Multiple Comorbid Conditions Challenge Heart Failure Self-Care by Decreasing Self-Efficacy
Dickson, Victoria Vaughan; Buck, Harleah; Riegel, Barbara
Victoria Vaughan Dickson, PhD, RN, FAHA, is Assistant Professor, College of Nursing, New York University.
Harleah Buck, PhD, RN, CHPN, is Assistant Professor, School of Nursing, The Pennsylvania State University, University Park.
Barbara Riegel, DNSc, RN, FAHA, FAAN, is Professor, School of Nursing, University of Pennsylvania, Philadelphia.
Editor’s note: Materials documenting the review process for this article are posted at http://www.nursing-research-editor.com/authors/open.php.
Accepted for publication July 26, 2012.
This paper was accepted under the editorship of Dr. Molly C. Dougherty.
The authors have no conflicts of interest to disclose.
Corresponding author: Victoria Vaughan Dickson, PhD, RN, FAHA, College of Nursing, New York University, 726 Broadway, 10th Floor New York, NY 10003 (e-mail: firstname.lastname@example.org).
Background: Most heart failure patients have multiple comorbidities.
Objective: This study aims to test the moderating effect of comorbidity on the relationship between self-efficacy and self-care in adults with heart failure.
Methods: Secondary analysis of four mixed methods studies (n = 114) was done. Self-care and self-efficacy were measured using the Self-Care of Heart Failure Index. Comorbidity was measured with the Charlson Comorbidity Index. Parametric statistics were used to examine the relationships among self-efficacy, self-care, and the moderating influence of comorbidity. Qualitative data yielded themes about self-efficacy in self-care and explained the influence of comorbidity on self-care.
Results: Most (79%) reported two or more comorbidities. There was a significant relationship between self-care and the number of comorbidities (r = −.25; p = .03). There were significant differences in self-care by comorbidity level (self-care maintenance, F[1, 112], 5.96, p = .019, and self-care management, F[1, 72], 4.66, p = .034). Using moderator analysis of the effect of comorbidity on self-efficacy and self-care, a significant effect was found only in self-care maintenance among those who had moderate levels of comorbidity (b = .620, p = .022, Fchange df[6,48], 5.61, p = .022). In the qualitative data, self-efficacy emerged as an important variable influencing self-care by shaping how individuals prioritized and integrated multiple and often competing self-care instructions.
Discussion: Comorbidity influences the relationship between self-efficacy and self-care maintenance, but only when levels of comorbidity are moderately high. Methods of improving self-efficacy may improve self-care in those with multiple comorbidities.
As the number of patients with heart failure (HF) continues to climb, the clinical management of these individuals has become increasingly complex. This complexity is attributed, in part, to the changing profile of the patient with HF, who is likely to be an older adult, taking more medications, and reporting multiple comorbid conditions. According to a national survey, 58% of patients with HF report five or more comorbid conditions (Wong, Chaudry, Desai, & Krumholz, 2011). Each condition comes with a unique set of symptoms, self-care practices, and clinical management requirements. Despite clinical guidelines for HF management, the heterogeneity of patient trajectories in HF adds to the complexity of this problem for patients and clinicians alike. For patients, this complexity is likely to interfere with patients’ confidence in their abilities to perform self-care.
Patients generally manage HF with a combination of treatment adherence to advice about medication and diet and timely symptom management (Riegel, Lee, & Dickson, 2011). Self-efficacy is defined as the confidence that one has in the ability to perform a specific action (Bandura, 1986). Individuals with high levels of self-efficacy report better HF self-care than those with low self-efficacy (Heo, Moser, Lennie, Riegel, & Chung, 2008). The manner in which comorbidity influences self-efficacy in the setting of HF is unknown, however. The purpose of this secondary analysis of four mixed methods studies was to test the moderating effect of comorbid conditions on the relationship between self-efficacy and self-care in adults with HF.
Comorbidity in Heart Failure
Comorbidity is relatively common and associated with increased age (Braunstein et al., 2003). Diabetes, chronic obstructive pulmonary disease, hypertension, and anemia are reported in 20%–30% of the adult HF population (Dahlström, 2005) and may be even higher among hospitalized patients with HF (Chen, Normand, Wang, & Krumholz, 2011). When patients have combinations of various conditions, the result is multiple, competing stressors on an ill individual.
