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thesis entitled

PREDICTORS OF HELP-SEEKING IN A NATIONAL SAMPLE OF
ASIAN AMERICANS: THE EFFECTS OF DEMOGRAPHICS,
LANGUAGE, DISORDER, DISTRESS, AND ETHNICITY

presented by

BRITTANY K. LANNERT

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PREDICTORS OF HELP-SEEKING IN A NATIONAL SAMPLE OF ASIAN
AMERICANS: THE EFFECTS OF DEMOGRAPHICS, LANGUAGE, DISORDER,
DISTRESS, AND ETHNICITY

By

Brittany K. Lannert

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirement
for the degree of
MASTER OF ARTS
Psychology

2010

ABSTRACT
PREDICTORS OF HELP-SEEKING IN A NATIONAL SAMPLE OF ASIAN
AMERICANS: THE EFFECTS OF DEMOGRAPHICS, LANGUAGE, DISORDER,
DISTRESS, AND ETHNICITY
By
Brittany K. Lannert

Disparities in mental health, Specifically in the underutilization of services, remain a
pervasive barrier to equitable outcomes for ethnic minority populations. One population
that has consistently been found to underutilize mental health services is Asian
Americans/Pacific Islanders (AAPIS). Extant studies suggest that mental illness rates
among AAPIs are within the same range as non—Hispanic Whites; however, AAPIS are
considerably less likely to utilize services relative to their population size. The goal of
this study was to assess the predictive value of a range of variables on help-seeking
behaviors. Predictor variables assessed include ethnicity, SES, gender, age, probable
DSM-IV disorder status, distress, and experiences of discrimination. Help-seeking
behaviors assessed included: 1) use of any service, 2) use of formal services, 3) use of
informal services, and 4) use of specialty mental health services. A sample of 2095
adults was drawn fiom the National Latino and Asian American Study CNLAAS). A
series of logistic regressions were conducted. A probable DSM-IV mood or anxiety
disorder and high levels of distress were found to significantly predict all forms of service
use. Predictors of all types of service use were found to vary by ethnic subgroup, with
significant differences according to DSM-IV disorder status. Implications for future

research and practice are discussed.

TABLE OF CONTENTS

LIST OF TABLES ................................................................................... iv
LIST OF FIGURES .................................................................................... vi
INTRODUCTION .................................................................................... 1
METHODS ........................................................................................... 19
Participants .................................................................................. 19
Procedures ................................................................................... 20
Measures ..................................................................................... 21
Education/SE8 ...................................................................... 21
DSM-IV Status ..................................................................... 21
Discrimination ...................................................................... 22
Acculturative Stress ............................................................... 23
Psychological Distress ............................................................. 23
Service Use ........................................................................... 24
Statistical Analyses ......................................................................... 25
Descriptives ......................................................................... 25
Chi-Square AnalysesZS
Logistic Regressions ................................................................. 26
RESULTS ............................................................................................ 27
Full Sample
Descriptive Statistics ............................................................... 27
Chi-Square Analyses ............................................................... 30
Logistic Regressions ............................................................... 31
By Ethnic Subgroup
Descriptive Statistics ............................................................... 33
Chi-Square Analyses ............................................................... 34
Logistic Regressions ............................................................... 34
DISCUSSION ....................................................................................... 37
APPENDICES .......................................................................................... 51
REFERENCES ....................................................................................... 71

iii

LIST OF TABLES

Table 1. Descriptive Statistics for Predictor Variables, Full Sample ......................... 51
Table 2. Descriptive Statistics for Outcome Variables, Full Sample ......................... 52
Table 3. Intercorrelations of Service Use and Demographic Variables ..................... 53
Table 4. Intercorrelations of Service Use and Psychosocial Variables ....................... 54
Table 5. Intercorrelations of Demographic and Psychosocial Variables ..................... 55

Table 6. Mean Values or Frequencies for Predictor Variables as a Function of Service
Use (Any) .................................................................................. 56

Table 7. Mean Values or Frequencies for Predictor Variables as a Function of Formal
Service Use .................................................................................. 57

Table 8. Mean Values or Frequencies for Predictor Variables as a Function of Informal
Service Use .................................................................................. 58

Table 9. Mean Values or Frequencies for Predictor Variables as a Function of Specialty

Mental Health Service Use ............................................................... 59
Table 10. Summary of Logistic Regression Analyses Predicting Any Service Use, Full
Sample ....................................................................................... 60
Table 11. Summary of Logistic Regression Analyses Predicting Formal Service Use, Full
Sample ........................................................................................ 61
Table 12. Summary of Logistic Regression Analyses Predicting Informal Service Use,
Full Sample .................................................................................. 62
Table 13. Summary of Logistic Regression Analyses Predicting Specialty Mental Health
Service Use, Full Sample .................................................................. 63
Table 14. Frequency of Service Use as a Function of Ethnicity .............................. 64

Table 15. Mean Values or Frequencies for Predictor Variables as a Function of
Ethnicity .................................................................................... 65

Table 16. Summary of Logistic Regression Analyses Predicting Any Health Service Use,
by Ethnic Subgroup ........................................................................ 66

Table 17. Summary of Logistic Regression Analyses Predicting Formal Health Service
Use, by Ethnic Subgroup .................................................................. 67

iv

Table 18. Summary of Logistic Regression Analyses Predicting Informal Health Service
Use, by Ethnic Subgroup .................................................................. 68

Table 19. Summary of Logistic Regression Analyses Predicting Specialty Mental Health
Service Use, by Ethnic Subgroup ......................................................... 69

LIST OF FIGURES

Figure 1. Example of computer-assisted interview (CAI) item from the Experiences of
Discrimination scale, as viewed by NLAAS respondents ........................... 70

vi

Predictors of Help-Seeking in a National Sample of Asian Americans:
The Effects of Demographics, English Language Proficiency, Distress, and Ethnicity

Studies on mental health service utilization in the United States have consistently
shown that ethnic minority individuals are significantly underrepresented in patient
populations (U .S. Department of Health and Human Services [USDHHS], 2001;
President’s New Freedom Commission on Mental Health [PNFCMH], 2003). Etiological
surveys have demonstrated that unmet need for treatment is greatest among racial-ethnic
minorities, such that ethnic minority individuals experiencing comparable mental health
concerns relative to the general population remain less likely to utilize mental health
services than their White counterparts (Wang et al., 2005). Greater understanding of the
traits, circumstances, and life experiences of underserved populations is essential to
understanding barriers to mental health treatment, remedying inequalities in service
access, and ultimately reducing health disparities (Takeuchi & Kramer, 2002).

One population that has consistently been found to underutilize mental health services
is Asian Americans (Abe-Kim, Takeuchi, & Hwang, 2002; Sue, 1994; Yamashiro &
Matsuoka, 1997). According to the US. Department of Health and Human Services
(2001), studies examining rates of service use in the formal mental health services sector
found that Asian Americans used fewer services per capita than other groups. In
addition, less than 20 percent (17%) of those individuals who reported experiencing
problems sought services, and less than 6% sought help from a mental health
professional. In contrast, studies have indicated that nearly one-half to two-thirds of

White individuals experiencing problems, one-third of Afi'ican American individuals with

a diagnosable disorder, and one-fifth of Hispanic American individuals with a
diagnosable disorder seek any form of treatment.

According to the US Census Bureau’s recent American Community Survey series
(2007), Asian Americans are one of the fastest-growing demographics in the United
States, a diverse group comprising approximately 4.7 percent of the US. household
population as of 2004. This compares to the proportion of approximately 4.2 percent
found only four years previously (US Census Bureau, 2000). Contrary to conceptions of
this population that treat Asian Americans as a single, monolithic entity, Asian
Americans represent more than 43 different ethnic groups whose origins, histories,
practices, and cultures vary widely (Takeuchi & Kramer, 2002). These intragroup
cultural differences are particularly salient in light of the fact that the rapid growth of the
Asian American population in recent years is primarily due to immigration:
approximately 67 percent of the Asian American population is foreign-bom, and 50% of
the current population immigrated to the United States after 1990 (US Census Bureau,
2007)

In addition to the treatment of Asian American groups as a single entity, one of the
most pervasive myths surrounding Asians in America is that of the “model minority”
(Sue and Sue, 1990; Zhang, Snowden, & Sue, 1998). According to this stereotype, Asian
Americans fare better than other ethnic groups in terms of income, occupational and
educational achievement, social status, and health. This stereotype manifests itself within
the domain of clinical psychology as an insidious characterization of Asian Americans as
being particularly resilient to mental health problems, experiencing fewer mental health

problems overall, and experiencing less severe mental health problems when they arise

(Tracey, Leong, & Glidden, 1986; Leong, 1994). The reality of Asian American status
and mental-health in the United States, however, belies these assumptions.

Although the median family income of Asian American families exceeds that of the.
general population, at $59,324 to $50,046, there is considerable variation among
subgroups (US Census Bureau, 2007). Japanese Americans have the highest median
income, at $70,708, followed by Asian Indian Americans at $70,708. Hmong Americans
have the lowest median family income of all groups, at $32,384, followed by Cambodian
Americans and Laotian Americans at $35,621 and $43,542, respectively. These groups
also experience considerably higher rates of poverty than the general US. population
(12.4%), with 37.8% of Hmong American, 29.3% of Cambodian American, and 18.5% of
Laotian Americans living below the poverty line in 2004. This bivariate distribution of
wealth is also evidenced within some Asian American groups. For example, the largest
Asian American ethnic group, Chinese Americans, comprises 23.4% of the Asian
American population and shows considerable within-group diversity (Organization of
Chinese Americans, 2006). Nationally, Chinese Americans have on average greater
median household and per capita incomes than the general population, but also
experience greater rates of poverty than non-Hispanic Whites (9.4% to 8.2%,
respectively). In addition, Chinese Americans at every level of education consistently
earn lower incomes than non-Hispanic Whites, and Chinese Americans are more likely to
be in poverty at each level of educational achievement than are non-Hispanic Whites.

The wide disparity between Asian American groups of higher income and those in
poverty is mirrored in the distribution of educational achievement among Asian

Americans. Although Asian Americans as a group are more likely to achieve a

bachelor’s degee or more (48.2%) than are non-Hispanic Whites (29.7%) and the general
population (27%), they are also more likely than non-Hispanic Whites to earn less than a
high school degree (11.4% to 15.2%, respectively) (US Census Bureau, 2007). These
differences are more striking when subgroups are considered; among Vietnamese
Americans, only 23.5% achieve a bachelor’s degree or higher, and 30% earn less than a
high school degree. Cambodian, Hmong, and Laotian American individuals are even less
likely to earn a high school degree, achieving less than a high school education at rates of
53.3%, 59.6%, and 49.6%, respectively (US Census Bureau, 2000). Asian Indian
Americans earn the highest proportion of bachelor’s degrees or higher among Asian
American groups, at 63.9% in 2000. Despite high levels of educational achievement
among some Asian American groups, however, income differences persist; Asian
Americans earn less income than the general population at every level of educational
achievement except Master’s degree and higher (Organization of Chinese Americans,
2006)

Given the paucity of studies on Asian American groups, information on health status
in general and mental health status in particular is limited. In addition, methodological
issues arise when attempting to compare prevalence rates of DSM-IV disorders across
ethnic groups, namely, the equivalence of constructs and measures, the existence of
culture-bound syndromes inadequately addressed by the DSM-IV, cultural bias in
diagnostic and conceptual schemes, and the role of acculturation and racism in
prevalence estimations (Sue & Chu, 2003). The 2001 Supplement to the Surgeon
General’s Report on Mental Health provides the most complete picture to date of the

status of mental health among Asian Americans (U SDI-IHS, 2001). It notes, however,

that exact prevalence rates of mental disorders among Asian American groups have been
particularly difficult to come by, as even large national studies contain limited and greatly
diverse Asian American samples.

