Support Care Cancer (2013) 21:2527–2535
DOI 10.1007/s00520-013-1824-5
ORIGINAL ARTICLE
Association between hope and burden reported
by family caregivers of patients with advanced cancer
Inger Utne & Christine Miaskowski & Steven M. Paul &
Tone Rustøen
Received: 14 August 2012 / Accepted: 12 April 2013 / Published online: 27 April 2013
# Springer-Verlag Berlin Heidelberg 2013
Abstract
Purpose The aim of this study, in a sample of family caregivers (FCs) of patients with advanced cancer, was to describe the level of FC burden using the Caregiver Reaction
Assessment (CRA). In addition, the effects of select FC and
patient characteristics on each of the CRA subscales were
evaluated.
Methods FCs and patients (n =112) completed a demographic questionnaire, and Herth Hope Index, and the Hospital Anxiety and Depression Scale. FCs completed the
CRA. Data were analyzed using multiple linear regression
analyses.
Results For three of the five CRA subscales (i.e., “impact on
finances”, “impact on daily schedule”, and “impact on
health”), the mean scores were comparable to a Norwegian
sample of FCs caring for patients in the late palliative phase.
The variance in each of the CRA subscales was explained
by different factors. Total explained variance ranged from
5.5 % (“lack of family support”) to 31.8 % (“impact on daily
schedule”). FC characteristics, such as being female and
lower educational level, distress regarding the patient’s pain,
anxiety, depression, and level of hope, as well as the
I. Utne (*)
Faculty of Health Science, Oslo and Akershus University College
of Applied Science, Oslo, Norway
e-mail: [email protected]
C. Miaskowski : S. M. Paul
Department of Physiological Nursing, University of California,
San Francisco, CA, USA
T. Rustøen
Division of Emergencies and Critical Care, Department of
Research and Development, Ullevål, Oslo University Hospital,
Oslo, Norway
T. Rustøen
Lovisenberg Diaconal University College, Oslo, Norway
patients’ number of comorbidities, depression, and hope
contributed to an increase in various domains of FC burden.
FCs’ level of hope was a significant predictor for three of
the CRA subscales (i.e., “self-esteem”, “lack of family support”, and “impact on health”).
Conclusions Findings suggest that FCs’ and patients’ level
of hope are important determinants of caregiver burden and
that FCs with lower levels of hope represent a high-risk
group for higher levels of caregiver burden.
Keywords Oncology . Family caregiver . Burden . Hope .
Cancer pain
Introduction
Caregiver burden is defined as the overall consequences associated with a demanding and stressful caregiver situation
[1]. FCs experience numerous difficulties and increased responsibilities during and after the patient’s cancer treatment
and rehabilitation [2, 3]. Both FC and patient characteristics
are known to impact the FCs’ experience of burden. Caregiver
characteristics associated with increased burden include younger age [4], being female [4], lower level of education [5],
living alone with the patient [6], having a distressed relationship [6, 7], as well as higher levels of anxiety [2, 8] and
depression [2, 8, 9]. For example, in one study [2], prevalence
rates for depression in FCs ranged from 20 to 73 % and
depressive symptoms had negative effects on FC outcomes.
In another study [10], caregiving for palliative care patients
with cancer had a negative impact on FCs’ mental and physical health, and FCs’ depression was the primary variable
associated with caregiver burden [9]. Finally, Cameron and
colleagues [11] reported that FCs with lower levels of education reported higher levels of emotional distress associated
with the caregiving experience.
2528
Patients characteristics including dependency [6, 12], and
care characteristics such as intensity of care [6], and deterioration of physical and mental function [13] are associated
with increased caregiver burden. For example, Kurtz and
colleagues [14] found that FCs who cared for depressed
patients reported a greater impact on their schedule. In
addition, increased symptoms, physical needs, and poorer
performance status had a negative impact on FCs’ level of
family support, finances, and schedule.
