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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 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
Authors’ disclosures of potential
conflicts of interest are found in the
article online at 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:
© 2015 by American Society of Clinical
DOI: 10.1200/JCO.2013.54.9386
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.
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.
Access to BREATH reduced distress among BCSs, but this effect was not sustained during
J Clin Oncol 33. © 2015 by American Society of Clinical Oncology
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,
is characterized by physical, emo-
tional, and social recovery.
Women report high
unmet care needs
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.
70% of breast cancer survivors (BCSs; ie, women
who have completed primary breast cancer treat-
ment with no evidence of recurrence
) adjust well
during the re-entry phase, but a substantial propor-
tion report high levels of distress.
Better diagnosis and therapy mean that more
women survive breast cancer, and self-management
and e-health
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,
the Internet is promising for providing psycho-
oncological interventions.
However, there are few
randomized controlled trials (RCTs) of Web-based
interventions to support re-entry adjustment. To
date, most Web-based interventions including
© 2015 by American Society of Clinical Oncology 1 latest version is at
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women with breast cancer have not been either re-entry specific
breast cancer specific,
or have predominantly focused on peer
support groups
or informational support.
In a recent overview
advocating re-entry specific care, Stanton
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,
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
and the model of psychological well-being in cancer
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.
Study Design and Participants
The BREATH study protocol has been published elsewhere.
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
(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
(n = 70)
Randomly allocated to
CAU alone
(n = 80)
Completed T1 assessment
at 4 months
(n = 62)
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 +
(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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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
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).
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
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.
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.
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).
The CEQ presumes that patients
can derive strength from themselves (intrapersonal) and from their
social surroundings (interpersonal). Baseline internal consistency was
good (Cronbach’s
Secondary outcomes reflected negative adjustment (general
and cancer-specific distress,
and fear of
cancer recurrence
) and positive adjustment (self-efficacy,
personal control,
quality of life,
new ways of living,
and valuing life
). For details of
secondary outcomes, see our study protocol
(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.
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)
(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
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
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 © 2015 by American Society of Clinical Oncology 3
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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.
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,
Schauenburg and Strack
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
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.
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
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)
(n 70)
CAU Alone
(n 80)
Primary outcomes
Distress (SCL-90
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†
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]
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]
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]
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]
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]
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]
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]†
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]†
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
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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).
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,
nonpharmacologic treatment,
and eHealth trials).
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)
(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]†
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]†
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.
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)
and Web-based (effect size
range, 0.17 to 0.21)
interventions for people with cancer
chronic somatic conditions.
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.
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,
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
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,
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.
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.
The study
sample also proved representative with regard to psychological
10 Months6 Months4 MonthsBaseline
SCL-90 Total Score
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
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 © 2015 by American Society of Clinical Oncology 7
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Copyright © 2015 American Society of Clinical Oncology. All rights reserved.
functioning during the first year after treatment. As in other studies
of patients with breast
or other
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.
Disclosures provided by the authors are available with this article at
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 © 2015 by American Society of Clinical Oncology 9
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Copyright © 2015 American Society of Clinical Oncology. All rights reserved.
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.
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.
... [11][12][13] So far, the effectiveness of these interventions has been shown in various diseases such as diabetes, hypertension, cardiovascular disease, and cancer. [14][15][16][17] The results of the study by Soriano Marcolino et al demonstrated that numerous m-health-based interventions had positive effects in cases such as managing chronic diseases, improving disease symptoms, and reducing mortality and hospitalization rates. 18 In critical situations such as the COVID-19 pandemic, providing care during m-health interventions can be an effective and efficient method when the elderly have limited access to healthcare services. ...
... 34 In addition, one study was about breast cancer. 17 Moreover, two, one, and four studies were about cancer screening (breast 35 and colorectal 36 ), chronic obstructive pulmonary disease (COPD), 37 and a combination of two diseases, respectively (Table 1). [38][39][40][41] Types of m-health interventions and the number of studies in any type are presented in Table 2. M-health interventions can be divided into 5 general groups, including messages, calls, applications, devices, and internet-based interventions. ...
... A general self-efficacy scale was used to measure self-efficacy in the form of selfreport. 17 ...
