Qual Life Res (2015) 24:399–404 DOI 10.1007/s11136-014-0768-7
BRIEF COMMUNICATION
The Caregiver Quality of Life Index–Cancer (CQOLC) in Singapore: a new preliminary factor structure for caregivers of ambulatory patients with cancer Rathi Mahendran • Haikel A. Lim • Joanne Chua • Chao Xu Peh • Siew Eng Lim Ee Heok Kua
•
Accepted: 24 July 2014 / Published online: 6 August 2014 Ó Springer International Publishing Switzerland 2014
Abstract Purpose The Caregiver Quality of Life Index–Cancer (CQOLC) is used worldwide to determine levels of quality of life of caregivers of patients with cancer; however, the few studies examining the underlying factor structure of the CQOLC have revealed differences between Western and Eastern cultures. This study sought to confirm the differences in the factor structures between the original CQOLC and a Taiwanese (Mandarin) version. Methods A total of 183 caregivers from a cancer center in Singapore participated in this exploratory cross-sectional study. All participants completed the CQOLC and a sociodemographic form; 30 participants repeated the CQOLC two weeks later. Results Test–retest reliability was adequate for the CQOLC; however, confirmatory factor analyses did not support either the original four-factor model or the Taiwanese five-factor model. Exploratory factor analyses suggested the retaining of five factors to form a 25-item
R. Mahendran (&) J. Chua E. H. Kua Department of Psychological Medicine, National University Hospital, NUHS Tower Block, Level 9, 1E Kent Ridge Road, Singapore 119228, Singapore e-mail: [email protected] R. Mahendran H. A. Lim C. X. Peh E. H. Kua Department of Psychological Medicine, National University of Singapore, NUHS Tower Block, Level 9, 1E Kent Ridge Road, Singapore 119228, Singapore e-mail: [email protected] S. E. Lim Department of Haematology-Oncology, National University Cancer Institute, Singapore (NCIS), National University Health System, NUHS Tower Block, Level 7, 1E Kent Ridge Road, Singapore 119228, Singapore
Singapore version (CQOLC-S25): burden, physical/practical concerns, emotional reactivity, self-needs, and social support. Inter-factor and factor scale correlations were positively significant for all factors except Support, which was negatively correlated with emotional reactivity and self-needs. Conclusions Cross-cultural differences, which require further investigations, appear to underlie the utility and understanding of the CQOLC. More research is needed to better understand the needs of Singapore caregivers. Keywords Caregivers Cancer Quality of life Singapore CQOLC
Introduction Cancer is a major cause of worldwide mortality and morbidity; in Singapore, an island state in Southeast Asia, cancer is the leading cause of deaths (30 % of total deaths in 2011) [1]. Caregivers, as primary providers of support, face the impact of the illness with consequent poorer quality of life [2]. There is therefore a need to determine the levels of, and deficiencies in, these caregivers’ quality of life (QOL) to better support them through the cancer journey. The Caregiver Quality of Life Index–Cancer in Asia The Caregiver Quality of Life Index–Cancer (CQOLC) [3] is one of the more widely used instruments holistically measuring the QOL of caregivers of cancer patients (hereafter referred to as caregivers). Developed in 1997 in the United States [4], the CQOLC is one of the few recommended instruments in measuring caregivers’ QOL [5]
123
400
in studies of caregivers of both curative and palliative mixed-cancer patients [6, 7]. The CQOLC has been shown to be psychometrically sound in Western societies like France and Turkey [8, 9], and the original US version has demonstrated an underlying factor structure of four domains: burden, disruptiveness, positive adaptation, and financial concerns [10]. In Asia, the CQOLC has been translated into Mandarin and Korean [11, 12]; the Mandarin version, studied in a sample of Taiwanese caregivers of palliative cancer patients, differs in its underlying factor structure [11]: in place of positive adaptation, there are, instead, factors of social support and spiritual well-being. Further, some of the items (e.g., satisfaction with sexual functioning) were found to be unsuitable for a conservative Asian society. Unfortunately, these results have not yet been replicated nor has this factor structure been validated. The present study This study therefore sought to uncover the underlying factor structure in Singapore. It was hypothesized that, in a sample of Singapore caregivers of ambulatory patients with cancer, the CQOLC would (a) not fit the original fourfactor model, but instead, because of cultural similarities, (b) fit the Taiwanese five-factor model.
