Chronic heart failure health-related quality of life questionnaire (CHFQOLQ-20): Development and psychometric properties

doi:10.21203/rs.3.rs-1963159/v1

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Research Article

Chronic heart failure health-related quality of life questionnaire (CHFQOLQ-20): Development and psychometric properties

https://doi.org/10.21203/rs.3.rs-1963159/v1

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Background

Health-related quality of life (HRQoL) is an important outcome indicator for chronic diseases. This study aimed to develop a new instrument for assessment of HRQoL in chronic heart failure (CHF) and evaluate its psychometric properties.

Methods

This study included two steps of conceptualization and item generation, and assessment of the psychometric properties of an instrument for measuring HRQoL in patients with CHF. Content validity, exploratory and confirmatory factor analyses, concurrent validity, convergent validity, known groups comparison were performed to assess construct validity. Internal consistency, and stability were estimated by the Cronbach’s alpha and intraclass correlation coefficients.

Results

The content validity of the developed chronic heart failure quality of life questionnaire (CHFQOLQ-20) was assessed by 10 experts. The exploratory and confirmatory factor analyses yielded and confirmed four factors with 20 items. The concurrent and convergent validity of the CHFQOLQ-20 were established using the Short Form Health Survey (SF-36), and the MacNew Heart Disease Quality of Life Questionnaire, respectively. The known-groups validity as assessed by using the New York Heart Association (NYHA) functional classification., showed that the questionnaire discriminated well between patients who differed in functional classification. The internal consistency and test-retest reliability of the CHFQOLQ-20 were satisfactory, with a Cronbach’s alpha and intraclass correlation coefficient (ICC) values of 0.93 and 0.84, respectively.

Conclusion

The results confirmed that CHFQOLQ-20 is a valid and reliable measure of quality of life (QoL) in patients with CHF. It is a short and easy-to-use instrument that is also capable of assessing the cognitive function, which has been overlooked in previous questionnaires.

Patient reported outcome measure

Health-related quality of life

Chronic heart failure

Reliability

Validity

Heart failure (HF) is an important public health problem in different communities worldwide. Approximately 64.3 million people worldwide suffer from HF, and its prevalence in developed countries is 1–2% of the general population of of adults [1]. In Iran, patients with HF comprise 3.3% of the population [2]. HF is a chronic progressive disease with a significant symptom burden, impaired quality of life (QoL), and high rate of mortality [3]. The QoL of HF patients is lower than the QoL of the general population and patients with other chronic diseases. Patients often experience a number of physical and psychological symptoms such as dyspnea, fatigue, edema, sleep disorders, chest pain, and depression. Thus, their physical and social activities are impaired, and their health-related QoL (HRQoL) decreases [4]. The prognosis of HF is poorer than many cancer types [5].

At present, patient-reported outcome measurement is a valuable tool for assessment of the daily activities and limitations in daily living and QoL of patients [6]. Accordingly, questionnaires are the only tools for assessment of HRQOL and the effects of HF on daily life and activities of patients [7]. HRQOL is an important outcome indicator in chronic diseases because the conventional indicators (such as physical, physiological, and biochemical indicators) cannot comprehensively assess the effect of disease or treatment on patients. Thus, assessment of HRQoL is important for monitoring and follow-up of patients [8]. HF patients often experience a cognitive decline following impairment of their hemodynamics, and cerebral hypo-perfusion [9]. Several qualitative studies on the perspective of patients have reported cognitive disorders as adverse effects of HF on QoL [10–13]; however, none of the available instruments have a cognitive disorder domain [14]. In a holistic assessment of health, it is important to include subjective cognitive wellbeing, as a component of HRQoL in HF, in order to precisely assess the memory, clarity of thoughts, and mental ability of patients in their important daily tasks, leisure activities, self-care, safety, and adherence to medication intake [15].

The HRQoL of HF patients can be assessed by several generic and disease-specific instruments. The generic measures include sickness impact profile (SIP) [16] and the 36-item Short Form Health Survey (SF-36) [17] that assess the health status, as well as the disease-specific instruments for HF which are more sensitive to clinical changes and include Quality of Life Questionnaire in Severe Heart Failure (QLQ-SHF) [18], Chronic Heart Failure Questionnaire (CHFQ) [19], Left Ventricular Disease Questionnaire (LVDQ) [20], the Kansas City Cardiomyopathy Questionnaire (KCCQ) [21], the Minnesota Living With Heart Failure Questionnaire (MLHFQ) [22], and the Chronic Heart Failure Assessment Tool (CHAT) [4]. However, some of the available tools for this purpose have methodological limitations. For instance, CHFQ [19] and LVDQ [20] have a small sample size. Also, the structural validity of patient reported outcome measurement instruments is evaluated by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA); while, assessment of the underlying factors by CFA has not been performed in some of them such as CHAT [23], or is not clear in some others. MLHFQ is among the most commonly used tools. Several researchers such as the developers of MLHFQ have assessed the psychometric properties of this instrument; however, some concerns still exist regarding the homogeneity of some items and their validity. Heo in her PhD thesis assessed the psychometric properties of MLHFQ in a larger sample size (638 patients) and showed that seven items of this questionnaire may not properly reflect the common concerns of the majority of patients. Also, 16 out of 21 items of MLHFQ were loaded on three factors, and similar to the results of previous analyses, only two factors (physical and emotional) were meaningful clusters. Furthermore, the physical scale of MLHFQ moderately assesses the physical measures, and its emotional scale poorly evaluates this domain [24].

