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Purpose: Early breast cancer survivors (BCSs) report high unmet care needs, and easily accessible care is not routinely available for this growing population. The Breast Cancer E-Health (BREATH) trial is a Web-based self-management intervention to support the psychological adjustment of women after primary treatment, by reducing distress and improving empowerment. Patients and methods: This multicenter, randomized, controlled, parallel-group trial evaluated whether care as usual (CAU) plus BREATH is superior to CAU alone. BREATH is delivered in sixteen fully automated weekly modules covering early survivorship issues. Two to 4 months post-treatment, BCSs were randomly assigned to receive CAU + BREATH (n = 70) or CAU alone (n = 80) using a stratified block design (ratio 1:1). Primary outcomes were distress (Symptom Checklist-90) and empowerment (Cancer Empowerment Questionnaire), assessed before random assignment (baseline, T0) and after 4 (T1), 6 (T2), and 10 months (T3) of follow-up. Statistical (analysis of covariance) and clinical effects (reliable change index) were tested in an intention-to-treat analysis (T0 to T1). Follow-up effects (T0 to T3) were assessed in assessment completers. Results: CAU + BREATH participants reported significantly less distress than CAU-alone participants (-7.79; 95% CI, -14.31 to -1.27; P = .02) with a small-to-medium effect size (d = 0.33), but empowerment was not affected (-1.71; 95% CI, 5.20 to -1.79; P = .34). More CAU + BREATH participants (39 of 70 [56%]; 95% CI, 44.1 to 66.8) than CAU-alone participants (32 of 80 [40%]; 95% CI, 30.0 to 51.0) showed clinically significant improvement (P = .03). This clinical effect was most prominent in low-distress BCSs. Secondary outcomes confirmed primary outcomes. There were no between-group differences in primary outcomes during follow-up. Conclusion: Access to BREATH reduced distress among BCSs, but this effect was not sustained during follow-up.
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BREATH: Web-Based Self-Management for Psychological
Adjustment After Primary Breast Cancer—Results of a
Multicenter Randomized Controlled Trial
Sanne W. van den Berg, Marieke F.M. Gielissen, José A.E. Custers, Winette T.A. van der Graaf,
Petronella B. Ottevanger, and Judith B. Prins
All authors: Radboud university medical
center, Nijmegen, the Netherlands.
Published online ahead of print at
www.jco.org on July 13, 2015.
Supported by Pink Ribbon, the Nether-
lands (Grant No. 2009-2013).
Presented at the International Psycho-
Oncology Society 15th World Congress
of Psycho-Oncology, Rotterdam, the
Netherlands, November 6-8, 2013; and
at the 13th International Congress of
Behavioral Medicine, Groningen, the
Netherlands, August 20-23, 2014.
The study sponsor had no role in the
study design, data collection, analysis
and interpretation of data, writing of the
report, or decision to submit the paper
for publication. The authors had full
access to all data and had final respon-
sibility for the decision to submit for
publication.
Authors’ disclosures of potential
conflicts of interest are found in the
article online at www.jco.org. Author
contributions are found at the end of
this article.
Corresponding author: Sanne W. van
den Berg, MSc, Radboud university
medical center, Department of Medical
Psychology (840), PO Box 9101, 6500
HB Nijmegen, the Netherlands; e-mail:
sanne.vandenberg@radboudumc.nl.
© 2015 by American Society of Clinical
Oncology
0732-183X/15/3399-1/$20.00
DOI: 10.1200/JCO.2013.54.9386
ABSTRACT
Purpose
Early breast cancer survivors (BCSs) report high unmet care needs, and easily accessible care is
not routinely available for this growing population. The Breast Cancer E-Health (BREATH) trial is a
Web-based self-management intervention to support the psychological adjustment of women
after primary treatment, by reducing distress and improving empowerment.
Patients and Methods
This multicenter, randomized, controlled, parallel-group trial evaluated whether care as usual (CAU)
plus BREATH is superior to CAU alone. BREATH is delivered in sixteen fully automated weekly
modules covering early survivorship issues. Two to 4 months post-treatment, BCSs were
randomly assigned to receive CAU BREATH (n 70) or CAU alone (n 80) using a stratified
block design (ratio 1:1). Primary outcomes were distress (Symptom Checklist-90) and empower-
ment (Cancer Empowerment Questionnaire), assessed before random assignment (baseline, T0)
and after 4 (T1), 6 (T2), and 10 months (T3) of follow-up. Statistical (analysis of covariance) and
clinical effects (reliable change index) were tested in an intention-to-treat analysis (T0 to T1).
Follow-up effects (T0 to T3) were assessed in assessment completers.
Results
CAU BREATH participants reported significantly less distress than CAU-alone participants
(7.79; 95% CI, 14.31 to 1.27; P.02) with a small-to-medium effect size (d0.33), but
empowerment was not affected (1.71; 95% CI, 5.20 to 1.79; P.34). More CAU BREATH
participants (39 of 70 [56%]; 95% CI, 44.1 to 66.8) than CAU-alone participants (32 of 80 [40%];
95% CI, 30.0 to 51.0) showed clinically significant improvement (P.03). This clinical effect was
most prominent in low-distress BCSs. Secondary outcomes confirmed primary outcomes. There
were no between-group differences in primary outcomes during follow-up.
Conclusion
Access to BREATH reduced distress among BCSs, but this effect was not sustained during
follow-up.
J Clin Oncol 33. © 2015 by American Society of Clinical Oncology
INTRODUCTION
Women diagnosed with breast cancer face chal-
lenges that do not end with treatment completion.
The first year after primary treatment, the so-called
re-entry phase,
1
is characterized by physical, emo-
tional, and social recovery.
2
Women report high
unmet care needs
3
and have to cope with lingering
physical and emotional symptoms of treatment, fear
of recurrence, decreasing social support, losing the
safety net of care providers, and resuming profes-
sional and recreational activities.
2,4-6
Approximately
70% of breast cancer survivors (BCSs; ie, women
who have completed primary breast cancer treat-
ment with no evidence of recurrence
7
) adjust well
during the re-entry phase, but a substantial propor-
tion report high levels of distress.
8,9
Better diagnosis and therapy mean that more
women survive breast cancer, and self-management
strategies
10
and e-health
11
have been proposed as
ways to support this growing population. Because
approximately half of all BCSs already search the
Internet for breast cancer–specific information,
12-15
the Internet is promising for providing psycho-
oncological interventions.
16
However, there are few
randomized controlled trials (RCTs) of Web-based
interventions to support re-entry adjustment. To
date, most Web-based interventions including
JOURNAL OF CLINICAL ONCOLOGY ORIGINAL REPORT
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women with breast cancer have not been either re-entry specific
17-20
or
breast cancer specific,
21,22
or have predominantly focused on peer
support groups
23-26
or informational support.
27
In a recent overview
advocating re-entry specific care, Stanton
2
reported promising but
inconclusive evidence from seven RCTs that psychoeducational inter-
ventions can be effective in BCSs.
We developed the Breast Cancer E-Health (BREATH) trial,
28
a
Web-based self-management intervention on the basis of cognitive
behavioral therapy that provides early BCSs with self-management
skills to enable them to take control of, and adjust to, post-treatment
survivorship. The intervention was developed using the transactional
model of stress
29
and the model of psychological well-being in cancer
survivors,
30
both of which describe negative and positive outcomes in
adapting to a stressor. Thus, the primary aim of this RCT was to study
whether care as usual (CAU) plus BREATH (CAU BREATH) can
effectively target negative and positive adjustment. We hypothesized
that CAU BREATH is superior to CAU alone in reducing distress
and improving empowerment. Because BCSs exhibit different levels
of distress during the re-entry phase, subhypotheses were that CAU
BREATH would reduce distress in high-distress BCSs, keep levels of
distress low in low-distress BCSs, and improve empowerment in both
distress groups.
PATIENTS AND METHODS
Study Design and Participants
The BREATH study protocol has been published elsewhere.
28
We conducted a multicenter, randomized, controlled, parallel-
group trial to evaluate the efficacy of a Web-based self-
management intervention in facilitating psychological adjustment
among BCSs. One university hospital and five regional hospitals in
the Netherlands participated (Fig 1). Female BSCs were eligible if
they had a histologically proven malignancy of the breast and had
completed curative-intent primary treatment (defined as surgery
plus adjuvant chemotherapy and/or radiotherapy) 2 to 4 months
before the baseline assessment. Participant characteristics are listed
in Table 1.
The local treatment team monitored patient recruitment and
eligibility and obtained informed consent. A researcher (S.v.d.B.)
contacted participants to check additional eligibility criteria: un-
derstanding the Dutch language, access to the Internet, and having
an e-mail address.
