S E C O N D A R Y A N A LY S I S

Behavioral Activation Contributed to the
Total Reduction of Depression Symptoms
in the Smartphone-based Cognitive
Behavioral Therapy: A Secondary Analysis
of a Randomized, Controlled Trial
A B S T R AC T
Objective: The contribution of components incognitive behavior therapy (CBT) to the total
reduction of depression symptoms has notbeen well elucidated, and previous studies
couldn’t exclude the human factors in thetherapy. Design: This is a secondary analysis
of a randomized, controlled trial comparing
automated smartphone CBT without humanfactors plus antidepressant switch against
antidepressant switch alone among patientswith antidepressant-resistant depression.
The present CBT consisted of self-monitoring,
behavioral activation, and cognitive
restructuring. We used linear regression topredict the overall pre- to post-symptom
improvement based on improvement achievedby sessions teaching each cognitive or behavioral
skill. The overall improvement was measured
with the Beck Depression Inventory-II andthe session-to-session improvement with K6.
Results: Of the 164 participants originallyenrolled in the study, 94 participants whocompleted all K6 evaluation were included in
the primary analyses. The results indicated that
K6 score reduction in the first half of behavioral
activation significantly predicted BDI-II scorereduction. The sensitivity analysis including
162 participants did not change the result. K6score reductions after other CBT sessions did
not significantly predict BDI-II score reduction.
Conclusion: The behavioral activation seems tocontribute to the total reduction of depressive
symptoms even if human factors are excluded byusing automated smartphone CBT.
KEYWORDS: Cognitive behavioral therapy,
depression, information technology,
smartphone, component study

by HISSEI IMAI, MD, PhD; MITSUHIKO YAMADA, MD, PhD;MASATOSHI INAGAKI, MD, PhD; NORIO WATANABE, MD, PhD; BUN CHINO, MD, PhD;AKIO MANTANI, MD, PhD; and TOSHIAKI A FURUKAWA, MD, PhD

Drs. Imai, Watanabe, and Furukawa are with the Department of Health Promotion of Human Behavior at Kyoto University Graduate
School of Medicine / School of Public Health in Kyoto, Japan. Dr. Yamada is with the Department of Neuropsychopharmacology at the
National Institute of Mental Health, National Center of Neurology and Psychiatry in Kodaira, Japan. Dr. Inagaki is with the Departmentof Psychiatry at Shimane University School of Medicine in Shimane, Japan. Dr. Chino is with the Ginza Taimei Clinic in Tokyo, Japan. Dr.
Mantani is with Mantani Mental Clinic, Hiroshima, Japan.

C

Innov Clin Neurosci. 2020;17(7–9):21–25

Cognitive behavioral therapy (CBT) is oneof the most rigorously studied treatments fordepression. One network meta-analysis showed
its effect was large compared to wait-list controls
and medium compared to usual care or placebo.1
Studies indicate the efficacy of CBT in treating
major depression is comparable to that ofantidepressants.2,3
Although CBT is an effective treatment
package for depression, its constituent techniques
are somewhat heterogeneous. The most common
treatments include psychoeducation, selfmonitoring, cognitive restructuring, behavioral
activation, exposure, assertion training, problemsolving, and mindfulness.
The inevitable question then is which
components contribute to the program’s

effectiveness. Four meta-analyses focusing on
components have been conducted, but the results
were inconsistent.4–7 The first meta-analysis of
27 studies in CBT and other psychotherapies
indicated that there was no significant difference
between psychotherapies with or without thecritical component.4 The second meta-analysis
included 34 studies with bona fide CBT andnon-bona fide treatments, which were not basedon any recognized psychological principles, inchildren and adolescents. The results also showedthat full CBT treatments had no significant
additional benefit over their components.5 As aresult, researchers emphasized the importance ofthe common factors in psychotherapies. However,these two meta-analyses did not distinguishbetween dismantling and additive designs. The

