Evaluate the practice theory
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JournalofAdvancedNursing-2013-Vellone-StructuralequationmodeltestingthesituationE28090specifictheoryofheart.pdf
ORIGINAL RESEARCH
Structural equation model testing the situation-specific theory of
heart failure self-care
Ercole Vellone, Barbara Riegel, Fabio D’Agostino, Roberta Fida, Gennaro Rocco,
Antonello Cocchieri & Rosaria Alvaro
Accepted for publication 9 February 2013
Correspondence to E. Vellone:
e-mail: [email protected]
Ercole Vellone MSN RN
Research fellow
School of Nursing, University Tor Vergata,
Rome, Italy
Barbara Riegel DNSc RN FAAN
Professor
School of Nursing, University of
Pennsylvania, Philadelphia, USA
Fabio D’Agostino MSN RN
PhD candidate
School of Nursing, University Tor Vergata,
Rome, Italy
Roberta Fida PhD
Assistant Professor
Department of Psychology, “Sapienza”
University, Rome, Italy
Gennaro Rocco MSN RN
President
Center of Excellence for Nursing
Scholarship, Rome, Italy
Antonello Cocchieri MSN RN
PhD candidate
School of Nursing, University Tor Vergata,
Rome, Italy
Rosaria Alvaro MSN RN
Associate Professor
School of Nursing, University Tor Vergata,
Rome, Italy
VELLONE E., R I EGEL B . , D ’AGOST INO F . , F IDA R . , ROCCO G . , COCCH IER I A .
& ALVARO R . ( 2 0 1 3 ) Structural equation model testing the situation-specific
theory of heart failure self-care. Journal of Advanced Nursing 69(11), 2481–
2492. doi: 10.1111/jan.12126
Abstract Aim. To test the situation-specific theory of heart failure self-care with structural
equation modelling.
Background. Several authors have proposed theories on heart failure self-care,
but only the situation-specific theory of heart failure self-care by Riegel and
Dickson is focused on the process that patients use to perform self-care. This
theory has never been tested with structural equation modelling.
Design. A secondary analysis of data from a cross-sectional study.
Methods. Patients with heart failure were recruited in 21 cardiovascular centres
across Italy during 2011. Data were collected with a sociodemographic
questionnaire, chart abstraction for clinical data and the Self-Care of Heart
Failure Index v.6�2. Results. A sample of 417 participants was enrolled in the study (59% males,
mean age 72 years). The following propositions were tested and supported:
Symptom monitoring correlates with treatment adherence; symptom monitoring
and treatment adherence have a direct, positive relationship with symptom
recognition and evaluation that in turn have a direct, positive relationship with
treatment implementation; treatment implementation has a direct, positive
relationship with treatment evaluation. In addition, the following three
relationships were found: Symptom monitoring has a direct, positive relationship
with treatment implementation; symptom recognition and evaluation have direct,
positive relationships with treatment evaluation and symptom monitoring
correlates with treatment evaluation. [Correction added on 9th April 2013, after
first online publication: ‘. . .symptom monitoring correlates with treatment
implementation.’ has been corrected to read ‘. . .symptom monitoring correlates
with treatment evaluation.’]
Conclusion. The data support the situation-specific theory of heart failure self-
care with the addition of three new relationships that emerged from the analysis.
Results of this study lend further support to the use of the situation-specific
theory of heart failure self-care in research and practice.
© 2013 Blackwell Publishing Ltd 2481
JAN JOURNAL OF ADVANCED NURSING
Keywords: heart failure, nursing, self-care, structural equation modelling, symp-
tom monitoring, symptom recognition and evaluation, theory testing, treatment
adherence, treatment implementation
Introduction
Heart Failure (HF) is the most common cardiovascular dis-
ease in many countries worldwide (Caldarola et al. 2009,
Jiang & Ge 2009, Ntusi & Mayosi 2009, Norton et al.
2011). It is estimated that 6�6 million North Americans
(Roger et al. 2012) and 15 million Europeans (Anguita
Sanchez et al. 2008) are affected by HF. The prevalence of
HF is constantly increasing due to the ageing of the popula-
tion, improved treatment, and survival rates after myocar-
dial infarction and the continuing problem of poor control
of hypertension.
Heart failure patients experience lower quality of life
than patients affected by other chronic conditions (Juenger
et al. 2002, Iavazzo & Cocchia 2011, Burstrom et al.
