Abstract
Background and aim
The 23-item Kansas City Cardiomyopathy Questionnaire (KCCQ) is widely used to assess health-related quality of life (HRQoL) in HF patients covering key HF-related health status domains. This study validated the Arabic KCCQ version and looked into potential correlation between patients’ HRQoL and their demographics/clinical characteristics, health literacy, medication adherence/knowledge.
Methods
This was a multicenter validation study from Jordan including HF adult patients. Cronbach’s alpha coefficient was employed to assess the scale internal consistency. Test-retest reliability evaluated stability of participants’ responses overtime. Construct validity was examined through exploratory factor analysis (EFA), supported by Kaiser-Meyer-Olkin measure and Bartlett’s sphericity test. Model fit was evaluated by confirmatory factor analysis (CFA). Associations between KCCQ scores and patient demographic/clinical characteristics, health literacy, medication adherence/knowledge were analyzed using linear regressions.
Results
A total of 331 participants were recruited from two centers. KCCQ domains’ scores ranged from mean±SD of 42.90±25.43 for symptom stability to 76.80±30.63 for social limitation. The total symptom, clinical summary and overall summary scores were 70.96±29.13, 74.67±25.67 and 70.67±25.70, respectively. The scale demonstrated excellent internal consistency (Cronbach’s alpha=0.937). Test-retest analysis showed strong significant intraclass correlation coefficients and Pearson’s correlation indicating good reliability. EFA and CFA supported data suitability for factor analysis and good model fit. The multivariate regression showed being married, performing exercise, being adherent to medication and taking fewer medications to significantly correlate to better HRQoL.
Conclusion
The Arabic KCCQ version is a reliable, valid tool for HRQoL assessment among Arabic-speaking communities. Implementing interventions targeting sedentary HF patients not adherent to treatment regimen can improve HRQoL.
Keywords: Kansas City Cardiomyopathy Questionnaire (KCCQ), health-related quality of life (HRQoL), Arabic language, validation
Introduction
Heart failure (HF) is a chronic, progressive condition marked by breathlessness, fluid retention, fatigue, and reduced exercise capacity affecting around 64 million people globally in 2017. In the Middle East and North Africa (MENA) region, with a population of 250 million, about 3.75 million are estimated to have HF. 1 Jordan reports approximately 100,000 cases annually, with an incidence of around 8,251 cases. 2 The high rates of coronary artery disease, obesity, tobacco use, and diabetes—affecting up to 25% of adults—contribute to the observed HF prevalence. Hypertension is also common, present in 40–70% of HF patients. 1 Heart failure arises from a complex interaction of hemodynamic, neurohormonal, structural, and inflammatory factors, driving disease progression and symptom development. 3 The New York Heart Association (NYHA) classifies HF severity into four classes, ranging from Class I (no physical activity limitation) to Class IV (symptoms at rest). 4 Given its high rates of morbidity, mortality, and healthcare utilization, HF remains a significant global public health issue. 5
Health-related quality of life (HRQoL) is a critical patient-reported outcome in HF and serves as a strong predictor of hospitalization and mortality. 6 Due to persistent symptoms such as dyspnea, fatigue, and edema, patients often experience reduced physical function and frequent hospitalizations. 6 These physical limitations are compounded by emotional and social challenges, including depression affecting around one third of HF patients.7,8 Multiple predictors influence the HRQoL in HF, including patients’ gender, age, marital status, NYHA class, and left ventricular ejection fraction (LVEF). In addition, health-related factors such as health literacy, medication adherence and medication knowledge have been linked to the patients’ health status including their disease-related HRQoL.9–11
Poor HRQoL is consistently associated with worse clinical outcomes, highlighting the importance of integrating HRQoL assessment into both clinical care and research. 7
Various tools and questionnaires have been used to assess HRQoL in patients with HF, aiming to capture the broad impact of the condition on their daily living. Commonly used instruments include the Kansas City Cardiomyopathy Questionnaire (KCCQ), 12 the Minnesota Living with Heart Failure Questionnaire (MLHFQ), the EuroQoL-5 Dimensions (EQ-5D), the Short Form Health Survey (SF-36), and the MacNew Heart Disease Health-Related Quality of Life Questionnaire. 13 Among these, the KCCQ is a widely recognized, self-administered tool specifically developed to assess HRQoL in HF patients. 14 It includes 23 items covering seven key domains that span from physical limitation to social limitation. 15 The KCCQ is used extensively in both clinical practice and research to monitor disease progression, assess treatment effectiveness, and evaluate outcomes in clinical trials. 12 Despite this, and while other tools such as the MLHFQ, the EQ-5D and even the short 12-item version of the KCCQ have been validated in Arabic,16–18 the original 23-item version of the KCCQ has never been validated in Arabic, which encompasses the aim of the current study. In addition, the study also aimed to evaluate possible correlation between the patients’ HRQoL measured by the KCCQ tool and certain relevant health-related factors including health literacy, medication adherence and medication knowledge.