One study that attempted to provide clearer estimates of mental illness prevalence
among Asian Americans is the Chinese American Psychiatric Epidemiological Study
(CAPES), which examined rates of depression among Chinese Americans living in Los
Angeles County, California (Takeuchi et al., 1998). Results suggested moderate levels of
depressive disorders among Chinese American Angelinos (about 7% lifetime
prevalence), lower than the findings of the earlier National Comorbidity Survey (N CS;
Kessler et al., 1994), but similar to the findings of the Epidemiological Catchment Area
(ECA) study of the 1980s (Robins & Regier, 1991). In the case of both the NCS and the
ECA, however, as Asian American sample sizes were small, diverse, and non-
representative of any particular sub-population, no prevalence estimates could be
confidently established. In general, the accumulated evidence suggests that mental
illness prevalence rates among Asian Americans are somewhat lower than, but within the
same range as, non-Hispanic Whites (Sue & Chu, 2003). However, there is some
suggestion that rates of psychopathology among Asian Americans are grossly
underestimated (Leong, Wagner, & Tata, 1995). Whatever the true rates of mental
disorders among Asian Americans, it is clear that they do exist — and represent a need for
services that is not being adequately met.

Compared to other ethnic groups in the United States, Asian Americans are
considerably less likely to utilize services relative to their population size (Y ing & Hu,

1994; Cheung & Snowden, 1990). For example, a recent study of help-seeking patterns

among Chinese Americans found that only 6% of the sample had previously used mental
health services, compared to rates of 15-25% across the general US. population (Kung,
2003). Data from the 2005 California Health Interview Survey found that, adjusting for
health conditions and service preferences, Asian American/Pacific Islanders report
similar levels of psychological stress to non-Hispanic Whites (15.4% to 14.1%), but are
43% less likely to use mental health services (UCLA Center for Health Policy Research,
2007, cited in Cheng, McDonnell, Lee, & Moskowitz, 2008). In addition, there is some
evidence that Asian Americans in distress are more likely to delay seeking help, are less
likely to self-refer for help, and present with more severe symptoms when treatment is
sought (Akutsu, Snowden, & Organista, 1996; Durvasula & Sue, 1996). Proposed
reasons for these disparities vary widely, and more research is required in order to
determine both ultimate and proximal causes. An overview of the theoretical
underpinnings of help-seeking and established research on correlates of Asian American
help-seeking is presented below.
Help-Seeking

Help-seeking is the utilization of sources of support, advice, or assistance in response
to illness, acute stress, specific life events, trauma, psychological disorders, or
interpersonal and personal problems (Gourash, 1978). These sources of help can be
formal (such as visiting a mental health professional or medical doctor) or informal (such
as consulting a religious leader). Kleinman (1978) further differentiated sources of help-
seeking, into three domains: lay (friends or family), folk (religious, community, and

alternative healing leaders), and professional (medical/psychological institutions). Early

studies on help-seeking behavior primarily focused on whether individuals sought formal
or informal sources of help as a direct result of need for assistance.

In a study examining help-seeking behavior among indigenous Puerto Ricans, Rogler
and Cortes (1993) proposed a model that reconceptualized help-seeking behavior as a
transactional process, deeply affected by cultural context, in which individuals follow
pathways of interaction toward institutionalized professional support. The authors
describe these pathways as “the sequence of contacts with individuals and organizations
prompted by the distressed person’s efforts, and those of his or her significant others, to
seek help as well as the help that is supplied in response to such efforts” (p. 555). The
steps in this process are as follows: first, there is an onset of distress that is recognized
and interpreted by the individual, typically in consultation with close family members
and significant others, within his or her cultural framework. These cultural factors affect
symptom expression and interpretation, conceptualization of symptom importance and
severity, and beliefs about the need to seek outside help. Second, the individual makes
initial contact with the health delivery system through various social networks, through a
series of lay individuals (“a network of personal contacts” [p. 557]), to more authoritative
laypersons (such as religious leaders) until contact is made with professional sources of
help (F reidson, 1960). The final stage of the Rogler & Cortes model extends beyond the
first-contact stage to examine patient inclusion in a “reliable treatment program” (p. 559).
This paradigm extension is necessary, they explain, when considering that there are often
a number of steps between the initial reception of professional help and incorporation in a

program that provides lasting relief; for example, attrition rates after the first session have

been estimated to be anywhere from 20 to 57% of psychotherapy patients (Mitchell,
1989, cited in Rogler & Cortes, 1993).

Cultural factors are heavily influential at each stage of the help-seeking process
(Rogler & Cortes, 1993). In the initial stage, cultural beliefs about the origins and
significance of mental illness shape the recognition and assessment of distress, attitudes
toward seeking professional help, and willingness to contact sources of professional help.
In the second stage, individuals interact directly with culturally-appropriate lay sources of
help, such as social networks and religious and community leaders; the authors note that
extended lay social networks that are heavily embedded in a particular cultural
framework may represent longer pathways to professional help, such that individuals who
are entrenched in cultural minority communities may traverse a greater number of
contacts before reaching professional services and subsequently experience delays in
receiving help. Conversely, individuals may prefer to seek help exclusively from lay
sources, according to their cultural appropriateness and/or wariness of mainstream
professional services. In addition, in the case of cultural minorities, this initial
professional contact is often within the general medical health sector. Finally, cultural
factors may influence the patient’s perception of the appropriateness and efficacy of
treatment and contribute to changes in treatment modalities or withdrawal from
treatment. The issue of withdrawal is a particularly salient one for racial and ethnic
minorities: Sue and Zane (1987) have estimated that the attrition rate for ethnic minorities
following the first psychotherapy session is approximately 50%.

The vast majority of studies of help-seeking among Asian Americans have focused

primarily on either attitudes toward seeking professional help (Tata & Leong, 1994;

Nguyen & Anderson, 2005) or willingness to seek counseling (Kim & Omizo, 2003).
Given low rates of service utilization and sampling limitations, very few studies have
examined actual help-seeking behaviors among Asian Americans (Y ing & Hu, 1994;
Akutsu & Chu, 2006; Abe-Kim et al., 2007). Studies examining attitudes toward seeking
professional help generally assess client-specific and cultural variables such as the impact
of stigma, loss of face, confidence in mental health professional, recognition of a need for
help, and degree of interpersonal openness (e. g., Tata & Leong, 1994). Studies exarrrining
willingness to seek counseling generally assess individual intent, but not behavior
(Solberg et al., 1994). In addition, those studies that assess help-seeking behaviors
directly have typically been performed using non-representative, local, and/or
convenience samples (Abe-Kim, Gong, & Tacata, 2004; Gong, Gage, & Tacata, 2003;
Ying & Miller, 1992).

Although it is true that attitudes and willingness do not necessarily predict behavior,
research has suggested that the link between attitudes and behavior is very strong
(F ishbein & Ajzen, 1975). Research with Asian Americans has found a strong link
between attitudes toward seeking professional help and willingness to seek counseling
(Liao, Rounds, & Klein, 2001; Tata & Leong, 1994). However, the paucity of studies on
Asian American help-seeking behaviors makes the link between willingness to seek help
and the actual seeking of help difficult to determine. Based on Ajzen’s (2001)
enumeration of the theory of attitudes and behaviors, namely, that intentions are the best
predictors of human behavior and these intentions are predicted by people’s attitudes,
feelings of social pressure (norms), and perceptions of control, it is reasonable to

conceive of attitudes, willingness, and behavior as a chain of personal assessments and

intents culminating in the action of seeking help. Although the precise causal
relationship between willingness to seek help and the actual behavior of seeking help is
yet to be determined, findings on Asian Americans’ attitudes toward professional help
and willingness to seek help can aid us in formulating tentative research questions about
behavioral outcomes. As such, these studies are included in the overview of correlates of
Asian American help-seeking provided below.
Correlates of Help-Seeking Among Asian Americans

Although research examining help-seeking behavior among Asian Americans is
limited, there is some evidence to suggest that culture plays an important role in the help-
seeking process enumerated by Rogler and Cortes. For example, stigma of depression
has been found to be more severe in Chinese Americans than in Caucasian Americans,
which may influence willingness to seek treatment (Hsu et al., 2008). Cultural values,
such as concerns with “face,” may also play a significant role in Asian American help-
seeking attitudes and behaviors (Gong, Gage, & Tacata, 2003). Expectations regarding
social roles, particularly familial roles, may influence when and where an individual
seeks help for distress (Aroian et al., 2005). Below, we examine findings related to the
following correlates of help-seeking attitudes and behavior among Asian Americans:
gender, age, education/SE8, English language proficiency, discrimination, and
acculturative stress. We will then discuss the extant research into ethnic subgroup
variations. The three ethnic subgroups surveyed in this study are Vietnamese Americans,
Filipino Americans, and Chinese Americans.

Variable selection was guided by the purpose of this study, which is to identify

predictors of treatment utilization for Asian American individuals. The variables of

10

ethnicity, gender, education/SE8, English language proficiency, and acculturative stress
were selected on the basis of previous findings that suggest that they may play an
important role in help-seeking for Asian Americans, although their relative influences
have not yet been established. The additional variable of experiences of discrimination
was included on the basis of its theoretical importance, given Rogler and Cortes’ (1993)
model of help-seeking behavior in which the choice of a source of services may be
influenced by previous salient experiences such as discrimination, as well as previous
research demonstrating a link between experiences of discrimination and service
utilization (Spencer & Chen, 2002). The variables of distress and DSM-IV disorder
status were included to assess direct predictors of service use, as well as to make
comparisons across types of distress.
Gender

Research with general population samples has consistently shown distinct gender
differences in the seeking of professional help. Of all individuals seeking psychological
help, two-thirds are female (Good, Dell, & Mintz, 1989). As overall rates of mental
illness do not vary widely by gender, one explanation for limited male professional help-
seeking is the stigma associated with needing help, according to masculine gender roles
(Wang et al., 2005). Studies examining the effects of gender role-induced stress among
men using the Gender Role Conflict Scale, which measures masculine role stress, have
found that the restricted emotionality expectation of male roles predicts decreased help-
seeking (O’Neil et al., 1986; Good, Dell, & Mintz, 1989). This restricted emotionality
expectation has also been shown to significantly relate to negative attitudes toward help-

seeking among male college students (Blazina & Watkins, 1996).

11

Research with Asian American populations has shown more mixed results. In
general, research has shown similar differential effects of gender, albeit with considerable
differences between ethnic subgroups. Some studies have found that Asian American
women have more favorable attitudes toward seeking professional help and are more
willing to participate in professional counseling (Tata & Leong, 1994). Others have
found no gender differences in attitudes toward seeking professional help, proposing
similar socialization processes with regard to help-seeking for mental illness (Y ing &
Miller, 1992). In a study examining help-seeking patterns of Chinese Americans in
California, Kung (2003) found that women’s odds of seeking professional help were
157.8 times greater than men’s odds when they met criteria for a diagnosable mental
illness. Girn et a1. (1990) found a more modest effect when considering self-esteem as a
moderating variable; they found that Chinese American women with high self esteem
were 8 times more likely to seek help than Chinese American men with high self esteem.
A similar study examining attitudes toward seeking professional help conducted with
Vietnamese Americans, however, did not find differences by gender (Nguyen &
Anderson, 2005). Gong, Gage, and Tacata (2003), assessing service use among Filipino
Americans, found that women sought informal services at a slightly increased rate, but no
other gender differences in service use were found.