The study of comorbidity in the setting of HF has gained significant recent interest (U.S. Department of Health and Human Services, 2010), probably because comorbidity is associated with increased mortality and healthcare costs in the HF population (Ekundayo et al., 2009). In a recent study examining 3-year mortality among newly diagnosed HF patients, extensive comorbidity, defined as a Charlson Comorbidity Index raw score of greater than 4, was associated with greater mortality risk (Oudejans, Mosterd, Zuithoff, & Hoes, 2012). Chen et al. (2011) analyzed trends in HF hospitalization rates and found that several specific comorbid conditions were reported more commonly over time, including hypertension (47.9%–60.9%, p < .001) and renal failure (8.0%–20.0%, p < .001). In addition, over the past two decades, the mean number of prescription medications for patients with HF has increased from 4.1 to 6.4 prescriptions (Wong et al., 2011).
Heart failure self-care, which is the cornerstone of patient management, is a two-phase process of vigilance and action in response to changes in condition. Self-care maintenance involves adhering to the plan of care and routine monitoring. Self-care management involves deciding to (and how to) respond to changes in HF signs and symptoms when they occur (Riegel et al., 2004; Figure 1). Persons with HF are expected to monitor their weight, maintain a low sodium diet, exercise, follow strict medication regimens, receive routine immunizations, and make regular clinic visits (Riegel, Moser, et al., 2009). An individual’s self-efficacy or confidence in the ability to perform HF self-care maintenance and management behaviors has been shown to influence both the self-care maintenance and management behaviors (Riegel & Dickson, 2008). However, the manner in which comorbidity influences the relationship between self-efficacy and HF self-care has not been explored. For this study, the manner in which comorbidity was hypothesized to influence the relationship between self-efficacy and self-care is illustrated in Figure 2.
Managing multiple diseases is a complex process for the clinician, and this process is further complicated by the current environment of specialization (Goodlin, 2005). If clinicians struggle, it is easy to appreciate that managing these diseases at home is even more complicated for the patient who needs to determine which disease is causing the symptom and then which self-care practice to use to address it. In our prior study, we found that individuals prioritize the self-care for one chronic illness over another, with both illness experience and perceived threat contributing to their decisions. In addition, integrating multiple self-care instructions led to skill deficits as well as decreased perception of being prepared to perform self-care (Dickson, Buck, & Riegel, 2011).
In this study, comorbidity was examined as a moderator of the relationship between self-efficacy and HF self-care in a sample of adults with HF. It was hypothesized that the presence of multiple comorbid conditions would attenuate the relationship between self-efficacy in self-care, resulting in poorer self-care. The qualitative data were examined to explain how self-efficacy influences HF self-care in HF patients with multiple comorbid conditions.
This study was a secondary analysis of quantitative and qualitative data collected on 114 patients with HF. Data included in this analysis were collected during four mixed methods studies conducted between 2007 and 2010.
The studies included diverse HF populations living in the United States and Australia. Individuals were eligible for participation if they had documented evidence of symptomatic (Stage C) HF for at least 3 months and could speak and read English. Exclusion criteria for each study included diagnosed dementia, a history of a prior neurological event that could cause dementia, or inability to perform tests (e.g., major visual or hearing impairment). Three of the samples (n = 85) were recruited from the outpatient settings associated with a large urban medical center in the United States (Dickson, Deatrick, & Riegel, 2008; Riegel et al., 2006; Riegel, Vaughan Dickson, Goldberg, & Deatrick, 2007). One sample (n = 29) was recruited from outpatient sites in Melbourne, Australia (Riegel, Dickson, Kuhn, Page, & Worrall-Carter, 2010). Appropriate IRB approvals were obtained for each of the studies. All participants gave informed consent.
Overview of Design
In this current mixed methods study, analysis of the quantitative data set was assigned as the priority and the qualitative data were used to explain and enhance the quantitative findings (Creswell, Clark, Gutmann, & Hanson, 2003). Parametric statistics were used to examine relationships among self-efficacy, self-care, and comorbidity. Moderator analysis methods were used to examine the effect of comorbidity on the relationship between self-efficacy and self-care. Qualitative meta-analytic methods were used (Noblit & Hare, 1988) to reanalyze the in-depth accounts of HF self-care and explore emergent themes about self-efficacy within the context of comorbid conditions. In the final analysis and interpretation stage, the data were integrated and the qualitative data were used to explain the quantitative findings.
