Depression

CorrelationalHeartFailure.pdf

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Introduction Heart failure (HF) is a progres- sive disease, which commonly results in functional impairment and activity intolerance (Yancy et al., 2013). As symptom se- verity increases, the ability to perform activities of daily liv- ing is affected, creating a barrier to effective self-care (Riegel et al., 2009). In fact, HF is one of the most common reasons for hospitalization among individu- als 65 years and older and the main reason for about 16 million visits to ambulatory care cen- ters each year (American Heart Association, 2013). Thus, many patients rely on home healthcare clinicians to assist with daily tasks and disease management (e.g., treatment adherence, daily weight monitoring, etc.) to pre- vent these adverse outcomes.

Living with HF not only has physiological ramifications, but psychological effects as well. For example, prior research indi- cates that approximately 50% of individuals with HF experience depressive symptoms (Gottlieb et al., 2004) secondary to HF symptoms and functional im- pairment (Carels, 2004; Cully et al., 2010). Depressive symptoms are known barriers to effective self-care (Suter et al., 2012) and influence morbidity and mortal- ity in HF (Yancy et al., 2013).

How one copes with increasing symptoms of HF may influence the development of depressive symptoms. Although findings

FACTORS ASSOCIATED WITH

in Patients With Heart Failure Depressive Symptoms

Home healthcare clinicians commonly provide care for individu- als with heart failure (HF). Certain factors may influence the de- velopment of depressive symptoms in those with HF. This cross- sectional, descriptive, correlational pilot study (N = 50) examined interrelationships among HF symptoms, social support (actual and perceived), social problem-solving, and depressive symptoms. Find- ings indicated that increased HF symptoms were related to more depressive symptoms, whereas higher levels of social support were related to fewer depressive symptoms. The use of more maladaptive problem-solving strategies was also associated with more depres- sive symptoms. Study results have implications for home healthcare clinicians providing care for individuals with HF, indicating a need for programs that strengthen coping skills and resources (i.e., social support and problem solving) in an effort to decrease the risk of developing depressive symptomatology.

Lucinda J. Graven, PhD, ARNP

Joan S. Grant, PhD, RN

David E. Vance, PhD, MGS

Erica R. Pryor, PhD, RN

Laurie Grubbs, PhD, ARNP

Sally Karioth, PhD, ARNP, CT

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describing the study. Interested patients then contacted the primary investigator for more infor- mation about the study.

Inclusion criteria were that participants: (a) have a diagnosis of HF; (b) be ≥55 years of age; (c) reside in an outpatient setting; and (d) speak, read, and understand English. Additionally, par- ticipants had to be cognitively unimpaired, as evidenced by a score ≥31 on the TICS (Brandt et al., 1988). Only one participant did not meet the minimum score of 31 on the TICS, and was there- fore not enrolled in the study.

Instruments HF Symptoms

Physical symptoms were measured using the 14- item Heart Failure Symptom Survey (HFSS) (Pozehl et al., 2006). Individuals rate 14 common symptoms of HF according to frequency, severity, and interfer- ence with physical activity, and enjoyment of life. Higher scores indicate more frequent and severe symptoms of HF, as well as more interference with physical activity and enjoyment of life (Pozehl et al.). Although empirical evidence supports its psy- chometric properties (Hertzog et al., 2010; Quinn et al., 2010), earlier studies failed to report whether the HFSS instrument is best viewed as a single- or multidimensional instrument. Following factor analysis, frequency, severity, and interference with physical activity and enjoyment of life were viewed as one domain to represent physical symptoms of HF in this study, with factor loadings of .30 or higher on one factor (Graven, 2014). In this study, Cronbach’s alpha was .97.

Social Support

Perceived social support was measured using the 12-item, Interpersonal Support Evaluation List (ISEL-12) (Cohen et al., 1985). Empirical evidence supports its construct validity (Cohen et al.) and reliability (Bakan & Akyol, 2008). Higher scores indicate greater perceived social support (Cohen et al.). Cronbach’s alpha in this study was .94.

