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A cultural research approach to instrument development:
the case of breast and cervical cancer screening among
Latino and Anglo women
Hector Betancourt
1,2
*, Patricia M. Flynn
1
, Matt Riggs
3
and Carlos Garberoglio
4
1
Department of Psychology, Loma Linda University, Loma Linda, CA 92354, USA,
2
Department of Psychology, Universidad de
La Frontera, Temuco, Chile,
3
Department of Psychology, California State University, San Bernardino, CA 92407, USA
and
4
Department of General and Oncologic Surgery, City of Hope National Medical Center, Duarte, CA 91010, USA
*Correspondence to: H. Betancourt. E-mail: hbetancourt@llu.edu
Received on October 13, 2009; accepted on August 13, 2010
Abstract
To illustrate the implementation of a bottom-up
approach to the study of culture in health dis-
parities, this article describes the development
of a cultural cancer screening scale (CCSS) us-
ing mixed methodologies. The aim was to iden-
tify cultural factors relevant to breast and
cervical cancer screening, develop an instru-
ment to assess them and examine its prelimi-
nary psychometric properties among Latin
American (Latino) and non-Latino White (Anglo)
women in Southern California. Seventy-eight
Latino and Anglo women participated in semi-
structured interviews, which were content
coded based on Triandis’ methods for the anal-
ysis of subjective culture. Based on the emerging
cultural elements, items relevant to cancer
screening were developed and pilot tested with
161 participants. After the instrument was re-
fined, 314 Latino and Anglo women from vari-
ous socioeconomic backgrounds completed the
CCSS and data were factor analyzed resulting
in five cultural factors: cancer screening fatal-
ism, negative beliefs about health professionals,
catastrophic disease expectations, symptomatic
deterrents and sociocultural deterrents. The in-
strument demonstrated measurement equiva-
lence, adequate reliability and predictive
validity. The research and the CCSS are dis-
cussed in terms of implications for the study of
culture in relation to health disparities and the
development of evidence-based interventions
with culturally diverse populations and their
health professionals.
Introduction
Research evidence suggests that increasing cancer
screening behaviors significantly improves cancer
outcomes and lowers mortality rates [1]. Although
cancer screening rates in the United States have
improved over the past decade, rates for minority
populations have improved to a much lesser degree
as compared with the Anglo population. For in-
stance, according to data from 1992, rates of mam-
mography (MAM) screening for Anglo and Latino
women in the United States were 58 and 55%, re-
spectively. In 2005, the rates were ;68% for Anglo
and 59% for Latino women [2]. These findings rep-
resent a 3-fold increase in the screening disparity
between the two ethnic groups (from 3 to 9 percent-
age points) in just over a decade. Although screen-
ing rates for cervical cancer are higher than for
breast cancer, compared with Anglo American
(79%) and African American women (80%), Latino
American women (74%) are the least likely to have
had a recent Pap test (Pap).
Research has identified a number of factors as-
sociated with ethnic disparities in breast and cervi-
cal cancer screening. These include income, health
HEALTH EDUCATION RESEARCH Vol.25 no.6 2010
Pages 991–1007
Advance Access publication 23 September 2010
ÓThe Author 2010. Published by Oxford University Press. All rights reserved.
For permissions, please email: journals.permissions@oxfordjournals.org
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insurance status, English proficiency [3], access to
transportation [4], education [5], social support [6,
7], acculturation [5, 8] and health care discrimina-
tion [9]. These and related findings suggest that
health disparities may be in part a function of cul-
tural differences between the health care professio-
nals and the culturally diverse patients they serve
[10, 11]. This is particularly important as the US
population is becoming increasingly diverse while
our health care system, policies and interventions
remain predominantly based on traditional Anglo
American cultural assumptions [12].
If cultural differences play a role in cancer
screening behavior, the cultural elements relevant
to screening need to be identified, properly mea-
sured and their role in cancer screening should be
tested in a culturally diverse population [10–11].
Once psychometrically appropriate instruments
have been developed, the cultural variables relevant
to cancer screening can be assessed among women
from the community targeted for intervention.
Then, the obtained cultural data can inform evi-
dence-based targeted or tailored interventions with
individuals from that community. Such interven-
tions are likely to be more effective at increasing
cancer screening behaviors than interventions based
on stereotypical or more general views of ethnic or
socioeconomic groups. This is particularly likely to
be the case as these groups are increasingly heteroge-
neous in terms of sources of cultural variation such as
country or region of origin, generation status, educa-
tion, income, acculturation and intercultural contact.
The purpose of this article was to illustrate the
implementation of a bottom-up approach to the de-
velopment of cultural instruments. The correspond-
ing aims of the research were 3-fold: (i) to identify
cultural factors relevant to breast and cervical can-
cer screening among Latino as compared with An-
glo women in Southern California, (ii) to develop
an instrument relevant to both Latino and Anglo
women to assess these cultural factors and (iii) to
perform a preliminary test of the psychometric
properties of the newly developed cultural instru-
ment. The research was guided by Betancourt’s
theoretical model for the study of culture in
psychology [11, 13, 14], which has been recently
applied to the study of health behavior in culturally
diverse populations [10].
The study of culture and health behavior
One of the problems observed in the health sciences
literature is the lack of clarity concerning the defi-
nition of culture. In fact, culture has been defined in
many different ways, depending on the focus and
conceptual orientation of the author. For instance,
Rohner [15] has provided a socially based defini-
tion of culture as a learned system of meanings that
is shared by a people or an identifiable segment of
the population. Others [16, 17] have defined culture
as the human-made part of the environment that
includes both objective and subjective components.
Objective culture refers to elements such as roads,
bridges, tools and technology whereas subjective
culture refers to norms, roles, beliefs, values and
practices. These elements of subjective culture are
the basis of how a number of cultural psychologists
and health science researchers conceptualize culture
as they are more directly related to psychological
processes and behavior [see 13,18–20]. In fact,
medical anthropologists Hruschka and Hadley [20]
argue that whenculture is defined in terms of socially
learned norms, values and behaviors, it is possible to
empirically investigate its influence on health.
From a health sciences perspective, culture
should be conceptualized in terms that are relevant
to health phenomena. Consistent with this, culture
is defined here in terms of elements such as socially
shared values, beliefs, norms, expectations and
practices that are relevant to health behavior and
outcome [10]. According to this definition, which
is consistent with the model guiding this research,
aspects of culture are likely to be shared among
individuals of an ethnic, racial, socioeconomic sta-
tus (SES) or gender group. However, such popula-
tion categories are conceived to be clearly different
from culture. For instance, race is generally defined
in terms of physical characteristics such as skin
color, facial features or hair type [13]. However,
these classifications are arbitrary and have been
considered problematic and of little relevance to
the study of behavior [13, 21–23]. Ethnicity, on
the other hand, is usually defined in terms of a
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common history, nationality, language and culture
[13]. Hence, as observed in Fig. 1, ethnicity, race,
SES or religion and other population categories
are sources of cultural variation, which relate to
health behavior through culture and psychological
processes.
