identity that buffers the risk of some mental health
problems (e.g., substance use, suicide) and not others (e.g., psychological distress, mood and
anxiety disorders).
Because unique psychological distress profiles do indeed characterize and distinguish
Latino groups, how are these distinct profiles associated with mental health treatment use?

42
Previous studies assessing treatment use have focused on identifying correlates of service use
(e.g., Dallo et al., 2013; Lo et al., 2014), providing mental health professionals with a greater
understanding of risk and protective factors associated with treatment use. However, few of these
studies modeled treatment use among Latino subgroups and thus were limited in terms of
providing a contextually accurate assessment of service use. Assessing treatment use in specific
contexts, with regard to both psychological distress and Latino subgroups, can provide mental
health professionals with a more comprehensive understanding of behavioral patterns associated
with treatment use among Latinos. Further research is needed to examine the association
between psychological distress profiles and mental health treatment use during the previous year.
Some limitations of this study should be noted. Nativity was not accounted for due to
limitations in the data. Much of the research on Latino mental health has accounted for nativity,
due to its association with mental health outcomes and significance to the understanding of
Latino group needs and the debate on various public health issues. Similarly, the NHIS
aggregation of Cubans and Cuban Americans and U.S.- and foreign-born Puerto Ricans
diminished the ability to make inferences regarding Latino groups that encompass both U.S.- and
foreign-born populations. Second, the current study assessed classes of psychological distress
behavior patterns among Latinos but did make comparisons using similar statistical methods to
Anglo American respondents to confirm differences in psychological distress behaviors between
the two major ethnic groups. Future investigations should expand on the present study to confirm
that psychological distress behaviors are indeed unique between these two major groups.
In sum, the current study suggested that worthlessness (and hopelessness to a smaller
degree) is not an inherent manifestation of psychological distress among all Latinos and may
help explain why Latinos are at less risk of certain mental illnesses and overall psychiatric

43
morbidity despite reporting rates of psychological distress higher than any other ethnic group.
Although Latinos face many challenges as ethnic minorities due to issues of language
proficiency, socioeconomic disadvantages, and discrimination, cultural factors are equally as
influential in buffering these effects on their mental health.

44
STUDY THREE: PSYCHOLOGICAL DISTRESS BEHAVIORAL PATTERNS AND MENTAL HEALTH
SERVICE USE AMONG LATINOS: A POST HOC ANALYSIS
One of the defining features of high psychological distress is the inability to effectively
cope with emotional turmoil and other stressors (Drapeau et al., 2012; Horwitz, 2007; Ridner,
2004). Treatment is thus accessed by individuals reporting distress and is often the final recourse
for many families that are unable to cope, despite the help they may receive from their social
network. Generally, increased psychological distress is associated with emergency
hospitalization, treatment by physicians, and use of services from health professionals
(Stockbridge, Wilson, & Pagán, 2014; Vilhjalmsson & Gudmundsdottir, 2014). When
considering the service use patterns of Latinos, however, the pathway toward mental health
services features various challenges. Compared to Anglo Americans, Latinos with a mental
illness are at risk of underutilizing services, particularly immigrants (Barrio, Yamada, Atuel, et
al., 2003; Barrio, Yamada, Hough, et al., 2003; USDHHS, 2001). Failure to receive mental
health treatment puts Latinos at greater risk of poor health outcomes, such as homelessness,
hospitalization, and worsening of psychiatric symptoms (Dixon et al., 2009; Fischer et al., 2008;
Kreyenbuhl et al., 2009). An estimated 40% of Latinos who are in need of care actually receive
treatment (Alegría, Mulvaney-Day, Woo, et al., 2007; Kessler et al., 2002; Wang et al., 2005),
thus demanding urgency on the part of researchers and authorities in terms of increasing access
to treatment for those in need.
Given the nature of these illnesses and the unique needs of Latinos related to their mental
health, a substantial amount of research has provided information on the various factors that
affect their path toward treatment (e.g., Ai et al., 2012; Ai et al., 2013; Alegría, Mulvaney-Day,
Woo, et al., 2007; Keyes et al., 2012). General findings from these studies indicated that

45
sociocultural factors, specifically nativity, language, age at migration, generation status, and
years of residence in the United States, are often associated with whether or not Latinos use
services and often vary from the effects seen in other major ethnic populations. Based on results
from previous studies, however, it is also important to assess Latino subgroups in their own
context, given how their unique immigration history, social class, and health backgrounds can
influence how psychological distress affects their needs. Alegría, Mulvaney-Day, Woo, et al.
(2007) considered heterogeneity among Latino groups with regard to mental health service use
and determined that rates of use were highest among U.S.-born Latinos and Puerto Ricans
compared to foreign-born Latinos and other Latino groups. Their data and conclusions
emphasized the inclusion of culture as a contextual factor in assessing how the treatment process
is affected among Latino groups. The current study expanded on Alegría, Mulvaney-Day, Woo,
et al.’s (2007) approach by including psychological distress behavioral profiles unique to Latinos
in evaluating treatment use. The study addressed the following question: What is the association
between psychological distress behavioral patterns and mental health service use during the
previous year? Based on evidence in the literature, it was hypothesized that (a) higher distress
would be associated with increased use of mental health services and (b) Puerto Ricans would be
most likely to seek mental health services compared to other Latino groups.
Methods
Data Source
The NHIS is an annual, cross-sectional survey designed to report nationally
representative estimates related to various health issues, including health status and treatment use.
Since 1960, the National Center for Health Statistics and the CDC have used the NHIS to
monitor trends in illness and treatment use and progress toward achieving national health

46
objectives (CDC, 2012). The NHIS excludes individuals in long-term care institutions, active-
duty armed forces personnel, U.S. nationals living in foreign countries, and individuals in
correctional facilities.
To accomplish sampling efficiency for a nationwide survey occurring throughout the year,
multistage sampling techniques were implemented to identify potential participants (CDC, 2012).
Since 2006, this method has been used to partition the target population into various strata and
clusters. The target universe consisted of individuals living in dwelling units that were either
households or noninstitutional quarters (e.g., collegiate dormitories). The first stage involved
partitioning the target universe into PSUs, generating roughly 1,900 geographically defined
PSUs in every state and the District of Columbia. A PSU is composed of single counties, various
adjacent counties, or a metropolitan area. Subsequently, PSUs may vary in population size.
Smaller PSUs were identified as non-self-representing PSUs, which were stratified
geographically (e.g., by state) using criteria consistent with NHIS goals. Once the strata were
identified, a sample of PSUs was selected. Among several non-self-representing strata, two PSUs
were chosen without replacement with probability proportional to sample size and self-
representing PSUs were selected with certainty. In non-self-representing strata with a smaller
population, one PSU was drawn (CDC, 2012).
To sufficiently recruit racial and ethnic groups, such as African Americans, Latinos, and
Asians, the NHIS also used clustering, stratification, and oversampling techniques. Based on
methods implemented by the U.S. Census Bureau, each non-self-representing and self-
representing PSU was partitioned into substrata of census blocks or combined blocks depending
on the density of African American, Latino, or Asian American individuals. The racial and
ethnic group density substrata were defined according to concentration figures from the 2000

47
Census. Recently developed housing in a PSU had its own substratum in an effort to produce the
most updated sample of households (CDC, 2012).
Participants
For the purpose of this project, 4,921 Latinos were available for study. The mean age of
participants was 40.2 years old (SE = 0.26), with an even distribution of men and women (50.9%
male). Mexicans (38.4%) accounted for the largest majority of Latinos, followed by Mexican
Americans (24.0%), Central or South Americans (16.1%), Puerto Ricans (10.0%), other Latinos
(7.1%), and Cubans and Cuban Americans (4.4%). Due to small subgroup numbers, a separate
category was created that included Dominicans, other Latin Americans, mixed Hispanic
individuals, and other Spanish individuals.
Measures
Mental health treatment use. Use of mental health treatment was measured by asking
participants, “During the past 12 months, have you seen or talked to any of the following health
care providers about your own health: a mental health professional such as a psychiatrist,
psychologist, psychiatric nurse, or clinical social worker?” Respondents who answered
affirmatively were categorized as having had a treatment visit.
Psychological distress. The NHIS implemented Kessler’s K6 scale (Kessler et al., 2002)
to measure psychological distress during the previous 30 days. The scale evaluates nervousness,
sadness, helplessness, restlessness, hopelessness, and worthlessness, with each item scored on a
range from 0 (none of the time) to 4 (all of the time). Most studies confirmed a single-factor
structure of the K6 scale (Drapeau et al., 2010; Green et al., 2010; Kessler et al., 2002). However,
a recent study by Arnaud et al. (2010) provided evidence of a two-factor structure of the K6 scale,
in which restlessness and nervous share a common latent structure.

