R E S E A R C H Open Access
Transdiagnostic efficacy of a group exercise
intervention for outpatients with
heterogenous psychiatric disorders: a
randomized controlled trial
, Britta Seiffer
, Gorden Sudeck
, Inka Rösel
, Martin Hautzinger
and Sebastian Wolf
Background: Exercise efficaciously reduces disorder-specific symptoms of psychiatric disorders. The current study
aimed to examine the efficacy of a group exercise intervention on global symptom severity and disorder-specific
symptoms among a mixed outpatient sample.
Methods: Groups of inactive outpatients, waiting for psychotherapy, with depressive disorders, anxiety disorders,
insomnia, and attention-deficit/hyperactivity disorders were randomized to a manualized 12-week exercise
intervention, combining moderate to vigorous aerobic exercise with techniques for sustainable exercise behaviour
change (n= 38, female = 71.1% (n=27),M
= 36.66), or a passive control group (n= 36, female = 75.0% (n=27),
= 34.33). Primary outcomes were global symptom severity and disorder-specific symptoms, measured with the
Symptom Checklist-90-Revised and Pittsburgh Sleep Quality Index pre- and post-treatment. Secondary outcome was
the self-reported amount of exercise (Physical Activity, Exercise, and Sport Questionnaire), measured pre-treatment,
intermediate-, and post-treatment. Intention-to-treat analyses were conducted using linear mixed models. Linear
regressions were conducted to examine the effect of the change of exercise behaviour on the change of symptoms.
Results: The intervention significantly improved global symptom severity (d=0.77,p=.007),depression(d=0.68,
p=.015),anxiety(d=0.87,p= .002), sleep quality (d=0.88,p= .001), and increased the amount of exercise (d=0.82,
p< .001), compared to the control group. Post-treatment differences between groups were significant for depression
(d=0.63,p= .031), sleep quality (d=0.61,p= .035) and the amount of exercise (d=1.45,p<.001).Acrossbothgroups,
the reduction of global symptom severity was significantly predicted by an increase of exercise (b=.35,p= .012).
Conclusions: The exercise intervention showed transdiagnostic efficacy among a heterogeneous clinical sample in a
realistic outpatient setting and led to sustained exercise behaviour change. Exercise may serve as an efficacious and feasible
transdiagnostic treatment option improving the existing treatment gap within outpatient mental health care settings.
Trial registration: The study was registered on ClinicalTrials.gov (ID: NCT03542396, 25/04/2018).
Keywords: Exercise, Transdiagnostic efficacy, Depression, Anxiety disorders, Insomnia
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* Correspondence: Johannaemail@example.com
Department of Education & Health Research, Faculty of Economics and
Social Sciences, Institute of Sports Science, University of Tuebingen, 72074
Full list of author information is available at the end of the article
Zeibig et al. BMC Psychiatry (2021) 21:313
In 2019, psychiatric disorders affected about 15.6%
(point prevalence) of the population in Germany .
Psychiatric disorders result in a considerable burden of
disease, accounting for 6.4% of disability-adjusted life
years (DALYS)  and increasing the risk for cardiovas-
cular diseases . The most frequent and burdensome
psychiatric disorders are depressive disorders (point
prevalence: 4.3%), anxiety disorders (point prevalence:
7.1%), including obsessive compulsive disorders (OCD)
and posttraumatic-stress disorder (PTSD), and insomnia
(point prevalence: 4%) [1,3]. Epidemiological studies
demonstrated that comorbidity across these disorders is
rather the rule than the exception . Additionally, these
disorders show a comorbidity with other psychiatric dis-
orders, such as attention deficit hyperactivity disorder
(ADHD) . Comorbidity is related to an increased im-
pairment, a worse prognosis and stronger chronicity of
symptoms compared to people affected by one single
mental disorder [6–8]. The high prevalence and burden
of psychiatric disorders as well as their comorbid occur-
rence, emphasize the substantial need for treating psy-
chiatric disorders. However, in Germany, only 10% of all
individuals with psychiatric disorders receive evidence-
based treatment and only 2.5% receive psychotherapy
. Furthermore, in 2018, the average waiting time for
psychotherapeutic treatment was approximately 5
months . The high necessity for treatment, on the
one hand, and deficits in mental health care, on the
other hand, illustrates the severe gap between people in
need for treatment and those actually receiving it .
This treatment gap aggravates the burden of psychiatric
disorders because the absence or delay in treatment can
lead to worsening and chronicity of symptoms and add-
itionally to the development of comorbid diagnoses .
Thus, there is a demand for treatment that can improve
this treatment gap by being applicable and efficacious to
individuals who meet criteria for one or more clinical
diagnoses and also for groups of heterogenous disorders.
In addition, this treatment would need to be easily and
fast accessible (i.e., efficient) to increase the number of
people receiving treatment.
The mental health care is dominated by treatments,
that are tailored to specific disorders (i.e., disorder-
specific treatments)  and are usually conducted in
individual format rather than in group format .
However, considering clinical reality with heterogenous
and also comorbid presentations of diagnoses , the
conduction of those treatments is not efficient because
multiple treatment protocols for different specific
disorders need to be applied . Furthermore,
disorder-specific treatments no longer correspond to
recent evidence supposing that underlying shared com-
mon etiological and maintenance processes rather than
specific diagnoses should be considered when treating
psychiatric disorders [12,14].
To address these underlying mechanisms instead of
specific disorders, transdiagnostic psychological treat-
ments, that “[…] apply the same underlying treatment
principles across mental disorders without tailoring the
protocol to specific diagnoses”(, p.21) have been
developed [27,28,29,30,31]. Recent meta-analyses [27–
31], that evaluated the efficacy of transdiagnostic psycho-
logical treatments, such as transdiagnostic cognitive be-
havior therapy (CBT) , among patients with depressive
disorders and/or anxiety disorders over comparison or
control interventions (i.e., diagnosis-specific intervention
control, treatment-as-usual, or a waitlist control), demon-
strated moderate to large effect sizes. This suggests that
transdiagnostic treatments can efficaciously augment
dominating disorder-specific treatments .
There is a body of evidence assuming that exercise,
defined as physical activity that is planned, structured,
and repetitive, with the primary aim to improve or main-
tain physical fitness  might represent a potential
transdiagnostic treatment for depressive disorders, anx-
iety disorders, insomnia and ADHD. Findings of a recent
meta-analysis  investigating the effects of exercise on
underlying processes of these psychiatric disorders (i.e.,
anxiety sensitivity, distress tolerance, stress reactivity,
and general self-efficacy) revealed a large effect of
exercise on reducing anxiety sensitivity, a moderate ef-
fect on increasing general self-efficacy and a small effect
on reducing stress reactivity. Similarly, a recent meta-
analysis of randomized controlled trials (RCTs) ,
which examined the impact of exercise on sleep quality
among people with psychiatric disorders, revealed a large
beneficial effect on the improvement of sleep quality.
Supporting the assumption of the transdiagnostic effi-
cacy of exercise, results of numerous systematic reviews
and meta-analyses have suggested moderate to large
disorder-specific effects of exercise on depressive disor-
ders [35,36], anxiety disorders [37,38], insomnia [39,
40]andADHD[41,42] over non-active [37,39], or ac-
tive and non-active controls [35,36,38,40,41].
