Caregiver Burden: Looking Beyond the Unidimensional Total Score.

ORIGINAL ARTICLE

Caregiver Burden Looking Beyond the Unidimensional Total Score Sabrina Lau, MBBS,* Mei Sian Chong, FRCP,wz Noorhazlina Ali, MRCP,wz Mark Chan, MRCP,wz Kia Chong Chua, MSc,y and Wee Shiong Lim, MRCP, MMed, MHPEdwz

Abstract: The Zarit Burden Interview allows caregiver burden to be interpreted from a total score. However, recent studies propose a multidimensional Zarit Burden Interview model. This study aims to determine the agreement between unidimensional (UD) and multidimensional (MD) classification of burden, and differences in predictors among identified groups. We studied 165 dyads of dementia patients and primary caregivers. Caregivers were dichotomized into low-burden and high-burden groups based upon: (1) UD score using quartile cutoffs; and (2) MD model via exploratory cluster analysis. We compared UD versus MD 2 2 classification of burden using k statistics. Caregivers not showing agreement by either definition were classified as “intermediate” burden. We performed binary logistic regression to ascertain differences in predictive factors. The 2 models showed moderate agreement (k = 0.72, P < 0.01), yielding 104 low, 20 intermediate (UD “low burden”/MD “high burden”), and 41 high-burden caregivers. Neuropsychiatric symptoms [odds ratio (OR) = 1.27, P = 0.003], coresidence (OR = 6.32, P = 0.040), and decreased caregiving hours (OR = 0.99, P = 0.018) were associated with intermediate burden, whereas neuropsychiatric symptoms (OR = 1.21, P = 0.001) and adult children caregivers (OR = 2.80, P = 0.055) were associated with high burden. Our results highlight the differences between UD and MD classification of caregiver burden. Future studies should explore the significance of the noncongruent intermediate group and its predictors. Key Words: Alzheimer disease, caregiver burden, Zarit Burden Interview, dimension, cluster analysis

(Alzheimer Dis Assoc Disord 2015;29:338–346)

Received for publication August 17, 2014; accepted January 9, 2015. From the *Yong Loo Lin School of Medicine, National University of Singapore; wDepartment of Geriatric Medicine; zInstitute of Geriatrics and Active Ageing, Tan Tock Seng Hospital (TTSH), Singapore, Singapore; and yInstitute of Psychiatry, King’s College London, London, UK. Supported by National Healthcare Group (NHG) Small Innovative Grant 2011/005. M.S.C. is supported by the NHG Clinician Scientist Career Scheme 2012/12002. S.L. and W.S.L.: designed the study, performed statistical analysis, and wrote the manuscript. M.S.C. and K.C.C.: supervised the data collection and contributed to writing the manuscript. N.A. and M.C.: helped in patient recruitment and contributed to writing the manuscript. The authors declare no conflicts of interest. Reprints: Wee Shiong Lim, MRCP, MMed, MHPEd, Department of Geriatric Medicine, Tan Tock Seng Hospital (TTSH), Annex 2, Level 3, 11 Jalan Tan Tock Seng, Singapore 308433, Singapore (e-mail: [email protected]). Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Website, www.alzheimerjournal.com. Copyright r 2015 Wolters Kluwer Health, Inc. All rights reserved.

C

aregiver burden is not an easy concept to define; it is a largely subjective perception of stress from the caregiving role that arises from the interplay among predisposing factors such as contextual factors, direct primary stressors, indirect secondary stressors, and appraisal.1 In neurodegenerative diseases such as dementia, the role of caregiver support cannot be underestimated as care recipients become increasingly reliant on their caregivers through the course of disease. It is projected that the number of people worldwide living with dementia will increase to 115.4 million by 2050,2 with the responsibility of day-to-day supervision and care being largely borne by the informal system of family caregivers with or without paid domestic help.3 Because family caregivers play a critical role in achieving patient-centered care for persons with dementia, it is important to accurately evaluate and address the complexity of burden arising from the caregiving experience. The Zarit Burden Interview (ZBI) has been used to assess caregiver burden in different countries and across many languages with good reliability and internal consistency.4 For many years, the degree of caregiver burden was assessed based upon the total score, constituting what is effectively a unidimensional (UD) approach.5 George and Gwyther6 proposed that burden is instead a multidimensional (MD) construct, which may not be comprehensively or accurately measured by a global score. Recent studies corroborate the multidimensionality of the ZBI, with the number of reported domains ranging from 3 to 5 (appendix Table, Supplemental Digital Content, http://links.lww.com/WAD/ A111).7–15 The proposed MD construct has been said to assess burden more holistically, as well as negate the effect of unequal question representation within individual domains. Caregivers with an identical score may be affected by different aspects of burden; while one may be overwhelmed with the physical demands of caregiving, another may be worried about his caregiving performance.13 However, despite recognition and validation of burden as a MD construct, an MD model of the ZBI has not been routinely translated into actual clinical practice, as reflected by the predilection to depend on the total score to classify caregivers as low or high burden.4,16 Again, in a recent study seeking to derive an abbreviated version of the ZBI, the investigators ignored the empirical MD constructs suggested by item response theory and focused solely on the predominant construct of burden to derive a 1-dimensional 12-item ZBI.17 This reluctance to incorporate the MD model may reflect 2 fundamental considerations, namely practicality and relevance. There are practical difficulties with the operationalization of the MD concept; specifically, it is much easier to classify caregivers into distinct high-burden and low-burden groups based on arbitrary cutoffs from the total score.

