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Social Science & Medicine 56 (2003) 851–862
Ethnic differences in choices of health information by cancer
patients using complementary and alternative medicine:
an exploratory study with correspondence analysis
Hisako Kakai, Gertraud Maskarinec*, Dianne M. Shumay, Yvonne Tatsumura,
Katsuya Tasaki
Cancer Research Center of Hawaii, University of Hawaii at Manoa, 1236 Lauhala Street, Honolulu, HI 96813, USA
Abstract
This study examined patterns in the use of health information among Caucasian, Japanese, and non-Japanese Asian
Pacific Islander cancer patients in Hawaii and explored the relation of ethnicity and educational level to choices of
health information sources. Information from 140 cancer patients, most of whom were users of complementary and
alternative medicine (CAM), was analyzed using correspondence analysis. Three clusters of health information
pertinent to the three ethnic groups emerged from the data. The results of this study revealed that Caucasian patients
preferred objective, scientific, and updated information obtained through medical journals or newsletters from research
institutions, telephone information services, and the internet. Japanese patients relied on media and commercial sources
including television, newspapers, books, magazines and CAM providers. Non-Japanese Asians and Pacific Islanders
used information sources involving person-to-person communication with their physicians, social groups, and other
cancer patients. A higher educational level was closely related to a cluster of health information stressing objective,
scientific and updated information, while a lower educational level was associated with interpersonally communicated
information. The three ethnicity-specific patterns of health information use remained relatively stable at different
educational levels, implying that the effect of patients’ ethnicity overrides their educational level in shaping their choices
of health information. The results of this study indicate the importance of recognizing cancer patients’ culturally
developed world views when understanding their health information-seeking behavior. For medical practice, these
findings indicate the need for healthcare providers to assist cancer patients to obtain accurate health information in a
culturally sensitive way. r 2002 Elsevier Science Ltd. All rights reserved.
Keywords: Cancer; Health information; Ethnicity; Complementary medicine; Japanese-Americans; Asians; Pacific Islanders
Introduction
Cancer patients use various sources of health information to gain knowledge about their illness and
prognosis, treatment options and side effects, ways to
prevent recurrence, and psychological resources for
coping (Cassileth, Zupkis, Sutton-Smith, & March,
1980; Fallowfield, Ford, & Lewis, 1994). These include,
but are not limited to, healthcare providers (e.g.,
*Corresponding author. Tel.: +1-808-586-3078; fax: +1808-586-2984.
E-mail address: [email protected] (G. Maskarinec).
physicians and nurses), publications (e.g., books and
magazines), phone assistance (e.g., Cancer Information
Service), newspapers, television, radio, and word of
mouth (Carlsson, 2000; Freimuth, 1993; Guidry, Aday,
Zhang, & Winn, 1998; Ward, Anderson, Pundik,
Redrick, & Kaufman, 1993; Worsley, 1989). Worsley
(1989) categorized sources of health information into
three major groups, ‘‘formal sources’’ (healthcare
providers), ‘‘informal sources’’ (friends and relatives),
and ‘‘commercial and media sources’’ (TV commercials,
newspaper, and magazine articles). In a different
approach, Carlsson (2000) distinguished an ‘‘active
information-seeking strategy’’ (internet, medical books,
0277-9536/03/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved.
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H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
narratives, and telephone information lines) and a
‘‘passive information-seeking strategy’’ (television,
radio, newspapers, other cancer patients, and friends).
Demographic variables associated with informationseeking behavior include age (Carlsson, 2000; TurkCharles, Meyerowitz, & Gatz, 1997; Worsley, 1989),
gender (Freimuth, 1993; Rimer, Catoe, Graves, Burklow, & Anderson, 1993), education (Brown et al., 1993;
Carlsson, 2000; Freimuth, 1993; Guidry et al., 1998;
Jubelirer, Linton, & Magnetti, 1994; Turk-Charles et al.,
1997; Ward et al., 1993), and ethnicity (Freimuth, 1993;
Guidry et al., 1998; Rimer et al., 1993; Ward et al.,
1993). The latter appears to be a critical contributor in
shaping health information-seeking behavior although
all ethnic groups perceive healthcare professionals as the
most helpful source of information (Freimuth, 1993;
Guidry et al., 1998; Rimer et al., 1993; Ward et al., 1993;
Pennbridge, Moya, & Rodrigues, 1999). For example,
Caucasian patients were more likely to use printed
materials such as books and reference materials, whereas
African-American patients tended to rely on pamphlets
and television when seeking information about treatment options and side effects (Guidry et al., 1998). Use
of the Cancer Information Service was dominated by
Caucasians and underutilized by racial and ethnic
minorities (Freimuth, 1993; Rimer et al., 1993; Ward
et al., 1993). Educational background may also influence
people’s health information-seeking behavior in combination with ethnicity (Brown et al., 1993; Carlsson,
2000; Guidry et al., 1998; Jubelirer et al., 1994; TurkCharles et al., 1997). For example, higher educational
attainment may be responsible for the greater use of
newspapers among Asians and Pacific Islanders (APIs)
(Ward et al., 1993). Recently, with the advancement of
information technology, the use of the internet as a
source of health information has been increasing (Elliott
& Elliott, 2000), particularly among cancer patients with
higher education and younger age (Carlsson, 2000;
Harris, 1998; Pennbridge et al., 1999). Whereas computer penetration and on-line access has been low among
Hispanic- and African-Americans (24%), it has been
high among APIs (51%). However, a breakdown for the
individual ethnic groups within APIs is not available
(National Telecommunication and Information Administration, 2000).
