From Theory to Practice: A Transtheoretical Treatment and Training Model (4TM).

Background: In this paper, we present the conceptual background and clinical implications of a research-based transtheoretical treatment and training model (4TM). Method: The model implements findings from psychotherapy outcome, process, and feedback research into a clinical and training framework that is open to future research. Results: The framework is based on interventions targeting patient processes on a behavioral, cognitive, emotional, motivational, interpersonal, and systemic/socio-cultural level. The 4TM also includes a data-based decision support and feedback system called the Trier Treatment Navigator (TTN). Conclusion: We discuss important problems associated with clinical orientations solely based on one school of thought. We then contrast these concerns with a clinical and training framework that embraces ongoing research, serving as a guiding structure for process-based transtheoretical interventions. Such research-based psychological therapy can take both traditional and novel clinical developments as well as findings from psychotherapy research into account and be adaptively disseminated to a variety of patient populations.

Web-Based Cognitive Behavioral Treatment for Bulimia Nervosa: A Randomized Clinical Trial.

Importance: Despite the existence of effective treatments, many individuals with bulimia nervosa (BN) do not receive evidence-based therapies. Integrating digital interventions into routine care might reach more patients and reduce the clinical burden of BN. Objective: To evaluate the effectiveness of a web-based cognitive behavioral self-help intervention for individuals with BN. Design, Setting, and Participants: A 2-group randomized clinical trial without follow-up was conducted between February 2, 2021, and July 9, 2022, in Germany. Participants aged between 18 and 65 years who met the diagnostic criteria for BN were enrolled online via self-referral. Data analyses were conducted from October 24, 2022, to December 23, 2023. Interventions: A web-based cognitive behavioral self-help intervention including 12 weekly modules was compared with a waiting-list control group only having access to routine care. Main Outcomes and Measures: The primary outcome was the change in the number of bulimic episodes between baseline and posttreatment. Secondary outcomes included changes in global eating disorder symptoms, clinical impairment, well-being, work capacity, comorbid symptoms, self-esteem, and emotion regulation complemented by weekly measures and ecological momentary assessment. Intention-to-treat analyses were performed. Results: Participants (N = 154; mean [SD] age, 29.6 [8.6] years; 149 [96.8%] female) receiving the web-based intervention demonstrated a significantly greater decrease in bulimic episodes compared with the control group (Cohen d = -0.48; 95% CI, -0.75 to -0.20; P < .001), representing a significant change in binge-eating episodes (Cohen d = -0.61; 95% CI, -0.89 to -0.33; P < .001), but not in compensatory behaviors (Cohen d = -0.25; 95% CI, -0.51 to 0.02; P = .21). The intervention was superior in improving global eating disorder symptoms (Cohen d = -0.61; 95% CI, -0.89 to -0.32; P < .001) and clinical impairment (Cohen d = -0.62; 95% CI, -0.92 to -0.33; P < .001). No significant effects were found for well-being (Cohen d = -0.08; 95% CI, -0.37 to 0.22; P > .99) and work capacity (Cohen d = -0.01; 95% CI, -0.68 to 0.66; P = .99). Exploratory analyses indicated significant changes in self-esteem and emotion regulation difficulties, but not in comorbid symptoms. Conclusions and Relevance: In this randomized clinical trial, a web-based cognitive behavioral self-help intervention effectively decreased eating disorder symptoms and illness-related burden in individuals with BN, underlining the potential of digital interventions to complement established treatments. Trial Registration: ClinicalTrials.gov Identifier: NCT04876196.

Love yourself as a therapist, doubt yourself as an institution? Therapist and institution effects on outcome, treatment length, and dropout.

