Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders.

Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders and non-responders of a given treatment) when using clinical routine data such as demographic and questionnaire data, while neuroimaging data achieved superior prediction accuracy. However, these studies may be considerably biased due to very limited sample sizes and bias-prone methodology. Adequately powered and cross-validated samples are a prerequisite to evaluate predictive performance and to identify the most promising predictors. We therefore analyzed resting state functional magnet resonance imaging (rs-fMRI) data from two large clinical trials to test whether functional neuroimaging data continues to provide good prediction accuracy in much larger samples. Data came from two distinct German multicenter studies on exposure-based CBT for anxiety disorders, the Protect-AD and SpiderVR studies. We separately and independently preprocessed baseline rs-fMRI data from n = 220 patients (Protect-AD) and n = 190 patients (SpiderVR) and extracted a variety of features, including ROI-to-ROI and edge-functional connectivity, sliding-windows, and graph measures. Including these features in sophisticated machine learning pipelines, we found that predictions of individual outcomes never significantly differed from chance level, even when conducting a range of exploratory post-hoc analyses. Moreover, resting state data never provided prediction accuracy beyond the sociodemographic and clinical data. The analyses were independent of each other in terms of selecting methods to process resting state data for prediction input as well as in the used parameters of the machine learning pipelines, corroborating the external validity of the results. These similar findings in two independent studies, analyzed separately, urge caution regarding the interpretation of promising prediction results based on neuroimaging data from small samples and emphasizes that some of the prediction accuracies from previous studies may result from overestimation due to homogeneous data and weak cross-validation schemes. The promise of resting-state neuroimaging data to play an important role in the prediction of CBT treatment outcomes in patients with anxiety disorders remains yet to be delivered.

Behavioural and functional evidence revealing the role of RBFOX1 variation in multiple psychiatric disorders and traits.

Common variation in the gene encoding the neuron-specific RNA splicing factor RNA Binding Fox-1 Homolog 1 (RBFOX1) has been identified as a risk factor for several psychiatric conditions, and rare genetic variants have been found causal for autism spectrum disorder (ASD). Here, we explored the genetic landscape of RBFOX1 more deeply, integrating evidence from existing and new human studies as well as studies in Rbfox1 knockout mice. Mining existing data from large-scale studies of human common genetic variants, we confirmed gene-based and genome-wide association of RBFOX1 with risk tolerance, major depressive disorder and schizophrenia. Data on six mental disorders revealed copy number losses and gains to be more frequent in ASD cases than in controls. Consistently, RBFOX1 expression appeared decreased in post-mortem frontal and temporal cortices of individuals with ASD and prefrontal cortex of individuals with schizophrenia. Brain-functional MRI studies demonstrated that carriers of a common RBFOX1 variant, rs6500744, displayed increased neural reactivity to emotional stimuli, reduced prefrontal processing during cognitive control, and enhanced fear expression after fear conditioning, going along with increased avoidance behaviour. Investigating Rbfox1 neuron-specific knockout mice allowed us to further specify the role of this gene in behaviour. The model was characterised by pronounced hyperactivity, stereotyped behaviour, impairments in fear acquisition and extinction, reduced social interest, and lack of aggression; it provides excellent construct and face validity as an animal model of ASD. In conclusion, convergent translational evidence shows that common variants in RBFOX1 are associated with a broad spectrum of psychiatric traits and disorders, while rare genetic variation seems to expose to early-onset neurodevelopmental psychiatric disorders with and without developmental delay like ASD, in particular. Studying the pleiotropic nature of RBFOX1 can profoundly enhance our understanding of mental disorder vulnerability.

ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders.

Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders.

Neural adaptation of cingulate and insular activity during delayed fear extinction: A replicable pattern across assessment sites and repeated measurements.

Adapting threat-related memories towards changing environments is a fundamental ability of organisms. One central process of fear reduction is suggested to be extinction learning, experimentally modeled by extinction training that is repeated exposure to a previously conditioned stimulus (CS) without providing the expected negative consequence (unconditioned stimulus, US). Although extinction training is well investigated, evidence regarding process-related changes in neural activation over time is still missing. Using optimized delayed extinction training in a multicentric trial we tested whether: 1) extinction training elicited decreasing CS-specific neural activation and subjective ratings, 2) extinguished conditioned fear would return after presentation of the US (reinstatement), and 3) results are comparable across different assessment sites and repeated measures. We included 100 healthy subjects (measured twice, 13-week-interval) from six sites. 24 h after fear acquisition training, extinction training, including a reinstatement test, was applied during fMRI. Alongside, participants had to rate subjective US-expectancy, arousal and valence. In the course of the extinction training, we found decreasing neural activation in the insula and cingulate cortex as well as decreasing US-expectancy, arousal and negative valence towards CS+. Re-exposure to the US after extinction training was associated with a temporary increase in neural activation in the anterior cingulate cortex (exploratory analysis) and changes in US-expectancy and arousal ratings. While ICCs-values were low, findings from small groups suggest highly consistent effects across time-points and sites. Therefore, this delayed extinction fMRI-paradigm provides a solid basis for the investigation of differences in neural fear-related mechanisms as a function of anxiety-pathology and exposure-based treatment.

