Skip to main content

The McGill Quality of Life Questionnaire-Revised (MQOL-R). Psychometric properties and validation of a Brazilian version on palliative care patients: a cross-sectional study

Abstract

Background

To assess the psychometric properties, including internal consistency, construct validity, criterion validity, criterion-group validity, and responsiveness, the Reviewed McGill Quality of Life Questionnaire (MQOL-R), into Brazilian Portuguese-(BrP). Also, to analyze the relationship of the BrP-MQOL-R with the scores on the Karnofsky Performance Scale (KPS) and on the Numerical Pain Scale (NPS 0–10).

Methods

The BrP-MQOL-R was administered to a sample of 146 adults (men = 78). A team of experts translated the MQOL-R according to international guidelines. Convergent validity and Confirmatory factor analysis (CFA) was performed.

Results

The BrP-MQOL-R Cronbach’s alpha was 0.85. CFA supported the original four-factor structure, with the following revised model fit-indices: PCLOSE = 0.131, Tucker-Lewis Index (TLI) rho 2 = 0.918, incremental fit index (IFI) delta 2 = 0.936. The convergence validity is supported by a significant correlation between BrP-MQOL-R total scores and their subscales with KPS and with the single item related to the quality of life. And by a converse correlation with the pain scores in the NPS (0–10). Receiver operator characteristics (ROC) analysis showed subjects with KPS equal to or lower than 30% could be discriminated from those with scores on KPS higher than 30% by an area under the curve (AUC) = 0.71, sensitivity = 97%, and specificity = 92%).

Conclusion

The BrP-MQOL-R proves to be a reliable instrument for assessing the quality of life (QOL) in palliative care (PC), with primary evidence of validity. BrP-MQOL-R presented adequate discriminate properties to identify distinct conditions that impact the QOL in PC.

Background

Palliative care is specialized medical care for people living with a severe illness with a life-threatening disease to prevent and relieve suffering through early identification, with appropriate evaluation and treatment of pain, physical, psychosocial, and spiritual problems. The palliative care provides relief from the symptoms to reduce the stress of the illness coming to the comfort of suffering and improvement of the Quality of Life (QOL) for both the patient and the family” [1]. The QOL comprises physical, emotional, psychological, and social dimensions. The concept must be contextualized since the term “quality of life” can have different meanings. The definition of QOL refers to patients' well-being with a terminal disease, including the dimensions mentioned above. Accordingly, the McGill Quality of Life Questionnaire (MQOL) was developed to measure the QOL of people at the end of life, to overcome specific limitations with the QOL measures existing: (i) They were too long for palliative care patients. (ii) They did not assess the existence or spiritual well-being. (iii) They focused exclusively on negative aspects of QOL, even if positive and negative factors influenced the quality of life [2,3,4,5]. Thus, the MQOL was developed with particular interest to assess physical symptoms (Physical Wellbeing; Physical Symptoms) that allow a brief symptom measurement as the Edmonton Symptom Assessment System (ESAS) [6, 7]. According to an earlier study, physical symptoms are essential predictors on measuring global QOL, and they have been of great importance to people with life-threatening illnesses [8].

The McGill Quality of Life Questionnaire-Reviewed [9], improved the MQOL version, addressing issues that arose during the use of MQOL over the years. The results provided a well-adjusted measurement structure and expected correlations between each subscale of the MQOL-R and MQOL single item scale (SIS). MQOL-R has strong psychometric properties, and it has been widely used in palliative care in both clinical and research for the life quality at the end of life assessment. It has subscales measuring the four relevant domains: physical, psychological, existential/spiritual, and social. It evaluates the physical condition's impact on the quality of life, rather than on the intensity of symptoms. In contrast, most other quality life assessment tools at the end of life do not include the existential/spiritual domain, have a primary focus on physical symptoms, or have many more items. An additional advantage of the MQOL-R is that it takes approximately 5–10 min to complete a self-administered in paper and pencil or online format [9]. Considering that the area of palliative care is in rapid development, and that lack of appropriate instruments to assess QOL, this motivated us to translate and adapt of the MQOL-R to the Brazilian Portuguese (BrP) within its linguistic and sociocultural context.

