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Internet-based versus face-to-face cognitive-behavioral intervention for depression: A randomized controlled non-inferiority trial


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In the past decade, a large body of research has demonstrated that internet-based interventions can have beneficial effects on depression. However, only a few clinical trials have compared internet-based depression therapy with an equivalent face-to-face treatment. The primary aim of this study was to compare treatment outcomes of an internet-based intervention with a face-to-face intervention for depression in a randomized non-inferiority trial. A total of 62 participants suffering from depression were randomly assigned to the therapist-supported internet-based intervention group (n=32) and to the face-to-face intervention (n=30). The 8 week interventions were based on cognitive-behavioral therapy principles. Patients in both groups received the same treatment modules in the same chronological order and time-frame. Primary outcome measure was the Beck Depression Inventory-II (BDI-II); secondary outcome variables were suicidal ideation, anxiety, hopelessness and automatic thoughts. The intention-to-treat analysis yielded no significant between-group difference (online vs. face-to-face group) for any of the pre- to post-treatment measurements. At post-treatment both treatment conditions revealed significant symptom changes compared to before the intervention. Within group effect sizes for depression in the online group (d=1.27) and the face-to-face group (d=1.37) can be considered large. At 3-month follow-up, results in the online group remained stable. In contrast to this, participants in the face-to-face group showed significantly worsened depressive symptoms three months after termination of treatment (t=-2.05, df=19, p<.05). Due to the small sample size, it will be important to evaluate these outcomes in adequately-powered trials. This study shows that an internet-based intervention for depression is equally beneficial to regular face-to-face therapy. However, more long term efficacy, indicated by continued symptom reduction three months after treatment, could be only be found for the online group.
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Research report
Internet-based versus face-to-face cognitive-behavioral intervention
for depression: A randomized controlled non-inferiority trial
Birgit Wagner
, Andrea B. Horn
, Andreas Maercker
Department of Psychosomatic Medicine and Psychotherapy, University of Leipzig, Semmelweisstr. 10, 04103 Leipzig, Germany
Department of Psychology, University of Zurich, Binzmühlestr. 14/17, 8050 Zurich, Switzerland
article info
Article history:
Received 12 April 2013
Received in revised form
20 June 2013
Accepted 21 June 2013
Background and aims: In the past decade, a large body of research has demonstrated that internet-based
interventions can have benecial effects on depression. However, only a few clinical trials have compared
internet-based depression therapy with an equivalent face-to-face treatment. The primary aim of this study
was to compare treatment outcomes of an internet-based intervention with a face-to-face intervention for
depression in a randomized non-inferiority trial.
Method: A total of 62 participants suffering from depression were randomly assigned to the therapist-
supported internet-based intervention group (n¼32) and to the face-to-face intervention (n¼30). The 8 week
interventions were based on cognitive-behavioral therapy principles. Patients in both groups received the same
treatment modules in the same chronological order and time-frame. Primary outcome measure was the Beck
Depression Inventory-II (BDI-II); secondary outcome variables were suicidal ideation, anxiety, hopelessness and
automatic thoughts.
Results: The intention-to-treat analysis yielded no signicant between-group difference (online vs. face-to-face
group) for any of the pre- to post-treatment measurements. At post-treatment both treatment conditions
revealed signicant symptom changes compared to before the intervention. Within group effect sizes for
depression in the online group (d¼1.27) an d th e faceto-face group (d¼1.37) can be considered large. At
3-month follow-up, results in the online group remained stable. In contrast to this, participants in the face-to-
facegroupshowedsignicantly worsened depressive symptoms three months after termination of treatment
(t¼2.05, df¼19 , po.05).
Limitations: Due to the small sample size, it will be important to evaluate these outcomes in adequately-
powered trials.
Conclusions: This study shows that an internet-based intervention for depression is equally benecial to regular
face-to-face therapy. However, more long term efcacy, indicated by continued symptom reduction three
&2013 Elsevier B.V. All rights reserved.
1. Introduction
Depression is a one of the most common mental disorders among
adults. It is associated with signicant impairments in health and
functional status, as well as with high economic and personal costs
(Andrews et al., 2001).Theearlyageofonset,highprevalencerateand
often long-term nature of depression make it a major public health
problem that generates large direct and indirect costs for the
depressed person as well as for society (Richards, 2011). In Europe
for the year 2010 the annual cost of depression per patient was
estimated at 3034 with an estimated number of 30.3 million people
affected (Olesen et al., 2012). These costs are incurred despite the fact
that the vast majority of people suffering from depression do not
access treatment (Collins et al., 2004). Barriers to assessing effective
treatment include fear of stigma, lack of time, long waiting times,
geographic distance to mental health services, or unwillingness to
disclose psychological problems (Collins et al., 2004). Internet-based
interventions may help to overcome these obstacles. Andersson and
Cuijpers found a strong inuence of therapist support on treatment
outcome in their 2009 meta-analysis of 12 internet-based randomized
controlled trials for depression, (Andersson and Cuijpers, 2009).
Computerized interventions with therapist support showed a mean
between-group effect size of d¼.61, which is comparable with face-to-
face treatment for depression, whereas interventions with little or no
therapist contact had signicantly smaller treatment effect sizes,
averaging d¼.25. A recently published meta-analysis, including data
from 25 controlled trials, supports these previous ndings and found
effect sizes ranging from d¼.10 to d¼1. 20 ( Johansson and Andersson,
2012). The authors categorized the studies by type of human contact.
Category 0 was used for no human contact at all throughout the
treatment, category 1 for therapist contact only before treatment,
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Journal of Affective Disorders
0165-0327/$- see front matter &2013 Elsevier B.V. All rights reserved.
Trial registration: Australian New Zealand Clinical Trial Registry:
Corresponding author. Tel.: +49 175 2452177.
E-mail address: (W. Birgit).
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎
category 2 was contact only during the treatment and nally category
3 was where therapist contact took place before, during and after the
intervention. The effect sizes were d¼.21, .44, .56 and .76. These
results indicate that higher levels of human contact yield larger effect
sizes. This matches other ndings of a signicant correlation between
the amount of therapist time in minutes per participant and the
between-group effect sizes of internet-based interventions (Palmqvist
et al., 2007). Moreover, studies on entirely self-guided programs have
shown not only reduced treatment effects, but also substantial
attrition rates of up to 41% (Christensen et al., 2006a,2006b;Clarke
et al., 2005,2002;Kaltenthaler et al., 2008). In summary, it can be
concluded that therapist-assisted online programs for depression yield
medium to large effect sizes.
However the question remains of whether internet-based thera-
pies for depression are equally as benecial for patients as standard
face-to-face treatments. Only a few studies have directly compared
computerized interventions with face-to-face interventions. Spek and
colleagues evaluated an 8 week internet-based intervention for non-
typical subthreshold depression in people aged 50 and older com-
pared to 10 weekly face-to-face group sessions and a waiting-list
condition (Spek et al., 2007). No signicant treatment effect differences
were found between the face-to-face group intervention and the
internet-based intervention. Other studies have evaluated and com-
pared online versus face-to-face therapies for tinnitus (Kaldo et al.,
2008), social phobia (Andrews et al., 2011), panic disorder (Bergstrom
et al., 2010), spider phobia (Andersson et al., 2009), and relaxation
(Carlbring et al., 2007) and found no signicant differences between
the two settings. Only one study, evaluating an intervention for body
image and eating disorders, showed a signicant difference between
the two groups (Paxton et al., 2007). Post-treatment improvements
were larger in the face-to-face than in the internet-based intervention.
Although there is mounting evidence that internet-based interven-
tions for depression are effective and there is support for the
assumption that therapist guided interventions are favorable over
unguided interventions, to our knowledge, no randomized controlled
trial for depression has been conducted to compare treatment efcacy
in the two treatments (online vs. face-to-face) in an experimental
Recognizing that time-intensive psychotherapies present an impor-
tant barrier to mental health care use, the present study used non-
inferiority methodology to compare the efcacy of a brief 8-week
internet-based CBT intervention with high therapist involvement for
depression with a face-to-face CBT intervention. The Internet-based
intervention was not self-guided and the treatment consisted of
structured writing assignments with an individualized feedback from
the therapist. The treatment manual was based on a German CBT
treatment manual for depression (Hautzinger, 2003). Patients from
timeframe and the time of contact between therapist and patient was
equal for both groups. Primary outcomes of the study were depres-
related outcomes (e.g. suicidal ideation, hopelessness and negative
automatic thoughts). It was predicted that participants in both groups
would have signicant reduced symptoms of depression after treat-
ment and that the improvements would be maintained at a 3-month
follow-up assessment. Further, it was hypothesized that the groups
would not differ signicantly at either post-treatment or 3-month
follow-up for both primary and secondary outcomes.
2. Methods
2.1. Ethics statement
Ethical approval for the trial was given by the institutional
review board at the University of Zurich. Signed informed consent
was given by all participants by fax or post. The protocol for this
trial and supporting CONSORT checklist are available as supporting
information; see Checklist S1 and Protocol S1.
