Heart failure (HF) is a complex clinical syndrome associated with high mortality rates, frequent hospitalizations, and significant impact in terms of costs for health systems worldwide.1 Preventable causes, such as low adherence to treatment, have been described as factors precipitating HF decompensation, subsequent hospitalization, worsening prognosis, and increased mortality rate. Adherence to pharmacological treatment and to self-care activities is needed to prevent rehospitalization due to worsening HF.2–6
Self-care has been defined as a naturalistic decision-making process used to maintain physiological stability (maintenance) and to manage symptoms when they occur (management). Self-care activities in HF involve managing multiple medications, following suggested diet and fluid restrictions, engaging in daily exercise, monitoring symptoms and weight daily, managing changes in symptoms, and navigating the healthcare system.6
Evidence has shown that self-care is important to improving patient outcomes such as quality of life, visits to the emergency department, and hospital readmission rates due to HF.7–9 Despite the evident importance of self-care in improving patient outcomes, patients with HF do not consistently engage in self-care activities.10,11 This is attributable to physiological and psychological factors, such as high comorbid burden, impaired cognition, and depression.12 Living with and managing a complex chronic condition such as HF is hard work, and patients need support to perform self-care. Caregivers, especially family members, are well positioned to provide this needed support by virtue of their relationship and proximity to the patient.13 It is in this background that the understanding of factors contributing to self-care, as well as social support, are relevant to the planning and implementation of interventions that can improve this behavior for patients with HF, and which should be incorporated during their follow-up.14,15
Self-care requires certain cognitive skills. When these skills are not available, an informal caregiver, such as a family member, will often play an important role in providing the necessary care to maintain health and clinical stability.16,17 In recent years, there has been growing research interest in the involvement of family members and caregivers in the self-care process,11–16 and a situation-specific theory of caregiver contributions to HF self-care was published.18
These publications illustrate the importance of caregivers in the daily life of patients with HF.19–21 Their contributions in the context of HF consist of giving time, effort, and support to patients with HF who need to perform self-care.20–22 Caregivers help patients improve their lifestyle (eg, exercise), improve medication and diet adherence, and monitor and recognize their symptoms (eg, fatigue).11 In contributing to HF self-care, caregivers adapt their behaviors to the patient's ability to perform self-care. In some cases, caregivers only recommend or remind patients of self-care maintenance and management measures (eg, daily weight measurement, medications, taking an extra water pill).19 However, when patients are unable to practice self-care themselves, caregivers substitute for patients in all self-care processes.23 In addition, caregivers are also responsible for including patients in social activities while ensuring safety and emotional support.24
The important role of the caregiver in contributing to HF self-care has also been emphasized in a recent study showing that caregiver contributions to self-care maintenance reduced patient mortality.22
Although recent research11,21,22 demonstrated the beneficial effects of social support provided by HF caregivers, few studies using established tools have focused on interventions to improve caregiver contributions to HF self-care. One of the reasons may be that few psychometrically sound instruments are available to assess caregiver contributions within this context. Therefore, this contribution has not been directly measured, and the impact of interventions is difficult to determine because of the scarcity of valid, reliable instruments.13,23
Quinn et al modified a version of the Self-care of Heart Failure Index (version 4.0) (SCHFI) to evaluate whether caregivers could be used as a proxy to rate self-care of patients with HF. However, their study included only self-care management and self-care confidence scales.25,26 To fill this gap, Italian researchers developed the Caregiver Contribution to Self-Care of Heart Failure Index (CC-SCHFI), an instrument with 3 separate scales measuring caregiver contributions to self-care maintenance (ie, caregiver behaviors to maintain the stability of HF), caregiver contributions to self-care management (ie, caregiver behaviors adopted to respond to HF symptoms), and caregiver confidence (ie, caregiver self-efficacy in dealing with the contribution to HF self-care).23,26 The CC-SCHFI was demonstrated to have construct validity and internal consistency and test-retest reliability in the Italian population.23 Furthermore, the CC-SCHFI