OBJECTIVE: Research suggests that some therapists achieve better outcomes than others. However, an overlooked area of study is how institution differences impact patient outcomes independent of therapist variance. This study aimed to examine the role of institution and therapist differences in adult outpatient psychotherapy. METHOD: The study included 1428 patients who were treated by 196 therapists at 10 clinics. Two- and three-level hierarchical linear regression models were employed to investigate the effects of therapists and institutions on three dependent patient variables: (1) symptom change, (2) treatment duration, and (3) dropout. Level three explanatory variables were tested. RESULTS: The results showed that therapist effects (TE) were significant for all three types of treatment outcome (7.8%-18.2%). When a third level (institution) was added to the model, the differences between therapists decreased, and significant institution effects (IE) were found: 6.3% for symptom change, 10.6% for treatment duration, and 6.5% for dropout. The exploratory analyses found no predictors able to explain the systematic variation at the institution level. DISCUSSION: TE on psychotherapy outcomes remain a relevant factor but may have been overestimated in previous studies due to not properly distinguishing them from differences at the institution level.

Effectiveness of a Web-Based Cognitive Behavioral Self-Help Intervention for Binge Eating Disorder: A Randomized Clinical Trial.

Importance: Binge eating disorder (BED) is one of the most frequent eating pathologies and imposes substantial emotional and physical distress, yet insufficient health care resources limit access to specialized treatment. Web-based self-help interventions emerge as a promising solution, offering more accessible care. Objective: To examine the effectiveness of a web-based cognitive behavioral self-help intervention for individuals with BED. Design, Setting, and Participants: This 2-arm, parallel-group randomized clinical trial conducted from January 15, 2021, to August 3, 2022, in Germany and other German-speaking countries enrolled patients aged 18 to 65 years who met the diagnostic criteria for BED (according to the Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]). Data analysis occurred between January 27 and September 4, 2023, following our statistical analysis plan. Interventions: Participants were randomized to a web-based self-help intervention or a waiting-list control condition. Main Outcomes and Measures: The primary outcome was a change in objective binge eating episodes from baseline to after treatment. Secondary outcomes included global eating pathology, clinical impairment, work capacity, well-being, comorbid psychopathology, self-esteem, and emotion regulation. Results: A total of 1602 patients were screened, of whom 154 (mean [SD] age, 35.93 [10.59] years; 148 female [96.10%]) fulfilled the criteria for BED and were randomized (77 each to the intervention and control groups). The web-based intervention led to significant improvements in binge eating episodes (Cohen d, -0.79 [95% CI, -1.17 to -0.42]; P < .001), global eating psychopathology (Cohen d, -0.71 [95% CI, -1.07 to -0.35]; P < .001), weekly binge eating (Cohen d, -0.49 [95% CI, -0.74 to -0.24]; P < .001), clinical impairment (Cohen d, -0.75 [95% CI, -1.13 to -0.37]; P < .001), well-being (Cohen d, 0.38 [95% CI, 0.01 to 0.75]; P = .047), depression (Cohen d, -0.49 [95% CI, -0.86 to -0.12]; P = .01), anxiety (Cohen d, -0.37 [95% CI, -0.67 to -0.07]; P = .02), self-esteem (Cohen d, 0.36 [95% CI, 0.13 to 0.59]; P = .003), and emotion regulation (difficulties: Cohen d, -0.36 [95% CI, -0.65 to -0.07]; P = .01 and repertoire: Cohen d, 0.52 [95% CI, 0.19 to 0.84]; P = .003). Conclusion and Relevance: In this randomized clinical trial of a web-based self-help intervention for patients with BED, the findings confirmed its effectiveness in reducing binge eating episodes and improving various mental health outcomes, highlighting a scalable solution to bridge the treatment gap for this condition. Trial Registration: ClinicalTrials.gov Identifier: NCT04876183.

Using Progress Feedback to Enhance Treatment Outcomes: A Narrative Review.

