The predicted explosion in the demographic shift toward more ethnic minorities representing a greater proportion of our nation (Angel & Angel, 2006
) has made the science of studying race and ethnicity a priority for the scholarly community. The National Institutes of Health (NIH) have made several recent revisions to their guidelines for human subject treatment (NIH, 2001
). One of the central points of change in policy is the strong statements and rules about the inclusion of minorities in federally funded research projects. Some scientists believe that this change is for social or political reasons and has no grounding in basic science. Others argue that if we are to adequately and thoroughly test hypotheses and provide answers to questions about America's diverse elders, we must formulate answers based on quality data that reflect the heterogeneity of our population (Curry & Jackson, 2003
These NIH guidelines are clearly increasing the amount of research that includes ethnic groups other than Caucasians. However, often the results from these studies are not thoroughly discussed relative to race, or only the main effect of race is presented, seldom exploring possible interactions between race and other variables (e.g., health, socioeconomic status, and personality). From these accounts, race is included as a variable to establish or control for between-group differences and not as a central factor of importance. Should every study have as its central question the issue of race? Of course not. When it is important, however, race is frequently conceptualized as Caucasians and others, differences are not well interpreted, and the research is insufficiently powered to detect differences because of small minority samples.
In this article, we argue that comparison studies, however necessary to establish inequities, are not sufficient to advance the science of diversity. Our goal in this article is to facilitate a discussion on how to advance research on psychological aspects of minority aging by presenting benefits and drawbacks of between-group comparisons and within-group examinations.
Comparison or control groups are necessary to test the effectiveness of interventions and therapeutics; however, when the comparison is between racial groups, the traditional concept of a comparison group, such as a placebo or standard of care control, does not necessarily apply. Often Caucasians are used as the comparison or control group necessary to decipher the importance of the findings from research on an ethnic minority group. Caucasians have traditionally been considered as the “control group” by which an understanding of minorities is gained from observing differences. There are some inherent difficulties with this perspective. First, there is a long history of research that does not include ethnic groups other than Caucasians. The validity of that research is seldom questioned in relation to the generalizability to the population but the validity of the reverse, research focused on a minority groups, is often examined. Second, Caucasians are sometimes thought to be needed in an analysis of ethnic minorities to assess differences. There is an assumption of differences, but different from what? The assumption seems to be that Caucasians represent some sort of standard from which ethnic minorities deviate. Finally, group-difference studies sometimes assume that the same underlying processes produce the outcome of interest. However, the process might be different and therefore leads to a difference in outcomes. For example, African American and Caucasian women have been found to face similar caregiving situations, but African American women report less burden than Caucasian women do (Martin, 2000
). These kinds of conceptualizations about racial-differences research have been discussed by Cauce, Coronado, and Watson (1998)
. They described three models typically used in thinking about and interpreting results from cross-cultural research, which exemplify the issue of misinterpretation. These models are the (a) Cultural Deviance Model, (b) Cultural Equivalence Model, and (c) Cultural Variant Model.
The Cultural Deviant Model characterizes differences or deviations between groups as deviant and inferior. An example might involve racial-group differences in cognitive aging. An interpretation using this model might suggest, for example, that African Americans do more poorly on cognitive tests because they lack the ability to do the tests. The Cultural Equivalence Model is an improvement over the Cultural Deviance Model in that it proposes that superior socioeconomic status (SES) provides advantages that create superior performance. With the use of the Cultural Equivalence Model, differences in performance on cognitive aging would be described differently. An interpretation of differences in cognitive performance using the Cultural Equivalence Model might suggest that the lack of opportunities to obtain equal education as a result of segregation hampered educational opportunities and achievement, which may account for a large portion of the differences between African Americans and Caucasians on tests of cognitive performance.