Exercise conducted two to three times per week, for
approximately 10 weeks, at a minimum of moderate in-
tensity and a duration of 30 min, partially supervised or
non-supervised, solely aerobic or aerobic combined with re-
sistance training, are key components of previous disorder-
specific exercise interventions and seem to be associated
with optimal therapeutic efficacy among patients with spe-
cific disorders [33,35,37,43]. These beneficial effects, such
as the reduction of depressive symptoms, seem to be only
sustainable when exercise is conduced and maintained on a
regular base. In an exercise trial , the antidepressant ef-
fect of exercise was compared to those of psychopharma-
cotherapy in patients with depressive disorders. Both
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 2 of 17
conditions showed similar improvements in depressive
symptoms. In the one-year follow up study, however, this
effect was only maintained for those participants who en-
gaged in exercise on a regular base . Exercise interven-
tions combined with behavior change techniques (BCTs),
that increase motivation and volition for exercise seem to
increase the initiation and maintenance of exercise among
healthy and psychiatric samples [46,47,48,49].
Despite of the promising evidence of the efficacy of
exercise among specific disorders and underlying pro-
cesses across disorders, to the best of our knowledge,
the effects of exercise have never been investigated
across a broad range of diagnostically heterogeneous
and a highly comorbid clinical sample in a realistic
outpatient setting. Furthermore, as far as we know,
there is no exercise trial that includes heterogenous
disorders and assessed global symptom severity with a
reliable and clinical measure.
Therefore, the manualized group exercise intervention,
named “ImPuls”, was developed. The intervention
was developed for inactive outpatients, waiting for psy-
chotherapeutic treatment in German health care settings
in outpatient units and practices, suffering from one or
more diagnoses of depressive disorders, anxiety disor-
ders, insomnia, and ADHD. The exercise intervention
integrates the most recent findings about optimal mo-
dalities of exercise for therapeutic efficacy for the
targeted disorders and sustainable behavior change by
integrating behavior change techniques (BCTs). All
components of this intervention are tailored to the care
reality of outpatients with psychiatric disorders to offer
an efficient treatment option in the outpatient mental
health care setting: 1) including a broad range of
heterogenous diagnoses for which prior research has
demonstrated therapeutic efficacy, 2) conducting the
intervention in group format, 3) short duration (i.e., 4
weeks of supervised sessions, 8 weeks non-supervised
exercise) to be feasible during waiting times for
The primary hypothesis was that participants of the
intervention group would demonstrate lower global
symptom severity and disorder-specific symptoms
(depression, anxiety, sleep quality) at post-treatment
assessment compared to a passive control group. The
secondary hypothesis was that participants of the
intervention group would demonstrate a significant
larger amount of exercise at intermediate- and post-
treatment assessment compared to the control group.
It was further hypothesized that the increase of the
amount of exercise from pre- to post-treatment as-
sessment would predict the reduction of global symp-
tom severity and disorder-specific symptoms from
pre- to post-treatment assessment across both treat-
The study was conducted at the University of Tuebingen.
Active enrollment lasted from April 2018 to October
2019. The study was registered on ClinicalTrials.gov (ID:
NCT03542396, 25/04/2018) and approved by the local
ethics committee for psychological research (Az_Wolf_
2018_0108_99). A block-randomized (allocation ratio 1:1)
parallel trial with two treatment arms (intervention group,
control group) and three measurement points (pre-, inter-
mediate-, post-treatment assessment) was conducted. Pri-
mary outcomes were assessed at pre- and post-treatment
assessment; secondary outcome at pre-, intermediate- and
post-treatment assessment. The study was reported ac-
cording to the Consolidated Standards of Reporting Trials
(CONSORT) statement .
Recruitment and participants
Recruiting was performed at the outpatient clinic of the
University of Tuebingen, medical and psychotherapist’s
offices, and by media advertising. Inclusion criteria were
age between 18 and 65 years, fluent in German, no med-
ical contraindications for exercise (participants needed
to receive a medical consultation prior to the interven-
tion that confirmed participant’s ability to exercise), on a
waiting-list for outpatient psychotherapy and diagnosed
according to DSM-IV-TR with at least one of the follow-
ing disorders: depressive disorders (F32, F33, F34.1),
anxiety disorders (F40.0, F40.1, F40.2, F41.0, F41.1,
F41.2, F42, F43.1, insomnia (F51.0), and ADHD (F90.0,
F90.1, F98.8). Exclusion criteria included: acute sub-
stance use disorders (F10.2, F11.2, F12.2, F13.2, F14.2,
F15.2, F16.2, F18.2, F19.2), chronic pain disorder (F45.1),
eating disorders (lifetime; F50), bipolar disorder (lifetime;
F31), antisocial personality disorder (F60.2), borderline
personality disorder (F60.3), acute suicidal tendencies,
regular exercise (≥30 min/week), change (i.e., reduction
and increase) of psychopharmaceuticals (≤2 months).
Any change in treatment led to a withdrawal from the
The sample size was determined a-priori through
power analysis, using G*Power (, v. 184.108.40.206.). A
moderate to large effect (Cohen’sd= 0.74) of the mean
post-difference between the two groups for the primary
outcome was expected. Effect estimation was the median
of the effect of exercise on disorder-specific symptoms
of depressive disorders, anxiety disorders and insomnia.
Since a small number of eligible participants with
ADHD was expected, the effect of exercise on symptoms
of ADHD was not included in the effect estimation.
Effect sizes were derived from the most recent meta-
analyses and RCTs available at the time of trial design
[36,40,53]. With significance level: α= .05, Power: 1-
β= .80, allocation ratio N2/N1: ε= 1, the required
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 3 of 17
sample size for a two-tailed t-test for independent sam-
ples was N= 60. With an expected dropout rate of 18%
for a clinical sample in an RCT , the total sample re-
sulted in N= 71. This resulted in a group size of ap-
proximately n= 36 for each group.
Randomization was performed when the maximum of
participants for one treatment group (n=5–10) was
eligible and/or when remaining waiting time for psycho-
therapy was shorter than intervention period (≤3
months). Participants were assigned a code, which was
sent to a research assistant. They were randomly
assigned to a group, based on a randomization table,
stratified by age and symptom severity (Global Assess-
ment of Functioning Scale, GAF) for each group, using
MATLAB (9.6.0, R2019a). The study therapist received
the allocation information, matched the codes to partici-
pants and informed them of their group allocation.
Psychologists performed a preliminary telephone screen-
ing of eligibility criteria. Eligible participants were invited
to the University of Tuebingen where they first com-
pleted a demographic questionnaire. Research assistants,
who were trained in the conduction of structured clin-
ical interviews, conducted the structured clinical inter-
view for DSM-IV (SCID)  for eligibility criteria.
ADHD was diagnosed by DSM-IV criteria through the
Homburg ADHD Scales for Adults (HASE) . Primary
insomnia was diagnosed by DSM-IV criteria combined
with the Pittsburgh Sleep Quality Index (PSQI) .