was used as a foundation to build the aforementioned theory of caregiver contributions to self-care. In this theory, caregiver contributions are used as a proxy of self-care in the dimensions of caregiver contributions to self-care maintenance, caregiver contributions to symptom monitoring and perception, and caregiver contributions to self-care management; all 3 dimensions are influenced by contributions at the caregiver, patient, and dyadic level, with caregiver confidence as mediator. In the CC-SCHFI, caregiver contributions to self-care maintenance and to symptom monitoring and perception are measured with the “caregiver contributions to self-care maintenance” scale; caregiver contributions to self-care management are measured with the “caregiver contributions to self-care management” scale; and, finally, caregiver confidence is measured with the “caregiver contributions to self-confidence” scale.18,23
Even though there is evidence to support the psychometric characteristics of the CC-SCHFI, so far, they have only been tested in 1 study.23 Considering the increasing importance of caregivers' contributions to self-care, it is essential that tested, validated instruments be available to assess this in countries other than Italy. For this reason, the aim of our study was to evaluate the psychometric properties of the CC-SCHFI in a sample of caregivers of patients with HF enrolled in the specialized HF clinic of a public university hospital in Brazil. Because we used confirmatory factor analysis for CC-SCHFI testing, according to the original study, we hypothesized that the caregiver contribution to self-care maintenance scale would include 4 factors: symptom monitoring (items 1 and 2), physical activity (items 4 and 7), medical treatment adherence (items 3, 5, 6, 8, and 10), and sodium intake control (items 6 and 9); the caregiver contribution to self-care management scale would include 2 factors: autonomous management (items 11, 12, 13, and 16) and provider-directed management (items 14 and 15); and the caregiver confidence in contributing to self-care scale would include 2 factors: advanced confidence (items 17, 21, and 22) and basic confidence (items 18, 19, and 20).
Design, Sample, and Procedures
This was a cross-sectional study carried out at a single specialized HF clinic of a public university hospital in Porto Alegre, the state capital of Rio Grande do Sul, Southern Brazil. We enrolled a convenience sample of adult caregivers of patients with HF. All had been designated by patients as their caregivers, had been engaged in caregiving tasks for at least 6 months with no payment, and were family members. The diagnosis of HF was based on international guidelines.27 We did not use a specific instrument to assess cognition; before consent, we merely assessed whether caregivers were oriented to person, time, and place. Caregivers with cognitive or communication impairments that could compromise their ability to complete the instruments and to understand the purpose of the study were excluded.
Data were collected between November 2015 and June 2016. The CC-SCHFI was administered by interview, in a private room, at the clinical research center of the study institution, on the days of patients' appointments at the HF clinic. The interviews lasted 20 minutes on average. All data were collected by the first author (CWA) and by a research assistant (DB) who was trained in the objectives of the study, the protocol, and application of the instruments.
A sample of 7 patients per item was needed to allow adequate inference in exploratory or confirmative factor analysis.28 As noted above, the CC-SCHFI was not intended to provide an overall measure of caregiver contribution to self-care; it was designed as an inventory with 3 separate scales measuring 3 different constructs. Self-care maintenance was the longest scale, with 10 items. Thus, a sample of 70 patients would have been adequate to address the main study objective (dimensionality and internal consistency); however, we enrolled 99 participants to support a more stable analysis.28,29
The CC-SCHFI is an adaptation of the SCHFI v 6.2, which is used to measure self-care in patients with HF. The CC-SCHFI is composed of 22 items divided across 3 scales: self-care maintenance, self-care management, and confidence in self-care.23,26
The caregiver contribution to self-care maintenance scale has 10 items that measure caregiver contributions to symptom monitoring and treatment adherence. In this section, caregivers are asked how often they recommend various behaviors (eg, weight monitoring, eating a low-salt diet, taking medications) to the patient or how often they do these activities themselves because the patient is not able to do them. Each of the 3 scales uses a 4-point Likert scale (never or rarely, sometimes, frequently, always, or daily).”23,26