The significance of assessment of the problems of HF patients and their treatment outcomes highlights the need for developing a valid, reliable, and responsive tool for this purpose. HRQoL is influenced by the experiences, beliefs, expectations, and perceptions of individuals, and reflects the cognitive perception of individuals from the effects of HF on their life; whereas, the majority of the available tools for this purpose are expert-driven rather than patient-driven [23]. The majority of HRQoL tools for HF patients have been designed in Europe and North America; while, significant cultural and social differences exist between the eastern and western worlds which can affect the QoL. In an international consensus process comprising of experts in psychology, epidemiology, statistics, and clinical medicine from all over the world, a consensus was reached regarding the taxonomy, definitions of measurement properties, and measurement properties for health-related patient-reported outcomes. Accordingly, consensus-based standards for the selection of health measurement instruments (COSMIN) checklist was designed [25, 26]. In most cases, patient-reported outcome measures face a great challenge due to lack of compatibility with the standard systems and frameworks. The most comprehensive and widespread attempt of the World Health Organization (WHO) in this respect was to create a standard framework entitled International Classification of Functioning, Disability and Health (ICF). This framework is a comprehensive system according to a physiological, biological and social model, which can be adapted to many health measurement and QoL assessment tools. Concepts such as QoL, health, and function are supported by this framework [27]. Since the methodology of none of the HF measurement tools has been in accord with the COSMIN panel with the application of ICF, this study aimed to develop an instrument for assessment of HRQoL in chronic heart failure (CHF) and assess its validity and reliability from the perspective of Iranian patients according to the COSMIN recommendations on terminology and research agenda with ICF application for maximum optimization of this instrument.

Design

This study was conducted in two steps and guided by the COSMIN checklist manual [26].

Item generation

Items were generated by performing a literature review (qualitative and quantitative), and conducting qualitative studies [28, 29]. An extensive review of the literature was conducted with special emphasis on theories, models, and existing tools for measuring health-related quality of life in CHF. We compared the content of the existing tools based on the global framework for the comparison of HRQOL measurement instruments based on the World Health Organization guideline entitled International Classification of Functioning, Disability and Health (ICF) [4]. The qualitative study addressed QoL-related issues from the perspective of 19 selected patients with heart failure through semi-structured interviews and framework analysis approach (19 participants including 6 females and 13 males, with the mean age of 59.5 ± 12.4 years, the mean disease duration of 5.2 years, and the mean ejection fraction of 23.1 ± 8.3). Accordingly, 37 items were generated. Response categories ranged from 5 = not at all, to 1 = very much) with regard to the effect of heart failure on daily life of patients within the past 4 weeks. Higher scores indicated better quality of life. The total score of the final version ranged from 20 to 100.

Content validity

Ten experts including HF fellowship with cardiologists, HF specialized nurses, and psychologists evaluated the primary 37-item questionnaire according to Waltz and Bausell content validity index (CVI). The experts scored the relevance, clarity, and simplicity of each item using a four-point Likert scale. The CVI of each item was calculated by dividing the number of experts that gave a score of 3 or 4 to a particular item by the total number of experts [30]. Items with a CVI ≥ 0.79 were accepted. The necessity of each item was analyzed using a three-point rating scale of (I) not necessary, (II) useful, but not essential, and (III) essential. Following assessment by the experts, the content validity ratio (CVR) for each item was calculated. According to the Lawshe’s table, the acceptable CVR for 10 experts was set at 0.62.

Psychometric evaluation: participants and data collection

A cross sectional study was conducted on a sample of CHF patients from March 2018 to January 2019. Patients were selected from outpatient clinics of a teaching hospital affiliated to Mashhad University of Medical Sciences, and a private clinic in Mashhad, Iran. An HF specialist screened the patients with respect to the eligibility criteria using the New York Heart Association functional classification (NYHA) [31]. Participants with confirmed diagnosis of CHF, and ejection fraction ≤ 40% were enrolled. Patients with cognitive disorders were excluded.

Participants completed the questionnaire while they were briefed about the questionnaire and signed informed consent form. Patients were ensured that they were free to quit whenever they wished to do so. In addition, they have completed the following questionnaires.

Additional measures

The Short Form Health Survey (SF-36) was used for assessment of concurrent validity. The SF-36 is a well-known generic HRQOL measure with eight subscales of physical functioning, role limitations due to physical problems, role limitations due to emotional problems, vitality, mental health, social functioning, bodily pain, and general health perception. A higher score indicates higher HRQoL. The psychometric properties of the Iranian version of SF-36 are well documented [32], and its validity and reliability for HF have been confirmed [33] .Since it was expected that the disease-specific HRQOL would be moderately correlated with a generic HRQOL instruments, in the present study, it was hypothesized that the CHFQOLQ-20 would have a moderate positive correlation with the SF-36.

