In the Eye of the Storm Race and Genomics in Research and Practice Vivian Ota Wang Stanley Sue

The difficulties of operationalizing race in research and practice for social, behavioral, and genetic researchers and practitioners are neither new nor related to recent genetic knowledge. For geneticists, the bases for understanding groups are clines, observed traits that gradually change in frequency between geographic regions without distinct identifiable population boundaries and population histories that carry information about the distribution of genetic variants. For psychologists, race may not exist or be a social and cultural construct associated with fluid social inferences. Because definitions of populations and race can be socially and biologically incongruent, the authors suggest that geneticists and social and behavioral scientists and clinicians attend to external validity issues by operationalizing population and racial categories and avoiding race proxies for other biological, social, and cultural constructs in research designs, data analyses, and clinical practice.

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he results of genomic discovery along with the promises of molecular medicine have energized the cultural discourse about science and health. Although confusion of this genetic twist for some people has been a naive faith (or dread) that genetics (the study of single genes and their effects), genomics (the study of gene functions and interactions across the genome and environmental factors; Guttmacher & Collins, 2002), and biology are interchangeable, not all biological differences are genetic. Acquired or inherited biological differences can exist because of human population differences secondary to migration effects (e.g., genetic drifts, bottlenecks, selection) and other factors such as occupation, nutrition, toxic exposures, fetal and neonatal development, and discrimination. To unravel the complexity of health, disease, and behaviors, social, behavioral, and epidemiologic scientists have studied disease etiologies and processes by investigating genetic, environmental, and Genetic ⫻ Environmental interactions in twin, association, and epidemiologic-based studies, approaches used long before the advent of molecular biology (e.g., Heath et al., 2002; Jinks & Fulker, 1970; Malhotra & Goldman, 1999; Plomin & Crabbe, 2000). Shortcomings to these approaches include false-positive associations, recall bias, limited phenotypic and environmental exposure data, ascertainment bias of more severe cases, underrepresentation of underserved populations, and replication problems. Although large cohort studies— January 2005 ● American Psychologist Copyright 2005 by the American Psychological Association 0003-066X/05/$12.00 Vol. 60, No. 1, 37– 45 DOI: 10.1037/0003-066X.60.1.37

U.S. Department of Health and Human Services University of California, Davis

National Health and Nutrition Examination Survey (NHANES; U.S. Department of Health and Human Services, 1982), Framingham Heart Study (Dawber, Meadors, & Moore, 1951; Kannel, 2004), United Kingdom Biobank (Critchley & Capewell, 2003), and deCODE (Hakonarson, Gulcher, & Stefansson, 2003; Nievergelt, Smith, Kohlenberg, & Schork, 2004)— have or are being planned to overcome some of these barriers, their use also has also been limited by unavailable and unclear race or population inclusion criteria that make data from these large national data sets difficult to combine and compare (Collins, 2004). In contrast, quantitative genetics arose in the 1920s to examine how genetic, environmental, and Genetic ⫻ Environmental interactions vary because of evolutionary, developmental, and environmental factors. For example, some variations (polymorphisms) in DNA sequences are transmitted generation to generation over evolutionary time scales, whereas some variants arose more recently. These differences influence the quantity, timing, and effect of protein activity during the developmental and physiological lifetime of the individual (e.g., Gray & Thompson, 2004). Given the increasing crossover among the genetics, social, and behavioral research communities, the complexity of health and disease processes can be better contextualized and understood than previously done. Geneticists can provide a genomic framework of mechanistic and evolutionary explanations of health and diseases, whereas social and behavioral scientists can examine the complex Vivian Ota Wang, Ethical, Legal, and Social Implications Program, National Human Genome Research Institute, National Institutes of Health, U.S. Department of Health and Human Services; Stanley Sue, Department of Psychology, University of California, Davis. We thank Francis S. Collins, Lisa D. Brooks, Kevin O. Cokley, Morris W. Foster, Mark Guyer, Jean E. McEwen, and Joseph F. Rath for thoughtful comments on earlier versions of this article. The views expressed in this article are those of the authors. No official endorsement of the University of California, the National Human Genome Research Institute, the National Institutes of Health, or the U.S. Department of Health and Human Services is intended or should be inferred. Correspondence concerning this article should be addressed to Vivian Ota Wang, Ethical, Legal, and Social Implications Program, National Human Genome Research Institute, National Institutes of Health, U.S. Department of Health and Human Services, 5635 Fishers Lane, Suite 4076, MSC 9305, Bethesda, MD 20893-9305. E-mail: otawangv@ mail.nih.gov