The significant influences of culture on health
behaviors have been discussed by scholars of various
fields (Helman,1994; Kreps & Kunimoto, 1994; Spector,
2000). Although multiple definitions of ‘culture’ exist,
many agree that the concept of culture refers to a set of
guidelines, which include values, beliefs, attitudes, and
behaviors, shared by members of a particular group
(Ember & Ember, 1985; Helman, 1994; Matsumoto,
2000). The choice of guidelines is often influenced by
individuals’ membership in various cultural groups
defined by nationality, ethnicity, age, gender, and
socioeconomic status (Kreps & Kunimoto, 1994).
Internal locus of control (Rotter, 1954), which is the
belief that individuals have control over events happening in their environments, is one concept that characterizes a tendency of individuals with Western cultural
backgrounds who hold individualistic values (Dyal,
1984; Hamid, 1994). Individuals with non-Western
cultural backgrounds, who generally cherish interpersonally oriented cultural values (Markus & Kitayama,
1991; Triandis, 1989), have been often described as
possessing spiritual–social (Edman & Kameoka, 1997)
or fatalistic (Domino & Lin, 1991; Domino & Lin,
1993) attributions to illness. This cognitive style is
likely to be shaped by a world view that is ‘‘less
dialectical, logical, or linguistic in character, less
analytical, more synthetic, or more sensitive to family
or community consensus than to individual autonomy,
more virtue-based than principle-based’’ (Pellegrino,
1992, p. 14).
The present study explored patterns of health
information use among cancer patients of diverse
ethnicity in Hawaii. Fifty-one percent of the state’s
population are APIs, including Hawaiian/part-Hawaiian, Japanese, Chinese, Filipino, Korean, and Samoan
(Hawaii State DBEDT’s Research and Economic
Analysis Division, 2000). With 17% of the state’s
population reporting exclusively Japanese ancestry and
an additional 8% reporting some Japanese ancestry,
Japanese-Americans represent the largest API group.
Immigration from Japan to Hawaii occurred primarily
during 1868–1924, when more than 200,000 Japanese
came to work on plantations (Nordyke, 1989). JapaneseAmericans have been considered unique because of their
rapid acculturation into mainstream America during
and after World War II (Kitano, 1969). The pressure to
assimilate and demonstrate their loyalty as ‘‘good
Americans’’ during the war accelerated Japanese-Americans’ becoming very American (Ina, 1997). Compared
to other APIs, more Japanese-American families speak
only English and a smaller percentage is foreign-born
(Uba & Sue, 1991). A number of cultural concepts are
important to understanding behavioral patterns among
Japanese-Americans. Confucianism which has greatly
influenced Japanese culture (DeVos, 1985; Johnson &
Marsella, 1978; Kitano, 1969; Marsella, 1993), emphasizes conformity, obedience, and the importance of
legitimacy and authority associated with social roles and
hierarchy. Therefore, Japanese-American patients, particularly elders, often defer to their physicians for
medical decision-making (Saldov, Kakai, McLaughlin
& Thomas, 1998), an accepted practice in traditional
Japanese culture. At the same time, Japanese-Americans’ enryo, ‘‘modesty in the presence of one’s superior’’
(Kitano, 1969, p. 102) or ‘‘denial of self-importance’’
(Johnson, 1985, p. 123), discourages assertiveness in
front of authorities such as physicians.
H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
The major objective of this study was to investigate
ethnic differences in health information-seeking behaviors among cancer patients in Hawaii who had
participated in a survey on complementary and alternative medicine (CAM). In addition, we explored a
possible association between patients’ education and
ethnicity and choice of health information.
Methods
Participants
Information for this analysis came from a larger study
with 1168 patients who had participated in a mail survey
on the use of CAM. As described in detail elsewhere
(Maskarinec, Shumay, Kakai, & Gotay, 2000), the study
subjects were identified through a state-wide populationbased cancer registry. All patients diagnosed with
invasive cancer during 1996 and a subgroup of the
1995 cases received a questionnaire asking for selfreported ethnicity and types of alternative therapies for
cancer (‘‘What kind of alternative therapies for cancer
have you tried?’’). The following choices were offered:
chiropractic, acupuncture, massage/body work, homeopathic medicine, relaxation techniques, hypnosis, yoga,
religious healing or prayer, support groups, herbal/
botanical treatment, osteopathy, traditional Hawaiian
healing, energy healing, meditation/mindfulness techniques, guided imagery/visualization, biofeedback, Tai
Chi or Chi Gong, psychological counseling, special diet,
megadoses of vitamins/other supplements, and other
alternative therapy. We classified everyone who chose at
least one of the categories as a CAM user.