Thus, we conduct the present study to examine the psychometric reliability of the translated MQOL-R for the Brazilian population [10]. (I) We evaluated the content validity and face validity by semantic equivalence, the comparison of items by experts, and a sub-sample of the target population to assess the cross-cultural, adapted from the English version of the Brazilian Portuguese (BrP)-MQOL-R. (II) We examined the internal consistency, criteria validity, factor structure, and construct validity of the MQOL-R translated instrument. (III) We assessed the convergence validity by the correlation of the MQOL-R with relevant correlates for the quality of life, such as the Karnofsky Performance Scale (KPS) and pain levels reported on the Numerical Pain Scale (NPS 0–10). (IV) We evaluated the criterion validity by the ability of MQOL-R to discriminate between subjects whose performance in the KPS equal to or lower than 30% those with a KPS higher than 30%.

Methods

The protocol of this cross-sectional study was approved by the Ethics Committee Board of the Hospital de Clínicas de Porto Alegre, Brazil (protocol no 2019–0207). All subjects gave their written formal consent for participation or their caregivers. Figure 1 presents the flow of the standardized phases of the study.

Fig. 1
figure1

Flow of the multiple standardized phases of the study. Abbreviations: Karnofsky Performance Status Scale (KPS); Numerical Pain Scale (NPS0-10)

Phase I. Translation, synthesis and back translation and consensus of experts assessed the content and face validity

Previously published guidelines carried out the procedures for the translation and cross-cultural adaptation of the MQOL-R to Brazilian Portuguese [10,11,12,13]. We follow the recommended practices by the Health Measurement Consensus guideline terminology (COSMIN) for assessing the content validity for health‐related Patients. According to the COSMIN, evaluating the content validity for health‐related Patient Reported Outcome Measures (PROMS) is categorized into three broad domains: Reliability, containing the Measurement and assessment of the conceptual semantics content of each item [14]. The procedures for assessing the semantics and conceptual content of each item of the MQOL-R [14] were through the Delphi method [15]. The McGill Quality of Life Questionnaire-Revised (MQOL-R) validated for Brazilian Portuguese is presented in Additional file 1.

Phase II. Pretesting of BrP-MQOL-R in a pilot study

Twenty patients assessed the comprehension of the item of BrP-MQOL-R. Among them, nine were inpatients, and 11 were women. The median age was 59.50 [interquartile ranges IQR) (IQR 25–75 = 46.5; 73.75)] and the median of formal schooling was 8 years (IQR 25–75 = 5; 11), respectively. They evaluated the meaning of the translated questions and the layout of the pre-final version of the BrP-MQOL-R and assessed each item's comprehension using a 10 cm visual analog scale (VAS; 0 completely incompressible to 10 cm entirely clear). The median of comprehension of all items was 8.70 (IQR 25–75 = 7.56; 10).

Phase III. Assessment of psychometric properties and the validity of the final version of the BrP-MQOL-R

A total of 157 patients over 18 years old at the Pain and Palliative Medicine Service of “Hospital de Clínicas de Porto Alegre, Brazil, from March 2019 to December 2019. Sixty-four in patients (43.8%) and 82 (56.2%) outpatients. Patients illiterate and those with cognitive impairment that prevented them from answering questions or communicating were excluded. Data were obtained by trained evaluators using a standardized questionnaire, the MQOL-R, the Performance de Karnofsky Scale, and a Numerical Pain Scale (NPS 0–10).

Self-report variables

NPS (0–10) was used to measure pain intensity, ranging from 0 (no pain) to 10 (the worst pain possible). They answered their pain level most of the time in the last 24 h and the pain score after taking pain medication.

The Karnofsky Performance Status Scale (KPS) was used to quantifying functional status. The KPS is an 11-point rating scale that ranges from normal functioning (100) to dead (0). The KPS of < 30 the patients unable to perform these activities with or without assistance [16].

The McGill Quality of Life Questionnaire-Revised (MQOL-R) consists of 14 items divided into four domains: The Single-Item Scale (SIS), physical symptoms (three items), feelings and thoughts (seven items), and social (three items). The overall scale has good internal reliability (α = 0.94) [10].