2.2. Participants and recruitment
Potential participants were recruited in the area of Zurich, Switzer-
land, through advertisements in newspapers, the depression website
of the university, local internet news forums and depression self-help
groups, advertisements in supermarkets and pharmacies, and local
press releases. Potential participants were informed that they would
be randomized either to the online or the face-to-face group, and that
Internet access was a prerequisite. Applicants indicated their interest
in the study by contacting the intake coordinator via e-mail or
telephone. The intake coordinator sent a reply e-mail with a patient
information sheet and the inclusion and exclusion criteria. Inclusion
Table 1
Demographic and descriptive characteristics of the online and face-to-face groups at baseline.
Online group (n¼32) Face-to-face group (n¼30) Group comparison
Age (M, SD) 37.25 (11.41) 38.73 (11.41) t¼,50, p¼.61
Age range 2067 1962
Gender (% female) 78% 50% χ
(1)¼5.35, po.05
Educational level (%) χ
(32)¼1.46, p¼.48
Primary education 16 27
Secondary education 37 27
University 47 47
Marital status (%) χ
(3)¼2.62, p¼.45
Single 59 57
Partnership/married 19 20
Divorced 16 7
Widowed 6 17
Professional status (%) χ
(4)¼4.4, p¼.52
Full-time work 72 67
Sick leave 3 10
Unemployed 22 20
Retired 0 3
No current antidepressants (%) 91 70 χ
(3)¼4.82, p¼.18
BDI-score, pre-test (M, SD) 22.96 (6.07) 23.41 (7.63) t¼,25, p¼.80
BDI pre-test (1117) in % 16.7 23.3 χ
(2)¼.44, p¼.80
BDI pre-test (1829) in % 63.3 56.7
BDI pre-test (30) in % 20 20
Completer in % 78 93
W. Birgit et al. / Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎2
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
criteria were a score of at least 12 on the Beck Depression Inventory
(BDI-II) (Beck et al., 1996) and age 18 years or older. Potential
participants were excluded if they were (1) currently receiving
treatment elsewhere, (2) also suffering from substance abuse or
dependence, (3) had been on antidepressant medication for less than
4 weeks, (4) not uent in German. Further exclusion criteria were high
risk of suicide, psychotic symptoms, post-traumatic stress disorder,
anxiety, phobia and bipolar disorder. Applicants who indicated that
they met the study requirements entered an online screening proce-
dure, data from which were later used as pre-test measures. After
condentiality issues had been addressed, eligible applicants returned
a signed informed consent formwhich informed them about poten-
tial risks and benets of study participationby fax or post. Participants
were randomly assigned by the study coordinator to either the
internet-based intervention group or the face-to-face group after
recruitment to the study. Excluded applicants were informed imme-
diately about other available forms of treatment. Applicants excluded
because of a high risk of suicide were contacted by telephone by the
study coordinator. Demographic characteristics of the sample are
presented in Table 1. A total 191 respondents applied for the
treatment. The numbers of patients and reasons for exclusion are
specied in the owchart (see Fig. 1). Participants were recruited
between November 2008 and February 2010.
2.3. Procedure
Primary and secondary outcome measures were collected at pre-
treatment, post-treatment and 3-month follow-up. All measures for
both intervention groups were administered through online diagnos-
tics. A number of studies have shown that online format question-
naires produce results as valid as pen-and-paper questionnaires (Fidy,
2008;Hollandare et al., 2010). The 62 applicants included in the study
were randomized by a true random-number service (http://www. using a 1:1 ratio, with 32 participants randomly allocated
Randomization was performed by the study coordinator and was
not stratied by any participant characteristics.
2.4. Interventions
Online and face-to-face intervention groups received a brief
(8 weeks) cognitive-behavioral therapy (CBT) program for depression
(Hautzinger, 2003). This German manual is based on the cognitive
theory of depression of Beck and colleagues (Hautzinger et al., 2006).
The program involved the following CBT modules: (1) introduction,
(2) behavioral analysis, (2) planning of activities, (3) daily structure,
(7) relapse prevention. The life-review module at the mid-treatment
time-point aimed to encourage participants to revisit past experi-
ences and to activate positive memories and individual resources in
order to achieve a balance between positive and negative memories
(Preschl et al., 2012). Further, patients in both groups were given the
same psychoeducation and received the treatment modules in the
same chronological order. Patients in the face-to-face condition
attended one-hour weekly treatment sessions for 8 weeks with their
allocated psychologist in the Department of Psychopathology and
Clinical Intervention at the University of Zurich. They were also given
weekly homework assignments (e.g., daily structure diaries, negative
thoughts log).
The online intervention was given as a guided intervention
with intensive therapist contact, based on the principles applied in
a number of previous studies (Lange et al., 2003;Ruwaard et al.,
2007;Ruwaard et al., 2009;Wagner et al., 2006). The internet-
based treatment manual was derived from the same cognitive-
behavioral treatment modules for depression as the face-to-face
intervention (Hautzinger, 2003). The therapist time involved
responding to texts, requiring 2050 min per text, depending on
the therapist's experience with internet-based therapies.
Applied to participate
(N= 191)
Did not respond after enrolling
(n= 68)
(n= 123)
Randomly allocated
(n= 62)
Excluded (n= 61) due to:
Co-existing psychiatric disorder (n
= 16)
High suicide risk (n= 8)
Bipolar disorder (n= 6)
Low symptom severity (n = 16)
No informed consent (n= 15)
Face-to-face group
(n= 30)
Online group
(n= 32)
Completed post-test
(n= 28)
Completed post-test
(n= 25)
3-month follow-up
(n= 20)
3-month follow-up
(n= 17)
Online group (n= 7):
Problems with writing (n= 2)
No reason (n= 1)
Preferred face-to-face (n= 1)
Technical problems (n= 1)
Improved (n = 1)
Face-to-face group (n= 2):
No reason (n= 1)
Improved (n = 1)
Fig. 1. Flowchart of patient participation.
W. Birgit et al. / Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎ 3
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
Each scheduled writing assignment lasted 45 min and patients
were given two writing assignments in each week of the 8-week
treatment period. Therapists provided individual written feedback
within one working day, along with instructions for the next
writing assignment. Model responses for the therapists were
available, but they also had the option to provide their own
commentary or supportive feedback on their patients'texts.
2.5. Therapists
The therapists were six psychologists and psychotherapists. All
psychologists were trained in psychotherapy and CBT for depres-
sion specically for this study. The therapists were given special
training in therapeutic writing for the online treatment and
received regular supervision (face-to-face and online), with thera-
pists in both groups receiving the same amount of supervision. All
but one of the therapists was involved in both treatment
2.6. Outcome measures
All outcome measures were collected at pre-treatment, post-
treatment and 3-month follow-up.
2.7. Primary outcome measure
The primary outcome measure of this study was depression
assessed with the German version (Hautzinger et al., 2006) of the
Beck Depression Inventory-II (BDI; (Beck et al., 1996)), comprised
of 21 multiple-choice items assessing specic symptoms of
depression. Symptom severity was dened for mild or moderate
depression (BDI score: 1117); moderate to severe depression (BDI
score: 1829); and severe depression (BDI score 30) (Hautzinger
et al., 2006). Recovery was dened as BDI-II at post-treatment
measurement of 10.
2.8. Secondary outcome measures
2.8.1. Suicidal ideation
Suicidal ideation was assessed with the Beck Suicide Ideation
Scale (BSI) (Beck et al., 1997), a 21-item inventory developed to
measure the intensity and recurrence of suicidal ideation in adults.
The BSI is one of the few well-validated self-report measures of
suicidal ideation The rst 5 items make up a brief subscale
measuring the presence of suicidal thoughts, either recently (in
the last 6 months) or ever in one's life. The BSI has a suggested
cutoff score of 3.
2.8.2. Anxiety
Anxiety was assessed using the Anxiety subscale of the German
version of the Symptom Checklist created by Derogatis (Franke,
1995). This 10-item subscale covers various symptoms of anxiety,
including cognitive and somatic correlates of anxiety and a cut-off
score of .64 has been validated to screen for anxiety (Geiser et al.,
2.8.3. Hopelessness
Hopelessness was measured with the Scale for the Assessment
of Hopelessness (Krampen and Beck, 1994), a German adaptation
of the American Hopelessness Scale (Beck et al., 1974). The Scale
for the Assessment of Hopelessness assesses the negative expecta-
tions of a person referring to himself, to his environment, or his
future life.
2.8.4. Automatic thoughts
The German version of the Automatic Thoughts Questionnaire-
Revised (ATQ-R, (Kendall et al., 1989), German version (Pössel
et al., 2005)) measures positive and negative automatic thoughts
which are specic to depressive thinking. The German ATQ-R
includes the three subscales (1) negative thoughts, (2) well-being,
and (3) self-condence.
2.8.5. Treatment satisfaction
The overall treatment satisfaction was asked with a one-item
question (How satised have you been with the intervention?)
on a 10-point Likert scale (1¼very dissatised, 10¼extremely
2.9. Exclusion criteria
2.9.1. Risk of psychosis
Risk of psychosis was measured using the Dutch Screening
Device for Psychotic Disorder (Lange et al., 2000), a seven-item
inventory that is a good predictor of psychotic episodes. Because
no data are yet available from a German norm group, the Dutch
norm data were used. A score of 13 has been identied as
providing a cutoff for identifying risk of psychosis.