Objectives: To investigate mobile health (m-health) interventions in self-care and treatment adherence in older adults. Design: A review study. Participants: People over 50 years of age with chronic diseases. Interventions: M-health-based interventions were used to promote self-care and treatment adherence. Outcome Measures: Self-care and adherence. Results: The duration of interventions in different studies was between 8 weeks to 12 months. All participants were over 50 years old and included both male and female groups. The findings showed that m-health has a good potential for educating and empowering the target population. M-health interventions can be categorized into 5 groups such as messages, calls, applications, devices, and Internet-based interventions. They can also be used to provide care and promote health in various diseases such as diabetes, heart disease, cancer, and lung disease. In this study, self-care included practices such as self-care behaviors, self-efficacy, and self-monitoring/management. Similarly, adherence included practices such as treatment/ medication adherence, and healthy behaviors adherence. Conclusions: The results indicated the positive effects of m-health on improving self-care and treatment adherence. Considering the increasing population of elderly people in the world, and the increase of various problems and challenges affecting their health, using novel technologies to provide health and care services while reducing the adverse effect caused by the lack of resources can bring positive social and economic effects. It seems that the planned use of this technology can help increase the healthcare system’s efficiency and reduce health costs.
... In den eingeschlossenen Publikationen bestand Heterogenität hinsichtlich der Ausgestaltung und den inhaltlichen Schwerpunkten der Interventionen. Insgesamt konnten 3 Publikationen mit Interventionen zur Lebensstiländerung [25,26,28] und 8 psychosoziale Interventionen unterschieden werden [18][19][20][21][22][23][24]27]. ...
... In der Mehrzahl der Publikationen erfolgte in den Studien der Kontakt zu den Behandlern und Therapeuten über E-Mail [22,24,27] bzw. einer Kombination aus E-Mail und Telefon [19-21, 23, 28]. ...
... In jeweils 8 Publikationen wurde in der jeweiligen Studie eine Warteliste als Kontrollgruppe (KG) festgelegt [18,20,21,[23][24][25][26][27]. In einer Publikation erhielten die Teilnehmer lediglich Informationsmaterial [28] und in weiteren 2 Publikationen die herkömmliche Nachsorge (TAU) [19,22]. ...
Zusammenfassung Hintergrund Brustkrebs ist die bedeutendste Krebserkrankung bei Frauen. Die tumor- und therapiebedingten Folgen führen zu einer langfristigen Beeinträchtigung der Funktionsfähigkeit. Der nachhaltige Transfer rehabilitativer Erfolge in den Alltag stellt eine Herausforderung für alle Akteure des Systems dar. Der Einsatz von Telemedizin erscheint vor diesem Hintergrund als eine Möglichkeit, das in der Rehabilitation Erreichte im Alltag langfristig zu stabilisieren. Das Ziel der vorliegenden Übersicht ist es die Evidenz von telemedizinischen Nachsorgeangeboten bei Frauen mit Brustkrebs darzulegen und die Wirksamkeit auf verschiedenen Ebenen der Funktionsfähigkeit herauszuarbeiten. Methodik Es erfolgte eine systematische Suche nach deutsch- oder englischsprachigen randomisiert kontrollierten Studien zur Wirksamkeit von telemedizinischen rehabilitativen Nachsorgeangeboten für Frauen mit Brustkrebs in den Fachdatenbanken PubMed und The Cochrane Library im Zeitraum April bis Mai 2020 und einer Aktualisierung der Suche im August 2020. Ergebnisse Insgesamt wurden 11 relevante Publikationen zu 10 Interventionsstudien identifiziert. Es wurde keine Studie aus Deutschland gefunden. Es fanden sich Studien für die Bereiche psychosoziale Interventionen und Interventionen zur Lebensstilveränderung. Hinsichtlich der untersuchten Zielvariablen sind vor dem Hintergrund der heterogenen Studienlage in einzelnen Parametern (therapieinduzierte Wechseljahresbeschwerden, Fatigue, Schlaffunktionen, Adhärenz) Hinweise auf positive Effekte zugunsten der Intervention festzustellen. Für einen Teil der Parameter (mentale Funktionen bzw. emotionale und kognitive Funktionen, gesundheitsbezogene Lebensqualität) kann jedoch keine ausreichende und belastbare Evidenz zur Wirksamkeit konstatiert werden. Schussfolgerungen Die Ergebnisse betonen den Bedarf der stärkeren Evidenzbasierung von telemedizinischen Angeboten zur rehabilitativen Nachsorge der Frauen mit Brustkrebs. Zur Absicherung der Befundlage sind randomisiert kontrollierte Studien im deutschen Versorgungskontext erforderlich.