Quantitative Data and Analysis
In each of the four studies, HF self-care was measured using the Self-Care of Heart Failure Index (SCHFI V4; Riegel et al., 2004), a validated instrument with 17 items measured on a 4-point Likert scale. These items form three scales: self-care maintenance (adherence and symptom monitoring behaviors done to maintain physiologic stability and prevent HF exacerbation), self-care management (ability to recognize and respond appropriately to symptoms), and self-care confidence (self-efficacy in self-care or perceived ability to perform the specific task of self-care). Scores on each of the SCHFI scales are standardized to 100; higher scores indicate better self-care. The self-care management scale is scored only in individuals who report symptoms. In this sample, the maintenance scale had a Cronbach’s alpha of .55, management of .65, and confidence of .86, consistent with prior research (Riegel, Lee, Dickson, & Carlson, 2009). Adequate self-care was achieved if the participant obtained a score of ≥70 on each of the SCHFI scales (Riegel, Moser, et al., 2009).
The interview format of the Charlson Comorbidity Index (CCI) was used to gather data about comorbid conditions (Charlson, Pompei, Ales, & MacKenzie, 1987). Participants were asked about preexisting diseases (e.g., diabetes), most of which are scored with 1 point, although some (e.g., cirrhosis) are assigned >1 point. Scores on the CCI can range from 0 to 34, with each study participant having a score ≥1 because of their HF. Responses were summed, weighted, and indexed into one of three categories: 0–1 = low, 2–3 = moderate, and ≥4 = high, according to the published method (Peterson, Paget, Lachs, Reid, & Charelson, 2012). The ability of the CCI to predict mortality, complications, acute care resource use, length of hospital stay, discharge disposition, and cost (Charlson et al., 1987) provide evidence for the criterion-related validity.
Quantitative data were analyzed using SPSS (version 18.0). Standard descriptive statistics of central tendency and dispersion were used to describe the sample. Preliminary analyses were conducted to ensure no violation of the assumptions of normality, linearity, multicollinearity, and homoscedasticity. Tolerance and variance inflation factor values confirmed that multicollinearity was within acceptable limits (Miles, 2005). Relationships between self-efficacy and self-care were analyzed using correlational methods. ANOVA with planned comparisons by comorbidity category was used to compare the groups for differences in self-care maintenance, management, and self-efficacy by comorbidity category.
Following the steps outlined by Baron and Kenny (1986) for tests of moderation, hierarchical regression analysis were performed to test whether comorbidity moderated the relation between self-efficacy and self-care maintenance and management. In the first step, demographic variables (i.e., gender and age) known to be important to the self-care (Lee et al., 2009), country in which the study was conducted, comorbidity, and self-efficacy were entered to control for the variance associated with each of them. In the second step, the interaction between self-efficacy and comorbidity total was added (Bennett, 2000). The model was repeated for self-care management. Then subgroup analyses by comorbidity category (low, moderate, and high) were used to examine the moderation effects of levels of comorbidity on the relation between self-efficacy and self-care maintenance and then self-care management. Post hoc effect sizes were calculated using Cohen’s f 2 (Cohen, 1992).
Qualitative Data Collection and Analysis
Descriptive meta-analysis is a qualitative technique used to reexamine primary qualitative research and ultimately draw upon a richer data set to answer a new research question (McCormick, Rodney, & Varcoe, 2003). Specifically, the qualitative research question was: How does self-efficacy influence HF self-care among a sample of patients with multiple comorbid conditions? In each of the four primary studies, a qualitative descriptive design was used in which the qualitative interview started with two open-ended questions (“Tell me about your heart failure” and “What do you do on a daily basis to take care of your heart failure?”) that yielded in-depth accounts of self-care. To gain insight into how self-care was practiced, a series of open-ended questions were asked about barriers and facilitators to self-care, and confidence was determined by asking, “How confident are you….” In two of the studies, targeted questions about self-efficacy (“How do you feel about your ability to….”) were included. The qualitative data from these four studies yielded a rich description (more than 2,500 pages of double-spaced transcription) of self-care practices and insightful narratives about self-efficacy.
Following the qualitative meta-analytic steps described by Noblit and Hare (1988), individual study findings of the four studies were reexamined at the level of codes, focusing on the categories and themes related to self-care and self-efficacy described by each individual and narratives about a comorbid condition. Next, common themes about self-efficacy in self-care were examined across the four studies. This within-study and across-study analysis was an iterative process involving a reanalysis of original raw data using content thematic analysis and reinterpretation of previous findings to answer additional questions about self-efficacy in self-care within the presence of a comorbid condition.