Social network was measured using the 12-item researcher-developed Graven and Grant Social Network Survey (GGSNS) (Graven, 2014). Higher

from several studies suggest social support influ- ences the development of depressive symptoms in individuals with HF, these studies primarily investi- gated perceived support only (Carels, 2004; Dekker et al., 2009; Park et al., 2006; Trivedi et al., 2009; Vollman et al., 2007), rather than both perceived and actual (i.e., social network) support. Similarly, although published research has investigated other coping strategies in individuals with HF (Trivedi et al.; Vollman et al.), the influence of social problem solving (i.e., problem-solving style) on depressive symptoms is yet to be examined in those with HF, even though a relationship between these variables exists in other populations (Prachakul et al., 2007).

This pilot study examined relationships among factors that may influence depressive symptoms in individuals with HF. Its main goal is to investigate factors not previously examined, particularly social network and social problem solving. This study is a preliminary analysis to a future investigation exploring mediation of social support and social problem solving in the relationship between HF symptoms and depressive symptoms and, there- fore, does not intend to examine any causal rela- tionships or predictions for depressive symptoms. This pilot study answered the following research question: What are the relationships among HF symptoms, social support, social problem solving, and depressive symptoms in outpatients with HF?

Methods Design This pilot study used a cross-sectional, descrip- tive, correlational design. Participants were screened for cognitive and clinical eligibility over the telephone using the Telephone Interview for Cognitive Status (TICS) (Brandt et al., 1988) and a sociodemographic questionnaire. Following consent, participants completed an individual in- terview at a clinic, using a set of self-report ques- tionnaires. No incentives for participation were provided. Approval from two university-affiliated institutional review boards and a hospital- affiliated institutional review board was granted before sample recruitment and enrollment.

Participants and Settings A convenience sample of outpatients with HF (N = 50) was recruited from three outpatient clin- ics in Northwest Florida. Recruitment methods included flyers displayed in each office and let- ters mailed to eligible patients from each office,

Findings suggest that as individuals use more adaptive problem-solving strategies, the use of maladaptive strategies decrease.

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males (n = 31; 62%), who ranged in age from 55 to 92 years (M = 72.42; SD = 9.1). Half of the sample was married (n = 25; 50%) and lived with at least one person in their household (n = 25; 50%). Scores on the HFSS (M = 2.13; SD = 1.90) sug- gested participants experienced mild-to-moderate HF-related physical symptoms, consistent with the high percentage of participants with Class II NYHA HF (54%) who commonly experience fewer HF-related symptoms and a lesser degree of func- tional impairment (Criteria Committee of the New York Heart Association, 1994). Although the mean score for the CES-D (M = 12.84; SD = 11.88) indi- cated negligible depressive symptoms for most participants, almost half of participants were ex- periencing either mild-to-moderate (n = 7; 14%) or major depressive symptoms (n = 11; 22%), scoring either 16 to 21 or greater than 21 on the CES-D, re- spectively. Mean scores on the GGSNS (M = 55.40; SD = 19.34) and the ISEL-12 (M = 26.54; SD = 9.43) suggested participants had above average actual and perceived support. For problem solving, mean scores indicated that even though participants reported fairly good adaptive problem solving (M = 27.00; SD = 8.49), a relatively high amount of maladaptive problem solving was also present (M = 47.34; SD = 7.88).

Bivariate Analysis Relationships among study variables are shown in Table 2. Physical symptoms of HF were posi- tively related to depressive symptoms (p < .01) and maladaptive problem solving (p < .05), indi- cating that as HF symptoms increased individu- als experienced more depressive symptoms and used more maladaptive problem solving. Social support was positively associated with social network ( p < .01) and negatively related to de- pressive symptoms ( p < .01), suggesting that those with more perceived support had a larger social network and experienced fewer depressive symptoms. Similarly, a larger social network also was related to fewer depressive symptoms ( p < .01). A negative relationship was found between adaptive problem solving and maladaptive prob- lem solving ( p < .01), suggesting that use of more adaptive problem solving is related to the use of less maladaptive problem solving. Lastly, more adaptive problem solving was found to be related to less depressive symptoms ( p < .05), whereas more maladaptive problem solving was related to increased depressive symptoms ( p < .01).

scores reflect a larger social network. Content validity was established using a modified Delphi technique and three content reviewers with ex- pertise in social support, HF, and psychometrics (Graven). The instrument was internally consis- tent, with a Cronbach’s alpha of .93.

