The rising prevalence and high costs of heart failure (HF) disease management are a serious public health issue. Heart failure cost the United States an estimated 39 million in 2010 largely because of the high rates of hospitalizations in this population.1 Heart failure is the most common discharge diagnosis for Medicare patients and the most frequent cause of readmission within 30 days.2 Poor self-care contributes to frequent hospital admissions3; thus, it is important to understand what factors contribute to better self-care. Cognitive impairment is associated with HF, with the prevalence ranging from 25% to 50%.4 When compared with patients without HF similar in age, HF patients have worse cognition in the areas of memory, psychomotor speed, and executive function.5 The cause of these impairments is likely related to inadequate cerebral perfusion or hypoxic brain injury.6 In addition, structural changes in the brain and grey matter loss can occur in HF, resulting in impairments in the cognitive domains of memory, attention, concentration, learning, executive function, and psychomotor speed.5,7
Cognitive impairments could limit a patient’s ability to acquire new knowledge and participate in self-care, resulting in more frequent hospital admissions; however, impairments often go unrecognized. A recent study by Cameron and colleagues8 found that mild cognitive impairment (MCI) was found in 73% of a sample of HF patients thought to be a group without impairment. Mild cognitive impairment is a syndrome defined as a decline in cognition beyond the normal variations expected for a person’s age and educational level.9 Patients with MCI are able to maintain general cognitive functions such that the impairment does not interfere notably with activities of daily living. The clinical criteria for diagnosing MCI includes identified impairment in 1 or more cognitive domains, but preserved independence with functional ability, and the absence of dementia.10 There is evidence that MCI could interfere with patients’ ability to carry out the steps needed to monitor and manage symptoms as part of a self-care regimen.8
Heart failure self-care is considered a naturalistic decision-making process composed of making lifestyle choices that will contribute to maintaining physiological stability (self-care maintenance), daily monitoring of symptoms for changes, and responding to symptoms when they occur (self-care management).11,12 Self-efficacy is also a component of self-care. The amount of confidence that a patient has in his/her ability to successfully carry out self-care behaviors is a key factor in achieving adequate self-care.13
The connection between cognitive function and HF self-care is not clear. Studies aimed at better understanding the impact of MCI on self-care and HF outcomes are limited and have mixed results. In a study by Riegel et al,14 poor cognitive function was associated with poor self-care behaviors. A later study found that cognitive function, measured using the Mini-Mental State Examination, was not a significant predictor of self-care when controlling for other factors.15 However, when this model was retested using the Montreal Cognitive Assessment (MoCA), a more sensitive tool for measuring MCI, cognitive impairment explained 9% of the variance in self-care management (P < .01).8 Mild cognitive impairment was found to predict a patient’s ability to carry out self-care management activities but did not predict self-care maintenance or confidence. This may be related to limitations in executive function, which would impair patients’ ability to recognize symptoms and make decisions related to symptom management.
Patients with cognitive impairments may be at greater risk for poor self-care and frequent hospitalizations. For their benefit, and to reduce the societal burden of HF, it is imperative that we better understand self-care in this subgroup of HF patients. The objective of this study was to determine the predictors of self-care in HF patients who screen positive for MCI. We hypothesized that HF knowledge, age, sex, race, education level, financial strain, depressive symptoms, social support, comorbid disease, disease severity, and experience managing HF could influence self-care in patients with MCI. We included ethnicity because racial differences in self-care have not been well studied.16 Depressive symptoms may diminish the patient’s ability to participate in self-care, but there is limited information on how depression may influence self-care in HF patients with MCI. Given the issues related to memory, attention, and executive function experienced by HF patients and the complexity of the HF self-care regimen, disease-specific knowledge, education level, and social support may be important factors in influencing self-care and healthcare utilization. Financial strain was included because adequate self-care can be dependent on the ability to obtain the necessary supplies and medications to monitor and manage symptoms.