Neural processing of emotional facial stimuli in specific phobia: An fMRI study.

BACKGROUND: Patients with specific phobia (SP) show altered brain activation when confronted with phobia-specific stimuli. It is unclear whether this pathogenic activation pattern generalizes to other emotional stimuli. This study addresses this question by employing a well-powered sample while implementing an established paradigm using nonspecific aversive facial stimuli. METHODS: N = 111 patients with SP, spider subtype, and N = 111 healthy controls (HCs) performed a supraliminal emotional face-matching paradigm contrasting aversive faces versus shapes in a 3-T magnetic resonance imaging scanner. We performed region of interest (ROI) analyses for the amygdala, the insula, and the anterior cingulate cortex using univariate as well as machine-learning-based multivariate statistics based on this data. Additionally, we investigated functional connectivity by means of psychophysiological interaction (PPI). RESULTS: Although the presentation of emotional faces showed significant activation in all three ROIs across both groups, no group differences emerged in all ROIs. Across both groups and in the HC > SP contrast, PPI analyses showed significant task-related connectivity of brain areas typically linked to higher-order emotion processing with the amygdala. The machine learning approach based on whole-brain activity patterns could significantly differentiate the groups with 73% balanced accuracy. CONCLUSIONS: Patients suffering from SP are characterized by differences in the connectivity of the amygdala and areas typically linked to emotional processing in response to aversive facial stimuli (inferior parietal cortex, fusiform gyrus, middle cingulate, postcentral cortex, and insula). This might implicate a subtle difference in the processing of nonspecific emotional stimuli and warrants more research furthering our understanding of neurofunctional alteration in patients with SP.

Efficacy of temporally intensified exposure for anxiety disorders: A multicenter randomized clinical trial.

BACKGROUND: The need to optimize exposure treatments for anxiety disorders may be addressed by temporally intensified exposure sessions. Effects on symptom reduction and public health benefits should be examined across different anxiety disorders with comorbid conditions. METHODS: This multicenter randomized controlled trial compared two variants of prediction error-based exposure therapy (PeEx) in various anxiety disorders (both 12 sessions + 2 booster sessions, 100 min/session): temporally intensified exposure (PeEx-I) with exposure sessions condensed to 2 weeks (n = 358) and standard nonintensified exposure (PeEx-S) with weekly exposure sessions (n = 368). Primary outcomes were anxiety symptoms (pre, post, and 6-months follow-up). Secondary outcomes were global severity (across sessions), quality of life, disability days, and comorbid depression. RESULTS: Both treatments resulted in substantial improvements at post (PeEx-I: dwithin = 1.50, PeEx-S: dwithin = 1.78) and follow-up (PeEx-I: dwithin = 2.34; PeEx-S: dwithin = 2.03). Both groups showed formally equivalent symptom reduction at post and follow-up. However, time until response during treatment was 32% shorter in PeEx-I (median = 68 days) than PeEx-S (108 days; TRPeEx-I = 0.68). Interestingly, drop-out rates were lower during intensified exposure. PeEx-I was also superior in reducing disability days and improving quality of life at follow-up without increasing relapse. CONCLUSIONS: Both treatment variants focusing on the transdiagnostic exposure-based violation of threat beliefs were effective in reducing symptom severity and disability in severe anxiety disorders. Temporally intensified exposure resulted in faster treatment response with substantial public health benefits and lower drop-out during the exposure phase, without higher relapse. Clinicians can expect better or at least comparable outcomes when delivering exposure in a temporally intensified manner.

Identifying CBT non-response among OCD outpatients: A machine-learning approach.