We face increasing demand for greater access to effective routine mental health services, including telehealth. However, treatment outcomes in routine clinical practice are only about half the size of those reported in controlled trials. Progress feedback, defined as the ongoing monitoring of patients' treatment response with standardized measures, is an evidence-based practice that continues to be under-utilized in routine care. The aim of the current review is to provide a summary of the current evidence base for the use of progress feedback, its mechanisms of action and considerations for successful implementation. We reviewed ten available meta-analyses, which report small to medium overall effect sizes. The results suggest that adding feedback to a wide range of psychological and psychiatric interventions (ranging from primary care to hospitalization and crisis care) tends to enhance the effectiveness of these interventions. The strongest evidence is for patients with common mental health problems compared to those with very severe disorders. Effect sizes for not-on-track cases, a subgroup of cases that are not progressing well, are found to be somewhat stronger, especially when clinical support tools are added to the feedback. Systematic reviews and recent studies suggest potential mechanisms of action for progress feedback include focusing the clinician's attention, altering clinician expectations, providing new information, and enhancing patient-centered communication. Promising approaches to strengthen progress feedback interventions include advanced systems with signaling technology, clinical problem-solving tools, and a broader spectrum of outcome and progress measures. An overview of methodological and implementation challenges is provided, as well as suggestions for addressing these issues in future studies. We conclude that while feedback has modest effects, it is a small and affordable intervention that can potentially improve outcomes in psychological interventions. Further research into mechanisms of action and effective implementation strategies is needed.

The relationship between interpersonal problems and therapeutic alliance in psychotherapy: A three-level mixed-effects meta-analysis.

Psychotherapy is an interpersonal process of collaboration toward specified treatment goals. The therapeutic alliance is well established as an important factor of psychotherapeutic change. However, the experience of distress in social interactions, commonly referred to as interpersonal problems, might be interfering with the collaborative process during psychotherapy. This study systematically reviews the literature and obtains an estimate of the relationship between pretreatment interpersonal problems and the quality of the therapeutic alliance. Overall, 27 studies with 48 correlation coefficients were included in the final analysis. Due to the nested structure of the data, a three-level meta-analytic approach with a restricted maximum likelihood estimator was applied. Alliance assessment phase, alliance rater, alliance measure instrument, and treatment type were tested as potential moderators. Heterogeneity and publication bias test were performed. The meta-analysis showed a small, but significant negative relationship between interpersonal problems at the beginning of psychotherapy and subsequent therapeutic alliance (r = -.12, SE = .02, 95% CI [-.16, -.08], p < .001, d = -.27). Only alliance assessment phase accounted for significant variability. There were no indications for a substantial publication bias. Interpersonal problems of patients before psychotherapy are a robust predictor for lower therapeutic alliance quality, albeit a small effect size. Consequently, patients who experience interpersonal problems may face greater challenges in developing a strong alliance with their therapists, especially in early stages of the treatment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

What time-varying network models based on functional analysis tell us about the course of a patient's problem.

Background: Relations among psychological variables are assumed to be complex and to vary over time. Personalized networks can model multivariate complex interactions. The development of time-varying networks allows to model the variation of parameters over time. Objectives: We aimed to determine the value of time-varying networks for clinical practice. Methods: We applied time-varying mixed graphical models (TV-MGM) and time-varying vector autoregressive models (TV-VAR) to intensive longitudinal data of nine participants with depressive symptoms (n = 6) or anxiety (n = 3). Results: Most of the participants showed temporal changes in network topology within the assessment period of 30 days. Time-varying networks of participants with small, medium, and large time variability in edge parameters clearly show the different temporal evolvements of dynamic interactions between variables. The case example indicates clinical utility but also limitations to the application of time-varying networks in clinical practice. Conclusion: Time-varying network models provide a data-driven and exploratory approach that could complement current diagnostic standards by reflecting interacting, often mutually reinforcing processes of mental health problems and by accounting for variation over time. They can be used to generate hypotheses for further confirmatory and clinical testing.

Exploring the complex interrelation between depressive symptoms, risk, and protective factors: A comprehensive network approach.