The caregiver contribution to self-care management scale consists of 6 items that measure the caregiver's ability to recognize symptoms of HF decompensation when they occur, the implementation of treatment in response to these symptoms, and the ability to evaluate the treatments used. In the CC-SCHFI, caregivers are asked: “If the person you care for had trouble breathing or ankle swelling in the past month, how quickly did you recognize it as a symptom of heart failure?” and “If the person you take care of has trouble breathing or ankle swelling, how likely are you recommend (or do) one of these remedies?” Choices include reduce salt intake, reduce fluid intake, take an extra water pill, and call the nurse or doctor for guidance. Responses to each item range from “not likely” to “very likely.”23,26
The caregiver confidence in contributing to self-care scale uses 6 items to evaluate caregivers' confidence in their skills in helping patients to engage in each phase of the self-care process. For instance, caregivers are asked: “In reference to the person you take care of, in general, how confident are you that you can recognize changes in the patient's health when they occur or prevent HF symptoms.” Responses to each item range from “not confident” to “extremely confident.”23,26
Each CC-SCHFI item is scored on a 4-point Likert scale. The total standardized score ranges from 0 to 100, with higher scores indicating higher contribution to self-care. Although the instrument was developed by Italian researchers, we used the English version (developed by the original authors of the instrument) for the present validation study. This version was translated from English into Portuguese by 2 independent translators, who were fluent in the original language (English) and in the language into which the instrument was being translated (Portuguese). Then, the instrument was back-translated from English into Portuguese by 2 translators who were United States–born native speakers of English and fluent in the Portuguese language. The translators were not familiar with the original English version. This back translation was shared with the original authors of the instrument, and minimal changes were suggested by email. No cultural adaptation was necessary during translations. After this process, a pilot test of the final version was conducted in 10 caregivers, and no modifications were found to be required. We also used a sociodemographic questionnaire, developed by the research team, to collect variables such as caregiver gender, age, marital status, and educational attainment.
The study was approved by the relevant institutional review boards. All research participants provided written informed consent. The investigation conforms with the principles outlined in the Declaration of Helsinki.
Continuous variables such as age were described as mean and standard deviation if normally distributed and as median and interquartile range otherwise. Categorical variables such as gender, occupation, and relationship with the patient were described as absolute and relative frequencies. The Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett test of sphericity were used to assess data factorability. The univariate distribution of the items of the CC-SCHFI scale was evaluated with both skewness and kurtosis indices.30 We tested the factor validity of the CC-SCHFI through confirmatory factor analysis for each separate CC-SCHFI scale. On confirmatory factor analysis, we tested the same model developed in the original Italian study.23 Specifically, the caregiver contribution to self-care maintenance scale was tested with 4 factors: symptom monitoring (items 1 and 2), physical activity (items 4 and 7), medical treatment adherence (items 3, 5, 6, 8 and 10), and sodium intake control (items 6 and 9). Also, these 4 factors were specified with a second-order factor.
The caregiver contribution to self-care management scale was tested with 2 factors: autonomous management (items 11, 12, 13, and 16) and provider-directed management (items 14 and 15). The caregiver confidence in contributing to self-care scale was also tested with 2 factors: advanced confidence (items 17, 21, and 22) and basic confidence (items 18, 19, and 20). As items were nonnormally distributed, we used the Maximum Likelihood Robust estimator, a method of parameter estimation with robust standard errors. Factor loadings of |0.30| or greater were considered adequate.31,32
To examine the adequacy of the tested model, a multifaceted approach was adopted and the following fit indices and criteria were evaluated33,34: the comparative fit index, Tucker and Lewis index, root-mean-square error of approximation, and standardized root-mean-square residual.35–37 The comparative fit index and Tucker and Lewis index were used to compare the model of interest with a null model,38 where values in the range of 0.90 to 0.95 indicate acceptable fit and values 0.95 or higher indicate good fit.39 The rootmean-square error of approximation was used to evaluate lack of model fit, where values 0.05 or lower indicate a well-fitting model, values between 0.05 and 0.08 indicate moderate fit, and values 0.10 or higher indicate poor fit.40 The standardized root-mean-square residual was used to measure fit in the sample, with values 0.08 or lower indicative of good fit.