48
The K6 was designed based on the item response theory model to increase precision and
sensitivity when assessing distress, ensuring consistency across gender and age groups (Drapeau
et al., 2010; Drapeau et al., 2012; Green et al., 2010; Kessler et al., 2002). Furthermore, various
other studies have validated the K6 for use in Spanish, with a satisfactory internal consistency for
Spanish-speaking participants (α = .87; Kim et al., 2011; National Comorbidity Survey, 2005).
No cultural bias has been identified thus far (Drapeau et al., 2012).
Covariates. Demographics and socioeconomic indicators were included to identify
patterns of psychological distress among Latino subgroups. Demographic factors included age,
gender, and marital status. Measures of socioeconomic factors included level of education and
employment. Education responses included never graduated high school, high school graduate or
GED, some college or associate’s degree, college graduate, and postgraduate. Due to the ordered
categorical measurement of education, the variable was treated as a Likert scale, using interval-
level measurement for analysis. Respondents were asked about their employment status and were
considered unemployed if they were looking for work. Income, which was included in the first
study, was not included in the analysis because it prevented modeling of latent classes.
Additionally, proxy measures of acculturation, namely language used during the NHIS interview
and number of years of residence in the United States, were not included in the analysis due to a
significant number of missing responses.
Statistical Analysis
LCA was used to identify mental health use among Latinos (McCutcheon, 1987). Classes
were determined by analyzing nervousness, hopelessness, restlessness, worthlessness, sadness,
and helplessness symptoms measured by the K6. Two parameters characterize LCA (Agrawal et
al., 2006): the prevalence of each class and the probability that an individual in a given class will

49
endorse one of the six items measured by the K6. Additionally, use of mental health services was
modeled along with the K6 responses as a binary distal outcome. To identify classes unique
among each Latino subgroup, each Latino group was entered as a covariate. The relationship of
covariates with class membership is ascertained by concurrently estimating multinomial logistic
regression and odds ratios to assess the effect of a covariate on the probability of class
membership relative to the reference class (Auerbach & Collins, 2006; Connell et al., 2009;
Lanza et al., 2007; Magidson & Vermunt, 2002; Nylund et al., 2007).
A preliminary series of models was conducted to determine the adequate number of
classes regarding psychological distress. A single-class model (without covariates) was created,
after which a series of models with covariates and multiple classes (e.g., two classes, three
classes), each representing different patterns of psychological distress behavior and mental health
treatment use, was developed. Model fit was compared among freely estimated models. The best
model was selected based on suggested indexes, including low adjusted BIC relative to other
models, significant LMR LRT, and adequate quality of classification (Nylund et al., 2007). After
completing these separate analyses, a final combined LCA model was estimated.
To determine the results of the binary distal outcome (i.e., mental health treatment use) in
the identified classes, latent class odds ratios were calculated. Sample weights, clusters, and
stratum variables were included in the analyses to account for the complex sampling design.
Because Mplus was unable to incorporate nonnested cluster and strata variables, primary
sampling units representing more than one stratum were treated as distinct clustering units
(Connell et al., 2009). All analysis were conducted in Mplus version 7.3.

50
Results
Table 10 lists the sample characteristics of respondents, including mental health services
use and psychological distress. Most respondents were married or cohabitating (61.0%), with
close to two thirds (61.3%) of respondents reporting a high school education or less and being
employed (64.7%). Most respondents reported few to no symptoms on the K6 (85.1% or higher),
with most respondents indicating few to no symptoms of worthlessness (94.4%). Finally, most
respondents (94.7%) reported no use of mental health services during the previous year.
Consecutive LCA models were identified to decide the best model to characterize mental
health treatment use and psychological distress (Table 11), with the final class model presented
in Table 12. Based on visual assessment of classes, psychological distress behavioral patterns
were similar to those confirmed by Barragán (2015). Although fit statistics suggested a three-
class solution, a four-class solution made more substantive sense (Nylund et al., 2007)
considering that psychological distress behavioral patterns were congruent with those established
by Barragán (2015), even when modeling mental health service use. The four class were named
and ranked from lowest to highest mental health service use: no psychological distress (1.8%);
mild sadness, nervousness, and restlessness (5.4%); moderate psychological distress with low
worthlessness and hopelessness (18.1%); and high psychological distress (29.2%).
To further determine the odds of mental health services use among respondents in each of
these classes, latent odds ratios were determined (Figure 2). Respondents in the mild sadness,
nervousness, and restlessness class were 3.11 (95% CI = 1.17–5.05) times more likely to have
seen a mental health professional than to not have seen one when compared to those in the no
psychological distress class. Those in the moderate psychological distress with low
worthlessness and hopelessness class were 12.10 (95% CI = 6.45–17.75) times more likely to

51
have seen a mental health professional than to not have seen one when compared to those in the
no psychological distress class. Finally, compared to respondents in the no psychological distress
class, those in the high psychological distress class were 22.69 (95% CI = 10.10–35.27) times
more likely to have seen a mental health professional than to not have seen one.
Multinomial logistic regression analyses showed that Puerto Ricans were more likely to
use mental health services (Table 13). Compared to Mexicans, Puerto Ricans were more likely to
be in the high psychological distress class (OR = 2.36, 95% CI = 1.22–4.59) or the moderate
psychological distress with low worthlessness and hopelessness class (OR = 1.87, 95% CI =
1.21–2.89). In contrast, Puerto Ricans (OR = 0.40, 95% CI = 0.22–0.72) and Cubans and Cuban
Americans (OR = 0.50, 95% CI = 0.28–0.89) were less likely to report mild sadness, nervousness,
and restlessness compared to Mexicans. In addition, men were less likely to be in the moderate
(OR = 0.59, 95% CI = 0.44–0.78) or mild (OR = 0.61, 95% CI = 0.48–0.78) psychological
distress classes than women. Increased education was associated with a decreased likelihood of
being in the high psychological distress class (OR = 0.60, 95% CI = 0.47–0.77). Compared to
being unemployed, employed respondents were less like to be in the moderate (OR = 0.62, 95%
CI = 0.47–0.82) or high (OR = 0.38, 95% CI = 0.23–0.65) psychological distress classes. Finally,
married or cohabitating respondents were generally less likely to report any psychological
distress compared to unmarried participants.
Discussion
Results from this study expanded on those from previous studies, indicating variation in
both psychological distress behavioral profiles and mental health service use among Latino
groups. The first hypothesis of the current study was confirmed, indicating an increased
likelihood of seeking mental health services as severity of distress increased. These results

52
suggest that despite the reduced likelihood of reporting feelings of worthlessness and
hopelessness, Latino respondents still required mental health services. A possible explanation for
the present study’s finding is that the buffering effects associated with lack of worthlessness and
hopelessness is confined to limited areas of psychiatric morbidity and independent of treatment
use. For example, Barragán (2015) outlined the buffering effects of reduced feelings of
worthlessness and hopelessness as a potential explanation for lower rates of suicide and
depression among Latinos compared to Anglo Americans. It is also likely that reduced feelings
of worthlessness and hopelessness among Latinos are not sufficient to overcome other aspects of
distress (e.g., nervousness, sadness, etc.), thus requiring the attention of a mental health service
provider.
Puerto Ricans were most likely to seek mental health services compared to other Latino
groups, confirming the second hypothesis of the study. Puerto Ricans, Cubans, and Cuban
Americans were less likely than Mexicans to use mental health services when reporting mild
sadness, nervousness, and hopelessness. To date, no studies have corroborated current findings
that use of services is greater among Mexicans compared to other Latino groups reporting mild
symptoms of distress. In fact, such findings run counter to the concept of needing mental health
services during periods of heightened distress. In cases of moderate and high distress, however,
Puerto Ricans reported the greatest use of mental health services compared to Mexicans. This
finding supports Alegría, Mulvaney-Day, Woo, et al.’s (2007) findings that 1 in 5 Puerto Ricans
reported mental health service use compared to 1 in 10 Mexicans. Mexican Americans did not
report increased mental health service use, despite literature suggesting increased risk of
psychiatric morbidity compared to their foreign-born counterparts. However, it is important to
note that increased morbidity specifically refers to mental illnesses among Mexican Americans

53
compared to Mexicans. It is likely that increased distress among Mexicans and Mexican
Americans may not be associated with increased likelihood of seeking mental health services.
There are several limitations to this study. It did not account for other factors that would
have generated a more comprehensive sociocultural evaluation of mental health treatment use
among Latinos. However, the use of a distal outcome (i.e., mental health service use) as a
response variable for psychological distress behavioral profiles allowed for a unique assessment
of treatment use that included an element of cultural context, thus providing insight at a more
nuanced level than in the current literature. Secondly, psychological distress responses were
based on the previous 30 days, whereas mental health service use was evaluated for the previous
year. Therefore, it cannot be presumed that reports of distress preceded use of mental health
services. Participant responses regarding distress during the previous 30 days could indicative of
a chronic health problem or an isolated life stressor (e.g., loss of a loved one, recent
unemployment, brief illness). Despite this limitation, results are reflective of morbidity rates
among Latino groups and provide a unique perspective on the influence of cultural factors on
treatment use.
In sum, Puerto Ricans were at greatest risk of increased distress in this study, potentially
explaining their increased rates of service use compared to any other group. Despite the inherent
buffering qualities of lower rates of worthlessness and hopeless among Latinos, Puerto Ricans
and other Latino groups still require a mental health professional to overcome periods of distress.
Although the current study hinted at the influence of cultural factors on psychological distress
and service use unique to Latinos, it may not represent a global assessment of psychological
distress. Nervios, a term for psychological distress prominent among Latinos, is a syndrome
involving both mental and physical symptoms (Guarnaccia, 1997; San Miguel et al., 2006). Thus,

54
the current study’s definition of psychological distress and measures evaluated only one
dimension of distress, rather than fully capturing the cultural mechanisms inherent in distress that
may ultimately influence mental health service use. Future studies that evaluate psychological
distress among Latinos should consider the limitations of using scales that do not measure other
features of distress unique to nervios.