Participants signed an informed consent form and com-
pleted online questionnaires via a secure online survey
software Sosci Survey  prior to randomization. This
pre-treatment assessment was conducted on an average
of 23.15 days (SD = 22.19) prior to the start of the
Ten groups of five-to-ten participants were sequen-
tially allocated to the intervention group or control
group. The intervention group completed the exercise
intervention, while the control group did not receive any
treatment. At week 9 of the intervention (intermediate-
treatment assessment), participants’amount of exercise
was assessed. No other assessments were conducted at
this assessment point. Intermediate-treatment assess-
ment was scheduled at week 9 of the intervention
because it was middle of the non-supervised time. The
non-supervised intervention period started at week 5 of
the intervention and lasted 8 weeks in total.
One-to-two weeks after intervention (post-treatment
assessment), the same procedure of the pre-treatment as-
sessment was performed. The SCID was also conducted
again at post-treatment assessment by an outcome
assessor (research assistants, who were trained in the
conduction of structured clinical interviews) that was
blind to group assignment. Afterwards, the control
group received 50€as a compensation for their time. All
participants were offered preferential psychotherapy at
the outpatient clinic in Tuebingen after post-treatment
assessment. The final post-treatment assessment was
conducted in October 2019.
Global symptom severity Global symptom severity was
measured by the Global Severity Index (GSI) of the
German version of the self-reported questionnaire
Symptom Checklist-90-Revised (SCL-90-R ;). The
GSI comprises the average distress rating on all symp-
tom scales and ranges from 0 to 4. Higher scores indi-
cate higher distress. Clinically relevant changes are
defined as a change on the GSI of at least 0.26 .
Among patients with affective disorders, the GSI has
demonstrated good internal consistency (α= .97) and
construct validity (r= .77) . The internal consistency
in the current study was α= .97 for the GSI.
Depression and anxiety Depression and Anxiety were
measured by the sub scores Depression and Anxiety of
the self-reported questionnaire SCL-90-R . Items of
the depression sub score ask participants for symptoms
of depression (e.g., “How much did you suffer from a de-
crease in your interest or pleasure in sexuality in the
past few days?”) and items of the anxiety sub score for
symptoms of anxiety (e.g., “How much did you suffer
from nervousness or inner trembling in the past days?”).
Scales ranges from 0 to 4 with higher scores indicating
higher distress. Symptoms are clinically raised when T-
values are ≥60. Among patients with affective disorders,
the depression scale (α= .89) and anxiety scale (α= .87)
have demonstrated internal consistency and construct
validity (r= .80 for depression and r= .61 for anxiety)
. The internal consistency in the current study was
α= .91 for depression and α= .90 for anxiety.
Sleep quality Sleep Quality was measured by the global
sleep quality score of the German version of the self-
reported questionnaire Pittburgh Sleep Quality Index
(PSQI ;). The global sleep quality score is the sum of
seven sleep component scores (range of component
scores: 0–3): subjective sleep quality (“Over the last four
weeks, how would you rate your overall sleep quality?”),
sleep latency (e.g., “Over the last four weeks, how long
have had it usually take you to fall asleep at night?),
sleep duration (e.g., “Over the last four weeks, how many
hours have you actually slet per night?”), habitual sleep
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 4 of 17
efficiency (e.g., “Over the last four weeks, what time have
you usually gotten up in the morning?”), sleep distur-
bances (e.g., “Over the last four weeks, how often have
you had a bad night’s sleep because you couldn’t fall
asleep within 30 minutes?”), use of sleeping medications
(e.g., “Over the last four weeks, how often have you
taken sleeping pills (prescribed by a doctor or over-the-
counter)?”), and daytime dysfunction (e.g., “Over the last
four weeks, how often have you had difficulty staying
awake, such as while driving, eating, or attending social
events?”). The global sleep quality score can vary from 0
to 21 with a cut-off score of 5, identifying clinically
raised sleep impairment . It has shown a high sensi-
tivity (98.7%) and specificity (84.4%) in identifying in-
somnia . In the literature, the internal consistency
for the global sleep quality score was α= .77 . In the
current study, it was α= .67.
Secondary outcome: exercise
The amount of exercise was measured using the self-
reported exercise activity index of the physical activity,
exercise, and sport questionnaire (BSA questionnaire
;). Participants specify whether they have engaged in
regular exercise in the past 4 weeks (“Have you engaged
in regular exercise in the past 4 weeks?”). If they have
engaged in regular exercise, participants were asked to
specify the type (“What kind of exercise activity (ies)
have you engaged in?”), frequency and duration (“I have
engaged in activity x approximately …times in the past
four weeks, every time for approximately …minutes”)of
it. The exercise activity index indicates the average
minutes of exercise per week. The BSA questionnaire
can validly assess changes in exercise behavior. Data of
reliability is not available  and could not be analyzed
for the current study it because this scale consists of one
Further measures (self-reported questionnaires),
described in the trial registration, but not included in
the current evaluation, were the Sleep Questionnaire B-
Revised version (SF-B ;), Perceived Stress Scale (PSS
;), 36-Item Short Form Health Survey (SF-36) (SF-36
;), Self Concordance of Sport- and Exercise-related
Goals Scale (SKK-Scale ;), Scales that assess motiv-
ation and volition for exercise , and Physical
Activity-related Health Competence Questionnaire .
Accelerometer derived exercise at seven consecutive
days was assessed. 5-min resting heart rate variability
was assessed by a trained research assistant.
The 12-week exercise intervention “ImPuls” was
conducted in a group format of three to four
participants and divided into a supervised and non-
supervised period. Behaviour change techniques (BCTs),
such as self-efficacy, goal setting, self-monitoring, forma-
tion of concrete exercise plans and coping planning,
were integrated to promote sustained exercise behaviour
change [49,70]. Intervention contents are displayed in
Fig. 1and Table 1.
Supervised period (week 0–4)
Participants took part in a combination of supervised
running session and group meetings with a total dur-
ation of 120 min. One supervised session is conducted
during week 0 (introduction to the intervention), three
supervised sessions during the second week, two super-
vised sessions plus one non-supervised exercise during
week 2–4, respectively. Running lasted 30 min and
participants could choose a standardized interval-based
training or endurance training. Both training methods
were conducted with moderate intensity, which was
tracked by a heart rate monitor (Polar Electro GmbH; A
300) combined with a chest strap (Polar Electro GmbH;
H7) and the Borg Rating of Perceived Exertion (RPE)
Scale . Moderate intensity was defined as 60 to 80%
of maximum heart rate, subtracting age from 220 
and from nine to 14 on the RPE Scale . Participants
engaged in additional 30-min, moderate-intensity, non-
Non-supervised period (week 5–12)
During the non-supervised period, participants engaged
in 30-min, moderate-intensity, non-supervised exercise
two to three times a week, which was accompanied by
an activity diary and weekly phone calls with one study
therapist, intending to maintain motivation, volition, and
adherence to exercise. A session for participant’s
supporters (e.g., friends, partner) was scheduled in week
5 to inform them about the possibilities to aid the par-
ticipants in transforming their intentions into action. A
final group meeting with a running session took place in
week 12 in order to exchange experiences and to en-
courage participants to maintain regular exercising.
