Copyright B 2016 Wolters Kluwer Health, Inc. All rights reserved.
Cannas Kwok, PhD Rona Pillay, MEd Chun Fan Lee, PhD
Psychometric Properties of the Breast Cancer Screening Beliefs Questionnaire Among Women of Indian Ethnicity Living in Australia K E Y
W O R D S
Background: Indian women have been consistently reported as having low
Breast cancer screening
participation in breast cancer screening practices. A valid and reliable instrument to
Cultural sensitive
explore their breast cancer beliefs is essential for development of interventions to
Indian women
promote breast cancer screening practices. Objective: The aim of this study was to
Psychometric properties
report the psychometric properties of the Breast Cancer Screening Beliefs
Validation
Questionnaire (BCSBQ) in an Indian community in Australia. Methods: A convenience sample of 242 Indian Australian women was recruited from Indian community organizations and personal networking. Explanatory factor analysis was conducted to study the factor structure. Clinical validity was examined by Cuzick’s nonparametric test, and Cronbach’s ! was used to assess internal consistency reliability. Results: Exploratory factor analysis showed a similar fit to the hypothesized 3-factor structure. The frequency of breast cancer screening practices was significantly associated with attitudes toward general health check-up. Knowledge and perceptions about the breast cancer scale were not significantly associated with clinical breast examinations and mammography. Perceived barriers to mammography were much less evident among women who engaged in breast awareness and clinical breast examination. Results indicated that the BCSBQ had satisfactory validity and internal consistency. Cronbach’s ! of the 3 subscales ranged from .81 to .91. Conclusions: The BCSBQ is a culturally appropriate, valid, and reliable instrument for assessing the beliefs, knowledge, and attitudes about breast
Author Affiliations: School of Nursing and Midwifery, University of Western Sydney, New South Wales, Australia (Dr Kwok and Ms Pillay); and Department of Biostatistics, Singapore Clinical Research Institute (Dr Lee). The authors have no funding or conflicts of interest to disclose.
Correspondence: Cannas Kwok, PhD, School of Nursing and Midwifery, University of Western Sydney, Locked Bag 1797, Penrith 2751, New South Wales, Australia ([email protected]). Accepted for publication June 8, 2015. DOI: 10.1097/NCC.0000000000000294
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Kwok et al
cancer and breast cancer screening practices among women of Indian ethnic extraction living in Australia. Implication for Practice: The BCSBQ can be used to provide nurses with information relevant for the development of culturally sensitive breast health education programs.
W
hile worldwide breast cancer incidence rates are increasing, the steepest increases are in developing countries such as India,1 where over the last decade breast cancer morbidity has overtaken that of cervical cancer.2 Despite having a lower incidence of breast cancer than white women, Indian women are more likely to be diagnosed at younger ages and at later stages and to have disproportionate mortality rates.3 Similarly, compared with white women in developed countries such as the United States, the United Kingdom, and Australia, where 5-year survival rates for breast cancer are 85% to 89%,4 survival rates among Indian women are only 51%.3 Given that the causes of breast cancer remain largely unknown, in many Western countries, preventive measures such as encouraging breast awareness and performing clinical breast examinations (CBEs) and mammography are widely promoted.5 However, women from culturally and linguistically diverse (CALD) backgrounds living in Australia,6 the United States,7 and the United Kingdom8 are consistently reported as having markedly lower mammographic screening rates compared with white women. While in 2009, 67.8% of white women in the United States had at least 1 mammogram over a 2-year period, the rate among Indian American women aged 52 to 64 years was only 52%, the lowest of any ethnic group.9 Although there has been considerable research into breast cancer screening behaviors among CALD women in Western countries,10Y12 little is known about Indian women in this regard. Studies by Filippi et al13 and Tolma et al14 reveal that IndoAmerican women have little knowledge about screening practices and breast cancer risks. Furthermore, a study by Grunfeld and Kohli15 has demonstrated that because some Indian women hold negative beliefs about breast cancer, they do not perceive themselves to be at high risk and do not see any need to have mammograms. These findings are consistent with those of studies by Kwok and Sullivan16 among Chinese and South Asian women in Australia.17 Culturally based beliefs about breast cancer common among CALD women have a profound impact on their screening behaviors.12,17 Literature suggests that cultural beliefs among women from Indian and Chinese backgrounds have similar effects.14,18Y20 For example, some Indian women, like their Chinese counterparts,18 are reluctant to commit to breast screening because of a fatalistic belief that nothing can be done to avoid or treat breast cancer.14 Moreover, because preventive medicine or early detection measures are not a priority in China19 and India,3 attending preventive health services is foreign to Chinese and Indian immigrants in Western countries. This would account for the fact that as studies have demonstrated women from Chinese20 and Indian21 backgrounds seldom present themselves for cancer screening when they are asymptomatic. In addition, as is the case with women from Chinese cultures,16 fears of diagnosis and
Psychometric Properties of BCSBQ
embarrassment have been identified as key factors discouraging Indian women from participating in mammography.15 The Chinese Breast Cancer Screening Beliefs Questionnaire (BCSBQ) was originally designed as a culturally sensitive instrument to assess Chinese Australian women’s knowledge of and attitudes toward breast cancer and screening practices and also to determine what barriers discourage them from undertaking these screening practices. The instrument was first developed in English and then translated into Chinese. Demonstrated to be valid and reliable22 and renamed the ‘‘Breast Cancer Screening Beliefs Questionnaire,’’ it was adapted to investigate the situation prevailing among other cultural groups, including those of Indian ethnic origin. This study forms part of a larger investigation of Indian Australian women’s beliefs, knowledge of, and attitudes toward breast cancer and screening practices in Australia. It should be said that Indians constitute 1 of the fastest-growing CALD groups in Australia.23 The aim of this study was to assess and report the psychometric performance of the BCSBQ on the grounds that a valid and reliable instrument to explore breast cancer beliefs is essential for the development of interventions to promote breast cancer screening practices among Indian women.
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Methods
Participants and Recruitment The target population was Indian Australian women 18 years or older, residing in Sydney, Australia, with no history of breast cancer. The term Indian Australian women refers to any female of Indian ancestry who migrated to Australia. The study was granted approval by the Human Ethics Committee of University of Western Sydney.
