Chapter 19

MENTAL HEALTH DISPARITIESJuniusJ. Gonzales, MD, MBA; andAiria Sasser Papadopoulos, MPH

Introduction

Even before the Institute of Medicine released its critical report Unequal Treatment:Confronting Racial and Ethnic Disparities in Health Care, evidence was mounting on thedifferential rates of access to services, quality of care received, and improvement inhealth outcomes among different groups of people (Smedley, Stith, & Nelson,2003). Since 2003, the Agency for Health Care Research and Quality (AHRQ) hasreleased its annual National Healthcare Disparities Report (Agency for HealthcareResearch and Quality [AHRQ], 2009), which "summarizes health care quality andaccess among various racial, ethnic, and income groups and other priority popula-tions, such as children and older adults" (p. i). As an example, the 2008 reportincludes residents of rural areas and individuals with disabilities and special healthcare needs as priority populations.

The evidence on mental health disparities is increasing. Studies from the 19805show that minorities were more likely to delay or not seek mental health care,receive less adequate care, and terminate care earlier (McGuire & Miranda, 2008).More recent work denotes that disparities are found in access to and the provisionand receipt of care, for example, for the treatment of depression (Miranda, McGuire,Williams, & Wang, 2008; Harman, Edlund, & Fortney, 2004), help-seeking behav-iors of children and adolescents (Zimmerman, 2005), overall mental health careservices use (Garland et al, 2005), and psychotropic drug use (Han & Liu, 2005).These mental health disparities data are important in light of the fact that althoughrates for most mental disorders are lower in Hispanics and Blacks than in Whites,the individuals receive poorer prognoses and their disorders are more chronic(Breslau et al., 2006; Williams et al., 2007).

Michelle Tong

Michelle TongPreference can be biased, and personal experience related. Some illness might need specific treatment and preference is not a choice.

Health (2003). In 1989, the Agency for Health Care Policy and Research wascreated within the U.S. Department of Health and Human Services. Its charge wasto "improve the quality, safety, efficiency, and effectiveness of health care for allAmericans" (AHRQ, 2008). In 1999, Congress mandated through the passage ofthe Healthcare Research and Quality Act that the agency, now renamed as theAgency for Healthcare Research and Quality (AHRQ), produce annual reports onhealth care quality and disparities in the United States (Poker, Hubbard, Sharp, &Collins, 2004).

Commissioned by the AHRQ, a special committee on quality and quality mea-surement produced two reports (Hurtado, Swift, Corrigan, & the Committee onthe National Quality Report on Health Care Delivery, 2001; Swift & the Committeeon Guidance for Designing a National Healthcare Disparities Report, 2002) thatassisted in the creation of the National Health Care Quality Report (NHQR) and theNational Healthcare Disparities Report (NHDR) in 2003.

The 2002 IOM report titled Unequal Treatment: Confronting Racial and EthnicDisparities in Health Care (Smedley et al., 2003) was produced within a year of theAHRQ reports and denoted a slightly different framework. The report also studiedfactors that contribute to inequities and proposed recommended policies for elimi-nating the inequities (Smedley et al., 2003). lOM's model for health disparitiesemphasized the presentation of patient needs to providers as the central pathwayfor how racial and ethnic disparities emerge. According to the framework, threeparties (clinicians, utilization managers who are slightly distanced but who partici-pate in the treatment process, and patients) exercise discretion in influencing thehealth care received by patients in a clinical setting. The model begins with patientinput, which leads to both the patient's contribution to a medical history and aphysical examination of symptoms. The second step outlines social, economic, andcultural influences on interpretation and intervention, respectively, both of whichare potentially subject to the outside influences of stereotyping, prejudice, andfinancial incentives. The third step and outcome of the first two steps is raciallydisparate clinical decisions.

The primary goal of the two AHRQ reports is to outline and monitor the sta-tus of the quality of health care provided to Americans with particular emphasis onsubpopulations. The NHQR identifies gaps in the provision of quality health care inthe United States. The NHDR is focused on racial, ethnic, and socioeconomic dis-parities in health care provided to vulnerable populations. It identifies where differ-ences exist and has the potential to influence the development of new and improvedinterventions to ensure that the highest quality of care is delivered to subpopula-tions (AHRQ, 2009).

From the NHQR emerged an early conceptual framework that identified twoaspects of treatment in a clinical setting that potentially influence health disparities.The first aspect of treatment addresses provider elements of treatment quality, suchas the effectiveness of treatment and the quality of the interaction between clinicianand patient. The second aspect of treatment identifies patient needs, such as stayinghealthy and living with illness/disability, which are potentially of primary concernto recipients of care. A slightly expanded framework appears in the NHDR thatbuilds upon the initial NHQR framework with the addition of measures that addressequity, including access to care, use of services, and costs. The dimensions of race,

ethnicity, and socioeconomic status were incorporated into the framework with afocus on influencing health outcomes (Poker et al., 2004).