Integrated Data Analysis
The final analysis phase involved integrating the quantitative and qualitative data using triangulation methods (Creswell et al., 2003). In each of the original four studies, congruence between the quantitative scores of SCHFI and qualitative accounts of self-care was examined; the percentage of concordance of cases where adequate score on the SCHFI self-care maintenance, management, and confidence scales (≥70) matched qualitative accounts of self-care maintenance, self-care management, and self-efficacy, respectively. Then, an informational matrix (Dickson, Lee, & Riegel, 2011) was created from the four study results to organize and analyze the relationships between qualitative accounts of self-efficacy and self-care within the context of comorbid conditions across all the cases. This method allowed exploration of similarities and differences in qualitative themes (e.g., number of comorbid conditions) regarding self-efficacy across cases.
Methodological rigor of the qualitative data and integrated data analyses was maintained using an audit trail and periodic debriefing with the coinvestigators who are experts in HF self-care and issues of comorbidity among older adults. Reliability was measured via consistency of interpretation and coding of the qualitative data (Byrne, 2001). As is typical of a qualitative analysis, an audit trail of process and analytic memos and coding books was maintained, which support the credibility of the results.
The sample was 71% Caucasian and 62% male and had a mean age of 59 years (SD = 15). Eighty percent of the sample reported at least 2 chronic conditions (M = 3.06, SD = 1.8). The most common comorbid condition was a history of myocardial infarction (52%), followed by diabetes, reported by 36% of the sample (Table 1).
On average, self-care was adequate in the sample (standardized mean SCHFI maintenance = 73.30, SD = 14.03; SCHFI management = 69.89, SD = 19.16; SCHFI confidence = 71.15, SD = 15.14). Two thirds of the sample (n = 74) reported evaluable symptoms of shortness of breath or ankle edema; 60% of those 74 individuals reported adequate self-care management, defined as a score of ≥70. Comparatively, 64% of these 74 reported adequate self-care maintenance and 50% reported adequate self-care confidence. Higher age was associated significantly with lower self-care confidence (r = −.305, p < .01) and poorer self-care management (r = −.326, p < .01).
There was a significant correlation between self-care maintenance and the number of comorbid conditions (r = −.253; p = .03), with the association of self-care management and number of comorbid conditions trending toward significance (r = −.223, p = .057). When the CCI comorbidity data were analyzed by category, there was a statistically significant difference between the self-care maintenance scores in the low comorbidity group and those in the moderate and high comorbidity categories (F =5.96, df[1, 112], p = .019). Among the 74 individuals who reported self-care management of symptoms, those with two or more conditions (moderate or high comorbidity category) scored significantly lower in self-care maintenance (F = 4.66, df[1, 72], p = .034). However, there was no significant difference in self-care confidence based on the total number of comorbid conditions or comorbidity category.
In the first moderation model examining the moderating effect of comorbidity on the relationship between self-efficacy and self-care maintenance, after controlling for study group (country), age, gender, and comorbidity, self-efficacy was associated with self-care maintenance (unstandardized b = .284, p = .002). However, the number of comorbid conditions was not associated significantly with self-care maintenance (unstandardized b = 1.127, p = .125) and the interaction term was not significant (Table 2). This analysis was then repeated with self-care management as the dependent variable (Table 2). Once again, in this model, although self-efficacy was significant, no moderator effect was found.
However, in the subgroup analysis of the moderating effect of comorbidity on the relationship of self-efficacy and self-care maintenance, there was a significant moderation effect in the moderate comorbidity category (Table 3). The interaction term entered in the second step significantly predicted self-care maintenance (b = .620, p = .022, Fchange = 5.61, df[6,48], p = .022) in the moderate (two to three conditions) comorbidity category. These results suggest that the relationship between self-efficacy and self-care maintenance is moderated by comorbidity, but only when patients have a moderate or intermediate level of comorbid illness. Post hoc effect size was calculated to be Cohen’s f2 of .12, indicating a small to moderate effect of comorbidity on the relationships (Cohen, 1992). There were not any significant moderation effects in the subgroup analysis of self-care management.