2012) and are prone to frequent hospitalization and emer-
gency department visits for illness decompensation (Krum-
holz et al. 2009, Ross et al. 2010). Mortality remains high
with about the 30% of people with HF dying within the
first year after diagnosis (Barsheshet et al. 2010, Chen et al.
2011).
Self-care of HF is considered essential to improving
patients’ quality of life and reducing hospitalization,
mortality, and emergency department visits (Bird et al.
2010, Buck et al. 2012). In the last two decades several
authors have proposed theories of self-care for use in
research and clinical practice. While all these theories
identify the components and predictors of HF self-care,
only the situation-specific theory by Riegel and Dickson
(2008) has specifically focused on the process that HF
patients use in the performance of self-care (Figure 1).
Although this theory is widely cited no study testing the
relationships among the theoretical concepts was
located.
Background
Theories of self-care in heart failure
Meleis (2011) defines theory as a coherent vision of the
context, process, and outcomes associated with a specific
phenomenon. As demonstrated below, numerous nursing
investigators have proposed models of HF self-care with
variable attention given to these elements of theory.
In studying self-care behaviours of people with HF,
Jaarsma et al. (2000), used three sets of self-care limitations
from Orem’s theory of self-care: knowledge, judging and
decision making, and action and result achievement. Later,
Orem’s theory was used by Jaarsma et al. (2003) to develop
the European Heart Failure Self-care Behaviour Scale
(EHFScBS). In this effort, HF self-care was specified as
involving three constructs: complying with the regimen,
(e.g. daily weighing, sodium and fluid restriction), asking
for help (e.g. call the doctor/nurse in case of weight gain or
excessive fatigue), and adapting activities (e.g. resting).
These three constructs, although describing the components
of self-care, do not represent a theory of HF self-care where
concepts are linked with propositions to explain a process.
Granger et al. (2006) used the middle-range Trajectory of
Chronic Illness Theory (TCIT) by Strauss et al. (1984) to
integrate patients’ perspectives in self-care with those of HF
providers. The TCIT evolved from ethnographic work with
patients affected by chronic illnesses. This theory conceptu-
alizes relationships among factors contributing to the man-
agement of illness and the target therapeutic interventions.
According to this theory patients have their own perception
of the illness; they interpret and report symptoms and per-
ceive prescribed medications differently from healthcare
professionals. Using the TCIC, clinicians can integrate their
perspectives with those of patients. The principal concepts
Symptom monitoring
Symptom recognition
and evaluation
Treatment implementation
Treatment evaluation
Treatment adherence
Figure 1 The situation-specific theory of
heart failure self-care showing the rela-
tionship between Self-care Maintenance
and Self-care Management.
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of the TCIC include the trajectory, that is the illness course,
the trajectory projection reflecting the goals of care, the tra-
jectory schema or the regimen for reaching the goals of
care, the trajectory management specifying how the regimen
is carried out, the conditions influencing management that
are the personal, interpersonal, and social contexts that
influence the regimen and the trajectory phasing, which is
the ups and downs of the clinical outcomes. Although this
theory can be considered a valuable tool to understand the
illness trajectory, it is not specific to HF self-care.
Bennett et al. (2001) developed the Beliefs about Medica-
tion Compliance Scale (BMCS) and the Beliefs about Die-
tary Compliance Scale (BDCS) for patients with HF. Both
instruments were based on the Health Belief Model (HBM)
that attempts to explain and predict health behaviours using
a focus on the individual’s attitudes and beliefs. From the
HBM, these authors took only the concepts of perceived
benefits and barriers, which were applied only to percep-
tions about water pills and the low-salt diet and not to other
self-care activities. In addition, the authors did not elaborate
a mechanism to explain how self-care works in HF.
From the HBM, Connelly (Connelly 1987, 1993) devel-
oped the Model of Self-Care in Chronic Illness (MSCCI)
that was modified and tested in people with HF (Rockwell
& Riegel 2001). The authors of this study conceptualized
that general and therapeutic self-care behaviours are influ-
enced by predisposing variables (self-concept, health moti-
vations, and patient perceptions) and enabling variables
(patient characteristics, psychological status, regimen fea-
tures, cue to action, social support, and system characteris-
tics). Study results showed that only educational level and
the severity of symptoms explained HF self-care. Although
the concepts of self-care maintenance and self-care manage-
ment were described in this article and the investigators
identified variables influencing self-care, they did not
explain the process of self-care per se or how self-care
maintenance related to self-care management.
