Feasibility of Process-based Therapy in a Naturalistic Setting
Phase: NA
Conditions: Depressive Disorder, Anxiety Disorder
Sponsor: Goethe University

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Submission to: BMC Pilot and Feasibility Studies 
Feasibility of Process-based Therapy in a naturalistic setting: Study protocol 
for a randomized controlled trial 
Ulrich Stangier 
Bettina Hufschmidt 
Nora Görg 
Lucie Sendig 
Viktoria Kohl 
Desiree Bonarius 
Arwin Nemani 
Mareike Ebert 
Stefan G. Hofmann 
 
Abstract 
Background 
In the naturalistic setting of mental health care, treatment decisions of 
psychotherapists are often based on theories or experience related to treatment 
approaches. An alternative approach to treatment decision is suggested by Process-
based Therapy (PBT), which emphasizes empirical and rational criteria for selection 
of intervention. It utilizes ecological momentary assessment (EMA) data, incorporates 
feedback from dynamic network analysis, and supports interventions to be chosen 
based on individual network models and empirical evidence from research related to 
change processes. Currently, there are no data on the feasibility and acceptability of 
PBT in practice. The present study investigates in a naturalistic setting, whether PBT 
can be implemented by psychotherapists in mental health care. Furthermore, we 
explore the acceptability and efficacy of PBT as compared to psychotherapy 
delivered in routine practice (r-PT). 
Methods/design 
The study is a randomized controlled trial (RCT) of PBT vs r-PT. 60 patients are 
recruited in psychotherapy practices and allocated to one of two interventions, PBT 
or r-PT. To control for therapist effects, randomization is stratified by therapists. 
As indicators of feasibility, adherence with process-based treatment rationale, 
acceptance of treatment by therapists and patients, and attrition rate will be 
assessed. Primary outcome is patient-rated quality of life. Secondary outcomes 
include psychological well-being, psychological symptoms of distress, depressive and 
anxious symptoms, adaptive behavior, psychological flexibility, and reflective 
functioning. Assessments of outcome variables are conducted pre-, mid-, and post-
treatment and at 6 months follow-up.  
 
Discussion 
The current study will be the first exploring the dissemination of PBT in a naturalistic 
mental health care setting. If feasibility of PBT is demonstrated, the results may give 
rise to new perspectives in the personalization of assessment and treatment based 
on dynamic network analysis of EMA and rationale treatment decision making. 
 

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Trial registration 
Clinicaltrials.gov JWGUniversity record III III L5 - 519/05.000.002 - 2. Registered 01 
August 2024 
 

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Background 
In mental health care, a wide range of psychological treatments is available. A recent 
meta-analysis of uncontrolled studies of psychological interventions delivered in 
routine practice [1] showed that large pre-post effect sizes were achieved in the 
reduction of depression and anxiety. However, it remains unclear whether such 
positive effects can also be obtained in routine mental health care settings. An 
exception is the Improving Access to Psychological Therapies program in England 
which demonstrated that the implementation of stepped-care clinical guidelines may 
help to bridge the gap between evidence-based research and practice [2]. 
However, treatment guidelines usually provide only rough recommendations for 
evidence-based manuals for specific diagnoses, and it remains unclear how these 
recommendations should be adapted to individual patients. Furthermore, empirical 
research indicates that in clinical practice, assessment of mental health problems is 
often unstructured, and interventions are mainly selected based on the therapist’s 
personal experience or school-based treatment theories than on empirical evidence 
[3,4].  
A promising approach to improve the outcomes of mental health care is 
personalization [5]. Personalization can be conceptualized is a process that involves 
a collaborative collection and processing of diagnostic information as well as shared 
decision-making in the treatment selection. Personalization refers to treatment 
related decisions which can be based on intuition and experience, theoretical models 
underlying the treatment concepts, algorithms using scientific evidence for effective 
interventions, or precise statistical models used to predict the outcome of specific 
interventions based on big data [5]. Preliminary results from randomized controlled 
trials indicate that the effectiveness of treatments may be increased by personalized 
treatments [6].  
A key to personalize treatment is to refine the adaptation of interventions to the 
individual problem and from research on active ingredients [7]. One possible way to 
select interventions more efficiently is by matching the specific mechanisms 
underlying psychological treatment to the psychological processes maintaining the 
psychological dysregulation of the individual patient. Following this concept, Hofmann 
and Hayes (2019) introduced the process-based therapy approach characterized by 
two principles [8]:  
1. To identify the key process maintaining the maladaptive pattern by using 
ecological momentary assessment (EMA) and dynamic network analysis [9] 
2. To select interventions according to scientific evidence for the ability to change this 
key process [10]. 
The process-based approach conceives psychological disorders as individual 
networks of psychological processes, as opposed to the latent disease model, which 
assigns symptoms to an underlying disease [11]. In contrast to syndrome-based 
treatment packages, interventions are selected based on change processes that 
have been empirically supported as mediators of treatment effects [12]. Furthermore, 
in an extended evolutionary meta-model, Hayes, Hofmann and Ciarrochi (2020) [13] 
propose that mental health problems can be conceptualized as an idiographic 
network of maladaptive psychological processes in a specific context, rather than 
symptoms of a static state of disease. Within this evolutionary framework, change 
processes in psychotherapy are guided by the principles of context-dependent 
variation, selection, and retention, modifying the elements of the maladaptive 
individual psychological network, and creating an adaptive, more flexible network. 
 