2.9.2. Phobia
The German version of the Symptom Checklist by Derogatis
(Franke, 1995) was also used to test for phobias. The Phobia
subscale contains seven items assessing severity of phobic
2.9.3. Post-traumatic stress
The Post-Traumatic Stress Scale 10 (Maercker, 1998), a
short screening instrument tapping DSM-III symptoms of post-
traumatic stress disorder, was used to measure symptoms of post-
traumatic stress.
2.10. Statistical analysis
Statistical analyses were performed with the Statistical Package
for the Social Sciences (SPSS), version 19.0 for MAC. Independent
t-tests and χ
-tests were used to estimate baseline between-group
differences in demographics and pre-treatment measures. To
evaluate recovery, the BDI-II was used. Changes of prevalence of
depression at pre-treatment and post-treatment were calculated
and analyzed with χ
-tests. Differences between the online and
face-to-face interventions were primarily investigated by mixed-
design ANOVAs with time as the within-subject factor and group
as the between-subject factor. All post-treatment and 3-month
follow-up analyses were based on an Intention to treat (ITT)
design. Missing data were addressed by carrying forward the rst
available data (baseline observation carried forward; BOCF) prin-
ciple. To examine the magnitude of change in mean symptoms
between baseline and post-treatment and between baseline and
3-month follow-up, we calculated effect sizes using Cohen'sdfor
repeated measures. An effect size of d¼.80 for a psychological
treatment is typically considered large (Cohen, 1988). Finally,
t-tests and χ
-tests were used to identify any differences between
dropouts and completers.
3. Results
Table 1 shows baseline sociodemographic characteristics of
participants in the online and face-to-face conditions. There were
no signicant differences for most of the baseline variables,
however, despite randomization, there was a signicantly higher
W. Birgit et al. / Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎4
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
percentage of women in the online group (78%) versus 50% in the
face-to-face group, χ
(1)¼5.35, po.05. The BDI baseline score
was M¼22.96 (S.D.¼6.07) for the online group and M¼23.41
(S.D.¼7.63) for the face-to-face group. Symptom severity was high
in the total sample: 20% of the participants met criteria for mild or
moderate depression (BDI score: 1117); 60% suffered of moderate
to severe depression (BDI score: 1829); and 20% showed a BDI
score 30. There was no signicant difference between the two
interventions groups regarding symptom severity (see Table 1).
Only a small subgroup (19%) was taking antidepressants at the
beginning of the study, and 53% reported that they had previous
experience of psychotherapy.
3.1. Intention-to-treat
Analysis of the change in the primary and secondary outcome
measures was conducted using an intention to treat (ITT) analysis.
Table 2 presents means and standard deviations of baseline, post-
treatment, and 3-month follow-up scores for all outcome measures in
both treatment conditions. The ITT analysis yielded no signicant
between-group difference (online vs. face-to-face group) at any of the
pre- to post-treatment measurements. At post-treatment both treat-
ment conditions revealed signicant symptom changes compared to
pre-intervention levels. The online group showed signicant symptom
reduction for depression (t¼6.98, df¼30, po.001), anxiety (t¼5.60,
df¼31, po.001), hopelessness (t¼5.57, df¼31, po.001), self-esteem
(t¼3.25, df¼31, po.01), and automatic negative thoughts (t¼3.29,
df¼31, po.01). Only suicidal ideation (t¼1.18 , d f ¼30, p¼.24) did not
undergo any signicant change from pre- to post-treatment in the
online group. Similar results and patterns of change were found in the
face-to-face group, with the exception of a signicant change in
suicidal ideation (t¼2.45, df ¼29, po.05). The between-group effect
sizes at post-treatment were small (see Table 2), while within-group
effect sizes for the primary outcome depression in the online group
(d¼1.27)andtheface-to-facegroup(d¼1.37) can be considered large.
Furthermore, as no signicant changes were found in any of the
outcome measurements at 3-month follow-up compared to immedi-
ately after treatment in the online group, there is an indication that the
outcomes remain stable after the treatment. In contrast to this,
participants in the face-to-face group showed a signicant increase
in depressive symptoms from post-treatment to 3-month follow-up
(t¼2.05, df¼19, po.05), although all secondary outcome measures
remained stable.
A MANOVA for repeated measures showed no signicant
interaction effect on any primary or secondary outcomes from
pre- to post-test, but a signicant difference for group effect from
post-treatment to 3-month follow-up for anxiety (F(1,33)¼5.33,
po.05), automatic negative thoughts (F(1,33)¼4.70, po.05) and a
nearly signicant effect for depression (F(1,34)¼2.88, p¼.09).
Pre-treatment to 3-month follow-up within-group effect sizes
on the BDI were more favorable for the online-group (d¼2.00),
compared to the face-to-face group (d¼1.04) (see Fig. 2). The
corresponding secondary outcomes in the online group for anxiety
(d¼1.13) versus the face-to-face group (d¼.55); hopelessness
(d¼1.14) versus the face-to-face group (d¼.65); and negative
automatic thoughts (d¼1.59) versus the face-to-face group
(d¼.52) revealed higher within-group effect sizes for the out-
comes of the online group at 3-month follow-up. Further, treat-
ment satisfaction and psychotherapy utilization comparisons
between the two intervention groups are detailed in Table 3.
3.2. Attrition
Seven (22%) participants in the online group and two (7%)
participants in the face-to-face group failed to nish the treatment
(see Fig. 1). Of these nine persons, three stopped treatment
without giving any reason and could no longer be reached; two
participants stated that writing was not the right approach for
them or that they were no longer interested in the treatment
program; one participant of the online group preferred face-to-
face therapy and therefore discontinued study participation; two
experienced sufcient improvement during the course of treat-
ment and one participant discontinued because of technical
problems. Completion rates revealed an almost signicant differ-
ence between the two groups, χ²(1)¼2.88, p¼.08. Non-completers
in the face-to-face group did not differ from completers in any of
Table 2
Results of mixed design ANOVAs and effect sizes for the online and face-to-face groups at baseline, post-treatment, and 3-month follow-up: intention-to-treat analysis.
Time Online group Face-to-face group Between-group difference Effect size, d
Effect size, d
3-month Follow-up
BDI Pre 22.96 6.07 23.41 7.63 F(1,59)¼.01, p¼.92 .00 .61
Post 12.41 10.03 12.33 8.77 F(1,34)¼2.88, p¼.09
FU 9.28 7.50 14.47 9.33
Suicidal ideation Pre 3.24 4.87 4.40 6.48 F(1,59)¼.23, p¼.63 .02 -
Post 2.27 4.78 2.40 4.80
FU - - - -
SCL-anxiety Pre .95 .52 .92 .56 F(1,58)¼.24, p¼.62 .29 .44
Post .48 .51 .63 .52 F(1,33)¼5.33, po.05
FU .44 .37 .63 .48
Hopelessness Pre 27.59 6.70 28.36 6.41 F(1,60)¼.30, p¼.58 .13 .47
Post 20.40 8.66 21.53 8.52 F(1,34)¼2.44, p¼.12
FU 19.18 7.90 23.20 9.07
Self-condence Pre 7.31 3.65 7.00 2.25 F(1,60)¼.46, p¼.49 .19 .10
Post 9.40 4.30 8.63 3.64 F(1,34)¼.28, p¼.59
FU 9.25 3.13 8.90 3.69
Negative thoughts Pre 35.56 8.08 37.13 9.28 F(1,59)¼.07, p¼.79 .02 .70
Post 26.62 15.95 26.27 9.03 F(1,33)¼4.70, po.05
FU 21.81 9.15 30.52 15.01
Well-being Pre 7.93 2.36 7.63 2.18 F(1,60)¼1,07, p¼.30 .27 .35
Post 12.25 5.13 10.93 4.59 F(1,34)¼1. 71, p¼.19
FU 12.06 4.66 10.50 4.24
Note. Online group: n¼25 (reduced to n¼17 at 3-month follow-up due to dropout); face-to-face group: n¼28 (reduced to n¼20 at 3-month follow-up due to dropout).
W. Birgit et al. / Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎ 5
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
the demographic variables. In the online group the only demo-
graphic difference found was that dropouts were older than
completers, t(30)¼2.33, po.05. Regarding symptom levels, no
signicant differences were found between dropouts and com-
pleters on any of the baseline measures.