Moser and Watkins (2008) described five factors affect-
ing decision making and subsequently self-care maintenance
and self-care management in HF patients in a life course
model. The five factors were health literacy, psychological
status, symptom status, ageing status, prior experiences
with symptoms, and the healthcare system. Although this
work gave an important overview of the factors affecting
decision-making and self-care in HF, the manner where the
variables relate to each other was not considered.
In early work, Riegel et al. (2000) described a process of
self-management of HF that later developed into the situa-
tion-specific theory of HF self-care (Riegel & Dickson 2008).
According to the situation-specific theory, self-care is a
naturalistic decision-making process that includes self-care
maintenance and self-care management (Figure 1). Self-care
maintenance refers to symptom monitoring (checking weight
and ankle for swelling) and treatment adherence (e.g. low salt
diet, keeping health provider appointment, exercising) that
reflect behaviours used to maintain physiological stability.
Self-care maintenance, considered the base of self-care, influ-
ences self-care management. Self-care management is a com-
plex process that requires HF patients to act when symptoms
of exacerbation occur, particularly ankle swelling and breath-
ing problems. Self-care management has been described as
being composed of symptom recognition, symptom evalua-
tion, treatment implementation and treatment evaluation.
These actions have been theorized as occurring in sequence,
so symptom recognition influences treatment implementation
and treatment implementation influences treatment evalua-
tion. According to Riegel, the self-care process is influenced
by confidence in one’s ability to perform self-care. As the situ-
ation-specific theory of HF self-care is most highly developed
and an instrument exists with which to measure the various
components of the process, we used structural equation mod-
elling (SEM) to improve our understanding of the process of
HF self-care and of the relationships among the theoretical
concepts.
The study
Aim
The aim of this study was to test the situation-specific theory
of HF self-care with SEM. Such testing would improve
knowledge of the process of HF self-care and of the relation-
ships among the theoretical concepts of treatment adherence,
symptom monitoring, symptom recognition and evaluation,
treatment implementation and treatment evaluation.
Research hypothesis
The overarching hypothesis was that the model would fit
the data, but the following specific hypotheses derived from
the situation-specific theory of HF self-care (Figure 1) were
tested as well:
● Symptom monitoring correlates with treatment adher-
ence.
● Symptom monitoring and treatment adherence have
direct, positive relationships with symptom recognition
and evaluation.
● Symptom recognition and evaluation have direct, posi-
tive relationships with treatment implementation.
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● Treatment implementation has a direct, positive rela-
tionship with treatment evaluation.
Design
A secondary analysis of data from a cross sectional study
was used.
Participants
A convenience sample of 659 participants was enrolled.
From these 659, 417 patients with data on self-care mainte-
nance and self-care management were included. Subjects
excluded at this point were typically missing data on self-
care management because this scale can be measured only
in symptomatic patients. All participants were at least
18 years of age and had a confirmed diagnosis of HF. The
confirmed diagnosis of HF was established using the diag-
nostic criteria specified by the European Society of Cardiol-
ogy guidelines (Dickstein 2008), reconfirmed in 2012
(McMurray et al. 2012). In addition, patients without a
coronary event in the last three months were selected based
on the rationale that soon after a coronary event patients
might find it difficult to perform physical exercise (a com-
ponent of self-care). Patients were recruited from 21 cardio-
vascular ambulatory clinics or day hospitals across Italy.
Data collection
Instruments
The following instruments were used to collect the data.
The sociodemographic questionnaire. This survey was
designed by the research team, even though most items
have been used repeatedly in other studies (Riegel et al.
2010a, Vellone et al. 2012b) to collect age, gender, mari-
tal status, job, educational level, New York Heart Associ-
ation (NYHA) class, ejection fraction, and time since
diagnosis. Functional class measured with the New York
Heart Association (NYHA) scale, ejection fraction, and
time since diagnosis were abstracted from the patient’s
clinical record.
The Self-care of Heart Failure Index version 6�2 (SCHFI
v.6�2) (Riegel et al. 2009). It is a widely used measure of
HF self-care. The instrument is composed of three scales:
(i) the self-care maintenance scale (ten items) measures
symptom monitoring (two items), and treatment adherence
(eight items); (ii) the self-care management scale (six items)
measures HF patients’ actions and responses when symp-
toms occur and specifically symptom recognition and evalu-
ation (one item), treatment implementation (four items),
and treatment evaluation (one item); (iii) the self-care confi-
dence scale (six items) evaluates confidence in each of the
self-care processes, but this scale was not used in the analy-
sis since self-care confidence is not a component of self-care
but instead a factor that influences self-care (Riegel et al.