Attendance and adherence
Participants performed 30 min non-supervised exercise if
they missed a supervised running session. Contents of
group meetings were repeated in one-to-one sessions
(by phone or face-to-face). The assessment of the
amount of exercise (see Procedure) served as a measure
of adherence during the non-supervised period (see
All main therapists were master’s degree psychologists
with either fully approved in psychological
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 5 of 17
psychotherapy or in advanced postgraduate training for
CBT. Assistant therapists were graduate students of
psychology. All therapists were trained in the back-
ground and contents of ImPuls und supervised by an ex-
ercise therapist and a psychotherapist.
Potential risks and benefits of the intervention
Most common risks associated with exercise are cardio-
vascular events and musculoskeletal injuries . Inter-
mediate and long-term potential benefits of exercise are
improved physical health, such as prevention of diabetes
(e.g., ) and improved mental health, such as the
reduction of depressive symptoms (e.g., ). Further-
more, majority of individuals are exposed to greater risk
by not exercising. Indeed, sedentary behavior seem to be
associated with a higher risk to develop mental disorders
[76,77] and reduced physical health . Since all par-
ticipants of the current intervention needed to receive a
medical consultation prior to the intervention, the po-
tential risk of exercise on physical health was minimized.
Therefore, potential benefits seemed to outweighs the
risks of participation in the study.
Individuals from both study arms, who fulfilled any
exclusion criteria (i.e., change of treatment, contraindica-
tions for exercise) during the intervention, were ex-
cluded from post-data collection, 18.1% (n= 13). Since
the current study contained exclusion criteria that could
change during study participation (e.g., change of treat-
ment), data from participants, who did no longer meet
eligibility criteria needed to be excluded from post-data
collection in order to reduce the risk of bias in the inter-
vention effect estimate . Missing data was assessed at
Fig. 1 Intervention procedure of the group exercise intervention. Dark grey boxes represent group meetings combined with supervised aerobic
exercise (starting session 3) and the supporters’session (session 14 in week 5). Session 1 contains an introduction into the intervention. Session 15 is
conducted in week 12. Light grey boxes represent non-supervised exercises or resistance training, which can be conducted as participants’first non-
supervised exercise (session 6). The phone represents the weekly phone contact from week 5–12. Week 1–2 mainly aimed to increase motivation,
week 2–4 mainly increase volition. Week 5–12 aimed to transfer motivation and volition for exercise into participants’daily life routines
Table 1 Overview of behaviour change techniques of the
group exercise intervention
Education about positive and negative
effects of exercise
Education about optimal modalities of
exercise to experience positive psychological
Selection of a preferred activity
Self-monitoring of goal achievement
Reflection about positive experiences/effects
Volitional (mainly week
Identification of barriers to exercise
Techniques to overcome barriers
Social support (intervention group and
Exercise self-monitoring (optimal modality)
volitional (week 5–12)
Social support (family, friends, trainer)
Self-monitoring of goal achievement
Exercise self-monitoring (optimal modality)
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 6 of 17
scale level. Linear mixed models, using maximum likeli-
hood estimations, were conducted to handle missing
data (also participants’data of those who were excluded
from post-data-collection). Linear mixed models, based
on all observed data, can be a valid and unbiased
method to handle data that is missing at random .
Potential outliers were identified through three mea-
sures: Leverage, Cook’s Distance, and Studentized Resid-
uals. Cases with greater than three time the average
leverage, cook’s distance greater than 1, and studentized
residuals greater than 3 [81,82], were considered as po-
tential outliers or influential data points. To evaluate the
influence of potential outliers on results of linear mixed
models, they were calculated again without cases that ei-
ther exceeded the cut-off value of all three measures, or
exceeded the cut-off values of cook’s distance and lever-
age, or exceeded the cut-off value of cook’s distance.
Post-difference and interaction-effect sizes were then
compared to those of linear mixed models including the
complete data set.
Assumptions of linear mixed models and linear regres-
sions (i.e., linearity, normality of the residuals, homosce-
dasticity, and multicollinearity) were visually inspected.
If residuals of linear mixed models were not normally
distributed, data was log-transformed.
For data preparation the Statistical Package for Social
Science (IBM SPSS, Inc., Chicago, IL, USA, version 26)
was used. Statistical analyses were carried out using R
(version 4.0.3) and RStudio (version 1.1.453). Descriptive
statistics were used to analyze sample characteristics and
dropout rates. Baseline differences between groups and
between those that completed the study versus dropped
out were analyzed using two-tailed t-tests for independ-
ent samples (continuous variables), Chi-scared tests or
fisher’s exact tests (categorical variables).
Differences between groups on primary and secondary
outcomes changes were analyzed as intention-to-treat
(ITT) analysis with linear mixed models using the lme4
package  in R. Models used maximum likelihood as
the estimation technique. Models included treatment
group,time point and time point-by-treatment group
interaction as fixed effects. Intercepts were included as
random effects. An unstructured covariance matrix
was assumed. Post-hoc tests for post-treatment-
differences between groups were carried out using
two-tailed t-test for independent samples. For post-hoc
tests of the secondary outcome, a Bonferroni correc-
tion was used. Effect sizes for differences between
groups (intermediate-, post-treatment-difference ef-
fects and interaction effects) were calculated according
An additional analysis inspected clinically relevant
changes of participants’symptomatology. Clinically rele-
vant changes were defined as a change on the GSI from
pre-treatment to post-treatment assessment of at least
Sufficient statistical power enabled exploratory ana-
lyses that examined the efficacy of exercise on depres-
sion for subgroups of participants diagnosed with
depressive disorders. Additional exploratory analysis
(per-protocol analysis) tested the predictive value of the
change of the amount of exercise on primary outcomes
changes. Linear regressions were calculated with change
of exercise (post-treatment assessment –pre-treatment
assessment) as a predictor variable and primary out-
comes changes (pre-treatment assessment –post-
treatment assessment) as criterion variables.
Participant flow during the study
In total, 106 individuals were assessed for eligibility.
Of those assessed, 30.2% (n= 32) were excluded and
69.8% (n= 74) were eligible for participation. Those
eligible were randomly assigned to the intervention
group, 51.3% (n= 38), or control group, 48.7% (n=
36). 5.3% (n= 2) of participants of the intervention
group were removed from the analysis due to a
wrong diagnosis at pre-treatment assessment (comor-
bid lifetime eating disorder, 2.6% (n= 1), and a co-
morbid alcohol use disorder, 2.6% (n=1) . This
led to an ITT efficacy group of N= 72 (50.0% (n=36)
of patients in the intervention group vs. 50.0% (n=
36) in the control group) (see Fig. 2).
Participant characteristics at baseline
Baseline characteristics of the studied sample are reported
in Table 2. There were no significant baseline differences
between intervention group and control group. Dropout
rates of the control group were higher compared to the
intervention group, but not statistically different. Com-
pared to the intervention group, participants of the con-
trol group dropped out more frequently due to treatment
change without reaching statistical significance (see
Table 2and Fig. 2). There were no significant baseline
differences between study completers and dropouts
(Additional file 1). There were no serious adverse events.