55
CONCLUSION
The purpose of these studies was to evaluate which Latino groups are most at risk of
increased psychological distress and identify psychological distress behavioral profiles and their
association with obtaining mental health services. Psychological distress, generally defined as a
state of emotional suffering, was studied as the main outcome due to recent shifts in
epidemiological research that have emphasized evaluation of mental illnesses based more on
severity and less on diagnosis (Kessler et al., 2002). Furthermore, exploring and identifying how
psychological distress manifests among Latinos was emphasized, given that distress is shaped by
culture. Thus this dissertation has implications for how to accurately measure distress, including
clinical evaluation of Latino groups with distress and how it influences their use of mental health
services.
Using epidemiological data from the 2012 NHIS, these studies used various multivariate
analytic methods to answer multiple questions. Study 1 employed bivariate analyses and multiple
linear regression models to examine levels of psychological distress and the variable effects of
comorbid illnesses on distress among Latino groups. Additionally, covariate effects were
assessed to determine potential risk and protective factors associated with distress in each group.
Study 2 and Study 3 used LCA to identify psychological distress behavioral profiles among
Latinos, determine how they differ among Latino groups, and assess mental health service use as
a distal outcome. Use of LCA is advantageous in terms of identifying the subjective
interpretations of distress symptoms unique to Latinos (Bratter & Eschbach, 2005; Guarnaccia,
1997; San Miguel et al., 2006), going beyond the standard psychometric testing used to assess
the validity of the K6 instrument (Drapeau et al., 2012; Green et al., 2010; Kessler et al., 2002;
Kim et al., 2011). Once the psychological distress behavioral profiles were identified, each of the

56
classes was tested as a predictor of mental health service use, providing insight into how distress
profiles can affect the likelihood of seeking care. This final chapter summarizes major findings
and their implications for practice and research.
Summary of Findings
Findings from these studies uncovered varied levels of psychological distress among
Latinos groups, with some groups reporting higher levels of distress than others when
experiencing comorbid mental and physical health illnesses. However, the nature of
psychological distress among Latinos didn’t include feelings of worthlessness (and hopelessness
to a lesser degree), which could serve as a protective factor and help explain the reduced
morbidity of some mental health problems among Latinos compared to the general population
(CDC, 2009, 2014; McLean et al., 2008; Oquendo et al., 2001). Despite inherent protective
qualities of certain cultural factors among Latinos, increased distress still required intervention
from a mental health service provider when respondents were in need of help. In general, Puerto
Ricans in all three studies had an increased risk of high psychological distress relative to other
groups and were thus most likely to use mental health services.
Major Findings
In Study 1, Puerto Ricans reported high levels of distress whereas Cubans and Cuban
Americans, Mexicans, and Mexican Americans reported low levels of distress. Physical and
mental health comorbidity was associated with distress at different levels based on subgroup.
Mexicans and Puerto Ricans reported higher levels of distress associated with comorbidity,
whereas Cubans, Cuban Americans, and Central and South Americans reported lower levels.
Further evaluation of covariate effects indicated that certain sociodemographic variables may
serve as protective or risk factors for psychological distress at varying magnitudes among Latino

57
groups. However, findings suggested an inverse effect of protective and risk factors depending
on subgroup. For example, speaking Spanish may be a protective component for Mexican
Americans, yet may represent a risk factor for Puerto Ricans.
Provided that psychological distress is a construct of hardship and anguish molded by
culture (Guarnaccia, 1997; San Miguel et al., 2006), Study 2 confirmed that reports of distress by
Latinos did not include increased feelings of worthlessness. Moderate to lower levels of distress
also were not associated with feelings of hopelessness. These findings indicate that despite the
claim of the K6 instrument’s validity across cultural groups (Drapeau et al., 2012; Green et al.,
2010; Kessler et al., 2002; Kim et al., 2011), cultural mechanisms influence the manifestation of
distress in ways that standard psychometric assessments are unable to capture. When
determining which distress profiles are more or less likely to be reported among Latino groups,
Study 2 concluded that Puerto Ricans, Cubans, and Cuban Americans were less likely than
Mexicans to report mild sadness, nervousness, and restlessness. Puerto Ricans were more likely
than Mexicans, including twice as likely in terms of high psychological distress, to report
moderate or high psychological distress.
Finally, a post hoc LCA model was used to extend Study 2 analyses in Study 3, using the
identified classes of psychological distress behavioral profiles to predict mental health service
use during the previous year. As a result, similar results were found in Study 3 and Study 2.
Participants were increasingly likely to seek mental health services as severity of distress
increased, and results confirmed the hypothesis that Puerto Ricans would be more likely than
Mexicans to use mental health services. These results suggest that the buffering qualities of not
reporting feelings of worthlessness and hopelessness were limited to specific mental health

58
problems in this sample, thus maintaining the need for intervention by a mental health
professional.
Research and Practice Implications
Research Implications
Conclusions based on these studies can be focused on the complex and counterintuitive
nature of Latino mental health. The Study 2 finding regarding the potential protective effect of
reduced reports of worthlessness as a potential explanation for lower than average rates of
suicide and depression, despite Latinos generally belonging to a lower socioeconomic category
compared to Anglo Americans, is consistent with the Latino paradox, as described by Alegria,
Mulvaney-Day, Torres, et al. (2007):
The typical finding that although low socioeconomic status is associated with suboptimal
health outcomes, the health status of Latinos in low socioeconomic categories is better
than that of [Anglo Americans] in the same categories, and the health status of Latino
immigrants is better than that of U.S.-born Latinos. (p. 73)
The paradoxical nature of Latino health also extends beyond this popular conception to Latino
subgroups. The studies in this dissertation identified a wide range of sociodemographic covariate
effects on Latino groups, wherein certain factors varied in strength and may serve as risk or
protective components of distress.
Furthermore, findings from this dissertation do not support the minority-status
perspective, which asserts that ethnic minorities are subject to distress due to prejudice and
discriminatory actions or low social class. Rather, the stressors associated with psychological
distress and the unique behavioral profiles identified in this dissertation are congruent with the
ethnic-cultural perspective, suggesting that psychological well-being varies based on cultural

59
practices and values that distinguish ethnic groups (Mirowsky & Ross, 1980). Previous literature
has already supported this assertion; nervios is a characteristic of distress unique to Latinos that
encompasses physical and mental symptomatology.
Practice Implications
An epidemiological approach to identifying problems affecting the health status and
social functioning of Latino groups is important in the development and implementation of
interventions at the clinical social work level (Standards Development Committee, 2005). The
varying behavioral profiles of psychological distress among Latino subgroups call into question
the appropriateness of large-scale social work efforts aimed at provided efficient mental health
treatments for Latinos in general. Furthermore, untangling the relationships between treatment
use and psychological distress profiles can inform social work leaders seeking to tailor service
provision at a sufficient scale to address the needs of all Latino subgroups. Findings from this
dissertation suggest that social workers and other health professionals should use community-
level approaches to tailor, assess, and allocate services to populations in greatest need while
anticipating changes in policies and legislation that could affect outreach and health services
(Aguilera & Lopez, 2008).
Recommended Future Studies
Although several explanations presented in the current dissertation addressed the
increased risk of psychological distress among Puerto Ricans, the mechanisms underlying this
phenomenon remain unclear (Canino & Alegría, 2009). Despite other studies employing a wealth
of sociocultural elements (e.g., Alegría, Takeuchi, et al., 2004; Grant et al., 2004), these studies
and this dissertation hinted at an underlying and unexplored sociocultural mechanism associated
with increased morbidity among Puerto Ricans experiencing distress. Future studies that explore

60
this mechanism will help answer this question and explain the Latino paradox at a deeper level of
understanding.
Future studies that use the K6, K10, or any other measures of psychological distress
should take special note of current findings. As previously mentioned, Study 2 indicated that
despite claims of the K6 scale’s validity across cultural groups, the measure could not accurately
assess the psychosomatic syndrome associated with nervios and thus may not be a reliable global
assessment of distress among Latinos. Therefore, future studies seeking to measure
psychological distress not specific to psychiatric disorders should either adapt current measures
to encompass culturally determined distress behaviors or create and test a measure. Otherwise,
future studies that use the K6, K10, or other instruments should also include supplemental
measures that globally assess distress among Latinos.
Finally, explanations used in this dissertation to interpret the results were somewhat
speculative due to the inherent shortcomings of cross-sectional data (Cook et al., 2009).
Identifying causal or semicausal effects using epidemiological data is needed to affirm these
explanations via hypotheses-driven inquiry. Both the National Epidemiological Survey on
Alcohol and Related Conditions and the National Latino and Asian American Study have or are
in the process of gathering follow-up data that will help answer various questions and address
limitations outlined in this dissertation and the general literature.