The Caregiver Reaction Assessment (CRA) [15] was
used in most of the aforementioned studies to evaluate
caregiver burden [1, 2, 6, 8, 12, 14]. Across these studies,
FC characteristics were used as the primary predictors of FC
burden. In addition, most of these studies assessed FCs of
newly diagnosed patients or those with recurrent disease.
Only one study evaluated FCs of patients with advanced
cancer [8]. In an extensive review of family caregiving, the
authors [3] noted that it is likely that variations exist in
symptoms, problems, and responsibilities depending on the
severity of patient’s illness.
Hope is considered an important factor in patients’ personal
adjustments during times of loss, uncertainty, and suffering
[16]. It is an essential element in the lives of people with
cancer [17] and in cancer patients with pain [18]. Hope is
considered an effective coping strategy for oncology patients
because it provides adaptive power to help them get through
difficult situations, achieve meaning, and achieve desired
goals [19–22]. In addition, in a recent metasynthesis of the
experience of hope in FCs of persons with chronic illnesses,
including cancer [23], the authors described the importance of
hope to FCs regardless of age, relationship, or setting. In a
study of FCs of palliative patients [24], FCs reported lower
levels of hope than the patients.
While numerous studies documented significant problems
and distress in FCs of oncology patients [24, 25], no study was
found that evaluated the influence of both patients’ and FCs’
level of hope on FCs’ evaluation of burden. However, as
optimism is described as a central part of hope [26, 27], it is
interesting to note that in a study of FCs of outpatients receiving chemotherapy [12], FCs who were more optimistic
reported lower levels of caregiver burden. Therefore, based
on the fact that hope is essential for oncology patients and
their FCs, we hypothesized that both patients’ and FCs’ level
of hope will influence FCs’ perceptions of burden.
Given the importance of FCs in cancer care, the limited
number of studies of FCs of patients with advanced cancer,
the limited number of studies that evaluated the impact of
both FC and patient characteristics on FCs’ burden, the
importance of hope in the lives of oncology patients and
their FCs, and the fact that the influence of patients’ and
FCs’ level of hope on FCs’ burden have not been investigated, additional studies are needed that incorporate all of
these potential predictors. Therefore, the purposes of this
Support Care Cancer (2013) 21:2527–2535
study in a sample of FCs of patients with advanced cancer
were to describe the level of FC burden using the CRA and
to evaluate the effects of select FC and patient characteristics on each of the CRA subscales.
Methods
This study is part of a randomized clinical trial that evaluated the efficacy of the Norwegian version of the PROSELF© Pain Control Program (PRO-SELF© PCP-N) in
oncology outpatients with pain from bone metastasis. The
PRO-SELF© PCP-N was adapted for this Norwegian sample based on the work of Miaskowski and colleagues [28]. A
detailed description of the PRO-SELF© intervention was
published previously [29].
Participants
A total of 179 oncology outpatients (>18 years old), who
experienced pain from bone metastasis, with a Karnofsky
Performance Status (KPS) score of >50; an average pain
intensity score of >2.5 on a 0 to 10 numeric rating scale
(NRS); and radiographic evidence of bone metastasis participated in the study. Of these patients, 112 (62.6 %) had a
FC who participated in this study. FCs were identified by the
patients as the person most involved in their care.
Study procedures
This study was approved by the Regional Medical Research
Ethics Committee, Health Region II (South) of Norway and
the Norwegian Social Science Data Services. Written informed consent was obtained from patients and FCs. For
the purposes of this paper, enrollment data from 112 dyads
were analyzed. Patients and FCs completed the enrollment
questionnaires during the initial home visit before the start
of the intervention.
Instruments
FC and patient questionnaires
Demographic characteristics obtained information on age,
gender, educational level, marital status, employment status,
and relationship between the FC and the patient.
Hope was measured using the Norwegian version of the
Herth Hope Index (HHI) [30]. Each item is rated on a 4point Likert scale that ranges from “strongly disagree (1)” to
“strongly agree (4)”. A total HHI score that can range from
12 to 48 is calculated and higher scores indicate higher
levels of hope. The validity and reliability of the HHI is
well established [18, 31–34].