Study assessments covered the first year after breast cancer, with
baseline at 2 to 4 months after completion of primary treatment (T0),
and follow-up assessments at 4 (T1), 6 (T2), and 10 (T3) months after
Women with primary breast cancer were
referred from participating centers and met
eligibility criteria
(N = 170)
Completed baseline T0 and
were randomly allocated
(n = 151)
Excluded (metastases) (n = 1)
Lost to 4 months (n = 8) Lost to 4 months (n = 9)
Declined to participate
Intervention did not meet
participants’ needs
Time investment
Assessments too confronting
Web-based nature of intervention
Participation in other trials
Unknown
(n = 19)
(n = 6)
(n = 5)
(n = 4)
(n = 2)
(n = 1)
(n = 1)
(34 RUMC; 45 RS; 24 SL; 24 CWZ; 18 ZGV; 6 JBZ)
Randomly allocated to
CAU + BREATH
(n = 70)
Randomly allocated to
CAU alone
(n = 80)
Completed T1 assessment
at 4 months
(n = 62)
Intention-
to-treat analysis
(n = 150)
Completed T1 assessment
at 4 months
(n = 71)
Completed T2 assessment
at 6 months
(n = 62)
Completed T2 assessment
at 6 months
(n = 73)
Completed T3 assessment
at 10 months
(n = 63)
Assessment completers
analysis (58 CAU +
BREATH; 66 CAU)
(n = 124)
Completed T3 assessment
at 10 months
(n = 72)
Fig 1. Trial profile. BREATH, Breast
Cancer E-Health intervention; CAU, care
as usual; CWZ, Canisius-Wilhelmina Hos-
pital, Nijmegen; JBZ, Jeroen Bosch Hos-
pital, Den Bosch; RS, Rijnstate Hospital,
Arnhem and Zevenaar; RUMC, Radboud
university medical center, Nijmegen; SL,
Slingeland Hospital, Doetinchem; ZGV,
Hospital Gelderse Vallei, Ede.
van den Berg et al
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Copyright © 2015 American Society of Clinical Oncology. All rights reserved.
baseline. The Radboud University Medical Center Medical Review
Ethics Committee (file No. 2009/144) and the ethics boards of local
participating centers approved the study (Netherlands Trial Register
NTR2935).
Intervention
BREATH (Appendix Fig A1, online only) targets re-entry
issues relevant to BCSs during a fixed 16-week modular program
for four phases of adjustment to breast cancer (looking back,
emotional processing, strengthening, and looking ahead).
28
Inter-
vention components (104 total) are based on cognitive behavioral
therapy and include information (26 scripts), assignment (48 tasks,
or homework), assessment (10 self-tests followed by automated
feedback), and video (20 topics illustrated with clips extracted
from interviews). BREATH is a pure self-help program without
therapist contact (also known as self-administered therapy
31
).
Each week, new materials are released, accompanied by standard
e-mail reminders, in an attempt to maintain or improve adher-
ence. Access to BREATH was withdrawn after 16 weeks.
BCSs receiving CAU alone did not have access to BREATH. For
both conditions, CAU consisted of visits to an oncologist three times
per month and psychosocial care on demand or referral. No restric-
tions were made regarding use of Internet or psychological or other
self-help interventions.
Outcomes
Study assessments and random assignment were conducted on-
line using RadQuest software (Radboudumc Medical Psychology,
Nijmegen, the Netherlands). Baseline characteristics were obtained
with a medical checklist derived from the patient chart.
General psychological distress was assessed with the Symptom
Checklist-90 (SCL-90; range, 90-450), which has good psychometric
properties in healthy and patient populations.
32
The SCL-90 total
score showed good internal consistency at baseline (Cronbach’s
.97). For the General Severity Index (GSI), which represents the mean
score of all responses, transformed item scores (0-4) were used. Gen-
eral psychological empowerment was assessed with the Cancer Em-
powerment Questionnaire (CEQ).
33
The CEQ presumes that patients
can derive strength from themselves (intrapersonal) and from their
social surroundings (interpersonal). Baseline internal consistency was
good (Cronbach’s
.92).
Secondary outcomes reflected negative adjustment (general
34,35
and cancer-specific distress,
36
fatigue,
37
helplessness,
38
and fear of
cancer recurrence
39,40
) and positive adjustment (self-efficacy,
41
rem-
oralization,
42
personal control,
43
quality of life,
44
fulfillment,
45
re-
evaluation,
45
new ways of living,
45
and valuing life
45
). For details of
secondary outcomes, see our study protocol
28
(or the legend of Table
2 with treatment effects).
Information about self-reported use of Internet and other re-
sources (individual support, peer support, rehabilitation support
groups) was collected at T1. General Internet use was assessed with the
question “Have you consulted the Internet for information on (learn-
ing to live with) breast cancer in the past 4 months?” Four-month
usage data of CAU BREATH participants were evaluated.
46
For the
current report, correlations were calculated between the mean differ-
ence (T0 to T1) in distress and the continuous usage variables of
frequency of log-ins, total duration (in minutes), and activity (number
of intervention components opened).
Random Assignment and Masking
BCSs were randomly assigned (allocation ratio 1:1) to receive
CAU BREATH or CAU alone. For each center, a randomized block
design with stratification by hormone therapy was generated. After
baseline assessment, a random number generator with variable block
sizes of 4, 6, and 8 automatically ensured blinded allocation until
intervention assignment. One researcher (S.v.d.B.) informed partici-
pants about treatment assignment by e-mail and was therefore not
blinded. In one case, a participant was told an incorrect treatment
assignment (CAU instead of CAU BREATH); this participant re-
ceived CAU alone and her data were analyzed accordingly.
Table 1. Baseline Characteristics of Study Participants (N 150)
Characteristic
CAU
BREATH
(n 70)
CAU alone
(n 80)
No. of
Patients %
No. of
Patients %
Age, years
Mean 51.44 50.18
SD 8.30 9.15
Educational level
Low (ISCED 0-1-2) 14 20 13 16
Medium (ISCED 3-4-5) 32 46 48 60
High (ISCED 6-7-8) 24 34 19 24
Marital status
Married/cohabiting 58 83 61 76
Unmarried 5 7 5 6
Divorced 5 7 10 13
Widowed 2 3 4 5
Children (yes) 61 87 62 76
Employment†
Paid work outside home 30 43 32 40
Home management 21 30 18 23
Unemployed 3 4 8 10
Sick leave 30 43 42 53
Disability insurance act 3 4 5 6
Voluntary work 7 10 4 5
Student 0 0 1 1
Retired 3 4 3 4
Treatment type
Surgery chemotherapy radiotherapy 48 69 56 70
Surgery chemotherapy 19 27 22 28
Surgery radiotherapy 3 4 2 2
Hormone therapy 46 66 53 66
Low distress (GSI 0.57) 51 73 55 69
Frequency of Internet use‡
Daily 24 59 38 73
2 to 4 times a week 12 29 9 17
Weekly or less 5 12 5 10
NOTE. No significant differences were found between the two conditions
(P.05). Pvalues were calculated using
2
tests for categorical variables and
a two-tailed Students’s ttest (independent samples) for continuous variables.
Abbreviations: BREATH, Breast Cancer E-Health intervention; CAU, care as
usual; GSI, General Severity Index; ISCED, International Standard Classifica-
tion of Education; SD, standard deviation.
ISCED 2011.
†Percentages do not add up to 100% because more options are possible.
‡CAU BREATH (n 41), CAU alone (n 52).
Breast Cancer E-Health (BREATH) Trial
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Statistical Methods
All statistical analyses were performed with SPSS 20 (IBM, Ar-
monk, NY). The sample size calculation for the primary outcomes at
T1 was 170: 128 BCSs (64 in each group) at 80% power for differences
between CAU BREATH and CAU alone with a medium effect size
of 0.50, plus a 25% dropout rate.
28
The level of significance in the
sample size calculation was adjusted to P.025 to keep the overall
chance of type I error at 5%. Inclusion was prematurely stopped at 151
participants, with approval of the ethics committee, because only 5%
(7 of 151) of the participants dropped out at T1.
Statistical Effect
The primary hypothesis was that CAU BREATH would be
superior to CAU alone in decreasing distress and increasing empow-
erment, and it was tested in an intention-to-treat (ITT) analysis of data
for T0 and T1. Missing data at T1 were imputed using last observation
carried forward. The significance of intervention effects on primary
and secondary outcomes was tested using one-way between-groups
analyses of covariance with group (CAU BREATH or CAU alone)
as a fixed factor. Because participants were not preselected before
inclusion, the analysis of covariance model corrected for baseline
differences. For primary outcome analyses, baseline distress (SCL-90)
and empowerment (CEQ) were used as covariates. For secondary
outcome analyses, baseline scores of corresponding questionnaires
were used as covariates. Interaction effects of mean adjusted differ-
ences between T0 and T1 by group are reported in Table 2, with SEs,
significance level, and 95% CI. Effect size Cohen’s dfor independent
groups was calculated using the pooled standard deviations and un-
adjusted means on T1.
Clinically Significant Change
Clinically significant change, assessed with the reliable change
index (RCI) of the GSI, was tested in ITT analysis (T0 to T1).