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To sum up, personalization is a promising way to improve the effectiveness of 
psychotherapy. However, whereas personalized treatment is associated with 
increased efficacy in randomized controlled trials, implementation into clinical 
practice may encounter barriers to data-driven and evidence-based decision 
algorithms [14]. Process-based therapy is characterized by two essential principles: 
1) key factors maintaining psychological problems are identified by using EMA and 
dynamic network analysis, and 2) interventions are selected based on active 
ingredients fitting to the key factors of the individual problem [8]. In the proposed 
study, we examine the hypothesis whether of the diagnostic process and treatment 
selection as intended in process-based therapy is feasible for the implementation into 
clinical practice. Furthermore, we want to explore whether PBT is more effective than 
routine CBT. Since the principles of PBT are not related or even restricted to specific 
disorders, patients with a broad range of diagnoses will be included in the trial. 
 
Objectives 
The main objective is to explore the feasibility of PBT in a routine mental health care 
setting delivered by practitioners. Feasibility comprises acceptance, evaluation of 
utility, compliance of patient and adherence of therapists with the treatment. To 
determine the degree of feasibility, we compare patients’ and therapists’ ratings of 
feasibility related to PBT with ratings in routine psychotherapy. 
The specific questions related to feasibility are:  
• Is the credibility of PBT assessed before treatment reduced, as compared to 
the credibility of routine psychotherapy?  
• Are patients after receiving PBT less satisfied with their treatment, as 
compared to r-PT?  
• With regards to the PBT condition, what is the ratio of therapists and patients 
who report low vs. high utility of EMA and dynamic network models?  
• How many therapists report low vs. high levels of acceptability, as defined by 
reasonableness, effectiveness, side effects, effort required, costs, and 
willingness to implement PBT in their usual practice? 
• As another aspect of feasibility, we also assess compliance of patients with 
EMA and adherence of therapists with process-based decision-making, i.e. 
application of EMA, use of dynamic network analysis, and network-based 
implementation of interventions. 
 
A secondary aim is to investigate the initial evidence for the effectiveness of PBT in 
clinical practice. For this purpose, the effects of PBT after EMA-Baseline, after 
treatment and at 6-month follow-up, as self-rated by patients, will be compared with 
psychological treatment as usual. The hypotheses related to effectiveness are: 
PBT will be superior to r-PT after treatment and at 6-month follow-up with regard to: 
• psychological distress 
• quality of life 
• psychological well-being 
• changes in psychological flexibility 
• adaptive behavior 
• reflective functioning  
• capacity for social and interpersonal pleasure  
 
Furthermore, we will examine the patients’ changes in avoidance/ behavioral control 
and cognitive style on outcome as a possible mediator. Our hypothesis is that PBT 

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will be associated with larger changes in avoidance/ behavioral control and cognitive 
style, and that these changes are significantly related to the primary outcome, i.e. 
psychological distress. 
Finally, we will investigate potential moderators of outcome, i.e. patient expectations, 
and therapeutic alliance across and within treatment conditions, and therapists’ 
adherence with the manual within the PBT condition. 
 
