Cross-cultural Adaptation and Validation of Kidney Disease Quality of Life (KDQOL™-36) - Malayalam Version


The aim of this study was to translate the original Kidney Disease Quality of Life (KDQOL™-36) questionnaire into one of the South Indian languagesMalayalamand estimate its psychometric properties. Patients with chronic kidney disease (CKD) generally have an impaired quality of life (QOL). Kerala, the southernmost state of Indiaclaimed to be a model in development indices for low- and middle-income countrieshas an alarming rate of kidney disease statistics. The KDQOL™-36 questionnaire has not been validated yet to Malayalam, the official language of Kerala. The study used a methodological research design. The questionnaire was first translated into Malayalam by bilingual subject experts, and then translated back to English. First, we drafted a re-conciliated version and then did a cognitive debriefing among ten CKD patients. The final questionnaire was administered to 200 patients with CKD. Internal consistency, test-retest reliability and construct validity were evaluated. Correlations between global health rating items and subscales were also made. The study followed the ‘STrengthening the Reporting of OBservational studies in Epidemiology’ (STROBE) guidelines for observational studies. The sample characteristics showed that a majority of participants were males (61%) with a mean age of 57.66 years. Cronbach’s alpha was within an acceptable level (0.74). All items of KDQOL™-36 had a substantial correlation with the global health status scale. The intra-class correlation coefficient for test-retest reliability was found to be 0.70. KDQOL™-36 is a valid and reliable tool for measuring the QOL of CKD patients in Kerala. A disease-specific CKD QOL scale was lacking in the clinical scenario of Kerala, especially when a significant proportion of patients is affected and is on renal replacement therapy. The cross-cultural adaptation of Malayalam KDQOL™-36 facilitates clinical utility for both healthcare providers and CKD patients, and it is simple to administer without any formal training in various settings.


In the last few decades, Health-Related Quality of Life (HRQoL) has gained momentous attention in the healthcare scenario [1, 2]. Quality of Life (QOL) is a complex, subjective entity and a much relevant concept in the current healthcare realm, specifically in the purview of chronic diseases [3]. In this era of non-communicable disease surge, chronic kidney disease (CKD) is a global health menace. Owing to its protracted and incapacitating nature, QOL among CKD population is impaired, in spite of advances in treatment modalities [4].

QOL measurement is significant as it forms the crux of policy decisions and technological innovations in healthcare. A variety of general and disease-specific tools are available to measure the QOL. However, an ideal tool should be culturally, linguistically and contextually appropriate and should have a colloquial appeal [5,6,7,8]. The Kidney Disease Quality of Life (KDQOL™-36) is a widely recommended tool for assessing the QOL among patients with CKD [9]. The KDQOL™-36 has been translated and validated to many languages but not in Malayalam, the official language of Kerala. Around 37 million people speak Malayalam globally [10, 11]. Hence, cross-cultural adaptation is necessary in this context.

Over the years, Kerala has gained significant attention in the global arena with its consistent and exemplary track record in the literary, healthcare and developmental indicators [12, 13]. However, a myriad of cultural, regional, and social factors made this state an abode of non-communicable diseases [14, 15]. Lack of a wholesome and comprehensive management system of non-communicable disease fuels up this aspect [16]. Few studies from India reported a CKD prevalence of 9–17% and incidence rate ranging from 151 to 232 per 100 thousand population [17]. Despite collaborative efforts to subsidise care strategies for CKD patients in Kerala, patients are experiencing innumerable hardships, and it has direct implications to the QOL of patients [18]. In this context, an evaluation of QOL using a culturally sensitive and dedicated tool is critical for Malayalam-speaking patient population. Though KDQOL has been translated into various languages across India, a regional version is imperative as India has a diverse and complex cultural, regional and demographic profiles [19,20,21]. Therefore, the researchers intended to test the psychometric properties, reliability and a cross-culturally adapted version of KDQOL™-36 among Malayalam-speaking patients with CKD.

Materials and Methods

This study used a methodological study design for validation and followed the ‘STrengthening the Reporting of OBservational studies in Epidemiology’ (STROBE) guidelines for observational studies to ensure quality (see Supplementary file 1).