Support Care Cancer (2013) 21:2527–2535
2529
Anxiety and depression were measured using the Hospital Anxiety and Depression Scale (HADS) [35, 36]. Each
item is scored from 0 (minimally present) to 3 (maximally
present) with higher scores indicating higher levels of anxiety and depression. Validity and reliability of the HADS is
well established.
0 (no pain) to 10 (the worst pain I can imagine) NRS.
Number of comorbidities was measured by answering
yes/no to whether or not the patient had 13 different illnesses. Functional status was assessed by the research nurse,
using the valid and reliable Karnofsky Performance Status
scale [44–47].
FC questionnaires
Statistical analyses
Self-assessed health was measured using one item from the
30-item European Organization for Research and Treatment
of Cancer Quality of Life Questionnaire (EORTC QLQ-C30)
[37]. FCs were asked to respond to the following question
“How would you rate your overall health during the past
week?” using a 1 (very poor) to 7 (very satisfied) scale.
Distress associated with the patient’s pain was measured
using one item from the Pain Experience Scale [38]. This
item assessed pain-related distress in the FC (i.e., “How
disturbing/upsetting is the patient’s pain to the FC?”), using
a 0 (not at all) to 10 (very much) NRS.
Satisfaction with life was measured using one item. FCs
were asked to respond to the following question “When you
think about how you are doing, are you in general satisfied
with life, or in general dissatisfied? “ using a 1 (extremely
satisfied) to 7 (extremely dissatisfied) scale.
Caregiver Reaction Assessment—caregiver burden was
evaluated using the 24-item CRA [39]. This instrument evaluates multiple dimensions of the FCs’ experience [15] and is
scored into five domains: self-esteem (seven items), lack of
family support (five items) that aims to assess the perceived
lack of help in delivering care by the FC, impact on finances
(three items) that measures financial strain on the caregiver,
impact on daily schedule (five items) that measures the extent
to which caregiving interrupts the usual daily activities, and
impact on health (four items) that aims to measure the FCs’
feeling of deterioration in physical health. Each item is rated
on a 5-point Likert scale that ranges from “strongly disagree
(1)” to “strongly agree (5)”. The subscale caregiver's selfesteem aims to measure positive experiences of caregiving,
(i.e., the extent to which caregiving imparts individual selfesteem; a lower score indicates higher burden). The other four
subscales assess negative experiences of caregiving (i.e.,
higher scores indicate higher level of burden). A mean score
for each subscale is created that can range from 1.0 to 5.0. The
CRA has well-established validity and reliability in FCs of
patients with cancer in different stages of the disease [6,
40–42], including advanced cancer [41].
Data were analyzed using SPSS Version 18.0 (SPSS Inc,
Chicago, IL). Descriptive statistics were generated to characterize the FCs and the patients and CRA subscales.
In order to develop the most parsimonious model for each
of the CRA subscales, the regression analyses proceeded in
two stages. In the first stage, the FC variables that were
hypothesized to be associated with caregiver burden (i.e.,
gender, age, lives with the patient, education, HHI total scores,
HADS scores, self-assessed health, satisfaction with life, and
how distressing the patients’ pain was for FCs) were entered
into the regression model simultaneously. Variables were removed sequentially until the most parsimonious model was
identified. In the second stage, select patient variables (i.e.,
KPS score, worst pain score, number of comorbidities, HHI
total scores, and HADS scores) were added along with the FC
variables that were retained in the first stage. To construct the
final model, variables were systematically removed until the
most parsimonious model was obtained. In order to include
education in the regression analyses, this variable was dummy coded into a set of three dichotomous variables (i.e.,
secondary versus primary school, college <4 years versus
primary school, and college >4 years versus primary). A p
value of <0.05 was used to determine statistical significance.