2009). The 22 item SCHFI v.6�2 uses a 4-point self-report
scale from Never or Rarely to Always or Daily. Three sepa-
rate scores can be computed from this index, all of which
have a possible range of 0–100, the higher the score the
better the self-care.
For the purposes of this study, the individual items were
aggregated conceptually as shown in Table 1 to obtain con-
ceptual measures that could be used to model the theoreti-
cal structure of the situation-specific theory. Each of these
Table 1 Conceptual aggregations of the SCHFI v.6�2 items
Conceptual components Definitions SCHFI v.6�2 item contents
Symptom monitoring Actions patients engage in to monitor HF symptoms and to
prevent HF exacerbation
Daily weighing
Ankle checking for swelling
Treatment adherence Actions patients engage in to follow the HF treatment plan
and to live a healthy life
Following low-salt diet
Taking medication as prescribed
Attending health care provider
Doing physical activities
Using systems to remind to take medicine
Symptom recognition and
evaluation
Recognition and evaluation of changes in health status
related to HF
Time for recognition ankle swelling and problem
breathing as HF symptoms
Treatment implementation Decision to take action and implement treatments in
case of HF symptoms
Likelihood patients do the following actions in
case of ankle swelling or problem breathing:
-reducing salt in diet;
-drink less water;
-taking an extra diuretic;
-calling healthcare provider to ask for advice.
Treatment evaluation Evaluation of the actions taken to treat HF symptoms Being sure that implemented treatment helped
of not helped the patient
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conceptual aggregates was standardized to a 0–100 point
scale to be consistent with scoring of the original measure.
Procedure of data collection
Participants signed informed consent after the study was
explained by research assistants, all of whom were regis-
tered nurses. Sometimes patients completed the instruments
on their own but often the research assistants assisted in
instrument completion. The same research assistants
abstracted clinical records to obtain information, such as
NYHA class, ejection fraction, and time since diagnosis.
Data were collected during 2011.
Ethical consideration
The Institutional Review Board of each centre approved the
study before data collection.
Data analysis
Descriptive statistics were used to describe the sociodemo-
graphic and clinical characteristics of the sample (mean, SD,
ranges, median, and interquartile ranges) and were used to
analyse the component scores. The relationships among the
theory components were analysed by Pearson’s r. Then the
hypothesized model (Figure 1) was tested using SEM. We used
SEM because it is particularly well-suited for simultaneously
investigating the nomological network among the different
constructs specified in the model. In this network, the first
series of paths corresponds to the posited relationship
between symptom monitoring and treatment adherence as
independent variables and symptom recognition and evalua-
tion as the dependent variable. A second series of paths corre-
sponds to the posited relationship between symptom
recognition and evaluation as an independent variable and
treatment implementation as the dependent variable. Finally,
a third series of paths corresponds to the posited relationship
between treatment implementation as independent variable
and treatment evaluation as the dependent variable
(Figure 1). This statistically powerful approach allowed us to
investigate the mediating role of symptom recognition and
evaluation and treatment implementation, which simulta-
neously act as both dependent and independent variables.
Using a multifaceted approach to the assessment of the
model fit (Tanaka 1993), taking into account the recommen-
dations of Hu and Bentler (Hu & Bentler 1998, 1999), the
following fit indices were considered: (i) chi square, (ii) Com-
parative Fit Index (CFI; (Bentler 1990)), (iii) Root Mean
Square Error of Approximation (RMSEA; (Steiger 1990)),
and (iv) Standardized Root Mean Square Residual (SRMR;
(J€oreskog & S€orbom 1993)). Overall model fit was judged
using these cut-off values: CFI � 0�95 (Hu & Bentler 1999),
RMSEA up to 0�05 and in the lower bound of the 90% CI
(Browne & Cudek 1993) and SRMR values below 0�08 (Hu & Bentler 1998, 1999) as indicating a good fit.