Statistical analysis

We conducted descriptive statistics to examine the underlying assumptions of normality for all variables of interest. The Cronbach’s alpha and Spearman-Brown were used for the assessment of the MQOL-R’s reliability. For the BrP-MQOL-R, the maximum likelihood factor analyses with oblique rotation were conducted. We checked the scale's internal structure using confirmatory factor analysis (CFA) and establishing its reliability and validity. Items with a loading equal to or higher than 0.4 were retained to be considered relevant [17]. Factors that win with eigenvalues greater than one were also excluded. Convergent validity was evaluated by Pearson’s correlation coefficient between BrP-MQOL-R total scores, subscales, and the SIS measuring overall quality of life with scores on NPS (0–10) and the KPS scale. The non-parametric receiver operating characteristics (ROC) analyses, with the exact binomial of the area under the curve (AUCs) with 95% confidence intervals (CI), is presented. We calculated the standard errors (SEs) by Hanley’s method [18]. The cutoff values with the highest Youden index, with 90% sensitivity and 100% specificity, are presented for the BrP-MQOL-R with a ROC AUC 0.70. Finally, a stratified-by-sex analysis was used to assess the correlation between age, education level, if they were hospitalized when they answered the MQOL-R (Yes/No), and the scores of the dependent variable MQOL-R. We employed regression analysis with a stepwise forward technique. The prior sample size was estimated a priori based on the number of volunteers' ratio to the number of items. In this case, the MQOL-R has 14 questions. Based on this criterion, we needed 140 volunteers. Considering potential loss by insufficient data, we increased the sample size by 10% [10]. For all statistical analyses, significance was set at P < 0.05. The analysis used SPSS version 24.0 (IBM, Armonk, NY, USA), and the CFA was conducted by means of SPSS. AMOS. Version 24.0 (IBM, Armonk, NY, USA).

Results

Phase III: assessment of psychometric properties and the validity of the final version of the Validation study

Sample characteristics

The demographic data and clinical characteristics are presented in Table 1. There was a proportionate number of females and males in our sample, 53.4% and 46.6%, respectively. The mean scores of the BrP-MQOL-R for males were 5.69 (1.63) and for females 5.69 (2.20) (t = 2.75, P = 0.007], respectively. The mean score on the BrP-MQOL-R for the total sample was 6.09 (SD = 2.0). The median of all items was 6.17 [interquartile (IQR25-75) 4.67; 7.60].

Table 1 Sociodemographic and Clinical Characteristics of the Study Sample (n = 146)

Psychometric properties of the MQOL-R- BrP

Internal consistency

The BrP-MQOL-R final 14-item had a satisfactory internal consistency (α = 0.85). The mean (SD) for all items of the scale was 6.09 [2].

The MQOL-R scale and subscales and the total result were scored by averaging across items. We checked whether the findings in subscales differ from one another; we conducted a one-way repeated-measures ANOVA. The data comply with the variance sphericity (Muychaly’s test: W = 0.89, P = 0.008). This result indicates that the results in the MQOL-R sub-scales differ from one another. The multiple comparison test by Bonferroni revealed that QOL in the subscale social [mean (standard deviation)] was highest in our sample [8.14, (1.87); P < 0.001 for all comparisons], followed by existential [6.36 (2.10) P < 0.001 for all comparisons], psychological [5.21 (2.60)], and physical [4.88 (2.01)]. Other comparisons returned no significant difference.

Construct validity: questionnaire item selection, structural validity and cross-cultural-validity