Data Collection In 2013, a convenience sample of Indian Australian women was recruited from Indian organizations including churches, social and community centers, festival groups, and also through personal networking. With the assistance of the leaders of organizations, female members were invited to participate in the study. The second author, who is of Indian background, attended women’s meetings to explain the details of the study, the method of administration, and the risks and benefits of participation. Women were given a written participant information statement and were invited to ask questions. Those who agreed to participate could choose to fill out the questionnaire and return it either immediately or through the mail. The questionnaire required 15 to 20 minutes to complete. Cancer NursingTM, Vol. 39, No. 4, 2016
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Instrument The BCSBQ contains 13 items in 3 subscales: (1) attitudes toward general health checkups with a subscale of 4 items that explores whether women had general health checkups in the absence of signs and symptoms; (2) knowledge and perceptions about breast cancer (4 items), which explores cultural beliefs relating to breast cancer; and (3) barriers to mammographic screening practices (5 items), which explore personal and practical issues perceived by women to hinder their participation in breast cancer screening. For simplicity, these are hereafter referred to as attitude, knowledge, and barriers subscales, respectively. Respondents gave ratings for each item within a subscale along a 5-point Likert scale ranging from ‘‘strongly agree’’ (score of 1) to ‘‘strongly disagree’’ (score of 5). Because of the wording of the items, responding either ‘‘disagree’’ or ‘‘strongly disagree’’ was taken to indicate a more proactive approach toward general health checkups, more accurate knowledge about breast cancer, and less perceived barriers to participating in mammographic screening practices. A brief description of the items is illustrated in Figure 1. A pilot group of 10 Indian Australian women with various background criteria (eg, length of stay in Australia, age, and edu-
cational level), who were asked to comment on the clarity, comprehensibility, and readability of the questionnaire, did not report any problems. The BCSBQ also contains items specific to demographic variables such as age, length of time in Australia, English-language proficiency, and education levels. Information was also collected on participants’ breast cancer screening practices. This involved asking women if they had ever heard of the concept of breast awareness (knowing the normal look and feel of their breasts, without needing to apply a special technique), CBE, and mammograms and, if so, how regularly they self-examined or had clinical examinations and/or mammograms.
Sample Size There is no generally agreed consensus as to the minimum sample size for factor analysis. Burns and Grove24 recommend 5 to 10 participants per item. We intended to recruit the maximum number for each of the 13 items in the BCSBQ, which meant recruiting 130 women. To obtain an adequate final sample size, 388 women were invited to participate in the study, 255 of whom returned the questionnaire, giving a response rate of 66%.
Figure 1 n Path diagram of a confirmatory factor analysis of the Indian Breast Cancer Screening Beliefs Questionnaire. The Values correspond to the standardized estimates. E26 n Cancer NursingTM, Vol. 39, No. 4, 2016 Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.
Kwok et al
Thirteen women were excluded, 2 women because they had a history of breast cancer, whereas 11 women failed to complete the questionnaire (the 3 subscales), thus giving a final sample size of 242. This represented an acceptable sample size for both confirmatory factor analysis and exploratory factor analysis (EFA).
Statistical Analysis The 3 subscale scores of the Indian BCSBQ were computed in the same way the Chinese version was scored.22 Missing values would be imputed by the half-rule, that is, the mean of the responses in the same subscale if at least half of the items in that subscale were answered and valid. Participants’ demographic characteristics and the distribution of the subscale scores of the instrument were summarized using descriptive statistics. Proportions of subjects scoring 0 and 100 were computed to assess the floor and ceiling effects. Substantial floor and ceiling effects imply that a 5-point Likert scale might not be sufficient to clearly distinguish the responses at the 2 extremes. We first studied whether the Indian BCSBQ has a 3-factor structure as it was designed; a confirmatory factor analysis (CFA) was performed. Goodness of fit of the factor model was assessed by the fit indices, including the root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), comparative fir index (CFI), and nonnormed fit index (NNFI). These indices addressed the parsimony correction, absolute fit, and comparative or incremental fit, as recommended.25 We followed the common criteria in considering the adequacy of the factor model, that is, RMSEA equal to or less than 0.06, SRMR equal to or less than 0.08, CFI equal to or greater than 0.95, and NNFI equal to or greater than 0.95.26 Addition of covariance between items was made based on the largest modification index if there were doubts about inadequate fit.27 If the factor structure could not be confirmed, an EFA would be conducted. Factors with eigenvalue larger than 1 were retained, and the factor loadings after a varimax rotation would be computed. The final EFA structure would be compared with the originally hypothesized 3-factor structure. Construct validity was then examined by testing 3 hypotheses regarding the association of the subscales with the frequency of screening practices and education level: (1) those who performed breast awareness exercises more frequently or had CBE and mammograms would have a more proactive attitude toward general checkups reflected by a higher score in the attitude subscale; (2) those who had a better education level would be more knowledgeable about breast cancer, thus obtaining a higher score in the knowledge subscale; and (3) having more screening practices was associated with less barriers to mammograms, resulting in a higher score on the barriers subscale. As the frequency of health practices and education level were of ordinal-type data, Cuzick’s28 nonparametric test was used for testing the trend. Item performance of the Indian BCSBQ was then assessed. Internal consistency reliability was evaluated by the Cronbach’s !. A good Cronbach’s ! should be at least .7, but not much higher than .9 because a low value indicates a low degree of homogeneity, whereas a too high value indicates item redundancy.29 Corrected item-total correlations (rcorr) were also assessed. Psychometric Properties of BCSBQ
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Results
A total of 242 women completed the questionnaire. Their demographic characteristics are summarized in Table 1. The age of the sample covered a wide range (20Y78), with a mean of 41.1 (SD, 11.7) years. They had lived in Australia for a mean of 12.3 (SD, 8.6) years. A majority were married (78.1%), born in India (63.9%), and educated in tertiary level (53.7%) and rated their English proficiency as good or very good (89.3%). All participants answered all 13 items (the 3 subscales) in the instrument, so imputation for missing values was not needed for
Table 1 & Demographic Characteristics of the 242 Participants