Patient questionnaires
Self-assessed worst pain in the past 24 h was measured
using a single item from the Norwegian version of the Brief
Pain Inventory (BPI-N) [43]. Worst pain was rated on a
Results
Demographic and clinical characteristics of the FCs As
shown in Table 1, the majority of the FCs was female
(60 %) with a mean age of 63.1 years (SD=10.7). Almost
all of the FCs (94 %) were married to the patients. FCs
reported their own mean health status as 5.4 (SD=1.3), satisfaction with life as 3.2 (SD=1.1), and distress associated with
the patient’s pain as 5.5 (SD=2.9). The mean HHI total score
was 36.8 (SD=4.0). Mean scores for anxiety and depression
were 13.7 (SD=3.7) and 11.4 (SD=3.4), respectively.
Demographic and clinical characteristics of the patients As
shown in Table 1, the majority of the patients was male
(57 %) with a mean age of 64.6 years (SD=12.3). The most
prevalent type of cancer was prostate (42 %), mean KPS
score was 71.3 (SD = 8.0), and the mean number of
comorbidities was 0.8 (SD=1.0). Patients’ mean worst pain
scores as 6.8 (SD=1.9). Mean HHI total score was 37.4 (SD
2530
Characteristics
Family caregivers (n=112)
Mean (SD)
Age (years)
63.1 (10.7)
Worst pain (0 to 10)
Number of comorbidities (0–13)
Karnofsky Performance Status score (0–100)
Self-assessed health (1–7)
Satisfaction with life (1–7)
Distress about patient’s pain (0–10)
Hope (12–48)
Anxiety (0–21)
Depression (0–21)
Gender
Education
Employment status
Relationship to the patient
Cancer diagnosis
CRA subscale scores As shown in Fig. 1, the mean scores
for each of the negative domains ranged from 1.8 (SD=0.6)
on the subscale “lack of family support” to 2.7 (SD=0.9) on
the subscale “impact on daily schedule”. The mean score on
the self-esteem subscale was 4.1 (SD=0.6).
Predictors of caregiver burden for each of the CRA
subscales Table 2 presents the results of the multiple regression analyses for the five domains evaluated using the CRA.
Each domain of FC burden was explained by different FC
and patient factors with a total explained variance ranging
from 5.5 % (“lack of family support”) to 31.8 % (“impact on
daily schedule”).
5.4 (1.3)
3.2 (1.1)
5.5 (2.9)
36.8 (4.0)
13.7 (3.7)
11.4 (3.4)
N (%)
45 (40)
67 (60)
55 (50)
15 (14)
19 (17)
37.4 (4.4)
12.4 (3.2)
11.7 (3.1)
N (%)
64 (57)
48 (43)
13 (11)
51 (46)
22 (20)
21 (19)
25 (23)
7 (6)
47 (42)
35 (31)
19 (17)
11 (10)
Lack of family support Only 5.5 % of the variance in lack of
family support was explained in the final model and all of
5
4
3
2
1
0
m
pp
ly
mi
f fa
c
La
t
or
tee
Es
ko
Self-esteem In the final model, 6.2 % of the variance in selfesteem was explained by FCs’ level of hope. FCs with
higher levels of hope reported higher self-esteem scores.
64.6 (12.3)
46 (41)
14 (12)
38 (34)
13 (13)
105 (94)
Child/sibling/other
Prostate
Breast
Other
Colon
=4.4). Mean scores for anxiety and depression were 12.4
(SD=3.2) and 11.7 (SD=3.1), respectively.
Patients (n=112)
Mean (SD)
6.8 (1.9)
0.8 (1.0)
71.3 (8.0)
Male
Female
Primary school
Secondary school
University/college<
4 years
University/college>
4 years
Working full/part time
Sick leave/welfare
Retired
Other
Spouse
Mean score
Table 1 Demographic characteristics of the family caregivers
(n=112) and demographic and
clinical characteristics of the oncology patients with advanced
cancer (n=112)
Support Care Cancer (2013) 21:2527–2535
ct
pa
Im
f
on
es
nc
ina
su
ct
pa
Im
ule
lth
ea
ed
ch
s
on
nh
o
ct
pa
Im
Fig. 1 Subscale scores for the Caregiver Reaction Assessment. All
values are plotted as means and standard deviation
Support Care Cancer (2013) 21:2527–2535
the variance was explained by FCs’ level of hope. FCs with
lower levels of hope perceived less family support.