FUNDING: The study was funded by the Ministry of Health, Labor and Welfare, Japan (H-22-Seishin-Ippan-008) from April 2013
through March 2014, and thereafter by the Japan Foundation for Neuroscience and Mental Health (JFNMH). The JFNMH received
donations from Asahi Kasei, Eli-Lilly, GSK, Janssen, MSD, Meiji Seika, Mochida, Otsuka, Pfizer, Shionogi, Taisho, and MitsubishiTanabe. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of thedata; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
DISCLOSURES: Dr Mitsuhiko Yamada has received speaking fees from Meiji and has contracted research with Nippon Chemiphar. Dr
Masatoshi Inagaki has received lecture fees from Pfizer, Mochida, Shionogi, Daiichi-Sankyo, Meiji, Takeda, and Sumitomo Dainippon
Pharma. He has received royalties from Nippon-Hyoron-Sha, Nanzando, Seiwa-Shoten, Igaku-Shoin, and Technomics. Dr Norio
Watanabe has received royalties from Akatsuki and Sogen-sha. Dr Chino has received lecture fees from Eli Lilly, Meiji and MitsubishiTanabe. Dr Mantani has received lecture fees from Mochida, Eli Lilly and Meiji. Dr Kato has received lecture fees from Eli Lilly and
Mitsubishi-Tanabe, and has contracted research with GlaxoSmithKline, MSD and Mitsubishi-Tanabe. He has received royalties from
Kyowa Yakuhin and Medical Tribune. Dr Furukawa reports personal fees from Meiji, Mitsubishi-Tanabe, MSD and Pfizer and a grantfrom Mitsubishi-Tanabe, outside the submitted work; he has a patent 2018-177688 pending. Dr Hissei Imai received the lecture fee
from Tanabe-Mitsubishi pharma and Kyowa pharmaceutical industry outside the submitted work.
CORRESPONDENCE: Hissei Imai, MD, PhD; Email: ihits@hotmail.com

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S E C O N D A R Y A N A LY S I S
former design compared full treatment withtreatment without a specific component, while
the latter design compared existing treatment
against an existing treatment with an additional
component.
Investigators of the third meta-analysis
considered these design differences in theiranalysis. They included 66 studies with CBT
as well as other psychotherapies. The results
indicated that the added specific component
yielded a significant effect in the meta-analysisof additive design studies, whereas there wereno significant differences between treatments
in dismantling design studies.6 The fourthmeta-analysis included 16 studies with various
psychotherapies and concluded that studies
lack the statistical power and quality to draw
any meaningful conclusion.7 In summary, thecontribution of each component to the total effectremains unsolved in any kind of psychotherapies
including CBT.
The present study is the first to evaluate thecontribution of the components to the total
effect by using smartphone CBT. We used thedata from a randomized, controlled trial (RCT)evaluating smartphone-based CBT as an adjunctto pharmacotherapy. It was a guided self-help,
nine-week intervention against patients withantidepressant-refractory depression.8,9 The
results indicated that our smartphone CBT was
effective in reducing depression severity.
All of the previous studies that evaluatedcomponents of CBT were conducted by humantherapists.10–12 However, such studies areconfounded by therapist factors. The alliance,
empathy, and therapist differences areimportant factors in psychotherapy and will
influence the outcome.13 Researchers conduct
training and supervision while monitoringthem via audio or videotapes and administeringsome scales to control these factors. However,therapy will not be completely the same in CBT
conducted by human therapists. By contrast,
our smartphone CBT app can completely control
therapist factors, so that the therapy provided in
the present study is essentially identical acrossparticipants. Moreover, in our smartphone
CBT we can closely monitor the patients’participation in the therapy. In our smartphone
CBT app, patients could not proceed to the next
session without reading all the current session
and completing the homework, and all of theiractivities were uploaded and recorded on the
remote server.

Objectives. The aim of the present study is
to clarify the contribution of the components
of smartphone CBT package to the total effect.
Elucidation of the more effective components ofa complex intervention such as CBT is not only
theoretically important but also pragmaticallymeaningful, as such knowledge will enable thefuture therapies to be more effective and efficient.