Methodology
Study design, settings and participants
This was a validation study conducted cross-sectionally on two clinical centers in Jordan, the Jordan University Hospital (JUH) and the King Abdullah University Hospital (KAUH), between May-Nov 2024. The study sites are two of the largest tertiary governmental hospitals covering the central and the north regions of the country, respectively.19,20 Adults patients, diagnosed with heart failure (any NYHA class) and with no cognitive or communicative disabilities were approached by a research assistant at the cardiology outpatient clinics of the study centers and were asked to participate in the study.
Patients with a condition interfering with the primary study aim (lung fibrosis, or leg amputation), or an acute event (acute coronary syndrome, or stroke) were excluded from the study. Participants were also asked whether they accept to be re-contacted after two weeks through a telephone call to re-collect information related to their HRQoL for the test-retest validation analysis of the study tool. A sample size of 300 is considered adequate for psychometric validation studies. 21 The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) reporting checklist has been applied in this study (Appendix A - supplementary material). 22
Ethical considerations
The study was approved by the Institutional Review Boards of JUH (10/2023/26301) and KAUH (16/169/2024). Written informed consents were obtained from the participants who agreed to take part in the study who were interviewed by the research assistant in an appropriate place to ensure the interviewee’s privacy and confidentiality. Data was properly coded (pseudonymized) and analyzed.
Data collection tool
During the interviews, data was collected from the study participants in relation to their demographic and clinical characteristics. In addition, specific tools were employed to collect information about patients’ HF-related QoL, their health literacy (HL), medication adherence, and medication knowledge.
Quality-of-life measurement using the Kansas City Cardiomyopathy Questionnaire (KCCQ)
The KCCQ is a self-administered 23-item questionnaire designed to comprehensively describe HRQoL in heart failure (HF) patients. It is superior to traditional QoL instruments due to its patient-centered assessment and coverage of a wide range of aspects of the patient’s life that are impacted by HF. The KCCQ has a two-week recall period and quantifies seven domains of patients’ HF-related health status: physical limitation (6 items), symptom stability (1 item), symptom frequency (4 items), symptom burden (3 items), self-efficacy (2 items), quality of life (3 items), and social limitations (4 items). 15 In addition, three summary scores can be calculated from the main domains: a total symptom score, a clinical summary score, and an overall summary score. 15
All KCCQ scores are expressed on 0 to 100 scale and can be categorized into 25-point ranges to represent health status as follows: 0 to 24: very poor to poor; 25 to 49: poor to fair; 50 to 74: fair to good; and 75 to 100: good to excellent.
Arabic version of the KCCQ
The Arabic version of the KCCQ and the right to use the tool alongside its scoring system was obtained by Outcomes Instruments, LLC under a license agreement. The linguistic validation of the Arabic version was conducted by PharmaQuest in accordance with the methodology outlined in Appendix B (supplementary material).
Health literacy, medication adherence and medication knowledge
The Arabic version of the 12-item European Health Literacy Survey Questionnaire (HLS-Q12)23,24 was used to assess the health literacy among the study population. According to its scoring system, the HLS-Q12 categorizes patients’ HL into being either high (scores between 33-48) or low (scores between 12-32). To assess patients’ adherence and knowledge to their HF medications, the Arabic version of the Morisky Green Levine scale (MGLS)25,26 and a modified version of the McPherson questionnaire27,28 were used, respectively. The MGL scale is a 4-item tool that measures adherence to medications using yes/no questions coding respectively 1/0. Participants were considered to have either high adherence to medications if the total score was 0-1, or low-moderate adherence if they scored 2-4. Patients’ knowledge was considered a dichotomous variable with a cut-off value equal to 4 (median). Participant’s knowledge was considered high if the total score was 4 or higher.