Power analyses for SEM models are complicated and often
rest on assumptions that are impractical or not viable. We
followed the practice recommended by Jaccard and Turrisi
(Jaccard &Wan 1996) that provides a rough sense of statisti-
cal power by applying power analytic methods for ordinary
least squares regression as applied to selected linear equations
from the set of linear equations implied by the model in ques-
tion. To determine an appropriate sample size, in fact, struc-
tural equation modeling requires that in addition to
statistical power, issues of the stability of the covariance
matrix and the use of asymptotic theory be taken into
account. In terms of power, it is difficult to evaluate the
power associated with specific path coefficients in complex
SEM models because of the large number of assumptions
about population parameters that must be made. A rough
approximation of power can be obtained by using a limited
information approach with single indicators of the path mod-
els implied by Figure 1. This permits the use of traditional
power analysis software to gain a sense of sample size
demands (Jaccard & Wan 1996). For a multiple regression
analysis with four predictors where the squared multiple cor-
relation is 0�30 and where one wants to detect a predictor
that accounts for at least 5% unique variance in the outcome,
the required sample size to achieve power of 0�80 is approxi-
mately 115. Moreover, Barret (Barret 2007) suggested the
use of the rule of a minimum of 200 subjects, since power
analysis is too complex in SEM. Overall our sample size of
417 is more than adequate for detecting the effects. The Sta-
tistical Package for Social Science 19 and the Mplus 6�12 were the two software programs used to analyse the data.
Validity and reliability
The SCHFI v.6�2 has recently been retested for its psychomet-
ric properties both in American and Italian samples (Vellone
et al. 2012a) and shown to have adequate validity and reli-
ability. Before its use the Italian SCHFI v.6�2 underwent
back-translation procedures to assure the equivalence
between the English and the Italian version. Specifically, the
SCHFI v.6�2 was translated from English into Italian by two
Italian nurses with expertise in English medical terminology.
Then, the translated version was back translated into English
by a bilingual English teacher and this version was reviewed
by the scale developer to check the accuracy of the transla-
tion. Some minor revisions were required to guarantee the
© 2013 Blackwell Publishing Ltd 2485
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same meaning of each item. Construct validity of the SCHFI
v.6�2 Italian version showed the following fit indices: v2
(28,330) = 39�23; P = 0�08; CFI = 0�97; NNFI = 0�95; RMSEA = 0�035 for the self-care maintenance scale, v2
(8,359) = 12�35; P = 0�14; CFI = 0�99; NNFI = 0�98; RMSEA = 0�040 for the self-care management scale, v2
(8,330) = 9�69; P = 0�28; CFI = 0�99; NNFI = 0�99; RMSEA = 0�025; SRMR = 0�030 for the self-care confidence
scale. Internal consistency reliability tested by the factor
score determinacy coefficient was between 0�77–0�91 for the
three scales.
Results
Participant characteristics
The sample of 417 participants enrolled in the study were
mostly older (59% over 72 years) and male (Table 2). The
level of education was quite low in the sample, with almost
three quarters educated at an elementary or middle school
level. Half of the participants were married and 84�4% were unemployed or retired. All of the NYHA classes were
represented in the sample with most individuals in classes II
and III. The mean ejection fraction was 42% and the med-
ian illness duration was 4 years.
Model component scores of the situation-specific theory
of HF self-care
Table 3 reports the model component scores. Symptom mon-
itoring and treatment implementation had the lowest score
while treatment adherence, symptom recognition and evalua-
tion, and treatment evaluation had higher scores. However,
all scores were less than adequate judged at a cut-point of 70
of the maximum of 100 (Riegel et al. 2009).
Correlations among the model components of the
situation-specific theory of HF self-care
The correlation matrix illustrating the relationships among
the components is shown in Table 4. All components were
significantly intercorrelated, although none were so highly
correlated as to suggest multicollinearity. Only the correla-
tion between treatment adherence and treatment evaluation
was not statistically significant.