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relationships among genetics, biology, society, culture, intrapsychic experiences, and behaviors. However, race, genetics, and psychology have shared a tumultuous history (Guthrie, 1998; Jones, 1997). On the one hand, geneticists recognize that genes act in concert with environmental factors and that a complete understanding of health, disease, and behavioral processes requires multifactorial, multidisciplinary research designs and analyses. However, they often focus their attention toward genomics and biology, overlooking environmental, social, cultural, and psychological factors that are rudimentary for social and behavioral scientists. On the other hand, many social and behavioral scientists have tended to disregard genetics. For some, their skepticism is due to their inability to make conceptual or theoretical connections between human health and the in vitro and animal models often used in genetics. Additionally, some are cautious about genetics because of their limited knowledge of biology. There is also nervousness about biological determinism because the history of psychology awkwardly reminds psychologists how their predecessors contributed to the conflation of genetics and race-based phenotypes (observable behaviors or traits such as intelligence and skin color) at the expense of other explanatory mechanisms (Duster, 2003; Guthrie, 1998). Yet others are more broadly concerned that focusing on genetics will divert attention from existing research efforts investigating reasons for health disparities by attributing poor health outcomes to genetics and thereby overemphasizing the potential of genetic research to alleviate health disparities (Sankar et al., 2004). Overall, the confluence of race, behavior, and genetics has been particularly contentious because misleading social and cultural inferences about biology and race especially in the area of behaviors (e.g., violence, intelligence, and ad38

dictions) have resulted in potential and real inequitable treatment of individuals and groups. Nevertheless, the debate about the biological and social meanings of race continues (Bhopal & Donaldson, 1998; Burchard et al., 2003; Cooper, Kaufman, & Ward, 2003; Foster & Sharp, 2002; Phimister, 2003; Risch, Burchard, Ziv, & Tang, 2002; Sankar & Cho, 2002). On the one hand, abandoning the variable of race because it has no biological or scientific validity has been an appealing choice for some researchers (Haga & Venter, 2003; Schwartz, 2001). On the other hand, if race does not exist, how are pharmacogenomic claims of inter- and intrapopulation differences in drug metabolism and toxicity justified (Evans & Johnson, 2001; Wilson et al., 2001)? To avoid unnecessary and potential harmful social or biological exaggerations of population differences, one needs a shared understanding of how geneticists and social and behavioral researchers define and use the concepts of population and race. This task is particularly difficult for both the social and behavioral scientists who are trying to find ways of achieving greater definitional precision of race without undervaluing the psychological and social significance and the geneticists who are cautious of not overestimating biological or genetic contributions to health and diseases in a race-conscious society. In this article, we describe ways geneticists and psychologists understand these concepts. We propose that increasing external validity, the extent to which research results can be applied to other people beyond the population studied (population validity) or settings (ecological validity; Campbell & Stanley, 1963; Cook & Campbell, 1979) will provide greater methodological consistency between these research communities. Ways of defining population categories and research design issues that avoid using race as proxy for other biological, social, and cultural constructs are also discussed.

Human Genetic Variation The human genome is organized into 23 pairs of chromosomes. These chromosomes carry the instructions for making proteins. Chromosomes are made of DNA and in turn are made of the smaller units called bases. Four bases, adenine, thymine, cytosine, and guanine, are specifically paired; an adenine with a thymine, and a cytosine with a guanine to form a double-stranded helix. The human genome contains three billion base pairs and is estimated to have 21,000 –25,000 genes. The genetic sequence of any human is estimated to be 99.9% identical to any other unrelated person (International Human Genome Sequencing Consortium, 2004). Of the roughly 20 million variable sites in the human genome, the major proportion, 85%, accounts for withingroup genetic diversity, with the remaining 10% representing variation between any two geographically distinct groups, and 5% between-groups from different continents (Jorde, Watkins, Bamshad, Dixon, & Ricker, 2000; Lewontin, 1972; Marth et al., 2003). This genetic variation is indicative of recent modern human ancestry with an initial low population size of about 20,000 people who January 2005 ● American Psychologist