Data analysis
Data was analyzed using SPSS (version 23) and AMOS (version 26). The demographics and clinical characteristics of the study participants were reported as frequency (percentage) for categorical variables and mean±SD for continuous variables. All tested hypotheses were two-tailed. A p-value<0.05 indicated statistical significance.
Reliability and internal consistency
The internal consistency of the KCCQ was assessed using Cronbach’s alpha, which reflects the tool’s ability to reliably measure the intended attributes of the scale. Values above 0.7 are generally considered indicative of good reliability.
Test-retest reliability
Test-retest reliability was assessed to evaluate the consistency of participants’ responses upon repeated measurements using the same scale. Accordingly, the tool was administered a second time to the participants two weeks after the initial interview. Reliability was measured using the Intra-class Correlation Coefficient (ICC) and Spearman’s rank (Spearman’s r) correlation coefficient. A Spearman r value of ≥0.75 indicates very good to excellent correlation, values between 0.51 and 0.75 indicate moderate to good correlation, values from 0.26 to 0.50 suggest a small correlation, and values between 0 and 0.25 reflect little to no correlation. 29
Construct validity
Construct validity was assessed through exploratory factor analysis (EFA) with varimax rotation, to evaluate the extent to which the KCCQ scale captures the quality of patient’s life. The Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s test of sphericity were determined. Parallel analysis and scree plots guided factor retention, with factors considered significant if they had eigenvalues greater than 1 and factor loadings of 0.4 or higher.
Model fit
Confirmatory factor analysis (CFA) was conducted to assess the model’s fit. The evaluation included several goodness-of-fit indices: acceptable thresholds for the Goodness of Fit Index (GFI) and the Adjusted Goodness of Fit Index (AGFI) were ≥0.95 and ≥0.90, respectively. Additional indices included the Normed Fit Index (NFI), where values ≥0.95 indicate a good fit, as well as the Root Mean Square Error of Approximation (RMSEA) and the Standardized Root Mean Square Residual (SRMSR), with acceptable values being <0.06 and <0.08, respectively. 30
Linear regression
Simple linear regressions were employed to investigate the presence of associations between the overall KCCQ summary scores and the participants’ demographics/clinical characteristics, HL, medication adherence and medication knowledge. Factors showing a p-value <0.20 were included in multivariate linear regression. Tested factors included marital status, exercise routine, education level, number of chronic diseases, number of medications, and MGLS scale.
Results
Demographic and clinical characteristics of the study participants
A total of 331 patients with HF with reduced ejection fraction (HFrEF) were enrolled in the study. Among them 70.7% (N = 234) were recruited from JUH and 23.3% (N = 97) from KAUH. The mean±SD age of the study participants was 63.3±11.9. Most of the respondents were female (67.4%), married (87%), living with a family member or caregiver, unemployed/retired (74%) and medically insured (92.1%). Half of the participants (50.2%) had a scholar degree. Only 21.1% of the respondents were performing exercise while the majority were non-smokers (62.5%), (Table 1).
Table 1.
Demographics characteristics of the study participants (N = 331).
| Variable # | Frequency (%) | p-value β |
|---|---|---|
| Age α | 63.3±11.9 | 0.317 |
| Gender | | 0.984 |
| Male | 108 (32.6) | |
| Female | 223 (67.4) | |
| Marital Status | | 0.002 |
| Married | 288 (87) | |
| Others (not married) | 43 (13) | |
| Living conditions | | 0.607 |
| With family member/caregiver | 324 (97.9) | |
| Alone | 7 (2.1) | |
| Education | | 0.143 |
| Scholar Degree | 166 (50.2) | |
| Diploma or higher degree | 165 (49.8) | |
| Occupation | | 0.632 |
| Unemployed/Retired | 245 (74) | |
| Employed | 86 (26) | |
| Medical Insurance | | 0.812 |
| No | 13 (3.9) | |
| Yes | 305 (92.1) | |
| Exercise | | 0.001 |
| No | 261 (78.9) | |
| Yes | 70 (21.1) | |
| Smoking Status | | 0.232 |
| No | 207 (62.5) | |
| Yes, current smoker | 124 (37.5) | |
Bold values indicate statistical significance p<0.05.