Statistics and data analysis
Missing data was missing completely at random
(14) = 12.33, p= .580). 106 (14.7%) values of
primary and secondary outcomes were incomplete. Per-
protocol analyses for each primary and secondary
outcome were conducted as sensitivity analyses, using
linear mixed models (Additional file 2), to examine
the robustness of the results.
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 7 of 17
Ten cases were detected as potential outliers in the
linear mixed model with the GSI (SCL-90-R) as criterion
variable and four cases in the linear mixed model with
the global sleep quality score (PSQI) as criterion vari-
able. No cases were detected as potential outliers in the
mixed models with exercise (BSA questionnaire) as cri-
terion variable. Excluding potential outliers did not
change direction, nor significance of intervention effects
(Additional file 4). Intervention effects on the global
sleep quality score increased from moderate to large
effect size (cohen’s d for post-treatment-difference be-
tween groups) when potential outliers were excluded.
Therefore, potential outliers were not excluded from
Efficacy of the intervention
Results of all primary and secondary outcomes and sub-
group analysis, including effect sizes, are presented in
Fig. 2 CONSORT flow diagram: profile and enrollment and flow through the randomized controlled trial of group exercise intervention versus a
passive control group for individuals with mental disorders
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 8 of 17
Table 3. The interaction effect of group by time was sig-
nificant for global symptom severity, F(1, 53) = 7.93, p=
.007, 95%CI[−0.50,- 0.08], depression, F(1, 55) = 6.30,
p= .015, 95%CI[−0.82, −0.09], anxiety, F(1, 54) = 10.12,
p= .002, 95%CI[−0.36, −0.08], and sleep quality, F(1,
58) = 11.24, p= .001, 95%CI[−4.68, −1.19], with larger
decreases in the intervention group. Post-treatment
difference effects were significant for depression, t
Table 2 Baseline demographic and clinical characteristics of participants
Intervention Group Control Group Intervention Group
Compared With Control
Group (N= 72)
(N= 36) (N= 36)
Measure N % N % χ
Female 25 69.4 27 75.0 0.28 1 .599
Married or partnered 25 69.4 24 66.7 0.06 1 .801
High school 31 86.1 25 69.4 2.89 1 .089
33 94.3 31 88.6 .673
Depressive disorders (single)
13 36.1 11 30.6
Depressive disorders (comorbid with
10 27.8 13 36.1
Panic disorder 2 5.6 2 5.6
Social anxiety disorder 2 5.6 2 5.6
Specific anxiety disorder 2 5.6 0 0.0
Generalized anxiety disorder 1 2.8 0 0.0
Agoraphobia 1 2.8 1 2.8
Obsessive-compulsive disorder 0 0.0 0 0.0
Obsessive-compulsive disorder and
social anxiety disorder
0 0.0 2 5.6
Post-traumatic stress disorder 1 2.8 2 5.6
Primary insomnia 3 8.3 3 8.3
Attention deficit hyperactivity disorder 1 2.8 0 0.0
Clinically raised symptoms (SCL-90-R, PSQI) 36 100.0 34 94.1 .493
21 58.3 17 47.2 0.89 1 .345
Receiving psychiatric drugs
18 50.0 20 57.1 0.36 1 .546
Dropout 7 19.4 14 38.9 3.29 1 .070
3 8.3 9 25.0 .111
Mean SD Mean SD t df p
Age (years) 37.33 14.23 34.33 12.39 0.95 68.69 .343
Global Severity Index (SCL-90-R) 1.06 0.63 1.02 0.61 0.27 69.91 .790
Sleep Quality (PSQI)
9.67 3.66 8.62 3.15 1.28 68.04 .204
Latency pre-treatment –initiation (days) 21.94 17.21 24.36 26.44 −0.46 60.15 .648
Note.SCL-90-R Symptom Checklist-90-Revised, PSQI Pittsburgh Sleep Quality Index
For employment, the number of participants was n= 35 for the intervention group and n= 35 for the control group because of incomplete data at
Depressive disorders (single) includes all participants diagnosed with a single depressive disorder.
Depressive disorders (comorbid with anxiety disorders) includes all participants diagnosed with depressive disorder and comorbid anxiety disorders.
Depression and anxiety levels were classified as clinically raised when t-values of the sub-scales depression and anxiety of the SCL-90-R were greater or equal to
60 (reference group: healthy men, aged between 35 and 44).
Symptoms of insomnia were classified as clinically raised when the cut-off value of five of the total sum score of the PSQI were reached. For clinically raised
symptoms and sleep quality, the number of participants was 36 for the intervention group and 35 for the control group because of incomplete data at pre-
treatment assessment on the PSQI.
For receiving psychiatric drugs, the number of participants was n= 36 for the intervention group and n= 35 for the control group because of incomplete data at
Treatment change is defined as the start of psychotherapy, inpatient treatment or psychopharmacological change.
Fisher’s exact test was used as a replacement for the chi-square test because the frequency of one or more cells was less than 5
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 9 of 17
(114) = 2.18, p= .031, and sleep quality, t(121) = 2.13,
p= .035, with lower scores in the intervention group.
Post-treatment difference effects for global symptom
severity, t(105) = 1.68, p= .096, and anxiety, t(110) =
1.88, p= .063, were moderate, with lower scores in the
intervention group, without reaching significance.
The interaction effect of group by time was significant
for the mean amount of exercise, F(2, 115) = 16.50,
p< .001, 95%CI [1.41, 3.61], with larger increases in the
intervention group. Bonferroni-corrected intermediate-
treatment difference effect, t(167) = −5.83, p< .001, and
post-treatment difference effect, t(170) = −5.04, p< .001,
were significant, with higher scores in the intervention
Compared to participants of the control group, more
participants of the intervention group revealed clinically
significant changes of symptomatology, without reaching
statistical significance (χ
(1) = 3.61, p= .058.