The internal consistency reliability of the CC-SCHFI was assessed with the factor score determinacy coefficient.41 Because the CC-SCHFI is multidimensional, we also tested its reliability with the composite reliability coefficient42 and the model-based internal consistency coefficient.43 To accommodate missing data, the full information maximum likelihood approach was used in Mplus.44 A P value of ≤.05 was considered statistically significant for all analyses, which were carried out in Mplus version 8.1 (Muthén and Muthén, Los Angeles, California) and IBM SPSS version 21 (IBM Corp, Armonk, New York).
The sample was composed of 99 caregivers of patients with HF. Most caregivers were women (73%), with a mean age of 48 ± 14 years; 57% were spouses, 82% lived with the patient, and about half were actively working (Table 1).
Item Descriptive Analysis
Table 2 shows descriptive statistics for the individual items of the CC-SCHFI. The highest-scoring items in the caregiver contribution maintenance scale were “try to avoid getting sick,” “keep doctor or nurse appointments,” and “eat a low-salt diet.” Items related to “daily weighing” and “exercising for 30 minutes” scored lowest. On the caregiver contribution to self-care management scale, the item that scored highest was “call your doctor or nurse for guidance,” whereas “take an extra water pill” scored lowest. On the caregiver confidence in contributing to self-care scale, the highest-scoring items were “follow treatment advice,” “evaluate the importance of HF symptoms,” and “recognize health changes in the person you care for.” The lowest-scoring items were “do something that relieves HF symptoms” and “evaluate how well a remedy works”
The Bartlett test of sphericity was significant (P < .0001), and the Kaiser-Meyer-Olkin index of sampling adequacy was 0.743. Based on these results, the data were deemed suitable for factor analysis.
Confirmatory Factor Analysis
Caregiver Contribution to Self-care Maintenance Scale
We hypothesized that this scale would have 4 dimensions: symptom monitoring, physical activity, medical treatment adherence, and sodium intake control, with the second-order factor. Testing this factor structure yielded the following supportive fit indices: χ233 (n = 99) = 43.583, P = .103, comparative fit index = 0.95, Tucker and Lewis index = 0.93, rootmean-square error of approximation = 0.057 (90% confidence interval, 0.000–0.099), P = .376, and standardized root-mean-square residual = 0.062. All factor loadings were greater than 0.30 and significant. Figure 1 shows a graphical representation of the hierarchical model, including estimates from the Mplus output (completely standardized solution).
This final model indicated that the 4 primary factors of symptom monitoring, physical activity, medical treatment adherence, and sodium intake control loaded on a second-order factor of caregiver contribution to self-care maintenance. In the model shown in Figure 1, factor loadings for the 10 items are shown as loading onto 4 primary factors that, in turn, loaded onto a second-order factor. As can be seen from Figure 1, factor loadings were generally medium to high, thus attesting to a substantial proportion of common variance among the items.
Caregiver Contribution to Self-care Management Scale
We hypothesized that the caregiver contribution to self-care management scale would have the dimensions of autonomous management and provider-directed management, as in the original study. However, this model was not identified because the 2 dimensions were highly correlated. Thus, we specified a model with a 1-factor solution that yielded a supportive fit: χ29 (n = 79) = 8.483, P = .49, comparative fit index = 1.00, Tucker and Lewis index = 1.05, rootmean-square error of approximation = 0.000 (90% confidence interval, 0.000–0.122), P = .63, standardized root-mean-square residual = 0.065 (Figure 2). All factor loadings were significant and greater than 0.30. This final solution indicated that the 6 scale items were able to capture, in a single factor, the variance of caregiver contribution to self-care management behaviors.