Objectives: Machine learning models predicting treatment outcomes for individual patients may yield high clinical utility. However, few studies tested the utility of easy to acquire and low-cost sociodemographic and clinical data. In previous work, we reported significant predictions still insufficient for immediate clinical use in a sample with broad diagnostic spectrum. We here examined whether predictions will improve in a diagnostically more homogeneous yet large and naturalistic obsessive-compulsive disorder (OCD) sample. Methods: We used sociodemographic and clinical data routinely acquired during CBT treatment of n = 533 OCD subjects in a specialized outpatient clinic. Results: Remission was predicted with 65% (p = 0.001) balanced accuracy on unseen data for the best model. Higher OCD symptom severity predicted non-remission, while higher age of onset of first OCD symptoms and higher socioeconomic status predicted remission. For dimensional change, prediction achieved r = 0.31 (p = 0.001) between predicted and actual values. Conclusions: The comparison with our previous work suggests that predictions within a diagnostically homogeneous sample, here OCD, are not per se superior to a more diverse sample including several diagnostic groups. Using refined psychological predictors associated with disorder etiology and maintenance or adding further data modalities as neuroimaging or ecological momentary assessments are promising in order to further increase prediction accuracy.

Psychometric Properties of an Abbreviated Version of the Apathy Evaluation Scale for Parkinson Disease (AES-12PD).

BACKGROUND: Apathy is a frequent symptom in Parkinson's disease (PD), substantially aggravating the course of PD. Regarding the accumulating evidence of the key role of apathy in PD, time-efficient assessments are useful for fostering progress in research and treatment. The Apathy Evaluation Scale (AES) is widely used for the assessment of apathy across different nosologies. OBJECTIVE: To facilitate the application of the AES in PD, we reduced the AES to two-thirds its length and validated this abbreviated version. DESIGN: Data sets of 339 PD patients of the DEMPARK/LANDSCAPE study without dementia and depression were randomly split into two samples. Data of sample 1 were used to develop a brief version of the AES (AES-12PD). A cross-validation was conducted in sample 2 and in a subsample of 42 PD patients with comorbid dementia and depressive symptomatology. Receiver operating characteristic analysis was applied to determine the optimal cutoff of the AES-12PD as an indicator of apathy. RESULTS: The AES-12PD featured high internal consistency that was better compared to the AES. The abbreviated scale was well differentiated from motor impairment and cognitive deficits. The AES-12PD cutoff of 27/28 was the optimal cutoff for apathy in PD patients without dementia and depression. The cutoff of 25/26 indicated apathy in PD patients with comorbid dementia and depression. CONCLUSION: Results confirm a high internal consistency and good discriminant validity of the AES-12PD. The AES-12PD represents a reliable tool for the efficient assessment of apathy that can be applied in PD patients with and without dementia and depression.

Effects of Cognitive Behavioral Therapy on Neural Processing of Agoraphobia-Specific Stimuli in Panic Disorder and Agoraphobia.

BACKGROUND: Patients suffering from panic disorder and agoraphobia are significantly impaired in daily life due to anxiety about getting into a situation due to apprehension about experiencing a panic attack, especially if escape may be difficult. Dysfunctional beliefs and behavior can be changed with cognitive behavioral therapy; however, the neurobiological effects of such an intervention on the anticipation and observation of agoraphobia-specific stimuli are unknown. METHODS: We compared changes in neural activation by measuring the blood oxygen level-dependent signal of 51 patients and 51 healthy controls between scans before and those after treatment (group by time interaction) during anticipation and observation of agoraphobia-specific compared to neutral pictures using 3-T fMRI. RESULTS: A significant group by time interaction was observed in the ventral striatum during anticipation and in the right amygdala during observation of agoraphobia-specific pictures; the patients displayed a decrease in ventral striatal activation during anticipation from pre- to posttreatment scans, which correlated with clinical improvement measured with the Mobility Inventory. During observation, the patients displayed decreased activation in the amygdala. These activational changes were not observed in the matched healthy controls. CONCLUSIONS: For the first time, neural effects of cognitive behavioral therapy were shown in patients suffering from panic disorder and agoraphobia using disorder-specific stimuli. The decrease in activation in the ventral striatum indicates that cognitive behavioral therapy modifies anticipatory anxiety and may ameliorate abnormally heightened salience attribution to expected threatening stimuli. The decreased amygdala activation in response to agoraphobia-specific stimuli indicates that cognitive behavioral therapy can alter the basal processing of agoraphobia-specific stimuli in a core region of the fear network.

Diagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.