In a subgroup of participants with depressive
disorders, the interaction effect was significant for
depression, F(1, 37.48) = 5.74, p= .022, 95%CI[−1.01,
−0.09], with larger decreases in the intervention
group. The Post-treatment difference in this subgroup
was significant, t(75) = 2.75, p= .008, with lower
scores in the intervention group (see Table 3). Across
both groups, the change of the mean amount of
exercise from pre- to post-treatment assessment
significantly predicted the change of global symptom
severity, b= .35, t(49) = 2.61, p= .012]. Predictions
Table 3 Marginal means, confidence intervals, effect sizes, and results of linear mixed models analyses
Change from Baseline in
Compared With Control
Group (N= 72)
Measure and Assessment Point Mean SD 95% CI Mean SD 95% CI d
B 95% CI d
Global Severity Index (SCL-90-R) −0.30 −0.50,-0.08 0.77**
Pre-treatment 1.06 0.59 0.87,1.26 1.02 0.59 0.83,1.22
Post-treatment 0.67 0.55 0.47,0.87 0.93 0.51 0.71,1.14 0.48
Depression (SCL-90-R) −0.46 −0.82,-0.09 0.68*
Pre-treatment 1.57 0.85 1.29,1.85 1.60 0.85 1.32,1.88
Post-treatment 0.94 0.80 0.65,1.24 1.43 0.76 1.11,1.76 0.63*
−0.22 −0.36,-0.08 0.87**
Pre-treatment 0.60 0.35 0.49,0.72 0.56 0.35 0.44,0.67
Post-treatment 0.36 0.33 0.24,0.48 0.53 0.31 0.40,0.67 0.53
Sleep Quality (PSQI) −2.94 −4.68,-1.19 0.88**
Pre-treatment 9.67 3.31 8.57,10.76 8.67 3.29 7.57,9.77
Post-treatment 6.47 3.21 5.29,7.65 8.41 3.12 7.09,9.73 0.61*
Exercise (BSA questionnaire)
2.51 1.41,3.61 0.82***
Pre-treatment 1.82 1.82 1.22,2.42 1.72 1.82 1.12,2.33
week 9 4.68 1.80 4.00,5.35 1.74 1.79 1.04,2.45 1.64***
Post-treatment 4.12 1.80 3.46,4.78 1.53 1.77 0.78,2.27 1.45***
Exploratory Analysis (N= 47)
Change from Baseline in
Compared With Control
Group (N= 47)
Depression (single and with comorbid
anxiety disorders) (SCL-90-R)
−0.55 −1.01,−0.09 0.78*
Pre-treatment 1.84 0.79 1.51,2.17 2.00 0.78 1.68,2.32
Post-treatment 1.10 0.77 0.77,1.44 1.81 0.71 1.42,2.20 0.95**
Note.SCL-90-R Symptom Checklist-90-Revised, PSQI Pittsburgh Sleep Quality Index, BSA questionnaire Exercise Activity Index of the Physical Activity, Exercise, and
Cohen’s d for post- and intermediate-treatment effect.
Cohen’s d for the interaction effect.
Log-transformed data due to a skewed data distribution.
Participants with depression with and without comorbidities.
*p< .05. ** p< .01. ***p< .001
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 10 of 17
disorder-specific symptoms across both groups and
for each group are displayed in Additional file 3.
This RCT compared a group exercise intervention with
a passive control group among 72 inactive outpatients,
suffering from one or more diagnoses of depressive
disorders, anxiety disorders, insomnia, and ADHD.
Compared to the control group, the intervention was
efficacious in improving global symptom severity, de-
pression, anxiety and sleep quality as well as the amount
of exercise with moderate to large effect sizes. Post-
treatment difference effects were moderate to large on
depression, sleep quality and the amount of exercise.
Among participants diagnosed with depressive disorders,
the antidepressant effect of the exercise intervention was
larger compared to the entire mixed sample. Across both
groups, an increase in the amount of exercise predicted
the reduction of global symptom severity, indicating that
those patients who engaged in more exercise showed de-
creased symptom severity.
Efficacy of the intervention
Beneficial effects of the intervention on global symptom
severity suggest that the exercise intervention
efficaciously reduced symptoms across the included
heterogenous sample. On the one hand, there are few
studies that investigated the efficacy of exercise among
outpatients with heterogenous psychiatric diagnoses
. On the other hand, the few existing studies
assessed physical health, rather than mental health as
primary outcomes . Two RCTs assessed quality of
life  and general mental health  as secondary
outcome. Their results suggested improvements on qual-
ity of life (i.e., physical function score, social function,
emotional role)  but not on general mental health
(i.e., psychological distress and well-being) . To the
best of our knowledge, there exists no study investigat-
ing the effects of exercise among a sample with
heterogenous diagnoses that include a clinical valid and
reliable measure to assess global symptom severity.
Whereas the intervention group revealed stronger im-
provements on global symptom severity, compared to
the control group, the post-treatment effect between
both groups was not significant. Since sample size calcu-
lation was based on large effects of exercise on disorder-
specific symptoms among included disorders, power
might have been to small to detect treatment effects on
global symptom severity across disorders at post-
Interaction effects of the current intervention on glo-
bal symptom severity are similar to those of recent
meta-analyses [27,28,29,30,31], evaluating the efficacy
of transdiagnostic psychological treatments among pa-
tients with depressive disorders and/or anxiety disorders
over comparison or control interventions (i.e., diagnosis-
specific intervention control, treatment-as-usual, or a
waitlist control). Results of these previous studies re-
vealed moderate to large effects on clinical measures
assessing symptom severity across included disorders
(i.e., depression-anxiety scales, quality of life).
Supporting the assumption of the transdiagnostic effi-
cacy of the intervention, our results demonstrated that
the intervention improved one underlying process across
included disorders with large effect size: poor sleep
quality [21,22]. This result is similar to a recent meta-
analysis of RCTs  which demonstrated large benefi-
cial effect of exercise on sleep quality among people with
various psychiatric disorders. Nonetheless, the analysis
included primarily RCTs assessing the effects of exercise
on sleep quality among study samples with specific diag-
noses. Only one RCT  included participants with a
primary diagnosis of a depressive disorder with and
without comorbid anxiety disorders. Similarly, another
recent meta-analysis  that investigated the effects of
exercise on various underlying processes across psychi-
atric disorders, mostly included participants with specific
diagnoses or even non-clinical samples. Thus, the
findings of our study therefore expand on the results of
recent meta-analyses by demonstrating effects on one
underlying process across a clinical sample with
heterogenous psychiatric disorders.
Correspondingly, our results suggest disorder-specific
efficacy by improving symptoms of depression, anxiety
and insomnia. The moderate antidepressant effect of the
intervention at post-treatment assessment is smaller
compared to prior meta-analytical findings suggesting a
large antidepressant effect of exercise, over non-active
controls . In contrast to our study, prior studies in-
cluded samples with a primary diagnosis of a depressive
disorder only . Although the large antidepressant ef-
fect among patients with a primary depressive disorder
have been consistently demonstrated in prior studies
[35,36], to the best of our knowledge, the antidepressant
effect of exercise among anxiety disorders, insomnia,
and ADHD has not been investigated yet. When analyz-
ing the antidepressant efficacy of our exercise interven-
tion among the subsample with a primary diagnosis of a
depressive disorder, the effect size is comparable to prior
studies . The mean change of anxiety symptoms
among the intervention group across the entire mixed
sample was large, compared to the control group. Prior
exercise trials have reported moderate interaction effects
of exercise on anxiety symptoms among patients with
anxiety disorders, over non-active controls . This re-
sult may suggest that the current exercise intervention
might have been more efficacious in reducing anxiety
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 11 of 17
across heterogenous disorders than prior exercise trials
that included only anxiety disorders . However, this
assumption needs to be considered with caution due to
different sample characteristics and exercise modalities.