61
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Table 1. Correlation Matrix of Mental Health Disorder Comorbidity

Variable VIF 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1. Psychological distress
2. High school 1.19 -.039**
3. Some college 1.28 -.026 -.229**
4. College graduate 1.32 -.055** -.141** -.128**
5. Spanish 1.42 .034* -.079** -.201** -.116**
6. Other language 1.23 .019 -.013 -.103** -.045** -.221**
7. Male 1.13 -.099** .015* -.029** -.029** -.018 .015
8. 1 MH disorder 1.07 .289** -.006 -.015 -.032* -.022 .023 -.115**
9. 2 or 3 MH disorders 1.04 .398** -.024 .014 -.018 -.002 -.021 -.050** -.072**
10. 5 years in U.S. 2.53 -.017 -.030** -.046** -.017 .113** .004 -.002 -.048** -.048**
11. 10 years in U.S. 3.38 -.045** -.021* -.034** -.019 .085** .023 .010 -.035** -.023 -.199**
12. 15 years in U.S. 4.80 .051** .047** .067** .009 -.172** -.016 .001 .084** .065** -.492** -.589**
13. Married or cohabitating 1.18 -.113** .156** .085** .120** .064** .042** .014* -.071** -.073** -.075** -.016 .119**
14. Employed 1.29 -.166** -.005 .067** .119** -.060** -.032 .203** -.112** -.121** .030 .081** -.083** .072**
15. Age 1.49 .068** .177** .114** .156** .078** .016 -.032** .087** .069** -.285** -.223** .500** .583** -.250**
16. Income 1.44 -.137** -.006 .123** .221** -.235** .073** .023** -.060** -.048** -.078** -.079** .152** .113** .224** .033**
Note. MH = mental health; U.S. = United States; VIF = Variance Inflation Factor.
*p < .05. **p < .01.

80

Table 2. Correlation Matrix of Physical and Mental Health Disorder Comorbidity

VIF 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1. Psychological distress
2. High school 1.19 -.039**
3. Some college or associate’s 1.28 -.026 -.229**
4. College graduate 1.32 -.055** -.141** -.128**
5. Spanish 1.42 .034* -.079** -.201** -.116**
6. Other language 1.23 .019 -.013 -1.03** -.045** -.221**
7. Male 1.13 -.099** .015* -.029** -.029** -.018 .015
8. Physical, no mental 1.34 -.052** -.007 -.026* .001 .019 -.009 .019
9. Mental, no physical 1.07 .226** -.003 .006 -.022 -.035* -.008 -.093** -.147**
10. Physical and mental 1.24 .402** -.021 -.014 -.030* .005 .020 -.082** -.156** -.083**
11. 5 years in U.S. 2.53 -.017 -.030** -.046** -.017 113** .004 -.002 -.094** -.023 -.067**
12. 10 years in U.S. 3.38 -.045** -.021* -.034** -.019 .085** .023 .010 -.121** .014 -.068** -.199**
13. 15 years in U.S. 4.80 .051** .047** .067** .009 -.172** -.016 .001 .194** .016 .125** -.492** -.589**
14. Married or cohabitating 1.19 -.113** .156** .085** .120** .064** .042 .014* .011 -.063** .075** -.075** -.016 .119**
15. Employed 1.30 -.166** -.005 .067** .119** -.060** -.032 .203** -.137** -.037** -.182** .030 .081** -.083** .072**
16. Age 1.76 .068** .177** .114** .156** .078** .016 -.032** .410** -.065** .212** -.285** -.223** .500** .538** -.250**
17. Income 1.44 -.137** -.006 .123** .221** -.235** -.073** .023** -.018 -.035** -.070** -.078** -.079** .152** .113** .227** .033**
Note. U.S. = United States; VIF = variance inflation factor.
*p < .05. **p < .01.

81
Table 3. Sample Characteristics
Total
(n = 5,859)
Mexican
(n = 2,226)
Mexican Am.
(n = 1,358)
Central/S. Am
(n = 945)
Puerto Rican
(n = 578)
Other Latino
(n = 461)
Cub./Cub. Am.
(n = 291)
Age
a
** 40.31 (0.26) 39.47 (0.38) 38.86 (0.57) 40.37 (0.68) 42.78 (0.80) 41.46 (0.94) 48.14 (1.14)
Income
a
** 48,714 (951.41) 40,527 (1,116.41) 56,961 (1,654.86) 51,979 (2,674.45) 50,227 (2,565.73) 53,168 (2,733.49) 51,627 (3,763.95)
Male* 50.09 (0.81) 53.45 (1.24) 49.49 (1.81) 47.73 (1.96) 44.76 (2.34) 47.66 (3.09) 48.87 (3.72)
Unmarried** 39.54 (0.83) 31.36 (1.40) 45.45 (1.69) 39.32 (1.80) 50.22 (2.74) 48.28 (2.74) 41.47 (3.57)
Education**
Less than HS 34.57 (0.90) 51.62 (1.44) 20.67 (1.31) 30.27 (1.80) 25.25 (2.07) 25.93 (2.54) 13.68 (2.18)
High School 27.14 (0.35) 24.72 (1.17) 31.68 (1.62) 22.83 (1.79) 33.52 (2.53) 22.86 (2.48) 32.55 (2.68)
Some college or assoc. 26.23 (0.80) 17.70 (0.98) 36.01 (1.75) 26.70 (1.96) 27.44 (2.04) 32.87 (2.83) 31.17 (2.91)
College grad or higher 12.06 (0.55) 5.96 (0.69) 11.63 (1.09) 20.21 (1.58) 13.79 (2.09) 18.34 (2.33) 22.60 (3.06)
Unemployed** 36.65 (0.75) 32.89 (1.14) 36.10 (1.75) 31.66 (1.61) 50.91 (2.50) 43.50 (2.89) 48.82 (4.08)
Language**
Spanish 24.06 (1.05) 38.27 (1.89) 4.70 (0.91) 29.41 (2.30) 10.13 (1.76) 18.97 (2.99) 32.82 (3.49)
English 66.36 (1.14) 46.90 (1.87) 91.74 (1.14) 60.11 (2.57) 84.13 (2.16) 73.87 (3.04) 58.92 (4.84)
Other 9.57 (0.64) 14.83 (1.33) 3.56 (0.86) 10.48 (1.44) 5.74 (1.17) 7.16 (1.44) 8.26 (3.52)
Years in the U.S.**
< 5 years 6.66 (0.55) 5.14 (0.74) 1.09 (1.08) 9.14 (1.32) 6.52 (1.36) 10.41 (2.54) 13.70 (2.15)
5-9 years 13.50 (0.84) 14.84 (1.12) 7.77 (3.18) 15.55 (2.10) 4.91 (1.47) 9.28 (2.01) 13.76 (2.63)
10-14 years 18.85 (0.83) 21.73 (1.11) 11.13 (2.94) 21.76 (1.96) 8.60 (1.96) 5.87 (1.92) 13.37 (3.83)
≥ 15 years 60.99 (0.97) 58.28 (1.30) 80.01 (3.99) 53.54 (2.43) 79.97 (2.64) 74.44 (3.47) 59.18 (3.43)
Mental health disorders**
Zero 86.23 (0.58) 89.24 (0.84) 84.33 (1.14) 88.81 (1.27) 77.90 (1.88) 81.82 (1.96) 86.12 (2.74)
One 10.10 (0.52) 7.99 (0.79) 11.79 (1.08) 8.72 (1.24) 15.63 (1.77) 10.96 (1.35) 10.80 (2.56)
Two or three 3.67 (0.31) 2.77 (0.46) 3.88 (0.59) 2.46 (0.65) 6.47 (1.15) 7.23 (1.53) 3.08 (0.85)
Comorbidity**
Neither 66.74 (0.81) 71.30 (1.16) 63.95 (1.75) 71.89 (1.78) 56.28 (2.60) 58.76 (2.51) 58.79 (2.59)
Physical, no mental, 19.48 (0.61) 17.93 (0.91) 20.38 (1.53) 16.93 (1.21) 21.62 (2.01) 23.05 (2.24) 27.33 (2.85)
Mental, no physical 7.04 (0.46) 5.87 (0.74) 8.15 (0.92) 6.54 (1.11) 9.40 (1.46) 9.60 (1.76) 3.69 (1.04)
Both 6.73 (0.34) 4.90 (0.50) 7.52 (0.75) 4.65 (0.76) 12.70 (1.53) 8.58 (1.27) 10.18 (2.33)
Psychological distress
ab
** 2.24 (0.07) 2.05 (0.09) 2.09 (0.11) 2.23 (0.20) 3.29 (0.20) 2.59 (0.26) 1.90 (0.23)
Note. Figures represent % (SE) unless otherwise noted. HS = high school; U.S. = United States.
a
Figures represent M (SE)
b
Data were missing for some respondents, but did not bias the sample.
*p < .05. **p < .01: Indicate significant differences between subgroups.

