Background
Globally, chronic diseases are leading causes of mortality, morbidity, and disability, with the greatest impact in low- and middle-income countries.[1] In India, the combination of a substantive and growing burden of noncommunicable diseases (NCDs), a persisting burden of chronic communicable diseases, increasing life expectancy, and changing socio-economic conditions pose a significant challenge. In addition, there is an increased burden of multimorbidity in India, with prevalence estimates ranging from <10% to >50% depending on the definition used and the population studied.[2,3] Chronic diseases require medical attention for extensive periods of time and frequently result in impaired performance of daily activities and reduced quality of life (QoL) of patients as well as caregivers.[4] For most chronic diseases the overall health of patients worsen due to decrease in their productivity and ability to perform daily activities, thus lowering health related quality of life (HR-QoL). Decrease in HR-QoL contributed to additional economic burden. As such, measuring QoL is key to understanding several aspects of chronic disease. While several tools for assessment of QoL in people with chronic disease exist, there has been no systematic evaluation of these tools through evidence synthesis methodologies. With the increasing corpus of research on chronic disease and multimorbidity in India, a “one-stop” summary of all such tools can enable researchers and program managers to choose tools more efficiently and in an evidence-informed manner. Such an exercise is also important from the point of view of informing the future research agenda on tool development for QOL in India. The study aims to identify reliable and validated tools used for measuring QoL for chronic conditions and multimorbidity for adults in India with a focus on measurement properties and domains of measurement. For this purpose, a scoping review was conducted. A scoping review is a fit-for-purpose evidence synthesis approach as we primarily aim to highlight the gaps in the domain without any intention of comparative assessment of tools.
Methods
Protocol and registration
The study is a part of a larger scoping review on QoL for chronic diseases in India – the protocol for which was registered in Open Science framework and is available publicly (https://osf.io/unbck). The current study reports on the tool component of the larger review, while other components (interventions to decrease QoL and impact on QoL) are being presented elsewhere. The PRISMA Extension for Scoping Reviews checklist [Appendix 1] was used for reporting the study.[5]
Eligibility criteria
Studies that met the following criteria were included:
Types of participants
Adult Indian participants (>18 years) with at least one of the following chronic conditions (as defined by primary study authors):
- Common mental disorders
- Depression (including subthreshold disorders)
- Anxiety disorders (including generalized anxiety disorder [GAD], panic disorder, phobias, social anxiety disorder, obsessive compulsory disorder, and posttraumatic stress disorder).
- Schizophrenia.
- Cardiovascular disease
- Cancers of any origin
- Stroke
- Diabetes
- Chronic kidney disease
- Chronic lung disease:
- Chronic obstructive pulmonary disease (COPD)
- Asthma
- Occupational lung disease
- Chronic liver disease
- Chronic infectious diseases:
- Tuberculosis (TB)
- Human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS)
- Hepatitis C or hepatitis B infection.
- Osteoarthritis (OA) or any other musculoskeletal disorders
- Multimorbidity (combination of two or more of the above conditions).
In case of multicountry studies, only those that reported outcomes separately for Indian participants were included.
Concept and context
Studies which examined QoL (as defined by primary study authors) tools in the Indian context for the aforementioned chronic conditions in adults. Studies that examined tools that were revalidated, translated, or adapted were also considered. Considering the broad scoping approach, no a priori list of tools was used.
Outcomes
Measurement properties of tools which included but were not limited to internal consistency, inter-rater reliability, test–retest reliability, validity, and acceptability. Acceptability referred to the proportion of questionnaires completely answered by the respondents, with no or minimal missing data. Studies which did not report any measurement properties of tools were excluded.
Study designs
Cross-sectional, cohort, case–control, qualitative studies, and mixed-methods studies. There were no sample size restrictions.
Search strategy
Four electronic databases – Ovid Medline, EMBASE, EBM Reviews Cochrane Central Register of Controlled Trials, and Ovid Emcare – were searched since their date of inception until July 2020. Search strategies used for each database are presented in Appendix 2. There were no language or date restrictions.
Screening and data collection
Two reviewers independently screened the titles and abstracts and full texts of studies for inclusion, with a third author resolving disagreements by consensus. A standardized data extraction form (including study and participant characteristics) was developed a priori, and piloting of data was undertaken to check for any errors in data extraction. Data from the retrieved full texts were extracted by one author, with a proportion verified by another to further reduce extraction errors.
Data analysis and reporting
The results were narratively synthesized, and the findings were reported on the major characteristics of all identified tools arranged as per different types of chronic conditions (including type of tool, number of questions asked/items observed, region, and target population) and measurement properties of the tools.
Results
Search results
A total of 6706 records were retrieved, and following removal of 1444 duplicates, the titles and/or abstracts of 5262 records were screened. Full texts of potentially eligible 60 studies were retrieved for further examination, and on full-text screening, 37 studies were included in this report. Figure 1 shows the PRISMA flowchart. The reasons for exclusion at the full-text level are presented in Appendix 3.