The Kidney Disease Quality of Life (KDQOL™-36) Questionnaire

KDQOL™-36 is an abridged form of the Kidney Disease Quality of Life Questionnaire, (KDQOL™-134) designed by the RAND Corporation (RAND), USA in 1994, which is a public document available free of charge [9]. We obtained permission from the RAND group for translating KDQOL™-36 and for making the required changes to adapt it to the Kerala culture. It has primarily two components—the generic core and the disease-specific component. The generic core is the Short Form 12 Health Survey (SF-12), and it contains the Physical Component Summary (PCS - 6 items) and the Mental Component Summary (MCS - 6 items). The disease-specific component has three subdomains, viz., burden of kidney disease (4 items), symptoms and problems (12 items), and effects of kidney disease (8 items). The score ranges from 0 to 100, with higher scores indicating a better QOL. The scoring toolkit is freely available online [22].

Translation Procedure

We followed the series of guidelines available for cross-cultural validation of instruments and also the specifications provided by RAND Health Care for the translation of KDQOL™-36 [23, 24]. Translation and psychometric validation are the two crucial steps in this process. Translation also requires special mention, as a mere literal translation of scales prepared in the western context may fail to capture the nuances and layers of the same attribute in a culturally different scenario at Kerala [24].

Forward Translation

Two independent bilingual subject experts (one psychologist and one dialysis nurse) have done the first step of forward translation from the source language (English) to Malayalam by focusing on ease of understanding, cultural equivalence and conceptual equivalence, rather than linguistic or precise rendition. Special care has been taken to make sentences as simple as possible without dropping the intended meaning.

Expert Panel Consultation

The first draft was then presented to a group of bilingual experts, comprised of original translators, social scientists, nurse researchers, nephrologists and a dialysis technician. They reviewed each item with its responses and discussed on the issues related to cultural differences. Changes were made in item numbers 2 and 3 by replacing the kind of household chores with more locally congruent ones. The panel sought most appropriate terms through an iterative approach and prepared a mutually agreed version.


After the expert committee review, the first draft was subjected to ‘back-translation’ (from Malayalam to English) by two subject experts with a high level of proficiency in English and Malayalam, who were not involved with the project. No reference was made about the original English version. This step was to ensure a meaningful process of translation.

Expert Consultation

The back translated version was then compared with the original KDQOL™-36 for any incongruity. A panel of inter-disciplinary experts reviewed this version and assessed the face and content validity of the tool. Furthermore, we had a series of discussions with the experts involved in the process, and a re-conciliated version was obtained.

Pre-Testing and Cognitive Interviewing

The final Malayalam draft tool was pre-tested and cognitive debriefing was done on ten patients with CKD including four on haemodialysis. This cognitive interview process mainly focused on the comprehensiveness and cultural appropriateness of the items and instructions. The patients were asked about their ability to understand and interpret items relevant to their disease processes. We encouraged critical feedback on instructions to administer scales and set of responses from the patients. Few of them expressed their confusion on certain items (e.g. item number 33 ‘dependence on health care personnel’. The exact Malayalam word for dependence was changed to a more colloquial word. Two of them expressed query on the term access site’ in item number 28). Further comments and suggestions were noted and later integrated in the draft to make the final version. Clarity and relevance of the tool were evaluated using the content validity index (CVI) by observing the percentage of dichotomous responses ‘yes’ or ‘no’. A CVI of > 0.8 was considered acceptable [25].

Field Testing

After the prescribed norms of translation, the researchers ensured the semantic, idiomatic, experimental and conceptual equivalences of the tool and undertook a field study. The field testing was carried out from August 2018 to January 2019. In order to be statistically scrupulous, the sample size was determined based on the norms, i.e. 5 subjects per item (total number of items: 36), calculated sample size was 180, rounded off to 200 [26]. The final version was administered to 200 patients with CKD—irrespective of the aetiology and stage. Samples were recruited consecutively from patients who came for a review at the outpatient clinic, belonging to the Department of Nephrology of a tertiary level referral institution in South Kerala. The screening criteria for inclusion were patients who were aged above 18 years, who knew how to read and write in Malayalam, and who gave their informed consent. Severely debilitated patients and patients with language and comprehension issues were excluded.