... We initially identified 1954 articles excluding duplicates, and then 1922 of these articles were excluded by reading the title and abstract. Ultimately, 13 articles involving 1448 patients (707 in the eHealth group and 741 in the control group) were included in the meta-analysis after reading the entire articles [6][7][8][9]11,[17][18][19][20][21][22][23][24] (Figure 1). The basic characteristics of the included trials and the demographic characteristics of their participants are shown in Table 1. ...
... Included studies were randomized trials published from 2005 to 2020. Ten studies were conducted in high-income countries: Netherlands, 17,18,24 Germany, 19 the United States of America, 20 Spain, 9 Finland, 8 Korea, 21,23 the United Kingdom 22 ; and three in upper-middle-income country: China. 6,7,11 Regarding study population and intervention, nine studies included breast cancer patients, [6][7][8]11,17,[19][20][21]24 and four included breast cancer survivors 18,22,23 ; seven studies involved non-mobile-based eHealth platforms (software, 20 websites, [17][18][19]22 pathway programs, 8 or a combination of the former two 9 ) and six included mobilebased platforms (apps). ...
... Ten studies were conducted in high-income countries: Netherlands, 17,18,24 Germany, 19 the United States of America, 20 Spain, 9 Finland, 8 Korea, 21,23 the United Kingdom 22 ; and three in upper-middle-income country: China. 6,7,11 Regarding study population and intervention, nine studies included breast cancer patients, [6][7][8]11,17,[19][20][21]24 and four included breast cancer survivors 18,22,23 ; seven studies involved non-mobile-based eHealth platforms (software, 20 websites, [17][18][19]22 pathway programs, 8 or a combination of the former two 9 ) and six included mobilebased platforms (apps). 6,7,11,21,23,24 Regarding the followup period, seven studies with follow-up ≤3 months 6,17,[19][20][21][22][23] and six studies with 3-to 12-month follow-up. ...
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Background: Women with breast cancer and improved survival face some specific quality of life (QOL) issues. Electronic health (eHealth) is a useful tool aiming to enhance health services. However, evidence remains controversial about the effect of eHealth on QOL in women with breast cancer. Another unstudied factor is the effect on specific QOL functional domains. Therefore, we undertook a meta-analysis about whether eHealth could improve the overall and specific functional domains of QOL in women with breast cancer. Methods: PubMed, Cochrane Library, EMBASE, and Web of Science were searched to identify appropriate randomized clinical trials from database inception to March 23, 2022. The standard mean difference (SMD) served as the effect size and the DerSimonian-Laird random effects model was constructed for meta-analysis. Subgroup analyses were conducted according to different participant, intervention, and assessment scale characteristics. Results: We initially identified 1954 articles excluding duplicates and ultimately included 13 of them involving 1448 patients. The meta-analysis revealed that the eHealth group had significantly higher QOL (SMD 0.27, 95% confidence interval [95% CI] 0.13-0.40, p < 0.0001) than the usual care group. Additionally, although not statistically significant, eHealth tended to improve the physical (SMD 2.91, 95% CI -1.18 to 6.99, p = 0.16), cognitive (0.20 [-0.04, 0.43], p = 0.10), social (0.24 [-0.00, 0.49], p = 0.05), role (0.11 [0.10, 0.32], p = 0.32), and emotional (0.18 [0.08, 0.44], p = 0.18) domains of QOL. Overall, consistent benefits were observed in both the subgroup and pooled estimates. Conclusions: eHealth is superior to usual care in women with breast cancer for improved QOL. Implications for clinical practice should be discussed based on subgroup analysis results. Further confirmation is needed for the effect of different eHealth patterns on specific domains of QOL, which would help improve specific health issues of the target population.
... Most BC patients in the study had completed active cancer treatment. There were 15 website-based interventions (n = 15) [24, 25, 28, 30, 32, 36, 38-40, 44, 46, 48-51], 3 telephone-based interventions (n = 3) [29,31,43], and 8 app-based interventions (n = 8) [26,27,35,37,41,42,45,52]. One intervention for the remaining interventions was e-mail [33], video [47], and video conference [34] (n = 3). ...