#All data is expressed as frequency (%) of participants unless otherwise indicated.
αData presented as mean±SD.
βSimple linear regression of the variable’s association with the KCCQ overall summary score.
Table 2 summarizes the clinical characteristics of the study population. The majority (74.3%) had two or less chronic diseases; the most common was disease of the circularity system (84.2%). Most of the population was treated with four or less HF medications (71.6%). The most common administered medications were renin-angiotensin-aldosterone antagonists (ACEI or ARB or ARNI), beta blockers and diuretics (98.1%, 93.3% and 63.6%, respectively). Just a minority of the participants were receiving a mineralocorticoid receptor antagonist (MRA) (16.7%) and sodium-glucose co-transporter 2 (SGLT2) inhibitors (12.7%).
Table 2.
Clinical characteristics of the study participants (N = 331).
| Variable# | Frequency (%) | p-value β |
|---|---|---|
| Chronic diseases | ||
| Endocrine nutritional and metabolic disease & immunity disorders | 193 (58.3) | 0.670 |
| Diseases of blood and blood forming organs | 28 (8.5) | 0.308 |
| Diseases of the circularity system | 279 (84.2) | 0.280 |
| Diseases of the respiratory system | 32 (9.7) | 0.114 |
| Diseases of the genitourinary system | 60 (18.1) | 0.015 |
| Diseases of the musculoskeletal system | 17 (5.1) | 0.015 |
| Others | 53 (16) | 0.614 |
| Total number of chronic diseases | | 0.008 |
| ≤2 | 246 (74.3) | |
| >2 | 85 (25.7) | |
| Medications | ||
| ACE | 108 (32.7) | <0.001 |
| ARB | 135 (40.9) | <0.001 |
| ARNI | 81 (24.5) | <0.001 |
| Diuretic | 210 (63.6) | <0.001 |
| BB | 308 (93.3) | 0.021 |
| MRA | 55 (16.7) | <0.001 |
| SGLT2i | 42 (12.7) | 0.001 |
| Number of HF Medications | | <0.001 |
| ≤4 | 237 (71.6) | |
| >4 | 93 (28.1) | |
Bold values indicate statistical significance p<0.05.
#All data is expressed as frequency (%) of participants.
βSimple linear regression of the variable’s association with the KCCQ overall summary score.
Participants’ HRQoL, health literacy, medication adherence, and medication knowledge
The participants’ HRQoL scores (N = 331) as measured by the KCCQ (seven domains and three summary scores) are reported in Table 3. The domains’ scores ranged from a mean±SD of 42.90±25.43 for symptom stability to a mean±SD of 76.80±30.63 for social limitation. The mean±SD of the total symptom, clinical summary and overall summary scores were 70.96±29.13, 74.67±25.67 and 70.67±25.70, respectively (Table 3).
Table 3.
Scores of the seven KCCQ domains and the summary scores (N = 331).
| Question | mean±SD |
|---|---|
| Physical limitation | 72.37±25.08 |
| Symptom stability | 42.90±25.43 |
| Symptom frequency | 68.33±3.66 |
| Symptom burden | 73.54±29.73 |
| Self-Efficacy | 54.64±23.86 |
| Quality of Life | 62.73±29.92 |
| Social Limitation | 76.80±30.63 |
| Total symptom score | 70.96±29.13 |
| Clinical summary score | 74.67±25.67 |
| Overall summary score | 70.67±25.70 |
Upon evaluation of HL using the HLS-Q12 tool among the study participants (N = 97), the most revealed to have low HL (62.9%). On the other hand, most of the population reported a moderate-high adherence to medication (87.6%) measured by the MGLS tool. Applying a cut-off threshold of 4 (median) to the total knowledge score, most of the participants (76.3%) scored 4 or more indicating high medication knowledge (N = 97) (Table 4).
Table 4.