3.3. Treatment recovery
Recovery was dened as BDI-II at post-treatment measurement
of 10. No difference was found between groups with regard to
recovery after treatment χ²(1)¼.06, p¼.80 or at 3-month follow-
up χ²(1)¼2.94, p¼.08. At post-treatment, 53% in the online-group
and 50% in the face-to-face group showed a clinically signicant
change. Although the increases were not signicant, at 3-month
follow-up the online group showed a increased recovery rate of
57% while the face-to-face group's recovery rate had decreased to
42%. In the online-group 80% of the participants who reported
mild depression at baseline received signicant clinical change at
posttreatment, compared to 100% in the face-to-face group. In the
online group of the moderate to severe depressive participants
67% achieved clinical change compared to 40% in the face-to-face
group. In the severe depressed group (BDI 30) the online-group
achieved 40% signicant change, while the face-to-face group
achieved 33%. However, no signicant difference could be found
between the two interventions groups in any of the depression
4. Discussion
The aim of this non-inferiority randomized controlled trial was
to test an internet-based intervention against a comparable,
traditional face-to-face therapy for depression. To our knowledge
this is the rst randomized controlled trial for depression compar-
ing both treatment forms with equivalent treatment modules and
treatment length. We assumed equal effects for the two condi-
tions. The main nding of this trial is that the internet-based
intervention is indeed equally as effective as face-to-face therapy
for depression. This is in line with previous studies comparing
face-to-face therapy with online interventions for other mental
conditions (Andrews et al., 2011;Bergstrom et al., 2010;Kaldo
et al., 2008;Spek et al., 2007). Furthermore, both interventions
showed large within group effect sizes at post-treatment for both
depressive symptoms and secondary outcomes, which conrms
ndings of Nieuwsma and colleagues that a brief intervention for
depression can be effective and comparable to standard duration
of psychotherapy (Nieuwsma et al., 2012). The within group effect
size in the online-group ranged from d¼.91 to d¼1.27 for
depression, anxiety and hopelessness. These effect-sizes conrm
the ndings of Johansson et al. (2012), who found the largest effect
sizes for interventions with a high therapist involvement in their
review. The high therapist involvement in our study therefore
seems to play a major role compared to treatment effects of self-
guided interventions for depression (Johansson and Andersson,
However, analysis revealed that from post-treatment to
3-month follow-up a difference between the internet-based inter-
vention and the face-to-face group could be found. Symptom
reductions were maintained for all primary and secondary out-
comes for the online group three months after treatment. In
contrast to this, participants in the face-to-face group signicantly
worsened from post-treatment to 3-month follow-up in terms of
depressive symptoms. Further, signicant differences were found
for the face-to-face group from post-treatment to the 3-month
follow-up for symptoms of anxiety and automatic negative
thoughts and a nearly signicant effect was observed for depres-
sion. Altogether it appears that the treatment effects from pre-
treatment to 3-month follow-up were larger in the online group
than in the face-to-face group. Moreover, at the 3-month follow-
up more participants in the online group indicated clinically
signicant changes than in the face-to-face group. Reasons for
this might include that the online intervention has less personal
guidance and therefore puts a stronger focus on self-responsibility
to conduct the treatment modules and homework assignments
than the face-to-face intervention. This might evoke a stronger,
longer-lasting sense of self-efcacy in handling negative thoughts
and depressive behavior. Further, no signicant difference could be
found regarding treatment satisfaction in both groups. 96% of the
participants in the online group described the contact between
therapist and themselves as personal, compared to 91% in the face-
to-face group. This conicts with previous ndings of Kaldo et al.
(2008), who found that the credibility rating of their internet-
based intervention was signicantly lower than that for the face-
to-face group intervention. Interestingly, there was an almost
Table 3
Treatment satisfaction and psychotherapy utilization at postmeasurement.
Online group (n¼25) Face-to-face group (n¼28) Group comparison
Treatment satisfaction (010), (M, SD) 7.88 (1.66) 6.83 (2.03) t¼.36, p¼.11
Treatment duration (%)
Too short 32 57 χ
(1)¼3.37, po.06
Good 68 43
Contact between therapist and patient (%)
Personal 96 91 χ
(1)¼1.11, po.57
Impersonal 4 4
Do not know 0 4
Started psychotherapy by 3-month follow-up (%) 25% 20% χ
(1)¼.04, po.83
Pretest Posttest 3 MFU
Online Face-to-face
Fig. 2. Online intervention in comparison to a face-to-face group measured with
the Beck Depression Inventory (BDI-II) at pretest, posttest and 3-months-follow-up,
including standard error.
W. Birgit et al. / Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎6
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
signicant difference regarding opinions about the treatment
duration in our study. While only 32% in the online group
experienced the treatment as too short, about 57% in the inter-
vention group found the duration of the 8-week program as too
short and wished that the treatment could have continued longer.
When looking at the clinical signicant change in the different
subgroups of symptom severity, we found that in both treatments
participants with mild to moderate depressive symptoms showed
a higher percentage of recovery. Least recovery was found in the
severely depressed subgroup. Further, we could not nd any
statistical difference between the two interventions and the
symptom severity subgroups.
Although these preliminary results provide some evidence that
online interventions might be as effective as face-to-face inter-
ventions, it remains unclear whether the factors that are respon-
sible for symptom reduction in face-to-face therapy operate in the
same way in online therapeutic settings. Therapeutic factors such
as missing face-to-face contact, decreased social presence and
increased anonymity were originally seen as disadvantages of
internet-based interventions. However, for a specic group of
patients, it might be exactly these factors that offer an advantage
in comparison to conventional therapies. Online participants
might be more focused on the structured treatment manual as
they are responsible for continuation of the intervention, for
example by completing homework assignments. This might lead
to a greater treatment manual adherence than in face-to-face
therapy. DeRubeis and Feeley (1990) differentiated between two
types of adherence to cognitive-behavioral therapies, concrete and
abstract adherence. Concrete adherence involves methods to
support use by the patients of cognitive-behavioral tools such as
cognitive restructuring worksheets, homework assignments and
behavioral techniques. In contrast to this, abstract adherence to
CBT involves broader discussions of therapy-relevant issues with
focus put upon understanding the patients'situation and beliefs
and conversations about the patients'wellbeing and therapy
progress. In internet-based interventions there is a clear focus on
concrete adherence to CBT through use of homework assignments,
psychoeducation and behavioral observation techniques. Only a
small part of the intervention involves abstract adherence, such as
conversations about the patient's current personal situation or
broader discussion of disorder-relevant topics. Face-to-face CBT,
even when highly structured as in our study, still gives the patients
more opportunities to discuss problematic current situations,
alongside pure adherence to the treatment modules. The compar-
ison of abstract and concrete adherence in face-to-face versus
online therapies should be addressed by future research.
Another important factor for therapeutic interventions is the
therapeutic alliance between therapist and patient throughout the
intervention. The therapeutic alliance has traditionally been seen
as a key element contributing to the treatment success of face-to-
face psychotherapy (Horvath and Symonds, 1991). A number of
studies have found that the therapeutic alliance signicantly
inuences symptoms of depression as an outcome measure
(Krupnick et al., 1996). Internet-based interventions involve less
therapeutic contact and are usually restricted to purely text-based
and computer-mediated communication. Initial assumptions that
internet-based therapeutic relationships are less stable or less
positively experienced by the patients have not been conrmed,
however. A number of studies have revealed that therapeutic
relationships in an online setting are consistently rated as posi-
tively and as stable as in face-to-face settings by study participants
(Knaevelsrud and Maercker, 2006;Preschl et al., 2011;Wagner
et al., 2012). However, the working alliance in internet-based
interventions seems to be less predictive of treatment outcome
than in face-to-face interventions and the role of the therapist
seems to be less prominent than in face-to-face treatments.
The drop-out rates in our studyseven (22%) participants in the
online group and two (7%) participants in the face-to-face group
was more favorable for the face-to-face group. This may indicate
that the more anonymous online therapeutic relationship is less
stable than a face-to-face relationship. Face-to-face interventions
involve more social control and it might seem, for a number of
participants, inappropriate to dropout of therapy once they get to
know the psychotherapist personally. It is easier for patients in
online interventions to stop therapeutic communication by simply
disappearing. A study of online romantic relationships revealed
that avoidance behavior and discontinuity are more likely in
online relationships than in face-to-face relationships (Merkle
and Richardson, 2000).
4.1. Limitations
This trial has a number of limitations, which need to be
addressed. First, all primary and secondary outcome measures
were administered as self-rated questionnaires in an online set-
ting. We aimed to conduct a fully internet-based treatment for the
online-group with no personal contact either on the telephone or
face-to-face, therefore we decided to conduct the diagnostic
procedure entirely through the internet for both groups. However,
a structured clinical interview would have allowed a better quality
of diagnosis of depression. Second, only one follow-up assessment,
at three months, was conducted, therefore we cannot draw any
conclusions about the truly long-term effects of the two treat-
ments. Furthermore, the sample used in this study was small, self-
referred, relatively well educated, and more than half of the
participants already had experience of psychotherapy. Therefore
it is unclear whether the results of this study can be generalized to
predict efcacy in people who are referred by health professionals
or who are less educated. Even though the results regarding the
3-months follow-up are surprisingly in favor of the online-
intervention group, it is important to acknowledge that only about
two thirds of the participants completed the 3-months-follow-up.
Future studies should enroll larger and more heterogeneous
samples. Finally, due to our strict exclusion criteria regarding co-
morbidity and psychosis, a number of applicants were excluded
from the study, which also limits the breadth of the conclusions.
