Validity and reliability of Persian version of chronic liver disease ...

Qual Life Res (2012) 21:1479–1485 DOI 10.1007/s11136-011-0059-5

BRIEF COMMUNICATION

Validity and reliability of Persian version of chronic liver disease questionnaire (CLDQ) Hilda Mahmoudi • Peyman Jafari • Mahvash Alizadeh-Naini Siyavash Gholami • Seyed Ali Malek-Hosseini • Sina Ghaffaripour

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Accepted: 27 October 2011 / Published online: 13 November 2011 Ó Springer Science+Business Media B.V. 2011

Abstract Purpose The aim of this study is to test the psychometric properties of the Persian version of the Chronic Liver Disease Questionnaire (CLDQ) in Iranian candidates for liver transplantation. Method One hundred and fifty-five consecutive adult patients awaiting liver transplantation completed the Persian version of CLDQ and the short-form health survey (SF-36). The etiology of cirrhosis, Child Pugh classification and Model for End stage Liver Disease (MELD) scores were taken from medical records. Results The scaling success rate for convergent validity was 100% for all domains, and the success rate for item

H. Mahmoudi Anesthesiology and Critical Care Research Center, Anesthesia Department, Shiraz University of Medical Sciences, Shiraz, Iran P. Jafari Department of Biostatistics, Shiraz University of Medical Sciences, Shiraz, Iran M. Alizadeh-Naini Gastroenterohepatology Research Center, Internal Medicine Department, Shiraz University of Medical Sciences, Shiraz, Iran S. Gholami Shiraz Organ Transplant Center, Shiraz University of Medical Sciences, Shiraz, Iran S. A. Malek-Hosseini Shiraz Organ Transplant Center, Department of Surgery, Shiraz University of Medical Sciences, Shiraz, Iran S. Ghaffaripour (&) Anesthesiology and Critical Care Research Center, Shiraz Organ Transplant Center, Department of Anesthesiology, Shiraz University of Medical Sciences, Shiraz, Iran e-mail: [email protected]

discriminant validity was 95.8% (139/145). The internal consistency (Cronbach a) for the domains ranged from 0.65 to 0.89. Multitrait–multimethod correlation matrix and factor analysis revealed that the CLDQ and SF-36 measure different constructs of quality of life. Conclusion The Persian version of the CLDQ, a diseasespecific questionnaire for measuring health-related quality of life, is accepted by liver transplantation candidates with adequate reliability and validity. There is no significant correlation of Child Pugh classification and MELD score with quality of life. Keywords Persian Quality Measurement Iran Transplantation CLDQ

Background People awaiting liver transplantation affected by advanced liver disease report remarkable impairments on Health Related Quality of Life (HRQL). Scores are typically impacted by cirrhosis and complications such as ascites and fatigue [1]. HRQOL that reflects patient’s subjective assessment of physical, mental and social dimensions of well-being and social functioning is considered a comprehensive and valuable outcome measure [2–4]. Generic instruments are used to compare the HRQOL between groups of patients, but disease-specific questionnaires distinguish the impairments of a specific illness and are more responsive to change [5]. The short-form health survey (SF-36) performs well as a generic instrument in liver disease patients [6] but it is less sensitive to changes in the patient’s health state. Therefore, the use of a diseasespecific HRQOL instrument for clinical studies in liver diseases is recommended [7–9].

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The Chronic Liver Disease Questionnaire (CLDQ) is the first liver-specific questionnaire developed by Younossi et al. [10] and has revealed appropriate validity and reliability. Appropriately translated and validated versions of the CLDQ provide a useful option for measuring HRQL of patients with chronic liver disease in different parts of the world [1]. The CLDQ has already been cross-culturally adapted and validated into a number of different languages [11–19]. Consequently, the aim of this study is to translate and validate the Persian version of the CLDQ in patients waiting for liver transplantation. Moreover, the correlation of Child Pugh Classification and Model for End stage Liver Disease (MELD) with quality of life was evaluated.

Materials and methods

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During this stage, the Persian version of the CLDQ was pilot tested in 10 patients waiting for liver transplantation. The patients completed the questionnaire and were interviewed as part of a cultural adaptation process with respect to the clarity of each item and the relevance of the content to their situation. Each patient was asked about what he or she thought was meant by each questionnaire item and the chosen response. Both the meaning of the items and responses were investigated. The results were reviewed, and the final version was obtained. The CLDQ, a 29-item self-reported questionnaire, is comprised of six domains including abdominal symptoms, fatigue, systemic symptoms, activity, emotional function and worry. All items are rated on an ordinal scale (1–7), with ‘‘1’’ corresponding to ‘‘all of the time’’ and ‘‘7’’ to ‘‘none of the time’’ which indicates the best possible function.