The narrative accounts revealed that the most challenging self-care practices among those with a moderate level of comorbidity were maintaining a low salt diet, monitoring of symptoms, and differentiating the source of symptoms (HF vs. other conditions). These challenges were cited more commonly by older adults (age, >65 years). Specifically, individuals described an inability to manage multiple diets (“There’s more that I can’t eat than I can”). Many also described HF symptoms that they attributed to other conditions (“…I think the breathing is the asthma…”). Interestingly, when asked about daily weight as a tactic to monitor symptoms for HF, those with diabetes more often reflected the misconception that weighing was for the purpose of weight management rather than monitoring fluid retention. As one obese 70-year-old woman with type II diabetes explained, “I know losing weight is good for controlling my diabetes…but I learned not to look at that scale every day in my [weight loss] class…so once a week that is IT!”
The overarching theme that emerged from the qualitative analysis was that self-efficacy in specific HF self-care maintenance (e.g., diet adherence) and management behaviors (symptom management) shaped how individuals made self-care decisions within the context of a comorbid condition. For example, self-efficacy influenced how individuals with multiple dietary restrictions made dietary choices (“I know what I can eat and what I can’t, I can do that [diabetes diet]; this salt thing…it is hard….”). Similarly, individuals who felt ill-prepared to carry out self-care management when experiencing HF symptoms described a lack of self-efficacy in managing HF symptoms within the context of another condition. In addition, individuals reported receiving fragmented self-care instructions by multiple providers (“…diabetic nurse didn’t mention salt”) that seemed to influence how individuals selected one set of self-care behaviors to engage in, most often those in which they felt most confident.
Integration of Data
In each of the four parent mixed methods studies, concordance between the qualitative accounts of self-care maintenance and management and the quantitative measurement of self-care was excellent (>95%). There was also very good congruence (85%) between the self-care confidence scale and qualitative accounts of self-efficacy. For example, one 59-year-old woman who had a self-care confidence scale score of 85.4 described in the qualitative data her confidence in ability to adhere to dietary restriction (self-care maintenance) as “no matter where I am or who does the cooking…if it tastes salty…that’s the last taste I take…” and recognize symptoms (“I know the symptoms…I feel it here [pointing to ring finger] and I know I am holding on to fluid…before the scale knows”).
Integrating the data provided insights into how the presence of comorbid conditions complicated self-care but highlighted the importance of self-efficacy in patient’s daily self-care. While the quantitative data showed a significant moderation effect in the relationship of self-efficacy with self-care maintenance in individuals with moderate comorbidity (two to three conditions), qualitative accounts help explain this finding. According to the narratives, having more than one comorbid condition in addition to HF challenged the individual’s ability to engage in self-care maintenance behaviors (“…I just get used to one thing and there is something more…a new diet or pill…so sometimes I just do what I know….you know, what I can…”). Self-efficacy influenced how individuals made choices about what self-care maintenance behaviors in which to engage.
For those with four or more comorbid conditions (high comorbidity category), self-care management was particularly difficult as reflected in the quantitative analysis and qualitative accounts. Although the moderation effect was not significant in this small sample (n = 36), self-efficacy emerged as a theme in the qualitative data to explain how individuals managed HF symptoms in the context of comorbid conditions. Individuals who lacked self-efficacy in self-care management often delayed or deferred management of symptoms and described a lack of confidence in their ability to correctly interpret symptoms. As one 72-year-old man with HF, diabetes, prostate cancer, and arthritis described, “I can tell when my sugar is too high or too low…no problem…and I know the bones…they don’t work so well anymore…I get tired easy…is that the heart or what…mostly I just wait to see if it passes or not.”
Older adults reported lower self-care confidence and lower self-care management in the quantitative data, which was explained in the qualitative data as a lack of self-efficacy in symptom management. Conversely, these individuals often described self-efficacy or confidence in their ability to recognize and manage symptoms of other conditions including diabetes and pulmonary disease. The significant quantitative findings can be explained via the integrated analysis, by characterizing the importance of self-efficacy as an important influence on self-care in this population. Importantly, when faced with several comorbid conditions, self-efficacy was weakened. As a result, individuals were vulnerable to poor self-care.