Caregiver Confidence in Contribution to Self-care Scale
We hypothesized that the caregiver confidence in contribution to self-care scale would comprise the 2 first-order factors of basic confidence and advanced confidence and a second-order factor. The confirmatory factor analysis confirmed our hypothesis, yielding the following supportive fit indices: χ28 (n = 99) = 8.844, P = .356, comparative fit index = 0.994, Tucker and Lewis index = 0.990, rootmean-square error of approximation = 0.033 (90% confidence interval = 0.000–0.125), P = .531, standardized root-mean-square residual = 0.056. All factor loadings were significant at >0.30. Figure 3 shows a graphical representation of the hierarchical model including estimates from the Mplus output (completely standardized solution).
This final model indicated that the 2 primary factors of advanced confidence and basic confidence loaded on a second-order factor of caregiver confidence in contribution to self-care. In the model shown in Figure 3, factor loadings for the 6 items are shown as loading onto 2 primary factors that, in turn, loaded onto a second-order factor. As can be seen from Figure 3, factor loadings were generally medium to high.
Internal Consistency Reliability
The internal consistency reliability of the caregiver contribution to self-care maintenance scale, tested with factor score determinacy coefficients, was 0.77, 0.94, 0.89, and 0.96 for the factors symptom monitoring, physical activity, medical treatment adherence, and sodium intake control, respectively. The factor score determinacy of the second-order factor was 0.83. Because this is a multidimensional scale, we also computed composite reliability and model-based internal consistency reliability, with 0.89 for both tests.
The internal consistency of the caregiver contribution to self-care management scale was determined with the factor score determinacy coefficient to be 0.81.
Finally, the internal consistency of basic confidence and advanced confidence of the caregiver confidence scale had a factor score determinacy coefficient of 0.93 for both factors. We reliability of the second-order factor was 0.92. Because this scale is multidimensional, as is the caregiver contribution to self-care maintenance scale, we computed the composite reliability and the model-based internal consistency, which were 0.89 and 0.85, respectively.
In this study, we tested the psychometric properties of the CC-SCHFI. To our knowledge, ours was only the second such test of this instrument. Our results show that the CC-SCHFI is a valid and reliable instrument to measure caregiver contributions to self-care in the Brazilian population, providing further evidence of its reliability and validity.
Instrument dimensionality was analyzed with 3 separate confirmatory factor analysis, in which we hypothesized and tested the same factor structure of the original study.23,26 Our hypotheses were confirmed for the caregiver contribution to self-care maintenance and caregiver confidence scales, but not for the caregiver contribution to self-care management scale, which was found to be unidimensional. Interestingly, item 10 (Use a system to help him or her to remember to take medicines), measuring the extent to which caregivers advise patients to use a system to remind them to take their medicines, loaded poorly in the Italian sample (0.27) but fairly in this study (0.41). This could suggest that using such a system is more common for Brazilians than for Italians. This difference could also be explained by the fact that, in our sample, most caregivers worked outside the home and thus use a pillbox to help patients remember to take their medications. Furthermore, 50% of patients had fewer than 8 years of formal education, so they may not routinely read medication labels. These findings are similar to those of a previous study that evaluated self-care in patients with HF in Brazil.45 In the self-care maintenance scale of the revised version of SCHFI v. 7.2, this item had a strong factor loading (0.48).46
Interestingly, the hypothesis that the self-care management scale was bidimensional was not supported by confirmatory factor analysis. Initially, we hypothesized the scale would load on the autonomous and provider-directed factors, as in the original study, but confirmatory factor analysis supported a 1-dimensional model instead. This means that, when thinking of self-care management, Brazilian caregivers do not view behaviors that are initiated spontaneously (eg, reducing salt intake in case of symptoms) and behaviors that are recommended by providers (eg, taking an extra diuretic) as “2 separate things.” It seems that Brazilian caregivers see their contributions to self-care management as a whole. These differences between the Brazilian and Italian caregiver populations could be a result of different cultural orientations or could be influenced by differences in healthcare services between the 2 countries.
For caregiver confidence, we hypothesized and found a 2-factor structure similar to that of the original test (basic and advanced confidence). Basic confidence covers quite simple self-efficacy skills, such as following treatment advice. Advanced confidence involves more complex self-efficacy skills that require caregiver competence, such as preventing HF symptoms. It is also interesting to note that, despite the cultural differences exist between Brazilian and Italian caregivers, these 2 different levels of confidence—specifically, basic confidence and advanced confidence—were clearly distinguished in both.