Interestingly, the AHRQ and the IOM reports situate key elements of respon-sibility for the occurrence of health disparities with both patients and clinicians.Neither report specifically condones or condemns the clinical structure/provider orthe patient, but rather identifies that both parties play a key role. Most evidentwithin these and other reports developed since that examine health disparities is thechallenge to revamp health care systems in order to better meet patient needs andto reduce, rather than further widen, gaps in outcomes.

Individual researchers expanded upon old frameworks and created new onesfor understanding disparities using the elements described above. Kilbourne,Switzer, Hyman, Crowley-Matoka, and Fine (2006) observed, in a review of thehealth disparities literature, that many researchers devoted their attention to docu-menting the occurrences of disparate treatment in clinical settings and less tounderstanding the underlying causes. In addition, little focus was placed upon howto address health disparities systematically. In response to this observation, theydeveloped an epidemiologically based conceptual framework (see Figure 19.1) toguide health services researchers, clinicians, and policymakers in future healthdisparities research in health care settings.

The framework focuses on the health care system, precisely and uniquelyextends the definition of vulnerable populations to include impoverished popula-tions in addition to racial ethnic minorities, and provides a distinct plan for how toproceed with effecting change in disparities. It consists of three phases, the first ofwhich is the detection of disparities and causes. The second phase is the under-standing of social determinants of disparities at four levels: patient, provider, theclinical encounter, and the health care system. The third phase includes stages forreducing or eliminating health disparities, including developing interventions,evaluating the effectiveness of treatment, translating and disseminating the find-ings, and changing policy. The authors posit a possible addition to this framework,namely, reciprocal feedback between phases. For example, interventions to reducedisparities (phase 3) may yield information for new ways to measure disparities(phase i).

Detecting

Define health disparitiesDefine vulnerablepopulationsMeasure disparities invulnerable populations

;onsider selectioneffects and confoundingfactors

Understanding

Identifying determinantsof health disparities atthe following levels:

Patient/individualProviderClinical encounterHealth care system

ReducingIntervene

EvaluateTranslate anddisseminateChange policy

. i iFigure 19.1 The Three Phases of the Disparities Research Agenda. (Source: Kilbourne,A. M., Switzer, G., Hyman, K., Crowley-Matoka, M., & Fine, M. J. [2006]. Advancinghealth disparities research within the health care system: A conceptual framework.American Journal of Public Health, p6[iz], 2113-2121.)

A second component of Kilbourne et al.'s framework builds upon the elementsoutlined in the other conceptual frameworks for identifying and understanding thenature of health disparities. This framework examines four factors (health care sys-tem, patient, clinical encounter, and provider) with the inclusion of a final step fordrawing the findings back into the overarching health care system in order to createchanges in the delivery of care (see Figure 19.2).

Examining the patient experience in treatment settings has been a primaryfocus of conceptual frameworks on health disparities. Cooper, Hill, and Powe(2002) credit the IOM report as moving beyond a traditional examination ofpatient-provider interaction to examining issues that affect equity, and they statethat it is "a useful starting point" (p. 478). They developed a new conceptual model,based upon Donabedian's traditional structure-process-outcomes model that mergeselements of a 1993 IOM report on access to care and the ability for a provider toadequately address a patient's needs. In addition, they layer in personal and familialbarriers that may intercede with a patient's ability to engage fully in treatment (seeFigure 19.3). The model begins with the patient's financial and personal situationand progresses to use of services, mediators, and outcomes. One additional uniqueelement of this framework is the importance of the patient's experience with the

Barriers Health Care ProcessesPersonal/Family

acceptability cultural language/literacy attitudes, beliefs preferences involvement in care health behavior education/income

Structural availability appointments how organized transportation

Finsncis! insurance coverage reimbursement

levels public support

>Use of Services

Visits primary care specialty emergency

Procedures preventive diagnostic therapeutic

Mediators Outcomes-> Quality of providers

cultural competence communication skills medical knowledge technical skills bias/stereotyping

Appropriateness of care

Efficacy of treatment

Patient adherence

-> Health Status mortality morbidity well-being functioning

Equity of Services

Patient Views of Care experiences* satisfaction

partnership

Figure 19.3 Barriers to and Mediators of Equitable Health Care for Racial and EthnicMinorities. (Source: Adapted from Cooper, L. A., Hill, M. N., & Powe, N. R. [2002].Designing and evaluating interventions to eliminate racial and ethnic disparities inhealth care. Journal of General Internal Medicine, iy[6], 477-486.)