Design, Setting, and Sample
We conducted a descriptive correlation study using baseline data collected for a longitudinal interventional study that tested the effect of a targeted self-care intervention designed for patients with MCI.17 Thus, for the purpose of the interventional study, we enrolled only patients who screened positive for MCI. Participants were recruited from a large, urban academic teaching hospital in the United States. Participants were screened for study eligibility by the HF case manager, an advanced practice nurse specialized in HF, between July 2010 and June 2011. The inclusion criteria for the initial screening were as follows: hospitalized for a primary diagnosis of HF as evidenced by the provider’s admitting diagnosis and history and physical examination, older than 21 years, and could be reached by telephone after discharge. Patients were excluded from the study based on the following criteria: unable to speak English; had Alzheimer’s disease, documented severe psychiatric or neurological conditions (ie, severe stroke, seizure disorder, Parkinson’s disease), or major hearing or vision loss; were at an end-of-life stage of care; expected to be discharged to a long-term care or rehabilitation facility rather than home; and weight greater than 350 lb, as this exceeded the weight limit for scales used in the intervention study. Patients who met the inclusion criteria were approached by research assistants and asked if they would be willing to take a cognitive screening test and potentially participate in the study. After signed consent was obtained, patients were screened for MCI. When patients scored within the threshold indicating signs of MCI on the screening measure, they were asked if they would like to participate in the study. When patients agreed, a second written consent to enter the study was obtained. Patients were interviewed as close to the discharge date as possible and once their clinical status had stabilized to minimize other factors that may contribute to cognitive difficulties.
Of the 288 eligible patients, 35% declined to participate. Informed consent for cognitive screening was obtained from 176 patients. Of those screened, 130 (74%) met the screening threshold for MCI and were asked to participate in the study. Five eligible patients declined to participate. Those excluded were 31 (18%) patients whose screening results indicated normal cognition and 15 (8%) whose screening results met the threshold for signs of dementia.
Demographics and clinical characteristics were collected from the medical record, and questionnaires measuring knowledge, self-care, social support, and depressive symptoms were administered verbally by research assistants to the patients while they were in the hospital. The data collection interviews required approximately 40 minutes to complete. The study was approved by the institutional review board.
The MoCA was used to screen for MCI as part of the inclusion criteria.18 This brief 10-minute screening tool was specifically designed to detect MCI. A lower education level is corrected with 1 point added for a person who has 12 years or fewer of formal education, for a possible maximum score of 30 points. Mild cognitive impairment is indicated if the score is less than 26, and dementia is indicated in scores less than 17. This is a screening measure and does not determine a diagnosis of MCI. Studies have shown that the MoCA had high sensitivity (90%) and specificity (87%) for detecting MCI in patients who performed in the normal range on the Mini-Mental State Examination.18
Self-care was measured by the Self-care of Heart Failure Index (SCHFI). This tool was developed to measure HF self-care and is composed of 22 items within 3 subscales to measure self-care maintenance, self-care management, and self-care self-confidence.11 Scores on each scale are standardized to a point range of 0 to 100, with scores of 70 or greater considered adequate self-care. The most recent psychometric testing of the SCHFI in a sample of 154 patients demonstrated adequate reliability coefficients for the self-care self-confidence subscale (α = .84) but lower for the self-care maintenance subscale (α = .54) and self-care management subscale (α = .59).13 Disease-specific knowledge was measured on the Dutch Heart Failure Knowledge Scale (DHFKS), a multiple-choice scale consisting of 15 items that assess general HF knowledge, knowledge related to HF symptom recognition, and management such as diet, fluid restriction, medication management, and importance of exercise.19 Scores range from 1 to 15, with high scores indicating greater knowledge. Construct and discriminant validity and reliability (α = .62) have been demonstrated.
The presence of depressive symptoms was measured on the 4-item version of the Geriatric Depression Scale, which is a basic screening measure for depression in older adults.20 Each of the 4 items is summed to give a total depression score. A score of 1 or greater is indicative of depressive symptoms, and construct validity has been tested (α = .80).20 The ENRICHD (Enhancing Recovery in Coronary Heart Disease) Social Support Inventory was used to assess the level of perceived social support. This is a 7-item measure that assesses social support developed for the ENRICHD study.21 The tool assesses 4 attributes of social support: emotional, instrumental, informational, and appraisal. Individual items are summed for a total score with a range of 11 to 34, with higher scores indicating greater social support. Internal consistency has been established (α = .88).21 The Charlson Comorbidity Index was used to quantify the extent of comorbid disease.22 The tool uses a weighted score according to relative risk of death. The summated scores are categorized into 4 levels based on the total score: 0, 1 to 2, 3 to 4, and 5 points or higher. The New York Heart Association (NYHA) classification was used to determine the degree of functional limitation caused by HF and as an indicator of disease severity.23