HL, medication adherence and Medication knowledge of the study participants.
| Variable # | Frequency (%) | p-value β |
|---|---|---|
| Health literacy (N=97) | | 0.679 |
| Low HL (score 12 – 32) | 61 (62.9) | |
| High HL (score 33 – 48) | 36 (37.1) | |
| Medication adherence (N=324) | ||
| Low adherence (score 3-4) | 34 (10.3) | 0.116 |
| Moderate-high adherence (score 0-2) | 290 (87.6) | |
| Medication knowledge (N=97) | | 0.885 |
| Low knowledge (score < 4) | 23 (23.7) | |
| High knowledge (score ≥ 4) | 74 (76.3) | |
#All data is expressed as frequency (%) of participants.
βSimple linear regression of the variable’s association with the KCCQ overall summary score.
Reliability and internal consistency of the study tool
The Arabic version of the KCCQ scale showed Cronbach’s alpha and standardized Cronbach’s alpha values of 0.937 and 0.944, respectively (Table 5). The corrected item-total correlation values ranged from -0.027 to 0.805 and the Cronbach’s alpha values when individual items were deleted ranged from 0.931 to 0.943 (Table 5). The negative corrected item-total correlation value for one of the items might indicate ambiguity in the item wording after translation, cultural differences in interpreting the concept being assessed, or the fact that it covers an aspect related to a distinct patient experience from others in the scale. Nevertheless, deleting the item doesn’t have a significant effect on the overall reliability. For the test-retest reliability the KCCQ questionnaire was used to collect responses a second time among 183 participants. The results showed a significant and strong intraclass correlation coefficient (ICC = 0.871, p <0.01), along with a significant and excellent Pearson’s correlation (r = 0.886, p <0.01); Table 6.
Table 5.
Reliability results (N = 331).
| Item number | Corrected item-total correlation | Cronbach’s alpha if item deleted |
|---|---|---|
| Q1a | 0.701 | 0.935 |
| Q1b | 0.509 | 0.936 |
| Q1c | 0.743 | 0.932 |
| Q1d | 0.778 | 0.932 |
| Q1e | 0.746 | 0.932 |
| Q1f | 0.563 | 0.935 |
| Q2 | 0.589 | 0.935 |
| Q3 | 0.586 | 0.934 |
| Q4 | 0.647 | 0.934 |
| Q5 | 0.723 | 0.933 |
| Q6 | 0.787 | 0.931 |
| Q7 | 0.720 | 0.933 |
| Q8 | 0.791 | 0.931 |
| Q9 | 0.595 | 0.934 |
| Q10 | 0.262 | 0.938 |
| Q11 | -0.027 | 0.943 |
| Q12 | 0.746 | 0.932 |
| Q13 | 0.745 | 0.932 |
| Q14 | 0.728 | 0.932 |
| Q15a | 0.741 | 0.932 |
| Q15b | 0.757 | 0.932 |
| Q15c | 0.805 | 0.932 |
| Q15d | 0.267 | 0.942 |
| Range | -0.027 – 0.805 | 0.931 – 0.943 |
Table 6.
Test-retest assessment using ICC and Pearson correlation (N = 183).
| Domain | Intraclass correlation coefficient (95%CI) | Spearman correlation coefficient (r) |
|---|---|---|
| Physical limitation | 0.953 (0.937-0.964) | 0.957 |
| Symptom stability | 0.383 (0.252-0.500) | 0.394 |
| Symptom frequency | 0.721 (0.643-0.784) | 0.729 |
| Symptom burden | 0.852 (0.806-0.887) | 0.853 |
| Self-Efficacy | 0.927 (0.903-0.945) | 0.928 |
| Quality of Life | 0.812 (0.756-0.856) | 0.816 |
| Social Limitation | 0.906 (0.877-0.929) | 0.912 |
| Total symptom score | 0.795 (0.735-0.843) | 0.802 |
| Clinical summary score | 0.897 (0.864-0.922) | 0.909 |
| Overall summary score | 0.871 (0.831-0.902) | 0.886 |
Construct validity
Exploratory factor analysis revealed a unidimensional structure, with only one component exhibiting an eigenvalue >1. This finding was further supported by the scree plot shown in Figure 1. The identified component accounted for approximately 54.6% of the total variance. Factor loadings were all above the minimum threshold ranging from 0.498 to 0.873 (Table 7). KMO measure of sampling adequacy was 0.935, and Bartlett’s test of sphericity was significant (p <0.01), indicating that the data were appropriate for factor analysis. These results confirmed the suitability of the dataset for conducting CFA.