The MacNew Heart Disease Quality of Life Questionnaire: It is a disease-specific questionnaire and was used for assessment of convergent validity. It was designed for myocardial infarction patients. Moreover, it has been acceptably used for HF patients as well. It has 27 questions and three domains namely physical, psychological, and social. Higher scores indicate higher QoL. The psychometric properties of the Iranian version of this questionnaire are well documented [34], and its validity and reliability for CHF patients have been confirmed [35]. The Cronbach’s alpha for this questionnaire was 0.95. It was hypothesized that a moderate positive correlation between the CHFQOLQ-20 and the MacNew questionnaire would be achieved.

The New York Heart Association (NYHA) functional classification: It is a clinical classification ranging from 1 to 4 which is extensively used for assessment of cardiac functional capacity [31]. The NYHA class was determined by a specialist who had a fellowship in HF. It was used for known groups comparison and hypothesized that those with higher scores on the CHFQOLQ-20 would have a better functioning as measured by the NYHA functional class.

Data analysis

Descriptive statistics were applied to summarize the clinical and demographic characteristics of patients. The exploratory factor analysis (EFA) was performed to explore the items and their underlying structure using principal component analysis by oblique rotation. To extract the number of factors, the scree plot, Eigen values over 1, and parallel analysis were applied. To assess the sample adequacy, the Kaiser-Meyer-Olkin test, and to justify undertaking a factor analysis, the Barrette test of sphericity was used. The factor loading threshold was considered ≥ 0.4. To fit the underlying structure with the observed data, the confirmatory factor analysis (CFA) with the maximum likelihood method was used. The goodness-of-fit indices (GFIs) to confirm the model fit included the χ²/df ratio < 3, comparative fit index (CFI) > 0.9, normed fit index (NFI) > 0.9, goodness-of-fit index (GFI) > 0.9, adjusted GFI (AGFI) > 0.9, and root-mean-square error of approximation (RMSEA) < 0.08 [36, 37]. To assess the concurrent validity, and convergent validity the Pearson’s correlation coefficient was used. To assess known-groups comparison, one-way analysis of variance (ANOVA) were applied. The reliability of CHFQOLQ-20 was assessed by internal consistency (Cronbach’s alpha) and test-retest analysis (intraclass correlation coefficient-ICC). The internal consistency (Cronbach’s alpha) > 0.7 was considered to be acceptable. Fifty patients who had no change in their treatment protocol, and not received any intervention affecting their QoL were selected for test-retest with a 2-week interval, and the ICC value of > 0.7 was considered acceptable for test-retest reliability assessment. The SPSS version 25 was used for the EFA, and the SPSS Amos was used for the CFA.

Item generation

The peer-reviewed literature and individual semi-structured interviews led to generation of an item pool of 37 statements.

Content validity

In assessment of CVR, six items were omitted according to the cut-off point. Thus, the 37-item questionnaire was changed to a 31-item questionnaire. The average CVR for the total scale was 0.73, which was a satisfactory result. The CVI of the questionnaire was also calculated. The mean CVI scale was 0.91 (0.87-1), which indicated good content validity (10 experts). According to face validity and cut-off point of 1.5 for impact score, two extra items were eliminated and the 31-item questionnaire was converted to a 29-item questionnaire (10 patients).

Psychometric evaluation

In all 495 patients were entered into the study. Of these the data from 160 patients were used for explanatory factor analysis, and the data from remaining 335 patients were used for confirmatory factor analysis. Patients who participated in qualitative interviews were not included in psychometric analysis. The characteristics of the study samples are shown in Table 1.

Table 1

The characteristics of participants
	EFA sample (n = 160)	CFA sample (n = 335)
Age, year (mean, SD)	60.0 (11.1)	59.4 (12.7)
Gender, male (no., %)	112 (70)	228 (68)
Living with partner/spouse (no., %)	147 (91.8)	302 (90.1)
Years of education (mean, SD)	7.5 (3.1)	8.9 ( 4.4)
Body mass index (kg/m²)	24 (3.9)	26 (4.9)
Heart failure characteristics
Etiology of heart failure, ischemic (no., %)	116 (72.5)	239 (71.3)
Duration since heart failure, years (mean, SD)	4.9 (1.9)	(2.1) 5
Left ventricular ejection fraction (no., %)	24.9 (0.9)	26.6 ( 0.7)
Hypertension (no., %)	44 (27.5)	97(28.9)
CABG (no., %)	54 (33.7)	120 (35.8)
Diabetes (no., %)	63 (39.3)	147 (43.8)

Exploratory factor analysis

The initial results obtained from EFA showed low loading (< 0.3) for 8 items. Accordingly, the number of items was reduced to 21. In EFA, the underlying factor structure was assessed and the remaining item pool was refined. The result of Kaiser-Meyer-Olkin test was 0.925, indicating that factor analysis can be used to determine the dimensions. The result of Barrette test of sphericity was also statistically significant as follows: χ² = 4054.903, df = 190, P ≤ 0.001. Both tests showed sample adequacy for the conduction of EFA. The criteria used to determine the number of factors included eigenvalue > 1, Scree plot and factor loading > 0.4, and theoretical considerations. The initial EFA extracted a four-factor solution. The Scree plot graph in Fig. 1 suggested 2 to 5 factors, and eventually, by the parallel analysis (by using the Monte Carlo software) four factors were extracted that explained 67.5% of the total variance. Since the framework used for this study was ICF, the factors were labeled by the ICF underlying construct, and the content of loading items was loaded on each factor. The factor loading of each item was higher than 0.5 except for item 9 which had a factor loading of 0.446. The first factor extracted by EFA was labeled as “physical functioning”. This factor contained 10 items, with a of variance of 42.016%. The second factor was “cognitive functioning” with four items, that explained 9.906% of variance observed. The third factor was named as “general health”. It contained three items that explained 7.705% of variance. The fourth factor was labeled as “mental health”. It had four items with a variance of 6.025% (Table 2).