Methods/design 
Design 
The current trial is an exploratory randomized controlled feasibility trial with two 
parallel treatment conditions, PBT and r-PT, delivered in a natural setting of mental 
health care. To control for systematic effects of therapist variables such as therapists’ 
competences and preferences, allocation will be stratified by therapists. Pairs of 
patients recruited by a therapist within his practice will be randomly assigned to one 
of the both study conditions. Thus, the same therapist implements PBT as well as r-
PT. Adherence to both conditions is ensured by controlling the use of EMA and a 
questionnaire covering essential ingredients of PBT. All participants across the two 
intervention groups will receive 24 weekly sessions. A CONSORT diagram is 
provided in Fig. 1. 
 
 
Figure 1: Consort flow-diagram 
 
 
To be assessed for eligibility
Pre-assessment
Randomization
Stratified for therapists
N=60
R-PT
(5 sessions)
Intermediate assessment
R-PT (19 sessions)
Post-assessment
6-Mo Follow-up
PBT: Baseline incl. EMA
(5 session)
Intermediate assessment
PBT (19 sessions)
Post-assessment
6-Mo-Follow-up

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Notes: EMA: Ecological Momentary Assessment; PBT: Process-based Therapy; r-
PT: Routine Psychotherapy 
 
Assessments 
Assessments of dependent variables are taken at four measurement points: before 
treatment, at mid-treatment, after treatment, and at 6-month follow-up (see. Table 1). 
The mid-treatment point is after session 5, to assess for changes due to EMA.  
Indicators for feasibility will be assessed before and after treatment. Feasibility 
measures include both patients’ and therapists’ ratings of pre-treatment credibility 
and acceptance and attitude towards utility of EMA after treatment. Furthermore, we 
examine patients’ compliance with EMA and therapists’ adherence with process-
based decision-making during treatment. 
Primary endpoints of outcome are patients’ self-ratings of emotional distress, 
secondary outcomes include psychological well-being, quality of life and mental 
health at post-intervention and at 6 months follow-up.  
 
Process variables include Psychological Flexibility, Reflective Functioning, Adaptive 
Behavior and Cognitive Behavioral Therapy Skills at pre, intermediate and post-
assessment and at follow-up. In addition, therapeutic relationship will be assessed at 
pre- and post-treatment. 
 
 
 
 

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Table 1 Overview of measurements 
 
Abbreviations: 
HAQ-11, Helping Alliance Questionnaire; 
FAMOS, Fragebogen zur Analyse Motivationaler Schemata, Kurzversion (Brief 
Assessment of Motivational schemas);  
PBDMQ, Process-based decision-making questionnaire; 
TAUEN, Therapist attitude towards utility of EMA and networks Scale;  
CEQ, Credibility/Expectancy Questionnaire 
TEI, Treatment Evaluation Inventory 
DASS-10, Depression Anxiety Stress Scale 10 Items; 
EQ-5D, EuroQol 5 Dimensions; 
PMH, Positive Mental Health Scale;  
AAQ, Acceptance and Action Questionnaire 
RFQ: Reflective Functioning Questionnaire;  
PBAT, Process-Based Assessment Tool;  
CBTSQ, Cognitive Behavioral Therapy Skills Questionnaire 
EMA: Ecological Momentary Assessment.  
Measurement Points Inclusion 
Pre-
Treatment 
Baseline 
Phase 
Inter-
mediate 
Treatment 
Phase 
Post-
Treatment 
Follow 
Up 
Treatment
Sessions
 
 
1-5 
 
6-24 
 
 
Week
Instrument 
0 
1 
2-7 
8 
9-27 
28 
51 
Thera
pist 
ICD-11  
Diagnosis  
X 
 
 
 
 
X   
X  
CGI 
 
X 
 
 
 
X 
X 
CGI-I 
 
 
 
 
 
X 
X 
HAQ-11 
 
X  
 
 
 
X 
 
FAMOS 
 
X 
 
 
 