BACKGROUND: Depressive symptoms seem to be interrelated in a complex and self-reinforcing way. To gain a better understanding of this complexity, the inclusion of theoretically relevant constructs (such as risk and protective factors) offers a comprehensive view into the complex mechanisms underlying depression. METHODS: Cross-sectional data from individuals diagnosed with a major depressive disorder (N = 986) and healthy controls (N = 1049) were analyzed. Participants self-reported their depressive symptoms, as well as several risk factors and protective factors. Regularized partial correlation networks were estimated for each group and compared using a network comparison test. RESULTS: Symptoms of depression were more strongly connected in the network of depressed patients than in healthy controls. Among the risk factors, perceived stress, the experience of negative life events, emotional neglect, and emotional abuse were the most centrally embedded in both networks. However, the centrality of risk factors did not significantly differ between the two groups. Among the protective factors, social support, personal competence, and acceptance were the most central in both networks, where the latter was significantly more strongly associated with the symptom of self-hate in depressed patients. CONCLUSION: The network analysis revealed that key symptoms of depression were more strongly connected for depressed patients than for healthy controls, and that risk and protective factors play an important role, particularly perceived stress in both groups and an accepting attitude for depressed patients. However, the purpose of this study is hypothesis generating and assisting in the potential selection of non-symptom nodes for future research.

Decoding emotions: Exploring the validity of sentiment analysis in psychotherapy.

OBJECTIVE: Given the importance of emotions in psychotherapy, valid measures are essential for research and practice. As emotions are expressed at different levels, multimodal measurements are needed for a nuanced assessment. Natural Language Processing (NLP) could augment the measurement of emotions. The study explores the validity of sentiment analysis in psychotherapy transcripts. METHOD: We used a transformer-based NLP algorithm to analyze sentiments in 85 transcripts from 35 patients. Construct and criterion validity were evaluated using self- and therapist reports and process and outcome measures via correlational, multitrait-multimethod, and multilevel analyses. RESULTS: The results provide indications in support of the sentiments' validity. For example, sentiments were significantly related to self- and therapist reports of emotions in the same session. Sentiments correlated significantly with in-session processes (e.g., coping experiences), and an increase in positive sentiments throughout therapy predicted better outcomes after treatment termination. DISCUSSION: Sentiment analysis could serve as a valid approach to assessing the emotional tone of psychotherapy sessions and may contribute to the multimodal measurement of emotions. Future research could combine sentiment analysis with automatic emotion recognition in facial expressions and vocal cues via the Nonverbal Behavior Analyzer (NOVA). Limitations (e.g., exploratory study with numerous tests) and opportunities are discussed.

To Use or Not to Use: Exploring Therapists' Experiences with Pre-Treatment EMA-Based Personalized Feedback in the TheraNet Project.

BACKGROUND: Using idiographic network models in psychotherapy has been a growing area of interest. However, little is known about the perceived clinical utility of network models. The present study aims to explore therapists' experiences with network model-based feedback within the context of the TheraNet Project. METHODS: In total, 18 therapists who had received network-based feedback for at least 1 patient at least 2 months prior were invited to retrospective focus groups. The focus group questions related to how participation in the study influenced the therapeutic relationship, how the networks were used, and what might improve their clinical utility. The transcribed focus groups were analyzed descriptively using qualitative content analysis. RESULTS: Most therapists mentioned using the feedback to support their existingtheir case concept, while fewer therapists discussed the feedback directly with the patients. Several barriers to using the feedback were discussed, as well as various suggestions for how to make it more clinically useful. Many therapists reported skepticism with regards to research in the outpatient training center in general, though they were also all pleasantly surprised by being involved, having their opinions heard, and showing a readiness to adapt research to their needs/abilities. CONCLUSIONS: This study highlights the gap between researchers' and therapists' perceptions about what useful feedback should look like. The TheraNet therapists' interest in adapting the feedback and building more informative feedback systems signals a general openness to the implementation of clinically relevant research. We provide suggestions for future implementations of network-based feedback systems in the outpatient clinical training center setting.