Table 2

Results obtained from exploratory factor analysis for the CHFQOLQ-20 (n = 160)
	Items	Factor 1 (Physical functioning)	Factor 2 (Cognitive functioning)	Factor 3 (General health)	Factor 4 (Mental health)
	Due to chronic heart failure, in the past 4 weeks:
1	Have you had trouble walking around the house?	0.789	0.000	-0.073	0.126
2	Did you have trouble taking a short walk (one block or around 100 meters)?	0.888	-0.079	-0.032	0.084
3	Did you experience difficulty in doing house chores (such as gardening, moving things, vacuum cleaning, or daily grocery shopping)?	0.894	-0.052	-0.022	0.030
4	Did you have trouble climbing up the stairs one floor with no rest?	0.9	0.006	0.014	-0.047
5	Did you have trouble fast walking for a few blocks or over 100 meters?	0.876	-0.041	0.041	-0.091
6	Did you experience difficulty in lifting heavy things (such as furniture or suitcase)?	0.838	-0.010	-0.043	-0.115
7	Did you have to lie-down or sit down during the day?	0.757	0.132	0.005	-0.010
8	Did you experience trouble in exercising, leisure activities or going on a trip?	0.630	0.088	0.114	0.107
9	Did you feel fatigue and low energy level?	0.464	0.163	0.159	0.155
10	Did you experience dyspnea during physical activities?	0.608	0.071	0.183	-0.023
11	Did you have problem concentrating (e.g. concentration in reading a topic or watching TV)?	0.087	0.752	-0.011	0.062
12	Did you have problem remembering things related to a few days earlier (e.g. remembering the location of things or an appointment)?	-0.053	0.899	0.045	-0.104
13	Did you have limitation in learning new topics or skills?	-0.017	0.875	0.035	0.050
14	Did you have problem in making decisions?	0.087	0.522	-0.142	0.423
15	How do you estimate your current general health status?	-0.019	-0.015	0.867	0.072
16	How do you assess your current health status in comparison with the past year?	0.046	-0.024	0.879	-0.088
17	How do you estimate your current quality of life?	-0.008	0.060	0.742	0.091
18	Do you feel as you are a burden to others?	0.360	0.035	0.038	0.501
19	Do you feel sad and depressed?	0.131	0.080	0.142	0.569
20	Do you feel useless and worthless?	0.083	-0.041	0.145	0.735
21	Do you have self-confidence*	-0.120	-0.016	-0.027	0.757
	Eigen values	8.823	2.080	1.618	1.265
	Variance (%)	42.016	9.906	7.705	6.025
This item was removed after confirmatory factor analysis.

Confirmatory factor analysis

The CFA was then performed for the fit of the extracted four-factor model to the data. The results obtained from the CFA eliminated one item from the mental health subscale, and thus, the number of items was reduced to 20. The model indicated excellent fit for the data: CFI = 0.947, NFI = 0.91, TLI = 0.937, IFI = 0.947, GFI = 0.899, AGFI = 0.869, RMSEA = 0.063. The results are depicted in Fig. 2. Table 3presents the minimum, maximum, and mean scores of each subscale and the total score of the instrument.

Table 3

Descriptive statistics for the CHFQOLQ-20
	Number of items (possible score)	Minimum	Maximum	Mean (SD)
Physical functioning	10 (10–50)	10	48	29.42 (10.34)
Cognitive functioning	4 (4–20)	5	20	15.07 (3.64)
General health	3 (3–15)	3	15	7.21 (2.59)
Mental health	3 (3–15)	3	15	10.62 (2.59)
Total	20 (20–100)	20	81	62.41 (15.73)

Concurrent validity

As hypothesized, the CHFQOLQ-20 was correlated very well with the following subscales of the SF-36: PF (r = 0.727, P < 0.001), BP (r = 0.687, P < 0.001), SF (r = 0.657, P < 0.001), RE (r = 0.478, P < 0.001), MH (r = 0.528, P < 0.001), VT (r = 0.636, P < 0.001), GH (r = 0.539, P < 0.001), and RP 0.595, P < 0.001). The results are shown in Table 4.