Following Jacobson and Truax,
47
Schauenburg and Strack
48
calcu-
lated the GSI cutoff 0.567 to discriminate between low and high
distress on the basis of normative and psychotherapy samples. The
magnitude of improvement (defined as RCI 0.16 for low-
distress participants and RCI 0.43 for high-distress partici-
pants) or deterioration (RCI 0.16 for low-distress participants
and RCI 0.43 for high-distress participants) was assessed using
one-sided
2
tests.
33
Follow-Up Effect
Follow-up effects for primary and secondary outcomes were
evaluated with mixed within-between repeated-measures analysis of
variance, including data for participants who completed all four as-
sessments (T0 to T3). Because participants were randomly assigned at
each center, center was not included as a random effect. Baseline
variables were taken into account as within factors in the model.
Differences between CAU BREATH and CAU alone were tested
using independent samples ttests.
RESULTS
Between August 2010 and March 2012, 170 women were referred
and 151 (89%) underwent random assignment (Fig 1). Data col-
lection was finalized in February 2013. One woman was errone-
ously enrolled (metastatic disease) and excluded after the random
assignment,
49
leaving a final ITT sample of 150 BCSs (70 CAU
BREATH, 80 CAU alone). At baseline, the two groups did not
differ on demographic characteristics (Table 1) and study out-
comes (Table 2). Participants with missing data at T1 (n 17) had
higher levels of baseline distress than participants with complete
data at T1 (mean difference, 23.57; 95% CI, 3.82 to 43.31; P.02).
Levels of baseline empowerment were similar (P.79). Missing
data at T1 were equally distributed between the two groups. Over-
all, 124 participants (58 CAU BREATH; 66 CAU alone) com-
pleted all four assessments, and their data were included in
follow-up analyses. No metastases or severe illnesses were reported
during the study. One woman was admitted to a psychiatric clinic;
this was reported as a serious adverse event.
Statistical Effect
The decrease in distress at T1 was significantly greater in
CAU BREATH participants than in CAU-alone participants, with a
small-to-medium effect size (d0.33; Table 2). Baseline distress
explained 53% of the variance in distress at T1 (P.005). No such
difference in empowerment was found.
Secondary outcome analyses (Table 2) revealed that CAU
BREATH led to significant improvements in five of seven negative
adjustment variables (general and cancer-specific distress, fatigue, and
two fear of cancer recurrence outcomes) with small-to-medium effect
sizes (d0.37 to 0.55), and in 3 of 10 positive adjustment variables
(self-efficacy, remoralization, new ways of living) with small-to-
medium effect sizes (d0.26 to 0.39).
Clinically Significant Change
More CAU BREATH participants (39 of 70 [56%]; 95% CI,
44.1 to 66.8) than CAU-alone participants (32 of 80 [40%]; 95% CI,
30.0 to 51.0) showed a clinically significant improvement (P.03).
We had hypothesized that more high-distress BCSs would show a
clinically significant improvement after CAU BREATH than after
CAU alone, but this was not the case (10 of 21 [48%]; 95% CI, 28.3 to
67.6 v14 of 27 [52%]; 95% CI, 34.0 to 69.3, respectively; P.39). Post
hoc analysis revealed that there was no difference in the proportion of
high-distress BCSs showing clinical deterioration (5 of 21 [24%] v2of
27 [7%], respectively; P.06). Of the low-distress BCSs, more
CAU BREATH participants than CAU-alone participants showed
clinical improvement or no change (41 of 49 [84%]; 95% CI, 71.0 to
91.5 v35 of 53 [66%]; 95% CI, 52.6 to 77.3 respectively; P.02).
Moreover, explorative post hoc analyses of low-distress BCSs revealed
that, compared with CAU-alone participants, CAU BREATH par-
ticipants showed more clinically significant improvement (29 of 49
[59%] v18 of 53 [34%], respectively; P.006) and less deterioration
(8 of 49 [16%] v18 of 53 [34%], respectively; P.02). The empow-
erment hypothesis was not tested, because empowerment was not
significantly different between CAU BREATH and CAU alone.
Follow-Up Effect
At T2 and T3, distress was significantly reduced regardless of
group assignment (F[3, 120] 5.88; P.001; Fig 2). This was also
true for the secondary negative adjustment outcomes of fear of cancer
recurrence (Cancer Worry Scale; F[3, 120] 5.954; P.001), fatigue
(F[3, 120] 4.40; P.006), and helplessness (F[3, 120] 11.964;
P.000). A significant time group interaction effect was found for
van den Berg et al
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Table 2. Effect of Treatment (intention-to-treat analysis) on Primary and Secondary Outcomes After 4 Months (N 150)
Treatment Effect
Mean (SD/SE)
Mean Difference (95% CI) PEffect Size (Cohen’s d)
CAU BREATH
(n 70)
CAU Alone
(n 80)
Primary outcomes
Distress (SCL-90
32
)
T0 135.44 (37.532) 140.33 (41.045)4.882 (17.640 to 7.875) .451
T1 (unadjusted) 124.90 (26.956) 135.84 (37.975)
T1 (adjusted) 126.676 (2.412) 134.463 (2.250) 7.788 (14.308 to 1.267) <.05 0.33
Empowerment (CEQ†
33
)
T0 156.90 (13.222) 154.06 (15.133) 2.838 (1.779 to 7.454) .226
T1 (unadjusted) 159.13 (15.116) 155.45 (13.639)
T1 (adjusted) 157.946 (1.293) 156.240 (1.206) 1.706 (1.787 to 5.200) .336 0.16
Secondary outcomes
Negative adjustment variables
General (distress [HADS-total score]
35
)
T0 9.07 (6.710) 10.01 (7.259) 0.941 (3.208 to 1.326) .413
T1 (unadjusted) 7.67 (6.033) 9.89 (6.129)
T1 (adjusted) 8.052 (0.461) 9.621 (0.431) 1.569 (2.815 to 0.322) <.05 0.37
General (Distress Thermometer
)
T0 3.89 (2.505) 4.53 (2.516) 0.639 (1.451 to 0.173) .122
T1 (unadjusted) 3.46 (2.506) 4.00 (2.408)
T1 (adjusted) 3.662 (0.249) 3.858 (0.232) 0.196 (0.868 to 0.477) .566 0.22
General (fatigue [CIS]
37
)
T0 33.29 (12.530) 33.38 (12.627)0.089 (4.159 to 3.980) .965
T1 (unadjusted) 28.57 (12.913) 32.77 (13.309)
T1 (adjusted) 28.602 (1.205) 32.746 (1.127) 4.144 (7.404 to 0.884) <.05 0.32
Cancer specific (fear of recurrence [CWS]
39
)
T0 14.31 (4.454) 15.36 (3.892) 1.048 (2.395 to 0.298) .126
T1 (unadjusted) 13.13 (3.310) 15.19 (4.119)
T1 (adjusted) 13.452 (0.296) 14.799 (0.277) 1.347 (2.149 to 0.545) <.001 0.55
Cancer specific (fear of recurrence [CAS]
40
)
T0 5.11 (1.584) 5.45 (1.630) 0.336 (0184 to 0.856) .204
T1 (unadjusted) 4.90 (1.395) 5.51 (1.567)
T1 (adjusted) 5.015 (0.120) 5.398 (0.112) 0.383 (0.707 to 0.059) <.05 0.41
Cancer specific (helplessness [ICQ]
38
)
T0 10.36 (3.301) 10.21 (3.133) 0.145 (0.894 to 1.184) .784
T1 (unadjusted) 9.39 (2.975) 9.45 (3.023)
T1 (adjusted) 9.335 (0.274) 9.488 (0.256) 0.153 (0.894 to 0.589) .685 0.02
Cancer specific [distress (IES-total score]
36
)
T0 18.11 (15.098) 18.88 (15.730)0.761 (5.754 to 4.232) .764
T1 (unadjusted) 11.81 (12.240) 17.35 (14.371)
T1 (adjusted) 12.024 (1.244) 17.143 (1.164) 5.119 (8.486 to 1.752) <.01 0.42
Positive adjustment variables
General (self-efficacy [SES]†
41
)
T0 19·97 (2·756) 20·30 (2·655) 0.329 (1.203 to 0.545) .459
T1 (unadjusted) 21.03 (3.217) 20.23 (2.556)
T1 (adjusted) 21.130 (0.290) 20.133 (0.271) 0.997 (0.213 to 1.781) <.05 0.28
General (remoralization [RS12]†
42
)
T0 3.09 (0.512) 3.06 (0.569) 0.022 (0.153 to 0.198) .802
T1 (unadjusted) 3.28 (0.495) 3.08 (0.540)
T1 (adjusted) 3.275 (0.051) 3.081 (0.047) 0.195 (0.058 to 0.332) <.01 0.39
General (personal control [Mastery]†)
T0 23.93 (4.604) 23.64 (4.653) 0.291 (1.206 to 1.789) .701
T1 (unadjusted) 24.74 (4.548) 23.58 (4.957)
T1 (adjusted) 24.655 (0.435) 23.677 (0.407) 0.977 (0.199 to 2.154) .103 0.24
General (acceptance [ICQ]†)
T0 16.17 (3.996) 16.14 (3.525) 0.034 (1.180 to 1.247) .956
T1 (unadjusted) 17.60 (4.109) 16.94 (3.509)
T1 (adjusted) 17.586 (0.313) 16.948 (0.293) 0.637 (0.209 to 1.1484) .139 0.17
(continued on following page)
Breast Cancer E-Health (BREATH) Trial
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fear of cancer recurrence (Cancer Worry Scale; F[3, 120] 4.563; P
.005), with CAU BREATH participants reporting less fear than
CAU-alone participants at T2 (1.459; 95% CI, 2.743 to 0.175).