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Figure 1: PRISMA study selection flowchart. PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Characteristics of the included studies
Most of the studies were conducted in a small number of Indian states – Maharashtra (n = 8, 21%), Chandigarh (n = 5, 13%), Kerala (n = 5, 31%), New Delhi (n = 5, 31%), and Karnataka (n = 4, 11%). Most were cross-sectional studies (n = 29, 78%), followed by cohort studies (n = 6, 16%) and case–control studies (n = 2, 6%). The follow-up duration ranged from 15 days to 9 months. Studies were mostly conducted in tertiary care hospital settings (n = 34, 91%) (including cancer institutes, various clinical departments, and chest clinics associated with hospitals), with very few conducted in primary care setting (n = 2, 6%) or were community based (n = 1, 3%). Many studies had sampled lesser women than men. The characteristics of the included studies are summarized in Table 1.
Table 1: Characteristics of included studies on tools for chronic diseases
Tools for measuring quality of life in those with chronic disease in India
A total of 29 tools to measure QoL in those with chronic diseases have been tested in the included studies from India. Nineteen out of 37 studies assessed both generic and disease-specific QoL tools,[6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24] while 11 studies assessed disease-specific tools,[25,26,27,28,29,30,31,32,33,34,35] and seven assessed generic QoL tools.[36,37,38,39,40,41,42] Table 2 presents the various tools that were identified in the included studies and were grouped into four different categories.
Table 2: List of identified tools classified under various categories
The most commonly assessed domains in the QoL tools are: physical health including limited functional capacity, psychological health, social relationships including social support, environment, and disease symptoms. The positive (+) sign indicates that the tool met the requirements of the relevant psychometric property evaluated, and NR indicates that the psychometric property was not evaluated and/or reported for that tool in the studies. The different tools identified are summarized with detailed information on each of the tools in Appendix 4. The most commonly used disease-specific tools were the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ)-C30,[9,16,26,27] FACT (G, B, and H&N),[14,15,23] and University of Washington QoL (UW-QOL) (for people with cancer);[9,31] Chronic Liver Disease Questionnaire (CLDQ) (for patients with chronic liver disease);[8,10,21] and Stroke and Aphasia Quality of Life (SAQOL) (for stroke patients)[20,34]
Reliability of a QoL tool was assessed by two methods, internal consistency using Cronbach's alpha and test–retest reliability using intra-class correlation (ICC, range from 0 [no agreement] to 1 [perfect agreement]). Internal consistency was considered acceptable if the alpha coefficient was > 0.70 and excellent if 0.90. A validity refers to the tool's ability to truly measure what it intended to measure. Construct validity is assessed by discriminant and convergent validity, i.e., correlations between items and scales and correlations between scales. Convergent and discriminant validity is measured by Spearman's rho correlation coefficient or Pearson's coefficient. A Spearman's correlation coefficient rho >0.7 was considered high or excellent. Acceptability refers to the proportion of questionnaires answered in full by the respondents, with no or minimal missing data. Responsiveness evaluated only in a few studies refers to the ability of the questionnaire to detect changes in clinical status even if they were small. The different tools identified to assess quality of life according to functions and items, and psychometric properties are summarised in Table 3.
Table 3: Tools used to assess quality of life according to functions and items, and psychometric properties of the identified tools
A narrative summary of the tools evaluated in a condition-wise manner is presented below. The detailed results of the internal consistency, reliability, and validity of QoL tools for different types of chronic conditions are provided in Appendix 4.
Cancer
Disease-specific tools for measuring QOL in head-and-neck, breast, ovarian, and laryngeal cancer were identified. Three tools were identified that measured QoL in head-and-neck cancer patients. In one study, acceptable internal consistency was reported for most of the subscales in the EORTC-QLQ-C30 and QLQ-H&N35 scales.[27] Good item-convergent validity, with all the items in both the questionnaires (QLQ-C30 and QLQ-H&N35), was reported.[27]
Two studies translated the UW-QOL questionnaire (to Hindi, Marathi and Tamil) and validated the translated tool. The results from one study indicated that there was a strong evidence of construct validity, as the UW-QOL composite scores correlated very well with the global question on overall QOL in both the Hindi (r = 0.69)- and Marathi (r = 0.66)-translated versions.[9] The Malayalam version of the Functional Assessment of Cancer Therapy for Head and Neck cancer (FACT-H&N) tool showed excellent internal consistency.[15]
Two studies[14,16] were identified that were reported on tools to assess QoL in patients with breast cancer. The internal consistency of the total Functional Assessment of Cancer Therapy for Breast cancer (FACT-B) indicated a good reliability of the scale.[14] Cronbach's alpha value of ≥ 0.70 was obtained for all domains except cognitive function in the EORTC module QLQ-C30 and BR-23.[16] Internal consistency of translated (Hindi and Marathi) versions of the EORTC ovarian cancer (OC) module (OV-28) was found to be acceptable (in most of the functional subdomains in patients with OC).[26] Translation and validation of the Voice-Related Quality of Life (V-RQOL) tool in Hindi and Marathi languages, without any modification, was conducted in a study including patients with advanced laryngeal cancer, and excellent internal consistency was observed.[29]