Confirmatory factor analysis of the MQOL-R

We tested the internal structure of the MQOL-R using CFA, using the generalized least squares method. CFA revealed that all items were related to four specified factors, verifying the item's relationships and latent factors. Figure 2 shows the diagram and factor loading generated and presented in Table 2, the fit indices for this model. The analysis elicited adequate model goodness of fit (Table 2). The χ2 test (CMIN = 117.38; df = 73; p = 0.001) suggests insufficient fit, although this statistical tool is too restrictive and often points to rejecting a model with high samples involved. The chi-square/degree of freedom (CMIN/df = 1.608) reached a satisfactory value under 5. Following the strategy of presenting fit indices suggested by Hu and Bentler [19] if the root means the square error of approximation (RMSEA = 0.065; confidence interval 0.042–0.086) is 0.06 or below, and the standardized root-mean-square residual (SRMR) is 0.08 or below, thus, the model fitting is good. Comparative Fit Index (CFI = 0.934; RMSEA = 0.065; 95% CI range 0.042, 0.086). The revised model has the following fit-indices: PCLOSE = 0.131, Tucker-Lewis Index (TLI) rho 2 = 0.918, incremental fit index (IFI) delta 2 = 0.936. A second-order factor model was specified (Fig. 2) to support the derivation of an MQOL-R total score.

Fig. 2
figure2

MQOL-R items and CFA for first order (subscale) and second order (overall QOL) latent factors. Factor loadings are standardized

Table 2 Descriptive statistics, alpha coefficients for scores on the Brazil adaptation of the McGill Quality of Life Questionnaire-Items and the Total Score (n = 146)

Convergence validity

The correlation between the BrP-MQOL-R total scale and subscale scores is displayed in Table 4. Convergence-related validity is also supported by significantly positively correlated with higher levels in the BrP-MQOL-R total scores and their subscales with both the KPS score and the SIS related to the quality of life. In contrast, the BrP-MQOL-R was conversely correlated with the pain scores in the NPS (0–10). Most of the time, patients with higher pain scores in the last 24 h and after use pain medication showed a lower score in the BrP-MQOL-R, or vice-versa.

The pain scores on NPS (0–10) in two conditions, the pain level on most of the time in the last 24 h and relive of pain score when you take pain medication. The mean (SD) on the KPS was 59.18 (21.38). The mean score (SD) in the SIS measuring overall quality of life was 6.5 (2.54). The mean (SD) on the question of their pain level on most of the time in the last 24 h was 4.50 (3.72), and after taking pain medication was 2.06 (2.78).

Responsiveness and criterion-group validity

The responsiveness of the BrP-MQOL-R can be seen by the mean (standard deviation) of the total score. Patients with KPS equal to or lower than 30% could be discriminated from those with scores on KPS higher than 30%; the score on the BrP-MQOL-R was 4.83 (1.77) vs. 6.36 (1.95) (P = 0.00), respectively. Also, the scores of the QOL scale and subscales tend to be higher in subjects with the best functional status. That is means that this tool has properties to capture differences between patients in palliative care with the worst performance of those who have better functional status. We assessed the criterion validity by the screening accuracy to discriminate patients with KPS equal to or lower than 30% (n = 25) those with scores on KPS higher than 30% (n = 121) by non-parametric receiver operating characteristics (ROC) analyses an area under the curve (AUC) = 0.71, sensitivity = 97% and specificity = 92%).

A regression analysis was used to assess if sex, hospitalization, formal education, and age could influence the score in the BrP-MQOL-R. The variables retained in the model were sex and the hospitalization at the time of assessment, the beta-coefficient was − 0.86 (95% CI; − 1.49 to − 0.23; P = 0.00) and 0.78 (95% CI; 0.15 to 1.42; P = 0.01), respectively. That is, females and, if they were at home at the time of the assessment, showed higher scores.

Separate regression analyses were performed to determine the global BrP-MQOL-R score and a combination of the BrP-MQOL-R subscales to predict the SIS. These models were adjusted by hospitalization at the time of assessment adjusted and sex. The total score predicted similar variance in the SIS (R2 adjusted = 0.36; β = 0.49, t = 4.50, p < 0.001) than those found in the MQOL-R subscales (R2 adjusted = 0.36). A combination of two subscales was significant in predicting the SIS: Physical (β = 0.25, t = 2.43, p < 0.01) and Existential (β = 0.21, t = 2.29, p = 0.02).

Discussion

These results display data about the cross-cultural adapted to the English version of the BrP-MQOL-R. The process of translating and back translating the English BrP-MQOL-R to the Brazilian Portuguese translation was carried out stringently following established guidelines [10]. The set of questions of the BrP-MQOL-R presented satisfactory internal reliability with Cronbach's alpha coefficients higher than 0.85, likewise to the original English version. Our findings indicated an adequate construct validity and internal consistency of the BrP-MQOL-R translated and adapted to Brazilian Portuguese [10]. They also showed that the items with higher load are those related to social and psychosocial, and the lowest was found in the physical domains.