Stanley Sue

shared genetic and physiological traits because of relative endogamy (preferential procreation of members of social units within their own group because of social or cultural norms) for prolonged time periods and a population expansion antedating the migration of modern humans out of Africa about 100,000 years ago (Cavalli-Sforza, Menozzi, & Piazza, 1994). However, cultural and geographic barriers to endogamy are fragile. Here, physical anthropologists and geneticists agree that traits (e.g., skin color) do not cluster in rigidly bounded populations but gradually change in frequency from one geographic region to another. This pattern of continuous variation is called clinal variation (Bamshad, Wooding, Salisbury, & Stephens, 2004). Even Charles Darwin (1871) recognized clinal variation, noting that there are no races without transitions to others; that every race exhibits within itself variations of color, of hair, of feature, and of form, to such a degree as to bridge over to a large extent the gap that separates it from other races. It is asserted that no race is homogeneous; that there is a tendency to vary. (p. 698)

Despite clinal variation, some human variation patterns cluster, are more common in particular population groups, and are biologically meaningful. For example, the ABO blood group is polymorphic in all populations. People belong to one of four blood types, A, B, AB, and O. Blood types are inherited in all people and have observed population frequency differences (e.g., in almost all populations, Type O is the most common type, with it being particularly common in some North and South American Indian populations; Lewontin, 1972). So why are some geographic regions perceived as major human population groups? In brief, human genetic variation patterns are influenced by population and migration history. People from local population groups are typJanuary 2005 ● American Psychologist

ically more closely related than are members of groups who live greater distances apart. Some population groups arose from a small number of people who expanded their geographic and social and cultural mores into other local and distant populations. Because of their small numbers coupled with a relatively endogamous lifestyle for large parts of their social and cultural history, their genetic contributions have been disproportionately magnified in their population cluster (Cavalli-Sforza et al., 1994). Because of migration events, biological meanings of genetic differences have been inferred in populations (King, 2002; Schwartz, 2001). For example, founder effects have resulted in variation in the prevalence of genetic variants and disease alleles such as Tay Sachs in Ashkenazi Jewish people, cystic fibrosis in people of Northern European ancestry (Arnason, Sigurgislason, & Benedikz, 2000; Lucotte & Hazout, 1995), and differences among populations in the frequencies of drug-metabolizing enzymes leading to pharmacogenomic differences among individuals in metabolism, efficacy, and drug toxicity (Exner, Dries, Domanski, & Cohen, 2001).

Looks or Drops When we talk about the concept of race, most people believe that they know it when they see it but arrive at nothing short of confusion when pressed to define it. (Higginbotham, 1992, p. 253)

The power of racialized thinking is derived from social impressions that race is biological and inextricable from a person’s essential character thereby having scientific legitimacy (Delgado, 1995). Because ethnocentric assumptions and stereotypes perpetuated by biology and race-based notions have been used to justify exploitation, slavery practices, and population stereotypes about behaviors, it is not necessarily the physical and biological realities but the social and personal significances attached to these features that people find unsettling (Gould, 1994; Takaki, 1994). Historically, race has been defined by morphological characteristics, such as skull volume and size, skin color, facial features, and other visible qualities that could be metrically measured and cataloged (Gould, 1981; Guthrie, 1998). Even now, people have been shown to place inordinate emphases on an overall physical gestalt of racial characteristics (e.g., Black, White, Asian) and are often unable to distinguish features that would help them recognize as individuals people who belonged to racial groups unlike their own (Levin, 2000). However, the practice of classifying groups on the basis of physical features is not new. For example, Linnaeus’s (1758) Systema Naturae categorized people by physical features and geographic ancestry into four racial groups (Europeaus, Asiaticus, Americanus, and Africanus). Linnaeus’s prote´ge´ Blumenthal defined five races (Caucasian, Mongolian, Ethiopian, American, and Malay) and has been suggested by Gould (1994) as proposing a race hierarchy of worth based on perceived beauty as embodied in a Caucasian ideal (from the people from the Caucasoid mountain range that lies between the Black and Caspian seas). All of these categories have been included in 39