Figure 1.
Scree plot the component number against eigenvalue (N = 331).
Table 7.
Items’ maximum factor loading.
| Item | Factors loading |
|---|---|
| Q1a | 0.612 |
| Q1b | 0.766 |
| Q1c | 0.691 |
| Q1d | 0.587 |
| Q1e | 0.589 |
| Q1f | 0.608 |
| Q2 | 0.712 |
| Q3 | 0.741 |
| Q4 | 0.719 |
| Q5 | 0.873 |
| Q6 | 0.683 |
| Q7 | 0.822 |
| Q8 | 0.603 |
| Q9 | 0.498 |
| Q10 | 0.729 |
| Q11 | 0.612 |
| Q12 | 0.578 |
| Q13 | 0.672 |
| Q14 | 0.587 |
| Q15a | 0.873 |
| Q15b | 0.771 |
| Q15c | 0.834 |
| Q15d | 0.697 |
Model fit
CFA results corroborated goodness of fit to the suggested scale. Values of estimated indices are: GFI = 0.971, AGFI = 0.943, NFI = 0.952, RMSEA = 0.010 and SRMSR =0.0131.
Regression
The multivariate linear regression revealed the KCCQ scores to be significantly associated with the following variables: marital status (p = 0.036), exercise routine (p = 0.008), adherence to medication evaluated by MGLS scale (p = 0.019), and the number of HF medications taken (p <0.001) (Table 8). Being married, performing exercise, and being more adherent to medications were associated with a better HRQoL. On the other hand, being treated with more HF medications was correlated to poorer HRQoL.
Table 8.
Multivariate linear regression.
| Model | Mean square | F | p-value |
|---|---|---|---|
| 498.048 (R=0.508) | 18.277 | 0.000 | |
| Variable | Standardized Beta | T | p-value |
| Marital Status (married/others) | 0.111 | 2.231 | 0.026 |
| Exercise (yes/no) | 0.133 | 2.691 | 0.007 |
| Total number of Chronic diseases (>2 disease/≤2 diseases) | -0.090 | -1.813 | 0.071 |
| MGLS (moderate-high/low) | 0.106 | 2.176 | 0.030 |
| Education (Higher/Scholar) | 0.028 | 0.562 | 0.574 |
| Number of HF Medications (>4 medications/≤4 medications) | -0.419 | -8.513 | <0.001 |
Bold values indicate statistical significance p<0.05.
Discussion
The current study is the first validating the Arabic version of the KCCQ among HF patients, and reporting the levels of HRQoL using the KCCQ in Jordan while also investigating potential correlations to a better HRQoL. Overall, the tool parameters showed satisfactory values as compared to the cut-off points for the used measures of reliability, internal consistency, construct validity, and model fit. This implies the Arabic KCCQ version to be a reliable and valid tool for measuring HRQoL among Arabic-speaking patients with HF.
The internal consistency of the Arabic KCCQ version was shown to be high (Cronbach’s alpha and standardized Cronbach’s alpha values of 0.937 and 0.944, respectively). These values are consistent with those reported by Green et al. and Creber et al. during the validation of the English version of the same tool, as well as by Albarrati et al. in their validation of the Arabic version of the shorter 12-item KCCQ.15,17,31 Similarly, the test-retest reliability revealed significant and strong intraclass correlation coefficient (ICC = 0.871, p <0.01) indicating high level of consistency between repeated measurements upon using the same scale after a two-week interval which is also comparable to the finding reported by Albarrati et al. (2023). 17 Measures of construct validity using EFA and estimation of factor loadings were also satisfactory and aligned with findings from previous validation studies.17,31 The unidimensional structure of the KCCQ implies that the tool was able to measure the single intended construct.