Four studies assessed QoL in patients with cancer, but did not specify the type of cancer.[23,40,41,42] Vidhubala et al. developed a standardized QoL questionnaire (Cancer Institute QoL Questionnaire Version I) to assess QoL in patients with cancer.[41] A follow-up study was conducted by the same authors that aimed to modify certain items in QoL Questionnaire Version I and developed Cancer Institute QoL Questionnaire Version II.[42] Overall, excellent internal consistency and high reliability was reported for both version I and version II, respectively.[41,42] The Malayalam version of the Functional Assessment of Cancer Therapy-General (FACT-G) validated in a study by Thomas et al. showed good internal consistency.[23] Tripathy et al. validated an Odia version of the EuroQol five-dimensions (EQ5D) and assessed its psychometric properties in cancer patients in Eastern India, which showed good internal consistency.[40]
Chronic lung disease
Three tools, the World Health Organization Quality of Life questionnaire (WHOQOL-BREF),[36] Mini Asthma Quality of Life Questionnaire (MiniAQLQ),[6] and Asthma Quality of Life Questionnaire (AQLQ),[28] were used to assess QoL of asthmatic patients in Indian settings. The Hindi version of WHOQOL-BREF in adult patients with asthma had good construct validity.[36] Content and construct validity as well as good convergent validity and internal consistency of the Hindi version of MiniAQLQ were found to be good to moderate in patients with bronchial asthma.[6]
Tools such as COPD Assessment Test (CAT),[7] Clinical COPD Questionnaire (CCQ), and St. George's Respiratory Questionnaire (SGRQ)[32] evaluated QoL in patients suffering from COPD. In a study that compared the validity of CCQ with SGRQ, the results demonstrated that each of the components and the total of CCQ significantly (P < 0.001) correlated with those of SGRQ.[32] In a study that validated the Hindi version of CAT tool, the Cronbach's alpha had a high value, indicating good internal consistency. In addition, the tool demonstrated a good test–retest reproducibility, and a strong correlation was reported between CAT scores with all domains of SGRQ and physical domain of WHOQOL-BREF scores.[7]
Diabetes
Four studies were identified that reported on QoL assessment in patients with type 2 diabetes. The Diabetic Foot Ulcer Patients (HRQLQDFU), a tool developed in India, had good acceptability, and all the patients were able to satisfactorily understand the questions and respond.[33] The Quality of Life Instrument for Indian Diabetes Patients (QOLID) that was developed for assessment of QoL in diabetic patients in India showed excellent overall reliability and good subscale reliability.[13] In another study, the Multi-Dimensional Questionnaire (MDQ) tool was translated into Hindi language and validated for use in Indian type 2 diabetic patients and was found to have excellent internal consistency.[18] The internal consistency of the translated (Malayalam language) WHOQOL-BREF tool was reported to be excellent and with a good convergent validity.[22]
Chronic infectious diseases
Two studies assessed QoL in patients with TB,[30,37] and one other study included patients living with HIV.[39] Dhingra and Rajpal developed and validated a new HRQoL questionnaire (DR-12 score) in patients with pulmonary and extrapulmonary TB, which had a good construct validity.[30] The utility of WHOQOL-BREF as an independent outcome measure was evaluated in a study conducted in a TB center in North India.[37] It was reported that the tool had acceptable internal consistency, good subscale reliability, good acceptance, and responsiveness. Kohli et al. adapted and validated the Medical Outcome Study-QOL core tool in a study that included HIV-infected individuals in India and found it to have acceptable internal consistency.[39]
Chronic musculoskeletal conditions
A study translated and validated the Knee Injury and Osteoarthritis Outcome Score (KOOS-QOL) tool (from English to Urdu language) in patients with knee OA, and it was reported that the tool had an acceptable internal consistency (Cronbach's alpha: 0.725).[25] The Marathi version of Rheumatoid Arthritis Pain Scale was validated to assess QoL in Indian patients with RA and it reported excellent internal consistency and good concurrent criterion validity.[11] The Hindi version of Quebec Back Pain Disability Scale had excellent internal consistency and good test–retest reliability (ICC: 0.96, 95% confidence interval: 0.93–0.97).[24]
Chronic liver disease
Three studies translated (Hindi,[8] Tamil,[10] and Bengali[21]) and validated the use of CLDQ in patients with chronic liver disease. The details of the psychometric properties of the QoL tool in chronic liver disease are provided in Appendix 4. The Hindi version of the tool showed an excellent internal consistency, test–retest reliability (ICC: 0.88), and good construct validity and convergent validity.[8] Both the Tamil and Bengali versions of CLDQ had an excellent internal consistency with good test–retest reliability reported in the Bengali one.[10,21]
Chronic mental disorders
Two studies assessed QoL in patients with schizophrenia[38] and depression,[35] using the Indian Disability Evaluation and Assessment Scale (IDEAS) and WHO-QOL-100[38] and Geriatric Depression Scale-15 (GDS-15),[35] respectively. The modified tool IDEAS showed acceptable internal consistency and good construct validity.[38] The study on Tamil version of GDS-15 tool did not report on validity of the tool.[35]
Stroke
Two studies translated and validated the SAQOL-39 tool with modifications into Kannada[34] and Malayalam languages.[20] Both the Kannada and Malayalam versions of SAQOL-39 tool showed an excellent internal consistency, high item reliability, and good acceptability, indicated by minimal missing data.[20,34]