Age

In general, studies examining the effects of age on help-seeking attitudes have found a
curvilinear relationship: young adults and the elderly have demonstrated more negative
attitudes, with individuals in-between demonstrating generally more positive attitudes

(Y ing & Miller, 1992). One explanation for this effect was provided by Aroian and

12

colleagues (2005), who examined service use among Chinese American elders and found
that these individuals would not use services unless need was sufficiently high. Differing
beliefs on what level of distress, as well as familial expectations and a desire not to
burden family members, affected level of service use. A study with Vietnamese
Americans found that increasing age predicted increasingly positive attitudes toward
seeking mental health services (Luu, Leung, & Nash, 2009). Similar results have been
found with Chinese American samples (Ying & Miller, 1992, Aroian etal., 2005). A
study with Filipino Americans, however, found that age was negatively associated with
use of lay services and positively associated with use of general medical services (Gong,
Gage, & Tacata, 2003).

Education/SE5

Research has shown that persons of lower socioeconomic status, as represented by
education or income, are less likely to voluntarily seek professional help (Thoits, 2005).
One explanation for these findings is that individuals of lower socioeconomic status face
greater barriers to health services, such as limited access to health insurance (U SDHHS,
2001). Socioeconomic markers such as income, occupatiOn, and educational attainment
are established predictors of health, and lower SES has consistently been shown to be
associated with greater risk for physical and mental illness (Adler et al., 1994).

Social status may reflect factors such as access to greater social networks that may
affect help-seeking behavior. A study conducted by West (1994) examined the
relationship between social status and access to help within a classroom setting; she
found that students with high social status had much greater access to help than their low-

status peers, and the effect of social status was so influential as to outweigh other posited

13

factors. While not intended to generalize outside of the immediate experimental context,
this study provides some evidence to support the notion that social status relates directly
to access to sources of help. Research with East and Southeast Asian immigrant and
refugee women has demonstrated that perceived access to sources of help predicted
attitudes toward seeking professional help more than other variables of consideration,
although socioeconomic status was not directly factored into the model (Fung & Wong,
2007)
English Language Proficiency

Limited English language proficiency, as well as a lack of lingually-diverse services,
has long been identified as a barrier to treatment for Asian Americans (Leong, 1986;
Gong, Gage, and Tacata, 2003). Research with Asian American populations has
demonstrated that client-therapist language match predicts lower drop-out rates, greater
levels of rapport, and higher ratings of the therapists’ effectiveness and empathy by
clients (Liu, 1990; Flaskerud & Soldevilla, 1986). This relationship between English
language proficiency (ELP) and service use has been replicated with Vietnamese
Americans, Filipino Americans, and Chinese Americans (Y ing & Miller, 1992; Gong,
Gage, & Tacata, 2003; Jang, Lee, & Woo, 1998). In addition, language barriers have
been found to be related to increased levels of distress, anxiety, and depression,
suggesting an unmet need (Ding & Lee, 2009).

Experiences of Discrimination

Sue & Chu (2003) argue that minority experiences of discrimination can serve as

stressors that have powerful effects on mental health, resulting in both increased

prevalence rates of mental illness and greater wariness of mainstream services. AS

14

Spencer and Chen (2004) note, “cultural and social contexts shape the mental health of
ethnic minorities and influence the types of mental health services they use; racism and
discrimination are facets of the social context that are ever present in the lives of
racial/ethnic rrrinorities” (p. 809). They further note that past abuses of the medical
establishment may influence current distrust on the part of minorities. In addition,
culturally-inappropriate services, whether biased, unresponsive to non-English speakers,
or incongruent with cultural values, may be correctly perceived as inadequate by ethnic
minorities (Alegria et al., 2008).

Studies of the effects of discrimination on help-seeking behavior among Asian
Americans generally support these hypotheses. High levels of racial/ethnic
discrimination and unfair treatment have been found to be a risk factor for smoking in
Asian Americans (Chae et al., 2008). Similarly, high levels of discrimination have been
found to be related to chronic health conditions in Asian American populations (Gee et
al., 2007a). Controlling for other known effect variables, Gee et al. (2007b) found that
individuals who reported discrimination were at a twofold greater risk for one DSM-IV
disorder within the past 12 months, and at a threefold risk for two or more DSM-IV
disorders. These findings support the chronic stress-disorder prevalence hypothesis.

Spencer and Chen (2002), examining the connection between experiences of
discrimination and service utilization, found that individuals who reported experiencing
unfair treatment in the past because they speak a different language or have an accent
were 2.2 times more likely to use informal services and 2.4 times more likely to use lay

support systems such as friends and family than individuals who did not report the same

15

experience. They also found that more negative attitudes toward formal mental health
services were associated with greater informal sector use.
Acculturative Stress

Immigration-related factors have been identified as predictors of both mental
disorders and service use among Asian Americans (Takeuchi et al., 2007; Zane etal.,
2009; Gee, 2001). Acculturation, or the process of adaptation to the values, expectations,
and beliefs of another culture, has been proposed as the primary mechanism mediating
distress recognition and use of services (Leong & Tata, 1994; Atkinson & Gim, 1989). In
general, studies have demonstrated that higher levels of acculturation to US. society are
associated with more willingness to seek psychological help, greater stigma tolerance,
and more openness to discussing problems with a therapist (Leong & Tata, 1994; Ying &
Miller, 1992). These results have been similarly reported for Vietnamese Americans,
Filipino Americans, and Chinese Americans (Luu, Leung, & Nash, 2009; Abe-Kim,
Gong, & Takeuchi, 2004; Gong, Gage, & Tacata, 2003; Ying & Miller, 1992.). It has
been proposed that cultural interpretations of distress affect explanatory models of mental
illness as well as the perceived appropriateness of services (Y ing, 1992).

Using data from the National Latino and Asian American Study, Abe-Kim and
colleagues (2007) demonstrated that mental health service use (general medical and
specialty mental health) varied according to birthplace and generation, with later-
generation Asian Americans more likely to seek services for distress. In addition, they
found that rates of mental health service use varied according to immigration status, with
U.S.-bom Asian Americans seeking services at a significantly higher rate.

The Current Study

16

The primary goal of this study is to determine the relative predictive value of a range of
demographic and psychosocial variables on differential patterns of service use among
Asian Americans. This study improves upon previous help-seeking studies of Asian
American populations by assessing a national sample and examining specific help-
seeking behaviors rather than willingness to seek counseling or attitudes toward help-
seeking. In addition, this study improves upon previous research on Asian American
help-seeking behaviors by examining the relationship between different forms of distress
and service use, specifically through the disaggregating of DSM-IV disorder categories.
Finally, this study expands upon previous research with Asian American groups by
disaggregating ethnicity and examining the relationship between predictor variables and
service use at the level of ethnic subgroups.

Predictor variables include the demographic variables of gender, age, and
education/SE8, and the psychosocial variables of English language proficiency (ELP),
past experiences of discrimination, acculturative stress, probable DSM-IV disorder status,
and distress. Service use outcomes assessed include: 1) use of any services, 2) use of
formal services, 3) use of informal services, and 4) use of specialty mental health
services. The secondary goal of this study is to examine ethnic subgroup differences in
predictor variables, patterns of service use, and the relationship between predictor
variables and service use. To these ends, we have formulated the following research
questions and hypotheses:

1. How do the demographic and psychosocial variables of age, gender,
education/SE8, discrimination, acculturative stress, DSM-IV disorder status, and

psychological distress predict use of services by Asian Americans?

17

2. Which of these variables predict formal service use, as opposed to informal
service use?

3. We predict that specialty mental health service use will be predicted by
variables related to acculturation and psychological distress, such as English
Language proficiency and DSM-IV disorder status.

4. We predict that rates of service use (any), formal service use, informal service
use, and specialty mental health service use will vary across ethnic groups.

5. We predict that the predictor variables of age, gender, education/SE8,
discrimination, acculturative stress, DSM-IV disorder status, and psychological
distress will vary across ethnic groups.

6. Finally, we predict that the nature of the relationships between these predictor
variables and service use (any), formal service use, informal service use, and
specialty mental health service use will vary across ethnic groups.

This study is exploratory in nature, as it is one of the first to assess behavioral help-
seeking outcomes among a nationally-representative sample of Asian Americans, and is
the first study to assess the interaction between ethnicity and types of distress in
predicting types of service use.

As such, data analyses will reflect this exploratory nature rather than attempt to constrain
variables to an established path or factor model. It is hoped that results will provide some
insight into the relative predictive value of previously-identified help-seeking covariates,

as well as illuminate future paths for research.

18

Methods

Participants

Participants are drawn fiom the Asian American subset of the National Latino and
Asian American Survey (NLAAS), the first national epidemiological household survey of
Asian Americans in the US. (Alegria et al., 2004). The NLAAS, conducted from 2002-
2003, was part of the Collaborative Psychiatric Epidemiology Studies, which also
included the National Comorbidity Survey Replication (NCS-R) and the National Survey
of American Life (N SAL). The primary goals of the CPES surveys were to collect data
about prevalence of, impairment due to, and treatment patterns for mental disorders from
representative samples of both majority and minority U.S. adult populations. Secondary
goals included obtaining information about the association between environmental
context, social position, and psychosocial factors with disorder prevalence and service
utilization. The final NLAAS sample included a total of 4649 adults: 2095 identified as
Asian American, and 2554 identified as Latino American. Our sample includes all of the
Asian American adults surveyed by the NLAAS: 520 Vietnamese Americans, 508
Filipino Americans, 600 Chinese Americans, and 467 identified as belonging to any other
Asian American ethnicity.
Procedures

The NLAAS was a stratified area probability sample of Latino and Asian American
adults, residing in any of the 50 states or the District of Columbia (Heeringa et al., 2004).
Three Asian American groups were targeted for data-gathering: Chinese Americans,
Filipino Americans, and Vietnamese Americans; individuals of “other” Asian ancestries

were included as a category, as well. The NLAAS survey was administered to non-

l9

institutionalized adults aged 18 years or older. To overcome language barriers that may
discourage participation, the measures were translated into four Asian languages —
Mandarin Chinese, Cantonese, Tagalog, and Vietnamese (Alegria et al., 2004). For the
purposes of the NLAAS, researchers defined “Asian American” as referring to any
individual of an Asian ancestry currently residing in the United States, whether as a
citizen of birth, naturalized citizen, permanent resident, or temporary resident (Heeringa,
2004). Information was collected regarding citizenship, residency, and migration status,
as well as ethnic identification. As the survey methods relied on contacting eligible
household members within sample strata prior to administering the survey, all individuals
are self-identified with regard to ethnicity.

Each survey within the CPES fi'amework followed a four-step method of sampling.
The NLAAS sampling methods were constructed to provide a nationally representative
sample of Asian Americans irrespective of geographic residency patterns. In the first
step (the primary stage), sampling of US. Metropolitan Statistical Areas (MSAS) and
counties was conducted. Second-stage sampling of area segments was followed by third-
stage sampling of housing units within selected area segments. In the final sampling
stage, interviewers randomly selected eligible members of already-surveyed households
to participate.

