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Contemporary exposure therapy models for anxiety argue that exposures must generate threat prediction error to be effective. More research is needed to test this claim in clinical settings. This study explored how threat prediction error learning relates to outcomes during an exposure analogue procedure. Adult undergraduate psychology students (N = 125) experiencing a broad range of social anxiety symptoms from healthy to clinical levels of social anxiety completed 667 online speech performance exposures over two testing sessions separated by a week (approx. 3 speeches/session). Self-reported anxiety, threat prediction, threat outcome, and surprise were measured for each exposure and used to derive learning indicators. These included threat prediction error, prediction change, and the extent that prediction errors were converted to prediction change (i.e., learning rate). We examined between- and within-person relationships between these learning indicators and outcomes over exposure using multilevel modelling. Average prediction change and prediction error learning rate, but not average prediction error per se, was associated with more anxiety reduction across the exposure. Within-person, anxiety was lower after exposures that triggered more prediction change. Threat prediction error was not linearly associated with anxiety at the next exposure. Higher threat prediction error during an exposure was associated with greater subjective surprise for that exposure. We concluded that exposure outcomes depend on how much the patient converts exposure-related prediction errors into threat prediction change. Future research should focus on strategies to enhance the prediction-error learning rate from exposures.

Background: Although evidence-based interventions for posttraumatic stress disorder (PTSD) are highly effective, on average about 20% of patients drop out of treatment. Despite considerable research investigating PTSD treatment dropout in randomized controlled trials (RCTs), findings in naturalistic settings remain sparse. Objective: Therefore, the present study investigated the frequency and predictors of dropout in trauma-focused interventions for PTSD in routine clinical care. Method: The sample included n = 195 adults with diagnosed PTSD, receiving trauma-focused, cognitive behavioral therapy in routine clinical care in three outpatient centers. We conducted a multiple logistic regression analysis with the following candidate predictors of dropout: patient variables (e.g., basic sociodemographic status and specific clinical variables) as well as therapist’s experience level and gender match between therapist and patient. Results: Results showed a dropout rate of 15.38%. Age (higher dropout probability in younger patients) and living situation (living with parents predicted lower dropout probability compared to living alone) were significant predictors of dropout. Dropout was not significantly associated with the therapist’s experience level and gender match. Conclusions: In conclusion, routinely assessed baseline patient variables are associated with dropout. Ultimately, this may help to identify patients who need additional attention to keep them in therapy.

Objective: The efficacy of trauma-focused cognitive behaviour therapy (tf-CBT) has been well established in randomized controlled trials (RCTs). More research is needed to demonstrate the effectiveness of tf-CBT in routine clinical care settings. Method: Eighty-five patients (68 female) with a primary diagnosis of PTSD received tf-CBT at two German outpatient centres (Münster and Mannheim) between 2014 and 2016. Treatment was delivered mainly by therapists in training and treatment duration was based on symptom course. The treatment consisted of a preparation phase, a trauma-focused phase (comprising imaginal exposure, discrimination training, changing dysfunctional appraisals) and a phase of reclaiming-your-life assignments, and relapse prevention. In an intent-to-treat-analysis (ITT), linear mixed effects models were fitted for self-assessments of traumatic symptom severity using the PTSD Checklist for DSM-5 (PCL-5) and the Clinician-Administered PTSD Scale for DSM–5 (CAPS-5). Potential moderators for treatment outcome, e.g. number of suicide attempts, were investigated. Results: The observed treatment effect was large for both the CAPS-5 (ITT: Cohen’s d = 2.07, CI [1.62, 2.51]; completers d = 2.34, CI [1.84, 2.83]) and PCL-5 respectively (ITT: d = 2.02, CI [1.56, 2.48]; completers d = 2.15, CI [1.66, 2.64]), and remained stable six months and one-year post-treatment. N = 27 patients (31.48%) were defined as study dropout and of these, n = 12 (14.12%) dropped out of the study but completed treatment. None of the fixed-effect estimates for treatment predictors interacted significantly with the effect of time. Conclusions: Tf-CBT is well-tolerated and it can be effectively delivered in routine clinical care. Its large treatment effects underline the practicability and benefits of the approach. This trial demonstrates its broad applicability among individuals with diverse patterns of clinical characteristics and comorbidities.