KDQOL was used as a self-reported tool in our study except for those patients who were not able to read. All questions were found to be easily understandable and acceptable. Time taken for completing the questionnaire was approximately 8–10 min. The collected data was then cleaned, coded and entered in the dedicated software designed by RAND.

Statistical Techniques

Socio-demographic characteristics of the participants were expressed in terms of means, standard deviations and percentages. Floor and ceiling effects were measured initially.

Reliability Analysis

Cronbach’s alpha, the corrected item total correlations, the mean inter-item correlations and the alpha-if-item-deleted were calculated to assess the internal consistency; and as per Nunnally’s criteria, 0.70 was taken as a degree of acceptability [27, 28]. We administered the final tool to 20 patients each on maintenance haemodialysis 2 weeks apart to measure the test-retest reliability. Inter-rater reliability was assessed by two simultaneous observations done by two raters on another set of 20 patients. Both reliability statistics were established by intra-class correlation coefficient.

Validity Analysis

The data were then subjected to principal component analysis. Prior to factor analysis, we examined the data for missing values and outliers and ensured its appropriateness for factorisation. Measures of sampling adequacy (MSA), Kaiser–Meyer–Olkin (KMO) statistics and Bartlett’s Test of sphericity were done. Minimum sample size should be five times the number of items or greater, and this criterion is fulfilled in this study [29]. In order to establish the construct validity, we have done an exploratory factor analysis (EFA) using principal component analysis and varimax rotation with Kaiser normalisation. In order to achieve the best possible factor structure, we used the following criteria: Eigenvalue > 1, factor loading > 0.35 and cumulative percentage variance > 60% [30].

The data were analysed using the statistics software Statistical Package for the Social Sciences (SPSS, IBM Corporation; Armonk, NY, US) version 20.


Sample Characteristics

In the final phase of tool validation, 200 patients with CKD were interviewed. The majority of the participants were males (n = 122; 61%). The mean age of study subjects was 57.66 ± 10.6. The majority of patients (n = 66; 33%) were in CKD stage III. Diabetes was found to be the major cause of CKD (134; 67%) and 18.5% of the cases had Chronic Kidney Disease of unknown origin (CKDu). Regarding occupation, 82% of the patients were previously employed, but a significant fraction of patients (63%) lost jobs due to the disease. The mean haemoglobin level was 10.45 (Table 1). Descriptive statistics of each item were determined to check for floor and ceiling effect.

Table 1 The demographic and clinical characteristics of the participants (n = 200)

Psychometric Evaluation

Psychometric properties were within satisfactory levels. Item wise and domain wise mean ± standard deviation was determined. Reliability analysis of 36 items in the KDQOL™-36 tool revealed that Cronbach’s alpha was acceptable, i.e. 0.746 [31]. Cronbach’s alpha coefficients of three disease-specific domains (burden, symptoms, effect) ranged from 0.729 to 0.856. Most of the items seemed to be worthy of retention, resulting in a reduction of alpha level if deleted. Factor level estimation of the questionnaire also revealed satisfactory internal consistency except for PCS and MCS (Table 2). Inter-item correlations were measured between global health items and all five domains, and the values ensured that the items captured the same construct (PCS, 0.52; MCS, 0.49; burden, 0.54; symptoms, 0.46; effect, 0.45).

Table 2 Cronbach’s alpha values of Malayalam version of the KDQOL-36 questionnaire among patients with chronic kidney disease. (n = 200)

Intra-class correlation coefficient established for test-retest reliability was 0.70 (95% CI 0.539–0.803, P < 0.001), and it was 0.732 for inter-rater reliability (95% CI, 0.713–0.751; P < .0.001). Both the values were found to be satisfactory.

The researchers carried out EFA using principal component analysis with varimax rotation to test the construct validity. The factor structure was evaluated by using inter-item and item-to-total scale correlations. KMO index yielded a value of 0.799, which reflected adequate sample size (middling criterion). Bartlett’s test of sphericity was also generated by SPSS and was found to be significant (p < .0001). Several items had cross-loadings and were hence sorted out logically based on principles of loading, and a seven-factor structure was obtained in contrast to the five-factor original one. However, after examining the loaded items and discussion with experts, it was decided to consider these newly emerged factors as subdomains under PCS and MCS. This factorisation output accounted for a total cumulative variance of 63.95% (Table 3 and Fig. 1).