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Alzheimer Dis Assoc Disord

Volume 29, Number 4, October–December 2015

The advent of statistical techniques such as cluster analysis has made possible the ability to define unbiased burden groups that incorporate the MD concept.18 Furthermore, the relevance of the MD construct depends on how much value it can add to current practice; in particular, is there a difference between UD and MD approaches to classifying burden? In the scenario of perfect congruence, we expect only 2 distinct groups of low and high burden. However, if there are discrepancies between the 2 models, the mismatched cases will give rise to an intermediate group comprising either high UD/ low MD or low UD/high MD burden. To date, there has been no study that compares the UD and MD classification of burden in the same study sample. Using the above conceptual framework, we conducted a proof-of-concept study to determine if there is a difference in classification of low-burden and high-burden groups between UD and MD approaches. For the MD model, we employed the 4-factor structure which was recently reported by Cheah et al13 in an independent sample of family caregivers of community-dwelling persons with mild to moderate dementia of predominantly Chinese ethnicity. Our secondary study objective is to describe the differences between the noncongruent intermediate-burden group and the low-burden and high-burden groups.

METHODS Study Subjects This is a cross-sectional study of 165 consecutive dyads of community-dwelling older adults (aged 55 y and older) with dementia and their primary family caregiver attending the Memory Clinic in Tan Tock Seng Hospital, Singapore from June 2011 to September 2012. Participants from this study were derived from another study on cost of informal care in community-dwelling mild-moderate dementia patients.3 As per the inclusion criteria, we included subjects who met the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for dementia with a Clinical Dementia Rating (CDR) global score of >0 and r2 (ie, mild to moderate severity).19,20 Subjects had to be accompanied by their primary family caregiver (ie, the family member most involved in the provision of care and most familiar with the care recipient’s condition) who was 21 years and older of age and fluent in either English or Mandarin. We excluded subjects with CDR score Z3 (severe dementia) or 0 (no dementia) and subjects without a primary family caregiver, as our participants were derived from a quality of life study. We also excluded patients with mild cognitive impairment and those living in an assisted living facility or nursing home. The nonresponse rate was 13.2%, but there was no significant difference in care recipient and caregiver demographics compared with our eventual study sample. This study was approved by the Institutional Review Board of the National Healthcare Group and consent was obtained from the subject’s caregiver or legally acceptable representative.

Assessment The assessment instruments were interview based— details of the diagnostic process and assessment tools have been described previously.3,13 We collected demographic data of the caregiver and care recipient, including age, sex, ethnicity, and education level. In addition, information on caregiver characteristics such as employment status, relationship and coresidence with care recipient, hours of Copyright

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Caregiver Burden: Multidimensional Versus Unidimensional

informal care, and presence of other caregivers (or domestic helpers) was obtained. We used the National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer’s Disease and Related Disorders Association criteria for diagnosis of Alzheimer disease,21 the National Institute of Neurological Disorders, and Stroke-Association Internationale pour la Recherche et l’Enseignement en Neurosciences criteria for vascular and mixed dementia,22 and published diagnostic criteria for other dementias.23,24 Dementia severity was assessed using the locally validated CDR scale.20 The composite global CDR score and the sum of all 6 domains were computed. Cognitive assessment was based on the locally validated Chinese Mini-Mental State Examination with a maximum score of 28.25 Functional status was assessed using the Bristol Activities of Daily Living (ADL) scale.26 Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory Questionnaire (NPI-Q).27 Severity and carer distress scores were computed separately. Caregiver burden was assessed using the 22-question ZBI, which was administered in either English or Chinese. The Chinese version was shown to have good interrater reliability and internal consistency without the need for major modification in content and wording.10,28 Each item was scored on a 5-point Likert scale, ranging from 0 = “never” to 4 = “nearly always,” yielding a total score ranging from 0 to 88. Monthly informal care time was assessed using the Resource Utilization in Dementia instrument (RUD)-Lite based on the care recipient’s basic ADL, instrumental ADL, and degree of supervision required.

Definition of High-burden and Low-burden Groups Caregivers were dichotomized into low-burden and high-burden groups as follows: (1) UD approach, using quartile cutoffs of ZBI total score; and (2) MD approach, via the exploratory technique of cluster analysis. There is no established agreement on what constitutes an appropriate ZBI total score to define high burden, with significant overlap in the recommended cutoff scores.4,29–31 For instance, in 1 study, scores of 21 to 40 correspond to mild-moderate burden, 41 to 60 to moderate-severe burden, and 61 to 88 to severe burden.4 Furthermore, many of the published cutoffs were based predominantly on white populations and may not be applicable to our study. Thus, for the UD model, we elected to empirically define low (ZBIr35) and high (ZBI > 35) burden groups based on 75th centile cutoffs derived from our study sample. A total ZBI score of 35 corresponds to moderate burden in 1 study.4 For the MD model, we adopted the 4-factor structure proposed in an independent sample by Cheah et al13 that accounted for 62.2% of variance with good internal consistency (Cronbach a = 0.919): (1) factor 1: demands of care and social impact on caregiver (40.6% of variance); (2) factor 2: confidence or control over the situation (9.7% of variance); (3) factor 3: psychological impact on caregiver (6.4% of variance); and (4) factor 4: worry about caregiving performance (5.6% of variance). Confirmatory factor analysis in follow-up analysis in a separate sample showed that the 4-factor structure was superior to the 3-factor ZBI structure (manuscript in preparation); a recent Hong Kong study of Chinese family caregivers corroborated these findings.14 As it would not be possible to derive a unitary cutoff to distinguish low-burden versus high-burden groups