Of the positive adjustment outcomes, acceptance significantly im-
proved in both groups (ICQ; F[3, 120] 8.531; P.000). Time
effects and time group interactions were not significant for all
remaining outcomes, including empowerment (Fig 3).
Use of BREATH and Other Resources
Use of the BREATH intervention varied considerably. Frequency
of logins ranged from 0 to 45, total duration ranged from 0 to 2,324
minutes, and activity ranged from 0 to 104 intervention components
opened. The mean difference in distress (SCL-90, T0 to T1) was not
correlated with frequency (r⫽⫺0.007; P.96), total duration (r
0.000; P1.00), or activity (r⫽⫺1.072; P.55).
At T1, similar proportions of women in CAU BREATH and
CAU alone had consulted the Internet in the previous 4 months on a
monthly (24% v34%), weekly (13% v8%), or daily (0% v2%) basis,
or not at all (61% v58%). There were also no significant differences
(n 126; P.27) between CAU BREATH and CAU-alone par-
ticipants in the use of individual support (eg, psychologist; 12% v25%,
respectively), peer and rehabilitation support groups (14% v12%,
respectively), or combined individual and group support (21% v13%,
respectively). Half of the participants in both groups did not make use
of other support (53% v50%, respectively).
DISCUSSION
At the start of the re-entry phase, 4-month access to BREATH in
addition to CAU resulted in a statistically and clinically significant
distress reduction compared with CAU alone. However, this small-to-
medium effect was not sustained, and levels of distress were similar at
6 and 10 months. CAU BREATH participants also showed a greater
decrease than CAU-alone participants in fear of cancer recurrence,
fatigue, and general and cancer-related distress. The effect of BREATH
on fear of cancer recurrence was sustained during follow-up. Access to
BREATH did not influence empowerment or clinical distress im-
provement in high-distress BCSs. Low-distress BCSs showed a greater
clinical improvement and less deterioration with CAU BREATH
than with CAU alone.
The RCT was designed according to quality standards
(CONSORT for parallel group,
50
nonpharmacologic treatment,
51
and eHealth trials).
52,53
Statistically and clinically significant
changes were evaluated in ITT analyses, with missing data imputed
using a conservative method (last observation carried forward)
Table 2. Effect of Treatment (intention-to-treat analysis) on Primary and Secondary Outcomes After 4 Months (N 150) (continued)
Treatment Effect
Mean (SD/SE)
Mean Difference (95% CI) PEffect Size (Cohen’s d)
CAU BREATH
(n 70)
CAU Alone
(n 80)
General (perceived benefits [ICQ]†)
T0 15.09 (4.169) 15.86 (3.801) 0.777 (2.063 to 0.509) .235
T1 (unadjusted) 15.66 (4.584) 16.21 (4.541)
T1 (adjusted) 16.042 (0.363) 15.926 (0.339) 0.116 (0.866 to 1.098) .816 0.12
Cancer specific (quality of life [EORTC QLQ-C30]†
40
)
T0 66.79 (16.575) 69.79 (17.906) 3.006 (8.601 to 2.589) .290
T1 (unadjusted) 72.50 (18.572) 70.52 (15.231)
T1 (adjusted) 73.295 (1.784) 69.882 (1.666) 3.413 (1.411 to 8.236) .164 0.12
Cancer specific (fulfillment [PAQ]†
45
)
T0 38.30 (6.686) 39.80 (6.934) 1.500 (3.706 to 0.706) .181
T1 (unadjusted) 40.89 (6.728) 40.10 (7.289)
T1 (adjusted) 41.284 (0.759) 39.788 (0.708) 1.496 (0.55 to 3.548) .152 0.11
Cancer specific (re-evaluation [PAQ]†)
T0 38.39 (6.160) 40.01 (6.407) 1.627 (3.662 to 0.409) .116
T1 (unadjusted) 38.81 (6.493) 39.44 (7.107)
T1 (adjusted) 39.380 (0.611) 38.835 (0.570) 0.545 (1.107 to 2.197) .516 0.09
Cancer specific (new ways of living [PAQ]†)
T0 41.19 (5.279) 41.34 (7.488) 0.152 (2.271 to 1.967) .888
T1 (unadjusted) 42.94 (6.230) 41.07 (8.012)
T1 (adjusted) 43.001 (0.709) 41.032 (0.663) 1.969 (0.051 to 3.886) <.05 0.26
Cancer specific (valuing life [PAQ]†)
T0 34.06 (5.778) 34.51 (4.963) 0.455 (2.188 to 1.278) .604
T1 (unadjusted) 34.40 (6.087) 34.11 (5.972)
T1 (adjusted) 34.595 (0.545) 33.971 (0.510) 0.623 (0.853 to 2.100) .405 0.05
NOTE. All Pvalues were calculated using an analysis of covariance with adjustment for baseline value. (Unadjusted) means unadjusted for baseline covariates.
(Adjusted) means adjusted for baseline value of the corresponding questionnaire. Bold font indicates significant effect and corresponding effect size.
Abbreviations: BREATH, Breast Cancer E-Health intervention; CAS, Cancer Acceptance Scale; CAU, care as usual; CEQ, Cancer Empowerment Questionnaire; CIS,
Checklist Individual Strength; CWS, Cancer Worry Scale; EORTC QLQ-C30, European Organisation for Research and Treatment of Cancer Quality of Life
Questionnaire Core 30 items; HADS, Hospital Anxiety and Depression Scale; ICQ, Illness Cognition Questionnaire; IES, Impact of Event Scale; PAQ, Positive
Adjustment Questionnaire; RS12, Remoralization Scale-12 items; SCL-90, Symptom Checklist-90 items; SD, standard deviation; SES, Self-Efficacy Scale.
Increase represents worsening; decrease represents improvement.
†Increase represents improvement; decrease represents worsening.
van den Berg et al
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because the patients in our sample were expected to improve on
distress over the study period.
8,9
The multicenter recruitment
strategy guaranteed referrals from both secondary and tertiary care
centers. The recruitment procedure, which ensured minimal in-
volvement of the research team, and lack of assistance regarding
intervention use and adherence support the ecological validity of
BREATH. In the absence of RCTs evaluating similar unguided
Web-based interventions for BCSs, the effect size of BREATH is
consistent with that of two recent meta-analyses of guided face-to-
face (effect size range 0.26 to 0.38)
54
and Web-based (effect size
range, 0.17 to 0.21)
55
interventions for people with cancer
54
and
chronic somatic conditions.
55
The secondary outcomes revealed that CAU BREATH de-
creased general and cancer-specific distress, fatigue, and fear of cancer
recurrence, which may reflect the multicomponent nature of distress
in cancer patients.
56
The clinical relevance of these outcomes needs to
be addressed in future research.
CAU BREATH did not significantly change empowerment
relative to the effect of CAU alone and had inconsistent effects on the
secondary positive adjustment variables. The study of positive adjust-
ment is a new research area and poses multiple challenges. Although
new models of survivorship care stress patient empowerment,
57,58
there is no consensus about the empowerment construct. Conse-
quently, positive adjustment questionnaires, such as the CEQ, are
new, but not extensively validated in BCSs and lack information on
sensitivity to change. Furthermore, in psycho-oncology, resource-
oriented therapeutic models
59
are lacking, and interventions are tra-
ditionally aimed at diminishing deficits instead of enhancing
strengths. It is possible that BREATH does not include a sufficient
number of empowerment modules (only 4 of the 16 weekly modules
targeted empowerment).
Results should be considered with caution for several reasons.
Consistent with the scarce literature on Web-based interventions
for cancer patients,
60
BREATH did not have a sustained effect on
distress. This may be because access to the Web site was for 4
months only. Although the limited access enabled accurate postin-
tervention assessments, in retrospect it might have been better to
allow participants to retain access, especially because information
often remains available with other psychoeducational interven-
tions or self-help books. Another explanation for lack of a sus-
tained effect may be the small-to-medium effect size, which might
not have been enough to compensate for the natural course of
emotional recovery. The missing-at-random assumption for im-
putation was violated. BCSs with missing data for the 4-month
assessment had significantly higher levels of distress at baseline.