nearly all subsequent race lists down to the present day (Risch et al., 2002; Rosenberg et al., 2002; D. W. Sue & Sue, 2003). By the 19th century, researchers were “discovering” that racial differences were biological and that morals, physical characteristics, intellectual capacity, and social differences were the consequence of blood or biology (Gould, 1981; Guthrie, 1998; Smedley, 1999). Using stateof-the-art science of the time, these researchers found evidence in biology, craniometry (measuring skulls to assign intelligence levels), anthropology, and medicine. Then as today, researchers were unsuccessful in finding valid and reliable population-specific metrics due to clinal and intragroup variation. For example, skin color (Parra et al., 2003) and ancestral geography (Bamshad et al., 2004) can be ambiguous proxies for genetic heritage. Recent reports of human genetic variation research reifying race or population clusters as naturally occurring (Risch et al., 2002; Rosenberg et al., 2002), rather than social and cultural constructions, has been occurring within the context of an increasing number of behavioral genetics claims related to mental illness (Chakravarti, 2002; Segurado, 2003), behaviors (Kluger, Siegfried, & Ebstein, 2002; McGough et al., 2002; Rhee & Waldman, 2002), and genetic determinism. The meaninglessness of race also has been gaining visibility in the popular and scientific press (Harpending & Cochran, 2002; Pinker, 2002). The issue of race and psychology again fills the pages of the American Psychologist over a decade after Yee, Fairchild, Weizmann, and Wyatt (1993) urged the American Psychological Association to address psychology’s problems with race and produce guidelines for research and publication. Many of the barriers to understanding race they listed still exist (e.g., inadequate definitions for race, fears of genetic determinism, misrepresentation of genetic information, and organizational and professional inaction). Therefore, we believe the task before psychologists is not to increase the length of their list or get mired in the details of how race should be defined but to advocate for intentionality and clarity when using race or population identifiers in research. Questions of whether studies are unduly racialized will largely depend on the questions being asked, the quality of the research, and the extent to which the conclusions can be supported. We believe the faults usually lie in problems of external validity where research findings and clinical applications are overgeneralized because of vague or unclear race or population descriptions and using race proxies in research designs, data analyses, and clinical interventions. Psychologists are all in the eye of the storm.

Recommendations Demographic variables are an essential and frequently unexamined part of the clinical and research enterprises. In its worst form, race is arbitrarily defined (if at all) and inconsistently used by researchers and clinicians because of their use of unclear and interchangeable terminology such as race, ethnicity, national origin, heritage, and ancestry. Varying notions of what population and race represent (e.g., biological aspects, psychological aspects, language, 40

behavior) also contribute to the confusion. Additionally, intragroup variation is rarely measured and accounted for, resulting in the tendency to ignore intragroup variation and report overgeneralized group findings. Failure to acknowledge intragroup variation can lead to overgeneralized clinical and research conclusions and thus problems of external validity. For example, social and behavioral researchers and clinicians often assume sample or group homogeneity because participants self-identify into a single forced-choice category (e.g., Asian) making it impossible to gauge intragroup variation. This in turn can lead them to erroneously conclude that a universal set of psychological qualities characterizes the population when comparisons are significant (Betancourt & Lo´pez, 1993; Zuckerman, 1990). Not only are these generalizations more monolithic than in actuality (e.g., Asians are nonverbal and family oriented), the conclusions drawn may bear little resemblance to possible unmeasured proximal processes that may better explain the observed phenomena (e.g., cognitive complexity/simplicity; individuation/collectivism, introversion/extroversion). This is particularly troublesome given psychologists training in identifying, measuring, and using proximal factors such as intrapersonal (e.g., cognitive styles, racial identity), situational (e.g., family systems, socioeconomic status, racism), and affective variables (e.g., depression, anxiety) in research and practice. S. Sue (1999) has argued that the state of psychological research is weakened by professional preferences and a selective encouragement (e.g., by journal editors) of internal validity (e.g., the confidence that causal relationships can be concluded between independent and dependent variables) over external validity as defining quality research. Although both forms of validity are important and necessary, internal validity dominates. We suggest that internal and external validity can be balanced. Compromises to research and clinical integrity need not be made if psychologists are equally deliberative and thoughtful about external and internal validity issues. If social and behavioral researchers and clinicians continue to rely on convenience sampling and disregard the importance of external validity and population identifiers, not only will the overall clinical utility and research quality diminish because of intra- and intergroup variation confounds, spurious clinical judgments and research results will contribute to fears of genetic determinism, eugenics, and discrimination. Geneticists and social and behavioral clinicians and researchers must attend to conceptual clarity by operationalizing population and racial categories and avoiding race proxies for other biological, social, and cultural constructs in research and clinical practice. Conceptual Clarity Researchers often assume that demographic categories such as race reflect phenotypically identifiable and stable qualities of people. However, great discrepancies in how race is defined and used have made population or racebased meta-analyses difficult. First, researchers frequently fail to operationalize what they mean when using populaJanuary 2005 ● American Psychologist