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Lau et al

from MD classification, we derived our MD groups via cluster analysis, an exploratory, descriptive, and noninferential statistical tool used to identify distinct groups based on a multivariate profile that both minimizes the within-group variation and maximizes the between-group variation.18 We conducted hierarchical cluster analysis to factor 1 to 4 scores using a 2-stage procedure. We first use Ward’s method applying squared Euclidean Distance as the distance or similarity measure to determine the optimum number of clusters, which in this case was 2. We then rerun the analysis using K-means clustering to classify subjects into 2 clusters corresponding to MD low-burden and highburden groups. In general, the K-means method will produce the exact K different clusters with the greatest possible distinction.18

Statistical Analysis We performed descriptive and analytical statistics using SPSS (version 19.0; SPSS Inc., Chicago, IL). All tests were 2-sided with a set at 0.05 for all hypothesis contrasts. Corrections were made for multiple comparisons using Bonferroni correction (ie, for n comparisons, the corrected P value is P/n). We compared characteristics between low-burden and high-burden groups based upon the UD and MD models. We then constructed a 2 2 table to compare the agreement between UD and MD classification of high-burden and lowburden groups. We anticipate 3 derived groups: concordant high-burden and low-burden groups, as well as an “intermediate”-burden group comprising mismatched cases of either high UD/low MD or low UD/high MD burden. We determined overall percentage agreement using the ratio of number of cases with a concordant classification over the total number of examined subjects. To correct for chance agreement, we calculated the k statistic. We also performed post hoc analyses of receiver operating characteristic curves to determine optimal cutoff for the intermediate group. Using the groupings derived from the 22 classification table, we performed univariate analyses to compare the intermediate-burden and the low-burden and high-burden groups. We applied w2 test for categorical variables. For continuous variables, we performed 1-way analysis of variance with post hoc comparisons using the Bonferroni correction for multiple post hoc pair-wise comparisons. We performed calculations for effect size, using Z2 for continuous variables, f coefficient for 2 2 categorical variables and Cramer’s V for categorical variables with tables larger than 22. A moderate effect size is indicated by Z2, f coefficient, and Cramer’s V values of 0.06, 0.30, 0.21, respectively. Variables with P < 0.15 by univariate analysis were included in multivariate binary logistic regression to determine the predictors of high caregiver burden; the cutoff of P < 0.15 in exploratory analyses was also employed in other studies.32 We performed separate analyses for low-burden versus intermediate-burden, as well as low-burden versus high-burden groups. We also repeated the logistic regression with individual NPI-Q domains substituting for total NPI-Q scores.

RESULTS Characteristics of Care Recipient and Caregiver Dyads One hundred and sixty-five care recipient and caregiver dyads of predominantly Chinese ethnicity were


included in the analysis. The mean care recipient age was 77.3 years (SD = 6.9 y) and 44.8% were male. The predominant dementia etiology was Alzheimer disease (62.4%). The mean CDR global score was 1.2 (SD = 0.5), corresponding to mild to moderate severity of dementia. The CMMSE, Bristol ADL score, and NPI-Q (severity) had mean scores of 18.4 (SD = 4.2), 15.2 (SD = 9.1), and 3.8 (SD = 4.1), respectively (Table 1). The caregivers interviewed were mainly females (61.8%) with mean age of 58.3 years (SD = 13.4 y). The majority were adult children (57.0%) or spouses (35.8%)

TABLE 1. Characteristics of Care Recipient and Caregiver Dyads

Care Recipients (n = 165) Demographics Age (y) Sex (male %) Ethnicity (%) Chinese Malay Indian Others Years of formal education Currently employed (%) Relationship with care recipient Spouse Child Others Living with care recipient (%) Monthly hours of informal care No. other caregivers Presence of domestic helper (%) Disease characteristics Etiology (%) Alzheimer disease Vascular dementia Mixed Alzheimer’s and vascular dementia Others* Clinical staging of dementia CDR global score (0-3) CDR sum of boxes (0-18) Cognitive status CMMSE (0-28) Functional status Bristol ADL score (0-60) Behavioral symptoms NPI-Q severity score (0-36) NPI-Q carer distress score (0-60) Caregiver burden—ZBI scores Total ZBI score (0-88) Factor 1 (0-36) Factor 2 (0-20) Factor 3 (0-24) Factor 4 (0-8)

Caregivers (n = 165)

77.3 ± 6.9 44.8

58.3 ± 13.4 38.2

90.9 2.4 5.5 1.2 7.2 ± 4.5

92.7 1.8 4.2 1.2 11.4 ± 3.7 46.7

(%) 35.8 57.0 7.3 69.7 91.8 ± 107.6 1.3 ± 1.2 37.6

62.4 9.1 24.8 3.6 1.2 ± 0.5 5.9 ± 2.8 18.4 ± 4.2 15.2 ± 9.1 3.8 ± 4.1 4.0 ± 5.1 25.3 ± 14.5 11.9 ± 6.9 3.8 ± 3.8 5.9 ± 4.6 3.7 ± 2.0

Mean ± SD unless otherwise indicated. *Frontotemporal (n = 4), alcohol-related (n = 1), and Parkinson disease dementia (n = 1). ADL indicates Activities of Daily Living; CDR, Clinical Dementia Rating; CMMSE, Chinese Mini-Mental State Examination; NPI-Q, Neuropsychiatric Inventory Questionnaire; ZBI, Zarit Burden Interview.