Interviews were primarily conducted using laptop computer-assisted personal
interview methods within households (Alegria et al., 2004). A subset of interviews was
conducted by phone. A print version of the survey was provided in the event of technical
problems. CPES questionnaires were administered using computer-assisted interview

(CAI) soflware, the Blaise Survey Processing System, Version 4.5, which allowed for

20

complicated skip pattern algorithms. The first questions asked requested the respondent
to provide language preferences for the interview; the interview was then conducted in
the respondent’s language of choice. An example of an English test item as viewed by
NLAAS respondents through the CA1 system is presented in Figure 2. The sampling
process is described in greater detail by Heeringa and colleagues elsewhere (2004).
Measures

The CPES questionnaires consisted of core measures common to all three surveys as
well as measures specific to the population concerns of target groups (Alegria et al.,
2004). The core questionnaire was based largely on the World Health Organization’s
(WHO) Composite International Diagnostic Interview (CIDI), initially developed for the
World Mental Health Survey Initiative and labeled the WMH-CIDI.
Predictor Variables

Socioeconomic Status

The two most frequently used proxy measures of socioeconomic status in health
literature are education and income; of these, education has frequently proven to be the
stronger predictor of health outcomes (Grzywacz et al., 2004; Webster et al., 2008; Yip,
2003). For this reason, we have chosen to use education level as a proxy measure for
socioeconomic status. Education levels are split into four levels in the original survey:
less than 12 years (coded “1”), 12-13 years (coded “2”), 13—15 years (coded “3”), and
greater than 15 years (coded “4”). In the United States, these levels correspond to: less
than a high school education, a high school education, some college and/or an

Associate’s degree, and a four-year or Bachelor’s degree.

DSM-IV Disorder Status

21

DSM-IV disorder status within the past 12 months was determined from the WHO-
CIDI assessment of symptoms, and includes any of the following: generalized anxiety
disorder, panic disorder with or without agoraphobia, post-traumatic stress disorder,
social phobia, dysthymia, major depressive disorder, substance use (alcohol, drug),
substance dependence (alcohol, drug), bulimia nervosa, anorexia nervosa, binge eating
disorder, intermittent explosive disorder, or agoraphobia without panic disorder.
Participants were asked a series of screening questions and assessed for the full range of
symptoms when initial criteria were met. For example, respondents who answered “yes”
to the following question were subsequently administered the depression section of the
WHO-CIDI: “Have you ever in your life had a period of time lasting several days or
longer when most of the day you felt sad, empty, or depressed?”

Respondents who met DSM-IV criteria for generalized anxiety disorder, panic
disorder with or without agoraphobia, post-traumatic stress disorder, social phobia,
dysthymia, major depressive disorder, bipolar disorder, or agoraphobia without panic
disorder were coded as positive for a probable mood/anxiety diagnosis. Respondents
who met criteria for alcohol abuse, alcohol dependence, substance abuse, or substance
dependence were coded as positive for a probable substance use disorder diagnosis.
Respondents who met criteria for intermittent explosive disorder were coded positive for
a probable IED diagnosis. Finally, respondents who met criteria for anorexia nervosa,
bulimia nervosa, or binge eating disorder were coded as positive for a probable eating

disorder diagnosis.

Experiences of Discrimination

22

The NLAAS included a measure of past experiences of discrimination consisting of 9
described situations originally designed for the Detroit Area Study by Williams et al.
(1997). Respondents indicated how often they experienced the following situations:
being treated with less courtesy than others; being treated with less respect; receiving
poorer service at a restaurant; people acting as if you aren’t smart, as if they are afraid of
you, as if you are dishonest, or as if you are not as good as they are; being threatened or
harassed; being called names and insulted. Responses were coded for frequency of
experience on a 1-6 Likert scale with the following values: never, less than once a year, a
few times a year, a few times a month, at least once a week, almost every day. This
measure has been used in the NLAAS literature numerous times and is considered a good
measure of perceived discrimination (Perez, Fortuna, & Alegria, 2008; Gee et al., 2007a).

Acculturative Stress

The acculturative stress scale of the NLAAS consists of eight items selected from the
Mexican American Prevalence and Services Survey (MAPSS), which were initially
adapted from the Occupational/Emotional Stress subscale of the Hispanic Stress
Inventory (Alegria, 2004b). It is intended to measure the level of stress due to processes
of acculturation after immigration to the United States. An example item on this scale
asks, “Do people treat you badly because they think you do not speak English well or
speak with an accent?” Participants responded either “yes” (coded “1”) or “no” (coded
“0”). Responses were summed to produce an acculturative stress score ranging from 0 to
9, with higher values indicating higher reported frequencies of acculturation-related
sources of stress. This measure was administered to a subset of the Asian American

sample (n = 1636) who reported being born in a country other than the United States.

23

Distress
Psychological distress was measured using eight items derived from the K-10 (Kessler
et al., 2002). This scale asks respondents to rate the frequency with which they
experienced signs of psychological distress such as restlessness, hopelessness,
nervousness, and tiredness within the previous thirty days. Reponses ranged fiom 0
(none of the time) to 4 (all of the time). Raw variables were reverse-coded so that a
higher score on the 0-32 scale indicates higher levels of psychological distress. Two
items, “During the last thirty days, how often did you feel so depressed that nothing could
cheer you up?” and “During the last thirty days, how often did you feel so restless that
you couldn’t sit still?” were answered by less than half of all respondents and so were
dropped from the scale.
Outcome Variables
Formal Service Use
Formal service use was defined as at least one visit to a professional source of help
within the past 12 months (concurrent with DSM-IV status parameters) for
“mood/nerve/substance problems.” If respondents indicated a number greater than zero in
response to any of the following questions, they were coded as having sought formal
services: “How many visits did you make to a psychiatrist/medical
doctor/psychologist/social worker/counselor in the past 12 months?”
Informal Service Use
Informal service use was defined as at least one visit to a non-professional (folk)
source of help for “mood/nerve/substance problems” within the past 12 months. If

respondents indicated a number greater than zero in response to any of the following

24

questions, they were coded as having sought informal services: “How many visits did you
make to a spiritual advisor/healer have you made in the last 12 months?” Participants
were given a list of types of healers to choose from: acupuncturist, biofeedback specialist,
chiropractor, energy healing specialist, exercise or movement therapist, herbalist,
homeopath, guided imagery specialist, hypnotist, guided imagery specialist, masseuse,
Spiritualist/psychic, yoga/relaxation/meditation expert, dietician, or doctor of oriental
medicine. A positive response to any of these indicates use of informal services.

Specialty Mental Health Service Use

Specialty mental health service use was defined as at least one visit to a mental health

professional (psychiatrist, psychologist, social worker, or counselor) for
“mood/nerves/substance problems” within the past 12 months. Participants who reported
at least one visit to a mental health professional in the previous year were coded as
having sought specialty mental health services.
Statistical Analyses

Descriptives. The 12-month prevalence of service use was computed for any
service, formal services, informal services, and specialty mental health services. 12-
month prevalence rates for mood/anxiety disorders, substance use disorders, intermittent
explosive disorder, and eating disorders were also computed. Predictor and outcome
variables were then stratified by ethnicity to examine differences across groups.

Correlations. To assess the relationship between variables, correlations between
predictor and outcome variables were computed for the full sample. As the variables of
age, distress, discrimination, and acculturative stress were found to violate assumptions

of normality, statistical transforms were applied in the following manner: cube-root

25

transforms were applied to correct skew in the distribution of the age and distress

variables, and skew was corrected for in distribution of the discrimination and

. . . 2/3 .
acculturative stress variables usrng an x transform. The method of transforrnatron

chosen was based upon the degree of skew. Correlations were computed between
corrected variables in the following manner: Pearson’s r was used to assess the strength
of relationships between quantitative (ratio or interval scale) data and ordinal or
quantitative data; point-biserial correlation coefficients were computed to assess the
strength of relationships between quantitative and nominal data; Phi (ch) values were
computed to assess relationships between dichotomous data; and Spearman’s Rho (p)
values were computed to compare relationships between sets of ordinal data.

Chi-Square Analyses. To assess the significance of relationships between
predictor variables at different levels of service use (use vs. non-use), a series of
likelihood ratio chi-square analyses were conducted. Significant results, as indicated by
p-values of less than .05, suggest a significant relationship between row and column
values.

To assess whether significant differences existed in rates of service use across
ethnic groups, a series of likelihood ratio chi-square analyses were conducted. Identical
analyses were conducted to assess the presence of significant variations in means or
frequencies of predictor variables. As above, p-values of less than .05 are taken as
indicative of significant differences.

Logistic Regression Analyses. To assess the relative effects of predictor variables
on service use, a series of binary logistic regression analyses were conducted with the full

sample. Separate analyses were conducted to assess the effects of predictor variables on

26

any form of service use, formal service use, informal service use, and specialty mental
health service use. Because logistic regression does not require the assumption of
normally-distributed data, non-corrected variables were used in this analysis; results are
thus interpretable within the same scales given for predictor variables in the descriptive
analysis. Variables were entered into the model directly so as to control for the effects of
each other predictor, with demographic variables (age, gender, education) entered first
and followed by the psychosocial variables of distress, DSM-IV status, English language

proficiency, experiences of discrimination, and acculturative stress. Odds ratios were

. +bX . . . .
computed usrng the e21 conversron. Sigruficance of effects was assessed usrng the

Wald Chi-Square statistic. Identical analyses were then conducted using each of the three
identified ethnic subgroups (Vietnamese, Filipino, and Chinese) as referent samples to
assess the predictive value of these variables on service use within each ethnic group.
Results
Full Sample
Descriptive Statistics
Descriptive statistics of the predictor variables for the fill] Asian American sample (n
= 2095) are presented in Table 1, and descriptive statistics of the outcome variables are
presented in Table 2. The age range of participants was 18-95, as only adults were
sampled (M = 41.2, SD = 14.77). Approximately twelve percent of the sample (11.7%)
met criteria for a DSM-IV mood or anxiety disorder within the past year, while 1.3% met
criteria for a substance use disorder, 2.4% met criteria for Intermittent Explosive
Disorder, and 1.6% met criteria for an eating disorder. Reported levels of past

experiences of discrirrrination, acculturative stress, and distress were generally low; as

27

previously reported, however, these variables were found to be significantly positively
skewed, indicating that the majority of participants reported very low rates of these
concerns while a smaller number of participants indicated high levels of discrimination,
acculturative stress, and distress. Reliabilities of the scales were computed using
Cronbach’s alpha. Reliabilities were acceptable for the experiences of discrimination (r
= .91) and psychological distress (r = .88) scales. However, the reliability of the
acculturative stress scale within the Asian American sample was found to be poor (r =
.43),'and so this variable was excluded from further analysis.

Reported rates of past-year service use by participants were low. Of the total sample,
131 participants (6.3%) reported using any form of service for mood, nervous, or
substance problems; of these, 113 (86.3%) reported using formal services and 47 (35.9%)
reported using informal services. Of those who used informal services, the majority
(61.7%) used informal services exclusively. Of those who used formal services, the
majority (69.9%) sought Specialty mental health services, while the remainder (30.1%)
sought general medical services exclusively.