Table 4

Correlation coefficient between the CHFQOLQ-20 and the SF-36 subscales
	PF	RP	BP	GH	VT	SF	RE	MH
Physical functioning	0.722**	0.534**	0.638**	0.457**	0.565**	0.588**	0.405**	0.404**
Cognitive functioning	0.359**	0.396**	0.364**	0.225**	0.341**	0.397**	0.308**	0.401**
General health	0.391**	0.393**	0.470**	0.490**	0.368**	0.388**	0.300**	0.242**
Mental health	0.508**	0.425**	0.514**	0.510**	0.605**	0.553**	0.441**	.627**
Total	0.727**	0.595**	0.687**	0.539**	0.636**	0.657**	0.478**	0.528**
PF physical functioning, RP role limitations due to physical problems, BP bodily pain, GH general heal perception, VT vitality, SF social functioning RE role limitations due to emotional problems, MH mental health.
* Significant at the 0.05 level
** Significant at the 0.01 level

Convergent validity

As shown in Table 5the CHFQOLQ-20 was correlated with the following three subscales of the MacNew: physical (r = 0. 772, P < 0.001), emotional (r = 0.671, P < 0.001), and social (r = 0.726, P < 0.001) as expected.

Table 5

Correlation coefficient between the CHFQOLQ-20 and the MacNew Heart Disease Quality of Life Questionnaire
	MacNew (Physical)	MacNew (Emotional)	MacNew (Social)
Physical functioning	0.741**	0.688**	0.647**
Cognitive functioning	0.406**	0.381**	0.38**
General health	0.456**	0.487**	0.452**
Mental health	0.542**	0.635**	0.675**
Total	0.772**	0.671**	0.726**
* Significant at the 0.05 level
** Significant at the 0.01 level

Known-groups comparison

One-way analysis of variance (ANOVA) revealed that the HRQoL scores were significantly different among different functional classes of heart failure (P < 0.05) indicating that the CHFQOLQ-20 could discriminate well between patients who differed in functional class (Table 6).

Table 6. The CHFQOLQ-20 scores by the New York Heart Association (NYHA) functional classification

Reliability

The overall Cronbach’s alpha for the CHFQOLQ-20 was 0.93. It was also calculated separately for each subscale, which was > 0.7, indicating satisfactory results. The intraclass correlation coefficients (ICC) ranged from 0.7 to 0.92 lending support to the stability of the instrument. (Table 7).

Table 7

Reliability measures for the CHFQOLQ-20
	Cronbach's alpha	ICC (95% CI)
Physical functioning	0.939	0.88 (0.86–0.91)
Cognitive functioning	0.817	0.85 (0.80–0.88)
General health	0.803	0.84 (0.80–0.88)
Mental health	0.748	0.80 (0.76–0.86)
Total	0.930	0.84 (0.80–0.88)

HRQoL is an important outcome measure for clinical research. However, the majority of the available questionnaires are not patient-driven, and to the best of the authors’ knowledge, CHFQOLQ-20 is the first patient-driven questionnaire for assessment of HRQoL in CHF. The CHFQOLQ-20 includes important domains of HRQoL known by patients. Factor analysis extracted four factors of (I) physical functioning, (II) cognitive functioning, (III) general health, and (IV) mental health. These subscales all were confirmed by the CFA.

The first underlying factor identified by factor analysis had a clear reflection of physical functions, and had 10 items. Thus, it was labeled as physical functioning according to ICF. This subscale is the main core of health-related instruments in CHF, and had the maximum percentage of variance in our study. Oldridge et al, in 2014 developed a 14-item questionnaire entitled HeartQoL for ischemic heart failure patients, which had two subscales of physical and emotional. They also included 10 items for the physical domain, similar to CHFQOLQ-20, and the remaining questions (4 items) were related to the emotional domain [38].

Cognitive functioning was the second underlying factor with a lower variance share than the physical domain. Cognitive disorders in HF impair self-care and lead to not reporting the signs and symptoms of disease progression in a timely manner, disability, frequent hospitalizations, decreased QoL, and increased morbidity and mortality, highlighting the significance of assessing the cognitive disorders in HF patients who are mostly elderly [39]. Despite the significance of the cognitive domain, none of the existing instruments have a cognitive domain, and only the MLHFQ [22] has an item entitled “difficulty in concentration or remembering things” which has been loaded under the emotional domain.

General health was the third underlying factor loaded with three items and mental health which was the fourth underlying factor in CHFQOLQ-20. According to the literature, 30–40% of CHF patients experience emotional distress such as depression following impaired physical function, role changes, financial insecurity, and social isolation [39]. Depression in HF patients is correlated with fear due to development of physical symptoms such as dyspnea, and functional limitations. Fear can also lead to denial of disease symptoms and result in not seeking medical attention in time [40].

Similar to HeartQoL [38], CHFQOLQ-20 did not have a social domain. Oldridge et al. explained that the social problems of ischemic heart failure patients may not be unique or strong enough to be suggested as an independent latent construct. On the other hand, the social domain items may be culture- or diagnosis-specific, and since in ischemic heart failure, different diagnoses such as angina, myocardial infarction, and ischemic heart failure are considered, social problems cannot be generalized to the aforementioned three groups of diseases [38]. Similarly, the present study was conducted on ischemic and non-ischemic HF patients with different comorbidities, different age groups, and different socioeconomic states, and showed that social problems might not be representative of common concerns for most patients. This also occurred in MLHFQ such that eventually, only two factors of physical and emotional domains were found to be meaningful clusters in MLHFQ [22].