Participants Missing data imputation method Patients enrolled at Shiraz liver transplantation center––the most active liver transplantation center in the Middle East. Enrollees were consecutive adult outpatients, on a liver transplantation waitlist, who attended follow-up visits in the outpatient pre-transplant clinic. The study was approved by a local ethics committee, and the patients provided informed, written consent. During follow-up visits, patients completed two selfadministered questionnaires: CLDQ and SF36 [20]. The demographic data, including age, gender and educational level, were collected. Etiology of cirrhosis was also recorded, and Child Pugh classification and MELD scores were obtained on the same day that the questionnaires were administered.

We have followed the imputation method recommended by AUTHORS. The imputation was carried out when a maximum of four items were not completed and when no domain contained more than one missing value. If this criterion was not met, we excluded the questionnaire from the analysis. We used the hot deck imputation method. We dealt with missing data sequentially. We used ‘‘within-class matching,’’ where the imputed value comes from a patient in the same diagnostic group as the case with the missing item. A within-class match had either the same scores or the same sum total for the non-missing items in the same domain. Statistical analysis

Development of Persian version of CLDQ After obtaining permission from the developer of CLDQ by the first author, forward–backward translation was carried out according to a standardized guideline [21]. Forward translation was carried out by two independent bilingual translators whose native language was Persian. Reconciliation of both forward versions was done subsequently. Back translation was conducted by a native English speaker living in Iran who was fluent in Persian, did not have a medical background and was not aware of the original version of the questionnaire. The abbreviation ‘‘CLDQ’’ was kept for international communications. The resulting instrument was reviewed during focus group discussions and then was culturally adapted through a cognitive debriefing process used to identify language problems and to check comprehension and cultural relevance of the questionnaire.

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Cronbach’s alpha coefficient was used to check the internal consistency of the domains. Convergent and discriminant validity was checked using Spearman correlation. The value of a correlation coefficient of greater than 0.40 between an item and its own domain is regarded as an adequate evidence of convergent validity. Discriminant validity is supported whenever a correlation between an item and its hypothesized domain is significantly higher than its correlation with the other domains [22]. We used Pearson correlation coefficient to check the correlation of MELD score and Child Pugh classification with quality of life domains. In order to compare quality of life domains according to Child Pugh classification scores, we used oneway analysis of variance (ANOVA) and LSD as a post hoc test. The T-test was used to compare our findings with other studies. We used multitrait–multimethod correlation matrix and factor analysis to test whether the SF-36 and CLDQ measure the same constructs. It was hypothesized

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that different domains measuring similar constructs would show high correlations, whereas domains measuring different traits would not correlate strongly. High correlations (r [ 0.7) were hypothesized for the following domains: ‘‘fatigue’’ and ‘‘activity’’ (CLDQ) with ‘‘vitality’’ (SF36); and ‘‘emotional function’’ (CLDQ) with ‘‘mental health’’ (SF-36). Low correlations (r \ 0.50) were hypothesized for the CLDQ domain ‘‘abdominal symptoms’’ with SF-36 domains ‘‘role-emotional’’ and ‘‘mental health’’; and ‘‘worry’’ (CLDQ) with ‘‘physical functioning,’’ ‘‘role-physical,’’ and ‘‘bodily pain’’ (SF-36).

Results A total of 155 patients were enrolled. Demographic and clinical characteristics of the participants are shown in Table 1. Sixteen patients were classified as Child Pugh A, 70 as B, and 69 as C. The most prevalent etiologies of liver disease were hepatitis B and cryptogenic (24.5%) followed

Table 1 Demographic and clinical characteristics of the study population Age (year), mean ± SD

41.48 ± 12.75

Men/women, n (%)

100 (64.5)/55 (35.5)

Educational level, n (%) Illiterate Primary school

19 (12.3) 29 (18.7)

Secondary school

27 (17.4)

High school or diploma

59 (38.1)

University

21 (13.5)

Etiology of disease, n (%) Hepatitis B

38 (24.5)

Cryptogenic

38 (24.5)

Autoimmune hepatitis

21 (13.5)

Hepatitis C

14 (9)

Budd–Chiari syndrome

13 (8.4)

Primary sclerosing cholangitis (PSC)