Multiple chronic illnesses moderated the relationship between self-efficacy and self-care maintenance interfering with patients’ abilities to adhere to the HF treatment regimen. Specifically, in the setting of multiple comorbid conditions, HF patients must respond to increasing self-care complexity but feel less confident to do so. Heart failure self-care includes the person’s belief that they are able to care for their HF (Riegel & Dickson, 2008). Self-efficacy has both a direct and indirect effect on self-care by influencing an individual’s choices, energy expenditure, perseverance, resiliency, and stress levels, which may be taxed by comorbid conditions (Pajares, 1991). In the setting of comorbid conditions, self-efficacy also influences the naturalistic decision-making inherent in self-care by shaping their perception of themselves, their problem that includes other comorbid conditions, and the environment (Riegel & Dickson, 2008).
The presence of multiple comorbid conditions was found to complicate self-care by lowering self-efficacy and increasing the likelihood of inadequate self-care. For example, when a patient felt fatigued by increasing fluid volume but blamed the fatigue on their diabetes and ate a few salted crackers, they actually increased the likelihood of symptom exacerbation and subsequent hospitalization. The findings are supported by a systematic review of clinical trials that found fewer readmissions to the hospital in those with higher self-confidence in their chronic care practices (Jacob & Poletick, 2008).
Also, HF patients who felt ill-prepared to carry out HF self-care instead chose to focus on a self-care practice for the comorbid condition in which they felt more confident. This finding builds on earlier work that showed that lack of confidence was a barrier to successful management of HF (Riegel & Carlson, 2002) and higher levels of confidence were associated with expert status in self-care (Riegel, Lee, Albert, et al., 2011) by describing how comorbid conditions influenced this association. When individuals were forced to select which self-care practices they would implement in response to symptoms, they reported consistently that they selected those in which they had the most confidence, albeit for a comorbid condition.
Older, chronically ill people are vulnerable to poor quality of care due to multiple, conflicting regimens (U.S. Department of Health and Human Services, 2010). The participants expressed an inability to integrate self-care instructions for multiple comorbid conditions into a coherent whole (or pragmatic action plan). As a result of fragmented self-care instructions, they felt forced to select one set of self-care behaviors out of several. They reported often just waiting out the symptom instead of taking action. Care coordination has been at the forefront of the Institute of Medicine’s (2001) mandate to improve the care of chronic conditions since 2001, but it remains a rarity rather than a system-wide practice. Moving from a disease-based model to a more integrated system or needs-based model would advance the care of those with multiple comorbid conditions.
The results of this study support the Situation Specific Theory of Heart Failure Self-Care (Riegel & Dickson, 2008), which conceptualizes self-care as the choice of behaviors and decisions that maintain physiologic stability and the response to symptoms when they occur. Specifically, the results help explain the theory’s propositions regarding the importance of self-efficacy in the self-care process. In the sample, individuals who had difficulty differentiating the source of symptoms of multiple chronic conditions struggled with HF self-care management; often acting on the condition with which they had the most experience and self-efficacy. Similarly, when faced with multiple treatment instructions, individuals described making choices about self-care behaviors and choosing the set of self-care behaviors in which they had the greatest self-efficacy or confidence. The situation-specific theory of HF self-care posits that confidence is a mediator or moderator in the relationship of self-care and outcomes. As found in this study, comorbidity moderates the relationship between self-efficacy and self-care. This finding lends more credence to the importance of self-efficacy throughout the self-care process. Further research is needed to identify more factors influencing self-efficacy in regard to self-care.
This was a secondary analysis of four data sets, and therefore the analysis was limited to the data as collected. The qualitative analysis relied on the existing narrative data derived from a common set of questions for which the exploration of comorbid conditions was not a primary aim. Although there may be some cases where more detail regarding comorbid conditions would have enhanced the findings, the robust sample size of 114 narratives provided a rich qualitative data set for this mixed methods study. Also, the sample was younger than is found typically in HF research, although participants reported multiple comorbid conditions consistent with the HF literature. To strengthen the findings, age was controlled in the analysis, although it was not a significant contributor to the variability in the data. It would be interesting to see if the relationships changed in a more typical elder population with HF and one that has greater ethnic diversity, since this sample was predominately Caucasian.
There were also several limitations related to sample size and instrumentation. Sample sizes greater than 200 are recommended when medium to small effects sizes are expected and instrument reliabilities are in the .70 range (Whisman & McClelland, 2005). However, the fact that a moderator effect was found despite these limitations suggests that the moderation effect may have been present elsewhere but we did not have adequate power to detect it.