A number of studies to date have evaluated the efcacy of tailored
internet-based interventions for patients with comorbidities
(Carlbring et al., 2011;Johansson et al., 2012) and have found
encouraging results suggesting that individually tailored interven-
tions are superior to non-tailored interventions. A recently con-
ducted trial explicitly developed for patients with suicidal
ideations concluded that this patient group should be considered
for future research on internet-based interventions (van Spijker
et al., 2010).
5. Conclusion
Depression has become a very prevalent und costly disorder
and in most countries therapeutic services do not manage to meet
the needs presented by this growing demand. This trial gives
preliminary results that a brief internet-based intervention for
depression is as effective as comparable face-to-face interventions.
Internet-based intervention may be the solution for tackling this
epidemic in a more cost-effective way than traditional face-to-face
therapies. However, further research is needed to replicate these
ndings and possible differences in underlying mechanisms
between online and face-to-face interventions need to be
W. Birgit et al. / Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎ 7
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
Role of funding source
This research was supported by the Selo Foundation, Switzerland.
Conict of interest
The authors declare no conict of interest.
The authors would like to thank Barbara Preschl, Jenni Keel, Luigina Di Lorenzo,
and Regula Usteri, who served as therapists in the study. This study was co-funded
by the Werner Selo Foundation.
Appendix A. Supplementary Information
Supplementary data associated with this article can be found in
the online version at
Andersson, G., Cuijpers, P., 2009. Internet-based and other computerized psycho-
logical treatments for adult depression: a meta-analysis. Cognitive Behaviour
Therapy 38, 196205.
Andersson, G., Waara, J., Jonsson, U., Malmaeus, F., Carlbring, P., Ost, L.G., 2009.
Internet-based self-help versus one-session exposure in the treatment of spider
phobia: a randomized controlled trial. Cognitive Behaviour Therapy 38,
Andrews, G., Davies, M., Titov, N., 2011. Effectiveness randomized controlled trial of
face to face versus Internet cognitive behaviour therapy for social phobia.
Australian and New Zealand Journal of Psychiatry 45, 337340.
Andrews, G., Henderson, S., Hall, W., 2001. Prevalence, comorbidity, disability and
service utilisation. Overview of the Australian National Mental Health Survey.
British Journal of Psychiatry 178, 145153.
Beck, A.T., Brown, G.K., Steer, R.A., 1997. Psychometric characteristics of the Scale
for Suicide Ideation with psychiatric outpatients. Behaviour Research and
Therapy 35, 10391046.
Beck, A.T., Steer, R.A., Brown, G.K., 1996. Manual for the Beck Depression Inventory-
II. TX: Psychological Corporation, San Antonio.
Beck, A.T., Weissman, A., Lester, D., Trexler, L., 1974. The measurement of
pessimism: the hopelessness scale. Journal of Consulting and Clinical Psychol-
ogy 42, 861.
Bergstrom, J., Andersson, G., Ljotsson, B., Ruck, C., Andreewitch, S., Karlsson, A.,
Carlbring, P., Andersson, E., Lindefors, N., 2010. Internet-versus group-adminis-
tered cognitive behaviour therapy for panic disorder in a psychiatric setting: a
randomised trial. BMC Psychiatry 10, 54.
Carlbring, P., BjÃrnstjerna, E., BergstrÃm, A.F., Waara, J., Andersson, G., 2007.
Applied relaxation: an experimental analogue study of therapist vs. computer
administration. Computers in Human Behavior 23, 210.
Carlbring, P., Maurin, L., Torngren, C., Linna, E., Eriksson, T., Sparthan, E., Straat, M.,
Marquez von Hage, C., Bergman-Nordgren, L., Andersson, G., 2011. Individually-
tailored, internet-based treatment for anxiety disorders: a randomized con-
trolled trial. Behaviour Research and Therapy 49, 1824.
Christensen, H., Grifths, K., Groves, C., Korten, A., 2006a. Free range users and one
hit wonders: community users of an Internet-based cognitive behaviour
therapy program. Australian and New Zealand Journal of Psychiatry 40, 5962.
Christensen, H., Grifths, K.M., Mackinnon, A.J., Brittliffe, K., 2006b. Online
randomized controlled trial of brief and full cognitive behaviour therapy for
depression. Psychological Medicine 36, 17371746 .
Clarke, G., Eubanks, D., Reid, E., Kelleher, C., OConnor, E., DeBar, L.L., Lynch, F.,
Nunley, S., Gullion, C., 2005. Overcoming Depression on the Internet (ODIN) (2):
a randomized trial of a self-help depression skills program with reminders.
Journal of Medical Internet Research 7, e16.
Clarke, G., Reid, E., Eubanks, D., OConnor, E., DeBar, L.L., Kelleher, C., Lynch, F.,
Nunley, S., 2002. Overcoming depression on the Internet (ODIN): a randomized
controlled trial of an Internet depression skills intervention program. Journal of
Medical Internet Research 4, E14.
Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences. Academic
Press, New York.
Collins, K.A., Westra, H.A., Dozois, D.J., Burns, D.D., 2004. Gaps in accessing
treatment for anxiety and depression: challenges for the delivery of care.
Clinical Psychology Review 24, 583616.
DeRubeis, R.J., Feeley, M., 1990. Determinants of change in cognitive therapy for
depression. Cognitive Therapy and Research 14, 469482.
Fidy, R., 2008. Psychologische Suizidalitäts-Diagnostik im Internet [Internet diag-
nosis of suicidal ideation]. Unpublished Lizenziat thesis., University of Zurich,
Zurich, Switzerland.
Franke, G., 1995. SCL-90-R. Die Symptom-Checkliste von Derogatis. [SCL-90-R. The
Symptom-Checklist from Derogatis]. Beltz Test GmbH, Göttingen.
Geiser, F., Imbierowicz, K., Schilling, G., Conrad, R., Liedtke, R., 2000.
Differences in 2 diagnostic groups of psychosomatic patients on the Symptom
Checklist 90-R (SCL-90-R). Consequences for using SCL-90-R in follow-up
research. Psychotherapie Psychosomatik Medizinische Psychologie 50,
Hautzinger, M., 2003. Cognitive Behaviour Therapy of Depression, 6th Ed. Beltz,
Hautzinger, M., Keller, F., Kühner, C., 2006. Das Beck Depressionsinventar II.
Deutsche Bearbeitung und Handbuch zum BDI II. Harcourt Test Services,
Frankfurt a. M.
Hollandare, F., Andersson, G., Engstrom, I., 2010. A comparison of psychometric
properties between internet and paper versions of two depression instruments
(BDI-II and MADRS-S) administered to clinic patients. Journal of Medical
Internet Research 12, e49.
Horvath, A.O., Symonds, B.D., 1991. Relation between Working Alliance and Out-
come in Psychotherapya Metaanalysis. Journal of Counseling Psychology 38,
Johansson, R., Andersson, G., 2012. Internet-based psychological treatments for
depression. Expert Review of Neurotherapeutics 12, 861870.
Johansson, R., Sjoberg, E., Sjogren, M., Johnsson, E., Carlbring, P., Andersson, T.,
Rousseau, A., Andersson, G., 2012. Tailored vs. standardized internet-based
cognitive behavior therapy for depression and comorbid symptoms: a rando-
mized controlled trial. PLoS One 7, e36905.
Kaldo, V., Levin, S., Widarsson, J., Buhrman, M., Larsen, H.C., Andersson, G., 2008.
Internet versus group cognitive-behavioral treatment of distress
associated with tinnitus: a randomized controlled trial. Behavior Therapy 39,
Kaltenthaler, E., Parry, G., Beverley, C., Ferriter, M., 2008. Computerised cognitive-
behavioural therapy for depression: systematic review. British Journal of
Psychiatry 193, 181184.
Kendall, P.C., Howard, B.L., Hays, R.C., 1989. Self-referent speech and psychopathol-
ogy: the balance of positive and negative thinking. Cognitive Therapy and
Research 13, 583598.
Knaevelsrud, C., Maercker, A., 2006. Does the quality of the working alliance predict
treatment outcome in online psychotherapy for traumatized patients? Journal
of Medical Internet Research 8, e31.
Krampen, G., Beck, A.T., 1994. Skalen zur Erfassung von Hoffnungslosigkeit (H-
Skalen), Hogrefe.
Krupnick, J.L., Sotsky, S.M., Simmens, S., Moyer, J., Elkin, I., Watkins, J., Pilkonis, P.A.,
1996. The role of the therapeutic alliance in psychotherapy and pharmacother-
apy outcome: ndings in the national institute of mental health treatment of
depression collaborative research program. Journal of Consulting and Clinical
Psychology 64, 532539.
Lange, A., Rietdijk, D., Hudcovicova, M., van de Ven, J.P., Schrieken, B., Emmelkamp,
P.M., 2003. Interapy: a controlled randomized trial of the standardized treat-
ment of posttraumatic stress through the internet. Journal of Consulting and
Clinical Psychology 71, 901909.
en validatie van de Gewaarwordingenlijst (GL) een hulpmiddel bij het
signaleren van een verhoogde kans op psychosen. Directieve Therapie 20, 162173 .