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Objectives This review aimed to synthesize the available evidence on the effectiveness of telemedicine-based psychosocial interventions among breast cancer (BC) patients regarding quality of life (QOL), depression, anxiety, distress, fatigue, sleep disorders, sexual function, and fear of cancer recurrence (FCR). Methods A search of 10 databases was conducted to identify RCTs of the effects of telemedicine-based psychosocial interventions on outcomes. Selection of studies, quality appraisal, and data extraction were performed by two reviewers independently. GRADE and Cochrane risk of bias assessment tools were used for quality appraisal. Heterogeneity was determined by I², standardized mean differences (SMD) were used to determine intervention effects, and meta-analyses, subgroup analysis, and sensitivity analysis were performed. Results In total, 29 RCTs were included. Telemedicine-based psychosocial interventions improved the primary outcomes of QOL (SMD = 0.32), distress (SMD = − 0.22), and anxiety (SMD = − 0.16) in BC patients with moderate effect size. There were some improvements in the secondary outcomes of sleep disorders (SMD = − 056), sexual function (SMD = 0.19), and FCR (SMD = − 0.41). After sensitivity analysis, the effect size of fatigue was moderate (SMD = − 0.24). Conclusion Telemedicine-based psychosocial interventions are superior to usual care in BC patients with improved QOL, sexual function, and less distress, anxiety, fatigue, sleep disorders, and FCR. Due to the heterogeneity of the results for QOL, anxiety, fatigue, sleep disturbance, and FCR, these results should be interpreted cautiously. In the future, more rigorous RCTs need to be designed to identify better delivery models and intervention times to further test their effectiveness.
... 9 Such interventions are increasingly being utilized to support individuals with cancer 10 and have been found effective in reducing various psychological outcomes. [11][12][13] Few interventions have targeted fertility and sexuality, some showing positive results in reducing reproductive concerns, 14 and in improving sexual functioning, [15][16][17] and fertility knowledge. 18 Inclusion of interactive elements and opportunity for peer discussion in web-based interventions is recommended as it may increase activity and uptake of interventions, 9,19 as well as reduce feelings of loneliness. ...
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Objective: This study sought to investigate interactive participation and content of a moderated discussion forum within a web-based psychoeducational intervention aimed at alleviating sexual dysfunction and fertility distress in young adults diagnosed with cancer. Methods: The study is part of the Fex-Can Young Adult randomized controlled trial (RCT), in which young adults with self-reported sexual dysfunction or fertility distress were invited to participate. This study focuses on RCT participants that were randomized into the intervention condition. Sociodemographics and clinical characteristics of intervention participants and level of activity in the intervention were analyzed with descriptive statistics and compared between subgroups ("high" and "low" activity participants). Inductive qualitative thematic analysis was used to analyze the posts in the discussion forum. Results: Of 135 intervention participants, 24% met the criteria for high activity participation. There were no statistically significant differences found in terms of clinical and sociodemographic characteristics between high and low activity participants. Ninety-one participants (67%) accessed the discussion forum, and 19 (14%) posted at least once. Posters shared intimate details of their experiences of sexuality and fertility following cancer. The thematic analysis of posts resulted in four themes: fertility fears, perceptions of the changed body, missing out on life, and importance of support and information. Conclusions: While a smaller proportion of participants posted in the discussion forum, a majority spent time reading posts (lurkers). Participants posting in the forum shared experiences of intimate relationships, body image, parenthood concerns, and support needs. The discussion forum was used by a majority of intervention participants, and provided appreciated support for those who posted in the forum. We therefore recommend similar interventions to include this opportunity for interaction and communication.
... 9,48 This study revealed the promising acceptability and perceived usefulness of the pilot version of our mobile app and highlighted suggestions for increasing its adoption. Randomized clinical studies have demonstrated that digital health may play an important role in facilitating patient empowerment and improving symptom management in survivors of BC. [49][50][51][52][53][54] However, these were mainly fragmented, symptomspecific interventions, and the role of a comprehensive digital companion allowing continuous education, selfmanagement, and monitoring is not yet established in cancer survivors. 55,56 Moreover, social determinants of health may affect the adoption of digital health, requiring the personalization of digital devices and navigation. ...