82

Table 4. Standardized Regression Models of Mental Health Disorder Comorbidity as a Predictor of Psychological Distress

Total

β
Mexican

β
Mexican
American
a

β
Central/S.
American
β
Puerto Rican

β
Other Latino

β
Cuban/Cuban
American
β
Mental health disorder
Two or three 0.36** 0.38** 0.45** 0.25** 0.48** 0.26** 0.30**
One 0.31** 0.27** 0.32** 0.28** 0.34** 0.45** 0.42**
Age 0.04** 0.03** 0.03** 0.05** 0.03 -0.03 -0.10**
Female 0.04** 0.07** 0.00 0.03* 0.09** -0.04 -0.02
Unmarried 0.05** 0.07** 0.03** 0.06** 0.00 -0.21** 0.01
Education
High School -0.06** -0.04** -0.06** -0.02 -0.17** -0.17** -0.08**
Some college or associate’s -0.05** 0.01** -0.06** -0.05** -0.11** -0.27** -0.02
College graduate or higher -0.04** 0.02** -0.07** -0.05** -0.09** -0.20** -0.06**
Unemployed 0.21** -0.02** 0.01** -0.00 0.05 0.15* 0.19**
Income -0.07** -0.01** -0.09** -0.16** -0.00 -0.11 -0.01
Language
Spanish 0.02 0.06** -0.00** 0.06** 0.12* -0.11* 0.05**
Other 0.04** 0.08** -0.03** 0.00 0.08** -0.09 0.25**
Years in U.S.
< 5 0.04** 0.00** – 0.01 0.07* 0.23** 0.10**
5 – 9 0.01** -0.04** – 0.11** -0.02 -0.00 0.14**
10 – 14 -0.00 -0.05** – 0.06** 0.02 0.02 0.08**
df
b
15 (250) 9 (250) 3 (272) 15 (250) 15 (250) 14 (250) 4 (250)
F statistic 314.84** 1.631E7** 1198549** 965.93** 351.14** 1333603** 4116.58**
n 2183 1051 845 521 236 135 134
Note. Reference categories were zero mental health disorders, male gender, married or cohabitating, less than high school, employed, English, and more
than 14 years of residence in the United States.
a
Years of residence in United States not included because respondents were born in the United States.
b
Figures represent numerator (denominator).
*p < .05. **p < .01

83
Table 5. Standardized Regression Models of Physical and Mental Health Disorder Comorbidity as a Predictor of Psychological Distress

Total

β
Mexican

β
Mexican
American
a

β
Central/S.
American
β
Puerto Rican

β
Other Latino

β
Cuban/Cuban
American
β
Comorbidity
Physical and mental 0.43** 0.39** 0.42** 0.32** 0.53** 0.48** 0.47**
Physical, no mental 0.08** 0.11** 0.04** 0.08** 0.02 0.12** 0.11**
Mental, no physical 0.23** 0.24** 0.29** 0.22** 0.21** 0.29** 0.28**
Age -0.01 -0.01** -0.00** -0.01 -0.01 -0.11** -0.13**
Female 0.05** 0.06** 0.00 0.03* 0.11** -0.03 -0.02
Unmarried 0.04** 0.05** 0.03** 0.07** -0.02 -0.21** 0.03
Education
High school -0.06** -0.04** -0.05** -0.01 -0.17** -0.17** -0.07**
Some college or associate’s -0.05** -0.00** -0.04** -0.06** -0.10** -0.29** -0.01
College graduate or higher -0.04** 0.02** -0.06** -0.05** -0.07** -0.22** -0.03
Unemployed 0.02* -0.02** 0.03** -0.01 0.03 0.15* 0.18**
Income -0.07** 0.00 -0.10** -0.15** -0.02 -0.12 -0.03*
Language
Spanish 0.02* 0.05** -0.00* 0.05** 0.14* -0.09 0.06**
Other 0.03** 0.06** -0.02** 0.00 0.07* -0.09 0.24**
Years in U.S.
< 5 0.03** 0.00 – 0.01 0.09* 0.22** 0.11**
5 – 9 0.01** -0.04** – 0.10** -0.03 -0.01 0.15**
10 – 14 0.00 -0.04** – 0.05** 0.01 0.01 0.08**
df
b
16, 250 9, 250 3, 272 16, 250 16, 250 14, 250 4, 250
F statistic 740.67** 2.124E7** 494808** 427.19** 2933.87** 2.221E7** 166.24**
n 2183 1051 845 521 236 135 134
Note. Reference categories were no mental or physical health disorders, male gender, married or cohabitating, less than high school, employed, English, and more
than 14 years of residence in the United States.
a
Years of residence in United States not included because respondents were born in the United States.
b
Figures represent numerator (denominator).
*p < .05. **p < .01

84
Table 6. Sample Characteristics and Psychological Distress, NHIS, 2012
Sample Characteristics Psychological Distress
Variable % n Variable % n
Subgroup Sadness
Mexican 38.4 1,880 None 74.0 3,487
Mexican American 24.0 1,130 A Little 13.7 752
Central/South Am. 16.1 774 Some 9.0 462
Puerto Rican 10.0 491 Most 2.4 142
Other Latino 7.1 394 All 1.0 66
Cuban/Cuban Am. 4.4 252 Nervousness
Gender None 68.9 3,316
Female 49.1 2,648 A Little 16.2 814
Male 50.9 2,273 Some 10.1 522
Marital Status Most 3.5 178
Unmarried 39.0 2,285 All 1.3 81
Married/Cohab. 61.0 2,633 Restlessness
Education None 75.2 3,612
Less than H.S. 34.4 1,782 A Little 11.7 594
High school 26.9 1,286 Some 8.9 470
Some college/assoc. 26.6 1,243 Most 2.6 150
College grad or higher 12.1 590 All 1.6 85
Employment Hopelessness
Unemployed 35.3 1,857 None 84.4 4,069
Employed 64.7 3,064 A little 7.4 390
Age (mean, SE) 40.2 (0.26) 4,921 Some 5.3 282
Most 1.8 104
All 1.1 61
Helplessness
None 78.3 3,781
A little 8.8 447
Some 6.9 359
Most 3.0 170
All 2.9 146
Worthlessness
None 89.5 4,352
A little 4.9 257
Some 3.7 187
Most 1.2 62
All 0.7 48
Note. Percentages are weighted, n values are unweighted.

85
Table 7. Fit Statistic Comparisons of Latent Class Analysis Models of Psychological Distress

Model Description AIC BIC Adjusted BIC LMR LRT p Entropy
1 One-class 44339.683 44495.669 44419.406 – –
2 Two-class 36563.160 36881.632 36725.928 .0000 0.905
3 Three-class 35241.372 35722.331 35487.185 .0000 0.860
4 Four-class 34660.707 35304.152 34989.565 .7739 0.886
5 Five-class 34295.771 35101.701 34707.673 .7712 0.863
6 Six-class 34148.167 35116.583 34643.114 .7670 0.877
Note. AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; LMR LRT = Lo-Mendell-Rubin
Likelihood Ratio Test p-value for (K-1) classes.

86
Table 8. Conditional Probabilities of Psychological Distress (n = 4,912)

Class Prevalence
No
psychological
distress
70.7%
Mild sadness,
nervousness,
restlessness
13.0%
Moderate psych.
distress w/ low
worth., hopeless.
13.6%
High
psychological
distress
2.8%
Sadness
None 0.934 0.454 0.181 0.048
A little 0.050 0.504 0.227 0.082
Some 0.015 0.039 0.500 0.148
Most 0.000 0.003 0.079 0.439
All 0.001 0.000 0.013 0.283
Nervousness
None 0.899 0.248 0.197 0.035
A little 0.068 0.682 0.145 0.072
Some 0.030 0.031 0.510 0.179
Most 0.002 0.034 0.108 0.494
All 0.001 0.005 0.040 0.221
Restlessness
None 0.946 0.390 0.272 0.062
A little 0.028 0.557 0.147 0.059
Some 0.022 0.037 0.454 0.190
Most 0.001 0.010 0.087 0.437
All 0.003 0.006 0.040 0.252
Hopelessness
None 0.997 0.668 0.409 0.014
A little 0.003 0.321 0.195 0.073
Some 0.000 0.009 0.344 0.148
Most 0.000 0.000 0.030 0.488
All 0.000 0.002 0.023 0.276
Helplessness
None 0.961 0.537 0.275 0.049
A little 0.018 0.366 0.171 0.082
Some 0.012 0.050 0.373 0.081
Most 0.002 0.014 0.108 0.414
All 0.006 0.032 0.073 0.373
Worthlessness
None 0.998 0.802 0.602 0.204
A little 0.001 0.181 0.155 0.082
Some 0.000 0.013 0.219 0.157
Most 0.000 0.003 0.015 0.348
All 0.000 0.000 0.009 0.208