 
 
Intervention 
Checklist  
 
 
 
 
 
X 
 
PBDMQ 
 
 
 
 
every 4 weeks 
 
 
TAUEN 
 
 
 
 
 
X 
 
CEQ 
 
X 
 
 
 
 
 
TEI 
 
 
 
 
 
X 
 
Patie
nt 
DASS-10 
 
X 
 
X 
 
X 
X 
EQ-5D 
 
X 
 
 
 
X 
X 
PMH 
 
X 
 
 
 
X 
X 
AAQ-II 
 
X 
 
X 
 
X 
X 
RFQ 
 
X 
 
X 
 
X 
X 
PBAT 
 
X 
 
X 
 
X 
X 
CBTSQ 
 
X 
 
X 
   
X 
X 
EMA (PBT) 
 
 
Daily   
(only PBT) 
 
  
X 
 
HAQ-11 
 
X 
 
 
 
X  
 
CEQ 
 
X 
 
 
 
 
 
PAUEN 
 
 
 
 
 
X 
 
CSQ 
 
 
 
 
 
X 
 

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PAUEN, Patient attitude towards utility of EMA and networks Scale;  
CSQ-8, Client Satisfaction Questionnaire 
 
Measures 
Feasibility 
The primary outcome measure for feasibility is the Treatment Evaluation Inventory 
(TEI) [17]. It consists of 14 Items with a 7-point scale. The items are phrased as 
statements about the treatment, and respondents indicate their level of agreement or 
disagreement with each statement after the treatment.  
Additionally, to assess the acceptance of treatment, treatment expectancy and 
credibility before treatment will be assessed using the Credibility/Expectancy 
Questionnaire (CEQ) [15]. Higher scores on the CEQ indicate better outcome 
expectations and greater perceived credibility of the treatment. The CEQ comprises 6 
items with three items on each of the two subscales credibility and expectancy. 
Furthermore, the study includes the Patient attitude towards utility of EMA and 
networks scale (PAUEN) and the Therapists attitude towards utility of EMA and 
networks scale (TAUEN) which are modified versions of the Therapist and Client 
Attitude Measures by Frumkin et al. (2021) [16]. The scales have eight items in the 
patient version and six items for therapists that can both be answered on a five-point 
scale. The items are assessed post-treatment. Designed to measure satisfaction with 
health services, the Client Satisfaction Questionnaire (CSQ-8) [18] will be assessed 
at post treatment as well. It consists of eight self-report items. 
Effectiveness 
To assess psychological symptoms of distress, depressive and anxious symptoms, 
the short version of the Depression Anxiety Stress Scale (DASS-10) [21] will be used 
at pre-treatment, at mid-treatment, post-treatment and at 6-month follow-up. 
Additional outcome measures include the health-related quality of life will be 
evaluated using the Euroqol-5D (EQ-5D) [19] pre-treatment, post-treatment and at 6-
month follow-up. 
Furthermore, the Positive-Mental Health Scale (PMH) [20] is used to assess positive 
mental health pre-treatment and post-treatment including emotional, psychological, 
and social aspects of well-being by including 9 self-report items.  
Psychological flexibility is measured by the Acceptance and Action Questionnaire 
Version 2 (AAQ-2) [22] on three self-report items. Furthermore, reflective functioning 
will be assessed by using the Reflective Functioning Questionnaire (RFQ-8) [23], a 
54-item self-report inventory evaluating the capacity to comprehend internal mental 
states of oneself and others across two dimensions: Certainty and Uncertainty about 
mental states. Using the Process-based Assessment Tool (PBAT) [24] variation, 
selection and retention of adaptive behavior will be measured pre-treatment, at 
intermediate treatment, post-treatment and at the 6-month follow-up. The Cognitive-
Behavioral-Therapy Skills Questionnaire (CBTSQ) [25] consisting of six self-report 
items measures patients’ use of cognitive behavioral therapy interventions in the 
study.  
Therapists’ ratings 

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Diagnosis will be based on the ICD-11 and made by the therapists. Post treatment a 
check-list of interventions for therapists is implemented to verify adherence. The 
Process-based Decision-making Questionnaire (PBDMQ) [26] comprises 24 items 
designed to evaluate adherence to process-based therapy (PBT). The "Clinical 
Global Impression Scale" (CGI) [27] that assesses the clinician's overall evaluation of 
the severity of a mental disorder and is utilized to monitor changes in symptom 
severity over time. It has 3-items that are answered by the therapists. 
 