As for the reported HRQoL among the participating HF patients, values of the different domains ranged from 42.90±25.43 (rated as very poor to poor) for symptom stability to 76.80±30.63 (rated as good to excellent) for social limitation. 12 Comparing these findings to those published in previous reports, also evaluating HF-related QoL using the KCCQ, reveals similarities and differences in the tool domains and summary scores. For instance, the observed physical limitation, quality of life and overall summary scores align with those reported by Flynn et al. also showing fair to good scores among their multicenter population. 32 Nonetheless, the mean values for the symptom stability and social limitation domains are, respectively, lower and higher than those observed by Flynn et al. 32 On the same line, the current fair to good values reported for the total symptom score, clinical summary score, and overall summary score can also be compared to those observed among the participants enrolled in the placebo arm of the multicenter study conducted by Siddiqi et al. 33 Furthermore, both studies showed consistently fair to good scores across the domains of symptom frequency, physical limitation, and quality of life. With respect to the remaining domains, this study findings indicated better social limitation scores (good to excellent) and lower scores for symptom stability, symptom burden, and self-efficacy. 33
Differences in the observed KCCQ-related QoL measures can be attributed to several contributing factors such as the type of heart failure (reduced vs preserved EF), the levels of functional ability among the study population (which can be described according to the NYHA classification system), differences in the participants’ underlying comorbidities, as well as diversities in the clinical settings and/or the sociocultural contexts. For instance, the social limitation scores observed in the current study suggest HF not to significantly impair the patients’ ability to engage in social activities. Considering the substantial amount of literature highlighting the negative impact of HF on patients’ social life this finding appears to be closely linked to the unique sociocultural context of Jordan.34,35 Previous research from Jordan has also consistently shown social support to positively influencing the HRQoL of patients with HF or other cardiac conditions.36,37
When looking into the factors associated with the reported KCCQ scores, being married, performing exercise routinely, and being adherent to medication were shown to be significantly associated with a better HRQoL. On the other hand, taking a higher number of HF medications correlated significantly with lower HRQoL scores. Marital status has been generally identified as a risk factor for cardiovascular diseases. 38 In patients with HF, previous studies found that being married or living with a partner is linked to reduced risks of mortality and hospitalization, as well as improvements in the HRQoL.39–41 On the same line, published reports showed high medication adherence to correlate to greater patients’ physical function, HRQoL and clinical event outcomes. 42 Supporting adherence of HF patients to their medical therapy showed improvements in their health status with interventions from healthcare providers showing the greatest impact in ameliorating adherence.43,44 In line with previous reports, taking a higher number of HF medications correlated to poorer HRQoL.45,46 This finding can simply reflect the need of more complex treatment among patients with lower KCCQ scores.
This is the first study validating the Arabic version of the KCCQ. It is also the first evaluating the HRQoL of HF patients in Jordan using this tool. The study participants were recruited from two of the largest tertiary hospitals in Jordan covering the central and north regions of the country. Despite the Arabic language of the KCCQ is the formal language spoken across all the Arabic-speaking countries, making it applicable to be used all over the MENA region healthcare context, further validation studies in other Arabic-speaking populations may still be necessary. Limitations of the study include relying on phone calls to collect information for the test-retest reliability and the possible overestimation of adherence rate due to desirability bias. In addition, some information such as patients’ NYHA classes and their LVEF were not collected and could not be correlated to the HRQoL scores. It is worth noting that patients’ HRQoL cannot be quantified into NYHA functional class as no exact mapping for such a conversion exists.
Conclusion
In conclusion, the current study demonstrated the Arabic version of the 23-item KCCQ to be a reliable and valid tool to assess HF-related QoL among Arabic-speaking patients. The study findings highlighted satisfactory tool reliability and validity measures, consistent with those observed from previous studies. Given the negative impact of HF on patients’ QoL making it a strong predictor of hospitalization and mortality, the KCCQ, with its comprehensive coverage of key domains related to HF health status, represents a valuable tool to be commonly used in clinical practice and research. This study offers validation for its use across the MENA region, paving the way for new opportunities towards patient-centered healthcare practice and research in Arabic speaking countries.
Future research from Jordan should include HF patients with preserved ejection fraction and further investigation of correlations between patients’ HRQoL and their relevant clinical characteristics. Interventions aiming at improving HRQoL should take into account risk factors such as physical inactivity and non-adherence to HF medications.