Qualitative studies with Latinos have already iden-
tified a number of cultural factors relevant to cancer
screening. For instance, Chavez et al. [24] have iden-
tified fatalistic beliefs. Other researchers [25] have
identified the belief that if nothing is wrong, there is
no need to screen, and still others [26] have identified
beliefs regarding health care professionals as deter-
rents to cancer screening. These studies represent an
important step forward in working with culturally
diverse populations. In fact, recent research has de-
veloped instruments to assess some of these cultural
beliefs relevant to breast cancer screening among
Latino women [27]. From a health disparities per-
spective, research and intervention would greatly
benefit from the development of additional cultural
instruments designed to assess these aspects of cul-
ture relevant to both mainstream (e.g. Anglo) and
minority (e.g. Latino) populations. Once instruments
are developed for both populations, hypotheses can
be tested and evidence-based interventions can be
developed to address disparities in breast and cervi-
cal cancer screening.
Cultural instruments, such as the one reported
here, are expected to be useful for testing the rela-
tions among specific cultural factors and other var-
iables included in the model guiding the research.
For example, if research with Latino women iden-
tifies cancer fatalism as a cultural factor relevant to
breast cancer screening, a cultural instrument could
then be developed and used to test the influence of
From distal... to more proximal determinants of behavior
Population Cultural Psychological Health
Categories Factors Processes Behavior
A B C D
Professionals’
Race, Ethnicity,
Gender, SES, and
Religion
---------------
Patients’
Race, Ethnicity,
Gender, SES, and
Religion
Professionals’
Socially Shared
Values, Beliefs,
and Expectations
about Patients
and Health-Care
Practices
--------------
Patients’
Socially Shared
Values, Beliefs,
and Expectations
Relevant to
Health Behaviors
and Interactions
with the Health-
Care System
Professionals’
Motivation and
Emotions Relevant
to Health-Care
Practices and
Interactions with
Patients
-----------
Patients’
Motivation and
Emotions Relevant
to Health Behaviors
and Interactions
with the Health-
Care System
Professionals’
Health-Care Practices
and Interactions with
Patients
----------------
Patients’
Health Behaviors and
Interactions with the
Health-Care System
Fig. 1. Betancourt’s model of culture, psychological processes and behavior adapted for the study of health behavior [10].
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cancer fatalism (column B of Fig. 1) on cancer
screening (column D), directly and/or indirectly
through psychological processes (column C). The
cultural instrument could also be used to examine
which population categories (e.g. ethnicity or SES
in column A) exert a greater influence as a source of
variation in cancer fatalism (column B) or whether
the influence of cancer fatalism is the same for indi-
viduals of different SES or ethnic groups. Such
a cultural instrument could be particularly useful
in the development of intervention programs ‘tar-
geted’ for a specific culturally diverse community
or ‘tailored’ to individuals of that community [28].
Still, when such measures are used to assess cultural
factors among individuals of different ethnic or
cultural backgrounds, it is crucial that measure-
ment equivalence is established [29]. This is impor-
tant to ensure that instruments measure the same
underlying factors for each cultural group [29, 30].
The development of the cultural cancer
screening scale
Triandis’ methods for the study of subjective cul-
ture [31] and Betancourt’s model and bottom-up
approach for the study of culture [10, 11, 14] guided
all phases of the mixed methods research. The bot-
tom-up approach begins with specific observations
relevant to an area of research (e.g. cancer screen-
ing), which are derived from the population(s) of
interest (e.g. ethnic or SES group) [10]. This ap-
proach evolves from observations to the develop-
ment of instruments, to testing hypotheses
employing the newly developed cultural instru-
ment. To this end, mixed methodologies are used
to implement the bottom-up approach.
An advantage of the bottom-up approach is that
aspects of culture specifically relevant to cancer
screening can be identified directly from the individ-
uals, rather than based on stereotypical views that
may ignore within-group differences [10]. An addi-
tional advantage of this approach is that the resulting
instrument developed for use with minority (e.g. La-
tino) and mainstream (e.g. Anglo) populations are
more likely to demonstrate measurement equiva-
lence. Often times, instruments intended for Anglo
American populations are simply translated for other
ethnic groups without establishing measurement
equivalence. Such research fails to ensure that instru-
ments measure the same underlying factors for each
cultural group prior to testing hypotheses concerning
cultural differences [29, 30].
In Phase I, open-ended, semi-structured inter-
views were conducted with Latino and Anglo
women to identify cultural factors associated with
breast and cervical cancer screening. In Phase II,
close-ended items were developed based on the
emerging cultural elements identified in Phase I.
Then, an instrument was compiled with these items,
which was pilot tested with a sample of Latino and
Anglo women and further refined. In Phase III,
the instrument underwent preliminary psychometric
testing with a larger sample to examine the structure,
reliability, predictive validity and measurement equiv-
alence of the cultural cancer screening scale (CCSS).
Phase I: identification of cultural
elements
Sampling procedures
Standard procedures for the study of culture as de-
fined by Triandis et al. [31] involves the inclusion
of a comparison group in order to identify elements
of culture that are unique to a particular group
(Latino), those that are unique to the mainstream
(Anglo) group or those that are common to all par-
ticipants. In accordance with these procedures,
monolingual English and English–Spanish bilin-
gual experimenters interviewed 78 self-identified
Latino and Anglo American women.
According to the model for the study of culture,
psychological processes and health behavior (see
Fig. 1), population categories such as ethnicity,
education and income transmit culture and are
sources of cultural variation. From this perspective,
sampling procedures associated with the bottom-up
approach must recognize the critical importance of
recruiting individuals from various demographic
backgrounds. Since the interview responses are
expected to provide the basis for the cultural
elements represented in the cultural instrument,
failing to interview individuals from various
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demographic backgrounds will result in a limited
perspective concerning the most relevant cultural
elements associated with cancer screening.
In accordance with this perspective, multi-stage,
stratified sampling was conducted in order to obtain
nearly equal proportions of Latino and Anglo women
of varying demographic characteristics. To ensurede-
mographic diversity, participants were recruited from
various settings including markets, churches, univer-
sities, free-/low-cost health clinics, mobile home
parks and community settings. Using US Census
tract data from the Federal Financial Institutions Ex-
amination Council, projections regarding ethnicity,
SES and age were anticipated for each recruitment
setting prior to data collection. Once data were col-
lected from a number of sites, the distribution of
participants across demographic criteria was exam-
ined. Based on these analyses, efforts were made to
recruit participants that would provide nearly equal
proportions of individuals within the different strata.
