558 Cultural Aspects of Health Psychology
services such as hormone therapy (Marks & Shinberg, 1998),
but not informal care (Tennstedt & Chang, 1998). Research
does suggest, however, that the relative lack of services for
some persons of low SES may be in”uenced by the assertive-
ness of the patient (Krupat et al., 1999).
FUTURE RESEARCH DIRECTIONS
With changes in the racial/ethnic composition of the United
States, trends in health technology, and a greater appreciation
for the need to study health in women, ethnic minorities, and
economically underserved populations, there are an endless
number of directions for future research. In summary, emerg-
ing areas of research on the relationship and impact of
race/ethnicity, gender, and SES on health, disease, and health
behaviors require a systems perspective for continued
advancements in the “eld.
Investigations that explore mechanisms linking SES and
health could bene“t from addressing questions such as: What
is the relationship between SES, psychosocial factors, and
health outcomes? Is SES a social hierarchy that will inher-
ently have toxic biopsychosocial effects? How are SES and
allostatic load related? Research is needed to elucidate the
relationship between SES and psychological traits/responses
and coping resources. Laboratory and ambulatory monitoring
studies would be instrumental in identifying the physio-
logical (e.g., cardiovascular, immune, and adrenocortical)
responses associated with perceptions of chronic interper-
sonal and environmental stressors, between and within SES
groups. In addition, cross-cultural studies are needed to
delineate biological, psychological, behavioral, and social
correlates of health among persons in societies with varying
degrees of social and economic orderings. We also suggest
examining the effect health promotion programs have on mit-
igating the relationship between SES and health outcomes
and processes to further our understanding of how to over-
come the impact of economic variability on health.
Considerations in the Study of Ethnicity, SES,
Gender, and Health
Much of the research on ethnicity, SES, gender, and health
involves statistical analyses that compare group means. One
central assumption in these types of analyses is homogeneity
of variance. Meeting this assumption may be very dif“cult in
cross-cultural comparisons of health indices across ethnic
groups. Ethnic minorities possess unique attributes by virtue
of their language, lifestyle, socioeconomic status, and histor-
ical experiences. These attributes create different degrees of
variability within groups that may violate assumptions of
homogeneity of variance.
If assumptions of homogeneity of variance can be met, the
misinterpretation of cross-cultural data on health and health
behaviors is another potential dif“culty and concern for re-
search on ethnicity. Cauce, Coronado, and Watson (1998)
describe three models typically used in conceptualizing
and interpreting results from cross-cultural research, which
exemplify this issue. 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. The Cul-
tural Equivalence Model is an improvement over the
Cultural Deviance Model in that it proposes that superior
socioeconomic status (SES) provides advantages, which
create superior performance. The Cultural Deviance Model
attributes advantages or superior performance to culture.
Putting the onus on culture blames a group for not having
the same ideals, resources, attitudes, and beliefs as the ma-
jority culture. Placing culpability on SES shifts the respon-
sibility to social structures that are inherently unbalanced in
their distribution of resources. The Cultural Variant Model
describes differences as adaptations to external forces,
exemplifying resilience in the face of oppression. Differ-
ences are explained not in relation to a majority/superior
group but as culturally rooted internal explanations. The
third model by de“nition allows an appreciation for
between-group differences, and challenges us to explore
within-group heterogeneity.
Including race as a between-subject variable assesses the
variability due to the categorization of subjects by race. How-
ever, it does not assess the possible dynamic effect of ethnic-
ity on the variables in the model being tested. Race implies
only a biological differentiation while ignoring other possible
sources of variability in cross-cultural comparisons, such as
lifestyle, beliefs about aging, language, and historical experi-
ences. Race then is not an adequate proxy for the synergistic
effects present in studies designed to address ethnic diversity.
To this end, an important point in developing research ques-
tions is that factors that account for between-group variabil-
ity do not necessarily account for within-group variability
(Whit“eld & Baker -Thomas, 1999). One strategy for over-
coming the performance bias in comparisons of different cul-
tural groups is to study each group as its own heterogenous
populationfirstand investigate the appropriateness of the
measure and its items for each population under study. Then
examine the mean and, perhaps more importantly, variances
and error variances between groups. Another approach is to
use an acculturation measure as a covariate in between-group