Qual Life Res (2015) 24:399–404 Table 1 Demographics of the present sample Demographic category
Participants and procedures Between August 2012 and January 2013, a trained research assistant invited caregivers of patients in the outpatient medical oncology clinic at the National Cancer Institute of Singapore (NCIS) to participate in this study during their patients’ appointments at the outpatient clinic. Caregivers were included if they were aged between 21 and 64 years, proficient in either English or Mandarin, and no past history of cancer; caregivers were excluded if they were illiterate. The study was approved by the National Healthcare Group Domain Specific Review Board A (reference: 2012/00193). Because Singapore is a bilingual society, the final pool of 183 caregiver participants (87 % response rate) were given a basic demographic questionnaire and the option to complete the CQOLC in their preferred master language (i.e., CQOLC for English, and the CQOLC-M for Mandarin [11]; both are national languages and our preliminary analyses with a larger dataset of an ongoing study have shown no significant differences between the scores of those completing the English and Mandarin versions of the CQOLC). The CQOLC is a 35-item self-report measure of caregivers’ QOL measured on a five-point Likert-type
123
%
Age \21
3
2
21–30
31
17
31–40
37
20
41–50
46
25
51–60
27
15
[60
29
22
139
76
Malay
29
16
Indian Othersa
8 7
4 4
5
3
Primary
24
13
Secondary
60
33
Tertiary
93
51
70
39
Ethnicity Chinese
Education No formal education
Relationship with patient Spouse Sibling
9
5
84
46
Grandchild
1
1
Niece/nephew
5
3
13
7
Early
83
46
Advanced Unsure
77 21
42 12
Child
Othersb
Methods
n
Care recipients’ cancer staging
a
This included ethnic groups like Eurasians and ethnic dialect groups
b
These were mainly in-laws and friends/long-term partners
scale from 0 (not at all) to 4 (very much) with a maximum score of 140. This score is obtained by summing the item scores, higher scores denote better QOL. The CQOLC takes about 20 min to complete. Item 4 (satisfaction with sexual functioning) was excluded from these calculations because there were missing data (due to the sensitivity of such a question in Singapore’s conservative Asian society). After completing and returning the questionnaire, to determine test–retest reliability, the research assistant gave all participants another identical questionnaire and instructed them to complete it at home on a specific date two weeks later and post it via a self-return envelope. We received 30 (16 %) completed CQOLC questionnaires and verified (by checking the postmarks) that none had sent it before the date specified on their questionnaire. The demographics of the sample are presented in Table 1. The majority of the participants were between 41 and 50 years of age (25 %), women (57 %), and of Chinese
Qual Life Res (2015) 24:399–404
401
ethnicity (76 %). Half of the participants had tertiary education (50 %) and more than three-quarters were English speaking (79 %). The majority were either children (46 %) or spouses (38 %) of their care recipient. There were an almost equal proportion of early (46 %) and advanced stage (42 %) care recipients.
suggested that the CQOLC in a sample of Singapore caregivers had a different underlying factor structure; as such, this was subsequently investigated via exploratory factor analyses.
Data analyses
The simultaneous use of Cattell’s scree plot and Horn’s parallel analyses were adopted to avoid under-factoring [20]. The results of the first iteration suggested retaining five factors, which were then extracted via a common factor analysis with a Promax oblique rotation. Only items that met the following criteria were retained: (a) had a significant primary factor loading of C.40 [21]; (b) did not have a secondary loading of C.32, or having a difference of \.15 from the primary loading [22]; and (c) there were at least three items in the factor [23]. Of the 34 items, 9 that failed to meet these criteria over four iterations were removed: items 7 (concern about insurance), 8 (economic future), 10 (outlook on life), 11 (level of stress), 12 (spirituality), 14 (sadness), 16 (social support), 27 (focus of caregiving), and 35 (family interest in caregiving). The fifth confirmatory iteration produced a rotated solution with 25 items over five factors (CQOLC-S25), as presented in Table 2, and communalities of C.20. The reliability coefficients for the total scale and Factors 1–4 ranged from .75 to .89 and fell within the range for good internal consistency [24]; the reliability coefficient for Factor 5 was somewhat wanting at .60, but the removal of items did not improve Cronbach’s alpha. The five extracted factors of the CQOLC-S25 were subsequently reviewed and labeled. Factor 1 (8 items), similar to the Taiwan and US versions, was determined to be ‘‘burden’’; factor 2 (5 items) was labeled ‘‘physical/ practical concerns’’; factor 3 (4 items) was termed ‘‘emotional reactivity’’; factor 4 (4 items) was considered ‘‘selfneeds’’; and factor 5 (4 items), similar to the Taiwan and US versions, was labeled ‘‘social support.’’ A comparison of the item loadings on the Taiwan and US version subscales are presented in Table 2. Bivariate correlations revealed that all except the social support was correlated to the total CQOLC-S25 score, rs(181–183) = .66–.89, all ps \ .001. Social support, however, was correlated with two other factors, namely emotional reactivity, and self-needs, rs(181–182) = -.14–.21, ps = .005–.044. Table 3 presents the descriptives and correlations of the CQOLC-S25.