Maercker, A., 1998. Posttraumatic Stress Scale-10 (PTSS-10) German version
adapted after Schüffel & Schade , Dresden (unpublished).
Merkle, E., Richardson, R., 2000. Digital dating and virtual relating: conceptualiz-
ing computer mediated romantic relationships. Family Relations 49,
Nieuwsma, J.A., Trivedi, R.B., McDufe, J., Kronish, I., Benjamin, D., Williams, J.W.,
2012. Brief psychotherapy for depression: a systematic review and meta-
analysis. International Journal of Psychiatry in Medicine 43, 129151.
Olesen, J., Gustavsson, A., Svensson, M., Wittchen, H.U., Jonsson, B., 2012. The
economic cost of brain disorders in Europe. European Journal of Neurology 19,
Palmqvist, B., Carlbring, P., Andersson, G., 2007. Internet-delivered treatments with
or without therapist input: does the therapist factor have implications for
efcacy and cost? Expert Review of Pharmacoeconomics & Outcomes Research
7, 291297.
Paxton, S.J., McLean, S.A., Gollings, E.K., Faulkner, C., Wertheim, E.H., 2007.
Comparison of face-to-face and internet interventions for body image and
eating problems in adult women: an RCT. International Journal of Eating
Disorders 40, 692704.
Pössel, P., Seemann, S., Hautzinger, M., 2005. Evaluation eines deutschsprachigen
Instrumentes zur Erfassung positiver und negativer automatischer Gedanken.
Zeitschrift für Klinische Psychologie und Psychotherapie 34, 2734.
Preschl, B., Maercker, A., Wagner, B., 2011. The working alliance in a randomized
controlled trial comparing online with face-to-face cognitive-behavioral ther-
apy for depression. BMC Psychiatry.
Preschl, B., Maercker, A., Wagner, B., Forstmeier, S., Banos, R.M., Alcaniz, M.,
Castilla, D., Botella, C., 2012. Life-review therapy with computer supplements
for depression in the elderly: a randomized controlled trial. Aging and Mental
Richards, D., 2011. Prevalence and clinical course of depression: a review. Clin.
Psychol. Rev. 31, 11171125.
Ruwaard, J., Lange, A., Bouwman, M., Broeksteeg, J., Schrieken, B., 2007. E-mailed
standardized cognitive behavioural treatment of work-related stress: a rando-
mized controlled trial. Cognitive Behaviour Therapy 36, 179192.
Ruwaard, J., Schrieken, B., Schrijver, M., Broeksteeg, J., Dekker, J., Vermeulen, H.,
Lange, A., 2009. Standardized web-based cognitive behavioural therapy of mild
to moderate depression: a randomized controlled trial with a long-term follow-
up. Cognitive Behaviour Therapy 38, 206221.
W. Birgit et al. / Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎8
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
Spek, V., Nyklicek, I., Smits, N., Cuijpers, P., Riper, H., Keyzer, J., Pop, V., 2007.
Internet-based cognitive behavioural therapy for subthreshold depression in
people over 50 years old: a randomized controlled clinical trial. Psychological
Medicine 37, 1797180 6.
van Spijker, B.A., van Straten, A., Kerkhof, A.J., 2010. The effectiveness of a web-
based self-help intervention to reduce suicidal thoughts: a randomized con-
trolled trial. Trials 11, 25.
Wagner, B., Brand, J., Schulz, W., Knaevelsrud, C., 2012. Online working alliance
predicts treatment outcome for posttraumatic stress symptoms in Arab war-
traumatized patients. Depression and Anxiety.
Wagner, B., Knaevelsrud, C., Maercker, A., 2006. Internet-based cognitive-beha-
vioral therapy for complicated grief: a randomized controlled trial. Death
Studies 30, 429453.
W. Birgit et al. / Journal of Affective Disorders (∎∎∎∎)∎∎∎∎∎∎ 9
Please cite this article as: Birgit, W., et al., Internet-based versus face-to-face cognitive-behavioral intervention for depression: A
randomized controlled non-inferiority trial. Journal of Affective Disorders (2013),
... Three months later, only patients receiving the online intervention maintained a low level of depressive symptoms (Holländare et al., 2013;Wagner et al., 2014). A short-term digital psychological guided group intervention for vulnerable quarantined populations during COVID-19 resulted in a significant improvement in their loneliness perception and depressive symptoms (Shapira, Yeshua-Katz, Cohn-Schwartz, et al., 2021;Shapira, Yeshua-Katz, Goren, et al., 2021). ...
... Tele-psychotherapy facilitates engagement, strengthens the alliance between therapist and patient, and creates unique therapeutic opportunities that may not be possible when therapy is performed in a face-toface format with its inherent inhibitions. Furthermore, online interventions' effectiveness does not fall short of traditional interventions and sometimes even exceeds them (Cavanagh et al., 2013;Spijkerman et al., 2016;Wagner et al., 2014). People dealing with depression or avoidance coping may benefit from video sessions, at least like in-person meetings, if not more (Simpson et al., 2021). ...
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For this analysis, 116 patients were randomized into an intervention group (n=55) or a control wait�list group (n=61). Both groups received medical treatment as usual. The relative change of the different variables was compared. Additionally, each participant served as their own control. In the third chapter (pg. 62), we analyzed the effect of COBMINDEX intervention on the psychosocial coping resources of 45 men and 75 women with active CD. A gender-wise analysis was also conducted, and the associations between the relative change in coping resources was assessed with the relative change of the patient's emotional distress and satisfaction with life. Integrated results of all three analyses showed that COBMINDEX is an intervention that elevates the well-being of adult CD patients with mild-to-moderate disease activity over a short period of three months. It is associated with enhanced use of adaptable coping strategies (emotional- and problem-focused strategies) and with the decreased use of dysfunctional coping strategies. COBMINDEX is also associated with elevated mindfulness disposition and decreased emotional distress assessed by the global severity index symptoms (GSI), fatigue (FACIT-Fatigue), and perceived stress (PSS�4). After COBMINDEX, clinical improvement of the patient's disease activity and reduced inflammatory biomarkers such as CRP and fecal calprotectin were reported as well. COBMINDEX is best suited to CD patients with higher III emotional distress, lower mindfulness disposition, and lower HRQoL, and is more beneficial for women than men. A possible mechanism for the patients' improved well-being is the implementation of those adaptive disease-related coping skills which the patients learned and practiced. The intervention serves as a platform that enhances the use of effective coping with disease-related everyday stress, replacing already well-established dysfunctional strategies with more adaptable strategies. Departing from dysfunctional coping use was associated with higher satisfaction with life. However, it is suggested that embracing more adaptive coping skills is easier than relinquishing unhealthy and dysfunctional coping strategies. Nonetheless, relinquishing the dysfunctional strategies was found to be a crucial factor in improving patients' satisfaction with life. A gender-wise analysis showed that altering coping resources is gender-associated. While there were no significant mindfulness and coping resource differences at baseline between the genders, except for higher use of venting and instrumental support among women, after COBMINDEX women showed a more positive change in more coping strategies than men. Women reported more frequent use of both emotion- and problem-focused coping, whereas men reported a significant increase only in emotion-focused coping. Women used significantly less dysfunctional coping (calculated with its venting subscale removed from the index), and less self-blame and denial. Furthermore, results showed that mindfulness disposition is negatively associated with emotional distress and positively associated with HRQoL. A path analysis showed that the effect of mindfulness on HRQoL is mediated by emotional distress, so greater levels of mindfulness were linked with lower emotional distress, which in turn led to improved HRQoL. Mindfulness disposition was also positively associated with adaptable coping strategies and negatively associated with dysfunctional strategies. As far as we know, this is the first study that assessed the relationships between coping strategies and mindfulness among CD patients, based on the assumption that mindfulness is an adaptable coping strategy. One of this dissertation's theoretical contributions is the use of Taylor's theoretical model. To the best of my knowledge, this is the first study in Israel IV and in the world to use a multivariate bio-psycho-social model as a structure for explaining the well-being of CD patients following a short-term COBMINDEX intervention. Our intervention altered the coping resources and therefore acts as a mediating factor between gender and CD patients" well-being. Another theoretical contribution of this dissertation is the use of innovative statistical analyses. First, we assessed the associations between the relative change of the variables, which enables us to show how a change in one variable is related to a change in other variables. Secondly, we used quantile regressions. These regressions are best used in non-normally distributed data and show the slopes of the regression line and more detailed results. These regressions are innovative and are less commonly used in social science research. A practical contribution is the use of a telehealth platform for the intervention. One of the main concerns about online psychological video session interventions is the lack of in-person (face-to-face) feeling. Our results and a relatively low dropout rate of 8.4% across the COBMINDEX intervention support the notion that therapeutic relationships between social workers and their patients can be delivered via digital platforms using tele-psychotherapy. It should also be noted that this digital intervention format, which initially aimed to be accessible for CD patients from all over the country, proved to be suitable, particularly in the COVID-19 era. Conclusions CD patients' well-being is affected by bio-psycho-social variables. COBMINDEX is a short-term digital psychological intervention that improves the well-being of adult CD patients with mild-to-moderate disease by teaching them the use of more adaptive coping resources and decreasing their emotional distress. COBMINDEX can be implemented relatively easily in CD centers' health care programs. Similar to other recent studies in the IBD field, there is a need to institutionalize and integrate a bio-psycho-social health care model into the treatment of CD policy and practice. The patients' health should not be V defined only according to their physical state and needs but should also include emotional and psychosocial status. The treatment for CD patients should be multidisciplinary, with integrated teams diagnosing and introducing treatments that include screening and managing psychological distress by professional social workers and mental health practitioners. Mental health care should be aided by digital means that make the treatment accessible to the various CD populations. This treatment should not be considered a privilege or a recommendation for complementary care, but rather a standard mandatory treatment. Keywords: cognitive-behavioral intervention; mindfulness; distress; Crohn's disease; chronic diseases; self-exercise; well-being; coping
... A meta-analysis of 25 positive strengths-based interventions targeting constructs such as gratitude, happiness, and optimism found a medium effect size for relief of depressive symptoms (median r=0. 26), with stronger effects seen for phenotypes of participants with current depressive symptoms [22,23]. Published studies comparing positive psychology interventions with treatment as usual show effectiveness and durability similar to those of traditional psychotherapy or pharmacotherapy [22]. ...