Development of interview schedule
A semi-structured interview schedule was devel-
oped based on Triandis’ methods for the study of
subjective culture, in a manner similar to applica-
tions to health behavior [32]. In accordance with the
definition of culture outlined in the model (see
Fig. 1), open-ended questions were developed to
obtain information concerning cultural aspects such
as socially shared beliefs, norms and expectations
concerning breast and cervical cancer screening
behaviors, including their antecedents and conse-
quences. An example of a question designed to
identify socially shared beliefs regarding the causes
for cancer screening included, ‘Why do you think
some women choose to have a mammogram?’ A
sample question designed to identify socially shared
expectations included, ‘What do you think happens
to women who do not have regular Pap tests?’
Identification of cultural elements
One of the key components of the bottom-up ap-
proach is that observations are made directly from
the population of interest. This approach provides
valuable contextual and linguistic information that
can be used for the development of items relevant to
the emerging cultural elements and is more likely to
produce psychometrically sound instruments that
ensure measurement equivalence [33]. To this
end, all interviews were transcribed and coded in
their original language by a group of monolingual
English and bilingual Spanish–English-speaking
judges using standard content analysis procedures.
Frequency distributions were calculated for La-
tino and Anglo women separately based on the
identified cultural elements. Results revealed dis-
tinct cultural elements relevant to breast and cervi-
cal cancer screening. These included socially
shared beliefs about cancer in general, symptoms,
systematic barriers to screening, fatalistic avoid-
ance and beliefs relevant to health care professio-
nals who perform screening examinations. Some of
the cultural aspects were reported as relevant by
Latino women but were not reported by Anglo
women (e.g. Latino-specific cultural belief). At the
same time, some elements were identified as cultur-
ally specific to Anglo women (e.g. Anglo-specific
cultural belief), whereas others were shared by both
ethnic groups (e.g. ethnic-general cultural belief).
Phase II: item development and pilot
test of cultural elements emerging from
Phase I
Item development and translation
Based on the most frequently reported ethnic-specific
and ethnic-general cultural themes that emerged from
the content analysis of the Phase I interviews, dichot-
omous and 7-point Likert Scale items were devel-
oped to assess these cultural aspects in relation to
clinical breast examinations (CBE), MAM and Pap.
To ensure scale equivalence, the items were con-
structed in the language of the interview from which
it emerged in Phase I. In fact, many of the items were
developed using the exact terminology and language
that women used during their interviews.
Since most of the cultural elements identified in
Phase I were relevant to both breast and cervical
cancer screening, 60 similarly worded items were
developed for the breast and cervical cancer sec-
tions of the instrument, respectively. Items were
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then translated into the other language by a group
of bilingual Spanish–English-speaking experts
through the double back-translation procedure to
eliminate parochial wording [33, 34]. The transla-
tion process occurred side by side to compare the
English and Spanish versions for appropriateness
and equivalence. Although efforts were made to pre-
serve participants’ language, a decentering process
was also employed, which views both languages as
equally important and equally open to modification
[35]. A final blind back-translation process was also
employed in which a translator not familiar with the
original version of the instrument translated it back
into the original language [36].
Instrument administration and refinement
A total of 161 Latino and Anglo women were
administered the pilot version of the CCSS in
a group setting by monolingual English and bilin-
gual English–Spanish-speaking research assistants.
When participants were finished, they met one-on-
one with a research assistant to provide feedback
concerning the instrument. Based on participants’
feedback and preliminary statistical analyses, 22
items were eliminated. The remaining items were
factor analyzed revealing a number of similar
factors relevant to both breast and cervical cancer
screening. Internal consistency was adequate and
several factors were correlated with breast and
cervical cancer screening behaviors.
Prior to testing the CCSS with a larger sample in
Phase III, some items were further refined for proper
language and dichotomous items were transformed
into 7-point Likert scale items to be consistent with
the response format for the overall instrument. As
a result, each section of the instrument was reduced
to 38 items representing the cultural elements
identified through the bottom-up approach.
Phase III: preliminary psychometric
validation
Methods
Two propositions were tested in Phase III using the
CCSS: (i) Latino and Anglo women were expected
to score differently on the emerging cultural factors.
(ii) The CCSS was expected to demonstrate
predictive validity with breast and cervical cancer
screening behaviors and related psychological
processes such as screening emotions.
Participants
As in Phases I and II, multi-stage, stratified sam-
pling was conducted to obtain nearly equal propor-
tions of participants from varying demographic
characteristics (e.g. ethnicity, SES, age). Based on
the recommendation that the number of participants
for factor analysis should be five times the number
of variables [37, 38], the sample of 314 participants
(167 Latino, 147 Anglo) is considered sufficient.
All women were 21 years of age and older who
had never been diagnosed with breast or cervical
cancer. Of these participants, 158 (84 Latino, 74
Anglo) were administered the breast cancer version
of the instrument while 156 (83 Latino, 73 Anglo)
responded to the cervical cancer version (see
Table I).
Measures
A questionnaire was compiled including a refined
version of the CCSS in addition to measures
designed to test the scale’s predictive validity. To
this end, a cancer screening measure was included
to assess past breast and cervical cancer screening
behaviors and intention to screen in the future. Con-
sistent with the conceptual model guiding the re-
search (see Fig. 1), measures of psychological
variables such as emotions associated with cancer
screening were also included to further test the pre-
dictive validity of the CCSS.
Demographics. Items relevant to participants’
age, education, ethnicity, income, marital status,
immigration status and insurance status were
assessed.
Cultural cancer screening scale. Since similar
factors emerged as relevant to both breast and cer-
vical cancer screening in Phase II, the instrument for
this phase included a total of 38 similarly worded
items in each section of the CCSS. The main differ-
ences between the sections of the instrument were
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the wording of items and/or instructions specific to
the type of screening behavior (e.g. MAM, CBE,
Pap). For instance, an item from the factor ‘cata-
strophic disease expectations’ was worded ‘Breast
cancer (cervical cancer) is the worst thing that can
happen to a woman’. Since several items from the
two sections are worded similarly, participants com-
pleted either the breast cancer screening or the cer-
vical cancer screening version of the CCSS to avoid
response bias and fatigue.