Health Care System FactorsHealth services organization, financing, and deliveryHealth care organizational culture, quality improvement

Provider Factors Beliefs and preferences Race/ethnicity, culture,

and familial context Education and resources Biology

Clinical Encounter Knowledge and attitudesCompeting demandsBias

Provider communicationCultural competence

Figure 19.2 Understanding the Origins of Health and Health Care Disparitiesfrom a Health Services Research Perspective: Key Potential Determinants of HealthDisparities within the Health Care System, Including Individual, Provider, andHealth Care System Factors. (Source: Kilbourne, A. M., Swit7,er, G., Hyman, K.,Crowley-Matoka, M., & Fine, M. J. [2006]. Advancing health disparities research withinthe health care system: A conceptual framework. American Journal of Public Health.

Providerbeliefs

about HS(Beliefs aboutclinical factors,

social and[behavioral factors,

resources, e.g.,conscious andunconsciously

activated beliefs)

Professionaldecision making

(diagnosis, treatment,referral, and case

disposition)

Provider Interpersonalbehavior

(e.g., participatory style,warmth, content, information

giving question-asking)

HS cognitive and affective factors(e.g., acceptance of advice, attitude.self-efficacy,

intention, feelings of competence.)

Note. HS = help seeker.

Figure 19.4 Proposed Mechanisms through which Health and Human ServiceProviders Can Influence Race/Ethnicity Disparities in Treatment. (Source: van Ryn, M., &Fu, S. S. [2003]. Paved with good intentions: Do public health and human service pro-viders contribute to racial/ethnic disparities in health? American Journal of Public Health,H[2], 248-255.)

Recent work, using decision-making theories and Bayesian models to under-stand disparities, has resulted in the concept of "statistical discrimination." Borrowedfrom the labor literature, statistical discrimination in health care addresses howpatient needs are matched to treatment by the provider based upon the quality ofinformation. Poor communication between the patient and provider, for example,may result in a minority-group patient being worse off on average when comparedto majority-group patients. Add to this the use of patient categorization, as men-tioned above, and one can see how miscommunication may result in less-than-effective treatment, a stance supported in the empirical literature addressingpatient-physician communication and improved patient outcomes (Balsa, McGuire,& Meredith, 2005; McGuire et al, 2006).

New statistical approaches (Duan, Meng, Lin, Chen, & Alegria, 2008) attemptto address the complexity of factors, at multiple levels, that may or may notcontribute to health disparities. Complex methodological issues are of paramountimportance and have even led to recommendations by the National Center forHealth Statistics within the Federal Centers for Disease Control and Prevention(Keppel et al., 2005). The main six issues (with eleven ensuing guidelines) in thatreport on measuring disparities are:

1. The selection of a reference point from which to measure disparity;2. Measurement of disparity in absolute or in relative terms;3. Measurement of disparity in terms of favorable or adverse events;

4. Measurement of disparity focusing on individual groups in a pair-wise fashionor focusing on a summary measure for the domain that includes thesegroups;

5. Choosing whether to weight component groups when calculating summarymeasures of disparity; and,

6. Choosing whether or not to consider the order inherent in the domainswith ordered categories when calculating summary measures of disparity.(Keppel et al., 2005, p. i)

These recommendations are important in accurately describing the size and direc-tion of a disparity, changes over time, and conclusions across different indicators,geographic locations, or groups. As the report notes "different choices can, andfrequently do, lead to different conclusions about disparities" (Keppel et al., 2005,p.i).

DISPARITIES AND STIGMA

Stigma may contribute to or even moderate intervention effects on disparities. TheUnited Kingdom Government's Foresight Programme report on mental capitaland well-being contains a thorough and exceptionally complex influence diagramthat denotes relationships between the target (person with mental illness) andsource of stigma using constructs from emotion, cognition, social policy, and otherresearch (Jenkins et al., 2008). On the target side, the combination of behaviorrepresenting mental ill health, stress, and loss of socioeconomic opportunities canlead to complex emotional states, such as loss of self-confidence and anticipateddiscrimination. This side intersects with the "source" side where emotions, preju-dice, culture, and ignorance can contribute to a multi-layered discrimination.