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who coresided with the care recipient (69.7%) and contributed a mean 91.8 (SD = 107.6) monthly hours of informal care. There was an average of 1.3 (SD = 1.2) caregivers per care recipient, 37.6% had a domestic helper, and 46.7% were currently employed. Caregivers reported a mean NPI-Q carer distress score of 4.0 (SD = 5.1). The mean total ZBI score was 25.3 (SD = 14.5), with individual factor 1 to 4 mean scores of 11.9 (SD = 6.9), 3.8 (SD = 3.8), 5.9 (SD = 4.6), and 3.7 (SD = 2.0), respectively. Of note, factor 4 correlated poorly with other factor scores (r = 0.18 to 0.27, P < 0.05) and total ZBI (r = 0.37, P < 0.01), unlike the other factor scores (r = 0.70 to 0.93, P < 0.01).

Comparison of Characteristics Between UD and MD Models The UD model identified 124 caregivers with low burden and 41 caregivers with high burden using quartile cutoffs of ZBI total score. In comparison, in the MD model, cluster analysis yielded 2 clusters corresponding to 104 caregivers with low burden and 61 caregivers with high burden. When comparing low-burden versus high-burden groups, both UD and MD models were largely similar in direction of trends. For ZBI total and factor scores, the UD model consistently identified caregivers at a slightly higher degree of burden as compared with the MD model [high burden groups, total ZBI mean (SD): 45.5 (8.7) vs. 41.0 (9.6), t100 = 2.41, P = 0.018]. None of the care recipient and caregiver demographic characteristics were statistically significant (P > 0.05), although there was a trend in the MD model among the high-burden group toward more spousal caregivers [31% vs. 22%, w2(1,N = 61) = 1.91, P = 0.167], residing with the care recipient [74% vs. 66%, w2(1,N = 61) = 2.12, P = 0.146] and fewer monthly hours of informal care [mean (SD): 111.9 (137.3) vs. 137.1 (159.9), t100 = 0.85, P = 0.397]. In both UD and MD models, higher caregiver burden was associated with increased CDR score, poorer cognitive status, increased functional dependence, and increased NPI-Q severity and distress scores (P < 0.05) (Table 2).

Classification of Low-burden Versus High-burden Groups There was overall good agreement between UD and MD models, with overall percentage agreement of 87.8% and k of 0.72 (P < 0.01). Both models classified 104 caregivers as “low burden” and 41 caregivers as “high burden.” However, there were 20 discordant cases of “intermediate burden” that were entirely attributable to the UD lowburden/MD high-burden category. The absence of discordant cases in the corresponding UD high-burden/MD low-burden category suggests that the MD model is more sensitive in identifying an intermediate group with significant burden. Post hoc analyses using receiver operating characteristic curves revealed an optimal cutoff of 0.05). In contrast, for disease characteristics, the CDR sum of boxes, CMMSE, Bristol ADL, and NPI-Q scores were significantly different across the 3 burden groups (P < 0.05, Z2 = 0.04-0.22); post hoc analyses were significant for high/ low but not high/intermediate comparisons, suggesting that the intermediate was more similar to high-burden as opposed to low-burden group. Caregivers in the intermediate group were mainly spouses [50.0%, w2(2,N = 165) = 5.50, P = 0.064], coresided with the care recipient (90%, w2(2,N = 61) = 4.47, P = 0.107), and rendered the fewest hours of monthly informal care [60.4 (SD = 38.7), F2,162 = 5.38, P < 0.01]. Among caregivers who were currently working, adult children accounted for 95% in the high-burden group, compared with 73% in the intermediate-burden group (Table 4).

Factors Predicting Caregiver Burden Variables with P < 0.15 from univariate analysis were eligible. The logistic regression models comprised 3 care recipient (CMMSE, CDR sum of boxes, NPI severity score) and 3 caregiver (relationship to care recipient, living with care recipient, monthly hours of informal care) independent variables. Although significant in univariate analyses comparing between low-burden/intermediate-burden and highburden groups (Table 4), we excluded Bristol ADL due to multicollinearity with CDR sum of boxes. Similarly, there was multicollinearity between NPI-Q severity and NPI-Q distress scores; we chose NPI-Q severity so as to allow comparison with earlier studies that also reported NPI-Q severity scores13,33 (Table 5). Three variables independently predicted intermediate burden: NPI-Q severity [odds ratio (OR) = 1.27, P = 0.003], coresidence with care recipient (OR = 6.32, P = 0.040), and decreased caregiving hours (OR = 0.99, P = 0.018). In comparison, only NPI-Q severity (OR = 1.21, P < 0.001) significantly predicted high burden, with relationship to care recipient (OR = 2.80, P = 0.055) approaching statistical significance. The Hosmer-Lemeshow test was nonsignificant for both models, indicating goodness of fit of the final model that accounted for 23.5% and 28.4% of the variance for intermediate-burden and high-burden models, respectively. To depict the exact neuropsychiatric components contributing to burden, we incorporated individual NPI-Q domains in place of total NPI-Q severity score. When comparing low versus intermediate burden, delusions (OR = 3.06, P = 0.009), irritability/lability (OR = 2.55, P = 0.005), and apathy/indifference (OR = 2.37, P = 0.010) contributed significantly to the model. This was different from the comparison between low and high burden, where the significant predictors were disinhibition (OR = 10.22, P = 0.002), irritability/lability (OR = 2.03, P = 0.012), and depression (OR = 1.69, P = 0.043).