Characteristic Age (mean, 41.1 [SD, 11.7] y), y 20Y29 30Y39 40Y49 50Y59 60Y69 Q70 Country (missing: n = 1) India South Africa Fiji Others Language at home (missing: n = 1) Tamil English Others Length of stay in Australia (mean, 12.3 [SD, 8.6] y), y 0Y5 6Y10 11Y15 16Y20 21Y25 Q26 Marital status Single Married/living together Divorced/separated Widowed Education level Never attended school/primary school Secondary school Technical and further education/college Tertiary or above Current employment status Employed, full time Employed, part time Unemployed Retired English proficiency Not at all Little Average Good Very good
n
%
42 76 59 50 12 3
17.4 31.4 24.4 20.7 5.0 1.2
154 63.9 6 2.5 64 26.6 17 7.1 46 19.1 88 36.5 107 44.4 63 62 48 28 21 20
29 12.0 189 78.1 11 4.5 13 5.4 5 2.1 26 10.7 81 33.5 130 53.7 113 46.7 78 32.2 50 20.6 1 0.4 1 0.4 6 2.5 19 7.9 87 36.0 129 53.3
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26.0 25.6 19.8 11.6 8.7 8.3
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Table 2 & Distribution of the Subscale Scores of the 13-Item Indian Breast Cancer Screening Beliefs Questionnaire
Subscale Attitudes toward general health check-ups Knowledge and perceptions about breast cancer Barriers to mammographic screening
Mean
SD
Median
Minimum
Maximum
% at Floor
% at Ceiling
52.5 65.6 65.3
28.4 23.7 21.9
56.3 75 70
0 0 0
100 100 100
5.4 1.7 1.2
6.2 9.9 5.8
the computation of the subscale scores. The distributions of the 3 subscales are summarized in Table 2. All 3 subscales had a range from 0 to 100 and showed some floor (1.2%Y5.4%) and ceiling (5.8%Y9.9%) effects. The CFA of the hypothesized 3-factor structure of the Indian BCSBQ resulted in a # 2 statistic = 269.0 (degrees of freedom [df ] = 62, P G .001), RMSEA = 0.12 (95% confidence interval = 0.10-0.13), SRMR = 0.12, CFI = 0.90, and NNFI = 0.87. A covariance between question 10 (Q10) and Q11 was added to the factor model and resulted in a # 2 statistic = 209.2 (df = 61, P G .001), RMSEA = 0.10 (95% confidence interval, 0.09Y0.12), SRMR = 0.12, CFI = 0.93, and NNFI = 0.91. The final CFA model is shown in Figure 1. Because the prespecified criteria were not satisfied, an EFA was performed. The eigenvalues for the first 5 factors were 5.30, 2.38, 1.79, 0.80, and 0.56. Having examined the scree plot (Figure 2), a 3-factor model was identified, which together explained 72.9% of the total variance. Table 3 shows the rotated factor loadings after varimax rotation. Items that have a rotated factor loading with magnitude equal to or greater than 0.4 within a particular factor were considered to be its major component and are highlighted in Table 3. All items of the knowledge and attitude subscales loaded more heavily on the first and second factors, respectively. The items in the barriers subscale loaded on the third factor; however, 2 items (Q10 and Q11) also had a loading equal to or greater than 0.4 on the first factor. If the 3 factors, respectively, represent the knowledge, attitude, and barriers subscales, the model would be similar to the originally hypothesized 3-factor structure tested in the CFA. The mean scores of the 3 subscales classified by frequency of screening practices and education level are shown in Table 4. For all 3 subscales, the scores were significantly higher in those who had more frequently performed breast awareness/CBEs (all P G .02). Women who had mammograms more frequently
Figure 2 n Scree plot of the exploratory factor analysis.
also obtained a higher score in the attitude subscale. The association between frequency of mammograms and the barriers subscale was insignificant (P = .067). Women with better education levels also had significantly higher scores in the knowledge (P = .001) and barriers (P = .013) subscales. In other words, significant difference was found in 6 of 7 tests of trend regarding the 3 hypothesized associations. The Cronbach’s ! of the 3 subscales ranged from .81 to .91 (Table 5). For the attitude and knowledge subscales, items correlated strongly with their own subscale (all rcorr 9 0.7) but only weakly to moderately with other subscales (all rcorr G 0.5). Comparatively, rcorr between the barriers subscale and its items were smaller, ranging from 0.47 to 0.77, but 2 items (Q10 and Q11) had a correlation of 0.47 with the knowledge subscale.
n
Discussion
The current study provides insight into factors that influence breast cancer screening behaviors among immigrant Indian women.
Table 3 & Rotated Factor Loadings of the
Exploratory Factor Analysis of the Indian Breast Cancer Screening Beliefs Questionnaire Factor Loadings
Items Attitudes toward general health check-ups Q1 Q2 Q3 Q4 Knowledge and perceptions about breast cancer Q5 Q6 Q7 Q8 Barriers to mammographic screening Q9 Q10 Q11 Q12 Q13
Factor 1 Factor 2 Factor 3
0.22 0.19 0.17 0.11
0.85 0.89 0.86 0.87
j0.02 j0.01 0.14 0.11
0.88 0.86 0.89 0.79
0.19 0.20 0.14 0.11
0.02 0.07 0.12 0.22
0.06 0.44 0.48 0.12 0.08
j0.02 0.28 0.20 0.07 0.01
0.75 0.52 0.44 0.89 0.88
Bold data indicates a factor loading of 0.4 or above, which means the item is regarded as being loaded on the corresponding factor.
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Table 4 & Construct Validity of the Indian Breast Cancer Screening Beliefs Questionnaire
n (%) Breast awareness (missing: n = 4) At least once a month Once every few months Once a year Never P Clinical breast examination (missing: n = 7) e1 91 G 2 y 2-3 y 93 y Never had one P for trend Mammogram (missing: n = 8) Once a year Once every 2 y Once every Q3 y Never had one P Education level Never attended school Primary school Secondary school Technical and further education/college P for trend
Knowledge and Perceptions About Breast Cancer
Barriers to Mammographic Screening
Mean (SD)
Mean (SD)
Mean (SD)
58 42 55 83
(24.4) (17.6) (23.1) (34.9)
66.7 (26.7) 60.3 (27.5) 53.6 (26.2) 39.2 (25.6) G.001
76.4 (20.3) 72.8 (18.5) 60.6 (26.3) 59.2 (22.5) G.001
73.2 (18.9) 69.0 (14.8) 66.1 (23.5) 58.9 (23.2) G.001
49 28 14 21 123
(20.9) (11.9) (6.0) (8.9) (52.3)
64.7 (24.7) 61.8 (22.8) 57.6 (20.1) 51.8 (27.0) 45.9 (30.2) G.001
71.9 (18.8) 62.9 (24.6) 78.6 (17.6) 71.1 (28.4) 62.0 (23.9) 0.019
78.1 (15.5) 74.8 (12.4) 63.6 (25.5) 64.3 (26.3) 58.9 (21.4) G.001
16 27 20 171
(6.8) (11.5) (8.5) (73.1)
65.2 (22.7) 67.1 (17.0) 53.8 (28.1) 49.3 (29.5) .010
68.0 (23.5) 63.7 (24.0) 71.9 (18.2) 65.4 (24.2) .727
80.9 (16.0) 74.4 (12.7) 53.8 (25.6) 64.0 (21.6) .067
5 26 81 130
(2.1) (10.7) (33.5) (53.7)
42.5 (22.3) 44.7 (27.8) 52.8 (28.7) 54.2 (28.5) .220
63.8 (16.2) 54.8 (23.8) 59.2 (24.6) 71.8 (21.7) G.001
47.0 (14.8) 65.4 (18.6) 60.2 (24.4) 69.1 (20.2) .013
Although our sample included women too young to be recommended for mammographic screening, the BCSBQ is none the less relevant because the peak incidence of breast cancer is among younger Indian women aged between 40 and 49 years.3 It is therefore important to understand the current cohort’s attitudes, beliefs, and knowledge regarding breast cancer and early detection practices, because these have direct impact on their later mammographic screening behaviors. Furthermore, it is vital to explore factors affecting the performance of breast awareness measures and also the frequency of CBEs among women younger than 50 years who are not eligible for mammographic screening.6 The 3-factor model could not be confirmed by the CFA. However, the EFA identified a model in which the 3 factors were similar to those originally hypothesized, that is, the 3 subscales. The only difference was that 2 items (Q10 and Q11) were double loaded in the first and third factors. These 2 items in the barriers subscales appeared to be related to the knowledge subscale, namely, Q10: ‘‘It would be difficult to arrange transportation for getting a mammogram’’ and Q11: ‘‘I don’t want to have a mammogram because I can’t speak English.’’ This was indicated by their substantial loadings on not only the barriers subscale but also the knowledge subscale (0.44 and 0.48) in the EFA, as well as the moderate corrected item-total correlations (both 0.47) with the knowl-