tion categories. Second, because race is often used as a proxy for other factors, it is at times unclear what the race demographic variable is actually measuring (or not measuring). Self-report is one way of ascertaining ancestry or race to define the population of interest. Research participants are typically asked to indicate their race (and/or ethnicity) by choosing one of a mix of options that reflect the researcher’s notions of race, ethnicity, national origin, or ancestry. Because a person’s self-reported identity incorporates a complex mix of biological, cultural, psychological, and behavioral factors not necessarily determined by genotype or biology (Li, 2003), racial self-referents can be highly variable and arbitrary, varying as a function of time, history, law, politics, social context, and emotions. Consequently, a person may define and respond differently at different times to the same questions about his or her race. Although some genetic researchers may be using multilocus genotype clustering as a way of avoiding the uncertainty of a study participant’s self-reported identity, similar to the forced choice of self-report, how they set their parameters will determine the scale and number of population clusters (Rosenberg et al., 2002). Ancestry, based on the lineage of progenitors who are assumed to compose lines of descent, is another population identifier that has often been used in genetics and social and behavioral research. Boyd’s (1950) forewarning more than a half century ago about the danger of “taking over the common man’s ideas of race and incorporating them into anthropological treatises” (p. 453) is particularly cogent given that populations that participate in research studies have been typically chosen because of convenience rather than more technical criteria. So, is self- or investigatoridentified ancestral geography adequate as a population identifier? Some researchers (e.g., Cavalli-Sforza et al., 1994) have presented dendrograms or tree diagrams equating their genetic data to colloquially defined races and believe that self- or investigator-identified ancestral geography is sufficient for defining populations. Other researchers have felt less confident of self- and investigator-identified ancestral geography as a proxy for population groups, especially when phenotypic overlap, increased population intermixing, changes of colloquial usages, and clinal and intragroup variation decrease its theoretical and predictive value and appeal. For a more detailed discussion of geographic ancestry, genetics, and race, see Bamshad et al. (2004). If researchers choose to use ancestral geography as a strategy for defining populations, they must explicitly operationalize what they mean by ancestry and geography and clearly state their underlying assumptions. This may be particularly relevant if the investigator is identifying how contextual variables are cohort or multigenerational experiences (e.g., access to health and mental health services in the context of discrimination and immigration laws). For example, given estimates that humans have been around for approximately 100,000 –200,000 years and assuming 20 years as the measure of one human generation, if a person January 2005 ● American Psychologist

is to be identified by grandparental geographic ancestry, then depending on the population’s history (e.g., patterns of migration) his or her identity may be reflective of contemporary temporal, geographic, political, and cultural factors rather than biological or genetic ones. Nevertheless, geneticists and social and behavioral scientists and clinicians should not be discouraged and summarily drop race as a variable or scientific term because they believe it is hopelessly ambiguous or a politicized descriptor of human populations. Instead, it is precisely because researchers and clinicians are subject to the same intentional and unintentional biases that exist in society that they must take particular care when describing and operationalizing what they mean when using race as a research variable or demographic descriptor. Therefore, operationalizing race is as an important part of the phenomenological world of the researcher, clinician, and study participants as the research question under investigation. Thus, researchers and clinicians alike will need to describe the assumptions and rationale underlying how their population or race labels are defined and used. As with any variable, psychologists should explain, define, and measure how they understand the variable of race and the rules they used to select and define the populations being studied. These efforts should meet similar standards of measurement and clarity as other constructs used in research. Not only must researchers strive for conceptual coherence and consistency, they will need to be thoughtful to a priori identify and include proxy variables into their study design or clinical judgments rather than relying on generating post hoc hypotheses that should have been initially accounted for or measured. As in most psychosocial research and practices, it is the psychological undercarriage of the demographic indices (e.g., attitudes, dispositions) that are of interest and not necessarily the biological or social nature of the variables themselves. With this approach, investigators will be able to investigate their questions with greater scientific rigor because they will have identified and included potential environmental and cultural proxy variables as possible independent, moderating, or mediating study variables. Race as a Second-Order Construct As a second-order construct, race is often used as a proxy for assumed biological, genetic, social, psychological, and other phenotypic factors including people’s beliefs about ancestry, nationality, language(s)/accent, religion, skin color, racial identity attitudes, and so forth. The danger of using proxy variables lies in their indirect quality and attached assumptions. For example, when Crow (2002) recently stated that members of certain races make good athletes but are less qualified to be physicians, he implied athletic ability and intelligence were innate to certain populations. Even with little to no supporting evidence that complex traits and behaviors, such as diabetes, intelligence, criminality, athletic ability, and so forth, are genetic, biological, or inherited (Herrnstein & Murray, 1994), these assertions are difficult to idiomatically dispute because of peoples’ social and racialized conditioning that reinforce 41