Impact on finances In the final model, 20.3 % of the variance in impact on finances was explained by FCs’ level of
depression, their level of education, and patients’ number of
comorbidities. Overall, education uniquely explained 9.3 %
of the variance. Specifically, a college education of >4 years
compared with primary school uniquely explained 7.2 % of
the variance in impact on finances. FCs with >4 years of
college education compared to those with only primary
school, reported less financial strain. FCs’ level of depression explained 5.5 % of the variance. FCs who had a higher
level of depression reported higher financial strain.
Impact on daily schedule In the final model, 31.8 % of the
variance in impact on schedule was explained by FCs’ level
of anxiety and distress associated with the patients’ pain and
patients’ level of depression. FCs’ anxiety uniquely
explained 14.1 % of the variance in impact of daily schedule
and their distress about the patients’ pain explained 3.1 %.
Patients’ depression uniquely explained 3.9 % of the variance. FCs who had a higher level of anxiety and were more
distressed about the patients’ pain, and who took care of
patients with higher levels of depression, reported a greater
level of impact on daily schedule.
Impact on health In the final model, 27.9 % of the variance
in impact on health was explained by FCs’ gender, hope,
and distress, and patients’ depression and hope. FCs’ gender
uniquely explained 5.0 % of the variance in impact on health
and FCs’ hope uniquely explained 9.3 %. The patients’
depression uniquely explained 6.5 % of the variance in
impact on health and their hope uniquely explained 6.6 %.
FCs who were women and those with a lower level of hope,
and those who took care of patients with a higher level of
depression and hope perceived more impact on health.
Discussion
This study is the first to assess factors associated with caregiver burden in FCs of advanced cancer patients and to
include both patients’ and FCs’ level of hope in these analyses. A variety of patient and FC characteristics explained
variations in the different domains of burden. Findings from
this study suggest that FCs’ and patients’ level of hope are
important determinants of three domains of caregiver burden.
Similar to a previous study of terminally ill cancer patients
[42], the variance in each of the domains of the CRA was
explained by different factors, with total explained variance
ranging from 5.5 % (lack of family support) to 31.8 % (impact
on daily schedule). In contrast, in a study of newly diagnosed
2531
patients with colorectal cancer [6], the total explained variance
ranged from 11 to 46 % (see Table 3). The differences across
these studies may be partly explained by the different predictors that were evaluated. Alternatively, different FC and
patient characteristics may contribute to different aspects of
caregiver burden depending on the stage of the patient’s
illness, the health status of the FC, as well as the duration
and demands of caregiving [5].
An important contribution of this study is its evaluation of
the impact of hope on caregiver burden. Of note, FCs’ level of
hope explained between 6.2 and 9.3 % of the variance in three
of the CRA subscales (i.e., self-esteem, lack of family support,
and impact on health). In fact, hope was the only significant
predictor for the self-esteem and lack of family support subscales and explained the largest amount of the variance in
impact on health. FCs with a higher level of hope, tended to
appraise their caregiving experience more positively, had more support from their family, and experienced less health
problems. Hope is known to be an effective coping strategy
for oncology patients because it provides adaptive power to
help them get through difficult situations, achieve meaning,
and achieve desired goals [19–22]. Therefore, it is possible
that hope is an effective coping strategy for FCs as well. This
hypothesis is supported by Mechanic [48] who noted that one
important function of the coping process was to maintain a
state of psychological equilibrium to better meet external demands. Higher levels of hope might assist FCs with adjustments to the caregiving situation and be associated with better
caregiver outcomes.
An alternative hypothesis is that hope may be linked to
the personality characteristic of optimism that partially explains who does and does not adapt to the demands of
caregiving. As optimism is described as a central component
of hope [26, 27], it is interesting to note that Given and
colleagues [12] reported that FCs who remain optimistic
may interpret the cancer experience less negatively and keep
stressors within manageable bounds. Consistent with our
study findings, FCs with higher levels of optimism reported
less impact on their health and daily schedule [12]. These
findings suggest that FCs’ personality characteristics that
are relatively stable over time, can moderate FCs’ distress,
and help FCs to adapt to the caregiving situation.