Psychometric Properties of BCSBQ
Attitudes Toward General Health Check-ups
edge subscale. Studies suggest that transportation and lack of English proficiency are often identified as barriers to screening among women from minority cultures.30Y32 Having easily available transportation often enables women to become socially active, but conversely its absence inhibits participation in social activities and thus indirectly limits exposure to health information and screening services. This would seem to be indicated by a previous study among Chinese women, which found that participation in community organizations was a means of exposing individuals to information about screening services.30 As far as lack of English proficiency is concerned, this often discourages women from using public transport and naturally also inhibits them from accessing or understanding health information. This is consistent with studies that have indicated a positive association between breast cancer knowledge and English proficiency31,32 among women from CALD backgrounds. Nevertheless, we note that the majority of the participants (89.3%) had either good or very good English proficiency, and this may have impacted on the factor analysis. That warrants a further validation study using a larger sample with a greater variation in English proficiency to confirm the factor structure. While there were some floor and ceiling effects in the subscales of the Indian BCSBQ, the proportion of such responses was not substantial (G10%), and thus, their effects were not
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Table 5 & Cronbach’s ! and Corrected Item-Total Correlation for the Subscales of the Indian Breast Cancer Screening Beliefs Questionnaire
Item
Attitudes Toward General Health Check-ups
Knowledge and Perceptions About Breast Cancer
Barriers to Mammographic Screening
.91
.91
.81
.77 .83 .80 .80
.36 .34 .36 .30
.16 .17 .28 .23
.36 .38 .33 .29
.80 .82 .84 .72
.29 .33 .37 .42
.06 .36 .29 .15 .10
.18 .47 .47 .25 .21
.53 .54 .47 .77 .70
Cronbach’s ! Attitudes toward general health check-ups Q1 Q2 Q3 Q4 Knowledge and perceptions about breast cancer Q5 Q6 Q7 Q8 Barriers to mammographic screening Q9 Q10 Q11 Q12 Q13
significant. The Cronbach’s !’s ranged from .81 to .91, indicating that the questionnaire had good internal consistency reliability under each of the 3 subscales with no indication of overlap among the items. The internal consistency was also supported by the results of the corrected item-total correlations. This is similar to the original version, which was used to test attitudes and knowledge among Chinese Australian women.22 Demonstrating that the Indian BCSBQ also had good construct validity is that the 3 hypothesized associations were significant and in the expected direction in 6 of 7 tests of trend. As was the case with the Chinese version of BCSBQ,22 the attitude subscale showed significant associations with all breast cancer screening practices. This is supported by the claim that being asymptomatic is a key factor deterring CALD women from engaging in screening practices.10,12,16 Knowledge and perceptions about the breast cancer scale were, however, not significantly associated with CBE and mammography. The lack of significance indicates that increasing knowledge alone may not be effective in promoting screening practices in this population. Rather, related factors such as attitudes toward health check-ups and perceived barriers to mammography appear to be more influential in determining women’s screening behaviors. It was evident that the barriers to the mammographic screening subscale were significantly associated with breast awareness and CBE but not with mammogram. The perceived barriers to mammogram were much less evident among women who engaged in breast awareness and CBE. This could be explained by the fact that early exposure to screening practices such as breast awareness and CBE could enhance their participation of mammograms in later life. The study had a number of limitations. The generalization is limited by the fact that this convenience sample was drawn mainly
from Indian community organizations and churches. Thus, socially isolated women, for example, were very likely underrepresented. Moreover, 11 questionnaires were eliminated, and it cannot be assumed that their responses would have been the same. Furthermore, the study utilized self-reported measures of breast cancer screening practices that could have been overreported or underreported. Further studies with adequate verification of selfreported information built into their design are warranted.
n
Conclusion
We conclude that BCSBQ is a culturally appropriate, valid, and reliable instrument for assessing Indian women’s beliefs, knowledge, and attitudes about breast cancer and breast cancer screening practices. It can be used to provide insights into the development and assessment of culturally sensitive breast health education programs. ACKNOWLEDGMENT
The authors thank the Indian organizations and Indian Australian women who participated.
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Psychometric Properties of BCSBQ
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screening: findings from a community based sample in the United States. Asian Pac J Cancer Prev. 2014;15(20):8719Y8724. Kwok C, Sullivan G. The influence of traditional Chinese beliefs on cancer screening behaviours among Chinese-Australian women. J Adv Nurs. 2006; 54(6):691Y669. Wang B, He M, Engelgau MM, Zhao W, Wang L. Breast cancer screening among adult women in China, 2010. Prev Chronic Dis. 2013;10:E183. Liang W, Yuan E, Mandelblatt JS, Pasick RJ. How do older Chinese women view health and cancer screening? Results from focus groups and implications for interventions. Ethn Health. 2004;9(3):283Y304. Daley CM, Kraemer-Diaz A, James AS, et al. Breast cancer screening beliefs and behaviours among American Indian women in Kansas and Missouri: a qualitative inquiry. J Cancer Educ. 2012;27(1 suppl):S32YS40. Kwok C, Fethney J, White K. Chinese Breast Cancer Screening Beliefs Questionnaire: development and psychometric testing with Chinese-Australian women. J Adv Nurs. 2010;66(1):191Y200. Australian Bureau of Statistics, 2012. Year of the book, Australia. http:// www.abs.gov.au/ausstats/[email protected]/mf/1301.0. Accessed December 5, 2014. Burns N, Grove SK. The Practice of Nursing Research: Conduct, Critique and Utilization. 5th ed. Philadelphia, PA: WB Saunders; 2005. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6:1Y55.29. Hu LT, Bentler PM. Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol Methods. 1998;3: 424Y453. Brown TA. Confirmatory Factor Analysis for Applied Research. New York: Guilford Press; 2006. Cuzick JA. Wilcoxon-type test for trend. Stat Med. 1985;4:87Y90. Streiner DL, Norman GR. Health Measurement Scales: A Practical Guide to Their Development and Use. 3rd ed. Toronto, ON, Canada: Oxford University Press; 2003. Kwok C, Cant R, Sullivan G. Factors associated with mammographic decisions of Chinese-Australian women. Health Educ Res. 2005;20(6): 739Y747. Kim JH, Menon U. Pre- and post-intervention differences in acculturation, knowledge, beliefs, and stages of readiness for mammograms among Korean American women. Oncol Nurs Forum. 2009;36(2):E80YE92. Perera JC, Peiris V, Wickramasinghe DP, de Zoysa I. Predictors in breast cancer screening behaviors of South Asian women [published online ahead of print February 27, 2014]. In: Asia Pac J Clin Oncol. 2014.