One important question is whether and how stigma may play a role in thevarious levels of putative mechanisms that can partially explain mental health dis-parities, such as the work by McGuire and colleagues on statistical discriminationdiscussed earlier (Balsa et al., 2005; McGuire et al., 2006). Does a provider, as a"source of stigma," possibly have "potential priors" about mental illness that existbecause of stigma? Does a patient, because of prior experience with stigma, present(or not) certain things to the provider? Recent work on stigma in poor young immi-grant and U.S.-born Black, Latina, and White depressed women offers some inter-esting insights. Nadeem et al. (2007) found that Black and Latina (U.S.-born andimmigrant) women had more stigma-related concerns than White women and thatstigma was correlated with less desire for treatment except in the case of immigrantLatina women. This work was extended to confirm, per previous studies, that dif-ferent people from different backgrounds have different preferences for mentalhealth care. Minorities are less favorably inclined toward antidepressant medica-tion, but the stigma of mental illness reduced the preference for group counseling(Nadeem, Lange, & Miranda, 2008). Even work from large secondary data analysesusing four years of data suggest that some disparities in mental health care usemay result from different propensities to both interpret and report symptoms(Zuvekas & Fleishman, 2008).

Other recent work investigated whether racial and ethnic differences existed inattitudes about people with mental illness or stigma. Issues of perceived dangerous-ness and desire for segregation from people with mental illness were examined andfound to differ. For example, while African Americans and Asian Americans per-ceived higher dangerousness and had more desire for segregation than Caucasians,Latinos perceived lower dangerousness and had less desire for segregation thanCaucasians (Rao, Feinglass, & Corrigan, 2007).

MENTAL HEALTH DISPARITIES: SELECTED FINDINGSThe literature related to health disparities has exploded and includes mental healthconditions. Much of the work is descriptive, limited by the nature of data and study-designs, and thereby often unable to elucidate mechanisms of action or contributeto thinking about predictive causal models. While factors such as income and lim-ited English proficiency are associated with poorer physical and mental health andservices utilization (Bandiera, Pereira, Arif, Dodge, & Asal, 2008; Dobalian &Rivers, 2008; Sentell, Shumway, & Snowden, 2007), much less work has elucidatedpossible mediating or moderating factors, especially in regard to preventing orreducing disparities.

The 2001 Surgeon General's report titled Mental Health: Culture, Race andEthnicity highlighted critical issues that special populations face. It also illuminatedthe complexity and difficulty involved in the development of evidence-based prac-tices and the conducting of day-to-day practice and policy decision-making(USDHHS, 2001). That report cited evidence for the following: i) minorities haveless access to, and availability of, mental health services; 2) minorities are less likelyto receive needed mental health services; 3) minorities in treatment often receivepoorer quality care; and 4) minorities are under-represented in mental healthresearch studies. The relationship of ethnicity to outcomes is often difficult tounderstand given not only the measurement of ethnicity, but also important factorssuch as acculturation, previous provision and receipt of services, discrimination,immigration experiences, cultural beliefs, environment, and social influences byother groups (Bernal, Bonilla, & Bellido, 1995).

The National Institute of Mental Health (NIMH) recently funded two largeepidemiologic studies of racial and ethnic minorities, the National Latino and AsianAmerican Survey (NLAAS) and the National Survey of American Life (NSAL), toaugment the most recent survey of mental disorders known as the NationalComorbidity Survey-Replication (Collaborative Psychiatric Epidemiology Surveys,n.d.). Known as the Collaborative Psychiatric Epidemiology Surveys (CPES), theCPES combined dataset is considered by many as a single, nationally representativestudy. Data are available on the prevalence of mental disorders, impairments associ-ated with these disorders, and treatment patterns from representative samples ofmajority and minority U.S. adult populations. Additional data collected examinedthe ties between mental disorders and socio-cultural issues, such as language use,perception of disparities, support systems, discrimination, and assimilation.

The CPES and similar studies can help tease out the possible differences inmental health symptoms, disorders, and related functional status. Capturing all of

these differences is beyond the scope of this chapter, but knowledge about these"clinical" differences is helpful in better understanding disparities. The CPES hasfound that for many mental disorders, either overall prevalence rates across racialand ethnic groups are similar, or, in fact, minorities may have lower prevalencerates (e.g., major depressive disorder or MDD). However, drill-down analysesacross and within groups are critical to employ. For example, while Blacks may havelower rates of MDD, the course and severity of the disorder may be more seriousand difficult. Even within the larger group of Blacks who have MDD, the long-standing notion of higher prevalence rates in women (e.g., 2/3) does not seem tohold among Caribbean Blacks, where men have rates of 50% (Williams et al., 2007).Other studies indicate such findings as lower rates of reported functional impair-ment in depressed Latinos versus other groups but no other differences related torace or ethnicity (that is, similar levels of functioning in the presence of depressivesymptoms). Interestingly, the issue of how people express and report their function-ing is critical, and similar findings for Latinos are seen in studies of diabetics andother chronic medical illnesses (Huang, Chung, Kroenke, & Spitzer, 2006).