The construct validity and internal consistency of CHFQOLQ-20 indicated that this scale is a promising instrument for assessment of HRQoL in a target population. The first assessment of this new instrument indicated emerging evidence of its validity and reliability. The item-total correlation for the total scale was high, indicating that the items measured the desired concept, and none of them had the criteria for removal. With regard to concurrent validity, the correlation between the similar subscales of the CHFQOLQ-20 and SF-36 was high and significant. Also, the significant correlation of CHFQOLQ-20 with MacNew indicated optimal convergent validity.

Minimum, maximum, and mean subscale and total scores of CHFQOLQ-20 can be used as a guide in the clinical setting. These results may serve as a unique finding in the clinical setting. Nonetheless, further evaluation of CHFQOLQ-20 is necessary. By offering the norms for each subscale of CHFQOLQ-20, the authors hope that clinicians can make correct decisions in favor of patients in well detectable areas (higher well-being versus lower well-being). For instance, clinicians can refer patients who acquire a low score in mental health domain to a psychologist for psychological counseling. Also, clinicians can optimally rehabilitate patients who have problems in physical functioning domain and acquire a low score in this domain by reenrollment in cardiopulmonary rehabilitation programs or assessment of comorbidities such as sleep apnea and improve their QoL as such. However, longitudinal studies are required to assess the responsiveness and significant clinical changes in the scores. Researchers are recommended to assess the responsiveness of CHFQOLQ-20 to determine its ability to detect significant clinical changes over time. With respect to the low frequency of the missing data, it may be stated that the new questionnaire is relevant and is not too burdensome or difficult to complete. This study did not find a clear pattern for the missing data, which indicates no emergence of systematic missing data.

Strengths And Limitations

One strength of this study was adoption of qualitative and quantitative approaches to develop the instrument based on the experiences of patients living with HF taking into account their cultural background. The participants in this study had different types of HF (ischemic and non-ischemic) and were from different socioeconomic background, which enhances comprehensive assessment of QoL of CHF patients. A rigorous methodology was another strength of this study, which included the COSMIN checklist and ICF. The CHFQOLQ-20 developed in this study showed excellent psychometric properties. This instrument had practical strengths. First of all, few missing values in this instrument indicated that it was comprehensible for patients. Also, its few items along with four unique subscales enable its application in clinical studies compared with other instruments. However, The first limitation of this instrument was that its responsiveness to detect clinical changes over time was not evaluated in this study. Another limitation was recruitment of patients by convenience sampling. Also, the information belonged to a limited geographical location. Thus, its generalizability to other geographical areas, cultures and races might be examined. Also, this study only evaluated patients presenting to HF clinics, and hospitalized patients were not enrolled. Recall bias was another limitation of this study, which might have affected the results since we asked the participants to recall the events of the past month.

The psychometric properties of the CHFQOLQ-20 were found to be excellent. Confirmation of validity and reliability of the CHFQOLQ-20 makes it a unique standard instrument for use in future studies on QoL of CHF patients. Longitudinal studies are required to assess the translatability, allocation of clinically meaningful scores, and responsiveness of CHFQOLQ-20.

HRQoL

Health-related quality of life

CHF

Chronic heart failure

CHFQOLQ-20

Chronic heart failure quality of life questionnaire 20

EFA

Exploratory factor analyses

CFA

Confirmatory factor analyses

NYHA

New York Heart Association

ICC

Intraclass correlation coefficient

QoL

Quality of life

Heart failure

SIP

Sickness impact profile

SF-36

36-item Short Form Health Survey

QLQ-SHF

Quality of Life Questionnaire in Severe Heart Failure

CHFQ

Chronic Heart Failure Questionnaire

LVDQ

Left Ventricular Disease Questionnaire

KCCQ

Kansas City Cardiomyopathy Questionnaire

MLHFQ

Minnesota Living With Heart Failure Questionnaire

CHAT

Chronic Heart Failure Assessment Tool

COSMIN

Consensus-based standards for the selection of health measurement instruments

WHO

World Health Organization

ICF

International Classification of Functioning, Disability and Health

CVI

Content validity index

CVR

Content validity ratio

GFIs

Goodness-of-fit indices

CFI

Comparative fit index

NFI

Normed fit index

GFI

Goodness-of-fit index

AGFI

Adjusted GFI

RMSEA

Root-mean-square error of approximation

TLI

Tucker Lewis index

IFI

Incremental Fit Index

Physical functioning

Body pain

Social functioning

Role-functioning

Mental health

Vitality, GH:General health

Role-functioning physical

ANOVA

One-way analysis of variance.

Ethics approval and consent to participate

The study was approved by the ethics committee of Gonabad University of Medical Sciences, Iran (IR.GMU.1395.18). The participants were assured that their information would remain confidential. Informed consent was obtained from all individual participants included in the study.

Consent for publication

Not applicable.

Availability of data and materials

All data presented in this paper are available from the corresponding authors on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was funded by Gonabad University of Medical Sciences, Iran (Grant Number A-10-1516-1).

Authors’ contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by AK, AM, and HH. The first draft of the manuscript was written by AK, AM, and HH and all authors commented on previous versions of the manuscript. HH and AM provided the final draft. All authors read and approved the final manuscript.

Acknowledgements

The authors thank the patients, the investigators and their teams who took part in this study.