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Cannas Kwok, PhD Rona Pillay, MEd Chun Fan Lee, PhD
Psychometric Properties of the Breast Cancer Screening Beliefs Questionnaire Among Women of Indian Ethnicity Living in Australia K E Y
W O R D S
Background: Indian women have been consistently reported as having low
Breast cancer screening
participation in breast cancer screening practices. A valid and reliable instrument to
Cultural sensitive
explore their breast cancer beliefs is essential for development of interventions to
Indian women
promote breast cancer screening practices. Objective: The aim of this study was to
Psychometric properties
report the psychometric properties of the Breast Cancer Screening Beliefs
Validation
Questionnaire (BCSBQ) in an Indian community in Australia. Methods: A convenience sample of 242 Indian Australian women was recruited from Indian community organizations and personal networking. Explanatory factor analysis was conducted to study the factor structure. Clinical validity was examined by Cuzick’s nonparametric test, and Cronbach’s ! was used to assess internal consistency reliability. Results: Exploratory factor analysis showed a similar fit to the hypothesized 3-factor structure. The frequency of breast cancer screening practices was significantly associated with attitudes toward general health check-up. Knowledge and perceptions about the breast cancer scale were not significantly associated with clinical breast examinations and mammography. Perceived barriers to mammography were much less evident among women who engaged in breast awareness and clinical breast examination. Results indicated that the BCSBQ had satisfactory validity and internal consistency. Cronbach’s ! of the 3 subscales ranged from .81 to .91. Conclusions: The BCSBQ is a culturally appropriate, valid, and reliable instrument for assessing the beliefs, knowledge, and attitudes about breast
Author Affiliations: School of Nursing and Midwifery, University of Western Sydney, New South Wales, Australia (Dr Kwok and Ms Pillay); and Department of Biostatistics, Singapore Clinical Research Institute (Dr Lee). The authors have no funding or conflicts of interest to disclose.
Correspondence: Cannas Kwok, PhD, School of Nursing and Midwifery, University of Western Sydney, Locked Bag 1797, Penrith 2751, New South Wales, Australia ([email protected]). Accepted for publication June 8, 2015. DOI: 10.1097/NCC.0000000000000294
E24 n Cancer NursingTM, Vol. 39, No. 4, 2016 Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.
Kwok et al
cancer and breast cancer screening practices among women of Indian ethnic extraction living in Australia. Implication for Practice: The BCSBQ can be used to provide nurses with information relevant for the development of culturally sensitive breast health education programs.
W
hile worldwide breast cancer incidence rates are increasing, the steepest increases are in developing countries such as India,1 where over the last decade breast cancer morbidity has overtaken that of cervical cancer.2 Despite having a lower incidence of breast cancer than white women, Indian women are more likely to be diagnosed at younger ages and at later stages and to have disproportionate mortality rates.3 Similarly, compared with white women in developed countries such as the United States, the United Kingdom, and Australia, where 5-year survival rates for breast cancer are 85% to 89%,4 survival rates among Indian women are only 51%.3 Given that the causes of breast cancer remain largely unknown, in many Western countries, preventive measures such as encouraging breast awareness and performing clinical breast examinations (CBEs) and mammography are widely promoted.5 However, women from culturally and linguistically diverse (CALD) backgrounds living in Australia,6 the United States,7 and the United Kingdom8 are consistently reported as having markedly lower mammographic screening rates compared with white women. While in 2009, 67.8% of white women in the United States had at least 1 mammogram over a 2-year period, the rate among Indian American women aged 52 to 64 years was only 52%, the lowest of any ethnic group.9 Although there has been considerable research into breast cancer screening behaviors among CALD women in Western countries,10Y12 little is known about Indian women in this regard. Studies by Filippi et al13 and Tolma et al14 reveal that IndoAmerican women have little knowledge about screening practices and breast cancer risks. Furthermore, a study by Grunfeld and Kohli15 has demonstrated that because some Indian women hold negative beliefs about breast cancer, they do not perceive themselves to be at high risk and do not see any need to have mammograms. These findings are consistent with those of studies by Kwok and Sullivan16 among Chinese and South Asian women in Australia.17 Culturally based beliefs about breast cancer common among CALD women have a profound impact on their screening behaviors.12,17 Literature suggests that cultural beliefs among women from Indian and Chinese backgrounds have similar effects.14,18Y20 For example, some Indian women, like their Chinese counterparts,18 are reluctant to commit to breast screening because of a fatalistic belief that nothing can be done to avoid or treat breast cancer.14 Moreover, because preventive medicine or early detection measures are not a priority in China19 and India,3 attending preventive health services is foreign to Chinese and Indian immigrants in Western countries. This would account for the fact that as studies have demonstrated women from Chinese20 and Indian21 backgrounds seldom present themselves for cancer screening when they are asymptomatic. In addition, as is the case with women from Chinese cultures,16 fears of diagnosis and
Psychometric Properties of BCSBQ
embarrassment have been identified as key factors discouraging Indian women from participating in mammography.15 The Chinese Breast Cancer Screening Beliefs Questionnaire (BCSBQ) was originally designed as a culturally sensitive instrument to assess Chinese Australian women’s knowledge of and attitudes toward breast cancer and screening practices and also to determine what barriers discourage them from undertaking these screening practices. The instrument was first developed in English and then translated into Chinese. Demonstrated to be valid and reliable22 and renamed the ‘‘Breast Cancer Screening Beliefs Questionnaire,’’ it was adapted to investigate the situation prevailing among other cultural groups, including those of Indian ethnic origin. This study forms part of a larger investigation of Indian Australian women’s beliefs, knowledge of, and attitudes toward breast cancer and screening practices in Australia. It should be said that Indians constitute 1 of the fastest-growing CALD groups in Australia.23 The aim of this study was to assess and report the psychometric performance of the BCSBQ on the grounds that a valid and reliable instrument to explore breast cancer beliefs is essential for the development of interventions to promote breast cancer screening practices among Indian women.