Other chronic conditions
The Kannada Version of the Kidney Disease and Quality of Life-36 tool for patients with chronic kidney disease on hemodialysis demonstrated acceptable internal consistency and good test–retest reliability.[12] The Cronbach's alpha value of the Hindi version of LupusPRO in patients with systemic lupus erythematosus for most domains acceptable.[19] The tool had good convergent validity, indicated by a significant Spearman's correlation coefficient between corresponding domains of LupusPRO and SF-36.[19]
A new tool, the Multimorbidity Assessment Questionnaire for Primary Care (MAQ-PC), was validated to assess the prevalence and outcomes of multimorbidity in primary care settings in India.[17] The inter-rater reliability was found to be excellent, and test–retest reliability (ICC) ranged from 0.970 to 0.741.[17]
Discussion
To the best of our knowledge, this is the first time that tools to assess QoL for chronic disease have been mapped, providing visibility to researchers and research funders to identify areas for collaboration and further investigation. Overall, the scoping review summarizes several tools that exist for the assessment of QoL in patients living with chronic conditions. This can prevent unnecessary investment into development of new tools and enable better selection within already existing and validated tools that are specific to different chronic conditions. However, the review findings also demonstrate a lack of consensus on the type of QoL tool to be adopted for several chronic conditions. Most of the studies focused on QoL in people with cancer. There is a need for research on tools for other chronic diseases and for multimorbidity. Most studies reported tools that had reasonable internal consistency and test–retest reliability, but there was variability in acceptability – a key contextual issue. Methodologically, many studies were limited by small sample sizes and were from a single center, thereby limiting generalizability. Effect of chronic conditions on QoL is best understood in communities, and as such, the lack of assessment of QoL tools being applied and tested in the community setting remains a significant gap. Our review demonstrated that currently, tools for QoL among patients with chronic conditions are primarily focused on hospital settings rather than the community.
Many studies had recruited fewer women than men, and tools did not have additional dimensions specific for other genders. Recent studies on QoL have shown important differences with respect to QoL between men and women due to difference in preferences and attitudes due to gender roles.[43] Tool development studies typically did not include or specifically look at Adivasi or tribal people – limiting generalizability further. Recent studies done in indigenous people in Australia have also led to development of a separate framework and tool for aboriginal Australians, which has been subsequently validated.[44,45] There is a need for similar studies in India.
The terms QoL and HRQoL are used interchangeably in many of the identified studies, although the two are related but distinct concepts.[46] Health is one of the important QoL domains; however, other important domains such as psychological state, level of independence, social relationships, and personal beliefs must be considered too.[47] The tools identified in this review were predominantly self-reported measures and multidimensional, which implies that QoL is generally construed of various dimensions (physical health and mental health) relevant to different individuals. There were no QoL tools available for patients with anxiety disorders (e.g., GADs), cardiovascular disease other than stroke, occupational lung disease, chronic infectious diseases such as hepatitis C or hepatitis B in India. Only one study assessed tool for patients with multi-morbidity.[17] Most of the studies included a disease-specific measure, given that these were specified target groups in most of the included studies. Generic tools of QoL were used either alone or in combination with a disease-specific tool. Generic tools were used to compare QoL between health conditions, while disease-specific tools particularly addressed the specific NCD of interest. Conceptually, generic and disease-specific QoL tools serve different purposes and focus on different aspects of life. Generic QoL tools allow comparison with other disease conditions but lack specific nuances which might be related to a specific disease. As such, applying them together in a research setting might be useful to understand the correlation between them. Based on such correlations, the choice of generic versus specific QoL in different conditions in practice scenarios can be informed. In addition, QoL for chronic diseases is also intricately related to the environment and societal values. Apart from the conventional dimensions of QoL, additional aspects arising as a result of pandemic, climate crisis, societal changes, technological advancement both within and outside the health system, should also be considered.
Most of the QoL tools identified in this review were created in the English language. The Hindi and Marathi versions of the UW-QoL were found to be reliable and valid, with good internal consistency, and possibly could be considered for implementation into routine clinical practice.[9,31] Similarly, the Malayalam versions of the FACT tool were found to be reliable and valid, with good internal consistency for use in patients with breast cancer and head-and-neck cancer.[14,15,23] The V-RQOL questionnaire,[29] the Odia version of EQ5D,[40] and the Cancer Institute QoL Questionnaire Version I and II[41,42] were reportedly comprehensive, valid, and reliable instruments and may be considered in adult patients with cancer in India.