New reports from one of the largest epidemiologic studies focusing on Latinomental health (using nationally representative samples) indicate that lifetime preva-lence rates of mental disorders are nearly equal in Latino men (28.1%) and women(30.2%) (Alegria et al., 2007). Prevalence rates were higher overall for people whohad migrated before the age of 13 or after age 34, while good or excellent languageproficiency was associated with increased risk for past year disorders in both gen-ders. The complex results suggest multi-factorial effects cutting across genetic,environmental, role, and nativity/origin constructs. The same study showed thatcultural factors such as language, age of migration, nativity, years of U.S. residence,and generational status were associated with use (or lack) of mental health servicesfor Latinos who did not meet full disorder status, but "who may need preventiveservices or who are symptomatic but not diagnosed with a disorder" (Alegria et al.,2007).

Access and Barriers to Care

The 1993 IOM report Access to Health Care in America noted:

Access is a shorthand term used for a broad set of concerns that center on thedegree to which individuals and groups are able to obtain needed servicesfrom the medical care system. Often because of difficulties in defining andmeasuring the term, people equate access with insurance coverage andhaving enough doctors and hospitals in the areas in which they live. Buthaving insurance or nearby health care providers is no guarantee that peoplewho need services will get them. Conversely, many who lack coverage or livein areas that appear to have shortages of health care facilities do, indeed,receive services. (Millman, 1993, p. 32)

The IOM committee took these concerns and predicated its final definition onboth use and impact of services: access is "the timely use of personal health services

Barriers

StructuralAvailabilityHow organizedTransportation

FinancialInsurance coverageReimbursement levelsPublic support

PersonalAcceptabilityCulturalLanguageAttitudesEducation/Income

Use of Services Mediators Outcomes

Visits

Procedures

ippropriatenessL

Efficacy oftreatment

Quality ofproviders

Patientadherence

Health Status Mortality Morbidity. Well-being FunctioningEquity ofServices

Figure 19.5 Model of Access to Personal Health Care Services. (Source: Millman M, L.[1993]. A model for monitoring access. In Access to Health Care in America [pp. 31-45].Washington, DC: Institute of Medicine, Committee on Monitoring Access to PersonalHealth Care Services. Washington, D.C.: The National Academies Press.)

to achieve the best possible health outcomes" (p. 33). The report depicted the fol-lowing model and created indicators for utilization and outcomes, but noted thedynamic and complex relationships between these factors.

The authors describe this '"access" model in order to provide a straightforwardframework for the many examples of mental health disparities in the literature.Another example is a recent review on Latino adults' access to mental health care(Cabassa, Zayas, & Hansen, 2006). It found existing studies to be helpful, but alsofraught with limitations that might provide misleading conclusions.

Whether or not someone uses services is a complex phenomenon that touchesissues at many levels, from an individual levelfrom knowledge to attitudes topreferencesto social level (e.g., stigma) to systems level (availability), as noted inthe Barriers category in Figure 19.5. Furthermore, unique combinations betweenaccess factors may or may not sum up service utilization, quantity, and duration ofthe utilization, or appropriateness. The following simple example notes the com-plexity of factors that play into access such as the personal factor of attitudes. Aperson may personally acknowledge mental health concerns, such as depressivesymptoms, but then not communicate those to the caregiver. This can certainlyimpact the provision and receipt of services.

Using a large national survey, Probst, Laditka, Moore, Harun, and Powell(2007) found that of those people who acknowledge depressive symptoms, only51.8% reported those to a physician or other practitioner (e.g., social worker, coun-selor, nurse). For the Whites (54%), Hispanics (48%), and African Americans(35.7%) who did report depression concerns, other differences and interactionswere found among individual characteristics, such as gender, age, marital status,health status, and health insurance. Another study using a large national survey

' with a baseline population of nearly 300,000 found complex interactions betweenrace/ethnicity, income, and chronic medical disease (asthma) on the reporting ofpoor mental health (Bandiera et al., 2008). Sentell et al. (2007) found that languagebarriers were critical in mental health treatment in non-English speaking Asian/Pacific Islander and Latino persons with mental disorders.

Finally, important factors such as family support (or lack thereof as a barrier)are not represented in the model, but are often described in studies. Ethnic andcultural differences in family involvement were associated with disparities in outpa-tient and inpatient mental health services (Snowden, 2007). Similarly, the role ofspirituality (Williams et al., 2007) is an emerging area of iriquiry.

The health services research literature is replete with descriptions of the struc-tural and financial barriers to care, and the area of mental health services is not anexception. Both qualitative and quantitative approaches have provided data frommultiple perspectives, and organizational characteristics (e.g., chaotic work envi-ronment; level of work control) of where minority patients receive care may offersome new insights for multi-level interventions (Barrio et al., 2008; Varkey et al.,2009).