DISCUSSION Despite the emergence of evidence that consistently supports the multidimensionality of caregiver burden, prevailing clinical practice continue to employ the UD approach using arbitrary cutoffs of the ZBI total score to define significant burden.4,16 To our knowledge, this is the first study that directly compares between UD and MD approaches in the classification of high versus low burden




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TABLE 2. Comparison of Characteristics Between the Unidimensional and Multidimensional Models

Unidimensional Low Burden (n = 124) ZBI scores Total ZBI score (0-88) 18.7 ± 8.8 Factor 1 (0-36) 8.9 ± 4.6 Factor 2 (0-20) 2.3 ± 2.4 Factor 3 (0-24) 4.1 ± 3.2 Factor 4 (0-8) 3.4 ± 2.0 Care recipient characteristics Demographics Age (y) 76.9 ± 6.9 Male sex [n (%)] 59 (47.6) Chinese ethnicity 115 (92.7) [n (%)] Years of formal 7.4 ± 4.4 education Clinical staging of dementia CDR global score 1.1 ± 0.5 (0-3) CDR sum of boxes 5.6 ± 2.7 (0-18) CMMSE (0-28) 18.8 ± 4.1 Bristol ADL score 14.0 ± 9.1 (0-60) NPI-Q severity score 3.0 ± 3.4 (0-36) NPI-Q carer distress 2.7 ± 3.6 score (0-60) Caregiver characteristics Age (y) 59.2 ± 13.9 Male sex [n (%)] 45 (36.3) Chinese ethnicity [n 116 (93.5) (%)] Years of formal 11.2 ± 3.8 education Currently employed (%) 57 (46.0%) Spousal caregivers 50 (40.3) [n (%)] Living with care 88 (71.0%) recipient (%) Monthly hours of 76.8 ± 78.9 informal care No. other caregivers 1.4 ± 1.3 involved in care Presence of domestic 45 (36.3%) helper (%)

Multidimensional

High Burden (n = 41)

Low Burden (n = 104)


P

P

45.5 ± 8.7 20.8 ± 4.6 8.5 ± 3.2 11.6 ± 3.4 4.7 ± 1.7

< 0.001*,w < 0.001*,w < 0.001*,w < 0.001*,w < 0.001*,w

0.64 0.55 0.51 0.51 0.08

16.1 ± 7.1 7.9 ± 4.2 1.6 ± 1.7 3.3 ± 2.5 3.3 ± 2.1

41.0 ± 9.6 18.6 ± 5.2 7.7 ± 3.2 10.5 ± 3.5 4.3 ± 1.8

< 0.001*,w < 0.001*,w < 0.001*,w < 0.001*,w 0.001*,w

78.6 ± 6.5 15 (36.6) 35 (85.4)

0.167 0.220 0.145

0.01 0.10 0.18

77.1 ± 7.0 49 (47.1) 96 (92.3)

77.7 ± 6.7 25 (41.0) 54 (88.5)

0.614 0.445 0.180

< 0.01 0.06 0.17

6.3 ± 4.9

0.177

0.01

7.4 ± 4.3

6.8 ± 4.9

0.469

< 0.01

1.3 ± 0.5

0.071

0.02

1.1 ± 0.45

1.3 ± 0.5

0.040*

0.03

6.8 ± 2.9

0.021*

0.03

5.5 ± 2.6

6.6 ± 3.0

0.022*

0.03

17.0 ± 4.0 18.8 ± 8.2

0.012* 0.003*

0.04 0.05

19.0 ± 4.1 13.4 ± 8.9

17.3 ± 4.1 18.3 ± 8.8

0.011* < 0.001*,w

0.04 0.07

6.4 ± 5.1

< 0.001*,w

0.09

2.7 ± 3.2

5.8 ± 4.8

< 0.001*,w

0.11

8.0 ± 6.8

< 0.001*,w

0.12

2.3 ± 3.4

6.9 ± 6.1

< 0.001*,w

0.15

55.5 ± 11.3 18 (43.9) 37 (90.2)

0.089 0.385 0.133

0.02 0.07 0.18

59.3 ± 14.0 38 (36.5) 97 (93.3)

56.5 ± 12.2 25 (41.0) 56 (91.8)

0.201 0.571 0.089

0.01 0.04 0.20

12.3 ± 3.2

0.090

0.02

11.2 ± 3.8

11.8 ± 3.6

0.362

0.01

20 (48.8%) 9 (22.0)

0.754 0.033w

0.02 0.17

46 (44.2%) 40 (38.5)

31 (50.8%) 19 (31.1)

0.413 0.344

0.06 0.07

27 (65.9%)

0.537

0.05

70 (67.3%)

45 (73.8%)

0.383

0.07

0.025*,w

0.03

80.0 ± 84.2

111.9 ± 137.3

0.066

0.02

1.4 ± 1.3

1.2 ± 1.2

0.209

0.01

39 (37.5%)