Social Problem Solving

The 25-item scale Social Problem-Solving Inven- tory–Revised Short-version (SPSI-R:S) (D’Zurilla et al., 2002) was used to evaluate individuals’ adaptive (i.e., constructive, effective, and facilita- tive problem solving) and maladaptive (i.e., de- fective, ineffective, and dysfunctional) styles to- ward solving everyday problems (Christopher & Thomas, 2008). Empirical evidence supports psy- chometric properties of the SPSI-R:S (D’Zurilla et al.). Both adaptive and maladaptive problem- solving styles were derived from the unweighted sum of items, with higher scores representing more of the respective problem-solving style. In this study, Cronbach’s alphas were .86 and .77, respectively, for adaptive and maladaptive items.

Depressive Symptoms

The 20-item Center for Epidemiological Studies– Depression (CES-D) scale (Radloff, 1977) measured depressive symptoms, with higher scores indi- cating more depressive symptoms (Park et al., 2006). A cutoff score of 16 indicates an indi- vidual is at risk for some degree of depressive symptoms (McDowell & Newell, 1996). Previous studies support validity and reliability (Lesman- Leegte et al., 2009; Park et al.). The Cronbach’s alpha in this study was .91.

Data Analysis SPSS version 20 software (IBM, Inc., Armonk, NY) was used for data analysis, with all tests for statistical significance set at an alpha level of .05. Descriptive statistics were obtained to examine sample characteristics and scores on all study instrument variables. Correlational analyses were conducted using Pearson product moment corre- lation coefficients.

Results Sample Characteristics and Descriptive Analyses Table 1 provides an overview of sample charac- teristics and descriptive analyses. The sample comprised primarily Caucasi an (n = 42; 84%)

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use of distraction and denial (i.e., maladaptive problem-solving strategies), whereas other re- searchers found that individuals who reported using fewer strategies, such as planned problem solving and taking action (i.e., adaptive problem- solving strategies) reported more depressive symptoms (Trivedi et al., 2009; Vollman et al., 2007). However, it is plausible that poor problem solving could be a consequence of depressive symptoms and negative affect (Nezu et al., 2004).

HF Symptoms and Depressive Symptoms Consistent with previous studies (Carels et al., 2004; Song et al., 2009; Trivedi et al., 2009), find- ings from this study indicate individuals who experience increased HF symptoms also experi- ence more depressive symptoms. These findings highlight the potential for psychological distress as HF progresses and symptoms increase.

Discussion HF Symptoms, Social Problem Solving, and Depressive Symptoms Findings suggest that as individuals use more adaptive problem-solving strategies, the use of maladaptive strategies decreases. This finding is consistent with prior research (D’Zurilla et al., 2002). Furthermore, it appears that as HF symp- toms increase, individuals use more maladaptive problem-solving strategies (e.g., solving prob- lems or making decisions in an impulsive or care- less manner; avoiding or minimizing problems). Results suggest that individuals who use fewer adaptive problem-solving strategies experience more depressive symptoms. Although studies are few, these findings support other empirical literature examining coping strategies in HF. For example, Carels et al. (2004) found that increased HF symptoms were positively associated with

Variable n % M (SD) Range

Age 72.42 (9.10) 55–92

Gender Male Female Transgender

31 18 1

62 36 2

Race White African American

42 8

84 16

Highest level of education 7th–9th grade 10th–12th grade High school graduate Some college College graduate Graduate degree

2 8 9 10 15 6

4 16 18 20 30 12

Annual Income <$30,000 $30,000–$50,000 $50,000–$75,000 $75,000–$100,000 >$100,000

21 12 8 7 2

42 24 16 14 4

Heart failure class (NYHA) I II III IV

11 27 7 5

22 54 14 10

Heart failure symptoms (HFSS) 2.13 (1.90) 0–7.39

Social network (GGSNS) 55.40 (19.34) 12–84

Social support (ISEL-12) 26.54 (9.43) 0–36

Maladaptive problem solving 47.34 (7.88) 28–60

Adaptive problem solving 27.00 (8.49) 9–40

Depressive symptoms (CES-D) 12.84 (11.88) 0–49

Note. CES-D, Center for Epidemiological Studies–Depression; GGSNS = Graven and Grant Social Network Survey; HFSS = Heart Failure Symptom Survey; ISEL-12, Interpersonal Support Evaluation List—12 item; NYHA = New York Heart Association.