Although not significant, more high-distress BCSs in the CAU
BREATH group showed a clinical deterioration. This leads to a
cautious interpretation of the results regarding high-distress BCSs,
and suggests that these women may need a more intensive inter-
vention than BREATH.
The limited data on BREATH use means it is not possible to
draw firm conclusions about how often the intervention should be
used to have an effect. Further investigations with larger samples,
mediation analyses, or usage pattern are needed to gain insight into
determinants of intervention use and to study a possible dose-
response relationship.
61
Data for BCSs who declined to participate
were not recorded. Although it was not feasible to recruit patients
consecutively, our sample seemed homogeneous and representa-
tive, because the mean age, treatment type, education, and work
situation of participants were comparable to those of other studies
evaluating the Dutch breast cancer population.
3,9,62,63
The study
sample also proved representative with regard to psychological
10 Months6 Months4 MonthsBaseline
SCL-90 Total Score
145
140
135
130
125
120
115
110
CAU + BREATH (n = 58)
CAU alone (n = 66)
CAU + BREATH (n = 58)
CAU alone (n = 66)
Fig 2. Psychological distress (Symptom Checklist-90 [SCL-90]) at baseline and
4, 6, and 10 months after baseline (n 124 assessment completers). Vertical
bars represent the 95% CI of the mean SCL-90 at each time point. BREATH,
Breast Cancer E-Health intervention;; CAU, care as usual.
10 Months6 Months4 MonthsBaseline
CEQ Total Score
170
165
160
155
150
145
140
135
130
CAU + BREATH (n = 58)
CAU alone (n = 66)
CAU + BREATH (n = 58)
CAU alone (n = 66)
Fig 3. Psychological empowerment (Cancer Empowerment Questionnaire
[CEQ]) at baseline and 4, 6, and 10 months after baseline (n 124 assessment
completers). Vertical bars represent the 95% CI of the mean CEQ at each time
point. BREATH, Breast Cancer E-Health intervention; CAU, care as usual.
Breast Cancer E-Health (BREATH) Trial
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functioning during the first year after treatment. As in other studies
of patients with breast
8,9
or other
64
cancer, most patients experi-
enced low levels of distress (n 102 [68%]).
To the best of our knowledge, this is the first RCT to demonstrate an
additional effect of a self-management intervention specifically designed
to support BCSs in the year after treatment completion. Although small,
the primary effect on distress was statistically robust and clinically relevant.
Moreover, the intervention does not necessarily require a lot of user
commitment. Future research should focus on replicating the current
findings, using more valid questionnaires for the positive adjustment
variables, and evaluating the follow-up effect beyond 4 months of access.
The magnitude of the effect in BCSs with low and high distress should be
investigated further. BREATH demonstrated its potential as a feasible first
step in a matched supportive care model providing evidence-based and
easily accessible re-entry care.
AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS
OF INTEREST
Disclosures provided by the authors are available with this article at
www.jco.org.
AUTHOR CONTRIBUTIONS
Conception and design: Sanne W. van den Berg, Petronella B.
Ottevanger, Judith B. Prins
Administrative support: Sanne W. van den Berg
Provision of study materials or patients: Petronella B. Ottevanger
Collection and assembly of data: Sanne W. van den Berg
Data analysis and interpretation: All authors
Manuscript writing: All authors
Final approval of manuscript: All authors
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■■■
Breast Cancer E-Health (BREATH) Trial
www.jco.org © 2015 by American Society of Clinical Oncology 9
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Copyright © 2015 American Society of Clinical Oncology. All rights reserved.
Acknowledgment
We thank all patients who gave their time to participate and the oncologists, radiotherapists, and research nurses of the participating hospitals:
Radboud university medical center, Nijmegen; Rijnstate, Arnhem and Zevenaar; Slingeland, Doetinchem; Hospital Gelderse Vallei, Ede;
Canisius-Wilhelmina Hospital, Nijmegen; and Jeroen Bosch, Den Bosch.
Appendix
Fig A1. Screenshot of the BREATH (Breast Cancer E-Health intervention) Web site (in Dutch) with four-phase structure.
van den Berg et al
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Copyright © 2015 American Society of Clinical Oncology. All rights reserved.
... 9 Patients with cancer who used e-mental health interventions experienced significantly reduced levels of distress, depression, pain, fatigue and anxiety. [10][11][12][13][14][15][16][17][18] E-mental health interventions have proven to be feasible and effective in improving quality of life. [10][11][12][13][14][15][16][17][18] Recent scientific findings extend their effectiveness by suggesting significant effects on well-being in terms of distress, depression and anxiety, 11 16-20 especially for web-based interventions that included cognitive behavioural therapy (CBT) techniques, acceptance and commitment therapy (ACT) and mindfulness-based stress reduction (MBSR). ...
... [10][11][12][13][14][15][16][17][18] E-mental health interventions have proven to be feasible and effective in improving quality of life. [10][11][12][13][14][15][16][17][18] Recent scientific findings extend their effectiveness by suggesting significant effects on well-being in terms of distress, depression and anxiety, 11 16-20 especially for web-based interventions that included cognitive behavioural therapy (CBT) techniques, acceptance and commitment therapy (ACT) and mindfulness-based stress reduction (MBSR). [10][11][12][13][14][15][16][17][18][19][20][21][22] Matis and colleagues conclude in their systematic literature review that mindfulness-based eHealth interventions are feasible and effective in improving different outcomes in patients with cancer. ...
... [10][11][12][13][14][15][16][17][18] Recent scientific findings extend their effectiveness by suggesting significant effects on well-being in terms of distress, depression and anxiety, 11 16-20 especially for web-based interventions that included cognitive behavioural therapy (CBT) techniques, acceptance and commitment therapy (ACT) and mindfulness-based stress reduction (MBSR). [10][11][12][13][14][15][16][17][18][19][20][21][22] Matis and colleagues conclude in their systematic literature review that mindfulness-based eHealth interventions are feasible and effective in improving different outcomes in patients with cancer. 23 Particularly in improving depression, anxiety and post-traumatic growth. ...
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Introduction Many patients with cancer experience severe psychological distress, but as a result of various barriers, few of them receive psycho-oncological support. E-mental health interventions try to overcome some of these barriers and the limitation of healthcare offers, enabling patients with cancer to better cope with psychological distress. In the proposed trial, we aim to assess the efficacy and cost-effectiveness of the manualised e-mental health intervention Make It Training- Mindfulness-Based and Skills-Based Distress Reduction in Oncology. Make It Training is a self-guided and web-based psycho-oncological intervention, which includes elements of cognitive behavioural therapy, mindfulness-based stress reduction and acceptance and commitment therapy. The training supports the patients over a period of 4 months. We expect the Make It Training to be superior to treatment as usual optimised (TAU-O) in terms of reducing distress after completing the intervention (T1, primary endpoint). Methods and analysis The study comprises a multicentre, prospective, randomised controlled confirmatory interventional trial with two parallel arms. The proposed trial incorporates four distinct measurement time points: the baseline assessment before randomisation, a post-treatment assessment and 3 and 6 month follow-up assessments. We will include patients who have received a cancer diagnosis in the past 12 months, are in a curative treatment setting, are 18–65 years old, have given informed consent and experience high perceived psychological distress (Hospital Anxiety and Depression Scale ≥13) for at least 1 week. Patients will be randomised into two groups (Make It vs TAU-O). The aim is to allocate 600 patients with cancer and include 556 into the intention to treat analysis. The primary endpoint, distress, will be analysed using a baseline-adjusted ANCOVA for distress measurement once the intervention (T1) has been completed, with study arm as a binary factor, baseline as continuous measurement and study centre as an additional categorical covariate. Ethics and dissemination The Ethics Committee of the Medical Faculty Essen has approved the study (21-10076-BO). Results will be published in peer-reviewed journals, conference presentations, the project website, and among self-help organisations. Trial registration number German Clinical Trial Register (DRKS); DRKS-ID: DRKS00025213.
... Low heterogeneity was found between studies (t 2 5 0, I 2 5 0.0%, P 5 .43). Interventions with a significant improvement in psychologic distress were self-guided 35,62 or health professional-supported (repeated contact via e-mail or ...
... Ryhänen et al 60 Carpenter et al 39 Van Den Berg et al 62 Admiraal et al 35 Ferrante et al 42 Kim et al 53 Zhu et al 69 White et al 66 Kim et al 54 Vallance et al 61 ...
... Two 39,69 included repeated researcher or health professional contact and one provided automated weekly e-mails about new website content. 62 Age, intervention period, and postintervention follow-up were not significant moderators (Data Supplement 1). Association between patient types could not be analyzed as there was one study in each patient type. ...