Testing of the situation-specific theory of HF self-care
The model specified according to Figure 1 showed an
unsatisfactory fit: v2(5) = 76�21, P < 0�01; CFI = 0�74;
RMSEA = 0�185 (90% CI = 0�149–0�223); SRMR = 0�097. Inspection of the modification indices revealed two signifi-
cant direct, positive relationships: symptom monitoring on
treatment implementation and symptom recognition and
evaluation on treatment evaluation. Furthermore, there was
evidence of a significant correlation between treatment
evaluation and symptom monitoring. The revised model
with the three new parameters provided a good fit to the
data as revealed by these fit indices: v2(2) = 7�65, P 0�02; CFI = 0�98; RMSEA = 0�08 (90% CI = 0�027–0�148),
Table 2 Sociodemographic and clinical characteristics of the
sample (N = 417)
Variables N (%)
Gender
Male 241 (57�8) Female 176 (42�2) Age (Mean–SD) 72�3 (12�2)
Education
Elementary 208 (49�9) Middle School 101 (24�2) Professional School 30 (7�2) High School 46 (11�0) University Degree 42 (7�7)
Marital Status
Married 223 (53�5) Single 38 (9�1) Widowed 127 (30�5) Divorced 29 (7�0)
Profession
Employed 65 (15�6) Unemployed or retired 352 (84�4)
NYHA Class
I 48 (11�5) II 144 (34�5) III 167 (40�0) IV 58 (13�9)
Ejection Fraction (%) (Mean–SD) 41�8 (14�0) Years Since Diagnosis (Median–Interquatile ranges) 4�0 (2–6)
NYHA, New York Heart Association.
Table 3 Model component scores of the situation-specific theory
of HF self-care
Components Mean (SD) Ranges
Symptom monitoring 49�3 (26�0) 0–100
Treatment adherence 57�5 (17�2) 16�7–100 Symptom recognition and evaluation 56�0 (29�8) 0–100
Treatment implementation 48�6 (24�5) 0–100
Treatment evaluation 62�6 (24�7) 0–100
Components’ score were standardized on a 0–100 where higher
scores mean higher self-care.
2486 © 2013 Blackwell Publishing Ltd
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SRMR = 0�023. As shown in Figure 2, results of this model
confirmed that symptom monitoring correlates with treat-
ment adherence (Hypothesis 1), that symptom monitoring
and treatment adherence have a direct, positive relationship
with symptom recognition and evaluation (Hypothesis 2),
that symptom recognition and evaluation have a direct,
positive relationship with treatment implementation
(Hypothesis 3) and that treatment implementation has a
direct, positive relationship with treatment evaluation
(Hypothesis 4). In addition to the initial model, we found
that symptom monitoring has a direct, positive relationship
with treatment implementation and that symptom recogni-
tion and evaluation has a direct, positive relationship with
treatment evaluation. Finally this model showed a positive
correlation between symptom monitoring and treatment
evaluation. This model explained 17% of the variance in
symptom recognition and evaluation, 16% of treatment
implementation, and 25% of treatment evaluation.
Discussion
To our knowledge, this is the first study using SEM to
explore relationships among dimensions of the self-care
maintenance and self-care management components of the
situation-specific theory of HF self-care. Overall, using SEM
we were able to confirm the situation-specific theory of HF
self-care as proposed and added three additional paths to
the theory.
As theorized, symptom monitoring and treatment adher-
ence were correlated, confirming the coexistence of these
two components of the self-care maintenance construct. At
least in HF, symptom monitoring is a behaviour recom-
mended for patients so that they recognize physiologic
decompensation quickly. As symptom monitoring is a
behaviour to which patients should adhere, it is not surpris-
ing that these two concepts would be significantly related.
Symptom monitoring and treatment adherence together
had a direct, positive relationship with the symptom recogni-
tion and evaluation components of the model. Several studies
have been conducted to identify variables influencing symp-
tom recognition (Patel et al. 2007, Hedemalm et al. 2008,
Jurgens et al. 2009, Riegel et al. 2010a, Dickson et al. 2011,
Rushton et al. 2011). In various studies age, (Riegel et al.
2010a) physical symptom distress, lower anxiety, (Jurgens
et al. 2009), and comorbidity, (Dickson et al. 2011, Rushton
et al. 2011) all have been found to be associated with symp-
tom recognition. The only study demonstrating that symp-
tom monitoring and treatment adherence were associated
with symptom recognition and evaluation was a study dem-
onstrating that immigrants to Sweden were unaware of the
connection of their symptoms with HF (Hedemalm et al.
2008), which led to delays in treatment implementation and
help seeking behaviour (Patel et al. 2007).