The content validity is evidenced by the high scores of the questionnaire items for readability, clarity, and comprehensiveness, as demonstrated by the scores on the visual analog scale in the assessment of the expert's committee consulted. Likewise, the result was found in a sample of patients in palliative care. This process yielded a Brazilian Portuguese version of MQOL-R semantically equivalent to the English language MQOL-R. Thus, the current version of the BrP-MQOL-R can be used without significant difficult in Portuguese-speaking populations. The test for internal consistency by Cronbach’s alpha indicates that either in the items and domains showed adequate consistency among their responses (see Tables 2, 3). These internal consistency coefficients by Cronbach's alpha are like them obtained original scale [8].

Table 3 Alpha coefficients for scores on the Brazil adaptation of the McGill Quality of Life Questionnaire-Revised and their subscales (n = 146)

CFA of the BrP-MQOL-R using a variety of different goodness of-fit model measures indicate an adequate construct validity. Like the original version, the model shows the goodness of fit with four factors: Existential, Social, Psychological, and Physical. [9] The CFA demonstrated that all items of four factors showed a load factorial higher than 0.4. This result indicates that all elements of each factor converge to a common point to constitute a construct. Thus, our result confirms how well our analyzed variables represent the original constructs [9]. A strength of BrP-MQOL-R is items in each of the four subscales remain as proposed by Robin Cohen et al. [9] The CFA suggests that it is possible to maintain the original structure scale items in the BrP-MQOL-R. Also, the factor analysis supports using separate scores for each one of the four domains.

We found moderate correlations between several domains, indicating that one life domain experience is related to other domains. Further, to examine the convergence validity of BrP-QOL-R, we analyzed the strength of the relationship with the functional status by KPS score and in the SIS about the quality of life. All correlation among these factors showed correlations coefficients less than 0.5 (see Table 4). According to literature, the correlation for concurrent validity measure similar concepts could not exceed 0.7 [20]. This way, the KPS scores’ correlation, either with the BrP-MQOL-R and their domains, indicates convergent validity. These results showed that these are measuring aspects of the same construct but not in an identical way. The KPS evaluates the functional status at the end of life, such as the patient’s ability to carry on his everyday activity and work or his need for a specific custodial care amount dependence or constant medical care to continue alive. These simple criteria serve to measure the burden that the patient's care represents to his family or society and indirectly evaluate aspects of life quality. We used the same rationale related to the convergent validity to interpret the weak association of the MQOL-R score with an SIS QOL (r = 0.33). However, in this case, the converse correction among the QOL score and their subscales indicates that this tool and its subscales can identify the negative impact of pain on life quality. From the clinical perspective, they support improving educational programs to improve pain management to relieve patients' suffering in palliative care.

Table 4 Correlations among the MQOL-RBr total scores and their dominions, the single-item related to quality of life, functional status, and severity of pain (n = 146)

The relevance of these results is to evidence that the BrP-MQOL-R showed a sensibility identify the effect of factors that contribute to worst QOL either cancer or non-cancer patients. For example, the pain level, which is a specific aspect of healthcare, is a person-centered experience. In sum, these findings demonstrated that this tool validated and adapted to the Brazilian population is suitable as part of an assessment of "quality of life" in patients in palliative care. Another measure that showed the theoretical construct of the BrP-MQOL-R is the criterion-validity to differentiate those patients unable to perform their activities with or without assistance compared to those that need medical care but less than the distinguished group. Thus, this intensive process to establish the validity of the BrP-MQOL-R provided reliable support for its validity in more depth. Thereby, we can offer the Brazilian population an instrument to assess the quality of life" in palliative care adequately adapted. This is important to clinical and for research from a transcultural perspective. Notably, it would be a useful tool to evaluate how the impact of support pharmacological and non-pharmacological in palliative care in different cultures. Mainly because in patients under palliative care, the illnesses are in progress, and healthcare takes on an increasingly important role day by day in these people’s life. Hence, the quality of life should be the most target in the care of these patients.