The sample size for the subsequent analyses was sufficient: the estimated minimum sample size adequate for factor analyses was calculated to be 170 (based on a minimum of five participants per variable) [13, 14], and for test–retest reliability, 30 (a = .05, b = .20) [15, 16]. Statistical analyses were conducted using IBM SPSS Statistics version 20 (Chicago, IL). Pearson’s correlations were employed to determine test–retest reliability, and the relationship between different factors. In order to ascertain whether the present data fit either the original or Taiwanese factor structures, confirmatory factor analyses (CFA) were conducted using SPSS AMOS. Goodness of fit model was examined using five indices: (a) a non-significant v2; (b) root-mean-square-error of approximation (RMSEA) below .08; (c) goodness of fit index (GFI) above .90; (d) adjusted goodness of fit index (AGFI) above .85; and (e) comparative fit index (CFI) above .90 [17–19]. Based on modification indices, error variance parameters were allowed to covary if they were under the same factor. Additional criteria and tests employed are detailed in the following section.
Results Reliability and internal consistency Cronbach’s alpha of the entire CQOLC was .89 for both the first and second administration. There was good test–retest reliability: Pearson’s correlation coefficient was .79, p \ .001. Because these two measures suggested that the CQOLC was reliable in this sample, subsequent CFA were conducted. Confirmatory factor analyses Both the proposed models (original four-factor and Taiwan five-factor) were tested. Results showed only a marginal to moderate fit for the original 4 factor model, v2(293, 209) = 425.71, p \ .001, RMSEA = .06, GFI = .81, AGFI = .75, CFI = .91. However, unexpectedly, the results also only showed a marginal to moderate fit for the Taiwan five-factor model, v2(403, 209) = 577.21, p \ .001, RMSEA = .06, GFI = .78, AGFI = .73, CFI = .90. This
Exploratory factor analyses
Discussion This study is the first to suggest a culturally variable factor structure in caregivers of ambulatory cancer patients in
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Qual Life Res (2015) 24:399–404
Table 2 Factor loading matrix for the final iteration and item loading on CQOLC-S25 compared with Taiwan and US version subscales Item number and descriptiona
Factor 1
Factor 2
Factor 3 Factor 4 Factor 5
Taiwan factor
US factor
19. I feel nervous
.926
-.094
-.025
.035
-.033
Burden
Burden
18. I feel frustrated
.834
-.045
-.023
.081
.075
Burden
Burden
17. I feel guilty
.676
-.098
.056
.086
.165
Burden
Burden
20. I worry about the impact my loved one’s illness has had on my children or other family members
.674
.022
-.001
-.094
-.348
Burden
Burden
15. I feel under increased mental strain
.601
.196
.231
-.206
.040
Burden
–
33. I am discouraged about the future
.549
-.007
.170
.038
.065
Burden
Burden
21. I have difficulty dealing with my loved one’s changing eating habits
.520
.134
-.190
.173
-.117
Disruptiveness
Disruptiveness
13. It bothers me, limiting my focus to day-today.
.486
.382
.081
-.001
.125
Burden
–
3. My daily life is imposed upon
-.077
.845
-.051
.080
.040
Disruptiveness
Disruptiveness
2. My sleep is less restful 1. It bothers me that my daily routine is altered
.028 -.120
.845 .728
.081 -.032
-.217 .219
.076 .014
Disruptiveness Disruptiveness
– Disruptiveness
.101
.676
-.167
.039
-.143
–
Disruptiveness
5. It is a challenge to maintain my outside interests 6. I am under a financial strain
.136
.463
.011
.065
.040
31. It upsets me to see my loved one deteriorate
.008
-.004
.744
-.058
-.134
9. I fear my loved one will die
Financial concerns
Financial concerns
Burden
Burden
.039
-.045
.684
-.029
.081
Burden
Burden
-.032
-.009
.541
.318
.025
Disruptiveness
–
.148
-.112
.528
.055
-.031
Burden
Burden
-.044
.057
.023
.707
-.088
Disruptiveness
Disruptiveness
30. The need to protect my loved one bothers me
.013
.004
.073
.683
.055
Disruptiveness
–
24. It bothers me that I need to be available to chauffeur my loved one to appointments
.266
-.014
-.117
.663
.051
Disruptiveness
Disruptiveness
26. The responsibility I have for my loved one’s care at home is overwhelming
.009
.121
.288
.406
-.089
Disruptiveness
Disruptiveness
22. I have developed a closer relationship with my loved oneb
.028
-.130
-.185
.032
.638
Social support
Positive adaptation
23. I feel adequately informed about my loved one’s illness.b
.000
.020
.235
-.010
.619
Social support
–
.149
-.057
-.150
-.096
.557
Social support
Positive adaptation
-.122
.279
-.034
.048
.469
Social support
Positive adaptation
32. The need to manage my loved one’s pain is overwhelming 25. I fear the adverse effects of treatment on my loved one 29. It bothers me that my priorities have changed
28. Family communication has increasedb 34. I am satisfied with the support I get from my familyb
Bolded items assist readers in identifying the items that load onto the different factors Factor 1 = Burden, Factor 2 = Physical/practical concerns, Factor 3 = Emotional reactivity, Factor 4 = Self-needs, Factor 5 = Social support a
All items, except where noted, were reverse-coded so that higher scores reflected a better quality of life