As shown in the original study,23 we found that the CC-SCHFI has a complex structure, emphasizing how the construct of caregiver contribution to HF self-care is indeed complex, encompassing several distinct aspects related to self-care (such as monitoring the patient's condition, stimulating adherence to pharmacological and nonpharmacological treatments, being vigilant about signs and symptoms, and responding to signs and symptoms with different levels of confidence).
Furthermore, we demonstrated that the CC-SCHFI scales are reliable in measuring caregiver contributions to self-care maintenance, management, and confidence. We did not use Cronbach's α coefficient to estimate reliability because this test assumes scale unidimensionality and is influenced by the number of items.47 Instead, we used the factor score determinacy coefficient, the composite reliability coefficient,42 and the model-based internal consistency coefficient.43 The first test is not influenced by the number of items; the other 2 are used for multidimensional scales, as in the present case.
The CC-SCHFI is not the only instrument available to measure caregiver contributions to HF self-care. Buck and Harkness developed the Caregiver Contribution to Heart Failure Self-Care.13 The main difference between the 2 scales is that the Caregiver Contribution to Heart Failure Self-Care was designed from the caregiver perspective, whereas the CC-SCHFI is an adaptation of a patient-based instrument. Furthermore, whereas the CC-SCHFI was developed considering the evidence-based behaviors that international guidelines identified as improving HF outcomes, the Caregiver Contribution to Heart Failure Self-Care was developed through qualitative interviews asking caregivers how they contributed to self-care of patients with HF.13,23 We believe that both instruments allow a comprehensive evaluation of caregiver contributions in this setting. However, one of the advantages of the CC-SCHFI is that its scales (maintenance, management, confidence) can be applied separately and do not result in a single score. This allows more targeted interventions because it is possible to identify at which stage of self-care caregivers need the most additional support. Moreover, combined use of the CC-SCHFI and the Self-care of Heart Failure Index has allowed investigators to study self-care as a dyadic phenomenon.48,49
Studies examining caregiver contributions to HF self-care are still few and limited, making future research in this field particularly important to better understand the outcomes. Recently, Vellone et al18 developed a situation-specific theory of caregiver contributions to HF self-care, the propositions of which can serve as the basis for future studies. Further studies should also focus on evaluating measurement invariance between the Italian and Brazilian versions of the CC-SCHFI to provide deeper insight into its psychometric properties.
The main practical implication of this study is that the CC-SCHFI can be used in clinical practice to measure caregiver contributions to HF self-care. The instrument can be administered at a regular office appointment in only a few minutes and yields immediate results. This allows the healthcare provider to provide objective and immediate guidance to caregivers with the aim of improving their skills. The fact that self-care is a continuing process that should be constantly reevaluated makes the speed and ease of use of this instrument even more appealing. Future research may include studies that evaluate the care relationships between patients with HF and their caregivers; studies with actor-partner analyses are particularly worthy of consideration.
Several limitations of this study must be taken into account. First, the sample size was small, although sufficient for statistical analysis. Although the small sample could compromise the quality of model fit indices, the factor loadings were similar to those obtained in the Italian study. Therefore, we can infer that the factor structure remained the same as in the original study.23 Second, we enrolled a convenience sample, which inherently only includes people who were willing to participate in the study and may potentially be more involved in patient care; these characteristics may be significant limitations in a study of caregiver contributions. Third, even though this study demonstrates that the CC-SCHFI is stable in its factor structure, caution is warranted when generalizing our findings to other populations, owing to the single-center design of the study and the lower average age of the caregivers.
The Brazilian version of the CC-SCHFI showed good psychometric properties of validity and reliability and can be used to measure the contribution of caregivers to the self-care of patients with HF in this and similar healthcare contexts.
What's New and Important
- To our knowledge, this is only the second test of the Caregiver Contribution to Self-care of Heart Failure Index (CC-SCHFI).