Culture: A Earner?

One important issue, linked to personal and social "barriers," that impacts access isculture. While beyond the scope of this chapter, a long-standing literature on therelationships between culture, illness, and help-seeking has provided understand-ing of their influence on mental health. A recent paper proposes a conceptual para-digm, the Cultural Influences on Mental Health (CLMH) model, to betterunderstand "the dynamic and interactive nature of culture on interrelated mentalhealth domains" (Hwang, Myers, Abe-Kim, & Ting, 2008). The authors defineculture "broadly as not only including the set of attitudes, values, beliefs, and behav-iors shared by a group of people, but also as inclusive of culture-related experiencessuch as those related to acculturation and being an ethnic minority" (p. 212).The figure below illustrates how culture might affect six domains of mental health:i) the prevalence of mental illness; 2) etiology of disease; 3) phenomenology ofdistress; 4) diagnosis and assessment issues; 5) coping styles and help-seeking path-ways; and 6) treatment and intervention issues.

The CIMH model can be used to understand recent work such as new datafrom audiotaped and videotaped clinical encounters, in both specialty mental healthand primary care, which try to elucidate missing information in diagnoses andpossible ensuing disparities for Latinos and about differences in visit durationfor African Americans (Alegria, Nakash, Lapatin et al., 2008; Ghods et al., 2008;Olfson, Cherry, & Lewis-Fernandez, 2009). Again, though beyond the scope of thisdiscussion, attention to culture and health care has led to developments and researchon cultural competency including new measure development (Lucas, Michalopoulou,Falzarano, Menon, & Cunningham, 2008) to overcome thorny measurement issuesthat troubled the concept. In similar fashion, the recent development of socio-cultural assessment protocols (SCAP), specifically for people who suffer from men-tal disorders, offers promise, but will need more testing and linking to consumer

Diagnosis Treatment

Figure 19.6 The Cultural Influences on Mental Health (CIMH) Model. (Sotme:Hwang, W.-C., Myers, H. E, Abe-Kim, J., & Ting, J. Y. [2008]. A conceptual paradigmfor understanding culture's impact on mental health: The cultural influences on mentalhealth [CIMH] model. Clinical Psychology Review, 28(2], 211-227.)

outcomes (Yamada & Brekke, 2008). More work is needed on understandinghow culture is not a barrier but a facilitator to access care and perhaps reducedisparities.

Utilization of Services: The Provision and Receipt of CareWhile the literature is rapidly accumulating studies of racial and ethnic disparities,one important empirical paper actually implemented the IOM definition of dis-parities regarding outpatient mental health care. The IOM definition was chosenfor three key reasons: i) high prevalence of mental disorders; 2) the role of socialfactors in the recognition and treatment of these disorders (status as mediators ofdisparities can be tested); and 3) data demonstrating disparities in mental healthcare (McGuire et al., 2006). Using a large national survey of nearly 10,000 persons,the study modeled expenditures for mental health care for Whites, Blacks andLatinos but asked the important guiding question to apply the IOM definition ofdisparity to the analytic strategies: "how much more (or less) treatment wouldminorities receive than whites if they had the same health status as whites?"(p. 1986). Analyses examined initial differences, computations based upon the esti-mated effect of race and ethnicity, and then adjustments of all other variables (e.g.,SES), thereby making comparisons with other disparity "measures." Significantdifferences (disparities) in care for mental health problems were found betweenWhites and both Blacks and Latinos. McGuire and co-authors note that one keypiece of the IOM definition, preferences, could not be examined with this data-set,but the rigorous methods used in this study set excellent standards given the vari-able application of definitions and conclusions drawn in other work. Other studies

used the same approach to test for "statistical discrimination" with a different largenational dataset, the Medical Expenditures Panel Survey, and data from a trial inprimary care. Both of these studies found similar results (Cook, McGuire, &Miranda, 2007; McGuire et al., 2008).

In the National Comorbidity Survey-Replication (NCS-R), racial and ethnicminorities had higher rates of no initial treatment contact after onset of a mentaldisorder and longer delays to seek treatment, and they were less likely to use ser-vices that were capable of delivering adequate psychopharmacology and psycho-therapy services (Wang et al., 2006). In a study of nearly i ,200 primary care patients,Latinos and Blacks were less than half as likely as Whites to receive any depressioncare, much less quality guideline-concordant care, even controlling for such factorsas age, education, employment status, comorbid medical illness, or depression oranxiety diagnosis (Lagomasino et al., 2005). Several other studies continue to showsimilar racial and ethnic disparities in the use of mental health services (Dobalian &Rivers, 2008) even when co-occurring chronic medical diseases (e.g., diabetes andischemic heart disease) (Glover et al., 2007; Waldman et al., 2009) or co-occurringsubstance use is present, which usually increases service utilization (Hatzenbuehler,Keyes, Narrow, Grant, & Hasin, 2008).