Anxiety disorders (AD) are associated with altered connectivity in large-scale intrinsic brain networks. It remains uncertain how much these signatures overlap across different phenotypes due to a lack of well-powered cross-disorder comparisons. We used resting-state functional magnetic resonance imaging (rsfMRI) to investigate differences in functional connectivity (FC) in a cross-disorder sample of AD patients and healthy controls (HC). Before treatment, 439 patients from two German multicenter clinical trials at eight different sites fulfilling a primary diagnosis of panic disorder and/or agoraphobia (PD/AG, N = 154), social anxiety disorder (SAD, N = 95), or specific phobia (SP, N = 190) and 105 HC underwent an 8 min rsfMRI assessment. We performed categorical and dimensional regions of interest (ROI)-to-ROI analyses focusing on connectivity between regions of the defensive system and prefrontal regulation areas. AD patients showed increased connectivity between the insula and the thalamus compared to controls. This was mainly driven by PD/AG patients who showed increased (insula/hippocampus/amygdala—thalamus) and decreased (dorsomedial prefrontal cortex/periaqueductal gray—anterior cingulate cortex) positive connectivity between subcortical and cortical areas. In contrast, SAD patients showed decreased negative connectivity exclusively in cortical areas (insula—orbitofrontal cortex), whereas no differences were found in SP patients. State anxiety associated with the scanner environment did not explain the FC between these regions. Only PD/AG patients showed pronounced connectivity changes along a widespread subcortical-cortical network, including the midbrain. Dimensional analyses yielded no significant results. The results highlighting categorical differences between ADs at a systems neuroscience level are discussed within the context of personalized neuroscience-informed treatments. PROTECT-AD’s registration at NIMH Protocol Registration System: 01EE1402A and German Register of Clinical Studies: DRKS00008743. SpiderVR’s registration at ClinicalTrials.gov: NCT03208400.

Background This paper reports on the outcomes of a proof-of-principle study for the Exposure Therapy Consortium, a global network of researchers and clinicians who work to improve the effectiveness and uptake of exposure therapy. The study aimed to test the feasibility of the consortium’s big-team science approach and test the hypothesis that adding post-exposure processing focused on enhancing threat reappraisal would enhance the efficacy of a one-session large-group interoceptive exposure therapy protocol for reducing anxiety sensitivity. Methods The study involved a multi-site cluster-randomized controlled trial comparing exposure with post-processing (ENHANCED), exposure without post-processing (STANDARD), and a stress management intervention (CONTROL) in students with elevated anxiety sensitivity. Feasibility was assessed using site performance metrics (e.g., timeline, sample size, missing data). Efficacy was assessed up to 1-month follow-up using the Anxiety Sensitivity Index-3. Results Despite challenges posed by unforeseen global crises, a standardized protocol for screening, assessment, and treatment at 12 research sites across four continents was successfully implemented, resulting in a total sample size of 400 with minimal missing data. Challenges in recruitment and adherence to the projected timelines were encountered. Significant reductions in anxiety sensitivity were observed in all conditions. Contrary to hypotheses, group differences were only observed at post-treatment, when ENHANCED and CONTROL outperformed STANDARD but were not significantly different from each other. Conclusions This study demonstrates the feasibility of the Exposure Therapy Consortium. Findings raise questions regarding the efficacy of large group exposure interventions and underscore the importance of careful research site selection and an iterative approach to treatment development.

Background. The Personalized Advantage Index (PAI) shows promise as a method for identifying the most effective treatment for individual patients. Previous studies have demonstrated its utility in retrospective evaluations across various settings. In this study, we explored the effect of different methodological choices in predictive modelling underlying the PAI. Methods. Our approach involved a two-step procedure. First, we conducted a review of prior studies utilizing the PAI, evaluating each study using the Prediction model study Risk Of Bias Assessment Tool (PROBAST). We specifically assessed whether the studies adhered to two standards of predictive modeling: refraining from using leave-one-out cross-validation (LOO CV) and preventing data leakage. Second, we examined the impact of deviating from these methodological standards in real data. We employed both a traditional approach violating these standards and an advanced approach implementing them in two large-scale datasets, PANIC-net (n = 261) and Protect-AD (n = 614). Results. The PROBAST-rating revealed a substantial risk of bias across studies, primarily due to inappropriate methodological choices. Most studies did not adhere to the examined prediction modeling standards, employing LOO CV and allowing data leakage. The comparison between the traditional and advanced approach revealed that ignoring these standards could systematically overestimate the utility of the PAI. Conclusion. Our study cautions that violating standards in predictive modeling may strongly influence the evaluation of the PAI’s utility, possibly leading to false positive results. To support an unbiased evaluation, crucial for potential clinical application, we provide a low-bias, openly accessible, and meticulously annotated script implementing the PAI.

Exposure-based CBT is effective in treating anxiety disorders, but individual responses vary substantially, underlining the need to identify and boost mechanisms underlying exposure. In this study, the role of positive emotions occurring after exposure was examined. In an analysis of 8,416 exposure records of 648 anxiety patients undergoing exposure therapy, the degree of positive emotions hope and joy occurring after exposure exercises, their predictors, and their role regarding treatment success were investigated. Positive emotions after exposure were medium to high and increased slightly across repeated exposure exercises. They were associated with exposure-related learning indicators (i.e., expectancy violation and change as well as the prediction-error learning rate) and were mainly predicted by adjusted threat expectancy assessed after completing exposure, controlling for baseline depressive …