Cancer screening behaviors. Participants were
provided an illustration of a woman having
aMAM,CBEorPapfollowedbyabriefdescrip-
tion of the corresponding test. Participants were
then asked the question ‘Have you ever had
a MAM (CBE or Pap, respectively)?’ followed
by ‘If yes, how many have you had in the last five
years?’. A compliance proportion score was com-
puted based on age recommendations for each
screening exam as outlined by the American Can-
cer Society [39]. Using methods similar to those
employed by Kundadjie-Gyamfi and Magai [40],
the screening compliance score for each type of
screening exam was calculated for participants
based on the total number of MAM/CBE/Paps
reported divided by the maximum number of tests
a woman of her age should have if they were fully
compliant with screening guidelines (maximum
compliance = 1.0). To assess intention to screen,
participants were asked ‘In the next year, how
likelyareyoutohaveaMAM(CBE/Pap)?’.Re-
sponse options were based on a 7-point Likert
scale from ‘not at all’ to ‘very likely’.
Screening emotions. During the qualitative phase
of this research, participants were also asked if they
experienced any emotions when they thought about
breast or cervical cancer screening. The content
analysis revealed that fear and anxiety were the pre-
dominant emotions experienced by both Latino and
Anglo women. Therefore, six items were developed
to assess the extent to which participants experi-
enced fear and anxiety in anticipation of having
a MAM, CBE and Pap, respectively. A sample item
includes ‘Thinking about having a mammogram
(CBE, Pap) makes me extremely anxious’. Items
were based on a 7-point Likert scale from ‘strongly
disagree’ to ‘strongly agree’. The following repre-
sent the scale reliabilities, CBE emotions: Latino
a= 0.94, Anglo a= 0.89 and total a= 0.92;
MAM emotions: Latino a= 0.89, Anglo a= 0.89
and total a= 0.90; and Pap emotions: Latino a=
0.84, Anglo a= 0.71 and total a= 0.80.
Procedure
The study was conducted at a university in South-
ern California and Institutional Review Board ap-
proval was granted prior to data collection.
Advertisements were placed at recruitment settings
Table I. Demographics for Phase III sample
Latinos,
n=165
Anglos,
n=149
Total,
n=314
Age (mean)* 41.19 47.98 44.39
Education (mean)* 12.75 14.82 13.73
Income (%)*
0–14 999 21.70 17.60 19.70
15 000–24 999 14.50 10.80 12.70
25 000–39 999 17.50 16.90 17.20
40 000–59 999 13.90 14.90 14.30
>60 000 22.90 39.20 30.60
Missing 9.60 0.70 5.40
Marital status (%)
Single 19.30 15.50 17.50
Married 55.40 54.70 55.10
Cohabitating 4.20 2.00 3.20
Divorced/separated 16.30 17.60 16.90
Widowed 4.20 10.10 7.0
Missing 0.60 0.30
Foreign born (%)* 41.6 4.1
Mexico 85
Puerto Rico 2.9
Central America 7.3
Cuba 0.7
South America 2.2
Other: Latin America 1.5
Europe 2.70
Canada 1.40
Insurance status (%)*
Yes 72.30 89.90 80.60
Missing 6.0 2.70 4.50
Survey language (%)*
English 73.50 100.00 86.0
Spanish 26.50 14.0
*P<0.05.
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indicating a specific time and place where interested
women could go to fill out the questionnaire. At the
time of participation, participants were met by a bi-
lingual research assistant who explained the study.
Participants who met the study inclusion criteria
and were willing to participate were provided with
a written consent form to sign. Participants were
then given an English or Spanish version of the
questionnaire, which took ;30 min to complete.
All participants were given $20 in cash as compen-
sation for their participation.
Results
Preliminary analyses were conducted to determine
if it was appropriate to collapse the two sections
(e.g. breast and cervical cancer) of the CCSS for
psychometric analyses. An examination of the de-
mographic background of the samples revealed that
there were no significant demographic differences,
other than age, which was expected as a result of
efforts to recruit a larger number of women >40
years to complete the breast cancer section. Also,
there were no significant differences in the mean
scores of items from the breast cancer section as
compared with the cervical cancer section. These
results suggest that items from each section of the
instrument functioned similarly. Furthermore, prin-
cipal axis exploratory factor analysis with Oblimin
rotation and Kaiser normalization revealed similar
factors for the breast and cervical cancer sections.
Last, t-tests revealed that the mean score for each
factor from the breast cancer section was not sig-
nificantly different from the mean score on the cor-
responding factor for the cervical cancer section.
Based on results from the analyses reported
above, data from the two sections of the instrument
were collapsed. Hence, all analyses were conducted
using the total sample of 314 women who
responded to one or the other screening section of
the instrument. As a result of multi-staged stratified
sampling, this sample was well-balanced between
Latino (n= 165) and Anglo (n= 149) participants.
Furthermore, Latino and Anglo women were repre-
sented across all levels of income, education and
age, respectively. Still, within the corresponding
strata Latino women were overall younger, of lower
income and education and more likely to be unin-
sured than their Anglo counterparts (see Table I).
Based on the sample of 314 women, principal
axis factor analysis with Oblimin rotation and Kai-
ser normalization was conducted for each ethnic
group separately, as well as for the total sample.
Conceptual meaning in addition to the examination
of scree plots were used to determine the number of
factors for the CCSS. A cutoff of 0.30–0.40 and
conceptual consistency of the item with the factor
were used as guidelines for item inclusion.
Results revealed five distinct cultural factors,
which are reported in Table II. Factor loadings from
the pattern matrix are reported for Latino women,
Anglo women and the total sample. The solution
resulted in a matrix with simple structure, and the
structure was consistent across the two groups. To-
tal variance recaptured by the solution was 65.11%
for the Latino sample, 62.84% for the Anglo sample
and 62.55% for the total sample. The rotated eigen
values (5.63, 2.49, 1.90, 1.61 & 1.40 for Latino;
4.94, 2.66, 1.23, 2.15 & 1.59 for Anglo and 5.21,
2.55, 1.89, 1.46 & 1.40 for the total sample) sug-
gested a good balance of factor influence, consistent
with the number of items in each factor.
Factor names were applied on the basis of item
content. The ‘cancer screening fatalism’ factor rep-
resents the belief that life events are inevitable
thereby rendering cancer screening unnecessary.
‘The negative cultural beliefs about health profes-
sionals’ factor reflects socially shared unfavorable
beliefs about health professionals, including lack of
concern, compassion and trustworthiness. The fac-
tor catastrophic disease expectations points to the
highly negative socially shared expectations asso-
ciated with a cancer diagnosis. Finally, the ‘symp-
tomatic deterrents’ factor reflects socially shared
beliefs that screening is not necessary when feeling
healthy or having negative test results, while the
‘sociocultural deterrents’ factor represents socially
shared beliefs concerning social and structural bar-
riers to cancer screening.
Correlations among the cultural factors and
the total CCSS are reported for both groups in Table
III. As with the factor loadings, the pattern of factor
correlations was similar across the two groups. All
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Table II. Factor loadings for Latinos/Anglos/total
12 3 4 5
Sociocultural deterrents
Having problems making an appointment is a reason for
not screening regularly.