23 (37.7%)

0.979

< 0.01

137.1 ± 159.9

Effect Size

1.2 ± 1.1

0.644

< 0.01

17 (41.5%)

0.553

0.05

Effect Size 0.66 0.56 0.54 0.55 0.06

Mean ± SD unless otherwise indicated. Effect size: Z2 for continuous variables, f coefficient for categorical variables. *P < 0.05. wP < 0.002 (corrected for multiple comparisons). ADL indicates Activities of Daily Living; CDR, Clinical Dementia Rating; CMMSE, Chinese Mini-Mental State Examination; NPI-Q, Neuropsychiatric Inventory Questionnaire; ZBI, Zarit Burden Interview.

among caregivers of persons with dementia. We were able to circumvent technical difficulties in defining the MD burden groups by using cluster analysis. Our results suggest that the MD model is more sensitive than the UD total score in identifying significant caregiver burden, allowing the identification of a distinct group with intermediate levels of burden. This intermediate group is characterized by disease features that more closely resemble the highburden group, unique caregiver characteristics, and by different caregiver and behavioral predictors of burden. Our study thus adds to the growing body of evidence that supports further exploration of the translation of the MD

caregiver burden concept into actual practice on the ground. Although the high-burden groups in both models share many similarities, there are distinct differences in terms of lower degrees of burden for ZBI total and factor scores, more spouses, and decreased monthly hours of informal care in the MD high-burden group. These differences are largely attributable to the discordant intermediate group of 20 caregivers who were classified as “low burden” by UD yet “high burden” by MD definitions. Despite the good agreement between UD and MD classification of caregiver burden, the lack of corresponding UD high-




TABLE 3. Classification of Low-burden Versus High-burden Groups

Multidimensional [n (%)]

Unidimensional Low burden (n = 124) High burden (n = 41) Total



Total [n (%)]

104 (63.0)

20 (12.1)

124 (75.2)

0 (0.0)

41 (24.8)

41 (24.8)

104 (63.0)

61 (37.0)

165 (100)

k = 0.72, P < 0.01.

burden/MD low-burden discordant cases suggests that the MD approach is more sensitive in picking up an intermediate group with significant burden which would have otherwise been missed by the UD model. Analysis of multiple domains via the MD model may provide a more holistic evaluation of caregiver burden, and thus overcome the limitations of a single UD score.8 Although we were able to define 3 levels of burden via the MD model, caregiver burden probably exists more along a continuum rather than in well-defined, equally distributed groups. As noted in our sample, the distinction between the 3 levels of burden is not equal in terms of disease and caregiver characteristics, as well as predictors of burden. For instance, while the presence of neuropsychiatric symptoms positively correlated with both intermediate and high burden, the specific symptoms leading to burden differed. In the intermediate-burden group, delusions and apathy caused more caregiver distress than the other NPI-Q components. Loss of motivation and engagement in apathetic care recipients leads to increased reliance on caregivers to initiate activities, and may also be misinterpreted as a sign of emotional disturbance or oppositional behavior, thus leading to caregiver stress and dissatisfaction with caregiving.34 The milder severity of dementia in our study population may explain why irritability/lability and apathy/indifference instead of agitation/ aggression were significant in the comparison models. Specific behavioral subdomains may also exert an influence on subjective burden by different mechanisms. For instance, the GERAS study reported that higher NPI-Q subdomain scores for apathy and psychosis, but not hyperactivity, were associated with greater caregiver supervision time; psychosis, affective, and apathy but not hyperactivity NPI-Q subdomains were also more likely to cause distress among adult-child caregivers compared with spousal caregivers.35 In contrast, personality changes, aggression, and mood problems were prominent in the high-burden group, as the physical and emotional strain from dealing with these problems leads to intense caregiver distress31 and increased additional hours of supervision.36 Other determinants unique to the intermediate-burden group were coresidence with the care recipient and decreased monthly hours of informal care. We noted that care recipients in the intermediate-burden group had less cognitive and functional impairment compared with the high-burden group. The main source of burden could thus be secondary to increased responsibilities and expectations of care33,37 or negative symptoms such as apathy, instead of actual functional dependence on the caregiver. Similar to Copyright