The Hindi and English versions of AQLQ and Mini AQLQ were found to have a high degree of acceptability, validity, and acceptable internal consistency in people with asthma in India.[6,28] In patients with COPD in an outpatient setting, the CAT and CCQ questionnaires could be considered for assessing QoL, as they were found to be valid and reliability, and well accepted.[7,32] A new tool, the HRQLQDFU tool in English for patients with diabetic foot ulcers, showed good acceptability by the users.[33] Other tools such as the QOLID and MDQ (Hindi version) also indicated high levels of internal consistency and reliability.[13,18] The modified MOS-QOL tool showed high reliability and validity in Indian context to assess the QoL in HIV-infected individuals.[39] The CLDQ was translated in three different languages (Hindi, Tamil, and Bengali) to evaluate the QoL in patients with chronic liver disease.[8,10,21] Overall, the translated versions of this tool demonstrated an excellent internal consistency, good test–retest reliability, validity, and good acceptability in Indian context.[8,10,21] The Kannada and Malayalam versions of SAQOL-39 reportedly showed good acceptability, test–retest reliability, and internal consistency.[20,34] The CLDQ and SAQOL-39 may therefore be considered for measuring QoL of patients with chronic liver disease and in those with stroke. The MAQ-PC was also found to be a comprehensive tool, with good validity and reliability for assessing QoL in patients with multimorbidity.[17]
Future researches with prospective studies and methodological standardization and reporting to evaluate QoL in people with various chronic conditions are recommended. India is a vastly diverse country which has 22 constitutionally recognized official languages, and there is a need for funding research on development of QoL tools in all languages and preferably local dialects too. Future studies should consider investigating linguistic validity and subsequent psychometric validation for adaptation of various QoL tools in multicultural settings.
Conclusion
The scoping review provides a one-stop summary of all tools for assessment of QoL in people with chronic diseases in India. It can enable future researchers to make informed decisions for choosing tools in the Indian setting. The study highlights the need for more research to develop the current QoL tools which are contextually applicable and enables the comparability across diseases, people, and regions within India and potentially in the South Asian region.
Financial support and sponsorship
This study was financially supported by the National Institute of Health Research, United Kingdom.
Conflicts of interest
There are no conflicts of interest.
Acknowledgment
The authors would like to acknowledge Dr. David Pieris for his feedback during conceptualization of the research project.
REFERENCES
1. Hajat C, Stein E. The global burden of multiple chronic conditions: A narrative review Prev Med Rep. 2018;12:284–93
2. Arokiasamy P, Uttamacharya, Jain K. Multi-morbidity, functional limitations, and self-rated health among older adults in
India: Cross-sectional analysis of LASI pilot survey, 2010 SAGE Open. 2015;5(1)
3. Pati S, Swain S, Metsemakers J, Knottnerus JA, van den Akker M. Pattern and severity of multimorbidity among patients attending primary care settings in Odisha,
India PLoS One. 2017;12:e0183966
4. Megari K.
Quality of life in chronic disease patients Health Psychol Res. 2013;1:e27
5. Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation Ann Intern Med. 2018;169:467–73
6. Aggarwal AN, Agarwal R, Gupta D, Jindal SK. Validation of a Hindi translation of mini asthma
quality of life questionnaire in north Indian patients with bronchial asthma Indian J Chest Dis Allied Sci. 2010;52:83–9
7. Aggarwal AN, Lallawmkima I, Basu D. Psychometric validation of a Hindi version of a chronic obstructive pulmonary disease (COPD) assessment test in patients in Northern
India Natl Med J
India. 2017;30:193–7
8. Benjamin J, Mani K, Saraya A, Joshi YK. Translation and validation of the Hindi version of chronic liver disease questionnaire (CLDQ) for the assessment of health related
quality of life in patient with chronic liver disease in
India Trop Gastroenterol. 2016;37:112–22
9. D'cruz AK, Yueh B, Das AK, McDowell JA, Chaukar DA, Ernest AW. Validation of the University of Washington
quality of life questionnaires for head and neck cancer patients in
India Indian J Cancer. 2007;44:147–54
10. Goel A, Arivazhagan K, Sasi A, Shanmugam V, Koshi S, Pottakkat B, et al Translation and validation of chronic liver disease questionnaire (CLDQ) in Tamil language Indian J Gastroenterol. 2017;36:217–26
11. Kianifard T, Kianyfard T, Chopra A. Validation and relevance of rheumatoid arthritis pain scale (RAPS) in Indian (Asian) patients suffering from rheumatoid arthritis Clin Rheumatol. 2016;35:63–71
12. Mateti UV, Nagappa AN, Attur RP, Nagaraju SP, Mayya SS, Balkrishnan R. Cross-cultural adaptation, validation and reliability of the South Indian (Kannada) version of the kidney disease and
quality of life (KDQOL-36) instrument Saudi J Kidney Dis Transpl. 2015;26:1246–52
13. Nagpal J, Kumar A, Kakar S, Bhartia A. The development of '
quality of life instrument for indian diabetes patients (QOLID): A validation and reliability study in middle and higher income groups J Assoc Physicians