racial stereotypes as being true. Thus, population comparisons often exaggerate group differences at the expense of within-group variation and distribution overlaps. To minimize this unfounded biological default, psychologists will need to expand their research design, analyses portfolio, and clinical decision making to include proxy variables. So how can psychologists engage in research that combines genetic, biologic, environmental, and intrapsychic factors without perpetuating unfounded racial stereotypes? They must begin using more multifactorial research designs and clinical data that accommodate complex, environment, and phenotype interactions. This information will enable researchers to realistically understand how interactions among biological, social, and physical environments can affect health and disease. Additionally, because of the de facto biological presumption conferred on independent variables in research designs, psychologists should explore more stepwise and complex linear models and data analyses (e.g., structural equation modeling) that use race as a moderating and/or mediating variable instead of as an independent variable. This will allow for a realistic account of how population variables moderate and mediate complex systems (Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001). Moderators are categorical (e.g., race, sex) or continuous (e.g., income, degree of depression) variables that affect the direction or strength of the relationship between the independent and dependent variables and address questions of when or for whom a variable causes or predicts an outcome. Mediators are variables that account for or explain the relationship between independent and dependent variables and usually involve establishing how or why an independent variable causes or predicts a criterion variable (Baron & Kenny, 1986; Holmbeck, 1997).

Race, Genetics, and Health Disparities One way to investigate the issues of race is to be more thoughtful about what race means as a distal or proximal variable when doing research on population and health disparities. By clarifying the roles and types of conclusions that can be drawn, psychologists will find that interpretations of research findings will be less confusing, especially when biological and social experiences (e.g., phenotypebased cognitive distortions and stereotyping) are being examined in the same research or clinical model. For example, race often is used as a distal variable. Unlike proximal factors that may actually be responsible for differences (e.g., acculturation), distal variables are furthest from the point of causation, are typically descriptive (e.g., race, gender), and do not directly explain an observed phenomenon. Thus, psychologists need to understand the research and clinical implications of using and interpreting race as a distal variable. To do this, they need to avoid overreliance on descriptive analyses and distal explanations and consider more theoretically driven proximal factors. Overall, to avoid contributing to and reifying existing notions of race as being biological and absolute, psychologists need to explain group differences beyond simple 42

descriptive analyses. As a starting point, researchers and clinicians who rely on self- or investigator-reported racial categories and attribute their research findings to race or population should clearly operationalize what they mean by race, population, or culture and include measures about the constructs underlying their population assumptions (e.g., collectivism, locus of control) rather than doing post hoc deductions. Additionally, population-based conclusions should be considered only when other possible proxy or confounding factors (e.g., socioeconomic status, insurance coverage, racial identity status) have been taken into account. Unless this is done, comparative population studies can become particularly troublesome, as they may unintentionally reify biological determinism and perpetuate unfounded stereotypes (Beutler, Brown, Crothers, Booker, & Seabrook, 1996). Therefore, researchers and clinicians should not avoid using the variable of race because race in fact is important as a social and cultural construct. However, unless researchers and clinicians use race judiciously, race can be misleading because of varying and inconsistent definitions and uses across studies, invalid biological or social/cultural assumptions, and misinterpretations of the proxy and/or distal variable(s). Although it is true that researchers and clinicians may want to use race as a gestalt or as a term encompassing many variables associated with the experience of racial minorities (e.g., minority group status, stigma because of skin color, experience with prejudice and discrimination, etc.), the usefulness of race as a variable is an empirical question that should be dismantled and examined in the following stages. First, what is the definition and what are the advantages and limitations imposed by the definition? Second, does the variable make a difference? Third, if differences are found, why do they exist? Are the racial explanations consistent with what is allowable given one’s definition? Particular care must be taken to avoid using a socially based definition and invoking a genetic explanation (or vice versa) in the absence of strong and compelling evidence. Additionally, if race is being examined as a proxy for other variables, the other variables should also be studied. Thus issues involving proxy variables, as well as moderators and mediators, should be examined in order to explain race effects.