The importance of hope is consistent with previous studies that explored FCs’ perspectives on hope. For example, in
a study of FCs’ experiences of caring for terminally ill
patients [49], hope served as a buffer to stress and was a
significant factor in FCs’ physical and mental well-being. In
addition, findings from studies of FCs of advanced cancer
patients suggest that hope is important for dealing with the
caregiver experience [50, 51]. Duggelby and colleagues [52]
noted in their metasynthesis, that hope was associated with
higher levels of physical and psychosocial well-being, and
social network was an important factor for FC’s hope.
2532
Table 2 The effect of family
caregiver (FC) and patient characteristics on each of the subscales of the caregiver reaction
assessment
Support Care Cancer (2013) 21:2527–2535
Source
R2
Dependent variable: self-esteem
Overall model
.062
Hope (FC)
Dependent variable: lack of family support
Overall model
.055
Hope (FC)
Dependent variable: impact on finances
Overall model
.203
Depression (FC)
Education (FC)
Secondary vs primary
College <4 years vs primary
College >4 years vs primary
Number of comorbidities (patient)
r
Beta
R2 change
df
F value
p value
.249
.249
.062
1,104
1,104
6.86
6.86
.010
.010
6.0
6.0
.016
.016
−.234
−.234
.055
1,104
1,104
.217
.236
.147
−.103
−.307
.229
.060
−.126
−.295
.174
.055
.093
.003
.014
.072
.028
5,103
1,103
3,103
1,103
1,103
1,103
1,103
5.260
7.091
4.011
.415
1.772
9.321
3.561
<.001
.009
.010
.521
.186
.003
.062
.397
.190
.204
.141
.031
.039
3,98
1,98
1,98
1,98
15.26
20.349
4.435
5.641
<.001
<.001
.038
.019
.236
−.316
.168
.286
.294
.050
.093
.025
.065
.066
5,95
1,95
1,95
1,95
1,95
1,95
7.362
6.641
12.292
3.331
8.544
8.649
<.001
.011
.001
.071
.004
.004
Dependent variable: impact on daily schedule
Overall model
.318
Anxiety (FC)
.478
Distress (FC)
.365
Depression (patient)
.291
Dependent variable: impact on healtha
a
Self-assessed health was not
considered as one of the predictors of “Impact on Health”
Overall model
Female (FC)
Hope (FC)
Distress (FC)
Depression (patient)
Hope (patient)
Therefore, it is interesting to note that Park and colleagues
[42] found that having other caregivers to share the caregiving with seemed to be the single most important determinant
of caregiver burden. This finding is supported by Daly and
colleagues [53] who reported that caregiver social support
played the most significant role in predicting caregiver
burden. Additional studies on the influence of hope and
social support on caregiver burden are warranted.
The mean scores for the CRA subscales of impact on
finances, impact on daily schedule, and impact on health
were similar to those reported by FCs of palliative care
patients in Norway [8]. However, FCs in this study reported
lower levels of family support (1.8 (SD=.6)) than a comparable sample of Norwegians FCs (2.1 (SD=.7)) [8]. This
difference equates with a medium effect size (i.e., d=.50)
and may be partially explained by the fact that the FCs
studied by Grov and colleagues had more restrictions on
their social interactions because patients were in the late
palliative phase of their illness [54]. In addition, as the
physical and emotional demands of caregiving increase,
the need for emotional support increases [53, 55]. Although
the FCs in the two Norwegian samples [8] reported different
.279
.227
−.258
.298
.251
.077
levels of family support, it is interesting to note that across
studies of FCs of patients with advanced disease [8, 41],
family support was the subscale for which FCs reported less
burden.