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Cheah et al,13 it was the working adult children caregivers who reported higher levels of burden in the high-burden group. This observation is likely due to generational differences and emotional distances between adult-child caregivers and care recipients.38 Adult-child caregivers also belong to the sandwich generation who has to deal with more secondary stressors (such as work commitments and family conflict), thus the perceived increase in role and personal strain from the caregiving role.1 Our study also highlights the inadequacy of the current arbitrariness surrounding what constitutes a suitable cutoff score in defining significant burden, which in turn creates uncertainty regarding the interpretation of ZBI total scores. In our study, the cutoff score of 28 for the intermediateburden groups corresponds to milder degrees of burden based upon the recommended ranges of 1 study.4 The existence of this intermediate-burden group opens up new ground for further research. A recent study among Japanese caregivers for patients with mild cognitive impairment using the short version of the ZBI reported that intermediate degrees of clinically significant burden are more prevalent than severe burden (20% vs. 4%).16 At this point, although the clinical significance of the intermediate group remains unclear, it could represent an at-risk group predisposed to caregiver stress and poorer outcomes, and with significant caregiver service needs. This is analogous to subsyndromal depression along the spectrum of depressive disorders, which can result in decrements in health status that do not differ significantly from “full-blown” syndromal subtypes.39 This suggests that the intermediate-burden group may benefit from early identification and institution of appropriate interventions such as caregiver education, coping strategies, and support programs.4 In a recent study among Asian family caregivers of persons with dementia, the use of behavioral disengagement and criticism as coping strategies were significant predictors of burden, whereas the use of encouragement was a predictor of gain from the caregiving role, suggesting that caregiver interventions that target coping strategies may improve outcomes of caregiving for dementia.40 While we managed to demonstrate that the MD approach is more sensitive in identifying a group with intermediate degree of burden, we were less successful in demonstrating the relevance of the MD model with regard to specific domains that contribute uniquely to overall burden. In particular, our MD clusters were more reflective of role and personal strain (factors 1 to 3) than worry about caregiving performance (factor 4). This was not an unexpected observation, as our results are consistent with those of earlier studies (appendix Table, Supplemental Digital Content, http://links.lww.com/WAD/A111) that factor 4 correlates weakly with ZBI total score and other ZBI dimensions.14,33 In our study, the observation of smaller effect size of factor 4 (Z2, 0.06 to 0.08) vis-a-vis the other factors (Z2, 0.50 to 0.76), supports the unique influence of factor 4 relative to the other factors. The lack of significant post hoc comparisons between different levels of burden in factor 4 scores could be either due to a high baseline level even in the low-burden group or to a less spectacular rise moving from intermediate-burden to high-burden groups. This corroborates earlier findings that worry about caregiving performance represents a unique dimension which is prominent even in mild cognitive impairment and the early stages of dementia.13,33 The validity of our results hinges on the success of cluster analysis in delineating high-burden and low-burden groups based upon similar data profiles across items. It is




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TABLE 4. Intermediate Versus Low-burden and High-burden Groups

ZBI scores ZBI total Factor 1 Factor 2 Factor 3 Factor 4 Care recipient characteristics Demographics Age Male sex [n (%)] Ethnicity [n (%)] Chinese Malay Indian Others Years of formal education Disease characteristics Clinical staging of dementia CDR global score CDR sum of boxes Cognitive status CMMSE (0-28) Functional status Bristol ADL score (0-60) Behavioral symptoms NPI-Q severity score (0-36) NPI-Q carer distress score (060) Caregiver characteristics Age Male sex [n (%)] Ethnicity [n (%)] Chinese Malay Indian Others Years of formal education Currently employed [n (%)] Relationship with care recipient [n (%)] Spouse Nonspousez Living with care recipient [n (%)] Total hours of informal care No. other caregivers Presence of domestic helper [n (%)]


Intermediate Burden (n = 20)


P

Effect Size

16.1 ± 7.1 7.9 ± 4.2 1.6 ± 1.7 3.3 ± 2.5 3.3 ± 2.1

32.0 ± 1.4* 14.1 ± 2.7* 6.0 ± 2.3* 8.3 ± 2.7* 3.7 ± 1.7

45.5 ± 8.7w,z 20.8 ± 4.6w,z 8.5 ± 3.2w,z 11.6 ± 3.4w,z 4.7 ± 1.7w

< 0.001y,8 < 0.001y,8 < 0.001y,8 < 0.001y,8 0.001y,8

0.76 0.64 0.65 0.63 0.08

77.1 ± 7.0 49 (47.1)

75.8 ± 6.9 10 (50.0)

78.6 ± 6.5 15 (36.6)

0.279 0.458 0.357

0.02 0.10 0.14

96 (92.3) 3 (3.9) 3 (2.9) 2 (1.9) 7.4 ± 4.3

19 (95.0) 0 (0.0) 1 (5.0) 0 (0.0) 7.9 ± 4.9

35 (85.4) 1 (2.4) 5 (12.2) 0 (0.0) 6.3 ± 4.9

0.366

0.01

1.1 ± 0.45 5.5 ± 2.6

1.2 ± 0.55 6.2 ± 3.3

1.3 ± 0.54 6.8 ± 2.9w

0.086 0.043y

0.03 0.04

19.0 ± 4.1

18.0 ± 4.3

17.0 ± 4.0w

0.025y

0.04

13.4 ± 8.9

17.1 ± 9.9

18.8 ± 8.2w

0.003y

0.07

2.7 ± 3.2 2.3 ± 3.4

4.7 ± 4.0 4.9 ± 4.0

6.4 ± 5.1w 8.0 ± 6.8w,z

< 0.001y,8 < 0.001y,8

0.15 0.22

59.3 ± 14.0 38 (36.5)

58.7 ± 13.8 7 (35.0)

55.5 ± 11.3 18 (43.9)

0.299 0.679 0.298

0.01 0.07 0.15

97 3 2 2 11.2 46

19 0 1 0 10.8 11

37 0 4 0 12.3 20

0.206 0.644 0.064

0.02 0.07 0.18

0.107 0.006y 0.350 0.686

0.16 0.06 0.01 0.07

(93.3) (2.9) (1.9) (1.9) (3.8) (44.2)

40 (38.5) 64 (61.5) 70 (67.3) 80.0 ± 84.2 1.4 ± 1.3 39 (37.5)

(95.0) (0.0) (5.0) (0.0) (4.2) (55.0)

10 (50.0) 10 (50.0) 18 (90.0) 60.4 ± 38.7 1.0 ± 1.3 6 (30.0)