87
Table 9. Multinomial Logistic Regression Results of Psychological Distress (n = 4,912)

Covariates
Mild
Sadness/Nervousness/
Restlessness vs. no
psych. distress
OR (95% CI)
Moderate psych.
distress w/ low worth.
& hopeless. vs. no
psych. distress
OR (95% CI)
High psych. distress
vs. no psych. distress
OR (95% CI)
Mexican (ref.) 1.00 1.00 1.00
Mexican-Am. 0.90 (0.66–1.22) 1.16 (0.83–1.62) 1.39 (0.79–2.43)
Central/South-Am. 0.92 (0.67–1.25) 1.07 (0.73–1.55) 1.32 (0.59–2.94)
Puerto Ricans 0.40 (0.22–0.72)** 1.88 (1.21–2.93)** 2.36 (1.21–4.57)*
Other Latinos 0.55 (0.31–0.96)* 1.27 (0.79–2.05) 2.07 (0.96–4.46)
Cuban/Cuban-Am. 0.49 (0.27–0.87)* 0.71 (0.37–1.36) 0.87 (0.27–2.85)
Age 1.00 (1.00–1.01) 1.01 (1.00–1.02)* 1.01 (1.00–1.02)
Female (ref.) 1.00 1.00 1.00
Male 0.62 (0.48–0.80)** 0.57 (0.44–0.75)** 0.65 (0.40–1.04)
Unmarried (ref.) 1.00 1.00 1.00
Married/Cohabitating 0.73 (0.57–0.94)* 0.75 (0.58–0.96)* 0.53 (0.34–0.82)**
Education 1.03 (0.91–1.16) 0.87 (0.76–1.00) 0.61 (0.48–0.78)**
Unemployed (ref.) 1.00 1.00 1.00
Employed 0.95 (0.70–1.30) 0.64 (0.49–0.84)** 0.38 (0.23–0.64)**
Note. OR = odds ratio; CI = confidence interval; ref. = reference category.
*p < 0.05; **p < 0.01

88
Table 10. Sample Characteristics, Mental Health Treatment, & Psychological Distress, NHIS,
2012

Sample Characteristics Mental Health Treatment & Psychological
Distress
Variable % n Variable % n
Subgroup MH Prof.
Mexican 38.4 1,880 No 94.7 4585
Mexican American 24.0 1,130 Yes 5.3 293
Central/South Am. 16.1 774 Sadness
Puerto Rican 10.0 491 None 74.0 3,487
Other Latino 7.1 394 A Little 13.7 752
Cuban/Cuban Am. 4.4 252 Some 9.0 462
Gender Most 2.4 142
Female 49.1 2,648 All 1.0 66
Male 50.9 2,273 Nervousness
Marital Status None 68.9 3,316
Unmarried 39.0 2,285 A Little 16.2 814
Married/Cohab. 61.0 2,633 Some 10.1 522
Education Most 3.5 178
Less than H.S. 34.4 1,782 All 1.3 81
High school 26.9 1,286 Restlessness
Some college/assoc. 26.6 1,243 None 75.2 3,612
College graduate 12.1 590 A Little 11.7 594
Employment Some 8.9 470
Unemployed 35.3 1,857 Most 2.6 150
Employed 64.7 3,064 All 1.6 85
Age (mean, SE) 40.2 (0.26) 4,921 Hopelessness
None 84.4 4,069
A little 7.4 390
Some 5.3 282
Most 1.8 104
All 1.1 61
Helplessness
None 78.3 3,781
A little 8.8 447
Some 6.9 359
Most 3.0 170
All 2.9 146
Worthlessness
None 89.5 4,352
A little 4.9 257
Some 3.7 187
Most 1.2 62
All 0.7 48
Note. Percentages are weighted, n values are unweighted.

89
Table 11. Fit Statistic Comparisons of Latent Class Analysis Models of Mental Health Treatment
& Psychological Distress

Model Description AIC BIC Adjusted BIC LMR LRT p Entropy
1 One-class 46322.504 46485.030 46405.589 – –
2 Two-class 38313.064 38644.618 38482.558 .0000 0.904
3 Three-class 36926.308 37426.890 37182.211 .0000 0.858
4 Four-class 36364.453 37034.063 36706.765 .7792 0.883
Note. AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion;
LMR LRT = Lo-Mendell-Rubin Likelihood Ratio Test p-value for (K-1) classes.

90
Table 12. Conditional Probabilities of Mental Health Treatment & Psychological Distress (n =
4,920)

Class Prevalence
No
psychological
distress
70.4%
Mild sadness,
nervousness,
restlessness
13.4%
Moderate psych.
distress w/ low
worth. & hopeless
13.4%
High
psychological
distress
2.8%
MH Prof.
No 0.982 0.946 0.819 0.708
Yes 0.018 0.054 0.181 0.292
Sadness
None 0.934 0.462 0.178 0.048
A little 0.049 0.495 0.223 0.082
Some 0.016 0.039 0.506 0.147
Most 0.000 0.003 0.080 0.441
All 0.001 0.000 0.013 0.282
Nervousness
None 0.901 0.257 0.194 0.036
A little 0.066 0.664 0.145 0.069
Some 0.030 0.037 0.514 0.177
Most 0.002 0.035 0.108 0.496
All 0.001 0.007 0.039 0.221
Restlessness
None 0.948 0.394 0.269 0.061
A little 0.026 0.548 0.143 0.058
Some 0.021 0.040 0.462 0.189
Most 0.001 0.011 0.087 0.436
All 0.003 0.007 0.039 0.256
Hopelessness
None 0.997 0.679 0.401 0.013
A little 0.002 0.310 0.195 0.069
Some 0.000 0.009 0.350 0.152
Most 0.000 0.000 0.031 0.487
All 0.000 0.002 0.023 0.278
Helplessness
None 0.962 0.540 0.273 0.048
A little 0.018 0.354 0.170 0.081
Some 0.011 0.055 0.377 0.084
Most 0.002 0.015 0.109 0.414
All 0.006 0.036 0.071 0.374
Worthlessness
None 0.998 0.807 0.600 0.202
A little 0.001 0.175 0.156 0.079
Some 0.000 0.016 0.220 0.161
Most 0.000 0.003 0.015 0.350
All 0.000 0.000 0.010 0.208

91
Table 13. Multinomial Logistic Regression Results of Mental Health Treatment & Psychological
Distress (n = 4,920)

Covariates
Mild sadness,
nervousness,
restlessness vs. no
psych. distress
OR (95% CI)
Moderate psych.
distress w/ low worth.
& hopeless. vs. no
psych. distress
OR (95% CI)
High psych. distress
vs. no psych.
distress

OR (95% CI)
Mexican (ref.) 1.00 1.00 1.00
Mexican-Am. 0.94 (0.69–1.27) 1.14 (0.82–1.58) 1.41 (0.80–2.47)
Central/South-Am. 0.95 (0.70–1.29) 1.07 (0.73–1.52) 1.36 (0.62–2.99)
Puerto Ricans 0.40 (0.22–0.72)** 1.87 (1.21–2.89)** 2.36 (1.22–4.59)*
Other Latinos 0.62 (0.36–1.07) 1.19 (0.74–1.89) 2.10 (0.98–4.51)
Cuban/Cuban-Am. 0.50 (0.28–0.89)* 0.71 (0.38–1.34) 0.75 (0.21–2.65)
Age 1.00 (1.00–1.01) 1.01 (1.00–1.01) 1.01 (1.00–1.02)
Female (ref.) 1.00 1.00 1.00
Male 0.61 (0.48–0.78)** 0.59 (0.44–0.78)** 0.65 (0.40–1.05)
Unmarried (ref.) 1.00 1.00 1.00
Married/Cohabitating 0.74 (0.58–0.95)* 0.72 (0.57–0.92)** 0.52 (0.34–0.81)**
Education 1.01 (0.90–1.14) 0.89 (0.78–1.03) 0.60 (0.47–0.77)**
Unemployed (ref.) 1.00 1.00 1.00
Employed 0.95 (0.70–1.29) 0.62 (0.47–0.82)** 0.38 (0.23–0.65)**
Note. OR = odds ratio; CI = confidence interval; ref. = reference category.
*p < 0.05; **p < 0.01

92
Figure 1. Adapted Ecological Systems Theory Model

Economy, laws, U.S. culture, attitude toward Latinos
Workplace dynamics, neighborhood resources, local
politics, media, access to services
Family, co-workers, friends, neighbors,
church
INDIVIDUAL
Sociodemographics: demographics,
immigration/migration background,
mental/physical illnesses,
employment status
MICROSYSTEM
EXOSYSTEM
MACROSYSTEM
CHRONOSYSTEM
Time
MESOSYSTEM
MESOSYSTEM
Conflict between systems:
• Practices
• Values
• Beliefs
• Language
• Culture