The CCI may not be sufficient as a measurement tool for this area of research because it cannot be used to assess all chronic conditions affecting HF patients. Although the CCI was developed to predict mortality (Charlson, Szatrowski, Peterson, & Gold, 1994) and cost (Charlson et al., 2008), it may not capture the HF patient’s experience in chronic illness. For example, the CCI weights cancer heavily, which can be relatively slow-growing in some forms, especially in older adults, while not measuring osteoarthritis, which may be more highly predictive of both cost and morbidity in the HF population.
The results of this study highlight the need for clinicians and researchers to acknowledge and seek to understand the self-care complexity faced by many patients with HF, particularly when there are coexisting chronic conditions. Of greatest importance is the call to deliver self-care education and instructions that integrate all chronic condition self-care. Second, research to develop and test interventions to foster self-efficacy and focus on self-care across multiple chronic conditions is needed. As suggested by Yancik et al. (2007) measurement tools that assess, categorize, and determine the influence of particular combinations of conditions in HF are needed.
Bandura A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.
Baron R. M., Kenny D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182.
Bennett J. A. (2000). Mediator and moderator variables in nursing research: Conceptual and statistical differences. Research in Nursing & Health, 23, 415–420.
Braunstein J. B., Anderson G. F., Gerstenblith G., Weller W., Niefeld M., Herbert R., Wu A. W. (2003). Noncardiac comorbidity increases preventable hospitalizations and mortality among Medicare beneficiaries with chronic heart failure. Journal of the American College of Cardiology, 42, 1226–1233.
Byrne M. (2001). Data analysis strategies for qualitative research. AORN Journal, 74, 904–905.
Charlson M. E., Charlson R. E., Peterson J. C., Marinopoulos S. S., Briggs W. M., Hollenberg J. P. (2008). The Charlson Comorbidity Index is adapted to predict costs of chronic disease in primary care patients. Journal of Clinical Epidemiology, 61, 1234–1240.
Charlson M. E., Pompei P., Ales K. L., MacKenzie C. R. (1987). A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases, 40, 373–383.
Charlson M., Szatrowski T. P., Peterson J., Gold J. (1994). Validation of a combined comorbidity index. Journal of Clinical Epidemiology, 47, 1245–1251.
Chen J., Normand S. L., Wang Y., Krumholz H. M. (2011). National and regional trends in heart failure hospitalization and mortality rates for Medicare beneficiaries, 1998–2008. JAMA, 306, 1669–1678.
Cohen J. (1992). A power primer. Psychological Bulletin, 112, 155–159.
Creswell J. W., Clark V., Gutmann M., Hanson W. (2003). Advanced mixed methods research designs. In Tashakkori A., Teddlie C. (Eds.), Handbook of mixed methods in social and behavioral research. Thousands Oaks, CA: Sage.
Dahlström U. (2005). Frequent non-cardiac comorbidities in patients with heart failure. European Journal of Heart Failure, 7, 309–316.
Dickson V. V., Buck H., Riegel B. (2011). A qualitative meta-analysis of heart failure self-care practices among individuals with multiple comorbid conditions. Journal of Cardiac Failure, 17, 413–419.
Dickson V. V., Deatrick J. A., Riegel B. (2008). A typology of heart failure self-care management in non-elders. European Journal of Cardiovascular Nursing, 7, 171–181.
Dickson V. V., Lee C. S., Riegel B. (2011). How do cognitive function and knowledge affect heart failure self-care? Journal of Mixed Methods Research, 47, 888–895.
Ekundayo O. J., Muchimba M., Aban I. B., Ritchie C., Campbell R. C., Ahmed A. (2009). Multimorbidity due to diabetes mellitus and chronic kidney disease and outcomes in chronic heart failure. The American Journal of Cardiology, 103, 88–92.
Goodlin S. (2005). Heart failure in the elderly. Expert Reviews in Cardiovascular Therapy, 3, 99–106.
Heo S., Moser D. K., Lennie T. A., Riegel B., Chung M. L. (2008). Gender differences in and factors related to self-care behaviors: A cross-sectional, correlational study in heart failure patients. International Journal of Nursing Studies, 45, 1807–1815.
Institute of Medicine. (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academies Press.
Jacob L., Poletick E. B. (2008). Systematic review: Predictors of successful transition to community-based care for adults with chronic care needs. Care Management Journals, 9, 154–165.