Purpose: Optimal comprehensive survivorship care is insufficiently delivered. To increase patient empowerment and maximize the uptake of multidisciplinary supportive care strategies to serve all survivorship needs, we implemented a proactive survivorship care pathway for patients with early breast cancer at the end of primary treatment phase. Methods: Pathway components included (1) a personalized survivorship care plan (SCP), (2) face-to-face survivorship education seminars and personalized consultation for supportive care referrals (Transition Day), (3) a mobile app delivering personalized education and self-management advice, and (4) decision aids for physicians focused on supportive care needs. A mixed-methods process evaluation was performed according to the Reach, Effectiveness, Adoption, Implementation and Maintenance framework including administrative data review, pathway experience survey (patient, physician, and organization), and focus group. The primary objective was patient-perceived satisfaction with the pathway (predefined progression criteria for pathway continuation ≥70%). Results: Over 6 months, 321 patients were eligible for the pathway and received a SCP and 98 (30%) attended the Transition Day. Among 126 patients surveyed, 77 (66.1%) responded. 70.1% received the SCP, 51.9% attended the Transition Day, and 59.7% accessed the mobile app. 96.1% of patients were very or completely satisfied with the overall pathway, whereas perceived usefulness was 64.8% for the SCP, 90% for the Transition Day, and 65.2% for the mobile app. Pathway implementation seemed to be positively experienced by physicians and the organization. Conclusion: Patients were satisfied with a proactive survivorship care pathway, and the majority reported that its components were useful in supporting their needs. This study can inform the implementation of survivorship care pathways in other centers.
Objectives: The purpose of this study was to determine the effects of technology-based cancer survivorship care interventions according to the types of intervention and participant characteristics for adult cancer survivors; and the extent to which the types of intervention and participant characteristics moderate the observed effects. Methods: We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) comparing technology-based survivorship care interventions with control groups for posttreatment adult cancer survivors. Results: A total of 50 RCTs with 422 effect sizes suggested an overall significant treatment effect of technology-based survivorship care interventions. Survivorship care domains, comparison groups, and targeted outcomes were significant moderators influencing treatment effects. Conclusions: Our findings reinforce the value and applicability of technology-based survivorship care interventions that promote skill-building specifically. Interventions addressing multidimensional domains for survivorship care should be developed with advances in technology, which in turn influence enhancing cancer survivors’ capacities to address psychosocial challenges.
Background: Physical activity (PA) can improve the physical and psychological health of prostate and colorectal cancer survivors, but PA behavior change maintenance is necessary for long-term health benefits. OncoActive is a print- and web-based intervention in which prostate and colorectal cancer patients and survivors receive automatically generated, personalized feedback aimed at integrating PA into daily life to increase and maintain PA. We evaluated the long-term outcomes of OncoActive by examining the 12-month follow-up differences between OncoActive and a control group, and we explored whether PA was maintained during a 6 month non-intervention follow-up period. Methods: Prostate or colorectal cancer patients were randomly assigned to an OncoActive (n = 249) or a usual care waitlist control group (n = 229). OncoActive participants received PA advice and a pedometer. PA outcomes (i.e., ActiGraph and self-report moderate-to-vigorous intensity PA (MVPA) min/week and days with ≥30 min PA) and health-related outcomes (i.e., fatigue, depression, physical functioning) were assessed at baseline, 6 months, and 12 months. Differences between groups and changes over time were assessed with multilevel linear regressions for the primary outcome (ActiGraph MVPA min/week) and all additional outcomes. Results: At 12 months, OncoActive participants did not perform better than control group participants at ActiGraph MVPA min/week, self-report MVPA min/week, or ActiGraph days with PA. Only self-report days with PA were significantly higher in OncoActive compared to the control group. For health-related outcomes only long-term fatigue was significantly lower in OncoActive. When exploratively examining PA within OncoActive, the previously found PA effects at the end of the intervention (6 months follow-up) were maintained at 12 months. Furthermore, all PA outcomes improved significantly from baseline to 12 months. The control group showed small but non-significant improvements from 6 months to 12 months (and from baseline to 12 months), resulting in a decline of differences between groups. Conclusion: The majority of previously reported significant between-group differences at 6 months follow-up were no longer present at long-term follow-up, possibly because of natural improvement in the control group. At long-term follow-up, fatigue was significantly lower in OncoActive compared to control group participants. Computer-tailored PA advice may give participants an early start toward recovery and potentially contributes to improving long-term health.