Implications for Clinical Practice The dilemmas of using race in research are similar to those encountered in clinical, counseling, and professional practice because clinicians’ definitions and assumptions about race influence diagnostics and clinical treatment plans. For example, how do clinician and client racial identities affect their assumptions about race? How do clients’ and clinicians’ racialized life experiences affect the therapeutic setting and working alliance? How does a clinician compare treatment efficacy that is found to be effective for one racial group with another group? Because treatment outcome disparities have been found for clients from various racial groups, guidelines have been established by the American Psychological AsJanuary 2005 ● American Psychologist

sociation (2002) to address how clients should be considered within their racial and cultural context and how culturally competent skills should be acquired by clinicians. In particular, the guidelines raise the following important issues pertinent in our discussion of professional practice and race: 1. Clinicians usually infer a client’s racial group membership on the basis of their personal judgment of the client’s physical appearance or by the client’s self-report. Of critical importance is the clinician’s ability to evaluate the client’s psychological and pragmatic experiences of being a member of a racial group. Just as researchers should understand the meaning of race in research studies, clinicians should understand what race means for their clients. 2. Understanding the meanings of race is critical for clinicians. Instead of solely placing race as belonging to their clients, clinicians must also be self-reflective of how their own racialized experiences have influenced their attitudes and behaviors toward similar and different racial groups compared with their own. 3. Although most clinicians are unlikely to consider overt client behaviors, attitudes, and values as genetically or biologically determined, their dependence on cultural issues as explaining behaviors may pose specific difficulties. On the one hand, some clinicians may be prone to overgeneralizations, racial mythology, and stereotyping because they overemphasize cultural influences at the expense of within-group heterogeneity (e.g., Asians are nonverbal and avoid eye contact). On the other hand, other clinicians may decontextualize their clients by deemphasizing race and culture as relevant by treating them as generic humans or individuals in diagnostics and treatment planning. Thus, the task for clinicians is to appreciate the importance of race and culture and to determine how racial and cultural factors operate and influence the treatment context and their clients’ mental health. 4. In the mental health treatment context, it is important to examine social, political, and racial group status. Culture refers to the behavior patterns, symbols, institutions, attitudes, values, and human products of a group or society. Minority group status is a person’s or group’s position or power status. For example, racially identified minority groups such as people of African descent may have cultural behavioral patterns that reflect not only their culture but also a social and political reaction to a history of prejudice and discrimination. Thus, clinicians must be informed of their clients’ and own overt and covert cultural, social, and political histories that may augment or jeopardize therapeutic alliances especially in treatment interactions. 5. In research as well as when applied in clinical settings, race when used as a demographic variable is often used as a proxy for presumed cultural or minority group experiences. Clinicians will need to distinguish and more precisely understand racial, cultural group experiences of clients. 6. Clinicians should be aware that research on the effectiveness of treatments has been primarily conducted January 2005 ● American Psychologist

on U.S. middle-class people of European ancestry. Although the treatments may well be effective with different populations, until research clearly demonstrates their effectiveness with different populations, clinicians should apply these interventions judiciously.