India. 2010;58:295–304
14. Pandey M, Thomas BC, Ramdas K, Eremenco S, Nair MK.
Quality of life in breast cancer patients: Validation of a FACT-B Malayalam version Qual Life Res. 2002;11:87–90
15. Pandey M, Thomas BC, Ramdas K, Eremenco S, Nair MK. Reliability & validity of the Malayalam functional assessment of cancer therapy for head & neck cancer Indian J Med Res. 2004;120:51–5
16. Parmar V, Badwe RA, Hawaldar R, Rayabhattanavar S, Varghese A, Sharma R, et al Validation of EORTC quality-of-life questionnaire in Indian women with operable breast cancer Natl Med J
India. 2005;18:172–7
17. Pati S, Hussain MA, Swain S, Salisbury C, Metsemakers JF, Knottnerus JA, et al Development and validation of a questionnaire to assess multimorbidity in primary care: An Indian experience Biomed Res Int. 2016;2016:1–9
18. Pawar SS, Thakurdesai PA. Translation and validation of Hindi version of the Multidimensional Questionnaire (MDQ) for
quality of life assessment in type 2 diabetes mellitus patients in Indian population Int J Pharma Sci Res. 2013;4:1827–32
19. Pinto B, Jolly M, Dhooria A, Grover S, Raj JM, Devilliers H, et al Hindi LupusPRO: Cross cultural validation of disease specific patient reported outcome measure of lupus Lupus. 2019;28:1534–40
20. Raju R, Krishnan G. Adaptation and validation of stroke-aphasia
quality of life (SAQOL-39) scale to Malayalam Ann Indian Acad Neurol. 2015;18:441–4
21. Ray I, Dutta D, Basu P, De BK.
Quality of life assessment of patients with chronic liver disease in eastern
India using a Bengali translation chronic liver disease questionnaire Indian J Gastroenterol. 2010;29:187–95
22. Sreedevi A, Cherkil S, Kuttikattu DS, Kamalamma L, Oldenburg B. Validation of WHOQOL-BREF in Malayalam and determinants of
quality of life among people with type 2 diabetes in Kerala,
India Asia Pac J Public Health. 2016;28:62S–69S
23. Thomas BC, Pandey M, Ramdas K, Sebastian P, Nair MK. FACT-G: Reliability and validity of the Malayalam translation Qual Life Res. 2004;13:263–9
24. Zaidi S, Verma S, Moiz JA, Hussain ME. Transcultural adaptation and validation of Hindi version of Quebec back pain disability scale Disabil Rehabil. 2018;40:2938–45
25. Ateef M, Kulandaivelan S, Alqahtani M. Cross-Cultural validation of Urdu version KOOS in Indian Population with primary knee osteoarthritis Int J Rheumatol. 2017;2017:1–4
26. Bajpai J, Panda PK, Kagwade S, Govilkar M, Velaskar S, Kembhavi Y, et al Translation and validation of European organization for research and treatment for cancer
quality of life questionnaire-OV-28 module into Indian languages (Hindi and Marathi) to study
quality of life of ovarian cancer patients from a tertiary care cancer Center South Asian J Cancer. 2018;7:37–41
27. Chaukar DA, Das AK, Deshpande MS, Pai PS, Pathak KA, Chaturvedi P, et al
Quality of life of head and neck cancer patient: Validation of the European organization for research and treatment of cancer QLQ-C30 and European organization for research and treatment of cancer QLQ-H&N 35 in Indian patients Indian J Cancer. 2005;42:178–84
28. Chhabra SK, Kaushik S. Validation of the asthma
quality of life questionnaire (AQLQ-UK English version) in Indian asthmatic subjects Indian J Chest Dis Allied Sci. 2005;47:167–73
29. Deshpande MS, Kakade AC, Chaukar DA, Gore VT, Pai PS, Chaturvedi P, et al Validation and assessment of voice-related
quality of life in Indian patients undergoing total laryngectomy and primary tracheoesophageal puncture Head Neck. 2009;31:37–44
30. Dhingra VK, Rajpal S. Health related
quality of life (HRQL) scoring (DR-12 score) in tuberculosis--additional evaluative tool under DOTS J Commun Dis. 2005;37:261–8
31. Ganesan S, Thulasingam M, Gunaseelan K, Kalaiarasi R, Penumadu P, Ravichandran S, et al Validity and reliability of Tamil translated University of Washington
quality of life questionnaire for head and neck cancers Asian Pac J Cancer Prev. 2019;20:3649–54
32. Herbert CM, Nambiar VK, Rao M, Ravindra S. Concurrent validity of clinical chronic obstructive pulmonary disease (COPD) questionnaire (CCQ) in South Indian population Indian J Physiother Occup Ther. 2013;7:270–3
33. Kateel R, Augustine AJ, Ullal S, Prabhu S, Bhat R, Adhikari P. Development and validation of health related
quality of life questionnaire (Indian scenario) in diabetic foot ulcer patients Diabetes Metab Syndr. 2017;11(Suppl 2):S651–3
34. Kiran S, Krishnan G. Stroke and aphasia