Descriptive statistics were computed on all study variables. Continuous data are presented as means and standard deviations, and categorical data are presented as percentages. Cronbach’s α was calculated for the SCHFI and the DHFKS to evaluate reliability of the measures in this sample. IBM SPSS (version 19 for Windows, Chicago, Illinois) was used for data analysis. The SCHFI subscale, DHFKS, and ENRICHD Social Support scores were calculated using established standards.13,19,24 Mean scores were calculated for each self-care subscale. Multiple regression analyses were performed on the 3 dimensions of self-care using predictor variables that were significant at the .10 significance level in the univariate analysis, as well as variables that have been found to be determinants of self-care in previous studies, using a forward selection process to identify which variables (age, sex, race, education, financial strain, comorbidity index, disease severity based on NYHA class, new diagnosis, social support, absence of depressive symptoms, and HF knowledge level) were predictors of self-care maintenance, management, and confidence scores. Dichotomized data were used for the following variables: sex, race (black, nonblack/other), education (<12 years of education, high school graduate), new HF diagnosis (<1 year since diagnosis, >1 year), and depressive symptoms. Multicollinearity was investigated for each regression model and the assumptions were not violated (variance inflation factor <1). A level of significance of α = .05 was used. The sample size calculations were based on 10 participants required for each predictor variable; thus, a sample of 125 patients would allow for up to 12 predictors.25
The 125 patients in this study were 53% men and 47% women (Table 1). Most were 50 years or older (75%) with an age range of 22 to 98 years (mean [SD], 59  years). The sample was predominately black and had 2 or 3 coexisting comorbidities, with most having an NYHA classification of II or III and over half the sample reporting depressive symptoms. One quarter of the sample was newly diagnosed with HF in the last year. Perceived social support was relatively high in this group (mean [SD], 28.73 [5.16]). The ENRICHD Social Support Inventory Cronbach’s α was adequate (.83) in this sample. Reliability for the DHFKS in this sample measured by Cronbach’s α was .39. This is much lower than the values reported by the scale authors with initial psychometric testing.19 Reliability was assessed for all 3 self-care subscales. Although measures of internal consistency were lower than desired on the self-care maintenance scale (α = .69) and self-care management scale (α = .65), both had Cronbach’s α scores higher than those reported most recently by the scale authors. The self-care confidence scale (α = .76) was slightly lower than published scores.
Heart Failure Knowledge
The mean (SD) HF knowledge scores (11.24 [1.84]) were above the level considered to be adequate (>10).26 Questions related to the etiology of HF, causes of rapid worsening of symptoms, how much exercise an individual should engage in, and what to do when thirsty were the most frequently missed questions.
In this sample, all but 4 patients reported symptoms of breathlessness or edema in the previous 30 days. Self-care scores were normally distributed, but overall scores in all 3 subscales were low (Table 2). Adequacy in self-care (defined as scores ≥70 on each subscale of the SCHFI) was evident in only 35% of the sample for self-care maintenance and only 33% had adequate self-care confidence scores. Surprisingly, patients seemed to score higher in self-care management, with 62% of the group having adequate self-care management scores.
Predictors of Self-care
Multiple linear regression was performed to determine the impact of a number of hypothesized predictors on self-care maintenance, management, and confidence scores in patients with MCI. The results from the multivariate analyses performed on each of the 3 SCHFI subscales are summarized in Table 3. Although not significant, sex was retained in each of the models because of the known gender differences in factors affecting HF, particularly in self-care maintenance.27–30 The significant variables included in the self-care maintenance model were HF knowledge, ethnicity, disease severity, and social support. When self-care maintenance was regressed on these variables, they explained 22% (P < .001) of the variance in self-care maintenance scores. Higher NYHA classification and greater HF knowledge were significant predictors of better self-care maintenance (NYHA: B = 7.55, P = .003; knowledge: B = 2.49, P = .005). Higher social support (P = .01) and ethnicity (P = .03) also contributed significantly to the model. Nonblacks, on average, scored 7.63 points higher in self-care maintenance than did blacks when controlling for the other variables.
In the final multiple linear regression model for self-care management, age, education level, and disease severity explained 19% of the variance in self-care management (P < .001). Again, higher NYHA classification made the largest contribution to better self-care management (B = 10.94, P < .001). Younger age was predictive of better self-care management (B = −0.33, P = .015), and those with a high school diploma, on average, scored 11.21 points higher in self-care management (P = .006) compared with those without. In terms of self-care confidence, only age and social support were significant variables, explaining 20% of the variance in self-care confidence scores (P < .001). Younger age (B = −0.45, P < .001) and higher social support (B = 0.78, P = .003) contributed to higher confidence levels.
To our knowledge, this is the first HF self-care study that included only patients who screened positive for MCI to determine predictors of HF self-care maintenance, management, and confidence. Our results indicate that predictors of self-care vary in terms of maintenance, management, and confidence. Furthermore, some of the predictors of self-care identified here in a sample of patients who screened positive for MCI differ from results in previous studies where patients were assumed to have normal cognition.31,32 These findings suggest that, perhaps, some factors associated with self-care may be unique to patients with MCI, and methods to improve self-care in this population may need to be tailored based on cognitive limitations.