Although the response rate was only 47.6%, age,
gender, place of residence, and ethnic distribution of the
respondents was very similar to the distribution of all
cancer patients recorded in the tumor registry. Only
Filipino and Native Hawaiian patients responded at a
slightly lower rate than the other groups. From the 439
patients who volunteered for an interview by indicating
their interest on the questionnaire, we selected 143
individuals using a stratified sampling technique that
attempted to include a variety of cancer sites, demographic backgrounds, residential areas, and types of
CAM used. Due to our primary interest in interviewing
CAM users, the majority of interviewees (76%) were
those who had reported in the survey that they had used
CAM for their cancers (Table 1). A smaller number
(24%) of patients reporting no CAM use were interviewed to gain insight into their thinking about cancer
and its treatment. Three patients were excluded from the
present analysis because they did not provide information regarding their sources of health information. The
initial survey study as well as the subsequent interview
study were approved by the Hawaii Cancer Commis-
853
sion, the Committee of Human Studies at the University
of Hawaii, and the Institutional Review Board of Kaiser
Permanente.
Interview procedure
All interviews were conducted by two members of the
research team at a location of the patients’ choice. All
conversations were tape recorded with the patients’
permission and later transcribed verbatim. During the
interview, the patient was asked various questions
regarding his or her medical and psychological experiences with cancer and its treatment, including both
conventional medicine and CAM. One of the questions
specifically asked the patient to identify the primary
sources of health information that he or she had used
since receiving the cancer diagnosis. Health information
was defined as any information related to the patient’s
health including cancer, cancer treatment and prevention.
Data coding
The transcribed interviews were coded using a
qualitative analysis software package, called NUD*IST
4 (N4) or Non-numerical Unstructured Data Indexing,
Searching and Theorizing (Qualitative Solutions and
Research Pty Ltd., 1997). We used N4 to develop a
coding and classification system for type of CAM
therapies, sources of health information, and other
required variables by searching for a character or a
sequence of characters and looking for key-word cooccurrences in the text. Sources of health information
were coded into nine categories, including information
provided by physicians (MDINF), telephone cancer
information services (TELEP), professional references
such as medical journals or newsletters from research
institutions (PROF), television (TV), printed media
materials such as newspapers, books, and magazines
available at regular bookstores (PRINTM), CAM
providers such as practitioners and product distributors
(e.g., health food stores) (CAMPRO), family, friends,
and co-workers (PEOPLE), other cancer patients
(CAPT), and the internet (INTERNET). We assigned
1 to health information sources mentioned by patients
and 0 otherwise. In a situation where the patient used
one source of information with which s/he became
acquainted through another source of information, we
assigned 1 to both sources. For example, if the patient
mentioned using a book recommended by his/her friend,
both PRINTM and PEOPLE were coded as 1. Selfreported ethnic identities of the interviewees were
categorized as Caucasian, Japanese, and non-Japanese
API, which included Chinese, Korean, Filipino, Hawaiian, Samoan, and others. For reasons described in the
introduction, Japanese-Americans were categorized as a
H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
854
Table 1
Demographic characteristics of the interviewed participants (N ¼ 140)
Variables
Categories
Caucasian (N ¼ 65)
Japanese (N ¼ 33)
Non-Japanese APIa (N ¼ 42)
Gender
Male
Female
25 (38.5%)
40 (61.5%)
11 (33.3%)
22 (66.7%)
14 (33.3%)
28 (66.7%)
Age group
o40 years
40–49 years
50–59 years
60–69 years
70–79 years
80+ years
4 (6.2%)
8 (12.3%)
17 (26.2%)
19 (29.2%)
14 (21.5%)
3 (4.6%)
3
4
7
7
9
3
(9.1%)
(12.1%)
(21.2%)
(21.2%)
(27.3%)
(9.1%)
5 (11.9%)
6 (14.3%)
15 (35.7%)
6 (14.3%)
9 (21.4%)
1 (2.4%)
Education
o=12 years
13–16 years
16+ years
33 (50.8%)
16 (24.6%)
16 (24.6%)
19 (57.6%)
8 (24.2%)
6 (18.2%)
23 (54.8%)
14 (33.3%)
5 (11.9%)
Cancer site
Breast
Gastrointestinal
Prostate
All Other Sites
19 (29.2%)
8 (12.3%)
13 (20.0%)
25 (38.5%)
13 (39.4%)
6 (18.2%)
9 (27.3%)
5 (15.2%)
13 (34.2%)
10 (23.8%)
5 (11.9%)
14 (33.3%)
Cancer state
Localized
Advanced
Unknown
40 (61.5%)
24 (36.9%)
1 (1.5%)
22 (66.7%)
10 (30.3%)
1 (3.0%)
26 (61.9%)
15 (35.7%)
1 (2.4%)
CAM use
Yes
No
55 (84.6%)
10 (15.4%)
22 (66.7%)
11 (33.3%)
30 (71.4%)
12 (28.6%)
Vitamins (44.6%)b
Religion (44.6%)b
Diet (40.0%)
Relaxation (35.4%)
Meditation (33.8%)
Herbs (29.2%)
Vitamins (43.8%)
Religion (31.3%)
Diet (25.0%)
Relaxation (18.8%)
Massage (15.6%)
Herbs (12.5%)
Religion (31.3%)
Herbs (26.2%)
Diet (23.8%)
Relaxation (19.0%)
Massage (16.7%)b
Vitamins (16.7%)b
Six most popular CAMs
a
Other non-Japanese Asians and Pacific Islanders (API) include 15 Hawaiians, 14 Chinese, 9 Filipinos, 2 Koreans, 1 Samoan, and 1
Mixed Race.