(90.2) (0.0) (9.8) (0.0) (3.2) (48.8)

9 (22.0) 32 (78.0) 27 (65.9) 137.1 ± 159.9w,z 1.2 ± 1.1 17 (41.5)

Post hoc Bonferroni (P < 0.05). Mean ± SD unless otherwise indicated. Effect size: Z2 for continuous variables, Cramer V for categorical variables. *Low versus intermediate burden. wLow versus high burden. zIntermediate versus high burden. yP < 0.05. 8P < 0.002 (corrected for multiple comparisons). z“Nonspouse” includes children, siblings, and friends of the care recipients. ADL indicates Activities of Daily Living; CDR, Clinical Dementia Rating; CMMSE, Chinese Mini-Mental State Examination; NPI-Q, Neuropsychiatric Inventory Questionnaire; ZBI, Zarit Burden Interview.

thus reassuring that while the derived MD and UD groups have different degrees of burden in total and factor scores, they exhibit broadly similar direction of trends in caregiver and care recipient characteristics. Variables other than the 4-factor scores may need to be included in the delineation of clusters to enhance the discriminatory ability of cluster analysis in teasing out the unique effect of factor 4. Some

unique features of our study population may limit the generalizability of our findings, notably the predominantly Chinese Asian ethnicity; milder severity of dementia with concomitant less florid behavioral and functional issues; inability to exclude with certainty the influence of the differential distribution of dementia subtypes in the burden groups; and the availability of domestic helpers in around





TABLE 5. Regression Model of Factors Predicting Caregiver Burden

B

Factors

SE

Wald

Exp(B)

A. Low versus intermediate burden (n = 124)w CMMSE 0.06 0.08 0.57 0.94 CDR sum of boxes 0.02 0.12 0.03 1.02 NPI-Q severity score 0.24 0.08 8.67 1.27 Adult-child caregiver 0.42 0.59 0.50 0.66 Living with CR 1.84 0.90 4.21 6.32 Monthly hours of informal care 0.01 0.01 5.57 0.99 Regression model incorporating individual NPI-Q domains in place of the NPI-Q severity score Delusions 1.12 0.43 6.84 3.06 Irritability/lability 0.94 0.34 7.82 2.55 Apathy/indifference 0.86 0.34 6.59 2.37 B. Low versus high Burden (n = 145)z CMMSE 0.10 0.06 2.51 0.90 CDR sum of boxes 0.03 0.10 0.09 0.97 NPI-Q severity score 0.19 0.06 11.25 1.21 Adult-child caregiver 1.03 0.54 3.67 2.80 Living with CR 0.04 0.52 0.01 1.04 Monthly hours of informal care 0.00 0.00 2.02 0.16 Regression model incorporating individual NPI-Q domains in place of the NPI-Q severity score Disinhibition 2.33 0.76 9.34 10.22 Irritability/lability 0.71 0.28 6.36 2.03 Depression 0.53 0.26 4.08 1.69

95% CI

P

0.81, 1.10 0.80, 1.30 1.08, 1.48 0.21, 2.08 1.09, 36.78 0.98, 1.00

0.449 0.868 0.003* 0.478 0.040* 0.018*

1.32, 7.08 1.32, 4.92 1.23, 4.58

0.009* 0.005* 0.010*

0.80, 0.81, 1.08, 0.98, 0.38, 1.00,

1.02 1.17 1.35 8.05 2.89 1.01

0.113 0.759 0.001* 0.055 0.940 0.155

2.30, 45.39 1.17, 3.51 1.02, 2.82

0.002* 0.012* 0.043*

*P < 0.05. ww2 = 18.33, df = 6, P < 0.01; Nagelkerke R2 = 0.235; tolerance 0.62-0.89. zw2 = 31.42, df = 6, P < 0.01; Nagelkerke R2 = 0.284; tolerance = 0.59-0.82. CI indicates confidence interval; CDR, Clinical Dementia Rating; CMMSE, Chinese Mini-Mental State Examination; CR, care recipient; NPI, Neuropsychiatric Inventory Questionnaire.

one third of cases to assist in caregiving. Much of the evidence that supports the multidimensionality of the ZBI is based on studies conducted in white populations,7,8,11,12,15 suggesting that this may not be unique to Chinese populations. Studies in more advanced stages of dementia are needed to ascertain if the MD concept applies equally well to greater degrees of caregiver burden. The clinical significance of the intermediate group also requires follow-up of clinically relevant outcomes in a longitudinal study. In summary, this study demonstrates the limitations of a UD ZBI score, as well as the increased sensitivity and breadth of the MD model in identifying caregiver burden. We also highlighted the importance of identifying a group with intermediate burden, for which early recognition and intervention may help in preventing progression to high burden. A holistic assessment of caregiver burden via the MD ZBI scale may thus be increasingly relevant in clinical practice. Future studies should look to further develop the MD ZBI model, particularly focusing on better defining factor 4 (worry about performance), developing culturally applicable burden cutoffs, and determining the significance of the intermediate-burden group. ACKNOWLEDGMENTS The authors thank Ang Yue Ying, Shirley Tan, and May Wong for their assistance in the data collection. REFERENCES 1. So¨rensen S, Duberstein P, Gill D, et al. Dementia care: mental health effects, intervention strategies, and clinical implications. Lancet Neurol. 2006;5:961–973.

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