METHODS

Study design. This is a secondary analysisof an RCT comparing smartphone CBT plus
antidepressant switch against antidepressant
switch alone among patients withantidepressant-resistant depression who had
not responded to one or more antidepressantsat adequate dosage for four or more weeks. A
detailed information of the RCT was described
elsewhere.9
Participants. Included participants were
patients with major depressive disorder without
psychotic features diagnosed by the Diagnostic
and Statistical Manual of Mental Disorders (Fifth
Edition) aged between 25 and 59 years andrefractory to antidepressant-treatment.
Procedure. In total, 164 participants wereenrolled in the study and randomized 1:1 tothe two arms. Participants in the CBT arm
received smartphone CBT for nine weeks, andthe other participants received CBT smartphoneintervention after waiting for nine weeks, bothin addition to medication switch, which is astandard treatment for treatment-resistantdepression. They completed the Beck Depression
Inventory-II (BDI-II)14,15 at baseline, at nine
weeks (post-treatment) and at 17 weeks (posttreatment follow-up); in addition, they filled in
K-616,17 during smartphone CBT intervention at
the beginning of every session.
Treatment. The smartphone CBT consistsof the following eight sessions: one welcome
session briefly explaining CBT and confirming theparticipants’ ability to use the smartphone, twosessions on self-monitoring, two on behavioral
activation, two on cognitive restructuring, andone session for relapse prevention. Participants
were expected to complete each session withinapproximately one week. They must complete
at least one homework to proceed to the next
session and fill in K6 score at the beginning ofeach session. The details of the program wasdescribed previously.18
Sessions 1 and 2 are about self-monitoring.
Participants learn how thought, behavior,

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emotion, and physical reaction influence eachother under emotion-evoking situations.
Homework is to fill in a so-called Mind map,
where participants describe the situation, theirautomatic thoughts, physical reaction, andbehavior and choose their emotion from among
the following four; sad/depressed; anxious/
worried; angry; and happy and monitor its
intensity in five grades. Session 1 teaches theprinciples of self-monitoring according to the
cognitive-behavioral model, and Session 2
provides more tips for filling in a Mind map.
Sessions 3 and 4 teach behavioral activation.
Participants learn how their behavior can
influence their emotional status. Homework is
a behavioral activation task, where participants
choose one of the many pleasurable activities
listed in the app or make up their own. They rate
their expected level of mastery and pleasure
before the activity and their achieved levels after
the activity. Listed activities are categorized
by the time required to finish them, namely,
less than five seconds, less than five minutes,
less than 60 minutes, and 60 minutes or more.
Participants are advised to progress in small steps.
Session 3 focuses on psychoeducation and tips
about behavioral activation, including dividing
a difficult task into small pieces and startingwith activities with pleasure rather than thosewith sense of mastery. Session 4 includes review
of Session 3 and other tips about behavioral
activation, such as starting from activities one
can do by oneself, scheduling, and imagining
themselves completing the chosen activity.
Sessions 5 and 6 are about cognitive
restructuring. Participants learn four perspectives
that can lead them to alternative thoughts. The
first one asks for the evidence for and against the
automatic thoughts. The second asks for possible
reasons to the contrary of the automatic thoughts
through rating their subjective confidence in theirthoughts. The third is to change the viewpointby imagining a friend asking for help with thesame automatic thoughts. The last one asks forsome course of action to take in the case theautomatic thought were true. Participants are
asked to rate their intensity of emotion after
looking at the alternative thoughts they havecome up with. Session 5 deals with the first two
perspectives, and Session 6 deals with the lasttwo perspectives.
The final session is an epilogue that discusses
relapse prevention. This session summarizes all
the previous sessions, asks participants about

S E C O N D A R Y A N A LY S I STABLE 1. Baseline characteristics.
PARTICIPANTS INCLUDEDMEASUREMENT
IN THE PRIMARY ANALYSIS(N=94)
Age, mean (SD)41.6 (8.5)
Gender (female), %50.0
Education (years), mean (SD)
14.8 (2.3)
Age at onset, mean (SD)33.7 (10.0)
Episode number, mean (SD)
3.4 (5.0)
Episode duration (months), mean (SD)25.2 (51.3)
Allocation (waiting list), %36.2
Full time
35.1
Part time
10.6
Employment
Leave of absence
27.7
status, %Homemaker
8.5
Unemployed
18.1
Single36.2
Marital status, % Divorced, separated
8.5
Married55.3
Baseline BDI score, mean (SD)25.1 (13.0)
BDI: Beck Depression Inventory; SD: standard deviation