Results of our study also showed that treatment imple-
mentation was influenced not only by symptom recognition
and evaluation, as the theory states, but even more by
symptom monitoring. This modification to the initial model
sheds new light on patients’ actions in response to
symptoms (reducing salt in the diet, drinking less water,
Table 4 Correlation Matrix of the model components of the situ-
ation-specific theory of HF self-care
Components 1 2 3 4 5
1. Symptom Monitoring 1
2. Treatment Adherence 0�41** 1
3. Symptom Recognition
and Evaluation
0�34** 0�35** 1
4. Treatment
Implementation
0�38** 0�23** 0�23** 1
5. Treatment
Evaluation
0�25** 0�05 0�28** 0�47** 1
**P < 0�01.
0·24
0·34
0·410·12
0·16
0·42
0·25
0·10
Symptom monitoring
Symptom recognition
and evaluation
Treatment implementation
Treatment evaluation
Treatment adherenceFigure 2 The situation-specific theory of
heart failure self-care as tested by the SEM.
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taking an extra water pill, and contacting the provider for
help) because not only symptom recognition and evaluation
have a direct, positive relationship with treatment actions
but also the monitoring of symptoms. Even though it is log-
ical that treatment implementation follows an evaluation of
symptoms, no studies have previously demonstrated this
relationship in HF.
A moderate amount of the variance in treatment evalua-
tion was explained by treatment implementation. That is,
people with HF who were likely to implement a treatment
when symptoms occurred were also better at evaluating
them. And, differently from the theory, symptom monitor-
ing had a direct, positive relationship with treatment imple-
mentation and not only with symptom recognition and
evaluation. This relationship is reasonable because the eval-
uation of treatments is based on symptoms. Again, apart
from the specific-situation theory of HF self-care, there are
no prior studies demonstrating that treatment evaluation in
HF is determined by treatment implementation and symp-
tom recognition and evaluation.
In addition to demonstrating that symptom monitoring
had a direct, positive relationship with treatment implemen-
tation, we also found that symptom monitoring correlated
with treatment evaluation. That is, people good at monitor-
ing their symptoms were also good in evaluating the treat-
ments they tried. These behaviours are consistent with the
description of the ‘Expert’ typology developed by Dickson
and colleagues (Dickson et al. 2008). In this study, experts
were proficient in self-care management, were able to link
symptoms with the HF pathophysiology and knew that eat-
ing salty food and experiencing overexertion preceded fluid
retention. Experts felt also a positive attitude towards self-
care (Dickson et al. 2008).
Limitations
Even though participants were selected from several cardio-
vascular ambulatory clinics across Italy, this was a conve-
nience sample of adults with HF. Another limitation is that
participants were all symptomatic, that is all reported prob-
lems breathing or ankle swelling in the last month, so the
study results apply only to HF patients who are symptom-
atic. Another limitation is that all participants were Italian
and cultural characteristics are known to influence self-care
(Chaudhry et al. 2011). So, the generalizability of the study
results to other cultures should be done with caution.
Undoubtedly, the cross-sectional nature of our data does
not allow us to draw alternative causal relations among our
variables, even though the posited model is strongly
grounded in prior theory (Riegel & Dickson 2008).
What is already known about this topic
● Self-care of heart failure can improve patients’ quality
of life and reduce hospitalization, mortality, and emer-
gency department visits.
● Several authors have proposed theories of heart failure
self-care but only the situation-specific theory of heart
failure self-care by Riegel and Dickson is focused on
the process that patients use to perform self-care.
● Some individual propositions of the situation-specific
theory of heart failure self-care have been tested statis-
tically and supported but the full model has not been
tested with structural equation modelling.
What this paper adds
● The structural equation model supports the situation-
specific theory of heart failure self-care.
● Symptom monitoring correlates with treatment adher-
ence; symptom monitoring and treatment adherence
have a direct, positive relationship with symptom rec-
ognition and evaluation that in turn have a direct,
positive relationship with treatment implementation;
treatment implementation has a direct, positive rela-
tionship with treatment evaluation.
● Three new relationships have been identified that
strengthen the situation-specific theory of heart failure
self-care: (i) symptom monitoring has a direct, positive
relationship with treatment implementation; (ii) symp-
tom recognition and evaluation have direct, positive
relationships with treatment evaluation; and (iii) symp-
tom monitoring correlates with treatment evaluation.
[Correction added on 9th April 2013, after first online
publication: ‘. . .symptom monitoring correlates with
treatment implementation.’ has been corrected to read
‘. . .symptom monitoring correlates with treatment
evaluation.’]
Implications for practice and/or policy
● The situation-specific theory of heart failure self-care
by Riegel and Dickson explains and predicts the rela-
tionships among symptom monitoring, treatment
adherence, symptom recognition and evaluation, treat-
ment implementation, and treatment evaluation.