Moderators 
Therapeutic alliance is assessed by patients and therapists by using the 11-item 
Helping Alliance Questionnaire (HAQ-11) [28]. 
FAMOS (Questionnaire for the Analysis of Motivational Schemata, short version), 
also known as the Brief Assessment of Motivational Schemata [29], captures 
motivational schemata by measuring how people structure their needs, goals, and 
motives and which motivational patterns they use in the process. 
EMA 
The Status-PBT (Vacay ©, 2024) is a mobile application for EMA during baseline 
phase which uses personalized questions and captures six dimensions (thought, 
emotion, body sensation, behavior, cognitive processing, motivational schema) on 
bipolar continuous scales ranging from -100 to +100. Similarity of the context with 
typical problem situations as defined in the hypothetical network model is rated on a 
continuous scale ranging from 0 to +100. 
A check-list of interventions for therapists is used after post-treatment assessment to 
check adherence, based on literature reviews [30,31] and meta-analyses [32-34]. 
 
Settings 
Therapists participating in the trial are psychotherapists who are licensed for 
cognitive-behavioral therapy or psychodynamic psychotherapy for adult patients 
Therapists will be recruited in the Rhine-Main-Area and neighboring regions. All 
therapists receive 20 hrs. training focusing on personalization of treatment by 
1) deriving a hypothetical network model of the individual problem,  
2) guiding patients through the collection of EMA data,  
3) interpreting dynamic network models,  
4) drawing network-related treatment decisions, and   
5) applying interventions based on mechanisms related to the central knot of the 
network. 
All therapists receive a manual [35] containing essential procedures in network-based 
assessment and treatment. 
Participants 
We aim to include 60 patients who meet the inclusion criteria: (1) a primary DSM-5 
diagnosis of a depressive or anxiety disorder, (2) age 18-65 years, (4) sufficient 
knowledge of the German language. Participating patients are not required to 
discontinue medication, but to keep medication constant over the treatment period. 
Patients will be excluded in case of (1) increased suicidality, (2) substance abuse or 
dependency, (3) diagnose of a cluster A or B (DSM-5) personality disorder, (4) 
pervasive developmental disorder, psychotic disorder, eating disorder, bipolar 

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disorder, or severe physical illness. Inclusion and exclusion criteria are assessed by 
intake clinicians using M.I.N.I. [36] adapted for DSM-5.  
Recruitment and randomization procedure  
Patients are evaluated by the therapists to be eligible for participation in the study 
based on inclusion and exclusion criteria described before. If patients are eligible for 
treatment, they will be provided with information about the project. Patients who 
consent to participate in the project will be included in the pretreatment assessment 
(see Table 1). Patients’ self-ratings are collected electronically with guidance of the 
trial management staff. Patients who cannot or will not participate in the study will be 
offered treatment as usual by the therapist. 
If eligibility for the study is confirmed, and informed consent to randomization is 
given, patient will be randomized to one of both conditions (PBT or R-PT) provided by 
the same therapist. To allocate study participants to treatment conditions, a 
randomization list is created by the data management staff using the statistical 
software R. The group allocations are printed out individually and placed in sealed 
envelopes. For each included participant, a member of the trial management staff 
draws an envelope and reads off the group allocation. 
 