b
Equal rank within the same ethnic group.
distinct group from other APIs. Information on educational achievement obtained during the interviews was
categorized into high (>12 years) and low (o12 years)
educational attainment according to the completion of
high school.
Correspondence analysis
For this study, we used correspondence analysis, an
inductive statistical technique that is suitable for
exploring relations among categorical variables but not
for hypothesis testing (Clausen, 1998). Like principal
components analysis, correspondence analysis allows
researchers to reduce a complex data matrix into a more
simple one without losing meaningful information. A
significant advantage of correspondence analysis is that
it permits results to be presented graphically. Categories
of variables with similar frequencies are placed as points
clustered together in space; on the other hand, categories
with dissimilar frequencies are displayed as points that
are far away from each other. The three important
concepts of correspondence analysis are: (a) profiles, (b)
masses, and (c) chi-square distances (Greenacre, 1994).
After transforming the frequencies of variables into
percentages relative to the row or column totals, also
called profiles, the analysis makes it possible to compare
the magnitude of occurrence among categories directly.
While profiles, considered to be mathematical vectors,
explain the proportional frequencies of categories only
relative to the group total, masses are values that adjust
different numbers in the group totals and are obtained
by dividing each group total by the grand total.
Distances between points in space are computed as
chi-square distances, which are equivalent to Euclidean
distances with an adjustment for proportions in
frequencies of categories using profiles.
H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
In this study, we used correspondence analysis in
order to explore (a) the relation between cancer patients’
ethnic backgrounds and their choices of health information sources, and (b) the association between the
patients’ educational levels and ethnicity-specific health
information-seeking patterns. In the latter analysis, our
purpose was not to observe differences in the choice of
health information by educational level within each
ethnic group, but to examine the association between
ethnicity-specific patterns of health information-seeking
behaviors and levels of educational attainment. Correspondence analysis allowed us to examine associations
among the variables of interest visually.
Results
The three ethnic groups did not differ significantly by
age (Caucasian M ¼ 60:66; Japanese M ¼ 62:09; nonJapanese API M ¼ 57:24; Fð2; 137Þ ¼ 1:37; p ¼ ns) and
educational level, with 1 being high school degree or less,
2 bachelor’s degree, and 3 graduate degree (Caucasian
M ¼ 1:74; Japanese M ¼ 1:61; non-Japanese API M ¼
1:57; F ð2; 137Þ ¼ 0:67; p=ns). The members of all three
ethnic groups typically reported using two or three
sources of health information (Caucasian M ¼ 2:34;
Japanese M ¼ 2:15; non-Japanese API M ¼ 2:26;
F ð2; 137Þ ¼ 0:44; p=ns). Among all three groups,
printed media sources were reported as the most
frequently used source of health information (67.1%),
followed by physicians’ information (42.1%). However,
the rank order and the extent of the use for the other
seven sources of health information differed across the
three ethnic groups (Tables 2 and 3).
Ethnicity and health information sources
The results of the initial correspondence analysis with
140 cancer patients displayed 11 eigenvalues, indicating
855
that 11 independent dimensions had been decomposed.
To raise the interpretability of the results, we decided to
retain the first two dimensions, which explained 31.35%
of the total inertia, i.e., variance (Dimension 1: 16.25%;
Dimension 2: 15.10%). Table 4 depicts column coordinates, eigenvalues, and percentages of inertias for the
retained two dimensions. Coordinates explain the
magnitude and direction of the contribution of points
to dimensions. The following included types of health
information that were positively loaded on Dimension 1:
MDINF, TELEP, PROF, PEOPLE, and CAPT. The
types of health information that were negatively loaded
on Dimension 1 included TV, PRINTM, CAMPRO,
and INTERNET. Non-Japanese API had a positive
loading on Dimension 1, whereas Caucasians and
Japanese had a negative loading on this dimension.