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PURPOSE Ongoing supportive care using electronic health (eHealth) interventions has the potential to provide remote support and improve health outcomes for patients with breast cancer. This study aimed to evaluate the effectiveness of eHealth interventions on patient-reported outcomes (quality of life [QOL], self-efficacy, and mental or physical health) for patients during and after breast cancer treatment and patient-reported experience measures (acceptability and engagement). METHODS Systematic review with meta-analyses (random-effects model) of randomized controlled trials was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Nine databases were searched using a prespecified search strategy. Patient-directed eHealth interventions for adult patients during or after active breast cancer treatment measuring QOL, self-efficacy, and mental (depressive, anxiety, and distress symptoms) or physical (physical activity, nutrition, and fatigue) health outcomes were included. Data from eligible full-text articles were independently extracted by six observers. RESULTS Thirty-two unique studies (4,790 patients) were included. All were health self-management interventions, and most were multicomponent (videos, forums, and electronic reminder systems) websites. Meta-analyses revealed a significant effect of eHealth interventions on QOL (standardized mean difference [SMD], 0.20 [95% CI, 0.03 to 0.36]), self-efficacy (SMD, 0.45 [95% CI, 0.24 to 0.65]), distress (SMD, –0.41 [95% CI,–0.63 to –0.20]), and fatigue (SMD, –0.37 [95% CI, –0.61 to –0.13]). Twenty-five studies (78.1%) measured patient-reported experience measures. Acceptability (n = 9) was high, with high ratings for satisfaction (range, 71%-100%), usefulness (range, 71%-95%), and ease-of-use (range, 73%-92%). Engagement (n = 25) decreased over time, but disease-focused information and interactive support were most engaging. CONCLUSION eHealth interventions may provide an acceptable and effective strategy for improving QOL, distress, self-efficacy, and fatigue among patients with breast cancer.
... 33 The literature has shown that telehealth practices are important for women with breast cancer due to their positive effects on cancer and treatment-related psychological conditions. [34][35][36] The studies have shown that internet-based cognitive behavioral therapy applied within the scope of telehealth/telepsychiatry services reduced fatigue, 37 increased sleep quality, 38 reduced stress, 39 increased the quality of life, reduced anxiety and depression. 37 Although there are many randomized controlled studies in the literature on the subject, no systematic review has been encountered. ...
... It was found that telehealth practices improved/increased psychological empowerment in 2 studies, and it did not affect psychological empowerment in 1 study. It was determined that telehealth BREATH 36 and PCO 51 improved the psychological empowerment of women with breast cancer, whereas My-GMC 44 did not affect psychological empowerment of them. ...
... Research findings proved that telehealth practices have an impact on the quality of life of women with breast cancer. 41,48,50 When the studies were examined in terms of intervention; patient education with mobile games, 41 breast cancer e-support program, 48 m-health, 50 psychoeducational intervention delivered on the phone, 48 Designing life rhythms 52 improved the quality of life, and it was determined that the web-based special psychoeducation program 45 and the breast cancer e-health trial, 36 which is a web-based self-management intervention, did not affect the quality of life. There are mind-body programs and psychoeducation practices that comprehensively address many aspects of the quality of life of breast cancer patients such as general health and cancer-related mental well-being, cognitive functions, fatigue, nausea and vomiting. ...
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Objective: The purpose of this systematic review is to determine the evidence-based information and results about the effectiveness of telehealth programs on the mental health of women with breast cancer. Methods: The research process was carried out using PRISMA guidelines. Randomized controlled trials with available abstract and full text, which were published in English with the keywords "telehealth," "telemedicine," "web-based therapy," "telepsychiatry," "online therapy" and "breast cancer" in Pub Med, PsycINFO, Medline, Science Direct, Scopus, Web of Sciences and Cochrane databases between 2015-2019 were searced. As a result of the evaluations, the research was completed with 16 studies meeting the research criteria. Results: There was strong evidence for reduce the fear of relapse of cancer, depressive symptoms and severity of depression, distress, intrusive thoughts, anxiety, sleep disorder, insomnia, improve quality of life and for improve cognitive functions, improve psychological strength and sleep quality of telehealth programs in women with breast cancer. Furthermore, evidence was found for increase psychological health, functionality, optimism and control over the future, positive mood and life appreciation, and drug compliance of these programs. Conclusion: This review found evidence for the effectiveness of telehealth programs on the mental problems of women with breast cancer. In this sense, it is recommended to expand the use of telehealth programs, which can save time and cost, are accessible and easily applicable by nurses, to improve the mental health of women with breast cancer, and further studies are recommended.
... Second, most studies used face-to-face delivery methods, and only a few studies employed either telephone-or internet-based interventions. Some previous studies showed that online-based interventions can be as effective as face-to-face treatments [59], but others claimed that supplementary approaches (e.g., professional support via face-to-face or online, standard telephone or email reminders) are necessary to compensate for the limitations of online-based interventions [60,61]. Thus, the question of which method is more effective in reducing FCR symptoms among BCSs remains. ...
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Background: Fear of cancer recurrence (FCR) has been addressed as a cause of emotional distress among breast cancer survivors (BCSs). This study aimed to systematically review the evidence on randomized controlled trials (RCTs) of cognitive behavioral therapy (CBT) designed to reduce FCR among BCSs. Methods: A systematic review of published original research articles meeting the inclusion criteria was conducted. Five electronic databases, including the Cochrane Library, CINAHL, PubMed, PsycINFO, and Web of Science, were independently searched to identify relevant articles. The Consolidated Standards of Reporting Trials (CONSORT) 2010 checklist was used to evaluate the quality of the eligible studies. Results: Through a database search and a manual review process, seventeen quantitative studies with an RCT study design were included in the current systematic review. The interventions varied greatly in length and intensity, but the study designs and methodologies were similar. RCTs with face-to-face interventions of at least 1 month seemed to be more effective in reducing FCR outcomes and complying with than the CONSORT 2010 criteria than those with a brief online or telephone format of interventions; nevertheless, most RCT interventions appeared to be effective. Conclusions: These findings highlight the importance of conducting well-designed CBT interventions to reduce FCR in BCSs with diverse populations at multiple sites, thereby improving the quality of research in this area.
Article
Objective Telehealth-based exercise intervention as a non-pharmacological intervention has gradually emerged in breast cancer (BC), which shows feasibility and high levels of patient satisfaction. This systematic review aims to identify the effect of telehealth-based exercise interventions on the physical activity (PA) of patients with BC. Methods CENTRAL, CINAHL, PsycINFO, EMBASE, PubMed, Web of Science, ClinicalTrials.gov, CNKI, Wanfang, VIP, and SinoMed were searched. Study selection and quality appraisal were performed independently by two reviewers. Standardized mean difference (SMD) with corresponding 95% confidence interval was pooled. The review protocol was registered in PROSPERO (CRD42022326484). Results Nine studies, which included 1127 patients with BC, were identified. Compared with usual care, the telehealth-based exercise intervention had a significantly positive effect on PA (SMD=0.26, 95% CI 0.09 to 0.43, P=0.003), aerobic capacity (SMD=0.20, 95% CI 0.03 to 0.38, P=0.002), upper body function (MD=−4.56, 95% CI −7.66 to −1.47, P=0.004), upper muscle strength (SMD=0.26, 95% CI −0.09 to 0.42, P=0.002), lower muscle strength (SMD=−0.95, 95% CI −1.27 to −0.62, P<0.00001), abdominal muscle strength (SMD=23.85, 95% CI −13.84 to 33.86, P<0.00001), fatigue (SMD=−0.56, 95% CI 0.13 to 1.00, P=0.01), and quality of life (QoL; SMD = −0.25, 95% CI: −0.50 to −0.01, P = 0.04). Conversely, anthropometric and body composition and pain did not differ significantly between the two groups. Conclusions Telehealth-based exercise intervention improved PA, physical performance, fatigue, and QoL of patients with BC compared with routine care, which should be promoted clinically as a comprehensive treatment for BC.
Article
Background: Globally, the burden of cancer on population health is growing. Recent trends such as increasing survival rates have resulted in a need to adapt cancer care to ensure a good care experience and manageable expenditures. eHealth is a promising way to increase the quality of cancer care and support patients and survivors. Objective: The aim of this systematic review was 2-fold. First, we aimed to provide an overview of eHealth interventions and their characteristics for Dutch patients with and survivors of cancer. Second, we aimed to provide an overview of the empirical evidence regarding the impact of eHealth interventions in cancer care on population health, quality of care, and per capita costs (the Triple Aim domains). Methods: The electronic databases Web of Science, PubMed, Cochrane, and Ovid PsycINFO were searched using 3 key search themes: eHealth interventions, cancer care, and the Netherlands. The identified interventions were classified according to predetermined criteria describing the intervention characteristics (eg, type, function, and target population). Their impact was subsequently examined using the Triple Aim framework. Results: A total of 38 interventions were identified. Most of these were web portals or web applications functioning to inform and self-manage, and target psychosocial factors or problems. Few interventions have been tailored to age, disease severity, or gender. The results of this study indicate that eHealth interventions could positively affect sleep quality, fatigue, and physical activity of patients with and survivors of cancer. Inconclusive results were found regarding daily functioning and quality of life, psychological complaints, and psychological adjustment to the disease. Conclusions: eHealth can improve outcomes in the Triple Aim domains, particularly in the population health and quality of care domains. Cancer-related pain and common symptoms of active treatment were not targeted in the included interventions and should receive more attention. Further research is needed to fully understand the impact of eHealth interventions in cancer care on participation, accessibility, and costs. The latter can be examined in economic evaluations by comparing eHealth interventions with care as usual.