 
Treatments 
Both treatments comprise 24 weekly sessions, including a 5-week baseline phase in 
PBT. 
In the baseline phase of PBT, a hypothetical network model of the problem is 
developed. EMA is then conducted based on the model's key components: 
situational context, cognition, emotion, bodily symptoms, behavior, cognitive 
processing, and motivational schema. Besides the definition of maladaptive 
responses, also the adaptive counterparts of the variables, representing the desired 
outcomes to be targeted in treatment, are defined. 
Participants of PBT are instructed to use the mobile app Status (Vacay ©), which 
prompts them to assess the seven dimensions from the hypothetical network model 
on a bipolar scale from -100 (maladaptive) to +100 (adaptive). Data are collected in 
the context of situations related to the problem. Therapists guide the adaptation of 
the items during weekly sessions and assist patients in recognizing situations and 
recording their judgments of the model components. EMA is completed when 100 
measurements are collected. 
Based on the EMA data, a dynamic network analysis is performed to assess 
autoregressive and cross-lagged effects of the variables [37]. The interactive effects 
of the variables are estimated and visualized in a network where variables are 
represented as 'nodes', effects between them as directed arrows ('edges'), and 
autoregressive effects as 'self-loops'. 
In the 5 initial session of r-PT corresponding to the baseline in PBT, no specific goals 
are prescribed. Usually, psychotherapists explore either current symptoms or major 
biographic events to gain insight into the psychological determinants of the problem. 
After 5 sessions, the intermediate assessment is conducted, followed by 19 treatment 
sessions in both conditions. In PBT, treatment begins with a collaborative 
interpretation of the dynamic network model, based on EMA data collected during the 
baseline phase. Therapists identify the central node, significant edges, self-loops, 
and positive or negative feedback loops between the nodes [38]. Using the outcomes 
from the dynamic network model, interventions are selected based on empirical 

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evidence for mechanisms of change that correspond to the individual patient's central 
node, as well as the feedback loops and self-loops, which are key in maintaining 
maladaptive patterns [10]. 
These interventions are framed within an evolutionary framework as the variation, 
selection, and retention of an adaptive mode of the central node in relation to the 
specific context of the problem [39]. The change in this key variable is monitored 
through daily judgments based on EMA. Treatment also focuses on additional targets 
to establish adaptive modes of the dimensions as defined in the positive network 
model. 
 
In r-PT, as opposed to PBT, a naturalistic setting is retained for treatment decisions. 
Treatment planning follows traditional theories about the factors maintaining the 
disorder and interventions changing them, e.g. avoidance and exposure in anxiety 
disorder or reduced reinforcement of activities and behavioral activation in 
depression [40]. Interventions are selected based on common treatment manuals 
related to diagnoses, e.g. CBT for depression. Individual data from the behavioral 
analysis are used to tailor the techniques to the individual problems of the patients. 
Treatment process is largely structured by personal preferences of the therapist due 
to experience, knowledge, or recommendations of the National guidelines for the 
mental health problem. 
 
Treatment fidelity 
Adherence with PBT vs. r-PT treatment will be checked using a questionnaire 
assessing process-based and naturalistic decision-making styles [26]. The 
questionnaire, validated by PBT experts, contains 24 items. Therapists in both 
conditions will complete the questionnaire after every four sessions in each 
treatment. Additionally, after each treatment session, an intervention checklist 
covering frequently used interventions for depression and anxiety disorders will be 
completed. 
Statistical analyses 
Since it is not the primary goal of this trial to assess the efficacy of PBT, no power 
analysis is planned to determine the sample size. Furthermore, statistical analysis will 
be based on completed assessments, but not include intention-to-treat analysis. For 
exploratory mediator analyses, we will apply Cross-Lagged Modeling and Structural 
Equation Modeling [41]. 
Dynamic network analysis of EMA data at baseline and at post-treatment will be 
computed using the R package "graphical VAR" [37].  
Ethics and governance 
The protocol has been approved by the Ethics Committee at the Department of 
Psychology (Registration number: ###) Protocol amendments will be communicated 
at https://clinicaltrials.gov and detailed in publications.  
 
Adverse events, in particular suicidal behavior/ideation, will be monitored. Withdrawal 
from the study will be considered in case of increased suicidal ideation or acute 
suicidality.  

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The first author, U.S. is principal investigator (PI) and initiated the project together 
with the senior author, S.G.H. The study does not have a data monitoring committee.  
 