Intracorrelations between variables are presented in Table 3, Table 4, and Table 5.
Following Cohen’s (198 8) guidelines of correlation coefficient interpretations,
correlations smaller than r = .10 are considered trivial and will not be discussed herein.

A small correlation was found between formal and informal service use (r = .22, p < .01),
and between specialty mental health and informal service use (r = .24, p < .01), reflecting
the extent to which participants sought both informal and formal sources of help.

Significant but trivial correlations were found between demographic variables and

service use. Of psychosocial variables, markers of distress were significantly associated

28

with different types of service use. Small correlations were found between psychological
distress and use of formal services (r = .22, p < .01), use of informal services (r = .14, p <
.01), and use of specialty mental health services (r = .17, p < .01). Probable DSM-IV
disorder status was differentially associated with service use: the presence of a
mood/anxiety disorder was moderately associated with the use of any service (r = .32, p <
.01) and formal services (r = .31, p < .01), with smaller correlations with informal (r =
.21, p < .01) and specialty mental health (r = .29, p < .01) services. Substance use
disorders had small correlations with all forms of service use. Correlations between IED
and service use were mostly trivial, with a small correlation between IED and informal
service use (r = .10, p < .01). Eating disorders were significantly, but trivially, associated
with informal service use.

Significant correlations among predictor variables suggest complex underlying
relationships. Increasing age was associated with lower levels of education (r = -.21, p <
.01), lower levels of English proficiency (r = —.35, p < .01), lower rates of reported
discrimination (r = -.23, p < .01), lower rates of substance disorders (r = -.10, p < .01),
and lower rates of IED (r = -. 10, p < .01). Higher levels of education were associated
with increased English proficiency (r = .42, p < .01) and increased amounts of reported
discrimination (r = .18, p < .01). Higher rates of reported discrimination were
significantly associated with higher rates of psychological distress (r = .25, p < .01),
mood/anxiety disorders (r = .16, p < .01), IED (r = .10, p < .01), and eating disorders (r =
.11, p < .01). The strongest correlations between psychological distress and DSM-IV
disorder status were found for mood/anxiety disorders (r = .33, p < .01), with small

. correlations found with IED (r = .10, p < .01) and eating disorders (r = .12, p < .01).

29

Chi-square analyses were conducted to assess for significant differences in means or

frequencies of predictor variables as a function of service use. For any service use,

women used services in significantly greater proportion than men (x2 = 4.25, p < .05).

Those who used servrces reported srgmficantly greater rates of past discrrrnrnatron (x =
. . . . 2

58.44, p < .05), psychological distress (x2 = 251.91, p < .01), mood/anxrety disorders (x

= 210.60, p < .01), substance use disorders (x2 = 32.45, p < .01), and IED (x2 = 8.30, p <

.01). Those who used services reportedly significantly greater English language

proficiency than those who did not use services (x2 = 10.69, p < .05).

When comparing rates of predictor variables across formal and informal services, we

find that women were significantly more likely than men to use informal services (x2 =
6.14, p < .05), but not formal services (x2 = 3.64, n.s.) Individuals with greater English

language proficiency were significantly more likely to use formal services (x2 = 10.12, p

< .05), but no significant differences were found in English language proficiency for
informal service use. Significant differences in rates of DSM-IV mood/anxiety,
substance use, and intermittent explosive disorders were found for formal service use, but
no significant difference was found in rates of eating disorders. Conversely, significant
differences were found between rates of all DSM-IV disorder statuses in informal service
use. Significant differences in rates of discrimination and distress were found for both
formal and informal services, such that individuals who sought formal and informal

sources of help reported significantly greater rates of discrimination and distress.

30

Significant differences were also found in predictor variables between users and non-

users of specialty mental health services. Women sought specialty mental health services

in greater proportions than men (x2 = 4.89, p < .05). Those who used specialty mental
health services reported significantly greater rates of mood/anxiety (x2 = 181.63, p <
.01), substance use (x2 = 24.39, p < .01), and intemrittent explosive disorders (x2 = 9.56,
p < .01), as well as significantly higher rates of distress (x2 = 240.57, p < .01) and

discrimination (x2 = 57.71, p < .05), than those who did not use specialty mental health

services.
Logistic Regression Analyses

A series of logistic regression analyses were conducted to examine the independent
effects of predictor variables, controlling for other variables in the model. Standardized
betas ([3), standard errors (SE), and odds ratios are reported for any service use, formal
service use, informal service use, and specialty mental health service use.

Table 10 presents the results of logistic regression analyses for any form of service
use. The presence of a probable DSM-IV mood/anxiety diagnosis was the strongest
predictor of service use, with individuals reporting a probable diagnosis more than five
times more likely to seek services than those without a probable diagnosis (OR = 5.27, p
< .01). Distress was also a positive predictor of service use (OR = 1.15, p < .01).
Finally, English language proficiency was found to be an independent positive predictor
of service use (OR = 1.28, p < .05).

Table 11 presents the results of logistic regression analyses for formal service use.

Once again, DSM-IV mood/anxiety disorder status was the strongest predictor of formal

31

service use (OR = 6.02, p < .01), and distress positively predicted formal service use (OR
= 1.15, p < .01). English language proficiency also positively predicted formal service
use (OR = 1.29, p < .05). Age found to be a positive predictor of formal service use,
albeit with small effect: for each year increase in age, the odds of using formal services
increased by approximately two percent.

Table 12 present the results of logistic regression analyses for informal service use.
As with formal service use, the strongest predictor of use of informal services was
mood/anxiety disorder status (OR = 4.11, p < .01), and distress predicted use of services
(OR = 1.12, p < .01). Unlike formal service use, however, age negatively predicted
informal service use (OR = 0.97, p < .05), such that each increasing year in age was
associated with a three percent decrease in the odds of using informal services.
Education was a positive predictor of informal services, such that increased education
predicted increased odds of using informal services (OR = 1.53, p < .05).

Finally, Table 13 presents the results of logistic regression analyses for specialty
mental health service use. Mood/anxiety disorders independently predicted specialty
mental health service use (OR = 7.88, p < .01), such that individuals with a probable
mood/anxiety disorder were nearly eight times more likely to use specialty mental health
services than those without a mood/anxiety disorder. English language proficiency was
found to most strongly predict specialty mental health service use as opposed to other
services (OR = 1.47, p < .01).

Results by Ethnicity
In order to assess any differential effects of predictors on service use as a function of

ethnicity, data was stratified into three major groups: Vietnamese American (n = 520),

32

Filipino American (11 = 508), and Chinese American (11 = 600). Chi-square analyses were
run to assess differences for each group in means or fi‘equencies of predictor variables as
a function of type of service use. Identical logistic regression analyses were run for each
group to assess the predictive value of variables on service use as a function of ethnicity.
Frequencies of service use for Vietnamese individuals with probable substance use or
eating disorder diagnosis were too low to conduct analyses; as such, these values are
omitted below.
Descriptive Statistics

Rates of service use for each subgroup are presented in Table 14. To assess for
significant differences in rates of use across group, a series of chi-square analyses were
conducted. Rates of any service, formal service, informal service, and specialty mental
health service use did not differ significantly across groups.

Means and frequencies of predictor variables for each subgroup, as well as chi-square
analyses assessing significant differences across groups, are presented in Table 15.

Significant differences were found between groups in the sample age; the Vietnamese

group was found to be significantly older than the Filipino and Chinese group (x2 =

276.61, p < .01). Significant differences were also found in the distributiOn of

educational achievement across ethnic groups (x2 = 214.44, p < .01): the Vietnamese

sample had a significantly higher percentage of individuals with less than a high school
degree than the Filipino or Chinese sample (29.2%, compared to 10.4% and 14.2%,
respectively), while the Chinese sample reported the highest percentage of individuals

with a college degree or more (50.3%). Significant differences were also found in

English language proficiency (x2 = 485.55, p < .01), with the Filipino sample reporting

33

the highest rates of proficiency (3.3), the Chinese sample the second-highest (2.6), and

the Vietnamese sample the lowest (2.1). Rates of reported discrimination were

significantly different across groups, as well (x2 = 365.76, p < .01), with Filipino
individuals reporting the highest rates of past experiences of discrimination.

Rates of psychological distress varied significantly across ethnic groups (x2 = 211.65,

p < .01). Chinese individuals reported significantly higher rates of psychological distress
(3.2) than Vietnamese (2.4) or Filipino (2.6) individuals. DSM-IV disorder status did not
vary across groups with respect to mood/anxiety disorders, substance use disorders, or
intermittent explosive disorder. However, significantly higher rates of eating disorders
were observed in the Filipino sample (2.9%) than in the Vietnamese (0.8%) or Chinese
(0.8%) samples.
Logistic Regressions

Results from logistic regressions predicting any service use for each ethnic group are
presented in Table 16. At the level of ethnic subgroups, demographic variables were not
significant predictors of general service use. The presence of a mood/anxiety disorder
significantly predicted service use for all three groups: Vietnamese individuals with a
mood/anxiety disorder were seven times more likely (OR = 7.23, p < .01), Filipino
individuals were about five times more likely (OR = 4.65, p < .01), and Chinese
individuals were more than nine times more likely to use services (OR = 9.12, p < .01).
Distress predicted service use at similar rates across the three groups. The presence of a
substance use disorder, however, only predicted service use for the Chinese subgroup,

increasing the odds of using services more than 14 times.

34

Results fiom logistic regression analyses predicting formal service use for each ethnic
group are presented in Table 17. Of the demographic variables, gender was found to be a
significant predictor of formal service use for the Filipino sample only (OR = 2.61, p <
.05). Filipino women were 2.6 times more likely than Filipino men to use formal
services. As with any service use, mood/anxiety disorder status was found to predict
service use for all three groups at different rates. Chinese with a mood/anxiety disorder
were nearly 14 times more likely to use formal services than those without the same
diagnosis (OR = 13.65, p < .01); Vietnamese were nearly six times more likely (OR =
5.94, p < .01); and Filipino were 4.5 times more likely (OR = 4.53, p < .01). Substance
use disorders predicted service use for the Filipino (OR = 5.88, p < .05) and Chinese (OR
= 13.12, p < .05) samples. Distress significantly predicted formal service use, with the
strongest relationship found in the Filipino sample (OR = 2.61, p < .05).

Results from logistic regression analyses predicting informal service use for each
group are presented in Table 18. Significant predictors were DSM-IV status and distress,
which varied by group. The presence of a mood/anxiety disorder predicted increased
odds of using informal services for the Filipino sample only (OR = 15.01, p < .01). IED
predicted the use of informal services for the Vietnamese sample at a high rate:
individuals with probable IED were more than thirty times more likely to use informal
services. IED did not predict informal service use for the Filipino or Chinese samples.
Conversely, the presence of an eating disorder predicted increased use of informal
services for the Chinese sample (OR = 14.62, p < .05), such that Chinese individuals with
a probable eating disorder diagnosis were nearly fifteen times more likely to seek

informal services. Distress, controlling for the other variables in the model, was a

35

significant predictor of informal service use for the Chinese sample only (OR = 1.11, p <
.05).