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Methods
Participants and Recruitment The target population was Indian Australian women 18 years or older, residing in Sydney, Australia, with no history of breast cancer. The term Indian Australian women refers to any female of Indian ancestry who migrated to Australia. The study was granted approval by the Human Ethics Committee of University of Western Sydney.
Data Collection In 2013, a convenience sample of Indian Australian women was recruited from Indian organizations including churches, social and community centers, festival groups, and also through personal networking. With the assistance of the leaders of organizations, female members were invited to participate in the study. The second author, who is of Indian background, attended women’s meetings to explain the details of the study, the method of administration, and the risks and benefits of participation. Women were given a written participant information statement and were invited to ask questions. Those who agreed to participate could choose to fill out the questionnaire and return it either immediately or through the mail. The questionnaire required 15 to 20 minutes to complete. Cancer NursingTM, Vol. 39, No. 4, 2016
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Instrument The BCSBQ contains 13 items in 3 subscales: (1) attitudes toward general health checkups with a subscale of 4 items that explores whether women had general health checkups in the absence of signs and symptoms; (2) knowledge and perceptions about breast cancer (4 items), which explores cultural beliefs relating to breast cancer; and (3) barriers to mammographic screening practices (5 items), which explore personal and practical issues perceived by women to hinder their participation in breast cancer screening. For simplicity, these are hereafter referred to as attitude, knowledge, and barriers subscales, respectively. Respondents gave ratings for each item within a subscale along a 5-point Likert scale ranging from ‘‘strongly agree’’ (score of 1) to ‘‘strongly disagree’’ (score of 5). Because of the wording of the items, responding either ‘‘disagree’’ or ‘‘strongly disagree’’ was taken to indicate a more proactive approach toward general health checkups, more accurate knowledge about breast cancer, and less perceived barriers to participating in mammographic screening practices. A brief description of the items is illustrated in Figure 1. A pilot group of 10 Indian Australian women with various background criteria (eg, length of stay in Australia, age, and edu-
cational level), who were asked to comment on the clarity, comprehensibility, and readability of the questionnaire, did not report any problems. The BCSBQ also contains items specific to demographic variables such as age, length of time in Australia, English-language proficiency, and education levels. Information was also collected on participants’ breast cancer screening practices. This involved asking women if they had ever heard of the concept of breast awareness (knowing the normal look and feel of their breasts, without needing to apply a special technique), CBE, and mammograms and, if so, how regularly they self-examined or had clinical examinations and/or mammograms.
Sample Size There is no generally agreed consensus as to the minimum sample size for factor analysis. Burns and Grove24 recommend 5 to 10 participants per item. We intended to recruit the maximum number for each of the 13 items in the BCSBQ, which meant recruiting 130 women. To obtain an adequate final sample size, 388 women were invited to participate in the study, 255 of whom returned the questionnaire, giving a response rate of 66%.
Figure 1 n Path diagram of a confirmatory factor analysis of the Indian Breast Cancer Screening Beliefs Questionnaire. The Values correspond to the standardized estimates. E26 n Cancer NursingTM, Vol. 39, No. 4, 2016 Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.
Kwok et al
Thirteen women were excluded, 2 women because they had a history of breast cancer, whereas 11 women failed to complete the questionnaire (the 3 subscales), thus giving a final sample size of 242. This represented an acceptable sample size for both confirmatory factor analysis and exploratory factor analysis (EFA).
Statistical Analysis The 3 subscale scores of the Indian BCSBQ were computed in the same way the Chinese version was scored.22 Missing values would be imputed by the half-rule, that is, the mean of the responses in the same subscale if at least half of the items in that subscale were answered and valid. Participants’ demographic characteristics and the distribution of the subscale scores of the instrument were summarized using descriptive statistics. Proportions of subjects scoring 0 and 100 were computed to assess the floor and ceiling effects. Substantial floor and ceiling effects imply that a 5-point Likert scale might not be sufficient to clearly distinguish the responses at the 2 extremes. We first studied whether the Indian BCSBQ has a 3-factor structure as it was designed; a confirmatory factor analysis (CFA) was performed. Goodness of fit of the factor model was assessed by the fit indices, including the root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), comparative fir index (CFI), and nonnormed fit index (NNFI). These indices addressed the parsimony correction, absolute fit, and comparative or incremental fit, as recommended.25 We followed the common criteria in considering the adequacy of the factor model, that is, RMSEA equal to or less than 0.06, SRMR equal to or less than 0.08, CFI equal to or greater than 0.95, and NNFI equal to or greater than 0.95.26 Addition of covariance between items was made based on the largest modification index if there were doubts about inadequate fit.27 If the factor structure could not be confirmed, an EFA would be conducted. Factors with eigenvalue larger than 1 were retained, and the factor loadings after a varimax rotation would be computed. The final EFA structure would be compared with the originally hypothesized 3-factor structure. Construct validity was then examined by testing 3 hypotheses regarding the association of the subscales with the frequency of screening practices and education level: (1) those who performed breast awareness exercises more frequently or had CBE and mammograms would have a more proactive attitude toward general checkups reflected by a higher score in the attitude subscale; (2) those who had a better education level would be more knowledgeable about breast cancer, thus obtaining a higher score in the knowledge subscale; and (3) having more screening practices was associated with less barriers to mammograms, resulting in a higher score on the barriers subscale. As the frequency of health practices and education level were of ordinal-type data, Cuzick’s28 nonparametric test was used for testing the trend. Item performance of the Indian BCSBQ was then assessed. Internal consistency reliability was evaluated by the Cronbach’s !. A good Cronbach’s ! should be at least .7, but not much higher than .9 because a low value indicates a low degree of homogeneity, whereas a too high value indicates item redundancy.29 Corrected item-total correlations (rcorr) were also assessed. Psychometric Properties of BCSBQ