In this study of FCs of palliative care patients as well as
in a study of FCs of terminally ill patients [42], and FCs of
newly diagnosed oncology patients [6], the only FC demographic characteristic associated with various domains of
caregiver burden across the studies listed in Table 3 was
education. Consistent with findings from Park and colleagues [42], higher levels of education were associated
with lower levels of FC burden. As noted by Grov and
colleagues [56], it may be easier for a well-educated person
to find and utilize help from others. However, Nijboer and
colleagues [6] found that FCs with more education reported
less self-esteem. In addition, consistent with two previous
reports [12, 14], FCs who cared for patients with higher
levels of depression felt a greater impact on their schedule
and on their health.
Findings from the studies reported in Table 3 [6, 42]
suggest that different FC, patients, and care characteristics
are associated with different domains of caregiver burden.
d
c
b
a
3.9
Depression (PT)
27.9
5.0
9.3
2.5d
6.5
6.6
Female (FC)
Hope (FC)
Distress (FC)
Depression (PT)
Hope (PT)
Care characteristics (changes in activities)
FC characteristics
Care characteristics (disease-related tasks, changes
in activities, accompany patients on visits)
FC characteristics
Dependency (PT)
Anxiety (FC)
Distress (FC)
2.8d
31.8
14.1
3.1
Number of comorbidities (PT)
Living situation (FC)
Quality of relationship (FC)
Education (FC)
Stoma (PT)
Income (FC)
Intensity of care
5.5
5.5
6.2
6.2
20.3
5.5
9.3
Depression (FC)
Education (FC)
Hope (FC)
Hope (FC)
Variable
Variable
% of
explained
variance
FCs of newly diagnosed oncology patientsa,b (n=148)
FCs of palliative care patients (n=112)
Not significant contribution to the final model
Park et al. [57]
Nijboer et al. [6, 39]
Variables which significantly contributed to the final model are listed in the table
Impact on health
Impact on daily schedule
Impact on finances
Lack of family support
Self-esteem
CRA subscales
9.0
23.0
13.0
24.0
46.0
7.0
15.0
11.0
6.0
5.0
15.0
10.0
5.0
18.0
18.0
% of
explained
variance
FC characteristics
(age, male)
Caregiver support—share
caregiving
Male (FC)
Caregiver support—share
caregiving
Income (FC)
Caregiver support—share
caregiving
Married (FC)
Education (FC)
Caregiver support—share
caregiving
Variable
4.5
14.2
9.0
15.5
4.5
10.1
14.4
11.0
2.9
23.4
33.6
8.4
% of
explained
variance
FC of terminally cancer patientsa,c (n=136)
Table 3 Comparison of predictors of caregiver reaction assessment (CRA) scale between family caregivers (FC) of palliative care patients and other published studies
Support Care Cancer (2013) 21:2527–2535
2533
2534
However, the findings across studies are inconsistent and
may be partially explained by differences in patients’ disease characteristics as well as the variables chosen as covariates. As suggested by Oberst and colleagues [5], it is
unlikely that any simple constellation of FC and/or patient
characteristics will explain or predict all aspects of FC
burden, given the complexities of family dynamics and
variation in patients’ disease trajectories.
Limitations of this study must be noted. First, due to its
cross-sectional design, research is needed to predict how
level of FC burden changes over time. Second, the sample
was relatively small which may have limited our ability to
identify additional determinants of FC burden and a higher
percentage of explained variance. Additional research is
needed that includes other potential predictors of caregiver
burden (e.g., lack of social support, personality characteristics, anxiety, and coping styles). Finally, findings from this
study may not generalize to other ethnic or cultural groups.
In summary, this study is the first to evaluate hope as a
predictor of burden in a sample of FCs of patients with advanced cancer. Findings from this study suggest that FCs’ and
patients’ level of hope are important determinants of caregiver
burden. FC characteristics seem more important predictors of
burden than patient characteristics. In order to develop interventions to decrease burden, longitudinal studies are needed
that examine changes in and predictors of caregiver burden
across the patients’ disease and treatment trajectories.
Acknowledgments The study was funded by The Research Council
of Norway and Oslo and Akershus University College of Applied
Science, Norway.
Conflict of interest None of the authors have any competing financial interests. The authors have full control of all primary data and
agree to allow the journal to review the data if requested.
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