93
Figure 2. Odds Ratios of Mental Health Service Use Predicted by Psychological Distress
Behavioral Profiles

0

10

20

30

40

Mild sadness, nervousness,
restlessness
Moderate psych. distress w/ low
worth. & hopeless.
High psychological distress
Odds Ratio
Psychological Distress Behavioral Profiles

94
APPENDIX A: SAS SYNTAX FOR MULTIPLE LINEAR REGRESSION ANALYSES
Multicollinearity Diagnostics (Tables 1 & 2)

title ‘Multicollinarity Check for FIRST Hypothesis (CORR)’;
proc corr data=dissert.dissertation2;
where HISP_SUB ne 0;
var PSYCHDIS HIGHSCHL SOMECOAS COGRADHI SPANISH OTHERLAN SEXR
ONEMHDIS TWTHREMH FIVENIUS TENFRTUS FIFTENUS MARITAL EMPLOYME
AGE_P FAMINCI2;
run;

title ‘Multicollinarity Check for FIRST Hypothesis (VIF)’;
proc reg data=dissert.dissertation2;
where HISP_SUB ne 0;
model PSYCHDIS = HIGHSCHL SOMECOAS COGRADHI SPANISH OTHERLAN SEXR
ONEMHDIS TWTHREMH FIVENIUS TENFRTUS FIFTENUS MARITAL EMPLOYME
AGE_P FAMINCI2 / vif tol collin;
run;

title ‘Multicollinarity Check for SECOND Hypothesis (CORR)’;
proc corr data=dissert.dissertation2;
where HISP_SUB ne 0;
var PSYCHDIS HIGHSCHL SOMECOAS COGRADHI SPANISH OTHERLAN SEXR
HLTHNOMH NOHLTHMH MHHLTH FIVENIUS TENFRTUS FIFTENUS MARITAL
EMPLOYME AGE_P FAMINCI2;
run;

title ‘Multicollinarity Check for SECOND Hypothesis (VIF)’;
proc reg data=dissert.dissertation2;
where HISP_SUB ne 0;
model PSYCHDIS = HIGHSCHL SOMECOAS COGRADHI SPANISH OTHERLAN SEXR
HLTHNOMH NOHLTHMH MHHLTH FIVENIUS TENFRTUS FIFTENUS MARITAL
EMPLOYME AGE_P FAMINCI2 / vif tol collin;
run;

95
Descriptive Analyses (Table 3)

title ‘Descriptives for Age, Income, and Psychological Distress’;
proc surveymeans data=dissert.dissertation2 all;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
domain HISP_SUB;
var AGE_P FAMINCI2 PSYCHDIS;
run;

title ‘Test for Age Differences Between Subgroups’;
proc surveyreg data=dissert.dissertation2;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
class HISP_SUB;
model AGE_P = HISP_SUB / anova;
run;

title ‘Test for Income Differences Between Subgroups’;
proc surveyreg data=dissert.dissertation2;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
class HISP_SUB;
model FAMINCI2 = HISP_SUB / anova;
run;

title ‘Test for P. Distress Differences Between Subgroups’;
proc surveyreg data=dissert.dissertation2;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
class HISP_SUB;
model PSYCHDIS = HISP_SUB / anova;
run;

96
title ‘Descriptives for Categorical Covariates & Predictors’;
proc surveyfreq data=dissert.dissertation2;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
tables (SEXR MARITAL EDUCATIO EMPLOYME LANGUAGE YEARSINU MHDISORD
COMOR_MH) * HISP_SUB / col chisq;
run;

97
Multiple Linear Regression Analyses (Tables 4 & 5)

title ‘Multiple Regression for FIRST Hypothesis’;
proc surveyreg data=dissert.dissertation3;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
domain HISP_SUB;
class MHDO_REC SEXR MARITAL LEVLOFED EMPLOYME LANG_REC YEARSINU
HISP_SUB;
model PSYCHDIS = MHDO_REC AGE_P SEXR MARITAL LEVLOFED EMPLOYME
FAMINCI2 LANG_REC YEARSINU / solution stb;
run;

*Since YEARSINU does not apply to Mex-Am (who are born in the US), the variable was
removed.
NOTE: use this output ONLY for Mex-Am;
title ‘Multiple Regression for FIRST Hypothesis (Sans YEARSINU)’;
proc surveyreg data=dissert.dissertation3;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
domain HISP_SUB;
class MHDO_REC SEXR MARITAL LEVLOFED EMPLOYME LANG_REC HISP_SUB;
model PSYCHDIS = MHDO_REC AGE_P SEXR MARITAL LEVLOFED EMPLOYME
FAMINCI2 LANG_REC / solution stb;
run;

title ‘Multiple Regression for SECOND Hypothesis’;
proc surveyreg data=dissert.dissertation3;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
domain HISP_SUB;
class COMO_REC SEXR MARITAL LEVLOFED EMPLOYME LANG_REC YEARSINU
HISP_SUB;
model PSYCHDIS = COMO_REC AGE_P SEXR MARITAL LEVLOFED EMPLOYME
FAMINCI2 LANG_REC YEARSINU / solution stb;
run;

98
*Since YEARSINU does not apply to Mex-Am (who are born in the US), the variable was
removed.
NOTE: use this output ONLY for Mex-Am;
title ‘Multiple Regression for SECOND Hypothesis (Sans YEARSINU)’;
proc surveyreg data=dissert.dissertation3;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
domain HISP_SUB;
class COMO_REC SEXR MARITAL LEVLOFED EMPLOYME LANG_REC HISP_SUB;
model PSYCHDIS = COMO_REC AGE_P SEXR MARITAL LEVLOFED EMPLOYME
FAMINCI2 LANG_REC / solution stb;
run;

99
APPENDIX B: MPLUS SYNTAX FOR LATENT CLASS ANALYSES

Descriptive Analyses for Sample Characteristics & Psychological Distress [SAS] (Table 6)

title ‘Sample Characteristics for Study Two (Age only)’;
proc surveymeans data=dissert.dissertation2;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
var AGE_P;
run;

title ‘Sample Characteristics for Study Two’;
proc surveyfreq data=dissert.dissertation2;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
tables SADR NERVOUSR RESTLESS HOPELESS EFFORTR WORTHLSR HISP_SUB
SEXR MARITAL EDUCATIO EMPLOYME;
run;

100
Fit Statistic Comparisons of Latent Class Analyses Models (Table 7)

TITLE: Determining Appropriate Number of Classes for Aim 2

DATA: FILE IS
aim2.csv;

VARIABLE: NAMES ARE HHX, FMX, FPX, USABORN, MHPROF1Y, MDSPEC1Y,
GENDOC1Y, HOSPIT1Y, WTFA_SA, FAMINCF2, FAMINCI2, STRAT_P,
PSU_P, SEX, AGE_P, COMOR_MH, HISP_SUB, MEXICAN, MEX_AM,
CENT_SAM, P_RICAN, OTHER_LA, CUB_CUBA, HISP_YES, SADR,
NERVOUSR, RESTLESS, HOPELESS, EFFORTR, WORTHLSR, PSYCHDIS,
MARITAL, EDUCATIO, YEARSINU, CARDIOVA, MHDISORD,
HLTHDISO, EMPLOYME, LANGUAGE, cluster1, SEXR, HLTHYORN,
MHYORN, COMYORN;

USEVARIABLES ARE SADR NERVOUSR RESTLESS HOPELESS
EFFORTR WORTHLSR;

CLASSES = c(1);

CATEGORICAL = SADR NERVOUSR RESTLESS HOPELESS EFFORTR
WORTHLSR;

STRATIFICATION = STRAT_P;

CLUSTER = cluster1;

WEIGHT = WTFA_SA;

SUBPOPULATION IS HISP_SUB NE 0;

MISSING ARE ALL(99999);

ANALYSIS: TYPE = COMPLEX MIXTURE MISSING;
!ALGORITHM=INTEGRATION;

OUTPUT: SAMP stand cint tech11;

Author’s Note. This syntax was modeled for each sequential number of CLASSES, beginning
with c(1) and ending at c(6).