b
These items were not reverse-coded
Southeast Asia. Although it was initially hypothesized that the underlying factor structure in this sample population would adhere to the Taiwanese five-factor structure, it seems that, despite cultural overlaps, there are other facts at play in the Singapore cohort. The analyses of the CQOLC-S25 align both Factors 1 and 5 with the Burden and Social Support/Positive
123
Adaptation subscales of the CQOLC and CQOLC-M; however, items from the factors of spiritual well-being and financial concerns of the CQOLC(-M) were unfortunately dropped, suggesting that these issues may not be as central to caregivers’ QOL in Singapore. Instead, analyses suggested three other factors derived from a mix of the CQOLC(-M)’s Burden and Disruptiveness subscales:
Qual Life Res (2015) 24:399–404 Table 3 Descriptives and correlations of the CQOLC-S25
a
All bivariate correlations are significant at p B .005 except where otherwise noted
b c
p [ .05 p = .04
403 Total and factor/subscalesa
a
Range
M ± SD
1
2
3
4
5
1. Total CQOLC-S25 Score
.89
0–92
60.13 ± 16.91
-
2. Burden
.89
0–32
20.24 ± 7.61
.89
-
3. Physical/practical concerns
.85
0–20
12.32 ± 4.79
.77
.58
-
4. Emotional reactivity
.75
0–16
6.00 ± 3.96
.66
.55
.31
-
5. Self-needs
.80
0–16
10.40 ± 4.36
.75
.57
.56
.47
-
-.21
-.15c
6. Social support
physical/practical concerns, emotional reactivity, and selfneeds. This could be a result of cultural notions of filial piety, coupled with the fact that those providing care were also financially supporting and caring for the rest of the family [25]. Unlike in the Taiwanese and US samples, caregivers here may also have employed a foreign domestic worker to assist in day-to-day care needs of the care recipient.
.60
0–16
6.
7.
8.
Limitations and future studies There are certain limitations that need to be addressed. Because the study did not aim to investigate the validity of the scale, no other tools were administered simultaneously with the CQOLC. Further, there may be inherent differences between the English and Mandarin versions due to the cultural connotations of the translated words. Therefore, given that a somewhat different factor structure has emerged, future studies should look to confirming these results and examining the discriminant and convergent validity of the scale. Only in better understanding these caregivers’ QOL concerns can more effective measures be undertaken to support and care for them.
9.
10.
11.
12.
13.
References 1. Singapore Ministry of Health. (2013). Principal Causes of Death. Singapore Health Facts. Retrieved December 20 2013, from http://www.moh.gov.sg/content/moh_web/home/statistics/Health_ Facts_Singapore.html. 2. Gaugler, J. E., Hanna, N., Linder, J., Given, C. W., Tolbert, V., Kataria, R., et al. (2005). Cancer caregiving and subjective stress: A multi-site, multi-dimensional analysis. Psycho-oncology, 14(9), 771–785. doi:10.1002/pon.916. 3. Weitzner, M. A., Jacobsen, P. B., Wagner, H., Friedland, J., & Cox, C. (1999). The caregiver quality of life index-cancer (CQOLC) scale: Development and validation of an instrument to measure quality of life of the family caregiver of patients with cancer. Quality of Life Research, 8(1–2), 55–63. 4. Weitzner, M. A., Meyers, C. A., Steinbruecker, S., Saleeba, A. K., & Sandifer, S. D. (1997). Developing a care giver quality-oflife instrument: Preliminary steps. Cancer Practice, 5(1), 25–31. 5. Grov, E. K., & Dahl, A. A. (2010). Quality of life measures in caregivers of patients with cancer. In V. R. Preedy & R. R. Watson (Eds.), Handbook of disease burdens and quality of
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life measures (Vol. 1, pp. 2935–2946). New York: Springer. doi:10.1007/978-0-387-78665-0_171. Wadhwa, D., Burman, D., Swami, N., Rodin, G., Lo, C., & Zimmermann, C. (2013). Quality of life and mental health in caregivers of outpatients with advanced cancer. Psycho-oncology, 22(2), 403–410. doi:10.1002/pon.2104. Leow, M. Q. H., Chan, M.-F., & Chan, S. W. C. (2013). Predictors of change in quality of life of family caregivers of patients near the end of life with advanced cancer. Cancer Nursing,. doi:10.1097/NCC.0000000000000101. Yakar, H. K., & Pinar, R. (2013). Reliability and validity of Turkish version of the caregiver quality of life index cancer scale. Asian Pacific Journal of Cancer Prevention, 14(7), 4415–4419. Lafaye, A., De Chalvron, S., Houe´de´, N., Eghbali, H., & Cousson-Ge´lie, F. (2013). The caregivers quality of life cancer index scale (CQoLC): An exploratory factor analysis for validation in French cancer patients’ spouses. Quality of Life Research, 22(1), 119–122. doi:10.1007/s11136-012-0113-y. Weitzner, M. A., & McMillan, S. C. (1999). The caregiver quality of life index-cancer (CQOLC) scale: Revalidation in a home hospice setting. Journal of Palliative Care, 15(2), 13–20. Tang, W.