In the present study, males were associated with the worst quality of life compared to females. Accordingly, prior research investigating sex differences in aggressiveness of end-of-life care preferences [21] and women are less likely to prefer life-sustaining technology and other aggressive treatments. Also, they are more likely to give do-not-resuscitate orders to have a dignified death [21]. While another survey found that among patients with advanced cancer, women were more likely than men to recognize that their disease was incurable and at an advanced stage and report having discussed life expectancy with their oncologist [22]. Another result that evidenced the discriminatory properties of the validated scale was identifying the worst quality of life of patients in the hospital compared to patients in palliative care at home. This finding is plausible and supported by earlier surveys conducted in the United States (US), the UK, and the Netherlands, which reported that the quality of the end of life in hospitals was not satisfactory [23,24,25].

The main limitations of this study should be addressed. First, the test–retest was not performed. However, it is important to realize that the reliability of the test–retest gives more reliable results when a patient's health status is stable at both times of the test [26]. In the context of palliative care, the clinical status changes faster sometimes in hours or in a few days at the way that this measure would be less reliable. Second, the study is limited by the nonrandom selection of patients recruited in palliative care service at a university hospital. Hence, selection bias is possible, and it is uncertain whether these findings can be extrapolated to patients receiving treatment in hospitals without palliative care. However, it is noteworthy that our results are consistent with findings observed in the original English language version, which involved a variety of a representative national sample [27]. Third, the study is based on self-report measures. Thus, the comprehension of items content of the assessment instruments may have implications for the internal validity of the survey. Finally, longitudinal studies are required with a more significant number of clinical samples.

Conclusion

This study provided evidence for the validity, reliability and demonstrated that the psychometric properties of the BrP-MQOL are satisfactory. Also, it showed adequate discriminate properties being sensitive to detecting the general conditions of patients with a terminal disease involving patients in palliative care in Portuguese-speaking countries. In sum, they suggest that this scale represents a valuable instrument for use in scientific studies and in the clinical setting involving patients in palliative care (Additional file 1).

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

AUC:

Area under the curve

BrP-MQOL-R:

Brazilian Portuguese McGill Quality of Life Questionnaire-Reviewed

CFA:

Confirmatory factor analysis

CI:

Confidence interval

CMIN:

Chi square

COSMIN:

Consensus Guideline Terminology

df:

Degree of freedom

HCPA:

Hospital de Clinicas de Porto Alegre

IFI:

Incremental fit index

IQR:

Interquartile ranges

KPS:

Karnofski performance score

MQOL-R:

McGill Quality of Life Questionnaire-Reviewed

NPS:

Numeric Pain Scale

PC:

Palliative care

PROMS:

Patients Reported Outcome Measures

QOL:

Quality of life

ROC:

Receiver operator characteristics

RMSEA:

Root means the square error of approximation

SD:

Standard deviation

SEs:

Standard errors

SIS:

Single Item Scale

SRMR:

Standardized root-mean-square residual

TLI:

Tucker Lewis index

UCACUE:

Universidad Católica de Cuenca

UFRGS:

Universidade Federal de Rio Grande do Sul

UK:

United Kingdom

US:

United States

VAS:

Visual Analogue Scale

References

  1. 1.

    WHO. WHO definition of palliative care [Internet]. (WHO | WHO definition of palliative care, 2020). 2020. https://www.who.int/cancer/palliative/definition/en/#:~:text=Palliative care is an approach,pain and other problems%2C physical%2C

  2. 2.

    Robin Cohen S, Mount BM, Strobel MG, Bui F. The McGill quality of life questionnaire: a measure of quality of life appropriate for people with advanced disease. A preliminary study of validity and acceptability. Palliat Med. 1995;9:207–19.

    Article  Google Scholar 

  3. 3.

    Cohen SR, Mount BM, Tomas JJN, Mount LF. Existential well-being is an important determinant of quality of life: evidence from the McGill Quality of Life Questionnaire. Cancer. 1996;77:576–86.

    CAS  Article  Google Scholar 

  4. 4.