OTHER PARTICIPANTS (N=70)
38.9 (9.1)
56.9
15.0 (3.0)
32.4 (11.0)
3.0 (4.1)
23.3 (46.5)
70.8
41.7
4.2
34.7
4.2
12.5
43.1
16.7
40.3
21.5 (12.6)

TABLE 2. Score reduction in BDI-II from pre- to post-intervention, and K6 score reduction after each session
SESSION/SCALESCORE REDUCTION, MEAN (SD)BDI
6.68 (8.09)
K6 session
Session 1 (self-monitoring: SM1)
1.53 (3.42)
Session 2 (self-monitoring: SM2)
0.76 (3.03)
Session 3 (behavioral activation: BA1)
1.04 (3.23)
Session 4 (behavioral activation: BA2)
0.20 (3.28)
Session 5 (cognitive restructuring: CR1)
0.23 (2.80)
Session 6 (cognitive restructuring: CR2)
0.84 (2.78)
BA: behavioral activation; BDI: Beck Depression Inventory; CR: cognitive restructuring; SM: self-monitoring

possible obstacles against using the CBT skills
they have learned, and troubleshoots them.

MEASURES

The second edition of Beck Depression
Inventory (BDI-II). The original Beck Depression
Inventory (BDI) was published in 1961.19 It has
been used widely for the self-evaluation ofdepression. The second edition of BDI (BDI-II) was
developed in accordance with DSM-IV, and its
reliability and validity have been established.20
The reliability and validity of the Japanese versionof BDI-II are also satisfactory.21 Cronbach’s alpha ofthe present sample was 0.91.
K6. K6 is composed of six items based on
the item response theory and used for thescreening of common mental disorders and forthe evaluation of psychological distress. The scale
ranges from 0 to 24 and a higher score indicatesgreater severity.16 Its reliability and validity are
high, and the validity of the Japanese version
has been established.17,22 Cronbach’s alpha of thepresent sample was 0.87.
Data analysis. The aim of our analysis is
to examine the contribution of each session to
overall improvement. We defined the overall
improvement as the score reduction in BDI-II frompre- to post-CBT intervention. The improvement
after each session was calculated as the scorereduction in K6 between sessions. For example,
the score reduction between Sessions 2 and 3
is considered to indicate the improvement after
Session 2.
First, univariate linear regression was
conducted with the overall improvement
represented by BDI-II score reduction as adependent variable and the K6 score reduction
between sessions as an independent variable.

Next, the multivariate linear regression adjusted
for age, gender, and allocation was also
conducted, using the same variables.
Our primary analysis was based on thecompleters’ dataset, where the data was included
only if participants completed all K6 evaluations.
As all the K6 data after the dropout could not
gain, it is appropriate to see the completer’s
dataset to compare the score reduction in eachsession. As a sensitivity analysis, we included
all available K6 data to see the robustness ofthe primary results. We set the threshold forstatistical significance at conventional p<0.05.

RESULTSOf the 164 participants originallyenrolled in the study, 94 participants whocompleted all K6 evaluation were includedin the primary analysis. Table 1 shows theirbaseline characteristics. The percentage of theparticipants allocated to the waiting list in the
primary analysis was significantly higher thanthat in the secondary analysis (χ2[1]=0.89,
p<0.001). There was no significant differencein other baseline characteristics between theparticipants included in the primary analysis
and those who were not.
The score reduction in BDI-II from preto post-intervention and in K6 between
sessions. Table 2 shows the score reductionin BDI-II from pre- to post-intervention, andK6 score reduction between sessions. There isa significant difference in K6 score reductions
between sessions (analysis of variance [ANOVA]
F[5, 558]=2.48, p=0.03]. Post-hoc comparison
using the Tukey Honest Significant Difference(HSD) test indicated that the mean scorereduction after Session 1 was significantly
greater than that after Session 4 (p=0.04) orafter Session 5 (p=0.049), but there was no
significant difference among other comparisons.
The relationship between BDI-II andK6 score reduction. Tables 3A and 3B
show the results of linear regression. The
results of the univariate regression indicatedthat K6 score reduction in Session 3, that is,reduction after the first session of behavioral
activation, explained 10 percent of the total
variance (R2=0.10, F[1,92]=10.23, p=0.002)
and significantly predicted BDI-II scorereduction (beta=0.32, p=0.002). Other K6score reductions did not significantly predict
BDI-II score reduction. The multivariate linear
regression adjusted for age, gender, andICNS INNOVATIONS IN CLINICAL NEUROSCIENCE July–September 2020 • Volume 17 • Number 7–9