0.84/0.70/0.77 0.004/0.01/0.01 0.002/0.07/0.02 0.07/0.02/0.04 0.09/0.004/0.03
Not knowing where I can be screened for breast/cervical
cancer is a reason for not screening regularly.
0.76/0.58/0.70 0.01/0.23/0.12 0.03/0.05/0.03 0.05/0.04/0.05 0.08/0.01/0.03
Not being able to get time off work is a reason for not
screening regularly.
0.68/0.79/0.74 0.01/0.10/0.05 0.02/0.15/0.01 0.05/0.03/0.02 0.01/0.02/0.02
Not having transportation to get to my appointment is
a reason for not screening regularly.
0.65/0.49/0.60 0.04/0.02/0.04 0.06/0.11/0.06 0.06/0.13/0.01 0.18/0.11/0.05
Not receiving a reminder postcard is a reason for not
screening for breast/cervical cancer regularly.
0.62/0.54/0.59 0.02/0.07/0.02 0.09/0.07/0.11 0.08/0.18/0.10 0.00/0.19/0.05
Having to take care of my child(ren) or family is a reason
for not screening regularly.
0.60/0.54/0.55 0.09/0.02/0.04 0.04/0.22/0.05 0.12/0.07/0.04 0.01/0.12/0.08
Not having health insurance or the money to pay for the
exam is a reason for not screening regularly.
0.51/0.47/0.51 0.16/0.08/0.12 0.10/0.10/0.02 0.12/0.01/0.13 0.02/0.21/0.03
Cancer screening fatalism
It is not important to screen regularly because everyone
will eventually die of something anyway.
0.05/0.07/0.03 0.82/0.70/0.79 0.14/0.01/0.10 0.05/0.09/0.04 0.15/0.004/0.09
It is not necessary to screen for breast/cervical cancer
regularly because it is in God’s hands anyway.
0.10/0.02/0.05 0.67/0.87/0.71 0.18/0.02/0.10 0.00/0.03/0.05 0.12/0.08/0.08
If nothing is physically wrong, then you do not need to
screen.
0.12/0.05/0.08 0.60/0.84/0.66 0.09/0.08/0.03 0.09/0.05/0.04 0.01/0.06/0.06
Symptomatic deterrents
Feeling healthy is a reason for not screening for breast/
cervical cancer regularly.
0.09/0.02/0.02 0.10/0.20/0.13 0.88/0.04/0.91 0.10/0.89/0.09 0.02/0.09/0.05
Having several normal screening test results is a reason for
not screening regularly.
0.20/0.09/0.10 0.02/0.02/0.01 0.82/0.07/0.81 0.06/0.75/0.03 0.60/0.02/0.01
Not feeling anything abnormal is a reason for not
screening regularly.
0.06/0.003/0.04 0.08/0.03/0.03 0.68/0.07/0.72 0.12/0.81/0.06 0.18/0.01/0.10
Catastrophic disease expectations
Breast/cervical cancer is the worst thing that can happen to
a woman.
0.06/0.06/0.00 0.06/0.06/0.08 0.08/0.10/0.07 0.83/0.01/0.77 0.02/0.59/0.01
Breast/cervical cancer is a deadly disease. 0.14/0.12/0.02 0.03/0.06/0.05 0.12/0.05/0.10 0.81/0.08/0.75 0.04/0.75/0.004
Negative beliefs about health professionals
Health professionals are not compassionate for what their
patients are going through.
0.11/0.03/0.03 0.01/0.03/0.05 0.04/0.78/0.02 0.04/0.01/0.02 0.80/0.08/0.83
Health professionals are always in a hurry and do not have
time for their patients.
0.06/0.04/0.03 0.21/0.18/0.24 0.09/0.57/0.12 0.04/0.12/0.02 0.63/0.01/0.60
I do not feel comfortable with health professionals doing
the screening examination.
0.001/0.01/0.01 0.27/0.04/0.16 0.03/0.51/0.07 0.04/0.13/0.04 0.58/0.01/0.56
Some health professionals inappropriately touch their
patients during the screening examination.
0.16/0.16/0.13 0.11/0.18/0.12 0.03/0.57/0.05 0.05/0.13/0.05 0.50/0.05/0.53
Health professionals performing screening examinations
are not trustworthy.
0.11/0.07/0.02 0.28/0.08/0.21 0.15/0.61/0.10 0.12/0.004/0.12 0.30/0.09/0.43
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but one correlation were small to medium in mag-
nitude, indicating conceptual discreteness among
the factors. The one correlation that approached
a large magnitude for both ethnic groups was be-
tween symptomatic deterrents and sociocultural
deterrents (Latinos: r= 0.54, P< 0.01; Anglo: r=
0.47, P< 0.01).
Means, standard deviations and scale reliabilities
as estimated using Cronbach’s alphas for Latinos,
Anglos and the combined sample are reported in
Table IV. Alphas for the overall CCSS were excel-
lent (Latino 0.84, Anglo 0.83, total, 0.84) and the
alphas for the cultural factors ranged from 0.66 to
0.90. The lowest alphas were obtained for the cat-
astrophic disease expectations factor, which con-
tains only two items.
Based on the suggestions of van de Vijver and
Leung [29] for establishing psychometric adequacy
with different cultural populations, a test for the
equality of reliability coefficients was conducted.
Results revealed no significant differences based
on ethnicity. Construct equivalence was tested
through target rotations and the computation of an
index of factorial agreement (Tucker’s phi [41])
across the ethnic samples. The test for measurement
equivalence revealed a Tucker’s phi of 0.98, indi-
cating strong factorial congruence for the two eth-
nic groups. The establishment of measurement
equivalence suggests that findings relevant to ethnic
group differences are most likely due to true cross-
cultural differences rather than the result of mea-
surement artifacts [30].
As predicted, there were some apparent differ-
ences between the two groups in the mean scores
obtained for some cultural factors. Independent
t-tests of group differences between Latino and
Anglo women for all factor scores are reported in
Table V. The overall CCSS and three of the five
cultural factors (catastrophic disease expectations,
cancer screening fatalism, and negative beliefs
about health professionals) showed significantly
higher scores for Latino women.
The correlations between the CCSS and breast
and cervical cancer screening behaviors, intentions
and screening emotions are represented in Tables
VI and VII. The overall CCSS was correlated with
several cancer screening behaviors and screening
emotions. For self-reported screening behaviors
and intentions, symptomatic deterrents produced
the most statistically significant results, though
all factors produced at least one correlation
coefficient of medium magnitude. The cultural
factors correlated more highly with screening
emotions than with screening behaviors or
intentions. Screening emotions, in turn, were
highly correlated with screening behaviors and
intentions, particularly for the Latino sample.