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Objective To identify the elements of internet-based support interventions and assess their effectiveness at reducing psychological distress, anxiety and/or depression, physical variables (prevalence, severity and distress from physical symptoms) and improving quality of life, social support and self-efficacy among patients with breast cancer. Design Systematic review and narrative synthesis. Data sources Web of Science, Cochrane Library, PubMed, MEDLINE, PsycINFO, CINAHL, CNKI, Wanfang and VIP from over the past 5 years of each database to June 2021. Eligibility criteria for study selection Included were randomised controlled trials (RCTs) or quasi-experimental (QE) studies focusing on internet-based support interventions in patients with breast cancer. Data extraction and synthesis Reviewers independently screened, extracted data and assessed risk of bias (Cochrane Collaboration’ risk of bias tool, Joanna Briggs Institute reviewer’s manual). Narrative synthesis included the effect and elements of internet-based support interventions for women with breast cancer. Results Out of 2842 articles, 136 qualified articles were preliminarily identified. After further reading the full text, 35 references were included, including 30 RCTs and five QE studies. Internet-based support interventions have demonstrated positive effects on women’s quality of life and physical variables, but inconsistent effectiveness has been found on psychological distress, symptoms of anxiety and/or depression, social support and self-efficacy. Conclusions Internet-based support interventions are increasingly being used as clinically promising interventions to promote the health outcomes of patients with breast cancer. Future research needs to implement more rigorous experimental design and include sufficient sample size to clarify the effectiveness of this internet-based intervention. PROSPERO registration number CRD42021271380.
Article
Aim: This study is conducted to synthesize the effects of web-based self-management intervention on patients with cancer. Evaluation: We searched Web of Science, PubMed, Embase and Cochrane library databases for related randomized controlled trials from inception through 2021. Reference lists of included studies were also searched for additional qualified studies. For quantitative data synthesis, standardized mean differences were used to eliminate the influence caused by different scales. Narrative synthesis was also performed. Key issues: Nine in 1149 studies were included for narrative and quantitative analysis. The pooled data suggested that patients in the intervention group had better quality of life (standardized mean difference = 1.091, 95% confidence interval: 0.155-2.028) and lower depression (standardized mean difference = -1.634, 95% confidence interval: -2.980 to -0.287) than those in the control group. The result of narrative synthesis is that patients receiving intervention had lower cancer or symptom distress and higher self-efficacy than those in the control group. Conclusion: Web-based self-management intervention improved lives of cancer survivors.
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Background Psychoeducation has emerged as an intervention for women with breast cancer (BC). This meta-analysis evaluated the effectiveness of psychoeducation on adherence to diagnostic procedures and medical treatment, anxiety, depression, quality of life (QoL), and BC knowledge among patients with BC symptoms or diagnosis and BC survivors. Methods A systematic literature search (in PubMed, Embase, PsycINFO and Cochrane) for randomised controlled trials (RCTs) comparing the effects of psychoeducation to control among patients with BC symptoms or diagnosis and BC survivors. Effects were expressed as relative risks (RRs) and standardized mean differences (SMDs) with their 95% confidence intervals. Results Twenty-seven RCTs (7742 participants; 3880 psychoeducation and 3862 controls) were included. Compared with controls, psychoeducation had no significant effect on adherence to diagnostic procedures and medical treatment (RR 1.553; 95% CI 0.733 to 3.290, p = .16), but it significantly decreased anxiety (SMD -0.710, 95% CI -1.395 to −0.027, p = .04) and improved QoL with (SMD 0.509; 95% CI 0.096 to 0.923, p < .01). No effects were found for psychoeducation on depression (SMD -0.243, 95% CI -0.580 to 0.091, p = .14), or BC knowledge (SMD 0.718, 95% CI -0.800 to 2.236, p = .23). Conclusion We demonstrated that psychoeducation did not improve adherence to diagnostic procedures and treatment, depression and BC knowledge but was valuable for reducing anxiety and improving QoL. Future studies may explore the effectiveness of psychoeducation in promoting adherence across various types of cancer.
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Purpose: To systematically evaluate the effects of Electronic health (eHealth) interventions on fatigue, pain, and sleep disorders in cancer survivors. Design: A systematic review and meta-analysis was conducted. Methods: Relevant studies were searched from five databases (MEDLINE, Embase, the Cochrane Central Register of Controlled trials, CINAHL, and PsycINFO). The comprehensive literature search was done in December 2020. Only randomized controlled trials (RCTs) that examined the effects of eHealth interventions among cancer survivors were included. Findings: Twenty-five RCTs were included. The meta-analysis showed that eHealth interventions had a positive impact on pain interference (SMD = -0.37, 95% CI: -0.54 to -0.20, p = 0.0001) and sleep disorders (SMD = -0.43, 95% CI: -0.77 to -0.08, p = 0.02) but not on pain severity or fatigue in cancer survivors. The sensitivity and subgroup analyses indicated that the pooled results were robust and reliable. Conclusion: eHealth interventions are effective in improving pain interference and sleep disorders in cancer survivors. Additional high-quality RCTs are needed to test the effectiveness of eHealth interventions on fatigue, pain, and sleep disorders in cancer survivors. Clinical relevance: This systematic review and meta-analysis provides evidence to offer effective and sustainable eHealth care for symptom management among cancer survivors.
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The population of cancer survivors has grown steadily over the past several decades. Surviving cancer, however, is not synonymous with a life free of problems related to the disease and its treatment. In this paper we provide a brief overview of selected physical and psychosocial health problems prevalent among cancer survivors, namely pain, fatigue, psychological distress and work participation. We also address issues surrounding self-management and e-Health interventions for cancer survivors, and programmes to encourage survivors to adopt healthier lifestyles. Finally, we discuss approaches to assessing health-related quality of life in cancer survivors, and the use of cancer registries in conducting psychosocial survivorship research. We highlight research and practice priorities in each of these areas. While the priorities vary per topic, common themes that emerged included: (1) Symptoms should not be viewed in isolation, but rather as part of a cluster of interrelated symptoms. This has implications for both understanding the aetiology of symptoms and for their treatment; (2) Psychosocial interventions need to be evidence-based, and where possible should be tailored to the needs of the individual cancer survivor. Relatively low cost interventions with self-management and e-Health elements may be appropriate for the majority of survivors, with resource intensive interventions being reserved for those most in need; (3) More effort should be devoted to disseminating and implementing interventions in practice, and to evaluating their cost-effectiveness; and (4) Greater attention should be paid to the needs of vulnerable and high-risk populations of survivors, including the socioeconomically disadvantaged and the elderly.
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Like other medical specialties, psychiatry has traditionally sought to develop treatments targeted at ameliorating a deficit of the patient. However, there are different therapeutic models that focus on utilising patients' personal and social resources instead of ameliorating presumed deficits. A synopsis of such models might help to guide further research and improve therapeutic interventions. To conduct a conceptual review of resource-oriented therapeutic models in psychiatry, in order to identify their shared characteristics. The literature was searched to identify a range of resource-oriented therapeutic models, particularly for patients with severe mental illness. Key texts for each model were analysed using a narrative approach to synthesise the concepts and their characteristics. Ten models were included: befriending, client-centred therapy, creative music therapy, open dialogue, peer support workers, positive psychotherapy, self-help groups, solution-focused therapy, systemic family therapy and therapeutic communities. Six types of resources were utilised: social relationships, patients' decision-making ability, experiential knowledge, patients' individual strengths, recreational activities and self-actualising tendencies. Social relationships are a key resource in all the models, including relationships with professionals, peers, friends and family. Two relationship dimensions - reciprocity and expertise - differed across the models. The review suggests that a range of different therapeutic models in psychiatry address resources rather than deficits. In various ways, they all utilise social relationships to induce therapeutic change. A better understanding of how social relationships affect mental health may inform the development and application of resource-oriented approaches.