The post-treatment difference effect between the
intervention group and control group on anxiety was
not statistically significant. As stated above, the power
analysis was based on the median effect size for
disorder-specific effects of exercise across depressive dis-
orders, anxiety disorders, and insomnia. Beneficial effects
of exercise on anxiety seem to be smaller than those for
depression  and insomnia symptoms . Further-
more, it appears that effect sizes differ across different
anxiety disorders . Therefore, the a-priori deter-
mined sample size might have been underestimated to
detect treatment effects on anxiety across the
heterogenous sample. The large post-treatment effect of
exercise on sleep quality among the intervention group,
compared to the control group, is comparable to prior
meta-analytical findings investigating the effect of
exercise on sleep quality in patients with insomnia, over
non-active controls . In comparison to meta-
analytical findings investigating disorder-specific effects
of CBT, over non-active controls, our results showed
similar efficacy for depression among depressed partici-
pants  and sleep quality among the entire mixed
The efficacy on global symptom severity and under-
lying mechanisms across the sample as well as
disorder-specific efficacy of the current exercise inter-
vention, suggests that exercise might be able treat a
broad range of heterogenous diagnoses with and with-
out comorbidities. Our study results further suggest,
that exercise interventions do not necessarily be tai-
lored to a specific psychiatric disorder referring to ex-
ercise modalities (i.e., type, frequency) to efficaciously
treat disorder-specific symptoms or underlying pro-
cesses across disorders. Rather, exercise modalities,
that have shown therapeutic efficacy among single
psychiatric disorders (i.e., two to three times per
week, for 10 weeks, at a minimum of moderate inten-
sity and a duration of 30 min, partially supervised or
non-supervised, solely aerobic or aerobic combined
with resistance training [33,35,37,43]) seem to be
adoptable to the treatment of heterogenous diagnoses
with and without comorbidities. Similar to the effi-
cacy of transdiagnostic psychological interventions,
this may result in a faster and easier dissemination,
compared to disorder-specific treatments, because
there is no need to learn and apply multiple treat-
ment protocols for different specific disorders .
Thus, exercise interventions may improve the existing
treatment gap in mental health care  by offering
an efficacious and effective treatment.
Effects on exercise behavior
Study results demonstrated that the current exercise
intervention was highly efficacious in increasing the
amount of exercise, even when participants were not su-
pervised. This is in line with a recent systematic review
 and Editorial , suggesting that exercise interven-
tions, combined with BCTs, are efficacious in increasing
the amount of exercise. To date, there are only a few ex-
ercise interventions for individuals with psychiatric dis-
orders integrating BCTs [46,85] and only approximately
one quarter of those seem to efficaciously increasing
participant’s amount of exercise . The frequent fail-
ure to increase exercise behavior among patients with
psychiatric disorders may be related to a lack of motiv-
ation and exercise-related self-regulatory skills (i.e., vol-
ition) in this population . A large proportion of
outpatients in Germany do not exercise on a regular
base . Thus, the integrated BCTs in our intervention
seem to be adequately tailored to outpatients to improve
their deficiencies in motivation and volition regarding
Results of our explorative analyses demonstrated a
prediction of symptom reduction by an increase of the
performed amount of exercise, indicating that the
change of exercise might indeed be one specific mode of
action of the therapeutic effects. This moderation effect
is often assumed in the exercise literature, however only
very few trials do report such effects. As far as we know,
only one of the recently published high quality RCTs
 did show changes of exercise as the specific mode
of action of the effects of exercise interventions. In
addition to the increase of exercise, results suggest also a
maintenance of exercise behavior because participants
were still exercising even when they were not supervised.
Since there is a lack of follow-up studies of exercise in-
terventions or an absence of measures for exercise be-
havior, little is known about the maintenance of exercise
behavior due to the conduction of exercise interventions
combined or without BCTs . As mentioned in the
introduction, beneficial effects of exercise seem to be
maintained only when exercise behavior has changed
sustainably . Since participants were still exercising
during the non-supervised period of the intervention,
participants might have integrated regular exercise into
their daily life routines. Since the amount of exercise
was assessed 5 weeks and 2 months after the supervised
period, no general conclusions can be drawn about the
long-lasting exercise behavior.
Feasibility of the intervention
Results of this study not only suggest efficacy of the
current exercise intervention but also its feasibility in a
realistic outpatient setting. First, the study sample
included a realistic outpatient sample, waiting for
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 12 of 17
psychotherapeutic treatment, with heterogenous, highly
prevalent psychiatric disorders with and without comor-
bid diagnoses. Second, approximately half of the partici-
pants of the intervention group revealed clinically
relevant changes of global symptom severity, compared
to less than one quarter of the control group. Third, the
dropout quote among participants of the intervention
group was low. Additionally, only 5.2% (n= 2) of the
intervention group dropped out due to lost to follow up.
Hence, a strong acceptance and few adherence issues re-
garding the intervention can be assumed. The dropout
rate is similar to prior exercise interventions [38,93] and
lower than other health behaviour change interventions
(e.g., exercise, health education) for individuals with psy-
chiatric disorders, in which the medium average dropout
rate was 45% . The current dropout rate was lower
than those of individual and group CBT interventions (35%).
Most dropouts were reported in outpatient settings .
The lower dropout rate in the current exercise intervention
over CBT, might suggest equivalent acceptance of exercise
than CBT among outpatients. Forth, the latency between
pre-treatment assessment and initiation of the intervention
was low, compared to waiting times for psychotherapy of
approximately 5 months in Germany . As stated in the
introduction, prolonged waiting times for treatment are as-
sociated with worsening and chronicity of symptoms and
the development of comorbid diagnoses. Consequently, the
current intervention could be conducted to improve nega-
tive consequences of delayed treatment in Germany. Lastly,
in comparison to an average duration of 19 weeks of prior
exercise intervention for patients with psychiatric disorders
, the current exercise intervention was short (12 weeks),
including a very short supervised period of 4 weeks. The
total number of 12 supervised sessions is equivalent to the
average treatment duration of CBT among depressive disor-
ders and anxiety disorders [97,98].
Hence, in addition to the suggested transdiagnostic
and disorder-specific efficacy of the intervention, current
results demonstrated that the exercise intervention
might be feasible treatment among outpatients, that
were waiting for psychotherapeutic treatment in German
health care settings in outpatient units and practices.
One limitation of the current study is the use of a pas-
sive control group, which does not allow to control for
non-specific effects of therapy, such as relationship
building or social support. However, the results of our
explorative analyses demonstrated a prediction of symp-
tom reduction by an increase of the performed amount
of exercise, indicating that the change of exercise might
indeed be one specific mode of action of the therapeutic
effects. Second, the measure for global symptom severity
symptoms was comprised of symptoms that were not
characteristic for all included disorders (e.g., aggression).
Therefore, the validity of this metric to assess global
symptom severity among the current sample is disput-
able. However, the GSI is a reliable and valid instrument
to assess clinical global symptom severity across
heterogenous psychiatric disorders and allows to rate
clinically relevant changes of symptomatology .