Supplemental material
Supplemental material for Validation of the Arabic version of the 23-item quality-of-life Kansas City Cardiomyopathy Questionnaire (KCCQ) by Oriana Awwad, Suha AlMuhaissen, Rama S. Odeh, Wejdan Shroukh, Basima A. Almomani, Abdulrahman Alsawafta, Mariam Abdeljalil in Sage Open Medicine.
Supplemental material for Validation of the Arabic version of the 23-item quality-of-life Kansas City Cardiomyopathy questionnaire (KCCQ) by Oriana Awwad, Suha AlMuhaissen, Rama S. Odeh, Wejdan Shroukh, Basima A. Almomani, Abdulrahman Alsawafta, Mariam Abdeljalil in Sage Open Medicine.
Appendix.
List of Abbreviations
Abbreviations Definition
- ACEIs
Angiotensin-converting enzyme inhibitors
- AGFI
Adjusted Goodness of Fit Index
- AMOS
Analysis of Moment Structures
- ARBs
Angiotensin II receptor blockers
- ARNI
Angiotensin receptor neprilysin inhibitor
- BB
Beta-blockers
- CFA
Confirmatory factor analysis
- EFA
Exploratory factor analysis
- EQ-5D
EuroQoL-5 Dimensions
- GFI
Goodness of Fit Index
- HF
Heart failure
- HFrEF
Heart Failure with reduced Ejection Fraction
- HL
Health literacy
- HLS-Q12
Health Literacy Survey Questionnaire
- HRQoL
Health-related Quality of life
- HRQoL
Health-related quality of life HRQoL
- ICC
Intra-class Correlation Coefficient
- JUH
Jordan University Hospital
- KAUH
King Abdullah University Hospital
- KCCQ
The Kansas City Cardiomyopathy Questionnaire
- KMO
Kaiser-Meyer-Olkin
- LVEF
left ventricular ejection fraction
- MENA
Middle East and North Africa
- MGLS
Morisky Green Levine scale
- MLHFQ
Minnesota Living with Heart Failure Questionnaire
- MRA
Mineralocorticoid receptor antagonist
- NFI
Normed Fit Index
- NYHA
New York Heart Association
- QoL
Quality of life
- RMSEA
Root Mean Square Error of Approximation
- SD
Standard deviation
- SF-36
Short Form Health Survey SF-36
- SGLT2i
Sodium-glucose co-transporter-2 inhibitors
- Spearman’s r
Spearman’s rank
- SPSS
Statistical Package for the Social Sciences
- SRMSR
Standardized Root Mean Square Residual.
Author contributions: Oriana Awwad (Conceptualization, Data curation, Methodology, Project administration, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing). Suha AlMuhaissen (Data curation, Formal Analysis, Validation, Visualization, Writing – original draft). Rama S. Odeh (Data curation, Formal Analysis, Investigation, Validation, Writing – review & editing). Wejdan Shroukh (Visualization, Writing – original draft). Basima A. Almomani (Resources, Supervision, Writing – original draft, Writing – original draft). Abdulrahman Alsawafta (Data curation, Investigation, Writing – review & editing). Mariam Abdeljalil (Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – review & editing).
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work received funds from the Deanship of Scientific Research at the University of Jordan under the grant number 19/2023/1739.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Supplemental material: Supplemental material for this article is available online.
ORCID iD
Oriana Awwad https://orcid.org/0000-0003-1750-6684
Ethical considerations
Ethical approval was obtained by the Institutional Review Boards of the Jordan University Hospital (10/2023/26301) and the King Abdullah University Hospital (16/169/2024). Written informed consents were obtained from all the participants.
Data Availability Statement
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.*
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplemental material for Validation of the Arabic version of the 23-item quality-of-life Kansas City Cardiomyopathy Questionnaire (KCCQ) by Oriana Awwad, Suha AlMuhaissen, Rama S. Odeh, Wejdan Shroukh, Basima A. Almomani, Abdulrahman Alsawafta, Mariam Abdeljalil in Sage Open Medicine.
Supplemental material for Validation of the Arabic version of the 23-item quality-of-life Kansas City Cardiomyopathy questionnaire (KCCQ) by Oriana Awwad, Suha AlMuhaissen, Rama S. Odeh, Wejdan Shroukh, Basima A. Almomani, Abdulrahman Alsawafta, Mariam Abdeljalil in Sage Open Medicine.
Data Availability Statement
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.*