quality of life scale in Kannada-evaluation of reliability, validity and internal consistency Ann Indian Acad Neurol. 2013;16:361–4
35. Sarkar S, Kattimani S, Roy G, Premarajan KC, Sarkar S. Validation of the Tamil version of short form geriatric depression scale-15 J Neurosci Rural Pract. 2015;6:442–6
36. Aggarwal AN, Agarwal R, Gupta D. Abbreviated World Health Organization
Quality of Life Questionnaire (WHOQOL-Bref) in North Indian patients with bronchial asthma: An evaluation using Rasch analysis NPJ Prim Care Respir Med. 2014;24:14001
37. Aggarwal AN, Gupta D, Janmeja AK, Jindal SK. Assessment of
health-related quality of life in patients with pulmonary tuberculosis under programme conditions Int J Tuberc Lung Dis. 2013;17:947–53
38. Grover S, Shah R, Kulhara P, Malhotra R. Internal consistency & validity of Indian disability evaluation and assessment scale (IDEAS) in patients with schizophrenia Indian J Med Res. 2014;140:637–43
39. Kohli RM, Sane S, Kumar K, Paranjape RS, Mehendale SM. Modification of medical outcome study (MOS) instrument for
quality of life assessment & its validation in HIV infected individuals in
India Indian J Med Res. 2005;122:297–304
40. Tripathy S, Hansda U, Seth N, Rath S, Rao PB, Mishra TS, et al Validation of the EuroQol five-dimensions – Three-level
quality of life instrument in a classical Indian language (Odia) and its use to assess
quality of life and health status of cancer patients in Eastern
India Indian J Palliat Care. 2015;21:282–8
41. Vidhubala E, Kannan RR, Mani SC, Karthikesh K, Muthuvel R, Surendran V, et al Validation of
quality of life questionnaire for patients with cancer – Indian scenario Indian J Cancer. 2005;42:138–44
42. Vidhubala E, Latha, Ravikannan R, Mani CS, Muthuvel R, Surendren V, et al Validation of cancer institute
quality of life questionnaire version II for cancer patients in
India Indian J Cancer. 2011;48:500–6
43. Reynolds CL, Weinstein AL. Gender differences in
quality of life and preferences for location-specific amenities across cities J Reg Sci. 2031;61:916–43
44. Smith K, Gilchrist L, Taylor K, Clinch C, Logiudice D, Edgill P, et al Good spirit, good life: A
quality of life tool and framework for older aboriginal peoples Gerontologist. 2021;61:e163–72
45. Gilchrist L, Hyde Z, Petersen C, Douglas H, Hayden S, Bessarab D, et al Validation of the good spirit, good life quality-of-life tool for older aboriginal Australians Australas J Ageing. 2022:1–9 doi: 10.1111/ajag.13128
46. Smith KW, Avis NE, Assmann SF. Distinguishing between
quality of life and health status in
quality of life research: A meta-analysis Qual Life Res. 1999;8:447–59
Appendix 3: List of Excluded Studies with Reasons for Exclusion
1. Bansal D, Gudala K, Lavudiya S, Ghai B, Arora P. Translation, adaptation, and validation of Hindi version of the pain catastrophizing scale in patients with chronic low back pain for use in India. Pain Med 2016;17:1848-58 - The study does not validate a QoL tool.
2. Bansal N, Duggal L, Jain N. Validity of simplified ankylosing spondylitis disease activity scores (SASDAS) in Indian ankylosing spondylitis patients. J Clin Diagn Res 2017;11:C06-9 - The study validates a tool for disease activity of AS but not a QoL tool. Further, no outcome data for QoL tool was reported.
3. Bengre ML, Venkatraya Prabhu M, Arun S, Prasad K, Gopalkrishna Bhat K. Evaluation of the multinational association for supportive care in cancer (MASCC) score for identifying low risk febrile neutropaenic patients at a South Indian tertiary care Centre. J Clin Diagn Res 2012;6:839-43. Klastersky J, Paesmans M. The multinational association for supportive care in cancer (MASCC) risk index score: 10 years of use for identifying low-risk febrile neutropenic cancer patients. Support Care Cancer 2013;21:1487-95 - The Multinational Association of Supportive Care in Cancer (MASCC) score in this study was used to identify low-risk febrile neutropenia patients with various cancers. No data on QoL tool/score was reported, including any validation.
4. Budrukkar A, Jalali R, Kamble R, Parab S. Translation and pilot validation of Hindi translation of assessing quality of life in patients with primary brain tumours using EORTC brain module (BN-20). J Cancer Res Ther 2006;2:166-70 - There is no outcome data on psychometric properties of the instrument. The main focus is on the accuracy of the translation of the tool.