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allocation, and also indicated that K6 scorereduction in Session 3 significantly predicted
BDI-II score reduction (beta=0.31, p=0.004).
Sensitivity analysis. We conducted asensitivity analysis including participants who
did not complete all the K6 evaluation. The
results were in accordance with the primary
analysis in that K6 score reduction after Session
3 significantly predicted BDI-II score reductionin univariate regression (beta=0.26, p=0.002)
and in multivariate regression adjusted for age,gender, and allocation (beta=0.26, p=0.001).
However, K6 score reduction after Session 2(second half of self-monitoring) also predicted
BDI-II score reduction in univariate regression(beta=0.18, p=0.02) and in multivariate
regression adjusted for age, gender, andallocation (beta=0.16, p=0.048). K6 scorereduction in any other period did not significantly
predict the total BDI-II score reduction.

DISCUSSION

The previous studies comparing the effect ofcomponents of CBT could not exclude the humanfactors in the CBT therapy. The present study is thefirst study to overcome the limitation by using theautomated smartphone CBT. The results indicatedthat improvement seen during the behavioral
activation was related to the total improvement,
which was confirmed by an analysis adjusting forage, gender, and allocation, and in a sensitivity
analysis.
Two component RCTs for depression havebeen published.10,11 These trials generally favoredbehavioral components. The first study compared
behavioral activation only, behavioral activation
plus cognitive restructuring, and behavioral
activation plus cognitive restructuring plus
schema work, but found no significant difference
among the three.10 The study conducted by
Dimidjian et al included a larger number ofparticipants and compared expanded behavioral
activation with cognitive therapy.11 It showed that
expanded behavioral activation was comparable
to antidepressant medication and significantly
superior to cognitive therapy in effect among
patients with severe depression. A directcomparison RCT between behavioral activation
only and full CBT has recently confirmed that theformer was non-inferior to the latter.23
One explanation of these advantages of
behavioral activation compared with cognitive
therapy is reducing avoidance. Patients withemotional disorders try to avoid unexpected

TABLE 3A. Univariate linear regression predicting score reduction in BDI-II based on between-session score reduction inK6 (completers’ analysis, n=94)
SESSION
B
SE
p
R2
Session 1 (SM1)
0.17
0.25
0.49
0.07
Session 2 (SM2)
0.15
0.28
0.59
0.06
Session 3 (BA1)
0.79
0.25
0.002
0.10
Session 4 (BA2)
0.22
0.26
0.39
0.01
Session 5 (CR1)
0.44
0.30
0.14
0.02
Session 6 (CR2)
0.29
0.30
0.35
0.01
BA: behavioral activation; BDI-II: Beck Depression Inventory-II; CR: cognitive restructuring; SM: self-monitoring“1” and “2” represents first-half and second-half of each component

TABLE 3B. Multivariate linear regression predicting score reduction in BDI-II based on between-session score reductionin K6 adjusted for age, gender and allocation group (completers’ analysis, n=94)
SESSIONB
SE B
p
Session 1 (SM1)
0.20
0.25
0.42
Session 2 (SM2)
0.09
0.28
0.75
Session 3 (BA1)
0.77
0.25
0.004
Session 4 (BA2)
0.15
0.26
0.55
Session 5 (CR1)
0.42
0.30
0.16
Session 6 (CR2)
0.31
0.30
0.30
BA: behavioral activation; BDI-II: Beck Depression Inventory-II; CR: cognitive restructuring; SM: self-monitoring“1” and “2” represents first-half and second-half of each component