Table 3 Principal component analysis output
Fig. 1

Scree plot


Chronic disease statistics are alarmingly high in Kerala. CKD also is not an exception. Thus, assessing QOL in a patient with CKD is critical. KDQOL™-36 has been validated and translated into many Indian languages like Hindi, Kannada, Marathi and Tamil. This is the first time that KDQOL™-36 Malayalam has been validated among patients with CKD in Kerala [19, 20].

The series of forward and backward translations was done as per the prescribed norms for translation and revalidation. Experts from all relevant disciplines were involved in a series of draft scrutiny process. This facilitated the researchers to handpick the most suitable terms in the vernacular language. The examples in item number 2 (pushing a vacuum cleaner, bowling or playing golf) were replaced with more locally congruent activities, such as mopping rooms or cutting vegetables. In accordance with the WHO guidelines, the researchers focused more on conceptual translation than on linguistic conversion. As the meaning of the word ‘accomplishment’ in Malayalam is more concerned with material gains, item numbers 4 and 6 (‘accomplished less than you would like’) were translated to ‘unable to perform up to the desired level’. The exact rendition for item number 11 (‘Have you felt downhearted and blue?’ ) was also found to be not fitting in true sense when used in the Malayalam tool. Therefore, the item was translated as ‘Have you felt depressed and sad?’. Such efforts have also been attempted in other related studies to address the cultural differences [19, 20, 32]. At every step, we ensured that forward and backward translations were robust, locally sensitive and culturally sensitive, and the meaning of each item did not deviate from the original meaning. This will simplify the process of administering KDQOL™-36 to the Malayalam-speaking population.

During the pilot study, the initially translated options for item numbers 2 and 3 were found confusing for the patients and were therefore modified to comprehensible terms. Cognitive debriefing revealed the nuances and subtleties of subject views on certain items like item numbers 11, 15, and 16 and the degree of trauma with the disease burden. Generally, patients preferred to restrict the item responses to three as the current five- or six-option format was often confusing or exhausting for a layperson.

All items had 100% response rate except for the item on sexual life (item number 35). This may be due to the sensitive nature of the item and the inherent reluctance of Keralites to open up on sexuality in a public sphere [33]. A trivial proportion of patients (8.5%) being unmarried may also contribute to the partial response.

This study, which explored the psychometric properties of the Malayalam version of KDQOL™-36, revealed an acceptable level of internal consistency reliability (Cronbach’s alpha > .746). Hence, it is evident that KDQOL™-36 and its subscales are feasible to use in Kerala’s social and cultural context. This is in congruence with major national and international studies [19, 20, 32, 34]. Mateti et al. validated the Kannada version of KDQOL™-36 and found that it possesses an acceptable range of internal consistency (PCS, 0.729; MCS, 0.7650; burden, 0.7731; symptoms/problems, 0.7391; effects, 0.7636) [19]. In our study, the mean scores of PCS and MCS were found to be low, 0.421 and 0.491, respectively. This may be due to the inadequate sample size or because of the domain dealing with general health issues or patients getting disturbed with disease-specific concerns. This finding was also congruent with a Chinese validation study conducted among Cantonese-speaking Hong Kong population [32].

Reliability statistics for the overall questionnaire showed an acceptable level of the intra-class correlation coefficient. Moderately lower range of test-retest reliability may be attributable to the acute worsening of symptoms among few patients in the cluster. Responses to item number 20 (symptoms/problems: Itchy skin?) and item number 22 (symptoms/problems: Shortness of breath?) demonstrated significant difference in the responses (‘not at all bothered’ in test and ‘very much bothered’ or ‘extremely bothered’ in retest). This was in contrast to the findings from most of the literature [33, 3435.36]. Though the original tool is designed as a self-administered type, we were forced to administer it, as few of our patients were sick and illiterate. Hence, we computed intra-class correlation coefficient to determine the inter-rater reliability, and it was found to be reliable.