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There is now substantial evidence that Web-based interventions can be effective at changing behavior and successfully treating psychological disorders. However, interest in the impact of usage on intervention outcomes has only been developed recently. To date, persistence with or completion of the intervention has been the most commonly reported metric of use, but this does not adequately describe user behavior online. Analysis of alternative measures of usage and their relationship to outcome may help to understand how much of the intervention users may need to obtain a clinically significant benefit from the program. The objective of this study was to determine which usage metrics, if any, are associated with outcome in an online depression treatment trial. Cardiovascular Risk E-couch Depression Outcome (CREDO) is a randomized controlled trial evaluating an unguided Web-based program (E-couch) based on cognitive behavioral therapy and interpersonal therapy for people with depression and cardiovascular disease. In all, 280 participants in the active arm of the trial commenced the program, delivered in 12 modules containing pages of text and activities. Usage data (eg, number of log-ins, modules completed, time spent online, and activities completed) were captured automatically by the program interface. We estimated the association of these and composite metrics with the outcome of a clinically significant improvement in depression score on the Patient Health Questionnaire (PHQ-9) of ≥5 points. In all, 214/280 (76.4%) participants provided outcome data at the end of the 12-week period and were included in the analysis. Of these, 94 (43.9%) participants obtained clinically significant improvement. Participants logged into the program an average of 18.7 times (SD 8.3) with most (62.1%, 133/214) completing all 12 modules. Average time spent online per log-in was 17.3 minutes (SD 10.5). Participants completed an average of 9 of 18 activities available within the program. In a multivariate regression model, only the number of activities completed per log-in was associated with a clinically significant outcome (OR 2.82, 95% CI 1.05-7.59). The final model predicted 7.4% of variance in outcome. Curve estimates indicated that significant logarithmic (P=.009) and linear (P=.002) relationships existed between activities completed per log-in and clinically significant change. Only one objective measure of usage was independently associated with better outcome of a Web-based intervention of known effectiveness. The 4 usage metrics retained in the final step of the regression accounted for little outcome variance. Medium level users appeared to have little additional benefit compared to low users indicating that assumptions of a linear relationship between use and outcome may be too simplistic and further models and variables need to be explored to adequately understand the relationship. Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12610000085077; http://www.anzctr.org.au/ACTRN12610000085077.aspx (Archived by WebCite at http://www.webcitation.org/6K9FQtKBn).
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New models of cancer care and survivorship ask for empowered patients. But how do we measure that patients can derive strength from themselves (intrapersonal) and their perceived social support (interpersonal)? The 40-item Cancer Empowerment Questionnaire (CEQ) measures psychological empowerment as an individual outcome measure. The CEQ was validated in 140 nonmetastatic female breast cancer survivors (mean 5.5 years postsurgery). Principal component analysis elicited four factors representing intrapersonal (personal strength) and interpersonal (social support, community, health care) aspects of empowerment. The CEQ provides a reliable (Cronbach's α = 0.73-0.94) and valid first attempt to operationalize psychological empowerment in cancer care.
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Generic fully automated Web-based self-management interventions are upcoming, for example, for the growing number of breast cancer survivors. It is hypothesized that the use of these interventions is more individualized and that users apply a large amount of self-tailoring. However, technical usage evaluations of these types of interventions are scarce and practical guidelines are lacking. To gain insight into meaningful usage parameters to evaluate the use of generic fully automated Web-based interventions by assessing how breast cancer survivors use a generic self-management website. Final aim is to propose practical recommendations for researchers and information and communication technology (ICT) professionals who aim to design and evaluate the use of similar Web-based interventions. The BREAst cancer ehealTH (BREATH) intervention is a generic unguided fully automated website with stepwise weekly access and a fixed 4-month structure containing 104 intervention ingredients (ie, texts, tasks, tests, videos). By monitoring https-server requests, technical usage statistics were recorded for the intervention group of the randomized controlled trial. Observed usage was analyzed by measures of frequency, duration, and activity. Intervention adherence was defined as continuous usage, or the proportion of participants who started using the intervention and continued to log in during all four phases. By comparing observed to minimal intended usage (frequency and activity), different user groups were defined. Usage statistics for 4 months were collected from 70 breast cancer survivors (mean age 50.9 years). Frequency of logins/person ranged from 0 to 45, total duration/person from 0 to 2324 minutes (38.7 hours), and activity from opening none to all intervention ingredients. 31 participants continued logging in to all four phases resulting in an intervention adherence rate of 44.3% (95% CI 33.2-55.9). Nine nonusers (13%), 30 low users (43%), and 31 high users (44%) were defined. Low and high users differed significantly on frequency (P<.001), total duration (P<.001), session duration (P=.009), and activity (P<.001). High users logged in an average of 21 times, had a mean session duration of 33 minutes, and opened on average 91% of all ingredients. Signing the self-help contract (P<.001), reporting usefulness of ingredients (P=.003), overall satisfaction (P=.028), and user friendliness evaluation (P=.003) were higher in high users. User groups did not differ on age, education, and baseline distress. By reporting the usage of a self-management website for breast cancer survivors, the present study gained first insight into the design of usage evaluations of generic fully automated Web-based interventions. It is recommended to (1) incorporate usage statistics that reflect the amount of self-tailoring applied by users, (2) combine technical usage statistics with self-reported usefulness, and (3) use qualitative measures. Also, (4) a pilot usage evaluation should be a fixed step in the development process of novel Web-based interventions, and (5) it is essential for researchers to gain insight into the rationale of recorded and nonrecorded usage statistics. Netherlands Trial Register (NTR): 2935; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2935 (Archived by WebCite at http://www.webcitation.org/6IkX1ADEV).
Article
Purpose: Internet support group (ISG) members benefit from receiving social support and, according to the helper therapy principle, by providing support to others. To test the mental health benefits of providing support to others, this trial compared the efficacy of a standard ISG (S-ISG) and an enhanced prosocial ISG (P-ISG). Methods: A two-armed randomized controlled trial with 1-month pretest and post-test assessments was conducted with women (N = 184) diagnosed in the past 36 months with nonmetastatic breast cancer who reported elevated anxiety or depression. Women were randomly assigned to either the S-ISG or P-ISG condition. Both conditions included six professionally facilitated live chat sessions (90-minute weekly sessions) and access to an asynchronous discussion board; P-ISG also included structured opportunities to help and encourage others. Results: Relative to the S-ISG, participants in the P-ISG condition exhibited more supportive behaviors (emotional, informational, and companionate support), posted more messages that were other-focused and fewer that were self-focused, and expressed less negative emotion (P < .05). Relative to the S-ISG, participants in the P-ISG condition had a higher level of depression and anxiety symptoms after the intervention (P < .05). Conclusion: Despite the successful manipulation of supportive behaviors, the P-ISG did not produce better mental health outcomes in distressed survivors of breast cancer relative to an S-ISG. The prosocial manipulation may have inadvertently constrained women from expressing their needs openly, and thus, they may not have had their needs fully met in the group. Helping others may not be beneficial as a treatment for distressed survivors of breast cancer.
Article
This article reports on the literature associated with Internet use by breast cancer patients. Reviewing the literature indicates that breast cancer patients can use the Internet as a source of information, social support, shared experience, empowerment, positive role models, professional support and patient advocacy. Also, studies reveal that a number of factors such as patients' personal characteristics, computer competence, computer access, attitudes of patients toward Internet and trust influence patients' decisions to use Internet to get cancer related information. It is suggested that health care providers should help patients to understand the role of Internet in their health care. Furthermore, they should encourage them to learn and use a credentialed website that is comprehensive and regularly updated by objective and unbiased experts to assist them in coping with their disease.
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Patients with chronic somatic conditions face unique challenges accessing mental health care outside of their homes due to symptoms and physical limitations. Internet-based cognitive behavioral therapy (ICBT) has shown to be effective for various psychological conditions. The increasing number of recent trials need to be systematically evaluated and quantitatively analyzed to determine whether ICBT is also effective for chronic somatic conditions and to gain insight into the types of problems that could be targeted. Our goal was to describe and evaluate the effectiveness of guided ICBT interventions for chronic somatic conditions on general psychological outcomes, disease-related physical outcomes, and disease-related impact on daily life outcomes. The role of treatment length was also examined. PubMed, PsycINFO, and Embase were searched from inception until February 2012, by combining search terms indicative of effect studies, Internet, and cognitive behavioral therapy. Studies were included if they fulfilled the following six criteria: (1) randomized controlled trial, (2) Internet-based interventions, (3) based on cognitive behavioral therapy, (4) therapist-guided, (5) adult (≥18 years old) patients with an existing chronic somatic condition, and (6) published in English. 23 randomized controlled trials of guided ICBT were selected by 2 independent raters after reviewing 4848 abstracts. Demographic, clinical, and methodological variables were extracted. Standardized mean differences were calculated between intervention and control conditions for each outcome and pooled using random effects models when appropriate. Guided ICBT was shown to improve all outcome categories with small effect sizes for generic psychological outcomes (effect size range 0.17-0.21) and occasionally larger effects for disease-specific physical outcomes (effect size range 0.07 to 1.19) and disease-related impact outcomes (effect size range 0.17-1.11). Interventions with a longer treatment duration (>6 weeks) led to more consistent effects on depression. Guided ICBT appears to be a promising and effective treatment for chronic somatic conditions to improve psychological and physical functioning and disease-related impact. The most consistent improvements were found for disease-specific outcomes, which supports the possible relevance of tailoring interventions to specific patient groups. Explorative analyses revealed that longer treatment length holds the promise of larger treatment effects for the specific outcome of depression. While the current meta-analysis focused on several chronic somatic conditions, future meta-analyses for separate chronic somatic conditions can further consolidate these results, also in terms of cost-effectiveness.
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