Final Thoughts How we define and discuss race has major biomedical, psychosocial, and public health implications. Genetic, social, and cultural interpretations of population and social histories can be used in ways that intentionally or unintentionally lead to genetic discrimination, stigmatization, and missed or delayed diagnoses. To these ends, how social, behavioral, and genetic scientists and health service providers understand how racism and race are used in research and practice continues to be investigated (Clark, Anderson, Clark, & Williams, 1999; Krieger, Sidney, & Coakley, 1998; Mays, Ponce, Washington, & Cochran, 2003; U.S. Department of Health and Human Services, 2001a, 2001b). Overall, geneticists and social and behavioral scientists and clinicians must recognize how their own unclear use of race creates havoc for scientific, clinical, and health policy enterprises. For example, identifying groups as possessing unsubstantiated genetic, biological, social, or behavioral characteristics can encourage erroneous assumptions and stereotyping with pseudobiopsychosocial precision. We must take responsibility for not perpetuating ethnocentric assumptions clothed as scientific questions (Gould, 1981). For psychologists, covertly accepting a de facto biological imperative about race in research designs, data analyses, and clinical applications and using race as a proxy for other variables may continue to distract research and clinical efforts away from relevant variables that may be pivotal in understanding people within their social, cultural, genetic, and environmental contexts. Adequate consideration of psychological, social, cultural, and political variables is critical for the successful integration of social, behavioral, and genetic information for research and practice. At some level, the current state of genetic research allows the study of diseases in enough detail to move beyond the nature–nurture debate. It is now clearer how DNA is both inherited and environmentally responsive. In many ways, a person’s attitudes and behaviors orchestrate the interplay between inherited and environmental changes on the genome. One way geneticists and social and behavioral scientists can begin collaborating is to develop interdisciplinary approaches to the study of race and health. For instance, the National Institutes of Health’s roadmap initiatives for research are examples of removing barriers to interdisciplinary research by encouraging collaborations in the development and implementation of long- and shortterm training programs and curriculum development that support interdisciplinary research training for investigators at all career levels. These efforts include exploratory centers for interdisciplinary research; training for a new interdisciplinary research workforce; supplements for methodological innovations in the behavioral and social sciences; interdisciplinary 43

health research training in behavior, environment, and biology; and curriculum and methodological development in interdisciplinary research (see http://nihroadmap.nih.gov/). Forty years ago, Snow (1964) described an abyss between the natural sciences and humanities (and social and behavioral sciences) as two cultures and bemoaned the inability of members of either to communicate effectively with one another. He also suggested that molecular biology could be the bridge between the two cultures because “this branch of science is likely to affect the way in which men [and women] think of themselves more profoundly than any scientific advance since Darwin’s—and probably more so than Darwin” (p. 74). What Snow may not have envisioned was the extent to which genetics would provide tools to help address questions posed by social and behavioral scientists. To this end, we hope that more social and behavioral scientists will take up the challenge and investigate the relationships among genes, populations, and behavior. Genetic differences exist among individuals, and small differences can have large effects on phenotypes and disease risk. Additionally, populations differ in the frequencies of many variants, and these can interact with environmental variables to contribute to differences in disease prevalence. Until population (and race) variables are more methodologically robust and used more consistently, social, behavioral, and genetic research will be limited in answering questions related to biological and psychological differences, treatment efficiency, diagnostic bias, and service delivery. Regardless of whether scientists believe race is real or just skin deep, race is personally, socially, and politically important to millions of people who have nothing to do with our scientific enterprise. Thus, perhaps the biggest challenge for understanding genetics and race for psychologists will be to disentangle not just the correlations of race with genetic variation and environmental exposures but adding the psychological and social factors to understand the complexity of health and disease processes. If improved health is the objective, efforts should be placed where the problems really lie. REFERENCES American Psychological Association. (2002). Guidelines on multicultural education, training, research, practice, and organizational change for psychologists. Washington, DC: Author. Arnason, E., Sigurgislason, H., & Benedikz, E. (2000). Genetic homogeneity of Icelanders: Fact or fiction? Nature Genetics, 25, 373–374. Bamshad, M., Wooding, S., Salisbury, B. A., & Stephens, J. C. (2004). Deconstructing the relationship between genetics and race. Nature Reviews Genetics, 5, 598 – 609. Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182. Betancourt, H., & Lo´pez, S. R. (1993). The study of culture, ethnicity, and race in American psychology. American Psychologist, 48, 629 – 637. Beutler, L. E., Brown, M. T., Crothers, L., Booker, K., & Seabrook, M. K. (1996). The dilemma of factitious demographic distinctions in psychological research. Journal of Counseling and Clinical Psychology, 64, 892–902.

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