Table 1. Sample Characteristics and Descriptive Statistics for Study Variables (N = 50)

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in aiding activity tolerance, physical functioning, and self-care. Intensive training is warranted to educate patients in the management of progres- sive symptoms (e.g., self-adjusting diuretics during times of weight gain and edema) and decreases in functional ability (e.g., adjusting environment, sim- plifying treatment regimens) in an effort to lessen the use of maladaptive problem-solving strategies.

Findings also support the need for patient educa- tion on adaptive problem-solving strategies to pro- mote psychological well-being. Interventions such as mutual goal setting and problem-solving skills training can reinforce adaptive problem-solving strategies and are associated with reduced depres- sive symptoms in individuals with HF (Gary et al., 2010; Sullivan et al., 2009). Additionally, screening for depressive symptoms should occur at the initiation of home healthcare and whenever there appears to be a change in physical or psychologi- cal status. Individuals who have a positive screen for depressive symptoms should be referred to a behavioral health specialist for further evaluation.

Findings from this study also reiterate the significant influence of social support on psycho- logical well-being. The inclusion of social network in this study, often underrepresented in research, provides insight into the importance of having adequate support systems that enable individuals with HF to talk about their problems and receive needed assistance. Thus, clinicians should assess the level of social network availability at the onset of home care and include support systems in the care process to lessen depressive symptoms.

Lucinda J. Graven, PhD, ARNP, is an Assistant Professor, College of Nursing, Florida State University, Tallahassee, Florida.

Joan S. Grant, PhD, RN, is a Professor, School of Nursing, University of Alabama at Birmingham, Birmingham, Alabama.

David E. Vance, PhD, MGS, is an Associate Professor, School of Nursing, University of Alabama at Birmingham, Birmingham, Alabama.

Erica R. Pryor, PhD, RN, is an Associate Professor, School of Nurs- ing, University of Alabama at Birmingham, Birmingham, Alabama.

Social Support, Social Network, and Depressive Symptoms Previously, few studies have investigated the as- sociation between social network and depressive symptoms in individuals with HF (Westlake et al., 2005; Yu et al., 2004). Findings of this study indi- cate that individuals with a larger social network perceived a greater level of social support, sug- gesting that the availability of a social network en- hances individuals’ perceptions of social support. In addition, consistent with previous research (Carels, 2004; Trivedi et al., 2009; Vollman et al., 2007; Yu et al.), individuals in this sample who reported less actual and perceived support also reported more depressive symptoms.

Limitations HF is more common in African Americans and equally frequent in males and females (Emory Healthcare, 2013). However, most participants in this study were White males, limiting the general- izability of findings. Self-selection or volunteering to be in the study may have resulted in individuals with fewer symptoms of HF. Likewise, this pilot study used a small sample to investigate multiple correlations among study variables, thereby in- creasing the risk of a Type I error.

Implications for Home Healthcare Clinicians Home healthcare clinicians commonly provide care for individuals with HF who are at an in- creased risk for depressive symptoms (Suter et al., 2012; Yancy et al., 2013). Patient education should be provided that lessens maladaptive problem- solving strategies and improves one’s ability to cope with HF symptoms (Sullivan et al., 2009). Further, cognitive behavioral therapy (e.g., ac- tivity scheduling, role playing, and journaling) has increased physical functioning in previous research (Gary et al., 2010) and may be beneficial

Variable 1 2 3 4 5 6

1. HF symptoms —

2. Social network –.136 —

3. Social support –.230 .829‡ —

4. Maladaptive problem solving .279† –.077 –.125 —

5. Adaptive problem solving –.036 .208 .251 –.520‡ —

6. Depressive symptoms .627‡ –.475‡ –.539‡ .549‡ –.343† —

Note. HF = heart failure. †p < .05. ‡p < .01.

Table 2. Bivariate Correlations for Study Variables (N = 50)

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patients: A pilot study. Journal of Cardiovascular Nursing, 25(4), 273–283.

Lesman-Leegte, I., Jaarsma, T., Coyne, J. C., Hillege, H. L., Van Veldhuisen, D. J., & Sanderman, R. (2009). Quality of life and depressive symptoms in the elderly: A comparison between patients with heart failure and age- and gender-matched community controls. Journal of Cardiac Failure, 15(1), 17–23. doi:10.1016/j.cardfail.2008.09.006

McDowell, I., & Newell, C. (1996). Measuring Health: A Guide to Rat- ing Scales and Questionnaires (2nd ed., pp. 254–259). New York, NY: Oxford University Press.