    Cohen SR, Mount BM, Bruera E, Provost M, Rowe J, Tong K. Validity of the McGill Quality of Life Questionnaire in the palliative care setting: a multi-centre Canadian study demonstrating the importance of the existential domain. Palliat Med. 1997;11:3–20.

    Article  Google Scholar 

  5. 5.

    Cohen SR, Hassan SA, Lapointe BJ, Mount BM. Quality of life in HIV disease as measured by the McGill Quality of Life Questionnaire. AIDS. 1996;10:1421–7.

    CAS  Article  Google Scholar 

  6. 6.

    Bruera E, Kuehn NMM. The Edmonton Symptom Assessment System (ESAS): a simple method for the assessment of palliative care patients. J Palliat Care. 1991;7:6–9.

    CAS  Article  Google Scholar 

  7. 7.

    Watanabe SM, Nekolaichuk CL, Beaumont C. The Edmonton Symptom Assessment System, a proposed tool for distress screening in cancer patients: development and refinement. Psychooncology. 2012;21:977–85.

    Article  Google Scholar 

  8. 8.

    Rybarski R, Zarzycka B, Bernat A. Measuring the quality of life of people with life-threatening illnesses: the internal structure of the Polish adaptation of the McGill Quality of Life Questionnaire-Revised. Contemp Oncol. 2018;22(4):252–9.

    Google Scholar 

  9. 9.

    Cohen SR, Sawatzky R, Russell LB, Shahidi J, Heyland DK, Gadermann AM. Measuring the quality of life of people at the end of life: The McGill Quality of Life Questionnaire-Revised. Palliat Med. 2017;31:120–9.

    Article  Google Scholar 

  10. 10.

    Mokkink L, Prinsen C, Patrick D. COSMIN: Methodology for Systematic reviews of Patient-Reported Outcome Measures (PROMS) user manual. Amsterdam Public Heal Res Inst. 2018;1:78.

    Google Scholar 

  11. 11.

    Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine. 2000;21:3186–91.

    Article  Google Scholar 

  12. 12.

    Guillemin F, Bombardier C, Beaton DE. Cross-cultural adaptation of HRQL measures: literature review and proposed guidelines. J Clin Epidemiol. 1993;46:1417–32.

    CAS  Article  Google Scholar 

  13. 13.

    Wagner AK, Gandek B, Aaronson NK, Acquadro C, Alonso J, Apolone G, et al. Cross-cultural comparisons of the content of SF-36 translations across 10 countries: results from the IQOLA Project. J Clin Epidemiol. 1998;51:925–32.

    CAS  Article  Google Scholar 

  14. 14.

    Deyo RA. Pitfalls in measuring the health status of Mexican Americans: comparative validity of the English and Spanish sickness impact profile. Am J Public Health. 1984;74:569–73.

    CAS  Article  Google Scholar 

  15. 15.

    Hsu CC, Sandford BA. The Delphi technique: making sense of consensus. Pract Assessment Res Eval. 2007;12:1–8.

    Google Scholar 

  16. 16.

    Mor V, Laliberte L, Morris JN, Wiemann M. The Karnofsky performance status scale: an examination of its reliability and validity in a research setting. Cancer. 1984;53:2002–7.

    CAS  Article  Google Scholar 

  17. 17.

    O’Rourke, Norm. Hatcher L. A step-by-step approach to using SAS for factor analysis and structural equation modeling. SAS Institute. 2013.

  18. 18.

    Ruopp MD, Perkins NJ, Whitcomb BW, Schisterman EF. Youden Index and optimal cut-point estimated from observations affected by a lower limit of detection. Biometrical J. 2008;50:419–30.

    Article  Google Scholar 

  19. 19.

    L. J. The structure of Chinese values: indigenous and cross-culture perspectives. 2015. 216 p.

  20. 20.

    Bolarinwa O. Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Niger Postgrad Med J. 2015;22(4):195. https://www.npmj.org/text.asp?2015/22/4/195/173959.

  21. 21.

    Sharma RK, Prigerson HG, Penedo FJ, Maciejewski PK. Male-female patient differences in the association between end-of-life discussions and receipt of intensive care near death. Cancer. 2015;121:2814–20.