Savarese G, Becher PM, Lund LH, Seferovic P, Rosano G, Coats AJ. Global burden of heart failure: a comprehensive and updated review of epidemiology. Cardiovascular Research. 2022:. https://doi.org/ 10.1093/cvr/cvac013.
Navidian A, Mobaraki H, Shakiba M. The effect of education through motivational interviewing compared with conventional education on self-care behaviors in heart failure patients with depression. Patient Education and Counseling. 2017;100(8):1499-504. https://doi.org/10.016/j.pec.2017.02.023.
Polikandrioti M, Panoutsopoulos G, Tsami A, Gerogianni G, Saroglou S, Thomai E, et al. Assessment of quality of life and anxiety in heart failure outpatients. Archives of Medical Science-Atherosclerotic Diseases. 2019;4(1):38-46.https://doi.org/10.5114/amsad.2019.84444
Moshki M, Khajavi A, Vakilian F, Minaee S, Hashemizadeh H. The content comparison of health-related quality of life measures in heart failure based on the international classification of functioning, disability, and health: a systematic review. Journal of cardiovascular and thoracic research. 2019;11(3):167.https://doi.org/ 10.15171/jcvtr.2019.29.
McMurray JJ, Stewart S. The burden of heart failure. European Heart Journal Supplements. 2002;4(suppl_D):D50-D8. https://doi.org/10.1016/S520-765X(02)90160-4.
Bullinger M, Quitmann J. Quality of life as patient-reported outcomes: principles of assessment. Dialogues in clinical neuroscience. 2022.https://doi.org/10.31887/DCNS.2014.16.2/mbullinger.
Moshki M, Hashemizadeh H, Khajavi A, Minaee S, Vakilian F. Content comparison of health-related quality of life measures in heart failure based on the international classification of functioning, disability, and health: A systematic review protocol. The Journal of Tehran University Heart Center. 2018;13(3):144.
Ojelabi AO, Graham Y, Haighton C, Ling J. A systematic review of the application of Wilson and Cleary health-related quality of life model in chronic diseases. Health and quality of life outcomes. 2017;15(1):1-15.https://doi.org/ 0.1186/s12955-017-0818-2.
Mene-Afejuku TO, Pernia M, Ibebuogu UN, Chaudhari S, Mushiyev S, Visco F, et al. Heart failure and cognitive impairment: clinical relevance and therapeutic considerations. Current Cardiology Reviews. 2019;15(4):291-303. https://doi.org/ 10.2174/1573403X15666190313112841.
Thornhill K, Lyons A, Nouwen A, Lip G. Experiences of living with congestive heart failure: a qualitative study. British journal of health psychology. 2008;13(1):155-75. https://doi.org/ 10.1348/135910706X170983.
Bosworth HB, Steinhauser K, Orr M, Lindquist J, Grambow S, Oddone E. Congestive heart failure patients’ perceptions of quality of life: the integration of physical and psychosocial factors. Aging & mental health. 2004;8(1):83-91. https://doi.org/ 10.1080/13607860310001613374.
Dunderdale K, Furze G, David RT, Beer SF, Miles JN. Health-related quality of life from the perspective of patients with chronic heart failure. British Journal of Cardiology. 2007;14(4):207-12.
Pattenden J, Roberts H, Lewin R. Living with heart failure; patient and carer perspectives. European Journal of Cardiovascular Nursing. 2007;6(4):273-9. https://doi.org/ 10.1016/j.ejcnurse.2007.01.097.
Garin O, Herdman M, Vilagut G, Ferrer M, Ribera A, Rajmil L, et al. Assessing health-related quality of life in patients with heart failure: a systematic, standardized comparison of available measures. Heart failure reviews. 2014;19(3):359-67. https://doi.org/ 10.1007/s10741-013-9394-7.
Falk S, Wahn A-K, Lidell E. Keeping the maintenance of daily life in spite of chronic heart failure. A qualitative study. European Journal of Cardiovascular Nursing. 2007;6(3):192-9. https://doi.org/ 10.1016/J.EJCNURSE.2006.09.002.
Gilson BS, Gilson JS, Bergner M, Bobbit R, Kressel S, Pollard WE, et al. The sickness impact profile. Development of an outcome measure of health care. American journal of public health. 1975;65(12):1304-10. https://doi.org/ 10.2105/ajph.65.12.1304.
Ware Jr JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36): I. Conceptual framework and item selection. Medical care. 1992:473-83.
WIKLUND I, Lindvall K, SWEDBERG K, ZUPKIS RV. Self‐assessment of quality of life in severe heart failure: an instrument for clinical use. Scandinavian journal of psychology. 1987;28(3):220-5.https://doi.org/10.1111/j.467-9450.1987.tb00758.x.
Guyatt GH, Nogradi S, Halcrow S, Singer J, Sullivan MJ, Fallen EL. Development and testing of a new measure of health status for clinical trials in heart failure. Journal of General Internal Medicine. 1989;4(2):101-7.https://doi.org/ 10.1007/BF02602348.
O'Leary C, Jones P. The left ventricular dysfunction questionnaire (LVD-36): reliability, validity, and responsiveness. Heart. 2000;83(6):634-40.https://doi.org/ 10.1136/heart.83.6.634.
Green CP, Porter CB, Bresnahan DR, Spertus JA. Development and evaluation of the Kansas City Cardiomyopathy Questionnaire: a new health status measure for heart failure. Journal of the American College of Cardiology. 2000;35(5):1245-55.https://doi.org/ 10.016/s0735-1097(00)00531-3.