-R., Tang, S., & Kao, C. (2009). Psychometric testing of the caregiver quality of life index-cancer on a Taiwanese family caregiver sample. Cancer Nursing, 32(3), 220–229. doi:10.1097/ NCC.0b013e31819b5ae8. Rhee, Y. S., Shin, D. O., Lee, K. M., Yu, H. J., Kim, J. W., Kim, S. O., et al. (2005). Korean version of the caregiver quality of life index-cancer (CQOLC-K). Quality of Life Research, 14(3), 899–904. De Winter, J. C. F., Dodou, D., & Wieringa, P. A. (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44(2), 147–181. doi:10.1080/00273170902794206. Gorsuch, R. L. (1983). Factor analysis (2nd ed.). Hillsdale, NJ: Erlbaum. Walter, S. D., Eliasziw, M., & Donner, A. (1998). Sample size and optimal designs for reliability studies. Statistics in Medicine, 17(1), 101–110. Bland, J. M., & Altman, D. G. (2007). Agreement between methods of measurement with multiple observations per individual. Journal of Biopharmaceutical Statistics, 17(4), 571–582. doi:10.1080/10543400701329422. Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258. doi:10.1177/0049124192021002005. Jo¨reskog, K. G., & So¨rbom, D. (2000). LISREL 8: User’s reference guide (2nd ed.). Lincolnwood, IL: Scientific Software International Inc. Ford, J. K., MacCallum, R. C., & Tait, M. (1986). The application of exploratory factor analysis in applied psychology: A critical review and analysis. Personnel Psychology, 39(2), 291–314. doi:10.1111/j.1744-6570.1986.tb00583.x.
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404 21. Hair, J. F., Anderson, R. E., Tatham, R. L., & William, C. B. (1998). Multivariate data analysis. Upper Saddle River: Prentice Hall. 22. Worthington, R. L., & Whittaker, T. A. (2006). Scale development research a content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806–838. doi:10. 1177/0011000006288127. 23. Costello, A. B., & Osborne, J. W. (2009). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pan-Pacific Management Review, 12(2), 131–146.
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Qual Life Res (2015) 24:399–404 24. Terwee, C. B., Bot, S. D. M., de Boer, M. R., van der Windt, D. A., Knol, D. L., Dekker, J., et al. (2007). Quality criteria were proposed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology, 60(1), 34–42. doi:10. 1016/j.jclinepi.2006.03.012. 25. Mehta, K. K. (2006). A critical review of Singapore’s policies aimed at supporting families caring for older members. Journal of Aging & Social Policy, 18(3–4), 43–57. doi:10.1300/J031v18n03_04.
BRIEF COMMUNICATION
The Caregiver Quality of Life Index–Cancer (CQOLC) in Singapore: a new preliminary factor structure for caregivers of ambulatory patients with cancer Rathi Mahendran • Haikel A. Lim • Joanne Chua • Chao Xu Peh • Siew Eng Lim Ee Heok Kua
•
Accepted: 24 July 2014 / Published online: 6 August 2014 Ó Springer International Publishing Switzerland 2014
Abstract Purpose The Caregiver Quality of Life Index–Cancer (CQOLC) is used worldwide to determine levels of quality of life of caregivers of patients with cancer; however, the few studies examining the underlying factor structure of the CQOLC have revealed differences between Western and Eastern cultures. This study sought to confirm the differences in the factor structures between the original CQOLC and a Taiwanese (Mandarin) version. Methods A total of 183 caregivers from a cancer center in Singapore participated in this exploratory cross-sectional study. All participants completed the CQOLC and a sociodemographic form; 30 participants repeated the CQOLC two weeks later. Results Test–retest reliability was adequate for the CQOLC; however, confirmatory factor analyses did not support either the original four-factor model or the Taiwanese five-factor model. Exploratory factor analyses suggested the retaining of five factors to form a 25-item
R. Mahendran (&) J. Chua E. H. Kua Department of Psychological Medicine, National University Hospital, NUHS Tower Block, Level 9, 1E Kent Ridge Road, Singapore 119228, Singapore e-mail: [email protected] R. Mahendran H. A. Lim C. X. Peh E. H. Kua Department of Psychological Medicine, National University of Singapore, NUHS Tower Block, Level 9, 1E Kent Ridge Road, Singapore 119228, Singapore e-mail: [email protected] S. E. Lim Department of Haematology-Oncology, National University Cancer Institute, Singapore (NCIS), National University Health System, NUHS Tower Block, Level 7, 1E Kent Ridge Road, Singapore 119228, Singapore
Singapore version (CQOLC-S25): burden, physical/practical concerns, emotional reactivity, self-needs, and social support. Inter-factor and factor scale correlations were positively significant for all factors except Support, which was negatively correlated with emotional reactivity and self-needs. Conclusions Cross-cultural differences, which require further investigations, appear to underlie the utility and understanding of the CQOLC. More research is needed to better understand the needs of Singapore caregivers. Keywords Caregivers Cancer Quality of life Singapore CQOLC