Table 19 presents results from logistic regression analyses predicting use of specialty
mental health services by ethnicity. Significant effects were not found for demographic
variables, but effects of psychosocial variables varied widely across groups. English
language proficiency was found to be a significant predictor of specialty mental health
service use for the Chinese sample (OR = 1.92, p < .05), but not for the Vietnamese or
Filipino samples. Past experiences of discrimination were found to decrease use of
specialty mental health services for the Vietnamese sample: for each single unit increase
in reported rates of past discrimination, rates of specialty mental health service use
decreased by 13 percent (OR = 0.87, p < .05). This effect was not found to be significant
in the Filipino or Chinese samples. Mood/anxiety disorders predicted the use of specialty
mental health services for each group; Vietnamese adults with a mood/anxiety disorder
were 4.4 times more likely to use services (p < .05), Filipino adults with a mood/anxiety
disorder were nearly 9 times more likely (OR = 8.74, p < .01), and Chinese adults with a
mood/anxiety disorder were 18.5 times more likely (OR = 18.54, p < .01). IED predicted
the use of specialty mental health services for the Vietnamese sample only (OR = 13.66,
p < .01), such that Vietnamese adults with probable IED diagnosis were nearly fourteen
times more likely to seek help through specialty mental health services than those not
meeting DSM-IV IED criteria. Psychological distress was a significant predictor for the
Vietnamese (OR = 1.12, p < .05) and Filipino samples (OR = 1.28, p <.01), but not for

the Chinese sample (OR = 1.10, n.s.).

36

Discussion
Results: Full Sample

Consistent with previous studies, we found that the rate of service use by Asian
Americans in the sample was low relative to reported levels of distress and lower than
rates found in the general population (Abe-Kim, Takeuchi, & Hwang, 2002; Sue, 1994;
Yamashiro & Matsuoka, 1997). Although approximately 14% of the sample met criteria
for one or more DSM-IV diagnoses, of these only 23% reported seeking any form of
service within the past year. Relationships between service use variables suggest that
formal services were sought at a higher rate than informal services. Small correlations
between formal and informal services suggest that some individuals sought both sources
of help for emotional problems; however, many individuals sought help exclusively via
formal or informal service providers. Of those who reported using any form of services
for mood, nervous, or substance problems, 24% sought help from general medical
services exclusively.

Our first research question asked, “How do the demographic and psychosocial
variables of age, gender, education/SE8, discrimination, acculturative stress, DSM-IV
disorder status, and psychological distress predict use of services by Asian Americans?”
We found that gender was an important predictor for the full sample, with women
seeking help at significantly higher rates than men. This is consistent with previous
research indicating that Asian American women display more favorable attitudes toward
seeking help (Tata & Leong, 1994). However, the proportion of females vs. males
seeking help was not as striking as the 2/3 proportion of female help-seeking frequently

found in general population samples (Good, Dell, & Mintz, 1989). Significant

37

differences between service users and non-users suggest that individuals who sought any
form of service experienced greater rates of past discrimination, higher levels of distress,
and higher rates of DSM-IV disorders. These findings are consistent with previous
research indicating that past experiences of discrimination are associated with increased
distress and psychopathology (Leong, 1986; Gee et al., 2007; Ying & Miller, 1992). Sue
and Chu (2003) have noted that discrimination can lead to both increased levels of
distress and increased mistrust of available mainstream services. Our findings with the
general sample supported the relationship between discrimination and distress. In
addition, individuals who sought services were found to have significantly higher levels
of English language proficiency than those who did not. This is also consistent with
previous research indicating that limited English language proficiency served as a barrier
to service use (Leong, 1986; Gong, Gage, and Tacata, 2003).

Once variables were entered into logistic models in order to control for shared effects,
it was found that the demographic variables of age, gender, and education did not
independently predict general service use. For service use in general, the strongest
predictors were variables of distress. Both DSM-IV mood/anxiety disorder status and
psychological distress predicted increased use of services. In addition, English language
proficiency was found to independently predict increased use of services, consistent with
previous findings (Gong, Gage, and Tacata, 2003; Ying & Miller, 1992; Jang, Lee, &
Woo, 1998).

When we examine differences between use of formal and informal services
(research question 2), we find that the presence of a DSM-IV mood or anxiety disorder

most strongly predicts use of both forms of services, with stronger associations between

38

DSM-IV disorder status and formal service use. Psychological distress independently
predicts use of both formal and informal services at approximately equivalent rates. In
‘addition, at the level of formal and informal services, age was found to be a predictor of
service use in differential fashion. For formal services, age was found to be a positive
predictor of use. This is consistent with previous findings indicating that greater age
predicted higher levels of willingness to use psychological services among Asian
American populations (Barry & Grilo, 2002). However, age negatively predicted
informal service use, such that older individuals were less likely to seek informal
services. This may reflect the effects of physical illness, which would increase the use of
formal services, particularly general medical services, in older populations. Conversely,
this may reflect cultural notions about appropriate care of older individuals, as surveyed
by Aroian et a1. (2005). This finding parallels that of Gong, Gage, and Tacata (2003),
who found that age was negatively associated with use of the lay system and positively
associated with use of the general medical domain.

English language proficiency was found to predict the use of formal services, but not
informal services. There is evidence to suggest that immigrants who have a language
barrier experience higher rates of stress, anxiety, and depression than those without a
language barrier (Ding & Lee, 2009). Consequently, these individuals may seek services
for these problems at a higher rate. These results suggest that English language
proficiency increases the use of formal services (controlling for forms of distress), but
may not affect use of informal services. Informal services are more likely to be
community-based (e.g., a community or spiritual leader), and hence are more likely to

offer services in the languages of the community (Callejas et al., 2008).

39

We predicted that the use of specialty mental health services would be predicted by
variables associated with higher acculturation, as reported by previous studies. In fact,
when we examine use of specialty mental health services we find two positive predictors
of service use: DSM-IV disorder status and English language proficiency. DSM-IV
mood/anxiety disorder status predicted increased used of specialty mental health services
at a greater rate than the use of formal service (in general) or informal services. This may
reflect the extent to which specialty mental health services are provided according to the
DSM-IV conceptualization of distress, such that Asian American individuals who
interpret distress in emotional terms may be more likely to seek services in accordance
with that view. Hence, as with English language proficiency, DSM-IV disorder status
may to some extent reflect acculturation to mainstream U.S. conceptualizations to
distress. Previous research has demonstrated greater rates of service use and greater
willingness to seek psychological help among Asian American individuals who report
higher levels of acculturation to mainstream U.S. norms (Abe-Kim et al., 2007, Tata &
Leong, 1995). In addition, studies with Chinese American populations have
demonstrated that interpretation of distress in primarily psychological terms predicted
increased help-seeking, while somatization of symptoms served as a barrier to receiving
psychological help (Kung & Lu, 2008; Ying, 1990). The finding with regard to ELP
supports the interpretation that use of formal services may reflect acculturative factors.
In addition, the significance of ELP as a predictor of service use may reflect barriers in
access to formal services for individuals without ELP (Callejas etal., 2008).

Results: Ethnic Subgroups

40

Given significant differences between Asian American ethnic subgroups with
regard to social status, values, conceptualizations of distress, and willingness to seek
treatment, we predicted that rates of service use and predictor variables would vary across
ethnic groups. Notably, although rates of service use did not significantly vary across
groups, many of the predictors were found to be significantly different for different ethnic
subgroups. The demographic variables of age and education were found to be
significantly different, reflecting the differential distribution of these variables within
groups (U .S. Census Bureau, 2007). Rates of English language proficiency, past
experiences of discrimination, and psychological distress were also found to vary across
groups. Filipino Americans reported the highest levels of English language proficiency
and discrimination, while Chinese Americans reported the highest levels of psychological
distress.

Given that rates of service use do not vary across groups while predictor variables do
vary, there is some evidence to suggest that predictor variables may differentially predict
service use for each ethnic subgroup. Our final hypothesis asserted that predictor
variables will differentially predict service use, and this is supported by our findings. Our
final analysis compared the predictive value of demographic and psychosocial variables
across ethnic groups and found significant differences in predictors of service use, with
the most striking differences found in sources in distress.

For service use in general, DSM-IV mood/anxiety disorder status was found to predict
service use for all groups. The strongest effect was found for the Chinese group, with
the weakest effect found for the Filipino group. Psychological distress, controlling for

DSM-IV status, predicted use of services for all groups at approximately equivalent rates.

41

However, for the Chinese subgroup, it was found that the presence of a probable
substance use disorder predicted use of services at a high rate. These results suggest that
some similarities exist between groups with regard to predictors of service use,
particularly with regard to psychological distress as defined by DSM-IV mood and
anxiety disorders; however, other forms of distress (e.g., substance use disorders) may
influence service use for certain subgroups only.

When we compare usage of formal and informal services, we find that formal service
use is predicted by the presence of a probable DSM-IV mood/anxiety disorder across all
three groups, while the presence of a mood/anxiety disorder predicts informal service use
for the Filipino group only. Once again, this may reflect the extent to which individuals
interpreted distress in psychological terms. Similarly, psychological distress predicts
formal service use for all three groups, but only predicts informal service use for the
Chinese sample. The use of informal services is predicted by the presence of a probable
IED diagnosis for the Vietnamese group, the presence of a mood/anxiety disorder for the
Filipino group, and the presence of an eating disorder among the Chinese group. This
further supports the idea that forms of distress predict service use patterns differentially
for different ethnic subgroups.

Finally, we examined predictors of specialty mental health service use across ethnic
subgroups. Once again, DSM-IV mood/anxiety disorder status was a positive predictor
of service use for all groups. In addition, IED predicted specialty mental health service
use for the Vietnamese sample. Distress, controlling for DSM-IV status, predicted
service use for the Vietnamese and Filipino samples, but not the Chinese sample. This

may indicate that Chinese Americans in the sample sought specialty mental health

42

services only for forms of distress encapsulated by DSM-IV diagnostic categories, or
possibly that Vietnamese and Filipino Americans sought specialty mental health services
for distress not encapsulated by the DSM-IV categories surveyed in the NLAAS.
Research into differential patterns of service use for distress across ethnic groups is
sorely lacking, and as such the interpretation of this finding is unclear. Of note is the
finding with regard to Vietnamese Americans, such that Vietnamese reporting higher
levels of discrimination were significantly less likely to seek specialty mental health
services. Previous research has suggested that discrimination may impact service use
through increased distress (Gee et al., 2007). It has also been argued that experiences of
discrimination may decrease use of formal services due to mistrust (Sue & Sue, 1990).
These results suggest that higher rates of discrimination predict lower rates of specialty
mental health service use when controlling for distress, indicating an independent effect
of discrimination that merits further investigation. This finding was non-significant for
the Filipino and Chinese samples, suggesting that past experiences of discrimination may
predict service use in a differential fashion for these groups (e.g., exclusively through
increased distress).

Use of specialty mental health services was also predicted by higher English language
proficiency in the Chinese American sample, consistent with previous findings indicating
that limited English proficiency is a barrier to formal mental health services (J ang, Lee, &
Woo, 1998). However, this effect was not found for any other ethnic group or for use of
any other service. This may indicate that English language proficiency, when controlling
for its associations with distress, may not be as important an independent factor across

Asian American subgroups. Conversely, this may reflect problems with the scale used,

43

such that the limited range of values precludes significant findings. Future research
should attempt to measure language proficiency more effectively so as to assess its
implications for service use.
Future Research

The results of this study suggest a number of avenues for future research into help-
seeking and distress among Asian American populations. Consistent positive
relationships between DSM-IV mood/anxiety disorder status and use of health services
for psychological problems, as well as positive relationships between ELP and service
use, suggest that use of formal services may be related to acculturation factors and
interpretations of distress, as suggested by previous studies (Y ing, 1990; Tata & Leong,
1994; Abe-Kim et al., 2007). Unfortunately, the limitations of the NLAAS preclude an
examination of the relationship between symptom expression and service use. The
diagnostic interview employed in this survey used a “gateway” approach to DSM-IV
diagnosis, such that only those individuals who reported that they had felt sad or hopeless
most of the day, nearly every day were given the firll depression questionnaire.
Consequently, it is difficult at this time to examine the possible effects somatic
expression of distress may have had on patterns of service use, and results may reflect
only those individuals who adopt an acculturated interpretation of distress. Future studies
should endeavor to examine somatization of distress and its effects on patterns of service
use (Y ing, 1990).