Also, some of the cultural factors were stronger
predictors of one or the other type of cancer
screening behaviors or intentions.
There were also some apparent differences in
correlation magnitude between the two ethnic
groups based on Fischer’s r-to-ztransformations
and z-tests of difference. Four of these differences
were statistically significant and one approached
significance (correlation differences noted in Table
VI). Except for one of these differences, screening
was more highly correlated with culture and/or
screening emotions for the Latino group.
The predictive validity of the CCSS was exam-
ined using Bentler’s structural equations program
[42] (EQS, 2005) for the analysis of causal models.
To this end, a model was tested including the hy-
pothesized relations among scores on the CCSS as
predictors of cancer screening and screening emo-
tions. In a manner consistent with the model for the
study of culture, demographic factors conceived as
sources of cultural variation were included in the
model as antecedents of the cultural factors
assessed by the CCSS (see Fig. 2). A mean com-
posite score for the CCSS was calculated which was
expected to directly and/or indirectly predict breast
and cervical cancer screening through screening
emotions.
Adequacy of model fit was assessed using v
2
goodness-of-fit statistic, the ratio of v
2
to the
degrees of freedom (v
2
/df), the comparative fit index
(CFI) and the root mean square error of approxima-
tion (RMSEA). The nonsignificant (P> 0.05) v
2
was used to determine the degree to which the esti-
mated covariance model matches the data covari-
ance matrix. For v
2
/df, a ratio of <2.0 is indicative
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of a good model fit [43]. A CFI value >0.90 is
considered indicative of an adequate fitting model
whereas a value of 0.95 is indicative of a good-
fitting model [44]. For the average error of param-
eter estimates, or the RMSEA, a value <0.05
indicates close approximate fit [45] and values
ranging from 0.08 to 0.10 indicate mediocre fit
[49]. Due to limitations with relying on cutoff
points, several goodness-of-fit measures should be
used to determine global model fit [46].
Table III. Correlations between cultural factors for Latino and Anglo sample
1 23456
Sociocultural deterrents 1.00 0.03 0.47** 0.20* 0.21* 0.75**
Cancer screening fatalism 0.10 1.00 0.24** 0.11 0.15 0.39**
Symptomatic deterrents 0.54** 0.29** 1.00 0.12 0.26** 0.75**
Catastrophic disease expectations 0.01 0.11 0.02 1.00 0.20* 0.39**
Negative beliefs about health care professionals 0.39** 0.28** 0.24** 0.18* 1.00 0.59**
CCSS 0.79** 0.50** 0.76** 0.27** 0.74** 1.00
Bottom left represents Latino correlations and top right represents Anglo correlations. *P<0.05, **P<0.01.
Table IV. Alphas, means (M) and standard deviations (SDs)
Latino/Anglo/total Latinos (n=157) Anglos (n=147) Total (n=304)
Factors Alphas M (SD) M (SD) M (SD)
Sociocultural deterrents 0.86/0.79/0.83 2.40 (1.47) 2.44 (1.30) 2.42 (1.39)
Cancer screening fatalism 0.72/0.80/0.75 1.89 (1.44) 1.48 (0.95) 1.69 (1.24)
Symptomatic deterrents 0.90/0.87/0.89 2.84 (2.06) 2.87 (1.91) 2.85 (1.99)
Catastrophic disease
expectations
0.70/0.66/0.69 5.37 (1.65) 4.75 (1.53) 5.08 (1.62)
Negative beliefs about health
professionals
0.77/0.75/0.77 2.56 (1.46) 2.18 (1.15) 2.38 (1.33)
CCSS 0.84/0.83/0.84 2.78 (1.1) 2.50 (0.85) 2.65 (1.00)
Table V. Differences in cultural factors based on ethnicity
Factors tdf PdConfidence interval
Sociocultural deterrents 0.25 293 0.80 0.03 (2.78, 0.36)
Cancer screening fatalism 2.94 271.54 0.004 0.34 (0.68, 0.14)
Symptomatic deterrents 1.6 294 0.87 0.03 (0.42, 0.49)
Catastrophic disease
expectations
3.44 308.61 0.001 0.39 (0.98, 0.27)
Negative beliefs about health
professionals
2.52 298.14 0.01 0.29 (0.67, 0.08)
CCSS 2.49 310 0.01 0.28 (0.50, 0.06)
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Table VI. Correlations among cultural factors, breast cancer screening and screening procedure emotions
MAM compliance ratio MAM intention CBE compliance ratio CBE intention MAM emotions CBE emotions
Latino
a
Anglo
b
Total
c
Latino
d
Anglo
e
Total
f
Latino
g
Anglo
h
Total
i
Latino
j
Anglo
k
Total
l
Latino
m
Anglo
n
Total
o
Latino
p
Anglo
q
Total
r
Sociocultural
deterrents
0.21 0.03 0.08 0.01 0.37* 0.16 0.13 0.08 0.10 0.21 0.29* 0.25** 0.29* 0.07 0.18 0.37** 0.34** 0.35**
Cancer screening
fatalism
0.20 0.41** 0.31** 0.27 0.21 0.26** 0.35** 0.27 0.34** 0.09 0.03 0.06 0.03 0.12 0.09 0.07 0.15 0.13
Symptomatic
deterrents
0.36* 0.32* 0.33** 0.21 0.25 0.23* 0.17 0.15 0.17* 0.11 0.20 0.14 0.42** 0.27* 0.38** 0.49y0.26y0.42**
Catastrophic
disease
expectations
0.36* 0.20 0.27** 0.13 0.09 0.14 0.04 0.11 0.10 0.05 0.19 0.10 0.33* 0.12 0.26** 0.30** 0.14 0.26**
Negative beliefs
about health
professionals
0.10 0.20 0.15 0.15 0.14 0.16 0.33** 0.12 0.16 0.06 0.13 0.01 0.01 0.28* 0.16 0.36 0.52** 0.42**
CCSS 0.44** 0.33* 0.38** 0.21 0.37** 0.29** 0.33** 0.14 0.28** 0.12 0.25* 0.16 0.40** 0.28* 0.37** 0.58** 0.46** 0.56**
MAM emotions 0.53** 0.24 0.38** 0.09 0.27* 0.19* 0.50** 0.09 0.30** 0.11 0.26* 0.17
CBE emotions 0.37** 0.20 0.30** 0.06 0.14 0.10 0.40** 0.01 0.25** 0.05 0.20 0.05
The italic, bold pairs represent significant differences in the correlation magnitudes between Latino and Anglo women at P<0.05 and bold pairs (no italics) are significant at
P<0.10. yP<0.10, *P<0.05, **P<0.01.
a
nranges from 49 to 52,
b
n=57–60,
c
n=106–112,
d
n=66–74,
e
n=68–70,
f
n=134–144,
g
n=63–71,
h
n=68–71,
i
n=131–142,
j
n=66–74,
k
n=68–70,
l
n=134–144,
m
n=50–53,
n
n=58–61,
o
n=108–114,
p
n=70–78,
q
n=72–75,
r
n=142–153.