Background: Internet-based cognitive behavioral therapy (ICBT) is a relatively new therapy with unknown effectiveness in patients with cancer. In addition, therapist-guided and self-guided ICBT patient-specific outcomes for cancer patients remain to be explored. Objective: To explore the effects of ICBT on psychological outcomes, physical outcomes, and daily life outcomes in patients with cancer. Methods: Electronic databases such as PubMed, Web of Science, Cochrane Library, EMBASE, APA PsycINFO, ProQuest, and were searched for relevant studies published from their inception to October 2022. Five GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) considerations were used to assess the quality of relevant evidence. Data analysis was performed via RevMan 5.4 (The Cochrane Collaboration, London, United Kingdom) and Stata 15.0 (StataCorp, College Station, Texas). Results: Three thousand two hundred forty-nine participants from 20 studies were included in the meta-analysis. Statistically significant effects of ICBT were found on psychological distress, quality of life (QOL), anxiety, and depression, after the intervention. A separate analysis of follow-up data showed that ICBT had a sustainable effect on psychological distress, anxiety, and depression. Subgroup analyses showed that therapist-guided ICBT was more effective for psychological distress and QOL. Conclusion: Internet-based cognitive behavioral therapy can improve symptom management for patients with cancer. Implications for practice: Internet-based cognitive behavioral therapy effectively improves psychological distress, anxiety, and depression in patients with cancer after intervention and at follow-up. Internet-based cognitive behavioral therapy improved QOL for cancer patients postintervention but not during follow-up. Internet-based cognitive behavioral therapy did not relieve fatigue or fear of recurrence in cancer patients. Therapist-guided ICBT is recommended for its superior outcomes in alleviating psychological distress and improving overall QOL in adults with cancer when compared with self-guided ICBT.
The objective of this study was to explore the mediation effects of coping strategies on the relationship between uncertainty and quality of life in Korean women with gynecological cancer. Mishel's Uncertainty in Illness Theory and Lazarus and Folkman's Stress and Coping Theory were used to guide the study. Three coping strategies (problem-focused, active emotional, and avoidant emotional) partially mediated the relationship between uncertainty and quality of life. This work provides evidence that reducing uncertainty has significant effects on coping strategies and positively affects the quality of life in women with gynecological cancer.
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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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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.
Adequate reporting of randomized, controlled trials (RCTs) is necessary to allow accurate critical appraisal of the validity and applicability of the results. The CONSORT (Consolidated Standards of Reporting Trials) Statement, a 22-item checklist and flow diagram, is intended to address this problem by improving the reporting of RCTs. However, some specific issues that apply to trials of nonpharmacologic treatments (for example, surgery, technical interventions, devices, rehabilitation, psychotherapy, and behavioral intervention) are not specifically addressed in the CONSORT Statement. Furthermore, considerable evidence suggests that the reporting of nonpharmacologic trials still needs improvement. Therefore, the CONSORT group developed an extension of the CONSORT Statement for trials assessing nonpharmacologic treatments. A consensus meeting of 33 experts was organized in Paris, France, in February 2006, to develop an extension of the CONSORT Statement for trials of nonpharmacologic treatments. The participants extended 11 items from the CONSORT Statement, added 1 item, and developed a modified flow diagram. To allow adequate understanding and implementation of the CONSORT extension, the CONSORT group developed this elaboration and explanation document from a review of the literature to provide examples of adequate reporting. This extension, in conjunction with the main CONSORT Statement and other CONSORT extensions, should help to improve the reporting of RCTs performed in this field.
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.
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.
The purpose of this trial was to evaluate the effect of a Web-based, self-report assessment and educational intervention on symptom distress during cancer therapy. A total of 752 ambulatory adult participants were randomly assigned to symptom/quality-of-life (SxQOL) screening at four time points (control) versus screening, targeted education, communication coaching, and the opportunity to track/graph SxQOL over time (intervention). A summary of the participant-reported data was delivered to clinicians at each time point in both groups. All participants used the assessment before a new therapeutic regimen, at 3 to 6 weeks and 6 to 8 weeks later, completing the final assessment at the end of therapy. Change in Symptom Distress Scale-15 (SDS-15) score from pretreatment to end of study was compared using analysis of covariance and regression analysis adjusting for selected variables. We detected a significant difference between study groups in mean SDS-15 score change from baseline to end of study: 1.27 (standard deviation [SD], 6.7) in the control group (higher distress) versus -0.04 (SD, 5.8) in the intervention group (lower distress). SDS-15 score was reduced by an estimated 1.21 (95% CI, 0.23 to 2.20; P = .02) in the intervention group. Baseline SDS-15 score (P < .001) and clinical service (P = .01) were predictive. Multivariable analyses suggested an interaction between age and study group (P = .06); in subset analysis, the benefit of intervention was strongest in those age > 50 years (P = .002). Web-based self-care support and communication coaching added to SxQOL screening reduced symptom distress in a multicenter sample of participants with various diagnoses during and after active cancer treatment. Participants age > 50 years, in particular, may have benefited from the intervention.