Rector T. Patient's self-assessment of their congestive heart failure: II. Content, reli-ability and validity of a new measure-The Minnesota Living with Heart Failure Questionnaire. Heart failure. 1987;3:198.
Dunderdale K, Thompson DR, Beer SF, Furze G, Miles JN. Development and validation of a patient-centered health-related quality-of-life measure: the Chronic Heart Failure Assessment Tool. Journal of Cardiovascular Nursing. 2008;23(4):364-70. https://doi.org/ 10.1097/01.JCN.0000317439.82704.e8.
Heo S. Health-related quality of life in patients with heart failure: University of Kentucky; 2004.
Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Quality of life research. 2010;19(4):539-49.https://doi.org/ 10.1007/s11136-010-9606-8.
Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. COSMIN checklist manual. Amsterdam: University Medical Center. 2012.
Üstün TB, Chatterji S, Bickenbach J, Kostanjsek N, Schneider M. The International Classification of Functioning, Disability and Health: a new tool for understanding disability and health. Disability and rehabilitation. 2003;25(11-12):565-71.https://doi.org/ 10.1080/0963828031000137063.
Moshki M, Khajavi A, Minaee S, Vakilian F, Hashemizadeh H. Perceived benefits of the disease: A qualitative study of patients' experiences of heart failure. Nursing & Health Sciences. 2020;22(2):464-71.https://doi.org/10.1111/nhs.12682.
Moshki M, Khajavi A, Hashemizadeh H, Vakilian F, Minaee S, Martin SS. Dark or bright half of the moon: a qualitative study exploring the experience of Iranian heart failure patients regarding their quality of life. Open Access Macedonian Journal of Medical Sciences. 2019;7(5):824.https://doi.org/ 10.3889/oamjms.2019.189.
Zamanzadeh V, Ghahramanian A, Rassouli M, Abbaszadeh A, Alavi-Majd H, Nikanfar A-R. Design and implementation content validity study: development of an instrument for measuring patient-centered communication. Journal of caring sciences. 2015;4(2):165. https://doi.org/ 10.15171/jcs.2015.017.
Caraballo C, Desai NR, Mulder H, Alhanti B, Wilson FP, Fiuzat M, et al. Clinical implications of the New York heart association classification. Journal of the American Heart Association. 2019;8(23):e014240.https://doi.org/ 10.1161/JAHA.119..
Montazeri A, Goshtasebi A, Vahdaninia M, Gandek B. The Short Form Health Survey (SF-36): translation and validation study of the Iranian version. Quality of life research. 2005;14(3):875-82.https://doi.org/ 10.1007/s11136-004-1014-5.
Huber A, Oldridge N, Höfer S. International SF-36 reference values in patients with ischemic heart disease. Quality of Life Research. 2016;25(11):2787-98.https://doi.org/ 10.1007/s11136-016-1316-4.
Asadi-Lari M, Javadi HR, Melville M, Oldridge NB, Gray D. Adaptation of the MacNew quality of life questionnaire after myocardial infarction in an Iranian population. Health and quality of life outcomes. 2003;1(1):1-6.https://doi.org/ 10.1186/477-7525-1-23.
Höfer S, Schmid JP, Frick M, Benzer W, Laimer H, Oldridge N, et al. Psychometric properties of the MacNew heart disease health‐related quality of life instrument in patients with heart failure. Journal of evaluation in clinical practice. 2008;14(4):500-6.10.1111/j.365-2753.007.00905.x.
Hooper D, Coughlan J, Mullen MR. Structural equation modelling: Guidelines for determining model fit. Electronic journal of business research methods. 2008;6(1):pp53‑60-pp53‑60.
Hu Lt, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal. 1999;6(1):1-55.
Oldridge N, Höfer S, McGee H, Conroy R, Doyle F, Saner H, et al. The HeartQoL: Part II. Validation of a new core health-related quality of life questionnaire for patients with ischemic heart disease. European journal of preventive cardiology. 2014;21(1):98-106.https://doi.org/ 10.1177/2047487312450545.
Celano CM, Villegas AC, Albanese AM, Gaggin HK, Huffman JC. Depression and anxiety in heart failure: a review. Harvard review of psychiatry. 2018;26(4):175.https://doi.org/ 10.1097/HRP.0000000000000162.
Heo S, Lennie TA, Okoli C, Moser DK. Quality of life in patients with heart failure: ask the patients. Heart & Lung. 2009;38(2):100-8.10.1016/j.hrtlng.2008.04.002.

No competing interests reported.

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Chronic heart failure health-related quality of life questionnaire (CHFQOLQ-20): Development and psychometric properties

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Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Methods

Design

Item generation

Content validity

Psychometric evaluation: participants and data collection

Data analysis

Results

Item generation

Content validity

Psychometric evaluation

Exploratory factor analysis

Confirmatory factor analysis

Concurrent validity

Convergent validity

Known-groups comparison

Reliability

Discussion

Strengths And Limitations

Conclusion

Abbreviations

Declarations

References

Additional Declarations

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