10 (6.5)

Primary biliary cirrhosis (PBC)

6 (3.9)

Willson disease

6 (3.9)

Drug induced

2 (1.2)

Hemochromatosis Alcohol

2 (1.2) 2 (1.2)

Non-alcoholic steatohepatitis

1 (0.6)

Amiloidosis

1 (0.6)

Hyperoxaluria

1 (0.6)

MELD score, mean ± SD

19.99 (±5.63)

Child Pugh classification, n (%) Child Pugh A

16 (10.3)

Child Pugh B

70 (45.2)

Child Pugh C

69 (44.5)

by autoimmune hepatitis (13.5%). All patients easily selfcompleted the questionnaires except for people who required assistance completing the questionnaire either the interviewer or family members provided it. Table 2 depicts the quality of life domains measured by CLDQ and SF-36. With respect to Child Pugh classification scores,’’ physical functioning,’’ ‘‘bodily pain,’’ ‘‘social functioning’’ and ‘‘physical component summary score’’ of SF-36 and ‘‘abdominal symptoms’’ domain of CLDQ showed significant difference when analyzed with ANOVA. Table 2 reveals more details. We also considered Child Pugh score as a continuous variable and checked the correlation of Child Pugh and MELD scores with quality of life domains. Weak negative correlation existed between Child Pugh class and the same domains of SF-36, which revealed significant difference with ANOVA analysis: ‘‘physical component summary score’’ (r = -0.23); ‘‘physical functioning’’ (r = -0.18); ‘‘bodily pain’’ (-0.18) and ‘‘social functioning’’(r = 0.21). Meld score was not correlated to SF-36 domains except for ‘‘social functioning’’ (r = -0.20). Regarding CLDQ, only ‘‘abdominal symptoms’’ was correlated weakly with Child Pugh score (r = -0.20), and there was no any other significant correlation between CLDQ domains and Child Pugh or MELD scores. Table 3 summarizes the results of convergent and discriminant validity of the Persian version of the CLDQ. These findings show that the scaling success rates for convergent validity is 100% for all domains and the success rate for item discriminant validity is 95.8% (139/145). Table 4 shows correlations of CLDQ and SF-36 domains in a multitrait–multimethod correlation matrix. The three shaded numbers showed the correlations of the scores when different instruments were used to assess the same trait. These correlations ranged 0.49–0.62 and were less than 0.70. The exploratory factor analysis with Varimax rotation was used to determine the structure of all of the CLDQ and the SF-36 domains, and the result is shown in Table 5. Our findings indicate that the first factor includes all domains of the CLDQ, and the second factor extracted includes all domains of the SF-36 except the ‘‘bodily pain’’ domain, which had an almost equal loading between the CLDQ and the SF-36. The internal consistency of the scales and the mean score of the domains are presented in Table 6. Cronbach’s a ranged from 0.65 to 0.89.

Discussion It is essential to assess and compare quality of life of liver disease patients including candidates for liver transplantation. Perhaps, better phrased in terms of instruments that have been translated and validated and the results

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Table 2 Mean (SD)a scores of the CLDQ and SF-36 domains in Iranian candidates of liver transplantation CLDQ

Total

Child Pugh classification

Domain; mean (SD)

Child Pugh class A (n = 16)

P value

Child Pugh class B (n = 70)

Child Pugh class C (n = 69)

Abdominal symptoms (AB)

4.26 (1.67)

4.81 (1.80)

4.54 (1.51)$

3.85 (1.71)$,

Fatigue (FA)

3.21 (1.40)

3.66 (1.76)

3.40 (1.37)

2.92 (1.31)

0.01* 0.06

Systemic symptoms (SYS)

4.07 (1.46)

4.06 (1.71)

4.20 (1.41)

3.95 (1.46)

0.58

Activity (AC)

3.38 (1.55)

3.56 (1.57)

3.60 (1.63)

3.11 (1.44)

0.15

Emotional function (EM) Worry (WO)

3.70 (1.51) 2.92 (1.57)

3.75 (1.55) 2.68 (1.55)

3.87 (1.55) 3.11 (1.60)

3.52 (1.47) 2.79 (1.54)

0.40 0.41

CLDQ overall score

3.59 (1.29)

3.75 (1.42)

3.79 (1.27)

3.36 (1.27)

0.12

Physical functioning (PF)

39.83 (25.98)

36.68 (20.20)

46.07 (26.53)$

33.55 (25.38)$

0.01*

Role-physical (RP)