5. Chow E, Nguyen J, Zhang L, Tseng LM, Hou MF, Fairchild A, et al. International field testing of the reliability and validity of the EORTC QLQ-BM22 module to assess health-related quality of life in patients with bone metastases. Cancer 2012;118:1457-65 - Multi-country study, but outcomes are not reported separately for Indian participants (n = 7).
6. Rostami Z, Einollahi B. How does KDQoL-36 questionnaire predict quality of life in Indian hemodialysis patients? Indian J Nephrol 2012;22:319-20 - Letter to Editor.
7. Ghai B, Gudala K, Asrar MM, Chanana N, Kanukula R, Bansal D. Development, validation and evaluation of a novel self-instructional module in patients with chronic non-specific low back pain. Indian J Anaesth 2020;64:299-305 - This study is not related to validity of a tool but of an intervention.
8. WHOQOL HIV Group. WHOQOL-HIV for quality of life assessment among people living with HIV and AIDS: Results from the field test. AIDS Care 2004;16:882-9 - - Multi-country study, but outcomes are not reported separately for Indian participants.
9. Guerra M, Ferri C, Llibre J, Prina AM, Prince M. Psychometric properties of EURO-D, a geriatric depression scale: A cross-cultural validation study. BMC Psychiatry 2015;15:12 - The study does not validate a QoL tool.
10. John R, Pise S, Chaudhari L, Deshpande PR. Evaluation of quality of life in type 2 diabetes mellitus patients using quality of life instrument for Indian diabetic patients: A cross-sectional study. J Midlife Health 2019;10:81-8 - This study is not about validity of QoL tool but on the impact of diabetes on QoL. Move to Impact component.
11. Kohli RM, Sane S, Kumar K, Paranjape RS, Mehendale SM. Assessment of quality of life among HIV-infected persons in Pune, India. Qual Life Res 2005;14:1641-7 - Measurement property of tool not mentioned; wrong outcome.
12. Naidu G, Shukla S, Nagi R, Jain S, Makkad R. Evaluation of oral health related quality of life in subjects diagnosed with head and neck malignancies undergoing chemotherapy, radiotherapy, and surgery. J Indian Acad Oral Med Radiol 2019;31:228-33 - Measurement property of tool not mentioned; wrong outcome.
13. New PW, Tate DG, Forchheimer MB, D'Andréa Greve JM, Parashar D, Post MW. Preliminary psychometric analyses of the international spinal cord injury quality of life basic data set. Spinal Cord 2019;57:789-95 - Secondary analysis of cross-sectional data; wrong study design.
14. Singh DP. Quality of life in cancer patients receiving palliative care. Indian J Palliat Care 2010;16:36-43 - Measurement property of tool not mentioned; wrong outcome.
15. Thomas K, Ruby J, Peter JV, Cherian AM. Comparison of disease-specific and a generic quality of life measure in patients with bronchial asthma. Natl Med J India 1995;8:258-60 - Wrong study design.
16. Wadasadawala T, Murthy V, Mahantshetty U, Engineer R, Shrivastava S, Dinshaw K. The European organization for research and treatment of cancer prostate-specific quality of life module (PR-25) in Hindi and Marathi: Translation and pilot testing process. J Cancer Res Ther 2008;4:64-9 - Measurement property of tool not mentioned; wrong outcome.
Full texts pending and/or not available
1. Kundu U, Chakravarty BP, Das MP, Phukan JD, Thakuria B, Borah RS. A prospective observational study for determining correlation between disease activity score (DAS28) and the HRQOL instruments in routine clinical practice. Indian J Rheumatol 2010;5:S17-S8.
2. Mahapatra HS, Pursunani L, Verma H, Kumar M, Renju, Arora A, et al. Analytical approach to modify SF 36 health related quality of life questionnaires for easy use in nephrology out door patients. Indian J Nephrol 2018;28:S51-S2. Available from: https://www.indianjnephrol.org/temp/IndianJNephrol28728-498919_135131.pdf.
3. Pawar SS, Thakurdesai PA. Quality of life with type 2 diabetes: Translation and validation of Indian version of DES-5. Int J Life Sci Biotechnol Pharma Res 2013;2:123-9.
4. Rawandale AV, Kurane CS, Patni LG, Sude N, Patil PA. Translation and validation of the international prostate symptom score and quality of life (IPSS + QoL) for a Non English speaking population. Eur Urol Suppl 2012;11:e221.
5. Shah KD, Balaraman V, Hithaishi C, Venkatraman G, Sumathi K, Veerappan I, et al. Measuring quality of life of patients using eq-5d-3l and eq-vas in a large national dialysis cohort in India. Indian J Nephrol 2016;26:S88.
6. Shah R, Kulhara P, Kumar S. Inter-relationships between spirituality and coping in patients with residual schizophrenia. Indian J Psychiatry 2010;52:S29-30.
7. Thumboo J, Fong KY, Chan SP, Leong KH, Feng PH, Thio ST, et al. The rheumatology attitudes index and its helplessness subscale are valid and reliable measures of learned helplessness in Asian patients with systemic lupus erythematosus. J Rheumatol 1999;26:1512-7.