TELEP, PROF, and INTERNET were the only
information sources that were positively loaded on
dimension 2. Japanese and non-Japanese API
were negatively and Caucasians positively loaded on
Dimension 2.
Three clusters of health information in relation to
ethnicity could be identified (Fig. 1). As illustrated
graphically, INTERNET, TELEP, and PROF were
found to be close to Caucasians, indicating an association between the three sources of health information and
this ethnic group. CAPT, MDINF and PEOPLE seemed
to be another cluster with which non-Japanese API
appeared to have a close relationship. The last cluster
included TV, PRINTM, and CAMPRO and appeared
to be related to the Japanese group. The identification of
these three clusters of information types and their
associations with certain ethnic groups were consistent
with the trends described in Table 2. For example,
21.5% and 26.2% of Caucasians utilized PROF and
INTERNET, respectively, while the use of these two
types of health information among Japanese and nonJapanese API patients was much lower. For Japanese
patients, the use of PRINTM (78.8%) and TV (24.2%)
Table 2
Frequency (%) of Caucasian, Japanese, and non-Japanese API cancer patients in Hawaii using different sources of health information
Sources of health informationa
Caucasian (n ¼ 65)
Japanese (n ¼ 33)
Non-Japanese APIb (n ¼ 42)
All (N ¼ 140)
Physicians
Telephone information
Professional information
TV
Printed materials
CAM providers
People in general
Other cancer Patients
Internet
25 (38.5%)
8 (12.3%)
14 (21.5%)
13 (20.0%)
44 (67.7%)
11 (16.9%)
17 (26.2%)
5 (7.7%)
17 (26.2%)
11 (33.3%)
1 (3.0%)
4 (12.1%)
8 (24.2%)
26 (78.8%)
6 (18.2%)
8 (24.2%)
3 (9.1%)
4 (12.1%)
23 (54.8%)
5 (11.9%)
5 (11.9%)
8 (19.1%)
24 (57.1%)
3 (7.1%)
12 (28.6%)
9 (21.4%)
6 (14.3%)
59
14
23
29
94
20
37
17
27
a
b
Total adds to more than 100 because of multiple answers.
Non-Japanese Asians and Pacific Islanders (API) includes 15 Hawaiians, 14 Chinese, 9 Filipinos,
2 Koreans, 1 Samoan, and 1 Mixed Race.
(42.1%)
(10.0%)
(16.4%)
(20.7%)
(67.1%)
(14.3%)
(26.4%)
(12.1%)
(19.3%)
856
H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
Table 3
Frequency (%) of Caucasian, Japanese, and non-Japanese API cancer patients in Hawaii at different educational levels using different
sources of health information
Sources of health
informationa
Physicians
Telephone information
Professional information
TV
Printed materials
CAM providers
People in general
Other cancer patients
Internet
Caucasian
Japanese
Non-Japanese APIb
All
Lowc
(n ¼ 33)
High
(n ¼ 32)
Low
(n ¼ 19)
High
(n ¼ 14)
Low
(n ¼ 23)
High
(n ¼ 19)
Low
(n ¼ 75)
High
(n ¼ 65)
14 (42.4%)
5 (15.2%)
7 (21.2%)
8 (24.2%)
20 (60.6%)
5 (15.2%)
9 (27.3%)
1 (3.0%)
7 (21.2%)
11 (34.4%)
3 (9.4%)
7 (21.9%)
5 (15.6%)
24 (75.0%)
6 (18.8%)
8 (25.0%)
4 (12.5%)
10 (31.3%)
7 (36.8%)
0 (0.0%)
2 (10.5%)
3 (15.8%)
14 (73.7%)
2 (10.5%)
6 (31.6%)
1 (5.3%)
1 (5.3%)
4 (28.6%)
1 (7.1%)
2 (14.3%)
5 (35.7%)
12 (85.7%)
4 (28.6%)
2 (14.3%)
2 (14.3%)
3 (21.4%)
13 (56.5%)
4 (17.4%)
3 (13.0%)
4 (17.4%)
14 (60.9%)
1 (4.3%)
5 (21.7%)
5 (21.7%)
4 (17.4%)
10 (52.6%)
1 (5.3%)
2 (10.5%)
4 (21.1%)
10 (52.6%)
2 (10.5%)
7 (36.8%)
4 (21.1%)
2 (10.5%)
34 (45.3%)
9 (12.0%)
12 (16.0%)
15 (20.0%)
48 (64.0%)
8 (10.7%)
20 (26.7%)
7 (9.3%)
12 (16.0%)
25 (38.5%)
5 (7.7%)
11 (16.9%)
14 (21.5%)
46 (70.8%)
12 (18.5%)
17 (26.2%)
10 (15.4%)
15 (23.1%)
a
Total adds to more than 100 because of multiple answers.