Significantly, Filipino Americans differed from the other groups with regard to DSM-
IV disorder status: Filipinos in the sample reported significantly higher rates of probable

eating disorder diagnoses. To date, research examining prevalence rates and correlates of

44

eating disorders in Filipino American populations is severely lacking. Extant research on
eating attitudes and body satisfaction has primarily focused on cross-cultural rather than
multicultural analyses, and has generally found that Filipino males exhibit patterns of
disordered eating at a much higher rate than Caucasian American males (Kayano et al.,
2008; Madanat, Hawks, Novella, & Lennileth, 2006). A single multicultural study by
Yates, Edman, and Aruquete (2004) examined body mass index (BMI) and body
dissatisfaction in Asian American subgroups in Hawaii. They found that Filipino
American males reported the highest BMIs of all groups but demonstrated a female
pattern of strong body dislike and preference for smaller body size. Our finding may thus
reflect culture-specific concerns about body image, weight, and disordered eating.
Further research on the prevalence and correlates of eating disorders among Filipino
Americans is needed.

Also of note is the finding that psychological distress predicted service use
independently of DSM-IV disorder status. One explanation for this finding is that the
psychological distress scale reflects the presence of forms of distress not captured by the
DSM-IV disorder statuses examined herein, for which Asian American adults seek
services (e.g., psychotic disorders). Conversely, this may reflect problems with the
diagnostic interview used in this study, and the psychological distress figures could
reflect sub-threshold symptoms of DSM-IV disorders. Finally, this may reflect problems
in the DSM-IV diagnostic categories themselves, which may fail to adequately assess
psychological disorders as conceptualized and expressed by Asian American adults (e.g.,
somatization of distress). Independent effects of psychological distress, controlling for

DSM-IV disorder categories, were found across multiple models in this study.

45

Additional research into the conceptualization and expression of psychological distress
among Asian American adults, and the relationship between the expression of distress
and service use, is recommended.

Research into the effects of different forms of distress on service use by Asian
Americans is very limited. A previous study by Abe-Kim et a1. (2007) found no
differential effects of DSM-IV status on patterns of service use according to ethnicity;
however, the variable of DSM-IV status was coded dichotomously in their study,
masking important subgroup differences according to disorder type. This study has
improved upon their design by disaggregating distress data so as to examine independent
effects of different major categories of DSM-IV disorders. Results indicate that DSM-IV
disorders differentially predict use of services across ethnic groups, such that individuals
belonging to different Asian American ethnic subgroups sought services for different
types of DSM-IV disorders. Further research is needed to determine patterns of service
use for different diagnostic statuses across Asian American ethnic subgroups.
Limitations

Although these findings may have strong implications for future research, this study
had some limitations. First, the use of a secondary data set for analysis constrained
variable selection; for example, although acculturative factors have been identified as
predicting service use, no scale of acculturative values was included in the NLAAS
survey. Hence, some variables (i.e., education) serve as proxies for preferred variables
(i.e., SES). In addition, the measurement of some variables was problematic: for
example, the English language proficiency variable was comprised of a four-level scale

based on subjective self-assessment, and as such differences between levels are difficult

46

to interpret and imprecise. The NLAAS surveyed both professional and folk sources of
help, but did not assess lay sources such as fiiends and family, which may serve as a
primary source of help for Asian American populations (Rogler & Cortes, 1993). Also,
some scales were altered from their original format in the development of the NLAAS,
and many of these scales have yet to be thoroughly validated with Asian American
samples. For example, although the concordance of WHO-CIDI diagnoses with
independent diagnoses made using the World Mental Health Structured Clinical
Interview for DSM-IV (WMH-SCID 2000) has been assessed with a Latino sample, as
yet no studies have examined concordance rates with an Asian American sample (Alegria
et al., 2009). As such, it is unclear to what extent CIDI diagnoses approximate diagnoses
given using other clinical diagnostic interviews.

Another limitation of this study is the poor match in timing between the DSM-IV
disorder status variables (12 month prevalence) and the psychological distress variable
(30-day functioning and distress). This limits the extent to which it can be argued that
distress predicts service use independent of DSM-IV disorder status, and may then
underestimate the extent of psychological distress over the course of the previous year.
Future studies should attempt to examine concurrent measures of DSM-IV status and
general psychological distress. In addition, we were unable to assess and control for the
impact of acculturative stress in this study due to poor reliability of the scale, and a
portion of the psychological distress reported by subjects may reflect distress associated
with processes of acculturation. As previous studies have demonstrated that acculturative

factors play a strong role in help-seeking behaviors among Asian Americans, future

47

research should consider the impact of acculturative stress on service use (Gee et al.,
2007)

Finally, although this study was performed with a nationally-representative sample of
Asian Americans sampled with sophisticated methodology, results may not necessarily
generalize to the general population. Specifically, oversampling of the three target
groups (Vietnamese, Filipino, and Chinese) may have resulted in a weighting of these
effects in the full sample analyses. Consequently, findings with regard to subgroup
differences are believed to be more generalizable to target groups. In addition, although
sample sizes were very large for this study the rate of service use was extremely low;
significant results may have been missed due to low base rates of occurrence. This
limitation highlights both the serious underutilization of services by Asian American
groups and the difficulties of conducting research with minority populations.

This study has improved upon previous research into service use, using a large,
nationally-representative sample of Asian Americans. Previous findings with regard to
the relationship between distress and service use have been supported, with partial
support of previous findings with regard to gender, English language proficiency, age,
and discrimination. This study is the first to examine differential patterns of use by Asian
American ethnic subgroups according to forms of distress, and has provided evidence to
suggest that subgroups may seek different services for different problems. These
findings may have significant implications for both research and practice. The
disaggregation of data into ethnic subgroups revealed service use differences masked by
the overly-inclusive use of a single, monolithic group, highlighting both the reality of

ethnic subgroup differences among Asian Americans and the need for future research to

48

consider results at the level of ethnic subgroups. As found in previous studies, there is
evidence of considerable underutilization of services by Asian American groups relative
to their population size and levels of reported distress. This study further illuminates the
need for culturally-appropriate, linguistically-diverse services and suggests that
distinctions in need for services lie at the level of ethnic subgroups.

In summary, our study highlights the need for more research into the correlates of
help-seeking behavior among Asian American adults, specifically with regard to seeking
services according to differential patterns of distress. These findings indicate that rates of
service use among Asian American adults are very low despite evidence of diagnosable
levels of psychopathology and psychological distress. In addition, patterns of service use
according to forms of distress vary significantly at the level of ethnic subgroups,
particularly with regard to the differential seeking of formal as opposed to informal
services for psychological problems. There is some indication that past experiences of
discrimination and limited English language proficiency may serve as barriers to service
use for some Asian American subgroups. Further, the independent predictive power of
the psychological distress measure, in combination with the consistently strong predictive
power of probable DSM-IV mood/anxiety disorder statuses, may indicate that Asian
American adults in our sample sought services for psychological distress expressed in a
manner unaccounted for by current DSM-IV conceptualizations of distress. Finally, these
findings support the assertion that group differences with regard to service use lie at the
level of ethnic subgroups rather than at the level of a single, monolithic Asian American
group, and suggest that future research in this domain should consider ethnic subgroup

differences when examining help-seeking behavior. This study has expanded upon

49

previous research into help-seeking behavior among Asian Americans, and may have

significant implications for future research and current practice.

50

APPENDIX A
Table l
Predictors of Help-Seeking in a National Sample of Asian Americans: Descriptive

Statistics for Predictor Variables, Full Sample (N = 2095)

 

 

Variables M (%) SD Range
Gender (Female) 52.0%
Age 41.2 14.77 18 - 95
Education

0-11 years 15.1%

12 years 17.8%

13-15 years 25.3%

2 15 years 41.9%
English Language Proficiency 2.7 1.03 1 — 4
Experiences of Discrimination 6.9 6.41 0 - 45
Acculturative Stress“ 2.3 1.41 0 — 9

DSM-IV Disorder Status

 

Mood/Anxiety 1 1.7%
Substance Use 1.3%
IED 2.4%
Eating Disorder 1.6%
Distress 2.71 3.58 0 — 23
* (n = 1636)

51

Table 2

Descriptive Statistics for Outcome Variables, Full Sample (N = 2095)

 

 

Yes No
Variables
N (%) N
Any Service Use 131 (6.3) 1964
Formal Service Use 113 (5.4) 1982
Specialty Mental Health 79 (3.8) 2016
Informal Service Use 47 (2.2) 2048

 

52

Table 3

Intercorrelations of Service Use and Demographic Variables

 

 

Variables 1 2 3 4 5 6
1. Any Service —
2. Formal Service .93**
3. Informal Service .44** .22**
4. Ment. Health Service .77** .83** .24**
5. Gender .05* .04 .05* .05* —
6. Age .00 .03 -.08** .02 .00 —
7. Education .02 .04 .05 .04 -.08** -.2l**

 

p < .05. **p< .01.

53

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55

Table 6

Mean Values or Frequencies for Predictor Variables as a Function of Service Use

 

 

(Any)
Service Use No Service Use
Variable (n = 131) (n = 1964) x2
Gender 4.25*
Male 51 947
Female 80 1017
Age 41.35 41.21 83.02
Education 1 .05
0-11 years 19 297
12 years 22 350
13-15 years 38 491
2 15 years 52 826
ELP 2.94 2.76 10.69*
Discrimination 8.71 6.88 58.44*
DSM—IV Status
Mood/Anxiety 67 178 210.60"
Substance 9 19 32.45“
[ED 8 42 8.30M
Eating Dis. 4 30 1.79
Distress 6.72 2.44 2.51.91"

 

*p<.05. **p<.01.

Table 7

Mean Values or Frequencies for Predictor Variables as a Function of Formal Service

 

 

Use
Service Use No Service Use
Variable (n = 113) (n = 1982) x2
Gender 3.64
Male 44 954
Female 69 1028
Age 43.29 41.10 86.01
Education 2.92
0-1 1 years 18 298
12 years 22 350
13-15 years 34 495
2 15 years 39 839
ELP 2.87 2.77 10.12*
Discrimination 8.42 6.91 56.32*
DSM-IV Status
Mood/Anxiety 61 184 206.83"
Substance 8 20 29.88"
IED 8 42 1 1.29**
Eating Dis. 3 31 0.80
Distress 6.97 2.47 252.33"

 

*p<.05. **p<.01.

57

Table 8

Mean Values or Frequencies for Predictor Variables as a Function of Informal Service

 

 

Use
Service Use No Service Use
Variable (n = 47) (n = 2048) x2
Gender 6.14*
Male 44 954
Female 69 1028
Age 33.51 41.40 74.82
Education 5.96
0-1 1 years 4 313
12 years 5 367
13-15 years 13 516
2 15 years 26 852
ELP 3.11 2.77 5.52
Discrimination 9.77 6.93 71 .09**
DSM-IV Status
Mood/Anxiety 26 219 88.60“
Substance 4 24 1877‘”
[ED 6 44 2223'”
Eating Dis. 4 30 14.29"
Distress 6.83 2.61 150.70"

 

*p<.05. **p<.01.