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Results
A total of 242 women completed the questionnaire. Their demographic characteristics are summarized in Table 1. The age of the sample covered a wide range (20Y78), with a mean of 41.1 (SD, 11.7) years. They had lived in Australia for a mean of 12.3 (SD, 8.6) years. A majority were married (78.1%), born in India (63.9%), and educated in tertiary level (53.7%) and rated their English proficiency as good or very good (89.3%). All participants answered all 13 items (the 3 subscales) in the instrument, so imputation for missing values was not needed for
Table 1 & Demographic Characteristics of the 242 Participants
Characteristic Age (mean, 41.1 [SD, 11.7] y), y 20Y29 30Y39 40Y49 50Y59 60Y69 Q70 Country (missing: n = 1) India South Africa Fiji Others Language at home (missing: n = 1) Tamil English Others Length of stay in Australia (mean, 12.3 [SD, 8.6] y), y 0Y5 6Y10 11Y15 16Y20 21Y25 Q26 Marital status Single Married/living together Divorced/separated Widowed Education level Never attended school/primary school Secondary school Technical and further education/college Tertiary or above Current employment status Employed, full time Employed, part time Unemployed Retired English proficiency Not at all Little Average Good Very good
n
%
42 76 59 50 12 3
17.4 31.4 24.4 20.7 5.0 1.2
154 63.9 6 2.5 64 26.6 17 7.1 46 19.1 88 36.5 107 44.4 63 62 48 28 21 20
29 12.0 189 78.1 11 4.5 13 5.4 5 2.1 26 10.7 81 33.5 130 53.7 113 46.7 78 32.2 50 20.6 1 0.4 1 0.4 6 2.5 19 7.9 87 36.0 129 53.3
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26.0 25.6 19.8 11.6 8.7 8.3
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Table 2 & Distribution of the Subscale Scores of the 13-Item Indian Breast Cancer Screening Beliefs Questionnaire
Subscale Attitudes toward general health check-ups Knowledge and perceptions about breast cancer Barriers to mammographic screening
Mean
SD
Median
Minimum
Maximum
% at Floor
% at Ceiling
52.5 65.6 65.3
28.4 23.7 21.9
56.3 75 70
0 0 0
100 100 100
5.4 1.7 1.2
6.2 9.9 5.8
the computation of the subscale scores. The distributions of the 3 subscales are summarized in Table 2. All 3 subscales had a range from 0 to 100 and showed some floor (1.2%Y5.4%) and ceiling (5.8%Y9.9%) effects. The CFA of the hypothesized 3-factor structure of the Indian BCSBQ resulted in a # 2 statistic = 269.0 (degrees of freedom [df ] = 62, P G .001), RMSEA = 0.12 (95% confidence interval = 0.10-0.13), SRMR = 0.12, CFI = 0.90, and NNFI = 0.87. A covariance between question 10 (Q10) and Q11 was added to the factor model and resulted in a # 2 statistic = 209.2 (df = 61, P G .001), RMSEA = 0.10 (95% confidence interval, 0.09Y0.12), SRMR = 0.12, CFI = 0.93, and NNFI = 0.91. The final CFA model is shown in Figure 1. Because the prespecified criteria were not satisfied, an EFA was performed. The eigenvalues for the first 5 factors were 5.30, 2.38, 1.79, 0.80, and 0.56. Having examined the scree plot (Figure 2), a 3-factor model was identified, which together explained 72.9% of the total variance. Table 3 shows the rotated factor loadings after varimax rotation. Items that have a rotated factor loading with magnitude equal to or greater than 0.4 within a particular factor were considered to be its major component and are highlighted in Table 3. All items of the knowledge and attitude subscales loaded more heavily on the first and second factors, respectively. The items in the barriers subscale loaded on the third factor; however, 2 items (Q10 and Q11) also had a loading equal to or greater than 0.4 on the first factor. If the 3 factors, respectively, represent the knowledge, attitude, and barriers subscales, the model would be similar to the originally hypothesized 3-factor structure tested in the CFA. The mean scores of the 3 subscales classified by frequency of screening practices and education level are shown in Table 4. For all 3 subscales, the scores were significantly higher in those who had more frequently performed breast awareness/CBEs (all P G .02). Women who had mammograms more frequently
Figure 2 n Scree plot of the exploratory factor analysis.
also obtained a higher score in the attitude subscale. The association between frequency of mammograms and the barriers subscale was insignificant (P = .067). Women with better education levels also had significantly higher scores in the knowledge (P = .001) and barriers (P = .013) subscales. In other words, significant difference was found in 6 of 7 tests of trend regarding the 3 hypothesized associations. The Cronbach’s ! of the 3 subscales ranged from .81 to .91 (Table 5). For the attitude and knowledge subscales, items correlated strongly with their own subscale (all rcorr 9 0.7) but only weakly to moderately with other subscales (all rcorr G 0.5). Comparatively, rcorr between the barriers subscale and its items were smaller, ranging from 0.47 to 0.77, but 2 items (Q10 and Q11) had a correlation of 0.47 with the knowledge subscale.
n
Discussion
The current study provides insight into factors that influence breast cancer screening behaviors among immigrant Indian women.
Table 3 & Rotated Factor Loadings of the
Exploratory Factor Analysis of the Indian Breast Cancer Screening Beliefs Questionnaire Factor Loadings
Items Attitudes toward general health check-ups Q1 Q2 Q3 Q4 Knowledge and perceptions about breast cancer Q5 Q6 Q7 Q8 Barriers to mammographic screening Q9 Q10 Q11 Q12 Q13
Factor 1 Factor 2 Factor 3
0.22 0.19 0.17 0.11
0.85 0.89 0.86 0.87
j0.02 j0.01 0.14 0.11
0.88 0.86 0.89 0.79
0.19 0.20 0.14 0.11
0.02 0.07 0.12 0.22
0.06 0.44 0.48 0.12 0.08
j0.02 0.28 0.20 0.07 0.01
0.75 0.52 0.44 0.89 0.88
Bold data indicates a factor loading of 0.4 or above, which means the item is regarded as being loaded on the corresponding factor.