There was a high prevalence of MCI in this sample (74%), which is higher than what has been found in other studies4,33; however this rate is consistent with studies that have used the MoCA to detect MCI.8,34 We chose the MoCA to screen for MCI because it has been shown to be more sensitive than other measures in successfully detecting MCI; hence, it is now recommended when screening for cognitive deficits that are likely vascular in nature.35,36 We used the standard threshold of less than 26 to indicate MCI, which may have contributed the high prevalence of MCI, as recent studies recommend lower thresholds in cardiovascular populations (<24) or in memory disorder clinic populations.37,38 Self-care scores in all 3 subscales were less than 70, indicating inadequate self-care. These scores are similar to those of cognitively impaired groups evaluated in other studies that measured self-care using the SCHFI in patients with and without impairment.8,14 In this sample, patients scored highest in self-care management. Conversely, Cameron et al8 found patients with cognitive impairment to have lower self-care management and self-care confidence, but no difference in self-care maintenance when compared with patients without impairment.
The regression models show the influence of both modifiable and nonmodifiable factors on the 3 domains of self-care. These predictive factors vary across the 3 domains of self-care perhaps because each domain differs in terms of skills and behaviors required. Screening for both MCI and these predictive factors could help identify patients who are more vulnerable to poor outcomes so that disease management strategies could be targeted to those at greatest risk for poor self-care and frequent hospitalizations.
Disease severity was a significant predictor of both self-care maintenance and self-care management but did not predict confidence. Those who were more symptomatic and functionally impaired from their HF appear to practice better self-care. Other studies aimed at identifying predictors of self-care have found similar results.8,32 Patients with more severe and potentially debilitating symptoms are likely to be more motivated to maintain and manage their symptoms for better quality of life; conversely, those with fewer limitations or less symptoms may not be as motivated to engage in self-care.39 It could also be that the patients with greater disease severity have had more experience managing their HF and thus have developed expertise with this complex process.40 This inverse relationship warrants further research, as it would seem that greater disease severity would coincide with lower levels of cerebral perfusion and subsequent hypoxia; thus, greater functional impairment would be expected.
Although time since HF diagnosis was not a significant predictor in any of our models, Cameron and colleagues41 found that patients with less experience with HF (<2 months) had lower self-care maintenance and management scores than experienced HF patients did. We defined “experience with HF” as greater than 1 year since HF diagnosis as opposed to greater than 2 months, which may explain why our results related to experience with HF and self-care behavior may differ from previous studies.
Rockwell et al32 found education level along with disease severity to be significant predictors of self-care management, consistent with our results. It may be that patients with lower levels of education may have more difficulty or require more time in learning the steps involved with self-care management. Heart failure knowledge was significant only in the self-care maintenance model. Adherence to the HF regimen is associated with higher knowledge levels (odds ratio, 5.67; confidence interval, 2.87–11.19).42 It is not clear how HF knowledge impacts self-care in patients with MCI. Cognitive function can strongly influence how learning occurs.7 Mild cognitive impairment could explain why some patients struggle with applying HF knowledge in their self-care practices. It is unclear why HF knowledge was not significant on the other subscales. In terms of confidence, it may be that when patients have more knowledge about what they need to do to manage their HF, they become overwhelmed and less confident that they will be successful.
The finding that younger age predicted self-care management and confidence but that age was not a significant predictor for self-care maintenance conflicts with other studies that found that older age was predictive of self-care maintenance.15,31 In a study that included patients with MCI, younger age was determined to be a predictor on the self-care confidence subscale, but not the other SCHFI subscales.8 In our sample, age ranged from 22 to 98 years. Other studies have set age limits for inclusion criteria. We did not set limits because we wanted to better understand MCI in all ages. Older patients may also have more severe cognitive impairments, which could have influenced their self-care scores. We used the MoCA for inclusion criteria purposes only and used a range of scores from 17 to 25 to determine MCI per the tool author guidelines18; therefore, the degree to which someone was impaired is not reflected or controlled for in these results.
Gender was not a significant predictor in any of the models. Previous studies have found that male gender is a significant predictor for self-care maintenance31 and management.15 Men are more likely to assume an active role in self-care and describe self-care as their responsibility; however, women have been shown to have higher self-care maintenance scores.43 Some factors may impact men and women differently. Lee and colleagues27 found small gender differences in self-care maintenance but determined that certain factors, such as comorbidities, influenced self-care only in men. Others have not detected gender differences in self-care behaviors.29,44,45 In this sample, gender differences varied across the subscales, where being male was predictive of higher self-care maintenance and confidence but not self-care management.