Discussion  
The study will be the first investigating the implementation of PBT in a natural setting. 
Although the interventions used in PBT are not different from established 
psychotherapeutic methods, there are innovative elements which might be 
associated with barriers to implementation in practice. 
First, the use of smartphone-based EMA implies that a hypothetical network model of 
the individual problem must be derived from exploration and then defined as 
dimensions which can be assessed in EMA. However, as some studies pointed out, 
practitioners are skeptical towards the application of digital assessment methods [16, 
42, 43]. The technical requirements also must be given [44] which might limit 
application. 
Second, the outcome of dynamic network analyses of EMA data is dependent on the 
quality of information covered in the smartphone-based assessments. Thus, the 
identification of relevant dimensions in the exploration is an important challenge in 
the initial sessions, before EMA is established during baseline. During the EMA 
phase, it is essential for users that it is understood when and what is to be assessed, 
depending on whether time sampling or experience sampling is carried out. 
Furthermore, interpretation of empirical dynamic network models is an important 
initial step to organize treatment. The identification of parameters such as central 
nodes, positive and negative feedback circles, as well as self-loops requires insight 
into the methodological background of these parameters, which is not part of the 
current academic and clinical training. Furthermore, the communication of the results 
must be fitted to the patients’ understanding, associated with obstacles concerning 
complexity, clarity, and utility for the treatment process [45]. 
Third, interventions are selected based on underlying mechanisms related to central 
nodes of the individual network, rather than treatment packages or traditional 
treatment schemata. However, dynamic network models represent a challenge of the 
established practice which is characterized by a strong link from syndromes to 
protocols or treatment packages [8]. The latent disease model claims that the 
problems of a person are caused by a latent dysfunction and is the target of the 
treatment. This model has determined the scientific and clinical training and is deeply 
rooted in the clinical knowledge of many practitioners. The dynamic network 
approach, however, argues that psychopathological patterns represent an individual 
system of interacting elements of psychological symptoms [46]. Therefore, selecting 
personalized interventions based on information about the dynamic network model 
are not yet established in clinical practice. Thus, the implementation of PBT requires 
“new” models, specific knowledge, and more complex decision processes, that also 
consider the individual competencies of a therapist which might limit its feasibility and 
effectiveness in practice. 
From the patients’ perspective, the implementation of EMA is associated with 
increased efforts. The collection of data in everyday’ s life may not only be associated 

13 
 
with digital distress, but also requires to interrupt automatic habits and to focus on 
psychological dimensions as worked out in therapy. Thus, patients must refrain from 
avoiding negative emotions, face the problem and judge their reactions. Thus, the 
capacity to accept distressing internal experiences is necessary to overcome 
experiential avoidance [47]. On the other side, using bipolar ratings including positive 
dimensions may also motivate the patient to engage in change processes even 
before therapeutic strategies are applied [48].  
This trial will give valuable insights into barriers to implement PBT, which helps to 
improve the conceptualization of decision processes in this new approach, as well as 
the training and supervision of therapists. However, with respect to effectiveness, 
design and setting of our study is associated with significant limitations in internal 
validity. First, since therapists will implement both treatment conditions, their 
therapeutic skills and attitudes will have profound effects on the delivery of PBT as 
well as of routine psychotherapy. Therapists’ competence in applying specific 
decision-making strategies in PBT, their adherence with network-based interventions, 
and their allegiance with PBT will largely determine whether significant differences in 
effectiveness will be detectable. Although measures for adherence and allegiance will 
be applied to control for these factors, it is difficult to estimate whether statistically 
significant differences can be achieved. Second, we did not include independent 
clinical judgements of primary outcome, due to problems in organizing the timing with 
practitioners. Thus, there will be a lack of objective information about treatment 
effects. Third, inclusion criteria are broadly defined and will allow for a heterogenous 
composition of the sample with respect to diagnoses and severity. Although patients 
are randomized to both treatment conditions within therapists, equivalence of 
subsamples with respect to clinical characteristics may be impaired.  
Besides these limitations, the implementation in a natural setting of practicing 
psychotherapists with low interference with the therapeutic procedures ensures that 
the generalizability of the outcome on the broader target of mental health care. 
Furthermore, in addition to providing information on the outcome, the practical 
experiences of psychotherapists will also stimulate new ideas how to improve the 
conceptualization and implementation of PBT. 
 
Trial status 
Training of therapists and outcome assessors is ongoing and the study will continue 
until September 2025. 
 
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