● Symptom monitoring, treatment adherence, and symp-
tom recognition and evaluation are the most important
elements of the self-care process for clinicians to focus
on improving if they hope to improve outcomes in
heart failure patients.
● The situation-specific theory of heart failure self-care
can guide clinical practice with heart failure patients.
2488 © 2013 Blackwell Publishing Ltd
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Future research
Testing the situation-specific theory of HF self-care in this
manner can help to build a broader theory of HF self-care
with additional predictors and outcomes. For example,
since a relatively small amount of the variance in symptom
recognition and evaluation was explained by symptom
monitoring and treatment adherence, clearly other variables
predict the rest of the variance. Investigators have already
identified older age, symptom distress, lower anxiety, immi-
gration, and comorbidity as predictors of symptom recogni-
tion (Patel et al. 2007, Hedemalm et al. 2008, Jurgens
et al. 2009, Riegel et al. 2010a, Dickson et al. 2011, Rush-
ton et al. 2011). The same can be said for treatment imple-
mentation and treatment evaluation.
Further studies should be conducted with self-care confi-
dence since the moderator and the mediator role of this vari-
able is still uncertain. Even though we know that self-care
confidence moderates the relationship between self-care and
HF costs (Lee et al. 2007) and self-care confidence mediates
the relationship between social support and self-care (Salyer
et al. 2012) the role of self-care confidence in HF patients is
still understudied. Future studies might also explore the effect
of cognitive impairment on the various components of the
self-care process since it has been shown that cognitive impair-
ment affects self-care management (Lee et al. 2012). Finally,
since our data were cross-sectional, future longitudinal and
experimental studies would strengthen the tested model.
Conclusion
Results of this study give more strength to the situation-
specific theory of HF self-care in predicting HF patients’
behaviours for guiding clinical practice. Using these
results, healthcare providers have a ‘picture’ of how self-
care works for patients. As theorized by Riegel and Dick-
son (2008) self-care in HF is a process of subsequent
phases and these phases, some newly identified in this
study, have been found to be statistically related. From a
clinical perspective this study emphasizes how important it
is to educate patients to monitor HF symptoms (e.g.
checking the body weight and ankles for swelling every
day) and to adhere to HF treatments (e.g. taking medica-
tions regularly, attending healthcare provider visits, exer-
cising, reducing salt in the diet) since these two
components influence the subsequent phases of the self-
care process. Helping patients to build skill in symptom
monitoring could improve the recognition and evaluation
of HF symptoms, (e.g. problems breathing and ankle
swelling) as already stated in the theory, but also increase
the probability of treatment implementation when symp-
toms occur. The importance of symptom monitoring
(weight monitoring) in preventing emergency department
visits and hospitalization was demonstrated in a recent
study (Jones et al. 2012). Education in symptom monitor-
ing could also improve patients’ abilities to evaluate the
effectiveness of treatment, providing security that the
implemented treatment was effective.
In conclusion, it appears from our analysis that it is
essential for patients to adhere to treatments, monitor the
symptoms of HF, and recognize changes quickly if they are
to be successful in self-care. In fact, these three self-care
components directly and indirectly influence the rest of the
self-care process. Nevertheless, it is a challenge for patients
to constantly adhere to HF treatments; a recent study
showed that only 9�1% of HF patients adhere with every
recommended self-care behaviour (Marti et al. 2012).
Symptom recognition is also a challenge for elderly people
and for those with high comorbidity (Riegel et al. 2010b,
Lam & Smeltzer 2012). However, both treatment adher-
ence and symptom recognition have been identified as key
components to improve patients’ outcomes, so renewed
efforts are needed in these specific areas (Lam & Smeltzer
2012, Wu et al. 2012).
Overall, the components of self-care and their relation-
ships as described by the situation-specific theory of HF
self-care and as tested in this study provide researchers and
clinicians with a framework for developing further knowl-
edge about HF self-care and for predicting and improving
HF patients’ outcomes.
Funding
This work was funded by the Italian Center of Excellence
for Nursing Scholarship, Rome, Italy.
Conflict of interest
No conflict of interest has been declared by the authors.
Author contributions
All authors have agreed on the final version and meet at least
one of the following criteria (recommended by the ICMJE*):
● Substantial contributions to conception and design,
acquisition of data, or analysis and interpretation of
data.
● Drafting the article or revising it critically for impor-
tant intellectual content.
*http://www.icmje.org/ethical_1author.html
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