Introduction Cancer is a major cause of worldwide mortality and morbidity; in Singapore, an island state in Southeast Asia, cancer is the leading cause of deaths (30 % of total deaths in 2011) [1]. Caregivers, as primary providers of support, face the impact of the illness with consequent poorer quality of life [2]. There is therefore a need to determine the levels of, and deficiencies in, these caregivers’ quality of life (QOL) to better support them through the cancer journey. The Caregiver Quality of Life Index–Cancer in Asia The Caregiver Quality of Life Index–Cancer (CQOLC) [3] is one of the more widely used instruments holistically measuring the QOL of caregivers of cancer patients (hereafter referred to as caregivers). Developed in 1997 in the United States [4], the CQOLC is one of the few recommended instruments in measuring caregivers’ QOL [5]
123
400
in studies of caregivers of both curative and palliative mixed-cancer patients [6, 7]. The CQOLC has been shown to be psychometrically sound in Western societies like France and Turkey [8, 9], and the original US version has demonstrated an underlying factor structure of four domains: burden, disruptiveness, positive adaptation, and financial concerns [10]. In Asia, the CQOLC has been translated into Mandarin and Korean [11, 12]; the Mandarin version, studied in a sample of Taiwanese caregivers of palliative cancer patients, differs in its underlying factor structure [11]: in place of positive adaptation, there are, instead, factors of social support and spiritual well-being. Further, some of the items (e.g., satisfaction with sexual functioning) were found to be unsuitable for a conservative Asian society. Unfortunately, these results have not yet been replicated nor has this factor structure been validated. The present study This study therefore sought to uncover the underlying factor structure in Singapore. It was hypothesized that, in a sample of Singapore caregivers of ambulatory patients with cancer, the CQOLC would (a) not fit the original fourfactor model, but instead, because of cultural similarities, (b) fit the Taiwanese five-factor model.
Qual Life Res (2015) 24:399–404 Table 1 Demographics of the present sample Demographic category
Participants and procedures Between August 2012 and January 2013, a trained research assistant invited caregivers of patients in the outpatient medical oncology clinic at the National Cancer Institute of Singapore (NCIS) to participate in this study during their patients’ appointments at the outpatient clinic. Caregivers were included if they were aged between 21 and 64 years, proficient in either English or Mandarin, and no past history of cancer; caregivers were excluded if they were illiterate. The study was approved by the National Healthcare Group Domain Specific Review Board A (reference: 2012/00193). Because Singapore is a bilingual society, the final pool of 183 caregiver participants (87 % response rate) were given a basic demographic questionnaire and the option to complete the CQOLC in their preferred master language (i.e., CQOLC for English, and the CQOLC-M for Mandarin [11]; both are national languages and our preliminary analyses with a larger dataset of an ongoing study have shown no significant differences between the scores of those completing the English and Mandarin versions of the CQOLC). The CQOLC is a 35-item self-report measure of caregivers’ QOL measured on a five-point Likert-type
123
%
Age \21
3
2
21–30
31
17
31–40
37
20
41–50
46
25
51–60
27
15
[60
29
22
139
76
Malay
29
16
Indian Othersa
8 7
4 4
5
3
Primary
24
13
Secondary
60
33
Tertiary
93
51
70
39
Ethnicity Chinese
Education No formal education
Relationship with patient Spouse Sibling
9
5
84
46
Grandchild
1
1
Niece/nephew
5
3
13
7
Early
83
46
Advanced Unsure
77 21
42 12
Child
Othersb
Methods
n
Care recipients’ cancer staging
a
This included ethnic groups like Eurasians and ethnic dialect groups
b
These were mainly in-laws and friends/long-term partners
scale from 0 (not at all) to 4 (very much) with a maximum score of 140. This score is obtained by summing the item scores, higher scores denote better QOL. The CQOLC takes about 20 min to complete. Item 4 (satisfaction with sexual functioning) was excluded from these calculations because there were missing data (due to the sensitivity of such a question in Singapore’s conservative Asian society). After completing and returning the questionnaire, to determine test–retest reliability, the research assistant gave all participants another identical questionnaire and instructed them to complete it at home on a specific date two weeks later and post it via a self-return envelope. We received 30 (16 %) completed CQOLC questionnaires and verified (by checking the postmarks) that none had sent it before the date specified on their questionnaire. The demographics of the sample are presented in Table 1. The majority of the participants were between 41 and 50 years of age (25 %), women (57 %), and of Chinese
Qual Life Res (2015) 24:399–404
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ethnicity (76 %). Half of the participants had tertiary education (50 %) and more than three-quarters were English speaking (79 %). The majority were either children (46 %) or spouses (38 %) of their care recipient. There were an almost equal proportion of early (46 %) and advanced stage (42 %) care recipients.
suggested that the CQOLC in a sample of Singapore caregivers had a different underlying factor structure; as such, this was subsequently investigated via exploratory factor analyses.