Therefore, the use of this measure was reasonable in this
study because of the inclusion of heterogenous and
highly comorbid psychiatric disorders. Furthermore, the
internationally widespread use of this measure  al-
lows to compare study results with international publica-
tions on the effect of various treatments on symptom
severity. Third, eligibility criteria of the current study
allowed for a wide age range. However, participants had
a low average age, which might limit the generalizability
of results to older individuals. Large standard deviations
around the mean value, a large age range (19–63 years)
of the current sample as well as a similar average age of
prior exercise trials  might increase the generalizability
of results to older individuals. Forth, although the SCID
was conducted at pre-treatment and post-treatment as-
sessment, we did not include results of the SCID from
post-treatment assessment in our analyses. We intended
to assess clinically relevant changes of symptomatology. If
a diagnosis, that was present at pre-treatment assessment,
had still been present at post-treatment assessment, rele-
vant changes on symptomatology would not have been
able to assess. Therefore, we considered self-reported out-
comes (GSI of the SCL-90-R) as a more valid measure to
assess clinically relevant changes of symptomatology.
Moreover, one eligible participant could meet multiple in-
clusion diagnoses. Thus, the comparison of the number of
inclusion diagnoses between pre-treatment and post-
treatment assessment did not seem as a valid indicator of
treatment responders vs. non-responders. Alternative in-
dicators of treatment responders vs. non-responders,
resulting from analyses of the SCID (e.g., counting of
symptom criteria for depressive disorders) seem to be an
arbitrary and not valid approach.
First, the high methodological standard is an important
strength of the study. The study involved an RCT design
with stratified block-randomization, which is considered
as the gold standard to evaluate intervention efficacy
. Equal treatment arms and allocation maximized
internal validity . Strict inclusion and exclusion cri-
teria controlled for factors that may obfuscate outcome
measures . Second, the inclusion of a heteroge-
neous sample with a broad age range and various psychi-
atric disorders allowed for a high generalizability of the
results. The conduction of the intervention in a realistic
outpatient setting, the large number of included patients
Zeibig et al. BMC Psychiatry (2021) 21:313 Page 13 of 17
with severe, clinically raised symptoms and comorbid
presentations of psychiatric disorders suggest a valid
representation of the clinical reality .
In conclusion, our findings suggest the transdiagnostic
efficacy of exercise across heterogenous psychiatric dis-
orders with comparable effects to transdiagnostic psy-
chological interventions. The transdiagnostic efficacy of
the group exercise intervention “ImPuls”, tailored to and
conducted with heterogenous psychiatric disorders, is
comparable to disorder-specific exercise interventions or
established treatments, such as CBT. The increase of
exercise behavior seemed to be responsible for the thera-
peutic effects of the intervention. The low dropout rate,
the short latency from first meeting to intervention initi-
ation, the small number of supervised sessions, and the
successful increase and maintenance of exercise by
integrating BCTs, may indicate a high feasibility and
acceptance of the current exercise intervention. Due to
the transdiagnostic efficacy and its feasibility within a
real-world outpatient setting, the current exercise inter-
vention may represent a treatment option that could im-
prove the existing treatment gap in the outpatient
mental health care in Germany. Future research is re-
quired to replicate findings with an active control condi-
tion, among older individuals, and additional measures
of global symptom severity. A follow-up study will allow
to assess the maintenance of treatment effects.
DALYS: Disability-adjusted life years; OCD: Obsessive compulsive disorders;
PTSD: Posttraumatic-stress disorder; ADHD: Attention deficit hyperactivity
disorder; CBT: Cognitive behavioural therapy; RCT: Randomized controlled trial;
BCT: Behaviour change technique; CONSORT: Consolidated Standards of
Reporting Trials; GAF: Global Assessment of Functioning Scale; SCID: Structured
Clinical Interview for DSM-IV (SCID); HASE: Homburg ADHD Scales for Adults;
PSQI: Pittsburgh Sleep Quality Index; GSI: Global Severity Index; SCL-90-
R: Symptom Checklist-90-Revised; BSA questionnaire: Physical Activity, Exercise,
and Sport Questionnaire; SF-B: Sleep Questionnaire B-Revised version;
PSS: Perceived Stress Scale; SF-36: 36-Item Short Form Health Survey; SKK-
Scale: Self Concordance of Sport- and Exercise-related Goals Scale; RPE
Scale: Rating of Perceived Exertion Scale; IBM SPSS: Statistical Package for Social
Science; ITT: Intention-to-treat; MCAR: Missing completely at random
The online version contains supplementary material available at https://doi.
Additional file 1. Characteristics of treatment completers versus
Additional file 2. Sensitivity Analysis using Study Completers.
Additional file 3. Additional Explorative Analyses of the Predictive Value
of Exercise on Primary Outcomes.
Additional file 4. Linear mixed models excluding potential outliers.
The authors gratefully acknowledge the psychotherapeutic outpatient clinical of
the department of psychology (especially Marco Daniel Gulewitsch) for helping
recruiting patients, the runners’shop in Tuebingen (Mischa Elbeshausen) for
gifting running shoes for each participant of the IG as well as David Butkiewicus
for proofreading the English Grammar of the article. The authors would also like
to thank Neele Alberts, Luca-Lars Hauser, Ann-Cathrin Werner, Franziska Stock,
Larissa Seyboth, Anna Trusheim, Tim Rohe, Julia Baur, Zuzanna Tkaczynska,
Jonathan Scheef, Sophia Stegmaier, Sonja Hondralis, and Ellen Brölz for serving
as study therapists and/or for their assistance with data collection. We acknow-
ledge support by Open Access Publishing Fund of University of Tübingen.
J.-M.Z., B.-A.S., G.S., I.R., M.H. and S.W. contributed to the conception and the
design of the study. J.-M.Z., B.-A.S., M.H., and S.W. completed the acquisition of
data. J.-M.Z., S.W. and I.R. performed the data analysis. J.-M.Z., B.-A.S., G.S., I.R.,
M.H. and S.W. assisted with the interpretation. Original draft preparation was
done by J.-M.Z. and S.W. J.-M.Z., B.-A.S., G.S., I.R., M.H. and S.W. contributed to the
drafting and revision of the final article. J.-M.Z., B.-A.S., G.S., I.R., M.H. and S.W.
have read and agreed to the published version of the manuscript.
The Robert-Enke Foundation partially funded the study by financing the
compensation for participants of the control group and research assistants.
The funding associations had no involvement in the study design, the collec-
tion, analysis and interpretation of data, in the writing of the report nor in
the decision to submit the article for publication. Open Access funding en-
abled and organized by Projekt DEAL.
Availability of data and materials
The datasets generated and analyzed during the current study are available
in the PsychArchives repository, https://doi.org/10.23668/psycharchives.4625.
Ethics approval and consent to participate
The study was conducted according to the guidelines of the Declaration of
Helsinki, and approved by the Ethics Committee for psychological research
of the University of Tuebingen, Department of Psychology
(Az_Wolf_2018_0108_99, February 22nd, 2018). Informed consent was
obtained from all subjects involved in the study.
Consent for publication
The authors declare that they have no competing interests.
Department of Education & Health Research, Faculty of Economics and
Social Sciences, Institute of Sports Science, University of Tuebingen, 72074
Faculty of Medicine, Institute for Clinical Epidemiology
and Applied Biostatistics, University of Tuebingen, 72074 Tuebingen,
Department of Clinical Psychology and Psychotherapy, Faculty of
Science, Psychological Institute, University of Tuebingen, 72074 Tuebingen,
Received: 19 February 2021 Accepted: 20 May 2021
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