The Cultural Deviance Model attributes advantages or superior performance to culture. Putting the onus on culture blames a social group for not having the same ideals, resources, attitudes, and beliefs as the majority culture. Placing culpability on SES shifts the responsibility to social structures that are inherently unbalanced in their distribution of resources. In contrast, the Cultural Variant Model describes differences as adaptations to external forces, exemplifying resilience in the face of oppression. Differences are explained not in relation to a majority or superior group but as culturally rooted internal explanations. The third model by definition allows an appreciation for between-group differences, and it challenges one to explore within-group heterogeneity. Using our example of cognitive aging, an interpretation of the performance differences between African Americans and Caucasians might include a discussion about how culture-fair stimuli were not used, how African Americans may be different because they have a different knowledge base, how among earlier cohorts the expectation was to leave the educational system early to financially support their family, or the fact that aging African Americans tended to live in rural areas where education was more optional than mandatory (Whitfield, 1996
; Whitfield & Willis, 1998
; Whitfield et al., 1997
As knowledge about ethnic minorities grows, so has the use of Cultural Variant Models to explain differences found between groups. The Cultural Variant Model is important not only for the design and interpretation of research but also for the translation of research. The presentation of findings in a manner that accurately depicts ethnic minority elders will be more informative for and received better by older minorities. At some level, minority elders know about the phenomena we study and make their own interpretations. It is doubtful that they compare their functioning to that of their aging Caucasian counterparts. Furthermore, given the current and expected growth of ethnic minority groups in the United States such as the predictions for the Hispanic population, the concept of majority–minority comparisons has to be reconsidered because groups who are minorities now will not be in the near future (Angel & Angel, 2006
Comparisons between two different minority groups may enlighten science and reduce bias by evaluating groups that share similar traits and examining whether the outcomes are different. For example, if we were interested in racial ethnic disparities in the impact of subjugation on subsequent generations' mental health, we might choose to study African Americans and Native Americans. These two groups share several similar features or characteristics, including a loss of familial solidarity, similar educational constraints, and patterns of early mortality.
Currently, most of the research on ethnicity, race, culture, and aging is designed to examine between-group differences in constructs known to be associated with age (Jackson, Antonucci, & Gibson, 1990
). Recent areas of research have focused on these distinguishable qualities by addressing the significant differences that are present between ethnic groups. This conceptual or methodological approach has generated a considerable body of literature in the area of racially comparative research on elders. Contemporary researchers contend that these cross-ethnic comparisons have several limitations (Markides, Liang, & Jackson, 1990
; Whitfield & Baker, 1999
). One limitation in most applications of comparative designed research is that it does not provide insight into the degree of within-group variability. For example, a Hispanic subgroup might include Mexican Americans, Latin Americans, and Puerto Ricans. Each of these cultural subgroups reflects some unique and varying historical culture and levels of assimilation. Inherently, these individual groups are different; by collapsing the groups under one “ethnic umbrella” and then comparing them with Caucasians, important distinctions within each group are lost. These lost distinctions may be very important for interpreting differences across various cultural groups (Whitbourne, Bringle, Yee, Chiriboga, & Whitfield, 2005
One of the challenges often posed in the study of ethnic groups is the identification of unique or new constructs. John Henryism, for example, is thought to be a behavioral construct that is highly salient, reflecting the personal struggles of African Americans (c.f. James, Hartnett, & Kalsbeek, 1983
). Although this unique and interesting behavioral measure has validity for understanding the increased risk for poor health, particularly cardiovascular disease, relative to SES (James, Keenan, Strogatz, Browning, & Garrett, 1992
; James, Strogatz, Wing, & Ramsey, 1987
), there are relatively few measures that are designed on the basis of a concept that is thought to reflect cultural values and issues more prevalent in African Americans. Identifying new or unique measures or concepts may not be as necessary as grasping how behavioral processes within minority groups make them different or unique in comparisons with Caucasians.
In addition to these limitations, there may be analytic problems to making comparisons. There are three potential problems, issues, or challenges to making comparisons between groups that are often overlooked. The first is differences in sample size. It is not uncommon to observe samples that consist of four to five times as many Caucasians as minorities. The second potential analytic problem involves measurement error (e.g., Ramirez, Ford, Stewart, & Teresi, 2005
; Ramirez, Teresi, Holmes, Gurland, & Lantigua, 2006
; Teresi & Holmes, 2002
). The typical observation that there are mean differences in group performance suggests that there may also be differences in measurement error across the groups. This is likely in racial-group comparisons, given the potential differences that arise from dissimilarities in language, history, socialization, and other psychosocial factors.
The third is a basic premise of the analysis of group differences by the use of analysis of variance (ANOVA). One of the assumptions is that there is homogeneity between the two groups. This proposition states that the variance observed in one group must be equal or relative to the group being compared. Studies seldom report tests of homogeneity of variance, and with large sample sizes the violations are usually ignored.