Non-Japanese Asians and Pacific Islanders (API) includes 15 Hawaiians, 14 Chinese, 9 Filipinos, 2 Koreans, 1 Samoan, and 1
Mixed Race.
c
Education: low—o12 years; high—X12 years.
b
Table 4
Column coordinates, eigenvalues, and percentages of inertias
for retained two dimensions
Column coordinates
Source of information
Dimension 1
Dimension 2
Information from physicians
Telephone services
Professional references
Television
Printed materials
CAM providers
Family and friends
Cancer patients
Internet
Caucasian
Japanese
Non-Japanese API
Eigenvalue
Inertia percentage
0.55
0.79
0.11
0.46
0.25
0.88
0.09
0.64
0.06
0.23
1.29
1.28
0.41
16.25
0.19
0.74
0.60
0.24
0.11
0.01
0.24
0.31
0.92
0.97
1.16
0.73
0.38
15.10
Note: The total inertia with 11 dimensions is 2.53.
was noticeably high compared to the other two ethnic
groups. MDINF and CAPT were the most popular
sources of information among non-Japanese API
(54.8% and 21.4%, respectively).
The following statements by patients capture the
ethnic patterns in health information seeking behavior
and illustrate Caucasians’ preferences for scientific
information sources, non-Japanese API patients’ reliance on interpersonal communication, and Japanese
patients’ tendency to rely on media and commercial
information.
Caucasian patients:
‘‘The number one is, of course, books. American
Cancer Society, they have, on the internet, they have
the latest. The internet has the latest information, too,
and I will be using that. The daily newspaper. As soon
as something new is printed in weekly magazines or
the daily newspaper, so I cut them out all the time’’ (a
50 year-old male patient with lung cancer).
‘‘Newsletters, I had the Harvard newsletter and reading
current books. And I’m learning lots from my
computer, which I’ve had for about a year and half
now ‘‘(a 90 year-old female patient with breast cancer).
Non-Japanese API patients:
‘‘Relatives and friends that said they know my
condition, so they say this would be good [for my
cancer]...Then you take them, cause I feel that they
are not going to do anything detrimental to my
health. They were good enough to go out and I know
they have to pay for it. Why not include them? The
only thing they can do is [to] help me’’ (a 56 year-old
part-Hawaiian female patient with colon cancer).
‘‘Actually, I guess our doctors and our friends, cause
we also verified who we chose based on our friends’
recommendations. Our doctors and our friends, but
now that, since my son is closer to the medical field
now, I ask him a lot too’’ (a 53 year-old Chinese
female patient with gastrointestinal cancer).
Japanese patients:
‘‘I think it [Coenzyme Q-10] was on TV one time.
They mentioned something about it; that it was not
H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
857
Fig. 1. Profiles of health information sources and ethnic groups in a two-dimensional plot (n ¼ 140). Sources of information include
INTERNET (the internet), PROF (professional information), TELEP (telephone information services), MDINF (physicians’
information), CAPT (other cancer patients’ information), PEOPLE (information from social group), TV (television), PRINTM
(printed materials available at regular bookstores), and CAMPRO (CAM providers).
only good for the heart, but they had something to
do with cancer’’ (a 61 year-old male patient with
prostate cancer).
‘‘I just rely upon the resource information that comes
through [Company X who distributes nutritional
supplements]. They cover everything, they don’t just
focus on cancer. I just use that as my nutritional
information base. That is all’’ (a 45 year-old female
patient with breast cancer).
Educational level and health information sources
After adding educational levels, the results of the
analysis (Table 3) indicated that 27.4% of the total
inertia was explained by the first and second dimensions
(Dimension 1: 14.0%; Dimension 2: 13.4%). In comparison to the original plot with sources of health
information and ethnicity alone (Fig. 2), the inclusion
of educational level did not affect the structures of the
three clusters very much. The only change was that
CAPT shifted its position from negative to positive
loading on Dimension 2. As indicated by the plot, high
educational level was close in distance to a cluster of
health information including TELEP, PROF, and
INTERNET. On the other hand, low educational level
was close to another cluster of health information
sources including CAPT, MDINF, and PEOPLE.