... Advantages of web-based delivery options include generally lower cost, easier dissemination, more consistent fidelity to the intervention protocol through automation that counteracts going off script, and greater accessibility in settings with Wi-Fi availability [24,25]. Comparative effectiveness trials document similar effect sizes for internet-based psychotherapy compared with traditional face-to-face approaches, with high patient satisfaction when rating these high-technology platforms [26,27]. Barriers to entry associated with traditional in-person forms of therapy may be bridged using web-based platforms that offer low-threshold and convenient at-home alternatives. ...
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Background Depression is highly prevalent in individuals on hemodialysis, but it is infrequently identified and remains undertreated. In this paper, we present details of the methodology of a randomized controlled trial (RCT) aimed at testing the feasibility and preliminary efficacy of a 5-week positive psychological intervention in individuals on hemodialysis with comorbid depression delivered using immersive virtual reality (VR) technology. Objective We aim to describe the protocol and design of the Joviality trial whose main objectives are 2-fold: determine the feasibility of the Joviality VR software through metrics capturing rates of recruitment, refusal, retention, noncompliance, and adherence, as well as end-user feedback; and assess preliminary efficacy for outcomes measures of depressive symptoms, psychological well-being and distress, quality of life, treatment adherence, clinical biomarkers, and all-cause hospitalizations. Methods This 2-arm RCT is scheduled to enroll 84 individuals on hemodialysis with comorbid depression from multiple outpatient centers in Chicago, Illinois, United States. Enrollees will be randomized to the following groups: VR-based Joviality positive psychological intervention or sham VR (2D wildlife footage and nature-based settings with inert music presented using a head-mounted display). To be eligible, individuals must be on hemodialysis for at least 3 months, have Beck Depression Inventory-II scores of ≥11 (ie, indicative of mild-to-severe depressive symptoms), be aged ≥21 years, and be fluent in English or Spanish. The Joviality VR software was built using agile design principles and incorporates fully immersive content, digital avatars, and multiplex features of interactability. Targeted skills of the intervention include noticing positive events, positive reappraisal, gratitude, acts of kindness, and mindful or nonjudgmental awareness. The primary outcomes include metrics of feasibility and acceptability, along with preliminary efficacy focused on decreasing symptoms of depression. The secondary and tertiary outcomes include quality of life, treatment adherence, clinical biomarkers, and all-cause hospitalization rates. There are 4 assessment time points: baseline, immediately after the intervention, 3 months after the intervention, and 6 months after the intervention. We hypothesize that depressive symptoms and hemodialysis-related markers of disease will substantially improve in participants randomized to the VR-based Joviality positive psychology treatment arm compared with those in the attention control condition. Results This RCT is funded by the National Institute of Diabetes and Digestive and Kidney Diseases and is scheduled to commence participant recruitment in June 2023. Conclusions This trial will be the first to test custom-built VR software to deliver a positive psychological intervention, chairside, in individuals on hemodialysis to reduce symptoms of depression. Within the context of an RCT using an active control arm, if proven effective, VR technology may become a potent tool to deliver mental health programming in clinical populations during their outpatient treatment sessions. Trial Registration NCT05642364; International Registered Report Identifier (IRRID) PRR1-10.2196/45100
... It is a short-term skill that incorporates restructuring, relaxation, training, and exposure therapy and can be delivered in person and online. Implementing cognitive behavior therapy can be helpful in T1D adolescents with anxiety and depressive symptoms to lead to better and improved diabetic outcomes [41,46,47,48]. ...
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Diabetes Mellitus is a global health issue, and the rising prevalence of depression and anxiety among individuals with diabetes poses a significant concern. Metabolic disturbances in diabetes can potentially impact psychological well-being. The study aims to determine the prevalence of depression, and anxiety, and explore the relationship between these mental health conditions and diabetes.
... Some forms of online psychological help are used as pure self-help, while others require regular contact with a psychologist via the Internet (Clarke et al., 2009). The majority of the literature indicates that online psychotherapy is as effective as its face-to-face counterpart (Wagner et al., 2014). Meta-analyses show small-to-medium effect sizes when Internet interventions are delivered as stand-alone selfhelp interventions, and medium-to-large effect sizes when delivered as therapist-guided interventions, both compared with usual care (Schröder et al., 2016). ...
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Introduction The COVID-19 pandemic shifted many aspects of life from face-to-face to an online form, including psychological help. Many people had to face the choice of adjourning contact with a psychologist or shifting it to the Internet. This study aimed to develop an understanding of attitudes and opinions toward relatively new phenomenon in Poland – online psychological help. Method Seventy two ( N =72) statements about relationship between COVID-19 pandemic and online psychological help from (potential) patients were included in this research. The statements were collected from a community sample via open-ended question for volunteers added to an online survey conducted regarding an existing project. The statements were exclusively written responses to the following question: If you want to provide us with something about the relationships between the COVID-19 pandemic and online help/psychotherapy, please let us know below. By reason of exploratory character of our study and general phenomenological philosophical approach and constructionist approach, a thematic analysis method was used to analyze the data. Results The analysis led us to identify three general themes with sub-themes that refer to meaningful aspects of online psychological help: 1. Online psychological help situates in the shadow of face-to-face help, 1.1. It frustrates the needs, especially the need for psychological contact, 1.2. It contributes to negative emotions, 1.3. It is sometimes better than the face-to-face help; 2. Online psychological help is a solution during the COVID-19 pandemic, 2.1. It provides a sense of continuity during lockdown, 2.2. It is a means to adapt to exceptional circumstances, 3. The concerns about the credibility and effectiveness of online psychological help. Discussion The results show (potential) patients’ attitudes (including emotions, thoughts, and concerns) toward online psychological help. The perspective presented here could be beneficial to professionals. A better understanding of client/patient attitudes will allow for more accurate customization of the online help and sensitize psychologists to the emotions that may occur about online psychological help. It could also be beneficial for patients to understand how other people would feel about online psychological help and develop ones’ own self-awareness of the attitudes toward online psychological help.
... Common support measures offered were weekly phone calls with a coach [62,64,73,74,80,81,84,86,94,103,109,116,119,132,134,139,148,159,161] and adherence reminders [61,63,95,107,112,122,129,144,153,158]. Many studies provided coach feedback to participants after each lesson [72,75,77,99,106,108,111,122,124,130,135,141,144,145,154,155,157,158]. A few studies integrated the digital intervention with face-to-face meetings, either with a therapist [104,112] or in a group counseling session [85,125]. ...
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Background New approaches to the treatment of depression are necessary for patients who do not respond to current treatments or lack access to them because of barriers such as cost, stigma, and provider shortage. Digital interventions for depression are promising; however, low patient engagement could limit their effectiveness. Objective This systematic literature review (SLR) assessed how participant adherence to and engagement with digital interventions for depression have been measured in the published literature, what levels of adherence and engagement have been reported, and whether higher adherence and increased engagement are linked to increased efficacy. Methods We focused on a participant population of adults (aged ≥18 years) with depression or major depressive disorder as the primary diagnosis and included clinical trials, feasibility studies, and pilot studies of digital interventions for treating depression, such as digital therapeutics. We screened 756 unique records from Ovid MEDLINE, Embase, and Cochrane published between January 1, 2000, and April 15, 2022; extracted data from and appraised the 94 studies meeting the inclusion criteria; and performed a primarily descriptive analysis. Otsuka Pharmaceutical Development & Commercialization, Inc (Princeton, New Jersey, United States) funded this study. Results This SLR encompassed results from 20,111 participants in studies using 47 unique web-based interventions (an additional 10 web-based interventions were not described by name), 15 mobile app interventions, 5 app-based interventions that are also accessible via the web, and 1 CD-ROM. Adherence was most often measured as the percentage of participants who completed all available modules. Less than half (44.2%) of the participants completed all the modules; however, the average dose received was 60.7% of the available modules. Although engagement with digital interventions was measured differently in different studies, it was most commonly measured as the number of modules completed, the mean of which was 6.4 (means ranged from 1.0 to 19.7) modules. The mean amount of time participants engaged with the interventions was 3.9 (means ranged from 0.7 to 8.4) hours. Most studies of web-based (34/45, 76%) and app-based (8/9, 89%) interventions found that the intervention group had substantially greater improvement for at least 1 outcome than the control group (eg, care as usual, waitlist, or active control). Of the 14 studies that investigated the relationship between engagement and efficacy, 9 (64%) found that increased engagement with digital interventions was significantly associated with improved participant outcomes. The limitations of this SLR include publication bias, which may overstate engagement and efficacy, and low participant diversity, which reduces the generalizability. Conclusions Patient adherence to and engagement with digital interventions for depression have been reported in the literature using various metrics. Arriving at more standardized ways of reporting adherence and engagement would enable more effective comparisons across different digital interventions, studies, and populations.