Lee C. S., Riegel B., Driscoll A., Suwanno J., Moser D. K., Lennie T. A., Worrall-Carter L. (2009). Gender differences in heart failure self-care: A multinational cross-sectional study. International Journal of Nursing Studies, 46, 1485–1495.
McCormick J., Rodney P., Varcoe C. (2003). Reinterpretations across studies: An approach to meta-analysis. Qualitative Health Research, 13, 933–944.
Miles J. (2005). Tolerance and variance inflation factor. In Everitt B. S., Howell D. (Eds.), Encyclopedia of statistics in behavioral science. Hoboken, NJ: Wiley.
Noblit G., Hare R. (1988). Meta-ethnography: Synthesizing qualitative studies. London, UK: Sage.
Oudejans I., Mosterd A., Zuithoff N. P., Hoes A. W. (2012). Comorbidity drives mortality in newly diagnosed heart failure: A study among geriatric outpatients. Journal of Cardiac Failure, 18, 47–52.
Pajares F. (1991). Current directions in self-efficacy research. In Maehr M., Pintrich P. (Eds.), Advances in motivation and achievement (Vol. 10, pp. 1–49). Greenwich, CT: JAI Press.
Peterson J. C., Paget S. A., Lachs M. S., Reid M. C., Charlson M. E. (2012). The risk of comorbidity. Annals of the Rheumatic Diseases, 71, 635–637.
Riegel B., Carlson B. (2002). Facilitators and barriers to heart failure self-care. Patient Education and Counseling, 46, 287–295.
Riegel B., Carlson B., Moser D. K., Sebern M., Hicks F. D., Roland V. (2004). Psychometric testing of the Self-Care of Heart Failure Index. Journal of Cardiac Failure, 10, 350–360.
Riegel B., Dickson V. V. (2008). A situation-specific theory of heart failure self-care. The Journal of Cardiovascular Nursing, 23, 190–196.
Riegel B., Dickson V. V., Hoke L., McMahon J. P., Reis B. F., Sayers S. (2006). A motivational counseling approach to improving heart failure self-care: Mechanisms of effectiveness. The Journal of Cardiovascular Nursing, 21, 232–241.
Riegel B., Dickson V. V., Kuhn L., Page K., Worrall-Carter L. (2010). Gender-specific barriers and facilitators to heart failure self-care: A mixed methods study. International Journal of Nursing Studies, 47, 888–895.
Riegel B., Lee C. S., Albert N., Lennie T., Chung M., Song E. K., Moser D. K. (2011). From novice to expert: Confidence and activity status determine heart failure self-care performance. Nursing Research, 60, 132–138.
Riegel B., Lee C. S., Dickson V. V., & Medscape. (2011). Self care in patients with chronic heart failure. Cardiology, 8, 644–654.
Riegel B., Lee C. S., Dickson V. V., Carlson B. (2009). An update on the Self-Care of Heart Failure Index. The Journal of Cardiovascular Nursing, 24, 485–497.
Riegel B., Moser D. K., Anker S. D., Appel L. J., Dunbar S. B., Grady K. L., … American Heart Association Interdisciplinary Council on Quality of Care and Outcomes Research. (2009). State of the science: Promoting self-care in persons with heart failure: A scientific statement from the American Heart Association. Circulation, 120, 1141–1163. doi: 10.1161/CIRCULATIONAHA.109.192628.
Riegel B., Vaughan Dickson V., Goldberg L. R., Deatrick J. A. (2007). Factors associated with the development of expertise in heart failure self-care. Nursing Research, 56, 235–243.
U.S. Department of Health and Human Services. (2010). Multiple chronic conditions—A strategic framework: Optimum health and quality of life for individuals with multiple chronic conditions. Washington, DC: Author.
Whisman M. A., McClelland G. H. (2005). Designing, testing and interpreting interactions and moderator effects in family research. Journal of Family Psychology, 19, 111–120.
Wong C. Y., Chaudry S. I., Desai M. M., Krumholz H. M. (2011). Trends in comorbidity, disability, and polypharmacy in heart failure. The American Journal of Medicine, 124, 136–143. doi: 10.1016/j.amjmed.2010.08.017.
Yancik R., Ershler W., Satariano W., Hazzard W., Cohen H. J., Ferrucci L. (2007). Report of the national institute on aging task force on comorbidity. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 62, 275–280.
comorbidity; chronicity; heart failure; mixed methods; self-care; self-efficacy
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