Disparities persist across age and subgroups from children (Howell &McFeeters, 2008; Snowden, 2007) to elders (Barrio et al., 2008; Dobalian & Rivers,2008), and across service sectors such as primary care (Stockdale, Lagomasino,Siddique, McGuire, & Miranda, 2008), emergency room settings, and other publicmental health settings (Snowden, 2005) and modalities of treatment (e.g., medica-tion, counseling, referral [Miranda et al., 2008; Stockdale et al., 2008]). Disparitiesin receipt of medication exist even after controlling for actual access and utilizationof specialty or tertiary services, yet some total psychotropic medication utilizationdifferences are not accounted for by observable characteristics and may representunobserved issues such as provider-patient relationships, trust, and socio-culturalfactors (Zuckerman et al., 2008; Chen & Rizzo, 2008). A recent study (Alegria,Chatterji et al., 2008) using the CPESwith national samples, good diagnostic andquality indicators, and large numbers of non-English speaking peoplefound thatin people with depression in the past year, 40.2% of Whites did not access mentalhealth care, but that respectively 58.8% of African Americans, 63.7% of Latinos,and 68.7% of Asians did not access care. Furthermore, the three minority groupswere on average nine to 2 3 percentage points less likely to access care and receiveadequate treatment.

OutcomesThe literature is thin on longitudinal assessment of mental health disparitiesregarding outcomes and even thinner on intervention work specifically designedto target disparities reduction. However, data from large studies where the pri-mary goal was improving outcomes, in general, for mental health problems areable to make a contribution. Using data from a large quality improvement trial,depressed Latinos who had initially much lower rates of care gained significant

improvements at 6 and 12 months compared to Whites that did not differ from thecontrols (Miranda et al., 2003). Nine year follow-up data indicate that, althoughthe minority groups are aggregated into one group for analysis, long-term benefitson outcomes for depressed minorities may come from psychotherapy interven-tions (Wells et al., 2007). Some recent work demonstrates that interventions aimedat structural barriers, integrating mental health into primary care, might overcomesome racial and ethnic disparities in both access to and engagement in mentalhealth treatments (Ayalon, Arean, Linkins, Lynch, & Estes, 2007) (see Chapter 16for more information on integration of primary care and mental health care).

Finally, work has indicated that "control-oriented" strategies to improve func-tional disablement associated with depression may have differential and improvedimpact on depression in older African Americans than Whites and provides insightinto the discrepancy between lower reported emotional distress and higher func-tional impairment in the former group (Gitlin, Hauck, Dennis, & Schultz, 2007).The literature is not lacking in calling for more inquiry into interventions to reducedisparities by cultural tailoring but also to consider low cost dissemination at thestart (Chin, Walters, Cook, & Huang, 2007; Van Voorhees, Walters, Prochaska, &Quinn, 2007).

Federal entities, such as the National Institute of Mental Health, are con-cerned about disparities and supported two important workgroupsone in 2001on psychosocial intervention development and one in 2005 on services and inter-vention research for Latinos. Both had relevant recommendations to this study(Hollon et al., 2002; Vega et al., 2007). The first one was the "development of user-friendly interventions and non-traditional delivery methods to increase access toevidence-based interventions, especially among underserved special populations"(Hollen et al., 2002, p. 615). The second group emphasized the importance of fiveresearch foci: diagnosis, quality of care and appropriate services, psychosocialintervention development, psychopharmacologic interventions, and access to care(Vega et al., 2007). The sparse literature on outcomes and intervention work mustbe augmented by new investments in these areas. Two disparities scholars (Rust &Cooper, 2007) delineated a dozen gaps in existing disparities research but offeredrecommendations to overcome those gaps using practice-based research-which canextend beyond primary care (Table 19.1).