TABLE 4A. Univariate linear regression predicting score reduction in BDI-II based on between-session score reduction inK6 (secondary analysis).
SESSIONB
SE B
p
R2
Session 1 (SM1) (n=162)
0.08
0.16
0.60
0.002
Session 2 (SM2) (n=162)
0.42
0.19
0.02
0.03
Session 3 (BA1) (n=142)
0.64
0.20
0.001
0.07
Session 4 (BA2) (n=130)
0.23
0.22
0.28
0.01
Session 5 (CR1) (n=116)
0.17
0.25
0.51
0.004
Session 6 (CR2) (n=94)
0.29
0.30
0.35
0.01
BA: behavioral activation; BDI-II: Beck Depression Inventory-II; CR: cognitive restructuring; SM: self-monitoring“1” and “2” represents first-half and second-half of each component

TABLE 4B. Multivariate linear regression predicting score reduction in BDI-II based on between-session score reductionin K6 adjusted for age, gender and allocation group (full analysis set)
SESSIONB
SE B
p
Session 1 (SM1) (n=162)
0.13
0.15
0.40
Session 2 (SM2) (n=162)
0.37
0.19
0.048
Session 3 (BA1) (n=142)
0.64
0.20
0.001
Session 4 (BA2) (n=130)
0.19
0.22
0.38
Session 5 (CR1) (n=116)
0.14
0.25
0.59
Session 6 (CR2) (n=94)
0.30
0.31
0.30
BA: behavioral activation; BDI-II: Beck Depression Inventory-II; CR: cognitive restructuring; SM: self-monitoring“1” and “2” represents first-half and second-half of each component

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S E C O N D A R Y A N A LY S I S
emotional experience, which might prevent
recovery from subjective distress.24,25 Anotherexplanation is change in reality. A study analyzing
cognitive therapy showed that interpersonalcognitive change was negatively related to global
functioning, but actual interpersonal change waspositively related to it.26
The present trial controlled the humantherapist factors, as it was conducted throughan automated smartphone CBT app. Our results
were also supportive of the importance of the
behavioral component in smartphone CBT. The
improvement in depressive symptoms during
behavioral sessions was significantly associatedwith the total improvement of depressive
symptoms, whereas there were no significant
relations between the improvement during selfmonitoring or cognitive restructuring sessions
and the total improvement.
One question is if the present result just reflects
the order of the components. In fact, Rabin et al27
reported that the depressive symptoms diminish
in curvilinear manner, and the improvement
occurred most in the first 3 to 4 weeks. In ourstudy, the behavior session, which was related
to the total effect in the present study, wasconducted in around 3 to 5 weeks. However,
the improvement in the present study was notcurvilinear—the relatively big improvement
occurred after Sessions 1, 3, and 6, with thebiggest improvement after Session 1, which was
not significantly related to the total effect. Thismeans that the biggest improvement seen after
the initial session does not necessarily contributeto the total improvement. The results suggest that
improvement might be accelerated if one gets a
positive effect from behavioral activation.
Interestingly, only the first of the two
behavioral activation sessions was significantly
related to the total effect. The first session focusedon psychoeducation and tips about behavioral
activation, such as breaking down difficult tasks
into small pieces and starting from activities
with pleasure, rather than those with mastery.
The second session focused on other tips about
behavioral activation, including starting from
activities one can do by oneself, scheduling, andimagining the goals. It might be that the former
tips are enough to produce the effect, but such ahypothesis should be tested in a future trial.
Limitations. The present study has some
limitations. First, we did not analyze the longterm effects of the behavior component. Gortner
et al28 showed CBT was no more effective thanits components in preventing relapse by thetwo-year follow up. Whether the improvement
seen in the behavioral activation session of
our smartphone app is related to long-term
improvement should be examined. Second, thepresent study is only observational in nature, andwe should confirm the importance of behavioral
components in other study designs, such asadditive or dismantling, and various sequential
designs. Another weakness in our study, as wellas other studies, is that the findings might beconfounded by the order of components, butsuch ordering effect has never been properly
researched.
By contrast, the strengths of the present study
are that we were able to completely control fortherapist factors and to closely monitor patients’participation and progress. No study using faceto-face CBT by live therapists has examined suchdetails.

CONCLUSION

In conclusion, this longitudinal observational
study suggests that the behavioral component
makes a significant contribution to the total
reduction of depressive symptoms, even if humanfactors are excluded by automated smartphone
CBT. Future CBT therapists, as well as CBT apps,
might wish to put more emphasis on behavioral
activation during the course of conducting thetotal CBT package.

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