Race was a significant predictor of self-care maintenance. Previous studies investigating predictors of self-care have not included race. Black race has been associated with lower health literacy.46 Race has also been associated with lower confidence to self-manage cardiovascular disease.47 These racial differences could be related to less healthcare access or poorer quality of care for minorities. The Institute of Medicine reports that racial and ethnic minorities receive lower quality healthcare than nonminorities do even when controlling for access-related variables.48 Heart failure knowledge was also a significant predictor of self-care maintenance, and blacks had lower HF knowledge. In this sample, blacks scored significantly lower (P = .012) on the DHFKS (10.85 [1.9]) compared with nonblacks (11.83 [1.6]). Further research is needed to explain racial differences in HF knowledge and self-care in patients with MCI.
Family engagement is known to be the primary factor for those who have become expert at self-care.14 Higher perceived social support is associated with lower readmission rates49 and better self-care behaviors including improved medication and dietary adherence and daily weighing.50 In this study, higher perceived social support was a significant predictor of better self-care maintenance and higher confidence in self-care abilities. This is an important finding because social support has not been identified as a significant predictor of self-care by other investigators.15,31,32 It may be that social support is more critical to success with self-care maintenance and improving confidence in patients with MCI. Patients who have higher perceived social support may have improved self-care behaviors because of a higher degree of self-efficacy related to the caring relationships they experience with family and friends. Greater levels of social support did not predict self-care management in this study. This may be because self-care management is more of an independent activity and requires intrinsic action. Although family members or friends may provide support for self-care maintenance and boost confidence, the behaviors required for self-care management require more independence. Dickson and colleagues43 found that regardless of the support, patients who took a passive role and relied on others for direction and help in managing symptoms had poorer self-care.
Although our analysis resulted in the identification of significant predictors of self-care, there is still a large amount of variance unexplained for each dimension of self-care. Further research is needed to identify other factors that may explain self-care in a population of patients with MCI. For example, health literacy, which has been shown to be associated with self-care,51 may overlap with education level or HF knowledge in this study. Although health literacy was not measured in this study, it is an important factor that could affect HF knowledge and self-care. Further research is needed to explore its effect on self-care in this population.
This study was conducted in a predominately black sample, and the sample was relatively younger than other HF samples studied, which may limit the ability to generalize the findings. Furthermore, the study excluded patients who did not speak English, thus limiting the cultural diversity of the sample. We used the standard thresholds recommended by the MoCA developers, where a lower threshold for this population may have had better predictive value. In addition, we used the MoCA for screening purposes only, and we did not use any other functional or activity metrics to diagnose MCI. We enrolled only patients who screened positive for MCI; thus, we were unable to compare our results with non-MCI HF patients to evaluate how cognitive deficits may exacerbate self-care challenges and determine if the rate and quality of self-care deficits in our sample are beyond the rate expected in a non-MCI sample. The study relies heavily on self-reported measures, which could be an issue given that these patients have known cognitive deficits, particularly in memory, and the SCHFI is largely based on the patient recalling activities and behaviors over the last 30 days. In addition, data were collected while the patient was in the hospital experiencing an exacerbation of HF symptoms, which could have altered the way the patient answered the questions, particularly those related to confidence in self-care. The DHFKS may not be an adequate measure of HF knowledge in this sample. The evaluation of knowledge is difficult, and a multiple-choice test such as the DHFKS is a method to quantify knowledge but does not provide a deeper understanding of the level of knowledge or the ability to analyze, draw conclusions, or use knowledge in new situations.52 Despite these limitations, important predictors of self-care maintenance, management, and confidence have been identified in this group of patients who screened positive for MCI.
Our study adds to the evidence showing that patients who screen positive for MCI may have inadequate self-care behaviors despite having adequate HF knowledge. There are a number of variables that may explain the variance in self-care performance seen in HF patients who screen positive for MCI. Poor self-care has significant negative clinical and societal implications. Identification of MCI may be an important step in planning HF education and support strategies. Further research is needed to describe how MCI affects self-care and HF outcomes over time. Furthermore, interventions aimed at potentially mitigating the negative impact of MCI on the uptake of self-care skills need to be tested.
What’s New and Important
- There is a high prevalence of MCI in HF patients, and those who screen positive for MCI may be at greater risk of inadequate self-care.
- Black race and older age were predictive of lower self-care; higher social support, HF knowledge, and education predicted better self-care.
- Assessing cognition is an important step in planning HF disease management strategies, and methods to improve self-care should be tailored based on modifiable predictors of better self-care and cognitive limitations.
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