... The results of Compen et al. 's study in face-to-face and online mindfulness intervention led to a statistically significant and clinically reliable reduction of psychological distress compared to conventional treatment [37]. In one clinical trial, Wagner et al. reported high and equal effectiveness in reducing depression scores in both CBT and ICBT [38]. The reason why SIT technique leads to depression reduction is that in this technique with coping skills program, how to use and receive social support is taught and this process helps to reduce depression in these people. ...
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Abstract Background Some studies indicate that more than 10% of pregnant women are affected by psychological problems. The current COVID‐19 pandemic has increased mental health problems in more than half of pregnant women. The present study compared the effectiveness of virtual (VSIT) and semi-attendance Stress Inoculation Training (SIT) techniques on the improvement of the symptoms of anxiety, depression, and stress of pregnant women with psychological distress. Methods This study was conducted on 96 pregnant women with psychological distress in a 2-arm parallel-group, randomized control trial between November 2020 and January 2022. The semi-attendance SIT received treatment for six sessions, sessions 1, 3 and 5 as individual face-to-face and sessions 2, 4 and 6 as virtual once a week for 60 min continuously [n = 48], and the virtual SIT received six sessions simultaneously once a week for 60 min (n = 48) in pregnant women of 14–32 weeks’ gestation referred to two selected hospitals. The primary outcome of this study was BSI-18 [Brief Symptom Inventory] and NuPDQ-17 [Prenatal Distress Questionnaire]. The secondary outcomes were the PSS-14 [Cohen’s General Perceived Stress Scale]. Both groups completed questionnaires measuring anxiety, depression, pregnancy-specific stress, and generally perceived stress questionnaires before and after the treatment. Results The post-intervention results showed that the stress inoculation training technique in both VSIT and SIT interventions effectively reduced anxiety, depression, psychological distress, pregnancy-specific stress and general perceived stress [P
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In the 21st century of digitalization, online counselling post pandemic had gained pertinent importance. The relationship between a therapist and client can be mended or evoke fissures as sessions shifted from offline to online mode. Thus, the objectives were twofold; to explore the reflections upon the experiences of the dyad through digital counselling and examine the themes found in the experiences of both the parties involved. The paper also documents certain factors responsible for the experiences such as asynchronous communication, privacy, lack of non-verbal cues, legal or ethical issues in the therapeutic dyad. This systematic review synthesized evidence using PRISMA guidelines conducted across Web of Science, PsycINFO and Scopus published between 2010-2022.Digital counselling has ameliorating effects and should not be considered as a substitute for in-person counselling. It helps the clients to connect with the therapist without any hassle of geographical barriers. Inferences have shed light on the change observed in the relationship such as mental state of the therapist, body language of the client etc. Future implications have been drawn for the present study.
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Background Obsessive-compulsive disorder (OCD) is a common and chronic mental illness with a high rate of disability. Internet-based cognitive behavioral therapy (ICBT) makes online treatment available to patients and has been shown to be effective. However, 3-arm trials on ICBT, face-to-face cognitive behavioral group therapy (CBGT), and only medication are still lacking. Objective This study is a randomized, controlled, assessor-blinded trial of 3 groups for OCD: ICBT combined with medication, CBGT combined with medication, and conventional medical treatment (ie, treatment as usual [TAU]). The study aims to investigate the efficacy and cost-effectiveness of ICBT related to CBGT and TAU for adults with OCD in China. Methods In total, 99 patients with OCD were selected and randomly assigned to the ICBT, CBGT, and TAU groups for treatment for 6 weeks. The primary outcomes were the Yale-Brown Obsessive-Compulsive Scale (YBOCS) and the self-rating Florida Obsessive-Compulsive Inventory (FOCI), compared at baseline, during treatment (3 weeks), and after treatment (6 weeks), to analyze efficacy. The secondary outcome was the EuroQol Visual Analogue Scale (EQ-VAS) scores of the EuroQol 5D Questionnaire (EQ-5D). The cost questionnaires were recorded to analyze cost-effectiveness. ResultsRepeated-measures ANOVA was used for data analysis, and the final effective sample size was 93 (ICBT: n=32, 34.4%; CBGT: n=28, 30.1%; TAU: n=33, 35.5%). After 6-week treatment, the YBOCS scores of the 3 groups significantly decreased (P
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Providing therapist-guided cognitive behaviour therapy via the Internet (ICBT) has advantages, but a central research question is to what extent similar clinical effects can be obtained as with gold-standard face-to-face cognitive behaviour therapy (CBT). In a previous meta-analysis published in this journal, which was updated in 2018, we found evidence that the pooled effects for the two formats were equivalent in the treatment of psychiatric and somatic disorders, but the number of published randomized trials was relatively low (n=20). As this is a field that moves rapidly, the aim of the current study was to conduct an update of our systematic review and meta-analysis of the clinical effects of ICBT vs. face-to-face CBT for psychiatric and somatic disorders in adults. We searched the PubMed database for relevant studies published from 2016 to 2022. The main inclusion criteria were that studies had to compare ICBT to face-to-face CBT using a randomized controlled design and targeting adult populations. Quality assessment was made using the Cochrane risk of bias criteria (Version 1), and the main outcome estimate was the pooled standardized effect size (Hedges’ g) using a random effects model. We screened 5,601 records and included 11 new randomized trials, adding them to the 20 previously identified ones (total n=31). Sixteen different clinical conditions were targeted in the included studies. Half of the trials were in the fields of depression/depressive symptoms or some form of anxiety disorder. The pooled effect size across all disorders was g=0.02 (95% CI: –0.09 to 0.14) and the quality of the included studies was acceptable. This meta-analysis further supports the notion that therapist-supported ICBT yields similar effects as face-to-face CBT.
Background Health planning should be based on data about prevalence, disability and services used. Aims To determine the prevalence of ICD-10 disorders and associated comorbidity, disability and service utilisation. Method We surveyed a national probability sample of Australian households using the Composite International Diagnostic Interview and other measures. Results The sample size was 10 641 adults, response rate 78%. Close to 23% reported at least one disorder in the past 12 months and 14% a current disorder. Comorbidity was associated with disability and service use. Only 35% of people with a mental disorder in the 12 months prior to the survey had consulted for a mental problem during that year, and most had seen a general practitioner. Only half of those who were disabled or had multiple comorbidity had consulted and of those who had not, more than half said they did not need treatment. Conclusions The high rate of not consulting among those with disability and comorbidity is an important public health problem. As Australia has a universal health insurance scheme, the barriers to effective care must be patient knowledge and physician competence.
Zusammenfassung. Theoretischer Hintergrund: Nach Beck sind negative automatische Gedanken eine wichtige Ursache fur Depressionen. Fragestellung: Wie gut sind die Gutekriterien des “Fragebogen positiver und negativer automatischer Gedanken“ (FAG)? Methode: Die psychometrischen Kennwerte des FAG wurden anhand von zwei Stichproben der Allgemeinbevolkerung (n = 352 und n = 171) und einer Patientenstichprobe (n = 59) ermittelt. Ergebnisse: Die drei Skalen des FAG klaren zusammen ca. 60% der Varianz nach VARIMAX-Rotation auf und zeigen Interne Konsistenzen zwischen r = .76-.93. In Abhangigkeit vom Ausmas an Depression, Manie und Angst zeigen sich unterschiedliche Muster positiver und negativer automatischer Gedanken in den Skalen des FAG. Schlussfolgerungen: Mit dem FAG liegt ein zeitokonomisches und reliables Instrument zur Erfassung von positiven und negativen automatischen Gedanken vor.
Results of 24 studies (based on 20 distinct data sets) relating the quality of the working alliance (WA) to therapy outcome were synthesized using meta-analytic procedures. A moderate but reliable association between good WA and positive therapy outcome was found. Overall, the quality of the WA was most predictive of treatment outcomes based on clients' assessments, less so of therapists' assessments, and least predictive of observers' report. Clients' and observers' rating of the WA appear to be more correlated with all types of outcomes reported than therapists' ratings. The relation of WA and outcome does not appear to be a function of the type of therapy practiced, the length of treatment, whether the research is published, or the number of participants in the study. (PsycINFO Database Record (c) 2012 APA, all rights reserved)