Implications for Mental Health

A rapidly growing literature on mental health disparities and the enormous diseaseburden that mental disorders incur provide a call for action and for a comprehen-sive research agenda to tease out the complex factors that belie the findings andshed light on intervention development. Since resources to develop brand newagendas for all subgroups are not a reality, this is particularly critical for anti-stigmainterventions and processes for cultural adaptation of existing interventions. Despiteprogress made through some policy and national initiatives, work demonstratesthat the disparity gaps for mental health care in certain groups, like Latinos, arewidening (Blanco et al., 2007). The title of a recent commentary (Race and MentalHealth: More Questions than Answers) summarizes where the field is:

Table 19.1 A Dozen Gaps in Existing Disparities Research and How Practice-Based Research could meet the NeedWhy Cuirent Disparities ResearchSometimes Falls Short Hou< Practice-Based Research Could Meet the Need

1. Research in academic or closed-panel settings

2. Nondiverse research teams

3. Investigator-initiated research4. Focus on changing provider

behaviors5. "Inside-the-practice" research

6. Focus on process measures

7. Narrowly focused single diseaseinterventions

8. Experiments test oneintervention

9. Static interventions heldconstant throughout the studyperiod

10. Academic cycle time

11. Randomized-controlled clinicaltrials

12. Replicability without scalability

Conduct research in real-world, limitedresource, high-disparity primary care practicesettingsDevelop diverse research teams that areproportionately representative of the disparitypopulation being studiedTrue community partnershipResearch on systems change involving patients,teams, and processes of careBlur the boundaries between practice-basedresearch and community-based interventionsMeasure health outcomes at the communitypopulation health levelAddress complex mix of disparities in chronicdisease outcomes, risk factors, and mentalhealth comorbiditiesTest multi-dimensional interventions thattriangulate on improved outcomes from atleast three directionsprovider, patient, andcommunityTest dynamic, constantly improvinginterventions

Rapid-change cycles, continuously revisingintervention based on rapid-feedback healthoutcomes data loopsAlternative study designs to measure multi-dimensional, dynamic interventions repeatedlyTest interventions that are both replicnble andscalable in real-world, under-resourced settingsthat serve high-disparity populations

Source: Rust, G., & Cooper, L. (2007). How can practice-based research contribute to the elimina-tion of health disparities? Journal of the American Board of Family Medicine: JAEFM, 20(2), 105-114.

A researcher's understanding of what "race" captures can importantly affectthe questions that are asked and the questions that remain unasked. Extantracial categories do not capture biological distinctiveness in humanpopulations and single-gene disorder models are unlikely to account forracial differences in disease with a complex etiology. Race is an imprecisevariable that captures differential exposure to the resources and rewards insociety and SES is regarded as a proxy for the social and economic inequalitythat race historically and currently reflects. (Williams & Earl, 2007, p. i)

Finally, not just researchers, but practitioners, policymakers, and commtirtiTOTmust all take up the following:

The challenge for disparities researchers in the 2 ist century will he to shmv,at the level of an entire zip code or county, and then an entire state, and ulti-mately for the nation, that we can substantially reduce disparities not just inquality of care but in health outcomes across all racial/ethnic groups andachieve health equity for all. (Rust & Cooper, 2007, p. in)

Racial and ethnic disparities in health continue to be a complicated issue thatcannot be reduced to either simple causes or resolutions. It has yet to be deter-mined whether there are unique or special factors that distinguish disparities inmental health. Additional consideration is needed to understand the implicationsfor developing, adopting, and implementing evidence-based practices for multicul-tural communities and for determining which factors facilitate or prevent a reduc-tion in disparities. Knowledge of the potential causes and effects is one of manysteps needed to reduce and eventually eliminate disparities.

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Chapter 20

THE RECOVERY MOVEMENTWilliam A. Anthony, PhD; and Lori Ashcraft, PhD

THIS CHAPTER examines the mental health field prior to the recovery movementand then traces the origins of recovery from severe mental illnesses and howrecovery became the guiding vision for the mental health field. The chapter notesemerging consensus as to the definition, components, and assumptions of recovery;identifies the research forming the evidence base for recovery; and advances a publichealth conceptual model of recovery, based upon the recovery research. It describesservice delivery that is guided by the vision of recovery, and, lastly, discusses policyissues, including implications for mental health and future challenges.

Introduction and Overview

For most of the previous century, the notion of recovery from severe mental ill-nesses was certainly not a movement in the mental health field. Not only wasrecovery not a movement, it was not even a mental health concept. In actuality, themental health system seemed to be designed to hinder recovery. The idea of recov-ery from severe mental illnesses was largely absent from the last century's diagnos-tic schemes (American Psychiatric Association [APA], 1987) and maintenance-typeinterventions (Bachrach, 1976; Grob, 19943; New Freedom Commission on MentalHealth [NFCMH], 2003). The Diagnostic and Statistical Manual of the AmericanPsychiatric Association characterized schizophrenia in this way: "the most commonoutcome is one of acute exacerbations with increasing deterioration between epi-sodes" (APA, 1980, p. 195). Even worse, for much of the previous century, through-out North America and Europe, not only were people with severe mental illnessesnot expected to recover, they were often dehumanized and devalued by both society