Discussion
As a result of the analysis, three clusters of health
information sources closely related to the three different
ethnic groups emerged. Caucasian background was
associated with the use of health information containing
scientific, objective, and updated knowledge, in particular, telephone cancer information services, professional information in medical journals and newsletters
from research institutions, and the internet. Patients of
Japanese ancestry appeared in the same cluster as
commercial and media information sources that included television, printed media materials, and CAM
providers. Non-Japanese API appeared close in space to
the cluster of information involving interpersonal
communication, such as other cancer patients, family
members, friends, and co-workers, and physicians. The
inclusion of educational level did not greatly change the
initial clusters of health information sources. High
educational level was closely related to the type of
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H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
Fig. 2. Profiles of health information sources, ethnic groups, and educational levels in a two-dimensional plot (n ¼ 140). Sources of
information include INTERNET (the internet), PROF (professional information), TELEP (telephone information services), MDINF
(physicians’ information), CAPT (other cancer patients’ information), PEOPLE (information from social group), TV (television),
PRINTM (printed materials available at regular bookstores), and CAMPRO (CAM providers).
health information emphasizing objectivity and scientific
evidence, while low educational level appeared close to
the health information sources valuing word-of-mouth
information given by the social group.
Consistent with previous research findings, this study
observed frequent use of the internet, professional health
information (Brown et al., 1993; Carlsson, 2000; Guidry
et al., 1998; Jubelirer et al., 1994; Turk-Charles et al.,
1997), and telephone information services (Freimuth,
1993; Rimer et al., 1993; Ward et al., 1993) among
Caucasian patients. The latter may be more effective for
Caucasians because they are more open than other
ethnic groups about disclosing personal problems and
discussing them with strangers (Sue & Sue, 1990). These
observations support the idea of an ‘‘active informationseeking strategy’’ (Carlsson, 2000) and reflect a desire to
seek objective, scientific, and updated information,
attributable to the Western epistemological emphasis
on ‘‘empiricism, objectivity, quantification of experience, and attempting to control nature’’ (Pellegrino,
1992, p. 14). In addition, Western cultural values of
independence, self-reliance, and self-determination
(Johnson, 1985; Markus & Kitayama, 1991; Triandis,
1989) and the internal locus of control (Rotter, 1954)
manifested in a desire to have some control over illness
through active health information-seeking may contribute to the pattern noted among Caucasian patients.
Unlike Caucasian patients, many of the non-Japanese
APIs engaged in a ‘‘passive information-seeking strategy’’ (Carlsson, 2000), in which a patient’s social group
plays a significant role in providing health information.
Although we have no supporting data, we speculate that
many non-Japanese APIs may see a minimal connection
between actively seeking health information and controlling their illness because they do not believe that
their own actions may greatly affect the outcome of their
disease (Domino & Lin, 1991, 1993; Edman & Kameoka, 1997). Consequently, non-Japanese APIs may be less
likely to seek information beyond what is given by their
physicians or social groups. Patients with non-Japanese
API backgrounds relied on physicians’ information
more heavily than the other two ethnic groups.
However, this preference for information from physicians does not rule out distrust towards the standard
Western healthcare system due to perceived cultural
incompetency, a frequently described issue among API
populations (Braun, Look, & Tsark, 1995; Gotay, Issell,
Hernandez, & Serxner, 1996; Uba & Sue, 1991). Because
physicians’ information is generally readily available
and orally communicated, the preference of receiving
H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
information from physicians could be interpreted as an
indication of API’s choice of person-to-person communication based on interpersonally oriented cultural
values (McLaughlin & Braun, 1998; Uba & Sue, 1991).
This experience-inductive approach among non-Japanese API patients, as opposed to the fact-inductive
approach preferred by many Caucasian patients, may
allow non-Japanese APIs to draw conclusions from the
subjective experiences of people in their social group.
For example, anecdotes about other cancer patients who
coped successfully with cancer may be more persuasive
than scientific evidence offered by professionals. The
perceived qualities and trustworthiness of the individual
who offers the information may be more important to a
person holding collectivistic values than the quality of
the information provided.
Japanese patients greatly relied on ‘‘commercial and
media sources’’ (Worsley, 1989) suggesting a preference
for objective or scientific information over interpersonally acquired health information. In contrast to Caucasian patients, Japanese-Americans were less likely to use
telephone information services, the internet, and professional information, possibly as a result of traditional
Japanese values. Japanese-Americans may prefer solving
personal problems within the family structure to
disclosing them to strangers (Ina, 1997; Marsella
1993). Although there are generational differences, the
stigma attached to cancer still makes it difficult for
Japanese-Americans to discuss their illnesses openly.
For example, Saldov et al. (1998) found that JapaneseAmerican elderly cancer patients had a resistance
toward uttering the word ‘‘cancer’’. This observation
was partly attributed to the elderly patients’ concerns
about self-fulfilling prophecy through speech, as originated in the Japanese indigenous religious belief of
kegare (Long & Long, 1982) and a concern of disclosing
a family history of cancer because it may affect the
offsprings’ chances of getting married (Saldov et al.,
1998). The skepticism towards the internet may be a
result of the importance attached to authority (DeVos,
1985; Johnson & Marsella, 1978; Kitano, 1969; Marsella, 1993). Similarly, self-effacing behavior, which discounts positive aspects of one’s own attributes,
(Akimoto & Sanbonmatsu, 1999) may prevent Japanese-American patients from considering themselves
legitimate users of professional information, such as
medical journals. It is interesting to note that physicians’
information was least utilized by Japanese-American
patients, despite their tendency to value authorities’
information. Perhaps, Japanese-Americans may hesitate
to ask many questions, demand more information, or
show assertiveness to avoid offending their physicians.