Data analyses
The simultaneous use of Cattell’s scree plot and Horn’s parallel analyses were adopted to avoid under-factoring [20]. The results of the first iteration suggested retaining five factors, which were then extracted via a common factor analysis with a Promax oblique rotation. Only items that met the following criteria were retained: (a) had a significant primary factor loading of C.40 [21]; (b) did not have a secondary loading of C.32, or having a difference of \.15 from the primary loading [22]; and (c) there were at least three items in the factor [23]. Of the 34 items, 9 that failed to meet these criteria over four iterations were removed: items 7 (concern about insurance), 8 (economic future), 10 (outlook on life), 11 (level of stress), 12 (spirituality), 14 (sadness), 16 (social support), 27 (focus of caregiving), and 35 (family interest in caregiving). The fifth confirmatory iteration produced a rotated solution with 25 items over five factors (CQOLC-S25), as presented in Table 2, and communalities of C.20. The reliability coefficients for the total scale and Factors 1–4 ranged from .75 to .89 and fell within the range for good internal consistency [24]; the reliability coefficient for Factor 5 was somewhat wanting at .60, but the removal of items did not improve Cronbach’s alpha. The five extracted factors of the CQOLC-S25 were subsequently reviewed and labeled. Factor 1 (8 items), similar to the Taiwan and US versions, was determined to be ‘‘burden’’; factor 2 (5 items) was labeled ‘‘physical/ practical concerns’’; factor 3 (4 items) was termed ‘‘emotional reactivity’’; factor 4 (4 items) was considered ‘‘selfneeds’’; and factor 5 (4 items), similar to the Taiwan and US versions, was labeled ‘‘social support.’’ A comparison of the item loadings on the Taiwan and US version subscales are presented in Table 2. Bivariate correlations revealed that all except the social support was correlated to the total CQOLC-S25 score, rs(181–183) = .66–.89, all ps \ .001. Social support, however, was correlated with two other factors, namely emotional reactivity, and self-needs, rs(181–182) = -.14–.21, ps = .005–.044. Table 3 presents the descriptives and correlations of the CQOLC-S25.
The sample size for the subsequent analyses was sufficient: the estimated minimum sample size adequate for factor analyses was calculated to be 170 (based on a minimum of five participants per variable) [13, 14], and for test–retest reliability, 30 (a = .05, b = .20) [15, 16]. Statistical analyses were conducted using IBM SPSS Statistics version 20 (Chicago, IL). Pearson’s correlations were employed to determine test–retest reliability, and the relationship between different factors. In order to ascertain whether the present data fit either the original or Taiwanese factor structures, confirmatory factor analyses (CFA) were conducted using SPSS AMOS. Goodness of fit model was examined using five indices: (a) a non-significant v2; (b) root-mean-square-error of approximation (RMSEA) below .08; (c) goodness of fit index (GFI) above .90; (d) adjusted goodness of fit index (AGFI) above .85; and (e) comparative fit index (CFI) above .90 [17–19]. Based on modification indices, error variance parameters were allowed to covary if they were under the same factor. Additional criteria and tests employed are detailed in the following section.
Results Reliability and internal consistency Cronbach’s alpha of the entire CQOLC was .89 for both the first and second administration. There was good test–retest reliability: Pearson’s correlation coefficient was .79, p \ .001. Because these two measures suggested that the CQOLC was reliable in this sample, subsequent CFA were conducted. Confirmatory factor analyses Both the proposed models (original four-factor and Taiwan five-factor) were tested. Results showed only a marginal to moderate fit for the original 4 factor model, v2(293, 209) = 425.71, p \ .001, RMSEA = .06, GFI = .81, AGFI = .75, CFI = .91. However, unexpectedly, the results also only showed a marginal to moderate fit for the Taiwan five-factor model, v2(403, 209) = 577.21, p \ .001, RMSEA = .06, GFI = .78, AGFI = .73, CFI = .90. This
Exploratory factor analyses
Discussion This study is the first to suggest a culturally variable factor structure in caregivers of ambulatory cancer patients in
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Qual Life Res (2015) 24:399–404
Table 2 Factor loading matrix for the final iteration and item loading on CQOLC-S25 compared with Taiwan and US version subscales Item number and descriptiona