101
Conditional Probabilities & Multinomial Logistic Regression Analyses (Tables 8 & 9)

TITLE: LCA Analysis for Aim 2

DATA: FILE IS
aim2.csv;

VARIABLE: NAMES ARE HHX, FMX, FPX, USABORN, MHPROF1Y, MDSPEC1Y,
GENDOC1Y, HOSPIT1Y, WTFA_SA, FAMINCF2, FAMINCI2, STRAT_P,
PSU_P, SEX, AGE_P, COMOR_MH, HISP_SUB, MEXICAN, MEX_AM,
CENT_SAM, P_RICAN, OTHER_LA, CUB_CUBA, HISP_YES, SADR,
NERVOUSR, RESTLESS, HOPELESS, EFFORTR, WORTHLSR, PSYCHDIS,
MARITAL, EDUCATIO, YEARSINU, CARDIOVA, MHDISORD,
HLTHDISO, EMPLOYME, LANGUAGE, cluster1, SEXR, HLTHYORN,
MHYORN, COMYORN;

USEVARIABLES ARE MEX_AM CENT_SAM P_RICAN OTHER_LA
CUB_CUBA AGE_P SEXR MARITAL EDUCATIO EMPLOYME
SADR NERVOUSR RESTLESS HOPELESS EFFORTR WORTHLSR;

CLASSES = c(4);

CATEGORICAL = SADR NERVOUSR RESTLESS HOPELESS EFFORTR
WORTHLSR;

STRATIFICATION = STRAT_P;

CLUSTER = cluster1;

WEIGHT = WTFA_SA;

SUBPOPULATION IS HISP_SUB NE 0;

MISSING ARE ALL(99999);

AUXILIARY = MEX_AM (R3STEP) CENT_SAM (R3STEP) P_RICAN
(R3STEP) OTHER_LA (R3STEP) CUB_CUBA (R3STEP) AGE_P (R3STEP)
SEXR (R3STEP) MARITAL (R3STEP) EDUCATIO (R3STEP) EMPLOYME
(R3STEP);

ANALYSIS: TYPE = MIXTURE COMPLEX;
!ALGORITHM=INTEGRATION;

OUTPUT: SAMP stand cint tech11;

102
APPENDIX C: MPLUS SYNTAX FOR LATENT CLASS ANALYSES WITH BINARY DISTAL OUTCOME

Descriptive Analyses for Sample Characteristics, Mental Health Treatment
& Psychological Distress [SAS] (Table 10)

title ‘Sample Characteristics for Study Three (Age only)’;
proc surveymeans data=dissert.dissertation2;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
var AGE_P;
run;

title ‘Sample Characteristics for Study Three’;
proc surveyfreq data=dissert.dissertation2;
where FAMINCF2=0;
where HISP_SUB ne 0;
strata STRAT_P;
cluster PSU_P;
weight WTFA_SA;
tables MHPROF1Y SADR NERVOUSR RESTLESS HOPELESS EFFORTR
WORTHLSR HISP_SUB SEXR MARITAL EDUCATIO EMPLOYME;
run;

103
Fit Statistic Comparisons of Latent Class Analyses Models (Table 11)

TITLE: Determining Appropriate Number of Classes for Aim 3

DATA: FILE IS
aim2.csv;

VARIABLE: NAMES ARE HHX, FMX, FPX, USABORN, MHPROF1Y, MDSPEC1Y,
GENDOC1Y, HOSPIT1Y, WTFA_SA, FAMINCF2, FAMINCI2, STRAT_P,
PSU_P, SEX, AGE_P, COMOR_MH, HISP_SUB, MEXICAN, MEX_AM,
CENT_SAM, P_RICAN, OTHER_LA, CUB_CUBA, HISP_YES, SADR,
NERVOUSR, RESTLESS, HOPELESS, EFFORTR, WORTHLSR, PSYCHDIS,
MARITAL, EDUCATIO, YEARSINU, CARDIOVA, MHDISORD,
HLTHDISO, EMPLOYME, LANGUAGE, cluster1, SEXR, HLTHYORN,
MHYORN, COMYORN;

USEVARIABLES ARE MHPROF1Y SADR NERVOUSR RESTLESS
HOPELESS EFFORTR WORTHLSR;

CLASSES = c(1);

CATEGORICAL = MHPROF1Y SADR NERVOUSR RESTLESS HOPELESS
EFFORTR WORTHLSR;

STRATIFICATION = STRAT_P;

CLUSTER = cluster1;

WEIGHT = WTFA_SA;

SUBPOPULATION IS HISP_SUB NE 0;

MISSING ARE ALL(99999);

ANALYSIS: TYPE = MIXTURE COMPLEX;
!ALGORITHM=INTEGRATION;

OUTPUT: SAMP stand cint tech11;

Author’s Note. This syntax was modeled for each sequential number of CLASSES, beginning
with c(1) and ending at c(4).

104
Conditional Probabilities & Multinomial Logistic Regression Analyses (Tables 12 & 13)

TITLE: LCA Analysis for Aim 3

DATA: FILE IS
aim2.csv;

VARIABLE: NAMES ARE HHX, FMX, FPX, USABORN, MHPROF1Y, MDSPEC1Y,
GENDOC1Y, HOSPIT1Y, WTFA_SA, FAMINCF2, FAMINCI2, STRAT_P,
PSU_P, SEX, AGE_P, COMOR_MH, HISP_SUB, MEXICAN, MEX_AM,
CENT_SAM, P_RICAN, OTHER_LA, CUB_CUBA, HISP_YES, SADR,
NERVOUSR, RESTLESS, HOPELESS, EFFORTR, WORTHLSR, PSYCHDIS,
MARITAL, EDUCATIO, YEARSINU, CARDIOVA, MHDISORD,
HLTHDISO, EMPLOYME, LANGUAGE, cluster1, SEXR, HLTHYORN,
MHYORN, COMYORN;

USEVARIABLES ARE MEX_AM CENT_SAM P_RICAN OTHER_LA
CUB_CUBA AGE_P SEXR MARITAL EDUCATIO EMPLOYME
MHPROF1Y SADR NERVOUSR RESTLESS HOPELESS EFFORTR
WORTHLSR;

CATEGORICAL = SADR NERVOUSR RESTLESS HOPELESS EFFORTR
WORTHLSR MHPROF1Y;

STRATIFICATION = STRAT_P;

CLUSTER = cluster1;

WEIGHT = WTFA_SA;

SUBPOPULATION IS HISP_SUB NE 0;

MISSING ARE ALL(99999);

AUXILIARY = MEX_AM (R3STEP) CENT_SAM (R3STEP) P_RICAN
(R3STEP) OTHER_LA (R3STEP) CUB_CUBA (R3STEP) AGE_P (R3STEP)
SEXR (R3STEP) MARITAL (R3STEP) EDUCATIO (R3STEP) EMPLOYME
(R3STEP);

ANALYSIS: TYPE = MIXTURE COMPLEX;
!ALGORITHM=INTEGRATION;

OUTPUT: SAMP stand cint tech11;

Abstract (if available)

Abstract Psychological distress, generally defined as a state of emotional suffering and characterized by symptoms of depression and anxiety, affects Latinos at higher rates and severity than the general population. Previous studies have focused on identifying the risk and protective factors associated with distress, but few studies have accounted for comorbid health illnesses, which affect Latinos at higher rates and could account for increased distress levels. Furthermore, our understanding of psychological distress among Latinos in epidemiological studies are based on a Western medical construct that may be incongruent with conceptualizations of distress among Latinos, thus calling into question the comprehensiveness of distress among Latinos. Using data from the 2012 National Health Interview Survey, the focus of this dissertation was to answer the following questions: (a) What differential effects does the number of lifetime health disorders have on the severity of psychological distress among Latinos? (b) How are protective and risk factors associated with psychological distress among Latinos? (c) Do Latinos exhibit psychological distress behavioral profiles that are ethnically unique and if so, what are they? (d) What is the association between psychological distress behavioral patterns and mental health service use during the previous year? Findings indicated an increased exacerbation of symptoms for comorbid health problems, yet some covariate effects indicated that some Latino groups are at risk of increased distress whereas the same covariates represent protective factors for other Latino groups. Furthermore, feelings of worthlessness, identified in literature as one of the major domains of psychological distress, did not characterize manifestations of distress among Latinos. Despite the inherent buffering effect of not endorsing feelings of low worth for some mental health problems, Latinos who report high levels of distress may still require outside mental health services. In the three studies conducted in this dissertation, Puerto Ricans were at greatest risk of psychiatric morbidity. Implications of these findings on research and practice are discussed, as are directions for future studies.

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Asset Metadata

Creator Barragán, Armando, Jr. (author)

Core Title Psychological distress behavioral patterns and mental health service use among Latinos in the 2012 National Health Interview Survey: a latent class analysis

School School of Social Work

Degree Doctor of Philosophy

Degree Program Social Work

Publication Date 07/28/2015

Defense Date 05/12/2015

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

Tag Latinos,Mental Health,OAI-PMH Harvest,protective,psychiatric epidemiology,psychological distress

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Gilreath, Tamika (committee chair), Yamada, Ann Marie (committee chair), Rueda, Robert (committee member)

Creator Email abarraganjr@gmail.com,barragaa@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-611502

Unique identifier UC11301669

Identifier etd-BarragnArm-3726.pdf (filename),usctheses-c3-611502 (legacy record id)

Legacy Identifier etd-BarragnArm-3726.pdf

Dmrecord 611502

Document Type Dissertation

Format application/pdf (imt)

Rights Barragán, Armando, Jr.; Barragan, Armando, Jr.

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 a...

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