The frequent use of vitamins and nutritional supplements among Japanese-American patients (Table 1) may
explain the high utilization of information from CAM
providers that is often found in health magazines
859
(Philen, Ortiz, Auerbach, & Falk, 1992), at health food
stores (Calder, Issenman, & Cawdron, 2000; Gotay &
Dumitriu, 2000), on TV, or in newsletters from
distributors of these products.
As to the association between education and ethnicity,
it was unclear from the present analysis whether the
identified patterns of health information use were due to
ethnicity or due to education. Nonetheless, our data
suggested that the observed ethnicity-specific trends
were largely consistent across different educational
levels with a few exceptions at a low educational level,
where we observed a lower use of telephone information
services among Caucasians than other non-Japanese
APIs and a lower use of TV among the Japanese than all
others (Table 3). This indicates that the effect of cultural
beliefs overrides educational attainment in shaping
cancer patients’ health information seeking behaviors.
Valuing objective, scientific, and factual information for
drawing conclusions is a predominant pattern of
thought in the United States (Lieberman, 1994), and
nurturing this epistemic mode among students is
emphasized in the American educational system (Serpell
& Hatano, 1997), an institution that largely reflects
white middle class values (Heath, 1989). As a result, it
seems reasonable that we found a close association
between high educational attainment and types of health
information emphasizing objectivity, scientific evidence,
and updated knowledge among Caucasians.
Selection bias arising from the fact that only a
proportion of survey participants volunteered for an
interview may limit the generalizability of this study.
However, the population-based recruitment strategy
included all cancer cases diagnosed in the state during
one year and provided for the inclusion of diverse cancer
patients. The results should also be interpreted cautiously because of the exploratory nature of correspondence analysis; it is not designed to make statistical
decisions. Nonetheless, the fact that our results are
largely consistent with previous research findings and
logically congruent with cross-cultural theories strengthens our interpretation. This study highlights CAM users’
sources of health information—important knowledge in
light of consistently rising CAM use (Eisenberg et al.,
1998; Ernst & Cassileth, 1998)—and adds new information about APIs to a literature primarily focused on
comparisons between Caucasians and African-Americans (Freimuth, 1993; Guidry et al., 1998).
It is important to understand the critical role that
cultural values and beliefs play in shaping cancer
patients’ health information seeking behaviors because
patients’ choices of health information may affect their
survival and quality of life. Barriers due to the cultural
incompatibility of healthcare providers and patients in
oncology practice may be problematic when negotiating
the course of cancer treatments. Our findings may
help healthcare providers to develop educational
860
H. Kakai et al. / Social Science & Medicine 56 (2003) 851–862
interventions that enhance patients’ understanding of
cancer and its treatment. Healthcare providers need to
make conscious efforts to eliminate cultural barriers
facing cancer patients in their acquisition of health
information. They should avoid stereotypes and offer
diverse resources to all patients while discussing the
benefits and limitations of each.
Despite a commonly observed lack of communication, an active exchange of health information between
patients and their physicians is essential and should be
encouraged. Physicians should remind their patients that
it is all right to ask questions or to share their ideas or
desires rather than deferring all medical decisions to
their physicians. Physicians may also need to encourage
patients, Japanese-American patients in particular, to
speak about their CAM use rather than assuming
physicians’ lack of knowledge in CAMs or unwillingness
to discuss them (Tasaki, Maskarinec, Shumay, Tatsumura, & Kakai, in press). All cancer patients, regardless
of their ethnicities, may need to be informed about the
availability of a variety of health information sources.
Educational brochures and cancer seminars in the health
care facilities may be of value. Patients and their families
with strong interpersonal values, often of non-Caucasian backgrounds, may particularly benefit from the
establishment of trusting and personal relationships with
healthcare providers or health educators while gaining
accurate information about cancer and general health
through such educational activities. These educational
efforts at a community level may also alleviate rising
issues involving the digital divide in today’s highly
technological society.
Acknowledgements
We would like to show our appreciation to all
participants for taking the time and effort to respond
to our questionnaire and to participate in the interviews.
The help of Carolyn Gotay, Ph.D., Marc Goodman,
Ph.D. and the staff of the Hawaii Tumor Registry are
greatly appreciated. We would also like to thank our
research team, including Tammy Brown, Carole Prism,
and David Henderson for their help with transcription
and analysis. This research was supported by a special
study grant from the National Cancer Institute,
Surveillance, Epidemiology, and End Result program
under contract number N01-PC67001 and by a medical
research grant from the Hawaii Community Foundation.
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