Nezu, A., Wilkins, V., & Nezu, C. (2004). Social problem-solving, stress, and negative affect. In E. Chang, T. D’Zurilla, & L. Sanna (Eds.), Social problem-sovling: Theory, research, and training (pp. 49–65). Washington, DC: American Psychological Assocation.

Park, C., Fenster, J. R., Suresh, D. P., & Bliss, D. E. (2006). Social support, appraisals, and coping as predictors of depression in congestive heart failure patients. Psychology and Health, 21(6), 773–789. doi:10.1080/14768320600682368

Pozehl, B., Duncan, K., & Hertzog, M. (2006). Heart failure symptom survey: Validity and reliability. Presented at the Heart Failure Society of America 10th Annual Scientific Meeting. Seattle, WA.

Prachakul, W., Grant, J. S., & Keltner, N. L. (2007). Relationships among functional social support, HIV-related stigma, social problem solving, and depressive symptoms in people living with HIV: A pilot study. Journal of the American Association of Nurses in AIDS Care, 18(6), 67–76. doi:10.1016/j.jana.2007.08.002

Quinn, C., Dunbar, S. B., & Higgins, M. (2010). Heart failure symptom assessment and management: Can caregivers serve as proxy? Journal of Cardiovascular Nursing, 25(2), 142–148.

Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychologi- cal Measurement, 1, 385–401.

Riegel, B., Moser, D. K., Anker, S. D., Appel, L. J., Dunbar, S. B., Grady, K. L.,… , Whellan, D. J. (2009). State of the science: Promoting self-care in persons with heart failure: A scientific statement from the American Heart Association. Circulation, 120(12), 1141–1163.

Song, E. K., Moser, D. K., & Lennie, T. A. (2009). Relationship of depressive symptoms to the impact of physical symptoms on functional status in women with heart failure. American Journal of Critical Care, 18(4), 348–356. doi:10.4037/ajcc2009450

Sullivan, M. J., Wood, L., Terry, J., Brantley, J., Charles, A., McGee, V., . . ., Cuffe, M. S. (2009). The Support, Education, and Re- search in Chronic Heart Failure Study (SEARCH): A mindfulness- based psychoeducational intervention improves depression and clinical symptoms in patients with chronic heart failure. Ameri- can Heart Journal, 157(1), 84–90. doi:10.1016/j.ahj.2008.08.033

Suter, P. M., Gorski, L. A., Hennessey, B., & Suter, W. N. (2012). Best practices for heart failure: A focused review. Home Healthcare Nurse, 30(7), 394–405. doi:10.1097/NHH.0b013e31825b11ab

Trivedi, R. B., Blumenthal, J. A., O’Connor, C. M., Adams, K., Hinder- liter, A., Dupree, C., … , Sherwood, A. (2009). Coping styles in heart failure patients with depressive symptoms. Journal of Psychosomatic Research, 67(4), 339–346. doi:10.1016/j.jpsy- chores.2009.05.014

Vollman, M. W., LaMontagne, L. L., & Hepworth, J. T. (2007). Coping and depressive symptoms in adults living with heart failure. Journal of Cardiovascular Nursing, 22(2), 125–130. doi:10.1097/00005082-200703000-00009

Westlake, C., Dracup, K., Fonarow, G., & Hamilton, M. (2005). De- pression in patients with heart failure. Journal of Cardiac Failure, 11(1), 30–35. doi:10.1016/j.cardfail.2004.03.007

Yancy, C. W., Jessup, M., Bozkurt, B., Butler, J., Casey Jr, D. E., Drazner, M. H., …, Wilkoff, B. L. (2013). 2013 ACCF/ AHA guideline for the management of heart failure: Execu- tive summary: A report of the American College of Cardiology Foundation/American Heart Association Task Force on prac- tice guidelines. Circulation, 128(16), 1810–1852. doi:10.1161/ CIR.0b013e31829e8807

Yu, D. S., Lee, D. T., Woo, J., & Thompson, D. R. (2004). Correlates of psychological distress in elderly patients with congestive heart failure. Journal of Psychosomatic Research, 57(6), 573– 581. doi:10.1016/j.psychores.2004.04.368

Laurie Grubbs, PhD, ARNP, is a Professor, College of Nursing, Florida State University, Tallahassee, Florida.