- Our results show that the CC-SCHFI is a valid and reliable instrument to measure caregiver contribution to self-care also in other populations, which strengthens the evidence of reliability and validity of the CC-SCHFI.
- The CC-SCHFI has good psychometric characteristics of validity and reliability and can be used in clinical settings and research.
1. Ambrosy AP, Fonarow GC, Butler J, et al. The global health and economic burden of hospitalizations for heart failure
: lessons learned from hospitalized heart failure
registries. J Am Coll Cardiol
2. Wu JR, Lee KS, Dekker RD, et al. Prehospital delay, precipitants of admission, and length of stay in patients with exacerbation of heart failure
. Am J Crit Care
3. Ziaeian B, Fonarow GC. The prevention of hospital readmissions in heart failure
. Prog Cardiovasc Dis
4. Goyal P, Delgado D, Hummel SL, Dharmarajan K. Impact of exercise programs on hospital readmission following hospitalization for heart failure
: a systematic review. Curr Cardiovasc Risk Rep
5. Arrigo M, Gayat E, Parenica J, et al. Precipitating factors and 90-day outcome of acute heart failure
: a report from the intercontinental GREAT Registry. Eur J Heart Fail
6. Riegel B, Dickson VV, Faulkner KM. The situation-specific theory of heart failure self-care
: revised and updated. J Cardiovasc Nurs
7. Jonkman NH, Westland H, Groenwold RH, et al. Do self-management interventions work in patients with heart failure
? An individual patient data meta-analysis. Circulation
8. Mussi CM, Ruschel K, de Souza EN, et al. Home visit improves knowledge, self-care
and adhesion in heart failure
: randomized clinical trial HELEN-I. Rev Lat Am Enfermagem
. 2013;21(Spec No.):20–28.
9. de Souza EN, Rohde LE, Ruschel KB, et al. A nurse-based strategy reduces heart failure
morbidity in patients admitted for acute decompensated heart failure
in Brazil: the HELEN-II clinical trial. Eur J Heart Fail
10. Jaarsma T, Strömberg A, Ben Gal T, et al. Comparison of self-care
behaviors of heart failure
patients in 15 countries worldwide. Patient Educ Couns
11. Buck HG, Harkness K, Wion R, et al. Caregivers
' contributions to heart failure self-care
: a systematic review. Eur J Cardiovasc Nurs
12. Lee JK, Won MH, Son YJ. Combined influence of depression and physical frailty on cognitive impairment in patients with heart failure
. Int J Environ Res Public Health
13. Harkness K, Buck HG, Arthur H, et al. Caregiver Contribution to Heart Failure Self-care
(CACHS). Nurs Open
14. Cené CW, Haymore LB, Dolan-Soto D, et al. Self-care
confidence mediates the relationship between perceived social support and self-care
maintenance in adults with heart failure
. J Card Fail
15. Wu JR, Frazier SK, Rayens MK, Lennie TA, Chung ML, Moser DK. Medication adherence, social support, and event-free survival in patients with heart failure
. Health Psychol
16. Fivecoat HC, Sayers SL, Riegel B. Social support predicts self-care
confidence in patients with heart failure
. Eur J Cardiovasc Nurs
17. Riegel B, Lee CS, Dickson VV, Medscape. Self care in patients with chronic heart failure
. Nat Rev Cardiol
18. Vellone E, Riegel B, Alvaro R. A situation-specific theory of caregiver contributions to heart failure self-care
. J Cardiovasc Nurs
19. Vellone E, D'Agostino F, Buck HG, et al. The key role of caregiver confidence in the caregiver's contribution to self-care
in adults with heart failure
. Eur J Cardiovasc Nurs
20. Buck HG, Kitko L, Hupcey JE. Dyadic heart failure
care types: qualitative evidence for a novel typology. J Cardiovasc Nurs
21. Dunbar SB, Clark PC, Quinn C, Gary RA, Kaslow NJ. Family influences on heart failure self-care
and outcomes. J Cardiovasc Nurs
22. Bidwell JT, Vellone E, Lyons KS, et al. Caregiver determinants of patient clinical event risk in heart failure