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Kwok et al
Table 4 & Construct Validity of the Indian Breast Cancer Screening Beliefs Questionnaire
n (%) Breast awareness (missing: n = 4) At least once a month Once every few months Once a year Never P Clinical breast examination (missing: n = 7) e1 91 G 2 y 2-3 y 93 y Never had one P for trend Mammogram (missing: n = 8) Once a year Once every 2 y Once every Q3 y Never had one P Education level Never attended school Primary school Secondary school Technical and further education/college P for trend
Knowledge and Perceptions About Breast Cancer
Barriers to Mammographic Screening
Mean (SD)
Mean (SD)
Mean (SD)
58 42 55 83
(24.4) (17.6) (23.1) (34.9)
66.7 (26.7) 60.3 (27.5) 53.6 (26.2) 39.2 (25.6) G.001
76.4 (20.3) 72.8 (18.5) 60.6 (26.3) 59.2 (22.5) G.001
73.2 (18.9) 69.0 (14.8) 66.1 (23.5) 58.9 (23.2) G.001
49 28 14 21 123
(20.9) (11.9) (6.0) (8.9) (52.3)
64.7 (24.7) 61.8 (22.8) 57.6 (20.1) 51.8 (27.0) 45.9 (30.2) G.001
71.9 (18.8) 62.9 (24.6) 78.6 (17.6) 71.1 (28.4) 62.0 (23.9) 0.019
78.1 (15.5) 74.8 (12.4) 63.6 (25.5) 64.3 (26.3) 58.9 (21.4) G.001
16 27 20 171
(6.8) (11.5) (8.5) (73.1)
65.2 (22.7) 67.1 (17.0) 53.8 (28.1) 49.3 (29.5) .010
68.0 (23.5) 63.7 (24.0) 71.9 (18.2) 65.4 (24.2) .727
80.9 (16.0) 74.4 (12.7) 53.8 (25.6) 64.0 (21.6) .067
5 26 81 130
(2.1) (10.7) (33.5) (53.7)
42.5 (22.3) 44.7 (27.8) 52.8 (28.7) 54.2 (28.5) .220
63.8 (16.2) 54.8 (23.8) 59.2 (24.6) 71.8 (21.7) G.001
47.0 (14.8) 65.4 (18.6) 60.2 (24.4) 69.1 (20.2) .013
Although our sample included women too young to be recommended for mammographic screening, the BCSBQ is none the less relevant because the peak incidence of breast cancer is among younger Indian women aged between 40 and 49 years.3 It is therefore important to understand the current cohort’s attitudes, beliefs, and knowledge regarding breast cancer and early detection practices, because these have direct impact on their later mammographic screening behaviors. Furthermore, it is vital to explore factors affecting the performance of breast awareness measures and also the frequency of CBEs among women younger than 50 years who are not eligible for mammographic screening.6 The 3-factor model could not be confirmed by the CFA. However, the EFA identified a model in which the 3 factors were similar to those originally hypothesized, that is, the 3 subscales. The only difference was that 2 items (Q10 and Q11) were double loaded in the first and third factors. These 2 items in the barriers subscales appeared to be related to the knowledge subscale, namely, Q10: ‘‘It would be difficult to arrange transportation for getting a mammogram’’ and Q11: ‘‘I don’t want to have a mammogram because I can’t speak English.’’ This was indicated by their substantial loadings on not only the barriers subscale but also the knowledge subscale (0.44 and 0.48) in the EFA, as well as the moderate corrected item-total correlations (both 0.47) with the knowl-
Psychometric Properties of BCSBQ
Attitudes Toward General Health Check-ups
edge subscale. Studies suggest that transportation and lack of English proficiency are often identified as barriers to screening among women from minority cultures.30Y32 Having easily available transportation often enables women to become socially active, but conversely its absence inhibits participation in social activities and thus indirectly limits exposure to health information and screening services. This would seem to be indicated by a previous study among Chinese women, which found that participation in community organizations was a means of exposing individuals to information about screening services.30 As far as lack of English proficiency is concerned, this often discourages women from using public transport and naturally also inhibits them from accessing or understanding health information. This is consistent with studies that have indicated a positive association between breast cancer knowledge and English proficiency31,32 among women from CALD backgrounds. Nevertheless, we note that the majority of the participants (89.3%) had either good or very good English proficiency, and this may have impacted on the factor analysis. That warrants a further validation study using a larger sample with a greater variation in English proficiency to confirm the factor structure. While there were some floor and ceiling effects in the subscales of the Indian BCSBQ, the proportion of such responses was not substantial (G10%), and thus, their effects were not
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Table 5 & Cronbach’s ! and Corrected Item-Total Correlation for the Subscales of the Indian Breast Cancer Screening Beliefs Questionnaire
Item
Attitudes Toward General Health Check-ups
Knowledge and Perceptions About Breast Cancer
Barriers to Mammographic Screening
.91
.91
.81
.77 .83 .80 .80
.36 .34 .36 .30
.16 .17 .28 .23
.36 .38 .33 .29
.80 .82 .84 .72
.29 .33 .37 .42
.06 .36 .29 .15 .10
.18 .47 .47 .25 .21
.53 .54 .47 .77 .70
Cronbach’s ! Attitudes toward general health check-ups Q1 Q2 Q3 Q4 Knowledge and perceptions about breast cancer Q5 Q6 Q7 Q8 Barriers to mammographic screening Q9 Q10 Q11 Q12 Q13
significant. The Cronbach’s !’s ranged from .81 to .91, indicating that the questionnaire had good internal consistency reliability under each of the 3 subscales with no indication of overlap among the items. The internal consistency was also supported by the results of the corrected item-total correlations. This is similar to the original version, which was used to test attitudes and knowledge among Chinese Australian women.22 Demonstrating that the Indian BCSBQ also had good construct validity is that the 3 hypothesized associations were significant and in the expected direction in 6 of 7 tests of trend. As was the case with the Chinese version of BCSBQ,22 the attitude subscale showed significant associations with all breast cancer screening practices. This is supported by the claim that being asymptomatic is a key factor deterring CALD women from engaging in screening practices.10,12,16 Knowledge and perceptions about the breast cancer scale were, however, not significantly associated with CBE and mammography. The lack of significance indicates that increasing knowledge alone may not be effective in promoting screening practices in this population. Rather, related factors such as attitudes toward health check-ups and perceived barriers to mammography appear to be more influential in determining women’s screening behaviors. It was evident that the barriers to the mammographic screening subscale were significantly associated with breast awareness and CBE but not with mammogram. The perceived barriers to mammogram were much less evident among women who engaged in breast awareness and CBE. This could be explained by the fact that early exposure to screening practices such as breast awareness and CBE could enhance their participation of mammograms in later life. The study had a number of limitations. The generalization is limited by the fact that this convenience sample was drawn mainly
from Indian community organizations and churches. Thus, socially isolated women, for example, were very likely underrepresented. Moreover, 11 questionnaires were eliminated, and it cannot be assumed that their responses would have been the same. Furthermore, the study utilized self-reported measures of breast cancer screening practices that could have been overreported or underreported. Further studies with adequate verification of selfreported information built into their design are warranted.
n
Conclusion
We conclude that BCSBQ is a culturally appropriate, valid, and reliable instrument for assessing Indian women’s beliefs, knowledge, and attitudes about breast cancer and breast cancer screening practices. It can be used to provide insights into the development and assessment of culturally sensitive breast health education programs. ACKNOWLEDGMENT
The authors thank the Indian organizations and Indian Australian women who participated.
References 1. Anderson BO, Jakesz R. Breast cancer issues in developing countries: an overview of the breast health global initiative. World J Surg. 2008;32: 2579Y2585. 2. Indian Council of Medical Research. National Centre for Disease Informatics and Research. Bangalore, India; 2014. http://www.pbcrindia.org/. Accessed December 9, 2014.
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