Sally Karioth, PhD, ARNP, CT, is a Professor, College of Nursing, Florida State University, Tallahassee, Florida.

The authors declare no conflicts of interest.

Address for correspondence: Lucinda J. Graven, PhD, ARNP, College of Nursing, 419 Duxbury Hall, 98 Varsity Way, Tallahassee, FL 32306 (lgraven@fsu.edu).

DOI:10.1097/NHH.0000000000000140

REFERENCES American Heart Association. (2013). Executive summary: Heart

disease and stroke statistics--2013 update: A report from the American Heart Association. Circulation, 127(1), 143–152. doi:10.1161/CIR.0b013e318282ab8f

Bakan, G., & Akyol, A. D. (2008). Theory-guided interventions for adaptation to heart failure. Journal of Advanced Nursing, 61(6), 596–608. doi:10.1111/j.1365-2648.2007.04489.x

Brandt, J., Spencer, M., & Folstein, M. (1988). The telephone inter- view for cognitive status. Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 1(2), 111–117.

Carels, R. A. (2004). The association between disease severity, functional status, depression and daily quality of life in conges- tive heart failure patients. Quality of Life Research, 13(1), 63–72. doi:10.1023/B:QURE.0000015301.58054.51

Carels, R. A., Musher-Eizenman, D., Cacciapaglia, H., Pérez- Benítez, C. I., Christie, S., & O’Brien, W. (2004). Psychosocial functioning and physical symptoms in heart failure patients: A within-individual approach. Journal of Psychosomatic Research, 56(1), 95–101. doi:10.1016/S0022-3999(03)00041-2

Christopher, G., & Thomas, M. (2008). Social problem-solving in chronic fatigue syndrome: Preliminary findings. Stress and Health, 25, 161–169. doi:10.1002/smi.1233

Cohen, S., Mermelstein, R., Karmarck, T., & Hoberman, H. (1985). Measuring the functional components of social support. In I. Sararon & B. Sararon (Eds.), Social Support: Theory, Research, and Application (pp. 73–94). Boston, MA: Maritinus Nijhoff.

Criteria Committee of the New York Heart Association. (1994). No- menclature and Criteria for Diagnosis of Diseases of the Heart and Great Vessels (9th ed.). Boston, MA: Little Brown & Company.

Cully, J. A., Phillips, L. L., Kunik, M. E., Stanley, M. A., & Deswal, A. (2010). Predicting quality of life in veterans with heart failure: The role of disease severity, depression, and comorbid anxiety. Behavioral Medicine, 36(2), 70–76. doi:10.1080/08964280903521297

Dekker, R. L., Peden, A. R., Lennie, T. A., Schooler, M. P., & Moser, D. K. (2009). Living with depressive symptoms: Patients with heart failure. American Journal of Critical Care, 18(4), 310–318. doi:10.4037/ajcc2009672

D’Zurilla, T. J., Nezu, A. M., & Maydeu-Olivares, A. (2002). Manual for the Social Problem-Solving Inventory-Revised. North Tonawa- nda, NY: Multi-Health Systems, Inc.

Emory Healthcare. (2013). Heart failure statistics. Retrieved from http://www.emoryhealthcare.org/heart-failure/learn-about- heart-failure/statistics/html

Gary, R. A., Dunbar, S. B., Higgins, M. K., Musselman, D. L., & Smith, A. L. (2010). Combined exercise and cognitive behavioral therapy improves outcomes in patients with heart failure. Jour- nal of Psychosomatic Research, 69(2), 119–131. doi:10.1016/j. jpsychores.2010.01.013

Gottlieb, S. S., Khatta, M., Friedmann, E., Einbinder, L., Katzen, S., Baker, B., … , Thomas, S. A. (2004). The influence of age, gender, and race on the prevalence of depression in heart failure patients. Journal of the American College of Cardiology, 43(9), 1542–1549. doi:10.1016/j.jacc.2003.10.064

Graven, L. J. (2014). Relationships among heart failure-related physical symptoms, social support, social problem-solving, de- pressive symptomatology, and self-care behaviors in individuals living with heart failure (Unpublished doctoral dissertation). Birmingham, Alabama: University of Alabama at Birmingham.

Hertzog, M. A., Pozehl, B., & Duncan, K. (2010). Cluster analysis of symptom occurrence to identify subgroups of heart failure