Research questions.

550 Home Healthcare Nurse www.homehealthcarenurseonline.com

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

M
B

I/
A

la
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y

Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

vol. 32 • no. 9 • October 2014 Home Healthcare Nurse 551

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.

Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

552 Home Healthcare Nurse www.homehealthcarenurseonline.com

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%)

Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

vol. 32 • no. 9 • October 2014 Home Healthcare Nurse 553

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)

Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

554 Home Healthcare Nurse www.homehealthcarenurseonline.com

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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vol. 32 • no. 9 • October 2014 Home Healthcare Nurse 555

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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

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Journal Club #4: Exit Ticket

Student Names:

Based on the conclusions of the study, what independent or collaborative nursing assessments and interventions could you implement to assist patients with heart failure?

Journal Club #4: Appraisal Worksheet

Student Names:

1. Based on the purpose of the study, was a correlational design appropriate for the research question? Why or why not?

2. What type of sampling method was used for this study? What extraneous variables did the inclusion and exclusion criteria control for? Did this sufficiently reduce bias in the study? Why or why not?

3. What were the five measurement instruments used and what did each measure? In your opinion, were the measurement instruments sufficiently valid and reliable? Use information from the article to support your opinion.

4.

What were the findings on the relationships among the variables?