58

Table 9

Mean Values or Frequencies for Predictor Variables as a Function of Specialty Mental

Health Service Use

 

 

Service Use No Service Use
Variable (n = 79) (n = 2016) x2

Gender 4.89”“

Male 28 970

Female 51 1046
Age 42.56 41.17 86.05
Education 3.20

0-11 years 12 304

12 years 16 356

13-15 years 25 504

2 15 years 26 852
ELP 2.98 2.77 8.63
Discrimination 8.52 6.93 57.71 *
DSM-IV Status

Mood/Anxiety 47 198 181.63“

Substance 6 22 24.39“

[ED 6 44 9.56**

Eating Dis. 3 31 2.43
Distress 6.91 2.55 240.57"

 

*p<.05. **p<.01.

59

Table 10

Summary of Logistic Regression Analyses Predicting Any Service Use, Full Sample

 

 

Predictor [3 SE Odds Ratio
Gender (Female) 0.29 0.20 1.34
Age 0.01 0.01 1.01
Education -0.03 0.1 1 0.97
ELP 0.24 0.12 1.28*
Discrimination 0.00 0.02 1 .00
DSM-IV Status

Mood/Anxiety 1.66 0.21 5.27“
Substance 0.92 0.51 2.51
[ED -0. 13 0.47 0.88
Eating Dis. -O.7l 0.66 0.49
Distress 0.14 0.02 1.15"

 

*p<.05. **p<.01.

60

Table 11

Summary of Logistic Regression Analyses Predicting Formal Service Use, Full Sample

 

 

Predictor 13 SE Odds Ratio
Gender (Female) 0.27 0.22 1.31
Age 0.02 0.01 1.02“
Education -0. 12 0.1 l 0.89
ELP 0.26 0.12 1.29*
Discrimination 0.00 0.02 1 .00
DSM-IV Status

Mood/Anxiety 1.80 0.25 6.02**
Substance 0.98 0.53 2.67
IED 0.10 0.48 1.10
Eating Dis. -O.89 0.75 0.41
Distress 0.14 0.02 1.15"

 

*p<.05. **p<.01.

61

Table 12

Summary of Logistic Regression Analyses Predicting Informal Service Use, Full Sample

 

 

Predictor 0 SE Odds Ratio
Gender (Female) 0.63 0.34 1.89
Age -0.03 0.02 0.97*
Education 0.42 0.19 1.53*
ELP -0.03 0.19 0.97
Discrimination 0.01 0.03 l .01
DSM-IV Status

Mood/Anxiety 1.42 0.37 4.1 1**
Substance 0.60 0.67 1.82
IED 0.91 0.52 2.49
Eating Dis. 0.61 0.66 1.83
Distress 0.12 0.03 1.12**

 

*p<.05. **p<.01.

62

Table 13

Summary of Logistic Regression Analyses Predicting Specialty Mental Health Service

Use, Full Sample

 

 

Predictor [3 SE Odds Ratio
Gender (Female) 0.40 0.26 1.50
Age 0.02 0.01 1.02*
Education -0.18 0.13 0.83
ELP 0.39 0.15 1.47**
Discrimination -0.01 0.02 l .00
DSM-IV Status

Mood/Anxiety 2.06 0.29 7.88**
Substance 0.70 0.56 2.01
IED 0.05 0.52 1.05
Eating Dis. -0.33 0.73 0.72
Distress 0.11 1.1 1**

0.03

 

*p<.05. **p<.01.

63

Table 14

Frequency of Service Use as a Function of Ethnicity

 

 

Vietnamese Filipino Chinese
N (%) N (%) N (%) )8
Any Service Use 34 (6.5) 31 (6.1) 37 (6.2) 0.10
Formal Services 32 (6.2) 27 (5.3) 32 (5.3) 1.03
Specialty Mental 22 (4.2) 18 (3.5) 25 (4.2) 1.40
Informal Services 6 (1.2) 11 (2.2) 17 (2.8) 4.40

 

*p<.05. **p<.01.

64

Table 15

Mean Values or Frequencies for Predictor Variables as a Function of Ethnicity

 

 

Vietnamese Filipino Chinese
Variable (n = 520) (n = 508) (n = 600) x2
Gender 2'15
Male 243 235 284
Female 277 273 316
Age 43.1 41.9 41.6 276.61“
*1:
Education 214'“
29.2% 10.4% 14.2%
0-11 years
22.3% 19.1% 16.0%
12 years
0 0 0
13_15 years 24.8%) 33.1% 19.5AI
2 15 years 23.7% 37.4% 50.3%
ELP 2.1 3.3 2.6 485.55M
D' . . . 4.2 8.9 7.1 365.76“
lscrrmrnatron
DSM-IV Status
0 0 0
Mood/Anxiety 9.2/0 12.0AI 12.7 /o 4.26
0
Substance 0.6 /o 1.8% 1.2% 4.37
IED 1.4% 3.2% 2.3% 4.01
o o 0 air
Eating Dis. 0.8 /o 2.9 /o 0.8 A) 11.13
Distress 2.4 2.6 3.2 211.65"

 

*p<.05. **p<.01.

65

 

Table 16

Summary of Logistic Regression Analyses Predicting Any Health Service Use, by Ethnic

 

 

Subgroup
Vietnamese Filipino Chinese
__Pfedi0t0r Ii S_E 93 Ii _S_E Q_R Ii SE 9.13
Gender
(Female) 0.17 0.43 1.19 0.61 0.44 1.84 0.27 0.41 1.31
Age 0.01 0.02 0.49 0.01 0.01 1.01 0.00 0.02 1.00
Education .001 0.23 1.01 -002 0.23 0.99 0.11 0.68 1.11
ELP -005 0.30 0.95 0.28 0.31 1.33 0.30 0.24 1.35
Discrimination —0.05 0.04 0.95 -0.01 0.03 1.00 0.05 0.03 1.05
DSM-IV
Status
Mood/Anx 1.98 0.52 7.23** 1.54 0.46 4.65" 2.21 0.43 9.12M
Substance ’ 1.21 0.88 3.35 2.65 1.08 1411*
IED 1.50 1.16 4.49 0.08 0.95 1.09 -0.61 0.92 0.54
Eating Dis. a -O.78 1.04 0.46 0.19 1.35 1.21
Distress 0.14 0.04 1.15" 0.21 0.06 1.23" 0.10 0.04 1.11*

 

*p<.05. **p<.01.

a. Frequencies are insufficient for analysis.

66

Table 17

Summary of Logistic Regression Analyses Predicting Formal Health Service Use, by

 

 

Ethnic Subgroup
Vietnamese Filipino Chinese
__Pfedi010f 11 $2 93 1.3. SE. % E SE QR
Gender
(Female) 0.00 0.43 1.00 0.96 0.49 261* 0.01 0.45 1.01
Age 0.02 0.02 1.02 0.02 0.02 1.02 0.01 0.02 1.01
Education .007 0.23 0.94 0.01 0.25 1.02 -0.10 0.26 0.91
ELP -0.12 0.30 0.89 0.35 0.33 1.42 0.36 0.25 1.43
Discrimination -0.04 0.04 0.96 -0.01 0.03 0.99 0.03 0.04 1.03
DSM-IV
Status
Mood/Aux 1.78 0.54 5.94** 1.51 0.50 4.53** 2.61 0.48 13.65"
Substance a 1.77 0.91 588* 2.57 1.07 1312*
IED 1.74 1.12 5.71 0.34 1.00 1.40 -073 0.95 0.48
EatingDis. a -1.70 1.33 0.18 0.36 1.38 1.43
Distress 0.13 0.04 1.14** 0.25 0.49 2.61“ 0.09 0.05 1.10*

 

*p<.05. **p<.01.

a. Frequencies are insufficient for analysis.

67

Table 18

Summary of Logistic Regression Analyses Predicting Informal Health Service Use, by

 

 

Ethnic Subgroup
Vietnamese Filipino Chinese
___Predict0r 12 SE Q 12 S_E_ DE 12 SE 98
Gender
(Female) 1.56 1.24 4.76 -0.07 0.74 0.93 0.46 0.59 1.58
Age 0.04 0.04 1.04 -0.05 0.03 0.95 -0.04 0.03 0.96
Education 1.01 0.57 2.74 -0.06 0.41 0.94 0.47 0.38 1.60
ELP -0.06 0.64 0.95 0.17 0.55 1.12 0.18 0.33 1.20
Discrimination -0.01 0.09 1.00 0.04 0.05 1.04 -0.02 0.05 0.98
DSM-IV
Status
Mood/Anx 2.31 1.33 10.11 1.54 0.46 15.01“ 0.79 0.64 2.19

Substance a 0.75 1.09 2.12 0.65 1.30 1.91

[ED 3.46 1.35 31 .72* 0.22 1.25 1.24 0.30 1.22 1.35

Eating Dis. a -0.24 1.45 0.79 2.68 1.26 14.62*
Distress 0.12 0.09 1.13 -0.01 0.10 1.00 0.10 0.04 1.11*

 

*p<.05. **p<.01.

a. Frequencies are insufficient for analysis.

68

Table 19

Summary of Logistic Regression Analyses Predicting Specialty Mental Health Service

Use, by Ethnic Subgroup

 

 

Vietnamese Filipino Chinese
__Predictor Q 5.1: Q! 11 SE. % 12 SE 9.8
Gender
(Female) 0.15 0.50 1.18 1.14 0.63 3.14 -0.24 0.50 0.79
Age 0.02 0.02 1.02 0.03 0.02 1.03 0.01 0.02 1.01
Education 0.09 0.26 1.10 -0.36 0.32 0.70 -0.13 0.32 0.88
ELP -0.07 0.35 0.93 0.85 0.47 2.35 0.65 0.31 1.92*
Discrimination -0.14 0.07 0.87* -0.01 0.04 0.99 0.05 0.04 1.05
DSM-IV
. Status
Mood/Anx 1.48 0.68 4.40* 2.17 0.62 8.74** 2.92 0.56 18.54“
Substance a 1.69 0.97 5.42 0.71 1.10 2.02
IED 2.61 1.09 13.66* -0.64 1.34 0.53 -0.24 0.92 0.79
Eating Dis. a -1.70 1.47 0.18 0.56 1.42 1.75
Distress 0.12 0.05 1.12* 0.25 0.08 1.28" 0.09 0.05 1.10

 

*p<.05. **p<.01.

a. Frequencies are insufficient for analysis.

69

 

APPENDIX B

Figure 1. Example of computer-assisted interview (CAI) item from the Experiences of

Discrimination scale, as viewed by NLAAS respondents.

DS 1 e

(RB, PG 52)

(In your day-to-day life how often have any of the following things happened to you?
(Would you say ahnost everyday, at least once a week, a few times a month, a few
times a year less than once a year, or never?))

People act as if they are afraid of you.

1 ALMOST EVERYDAY

2 AT LEAST ONCE A WEEK

3 A FEW TIMES A MONTH

4 A FEW TIMES A YEAR

5 LESS THAN ONCE A YEAR

6 (IF VOL) NEVER

 

70

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