    Article  Google Scholar 

  22. 22.

    Fletcher K, Prigerson HG, Paulk E, et al. Gender differences in the evolution of illness understanding among patients with advanced cancer. J Support Oncoogy. 2013;11:126–32.

    Article  Google Scholar 

  23. 23.

    People N survey of bereaved. Office for National Statistics. National survey of bereaved people (VOICES). 2015. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthcaresystem/bulletins/nationalsurveyofbereavedpeoplevoices/england2015#preferences-and-choice-at-the-end-of-life.

  24. 24.

    Witkamp FE, Van Zuylen L, Borsboom G, Van Der Rijt CCD, Van Der Heide A. Dying in the hospital: what happens and what matters, according to bereaved relatives. J Pain Symptom Manage. 2015;49:203–13.

    Article  Google Scholar 

  25. 25.

    Walling AM, Asch SM, Lorenz KA, Roth CP, Barry T, Kahn KL, et al. The quality of care provided to hospitalized patients at the end of life. Arch Intern Med. 2010;170:1057–63.

    Article  Google Scholar 

  26. 26.

    Schougaard LMV, de Thurah A, Bech P, Hjollund NH, Christiansen DH. Test-retest reliability and measurement error of the Danish WHO-5 Well-being Index in outpatients with epilepsy. Health Qual Life Outcomes. 2018;16:175.

    Article  Google Scholar 

  27. 27.

    Robin Cohen S, Russell LB, Leis A, Shahidi J, Porterfield P, Kuhl DR, et al. More comprehensively measuring quality of life in life-threatening illness: The McGill Quality of Life Questionnaire-Expanded. BMC Palliat Care. 2019;18:92.

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the collaboration to the following Brazilian agencies: Committee for the National Council for Scientific and Technological Development (CNPq) (grants to ILST and WC); Postgraduate Program in Medical Sciences at the School of Medicine of the Federal University of Rio Grande do Sul (material support); Postgraduate Research Group at the Hospital de Clínicas de Porto Alegre (FIPE-HCPA) (material support); and the Brazilian Innovation Agency (FINEP) (process number 1245/13; WC).

Funding

Brazilian agencies, Committee for the Development of Higher Education Personnel—CAPES—PROEX to material support. Postgraduate Research Group at the Hospital de Clínicas de Porto Alegre—FIPE HCPA (material support—16-0635). Research grant: National Council for Scientific and Technological Development-CNPq (Torres, I.L.S. 302345/2011-6 and Caumo, W. WC-301256/2013-6). Incentive Funding (FIPE/HCPA) at the Hospital de Clínicas de Porto Alegre (project number 2019–0207) and Hospital de Clínicas de Porto Alegre for material and infrastructure support.

Author information

Affiliations

Authors

Contributions

All authors made a significant contribution to study concept and design, acquisition of data, or analysis and interpretation of data, drafting or revising the manuscript for important intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Wolnei Caumo.

Ethics declarations

Ethics approval and consent to participate

The protocol of this cross-sectional study was approved by the Ethics Committee Board of the Hospital de Clínicas de Porto Alegre, Brazil (protocol no 2019-0207). All subjects gave their written formal consent for participation or their caregivers.

Consent for publication

Not applicable.

Competing interests

The authors declare that there are no financial and/or non-financial interests that might lead to conflicts of interest involving any of the following arrangements: financial relationship to the work, employees of a company, consultants for a company, stockholders of the company, members of a speaker’s bureau or any other form of financial compensation. The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Additional file 1

. The McGill Quality of Life Questionnaire-Revised (MQOL-R) validated for Brazilian Portuguese

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Serrano, P.V., Serrano, G.B., Torres, I.L.S. et al. The McGill Quality of Life Questionnaire-Revised (MQOL-R). Psychometric properties and validation of a Brazilian version on palliative care patients: a cross-sectional study. Health Qual Life Outcomes 18, 368 (2020). https://doi.org/10.1186/s12955-020-01621-8

Download citation

Keywords

  • Quality of life
  • Palliative care patients
  • Karnofsky performance
  • MQOL-R