Construct validity was evaluated using the principal component method with varimax rotation. In our study, factor loadings of the items ranged from 0.385 to 0.657(Table 4). This study considered the sample size for evaluating the acceptability of factor loading. The findings from the current study found few differences from the original tool, possibly due to inadequate sample size, variation in samples, different types of factoring used and different study settings.

Table 4 Seven factors with factor loading for CKD patients (n = 200)

Like health and illness, QOL is also a subjective phenomenon. Cultural and linguistic sensitiveness is crucial in tapping the nuances of QOL. Owing to the chronicity, treatment-related burden and disabling nature of CKD, the perceptions of patients with regard to QOL is vital in rendering healthcare services. Apart from the quantitative measurements, in-depth qualitative explorations will generate fruitful aspects of QOL, and its assimilation into existing questionnaires can be considered. Kerala’s innate linguistic and cultural diversity further demands extended works based on the current study. Hence, a multi-centric study with large sample size using KDQOL™-36 Malayalam may yield results which may be more promising.

Since the study was carried out at one of the largest tertiary care referral and teaching hospitals in South India, the researchers could ensure a representative population. The major limitation of this study is that the participants comprised of patients with varying stages of CKD. Another limitation is that we could not perform other validity measures like convergent or concurrent validity because of patients’ discomforts related to multiple tool administration. Therefore, such initiatives among specific homogenous group—like patients on haemodialysis or peritoneal dialysis or stage wise comparisons—will be clinically meaningful.


The present study intended to translate KDQOL™-36 into Malayalam and confirm a cross-cultural equivalence and validation for the same. Until now, there were no validated tools in Malayalam to assess the QOL among CKD patients. Our study is the first of its kind and the findings reveal that the Malayalam version of KDQOL-36™ possesses robust psychometric properties and its cultural adaptation is acceptable.


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The authors express their gratitude to RAND—the original developers of KDQOL-36—for their permission to translate and use the KDQOL-36. We are indebted to all the patients who participated in this study and unwearyingly given their responses. We also would like to express our sincere gratitude to all the experts who were involved at various phases for translation, back-translation, and preparation of a Malayalam KDQOL-36 tool. We are also grateful to the funders of this study, State Health System Research council, Kerala.


This study has been funded by State Health System Research council, Kerala.

Author information




Study design: RCK, ASK; data collection and analysis: RCK, ASK, and SKKS; manuscript preparation: RCK, ASK, and SKKS.

Corresponding author

Correspondence to Radhika C K.

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Conflict of Interest

The authors declare that they have no conflicts of interest.


Permission has been obtained from RAND for translating and validating the questionnaire through email. Prior to the commencement of the study, approval was obtained from the Human Ethics Committee, Government Medical College, Thiruvananthapuram. After explaining the purpose of the study, an informed written consent in the native language was taken from all participants for recruitment and for publication of the study findings. Respondents were asked for voluntary participation only and they were assured the right to withdraw from the study at any point of time. A copy of the consent and participatory information sheet was given to the participants. All authors declare that they do not have any conflicts of interest. The authors hereby acknowledge the funding support provided by State Health System Research Centre, Kerala (SHSRCK).

Additional information


What does this paper contribute to the wider global clinical community?

• QOL measurement always holds a prominent and significant place in the healthcare realm. The KDQOL™-36 is a widely recommended tool for assessing the QOL among patients with CKD. No Malayalam version existed.

• Appropriate and efficient clinical tools are required to measure the QOL of CKD patients in Kerala, especially at a time when Kerala has been branded as the ‘hub of lifestyle diseases’ with escalating rates of non-communicable diseases and CKD.

• The validated version of Malayalam KDQOL™-36 is easy to administer. This will help nurses, who are the first-line care providers, to assess the varying needs of patients and to design individually tailored healthcare interventions to enhance the QOL of the CKD population and to assess the effectiveness of such interventions.

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K, R.C., Kumar, A.S. & Kumar, K.S.S. Cross-cultural Adaptation and Validation of Kidney Disease Quality of Life (KDQOL™-36) - Malayalam Version. SN Compr. Clin. Med. 2, 933–941 (2020).

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  • Chronic kidney disease
  • Quality of life
  • KDQOL™-36
  • Reliability
  • Validity
  • Translation
  • Cross-cultural adaptation