Factor 1
Factor 2
Factor 3 Factor 4 Factor 5
Taiwan factor
US factor
19. I feel nervous
.926
-.094
-.025
.035
-.033
Burden
Burden
18. I feel frustrated
.834
-.045
-.023
.081
.075
Burden
Burden
17. I feel guilty
.676
-.098
.056
.086
.165
Burden
Burden
20. I worry about the impact my loved one’s illness has had on my children or other family members
.674
.022
-.001
-.094
-.348
Burden
Burden
15. I feel under increased mental strain
.601
.196
.231
-.206
.040
Burden
–
33. I am discouraged about the future
.549
-.007
.170
.038
.065
Burden
Burden
21. I have difficulty dealing with my loved one’s changing eating habits
.520
.134
-.190
.173
-.117
Disruptiveness
Disruptiveness
13. It bothers me, limiting my focus to day-today.
.486
.382
.081
-.001
.125
Burden
–
3. My daily life is imposed upon
-.077
.845
-.051
.080
.040
Disruptiveness
Disruptiveness
2. My sleep is less restful 1. It bothers me that my daily routine is altered
.028 -.120
.845 .728
.081 -.032
-.217 .219
.076 .014
Disruptiveness Disruptiveness
– Disruptiveness
.101
.676
-.167
.039
-.143
–
Disruptiveness
5. It is a challenge to maintain my outside interests 6. I am under a financial strain
.136
.463
.011
.065
.040
31. It upsets me to see my loved one deteriorate
.008
-.004
.744
-.058
-.134
9. I fear my loved one will die
Financial concerns
Financial concerns
Burden
Burden
.039
-.045
.684
-.029
.081
Burden
Burden
-.032
-.009
.541
.318
.025
Disruptiveness
–
.148
-.112
.528
.055
-.031
Burden
Burden
-.044
.057
.023
.707
-.088
Disruptiveness
Disruptiveness
30. The need to protect my loved one bothers me
.013
.004
.073
.683
.055
Disruptiveness
–
24. It bothers me that I need to be available to chauffeur my loved one to appointments
.266
-.014
-.117
.663
.051
Disruptiveness
Disruptiveness
26. The responsibility I have for my loved one’s care at home is overwhelming
.009
.121
.288
.406
-.089
Disruptiveness
Disruptiveness
22. I have developed a closer relationship with my loved oneb
.028
-.130
-.185
.032
.638
Social support
Positive adaptation
23. I feel adequately informed about my loved one’s illness.b
.000
.020
.235
-.010
.619
Social support
–
.149
-.057
-.150
-.096
.557
Social support
Positive adaptation
-.122
.279
-.034
.048
.469
Social support
Positive adaptation
32. The need to manage my loved one’s pain is overwhelming 25. I fear the adverse effects of treatment on my loved one 29. It bothers me that my priorities have changed
28. Family communication has increasedb 34. I am satisfied with the support I get from my familyb
Bolded items assist readers in identifying the items that load onto the different factors Factor 1 = Burden, Factor 2 = Physical/practical concerns, Factor 3 = Emotional reactivity, Factor 4 = Self-needs, Factor 5 = Social support a
All items, except where noted, were reverse-coded so that higher scores reflected a better quality of life
b
These items were not reverse-coded
Southeast Asia. Although it was initially hypothesized that the underlying factor structure in this sample population would adhere to the Taiwanese five-factor structure, it seems that, despite cultural overlaps, there are other facts at play in the Singapore cohort. The analyses of the CQOLC-S25 align both Factors 1 and 5 with the Burden and Social Support/Positive
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Adaptation subscales of the CQOLC and CQOLC-M; however, items from the factors of spiritual well-being and financial concerns of the CQOLC(-M) were unfortunately dropped, suggesting that these issues may not be as central to caregivers’ QOL in Singapore. Instead, analyses suggested three other factors derived from a mix of the CQOLC(-M)’s Burden and Disruptiveness subscales:
Qual Life Res (2015) 24:399–404 Table 3 Descriptives and correlations of the CQOLC-S25
a
All bivariate correlations are significant at p B .005 except where otherwise noted
b c
p [ .05 p = .04
403 Total and factor/subscalesa
a
Range
M ± SD
1
2
3
4
5
1. Total CQOLC-S25 Score
.89
0–92
60.13 ± 16.91
-
2. Burden
.89
0–32
20.24 ± 7.61
.89
-
3. Physical/practical concerns
.85
0–20
12.32 ± 4.79
.77
.58
-
4. Emotional reactivity
.75
0–16
6.00 ± 3.96
.66
.55
.31
-
5. Self-needs
.80
0–16
10.40 ± 4.36
.75
.57
.56
.47
-
-.21
-.15c
6. Social support
physical/practical concerns, emotional reactivity, and selfneeds. This could be a result of cultural notions of filial piety, coupled with the fact that those providing care were also financially supporting and caring for the rest of the family [25]. Unlike in the Taiwanese and US samples, caregivers here may also have employed a foreign domestic worker to assist in day-to-day care needs of the care recipient.
.60
0–16
6.
7.
8.
Limitations and future studies There are certain limitations that need to be addressed. Because the study did not aim to investigate the validity of the scale, no other tools were administered simultaneously with the CQOLC. Further, there may be inherent differences between the English and Mandarin versions due to the cultural connotations of the translated words. Therefore, given that a somewhat different factor structure has emerged, future studies should look to confirming these results and examining the discriminant and convergent validity of the scale. Only in better understanding these caregivers’ QOL concerns can more effective measures be undertaken to support and care for them.
9.
10.
11.
12.
13.
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