Table VII. Correlations among cultural factors, cervical cancer screening and screening procedure emotions
Pap compliance ratio Pap intention Pap emotions
Latino
a
Anglo
b
Total
c
Latino
d
Anglo
e
Total
f
Latino
g
Anglo
h
Total
i
Sociocultural deterrents 0.15 0.13 0.01 0.02 0.11 0.06 0.09 0.03 0.06
Cancer screening fatalism 0.15 0.14 0.11 0.21 0.39** 0.24** 0.04 0.03 0.004
Symptomatic deterrents 0.09 0.03 0.08 0.22 0.11 0.17* 0.06 0.20 0.11
Catastrophic disease expectations 0.19 0.02 0.10 0.01 0.05 0.05 0.03 0.20 0.07
Negative beliefs about health professionals 0.13 0.38** 0.14 0.13 0.05 0.06 0.09 0.08 0.10
CCSS 0.10 0.08 0.08 0.21y0.09 0.14y0.05 0.18 0.10
Pap emotions 0.10 0.33** 0.13 0.16 0.04 0.08 0.09 0.07 0.09
a
nranges from 59 to 63,
b
n=57–59,
c
n=117–122,
d
n=72–76,
e
n=71–73,
f
n=142–147,
g
n=74–79,
h
n=72–74,
i
n=146–151.
*P<0.05, **P<0.01, yP<0.10.
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The model testing the predictive validity of the
CCSS with MAM and MAM emotions provided
a good fit of the data [CFI = 0.96, v
2
(11, n= 103) =
18.15, P= 0.08, v
2
/df = 1.65, RMSEA = 0.08] and
accounted for 26% of the variance (see Fig. 2).
Women who scored higher on the CCSS were
less likely to be compliant with MAM screening
(b=0.26, P< 0.01) and more likely to have neg-
ative MAM emotions (b= 0.35, P< 0.01). In fact, the
CCSS was found to exert both a direct as well as
an indirect effect on MAM compliance through neg-
ative MAM emotions (b
indirect
=0.126, P< 0.01).
The model testing the predictive validity of the
CCSS with CBE compliance and negative CBE emo-
tions provided an adequate fit [CFI = 0.95, v
2
(11,
n= 127) = 27.85, P= 0.00, v
2
/df = 2.53,
RMSEA = 0.11] and accounted for 14% of the
variance (see Fig. 2; paths noted in parentheses).
Higher scores on the CCSS predicted less CBE
compliance (b=0.29, P< 0.01) and greater nega-
tive CBE emotions (b= 0.63, P<0.001).The
CCSS however only exerted a direct and no indirect
effect on CBE compliance through CBE emotions
(b
indirect
=0.029, P> 0.05). A third model predict-
ing Pap compliance was tested and also provided an
adequate fit [CFI = 0.95, v
2
(11, n= 113) = 16.13,
P= 0.10, v
2
/df = 1.46, RMSEA = 0.07]. In this case,
the path between CCSS and Pap compliance was not
very strong (b=0.09, P> 0.05). However, when
intention to have a Pap was used as an outcome, the
path was stronger (b=0.17, P< 0.05) [CFI = 0.94,
v
2
(11, n= 140) = 19.54, P= 0.03, v
2
/df = 1.78,
RMSEA = 0.08].
Discussion
Overall, this research serves to illustrate the imple-
mentation of the bottom-up approach to the study of
culture and psychological processes in health be-
havior with culturally diverse populations employ-
ing mixed methodologies. The research resulted in
the development of an instrument designed to as-
sess cultural factors related to cancer screening that
can inform evidence-based interventions with La-
tino and Anglo women. A number of distinct fea-
tures that characterize the research involved in the
development of the CCSS are noteworthy. First, the
work was guided by a theoretical model (see Fig. 1)
that clearly specifies the manner in which the iden-
tified cultural factors were expected to relate to
screening behavior and psychological processes,
as well as to population categories conceived as
sources of cultural variation (e.g. ethnicity and
SES). This is important as theory-based results
may contribute not only to intervention but also
to advance theory and future research. Second, the
identification of cultural factors was based on
a well-defined concept of culture that focuses on
phenomena particularly relevant to psychological
.95
(.87)
.80**
(.83**)
.86***
(.97***)
.70
(.71)
-.36***
(-.12)
.35**
(.63***)
-.26** (-.29**)
-.35***
(-.47***)
.09
(.10)
-.10
(-.31***)
Ethnicity
Education
SES
CCSS
Emotions
Fea
r
Anxiety
Screening
Compliance
Income
Fig. 2. Model testing the predictive validity of CCSS (paths in parentheses represent the paths for CBE; paths not in parentheses
represent paths for MAM).
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functioning and health behavior, such as socially
shared beliefs, norms and expectations. Third, the
bottom-up approach allowed for the generation of
items based on cultural aspects that emerged di-
rectly from the minority and majority populations,
respectively. Last, statistical procedures consistent
with recommendations for cross-cultural research
were implemented to establish measurement
equivalence [29] resulting in an instrument that
could be used with both minority and majority
populations to examine ethnic-based health
disparities.
The resulting CCSS includes five factors that
emerged from the analysis of cultural elements
identified as important to one or the other ethnic
group, but relevant to individuals from both groups.
Interestingly the contents of some of the factors that
emerged from this research are similar to those
identified as deterrents of cancer screening in
previous qualitative studies [24–26]. The CCSS
was found to be reliable and demonstrated predic-
tive validity. Moreover, the CCSS demonstrated
measurement equivalence across ethnic groups
suggesting that it could be useful for health
disparities research and intervention efforts with
both Latino and Anglo women of various SES
backgrounds.
Concerning the relations between cultural factors
and screening (see Tables VI and VII), the finding
that some factors were relevant to all forms of can-
cer screening while others were relevant to one or
another is consistent with the unique nature of some
screening methods. Specifically, the procedures and
type of health professionals involved when having
a CBE, MAM or Pap are quite different. Also, in-
tention to screen and screening compliance repre-
sent different behavioral responses and may reflect
different concerns for patients. Hence, although the
CCSS can be used to assess cultural aspects rele-
vant to a variety of cancer screening behaviors, it is
important to consider that some cultural factors may
relate to or influence each form of screening in
a different way. Ignoring this, as well as assuming
that a particular cultural factor is equally important
to all individuals of an ethnic group can negatively
impact intervention efforts and may explain some
of the inconsistencies observed in research findings
and interventions dealing with the role of culture
and cultural sensitivity in health behavior.