31.00 (25.53)

36.71 (27.65)

34.46 (26.12)

26.17 (23.90)

Bodily pain (BP)

40.64 (25.56)

49.21 (30.20)

44.07 (25.84)$

35.18 (23.26)$,

General health (GH)

37.58 (18.39)

32.81 (15.38)

39.64 (18.24)

36.59 (19.12)

36.65 (23.61)

44.14 (25.25)

38.83 (22.71)

32.69 (23.75)

0.12

42.82 (27.83)

43.75 (30.27)

51.60 (26.23)$

33.69 (26.28)$

0.001*

SF-36

Vitality (VT) Social functioning (SF)

a

0.10

0.04* 0.34

Role-emotion (RE)

39.03 (27.27)

39.06 (26.47)

40.11 (26.05)

37.92 (28.95)

0.89

Mental health (MH)

52.03 (23.15)

49.06 (21.38)

53.35 (22.53)

51.37 (24.37)

0.76

Physical component summary score

35.34 (8.02)

36.94 (8.67)

37.26 (7.84)$

33.02 (7.53)$

0.005*

Mental component summary score

37.65 (10.47)

37.12 (10.33)

38.57 (10.04)

36.83 (10.99)

0.60

Standard deviation

* Indicates that the differences are significant at 0.05 level $

Difference is significant between Child Pugh Class B and C

Difference is significant between Child Pugh Class A and C

Table 3 Convergent and discriminant validity of the Persian version of the CLDQ Scale

No. of items per scale

Convergent validitya Range of correlation

Discriminant validityb Scaling success (%)

Range of correlation

Scaling success (%)


3

0.81–0.89

3/3 (100)

0.29–0.61

15/15 (100)

Fatigue (FA)

5

0.72–0.79

5/5 (100)

0.41–0.70

23/25 (92)


5

0.66–0.75

5/5 (100)

0.30–0.60

24/25 (96)

Activity (AC)

3

0.67–0.80

3/3 (100)

0.32–0.64

14/15 (93)

Emotional function (EM)

8

0.64–0.82

8/8 (100)

0.33–0.64

38/40 (95)

Worry (WO)

5

0.73–0.83

5/5 (100)

0.27–0.65

25/25 (100)

a

Number of correlation between items and hypothesized scale corrected for overlap C0.4/total number of convergent validity tests

b

Number of convergent correlations significantly higher than discriminant correlations/total number of correlations

compared to those who have translated and validated the same instrument in another country [23]. We concluded that the Persian version of CLDQ, a disease-specific questionnaire for measuring HRQOL, is accepted by liver transplantation candidates with adequate reliability and validity. All domains met the minimum reliability criterion of Cronbach‘s a coefficient over 0.7, except for the ‘‘Activity’’ domain. Our findings revealed that the CLDQ has excellent convergent and discriminant

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validity. Although our results showed that the correlations between CLDQ and SF-36 domains are significant, they are not higher than [0.7. Hence, we cannot conclude our hypothesis that the CLDQ and SF-36 measure the same trait. Moreover, the exploratory factor analysis extracted two different QOL factors: one includes all of the domains of the SF-36 while the other one includes all of the domains of the CLDQ. This issue indicates that the Persian version of the SF-36 and CLDQ measure two different constructs

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Table 4 Multitrait–multimethod correlation matrix: CLDQ domain intercorrelations and correlations of CLDQ domains with SF-36 domains Abdominal symptoms (AB)

Fatigue (FA)


Activity (AC)


Worry (WO)

CLDQ Abdominal symptoms (AB) Fatigue (FA)

0.62


0.67

0.74

Activity (AC)

0.59

0.79

0.72


0.060

0.73

0.77

0.068

0.470

0.62

0.67

0.59

Worry (WO) SF-36

0.73


0.32

0.49

0.42

0.50

0.42

0.32

Role-physical (RP)

0.36

0.56

0.49

0.58

0.44

0.43

Bodily pain (BP)

0.47

0.61

0.63

0.55

0.58

0.49

General health (GH)

0.35

0.49

0.48

0.43

0.46

0.50

Vitality (VT)

0.30

0.57

0.41

0.49

0.48

0.46

Social functioning (SF)

0.33

0.52

0.51

0.47

0.54

0.47

Role-emotion (RE)

0.31

0.51

0.50

0.43

0.55

0.54

Mental health (MH)

0.31

0.49

0.46

0.38

0.62

0.49

Correlations hypothesized to be high are in italics Table 5 Factor loadingsa of two construct solution