. Eur J Cardiovasc Nurs
23. Vellone E, Riegel B, Cocchieri A, et al. Validity and reliability of the caregiver contribution to self-care
of heart failure
index. J Cardiovasc Nurs
24. Chen Y, Zou H, Zhang Y, Fang W, Fan X. Family caregiver contribution to self-care
of heart failure
: an application of the information-motivation-behavioral skills model. J Cardiovasc Nurs
25. Quinn C, Dunbar SB, Higgins M. Heart failure
symptom assessment and management: can caregivers
serve as proxy?J Cardiovasc Nurs
26. Riegel B, Lee CS, Dickson VV, Carlson B. An update on the self-care
of heart failure
index. J Cardiovasc Nurs
27. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure
: the Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure
of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure
Association (HFA) of the ESC. Eur Heart J
28. Terwee CB, Bot SD, de Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol
29. Terwee CB, Mokkink LB, Knol DL, et al. Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Qual Life Res
30. Muthén B, Kaplan D. A comparison of some methodologies for the factor analysis of non-normal Likert variables. Br J Math Stat Psychol
31. Comrey AL, Lee HB. A First Course in Factor Analysis
. Hove, England: Psychology Press; 2013.
32. Tabachnick BG, Fidell LS. Using Multivariate Statistics
. 5th ed. Boston, MA: Allyn & Bacon/Pearson Education; 2007.
33. Hu L, Bentler PM. Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol Methods
34. Tanaka JS. Multifaceted conceptions of fit in structural equation models. In: Bollen KA, Long JS, eds. Testing Structural Equation Models
. Newbury Park, CA: Sage Publications; 1993:136–162.
35. Byrne BM. Structural Equation Modeling With EQS: Basic Concepts Applications and Programming
. 2nd ed. Mahwah, NJ: Lawrence Erlbaum Associates Inc; 2006.
36. Meade AW, Johnson EC, Braddy PW. Power and sensitivity of alternative fit indices in tests of measurement invariance. J Appl Psychol
37. Vandenberg RJ, Lance CE. A review and synthesis of the measurement invariance literature: suggestions, practices and recommendations for organizational research. Organ Res Methods
38. Bentler PM. Comparative fit indexes in structural models. Psychol Bull
39. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling
40. Browne MW, Cudek R. Alternative ways of assessing model fit. In: Bollen KA, Long JS, eds. Testing Structural Equation Models
. Newbury Park, CA: Sage Publications; 1993:136–162.
41. Tabachnick BG, Fidell LS. Using Multivariate Statistics
. 6th ed. Boston, MA: Allyn & Bacon; 2013.
42. Fornell C, Larcker D. Evaluating structural equation models with unobservable variable and measurement error. J Market Res
43. Bentler PM. Alpha, dimension-free, and model-based internal consistency reliability. Psychometrika
44. Muthén LK, Muthén BO. Mplus User's Guide: Statistical Analysis With Latent Variables
. 7th ed. Los Angeles, CA: Muthén & Muthén; 1998–2012.
45. Avila CW, Riegel B, Pokorski SC, Camey S, Silveira LC, Rabelo-Silva ER. Cross-cultural adaptation and psychometric testing of the Brazilian version of the self-care
of heart failure
index version 6.2. Nurs Res Pract
46. Riegel B, Barbaranelli C, Carlson B, et al. Psychometric testing of the revised self-care
of heart failure
index. J Cardiovasc Nurs
47. Barbaranelli C, Lee CS, Vellone E, Riegel B. The problem with Cronbach's alpha: comment on Sijtsma and van der Ark (2015). Nurs Res
48. Vellone E, Chung ML, Alvaro R, Paturzo M, Dellafiore F. The influence of mutuality on self-care
in heart failure
patients and caregivers
: a dyadic analysis. J Fam Nurs
49. Lyons KS, Vellone E, Lee CS, et al. A dyadic approach to managing heart failure
with confidence. J Cardiovasc Nurs
. 2015;30(4 Suppl 1):S64–S71.