Despite the differential influence of the individ-
ual cultural factors on screening behaviors, the
CCSS demonstrated predictive validity. Consistent
with the model for the study of culture, structural
equation modeling demonstrated a good level of
predictive validity for the CCSS, particularly in
the case of MAM and CBE compliance in addition
to MAM and CBE emotions. Still, even though the
predictive validity of intention to have a Pap was
also good, the lower predictive validity for Pap
compliance needs to be further examined in future
research. The observed differences in predictive
validity may be a consequence of collapsing the
individual cultural factors into one composite score.
For instance, correlations suggest that in the case of
cervical cancer screening, cancer screening fatalism
and negative beliefs about health care professionals
are the two cultural factors that relate to Pap screen-
ing the most. Although it was beyond the scope of
this paper to test the predictive validity of the in-
dividual cultural factors, this should be more
closely examined in future research along with
other aspects of the conceptual model that guided
this study.
Of theoretical and practical significance is the
finding that in the case of MAM compliance, the
influence of the CCSS was both direct and indirect
through screening emotions. Correlations among
the individual cultural factors from the CCSS sug-
gest a similar trend. For instance, some cultural
factors were not related to screening but were re-
lated to psychological processes such as emotions
that in turn were related to screening behavior.
Therefore, when research only examines the direct
influence of cultural factors on health behavior and
ignores the role of potential indirect psychological
aspects, these important cultural factors may not
appear to be related to health behavior. As a result,
such aspects of culture may be left out of instru-
ments or interventions dealing with diverse popu-
lations. Future research should examine the extent
to which the individual cultural factors included in
the CCSS may relate to psychological processes
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such as emotions, which in turn are likely to influ-
ence cancer screening behaviors.
These findings also point to the necessity for
employing statistical procedures such as Fischer’s
r-to-ztest of difference or multi-group structural
equation modeling. Such statistical analyses spe-
cifically take into consideration the divergence in
findings based on ethnicity and their impact on psy-
chological processes and health behavior. For ex-
ample, consider the differential relation between
negative beliefs about health professionals and
CBE compliance for Latino and Anglo women
(r=0.33, P<0.01 and r= 0.12, P>0.05, respec-
tively). If these data were not analyzed separately
for the two ethnic groups, but rather collapsed
across ethnicity, one might conclude that this
cultural factor does not relate to CBE compliance
(r=0.16, p> 0.05). As a result, intervention
efforts may erroneously ignore cultural beliefs
about health professionals that are particularly
important for Latino women.
An additional conceptual and methodological is-
sue to be further examined is the influence of eth-
nicity and SES as sources of variation in the CCSS.
Results from t-tests revealed that on the average
Latino women reported higher scores on the CCSS
as compared with Anglo women. However, struc-
tural equation modeling indicated that when SES is
taken into consideration, the impact of ethnicity as
a source of cultural variation is weaker. Moreover,
these analyses did not reveal a direct effect of SES
or ethnicity on screening behaviors, highlighting
that cultural factors measured through the CCSS
were more proximal predictors of cancer screening.
Murguia and Zea [47] reported similar findings in
that Latino cultural health beliefs were found to be
better predictors of health care utilization as com-
pared with SES and acculturation.
While these findings are consistent with the view
of the model for the study of culture, which con-
ceives SES as a source of cultural variation, the
complexity of relations between ethnicity, SES
and other demographic factors needs to be further
examined, as suggested by Borrayo and Jenkins
[48]. Still, it is important to recognize that ethnicity
influenced the strength of relations among the
cultural factors and cancer screening. These find-
ings suggest that even though the same cultural
aspects apply to both ethnic and SES groups, eth-
nicity moderates these relations.
Despite the demonstrated utility of the CCSS, the
interpretation of results is limited in some ways. For
instance, while measurement equivalence was estab-
lished for the Latino and Anglo samples, it was not
possible to establish equivalence based on the Span-
ish and English version of the CCSS since only 43
Latino women completed the Spanish survey. An
examination of the reliabilities for the English and
Spanish versions suggests that the Spanish CCSS is
likely to be reliable (e.g. alphas for three of the five
subscales and the total CCSS was higher for the
Spanish version). However, future research should
demonstrate the factor structure, predictive validity
and measurement equivalence of the Spanish CCSS.
Furthermore, the convergent and discriminant valid-
ity of the CCSS needs to be established.
Another potentially limiting factor is that the re-
gion in which the research was conducted is predom-
inantly comprised of Latinos of Mexican cultural
background. Therefore, it is unclear how the factors
included in the instrument may work with Latinos
from other national origins or regions of the United
States. Furthermore, while this research demon-
strated between-ethnic group differences in the rela-
tions among some of the cultural factors and cancer
screening, within-ethnic group differences are also
possible. Hence, future research should examine
whether or not variations in the relevance of the
cultural factors exist among individuals from Latino
subpopulations such as SES, national origin, region
in which they reside and generation status.
An important aspect of this research and the de-
velopment of the CCSS is that it provides the tools
necessary for generating empirical findings that can
inform the development of evidence-based cultural
interventions. The procedures outlined in this re-
search and the resulting CCSS allow for the devel-
opment of both targeted and tailored programs
based on the assessment of cultural information.
Utilizing the CCSS, health professionals can obtain
a profile of the screening-relevant cultural factors for
a particular population or community. Although the
A cultural research approach to instrument development
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development of the CCSS is expected to be particu-
larly important for working with culturally diverse
populations, health professionals must be cautious
when attributing to a community or subpopulation
cultural factors based on mean scores for a much
larger and more heterogeneous ethnic population.
Health professionals should also take into
consideration the importance of within-group
differences such as those based on immigration
status, education and income in their clinical work
at the individual level. To this end, the CCSS can be
administered to an individual from a particular
community to determine their personal cancer-
relevant cultural profile. To enhance the effective-
ness of tailored interventions, health professionals
can consider an individual’s cultural profile to iden-
tify specific cancer-relevant cultural elements that
may be particularly important to that individual.
Funding
National Cancer Institute and the Office of Research
on Women’s Health at the National Institutes of
Health, Grant 1R21CA101867, H. Betancourt, PI.
Acknowledgements
We would like to thank Claudia Argueta, Crystal
Coker, Monica Hodges, Natalie Kaiser, Brenda
Navarrete and Jennifer Tucker for their help collect-
ing data and their assistance with preliminary data
analyses. We would also like to thank all of the
women that graciously agreed to participate in this
study and the community organizations that
facilitated this process.
Conflict of interest statement
None declared.
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