Table 6 Mean score and internal consistency of the domains of the Persian version of the CLDQ

Domains

CLDQ

SF-36


0.193

0.724

Role-physical (RP)

0.311

0.689


4.26 (1.67)

0.83

3.21 (1.41)

0.83

Domains

Mean score (SD)

Cronbach’s a

Bodily pain (BP)

0.560

0.510

Fatigue (FA)

General health (GH)

0.391

0.514


4.08 (1.46)

0.74

Vitality (VT)

0.199

0.780

Activity (AC)

3.38 (1.56)

0.65

0.575


3.70 (1.52)

0.89

2.92 (1.57)

0.83

3.59 (1.29)

Social functioning (SF)

0.403

Role-emotion (RE)

0.359

0.621

Worry (WO)

Mental health (MH)

0.252

0.732

Total score


0.826

0.084

Fatigue (FA)

0.755

0.453

Systemic symptoms (SYS) Activity (AC)

0.848 0.751

0.318 0.382


0.770

0.418

Worry (WO)

0.674

0.401

The loading weights of the factor corresponding to the domains of each questionnaire are bolded a

Extraction method: principal component with Varimax rotation

of health-related quality of life and cannot be used instead of each other. This disparity between Iranian and American versions may be the cause of cross-cultural differences. Previous published data demonstrated that when liver disease becomes more severe, identified by an increase in the Child Pugh score in advanced cirrhosis compared to no cirrhosis or compensated cirrhosis, HRQL also becomes more impaired [11, 24–26]. However, CLDQ revealed similar HRQL scores in patients with advanced cirrhosis

(Child Pugh class B or C). One possible explanation is that clinical worsening between Child Pugh class B and C is not accompanied by the corresponding worsening in HRQL [10]. It seems that the ‘‘floor effect’’ for CLDQ, with disease severity, prevents the measurement of deterioration between Child Pugh class B and C. In the present study, we enrolled patients waiting for liver transplantation. The vast majority with advanced liver cirrhosis was categorized in Child Pugh class B or C. Moreover, some interventions such as salt restriction, diuretics and Vitamin K can temporarily decrease the Child Pugh score especially in a patient with a borderline child Pugh score (e.g., score 7 classified in child Pugh class B). But quality of life does not improve with the same speed. Consequently, a patient classified in Child Pugh class A may have more impairment in his/her quality of life than expected for this class. This assumption is made because

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limitation of the Child Pugh classification happens in patients who are treated a few days before visiting in pretransplant clinic. Consideration of the above along with the small sample size of the Child Pugh class A (16 patients) are possible reasons for our inability to show difference in CLDQ domains between Child Pugh classes. One study, which recruited liver transplantation candidates with advanced liver disease, showed that neither the MELD score nor the Child Pugh score was a predictor of CLDQ and SF-36 domains [27]. We found that the quality of life measured by the SF-36 questionnaire is profoundly impaired in candidates of liver transplantation compared with that of the general Iranian population [28]. Our findings indicate that quality of life in Iranian candidates of liver transplantation measured by CLDQ is similar to Americans candidates, except for the ‘‘Worry’’ domain which is lower in Iranians patients [27, 29]. It shows that Iranian patients are more concerned about their disease, its impact on their family and the availability of a suitable liver for transplantation. When we compared CLDQ domains of our patients with those of American cirrhotic patients, it was revealed that ‘‘activity,’’ ‘‘emotional function,’’ ‘‘worry,’’ and total CLDQ domain scores are significantly lower in our study population [24]. The mean scores of CLDQ found in our patients are lower than those found in Thailand [11], Germany [13], Spain [14] and China [18]. This might be the result of sampling differences. Specifically, about ninety percent of our patients had advanced liver cirrhosis, either Child Pugh class B or C, which is significantly higher than other studies’ samples. Our study had some limitations. First, we were unable to evaluate the instruments responsiveness to change in health-related quality of life over time due to the crosssectional design of our study. Second, all patients in our study were recruited from the outpatient, pre-transplant clinic. This means that admitted patients with more severe disease may not have been captured. This potentially brings the problem of generalizability of our findings to all candidates of liver transplantation. Acknowledgments We would like to express our appreciation to all patients for consenting to participate in this study. We also thank Dr Zobair M. Younossi for permission to use and translate the CLDQ English version into Persian. In addition, we thank Raymond McCarthy Bergeron and Meghdad Asadi for English editing.

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