While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety disorders, findings based on diagnostic groups do not translate into diagnostic value for the individual patient. Machine-learning generates predictive information that can be used for single subject classification. We applied Gaussian process classifiers to a sample of patients with specific phobia as a model disorder for pathological forms of anxiety to test for classification based on structural MRI data. Gray (GM) and white matter (WM) volumetric data were analyzed in 33 snake phobics (SP; animal subtype), 26 dental phobics (DP; blood-injection-injury subtype) and 37 healthy controls (HC). Results showed good accuracy rates for GM and WM data in predicting phobia subtypes (GM: 62 % phobics vs. HC, 86 % DP vs. HC, 89 % SP vs. HC, 89 % DP vs. SP; WM: 88 % phobics vs. HC, 89 % DP vs. HC, 79 % SP vs. HC, 79 % DP vs. HC). Regarding GM, classification improved when considering the subtype compared to overall phobia status. The discriminatory brain pattern was not solely based on fear circuitry structures but included widespread cortico-subcortical networks. Results demonstrate that multivariate pattern recognition represents a promising approach for the development of neuroimaging-based diagnostic markers that could support clinical decisions. Regarding the increasing number of fMRI studies on anxiety disorders, researchers are encouraged to use functional and structural data not only for studying phenotype characteristics on a group level, but also to evaluate their incremental value for diagnostic or prognostic purposes.

Therapygenetics: anterior cingulate cortex-amygdala coupling is associated with 5-HTTLPR and treatment response in panic disorder with agoraphobia.

Variation in the 5'-flanking promoter region of the serotonin transporter gene SLC6A4, the 5-HTT-linked polymorphic region (5-HTTLPR) has been inconclusively associated with response to cognitive-behavioural therapy (CBT). As genomic functions are stronger related to neural than to behavioural markers, we investigated the association of treatment response, 5-HTTLPR and functional brain connectivity in patients with panic disorder with agoraphobia (PD/AG). Within the national research network PANIC-NET 231 PD/AG patients who provided genetic information underwent a manualized exposure-based CBT. A subset of 41 patients participated in a functional magnetic resonance imaging (fMRI) add-on study prior to treatment applying a differential fear conditioning task. Neither the treatment nor the reduced fMRI sample showed a direct effect of 5-HTTLPR on treatment response as defined by a reduction in the Hamilton Anxiety Scale score ≥50 % from baseline to post assessment. On a neural level, inhibitory anterior cingulate cortex (ACC)-amygdala coupling during fear conditioning that had previously been shown to characterize treatment response in this sample was driven by responders with the L/L genotype. Building upon conclusive evidence from basic and preclinical findings on the association of the 5-HTTLPR polymorphism with emotion regulation and related brain connectivity patterns, present findings translate these to a clinical sample of PD/AG patients and point towards a potential intermediate connectivity phenotype modulating response to exposure-based CBT.

Neural correlates of procedural variants in cognitive-behavioral therapy: a randomized, controlled multicenter FMRI study.

BACKGROUND: Cognitive behavioral therapy (CBT) is an effective treatment for panic disorder with agoraphobia (PD/AG). It is unknown, how variants of CBT differentially modulate brain networks involved in PD/AG. This study was aimed to evaluate the effects of therapist-guided (T+) versus self-guided (T-) exposure on the neural correlates of fear conditioning in PD/AG. METHOD: In a randomized, controlled multicenter clinical trial in medication-free patients with PD/AG who were treated with 12 sessions of manualized CBT, functional magnetic resonance imaging (fMRI) was used during fear conditioning before (t1) and after CBT (t2). Quality-controlled fMRI data from 42 patients and 42 healthy subjects (HS) were obtained. Patients were randomized to two variants of CBT (T+, n = 22, and T-, n = 20). RESULTS: The interaction of diagnosis (PD/AG, HS), treatment group (T+, T-), time point (t1, t2) and stimulus type (conditioned stimulus: yes, no) revealed activation in the left hippocampus and the occipitotemporal cortex. The T+ group demonstrated increased activation of the hippocampus at t2 (t2 > t1), which was positively correlated with treatment outcome, and a decreased connectivity between the left inferior frontal gyrus and the left hippocampus across time (t1 > t2). CONCLUSION: After T+ exposure, contingency-encoding processes related to the posterior hippocampus are augmented and more decoupled from processes of the left inferior frontal gyrus, previously shown to be dysfunctionally activated in PD/AG. Linking single procedural variants to neural substrates offers the potential to inform about the optimization of targeted psychotherapeutic interventions.

Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis.

Predicting treatment outcome in internalizing mental disorders prior to treatment initiation is pivotal for precision mental healthcare. In this regard, resting-state functional connectivity (rs-FC) and machine learning have often shown promising prediction accuracies. This systematic review and meta-analysis evaluates these studies, considering their risk of bias through the Prediction Model Study Risk of Bias Assessment Tool (PROBAST). We examined the predictive performance of features derived from rs-FC, identified features with the highest predictive value, and assessed the employed machine learning pipelines. We searched the electronic databases Scopus, PubMed and PsycINFO on the 12th of December 2022, which resulted in 13 included studies. The mean balanced accuracy for predicting treatment outcome was 77% (95% CI: [72%- 83%]). rs-FC of the dorsolateral prefrontal cortex had high predictive value in most studies. However, a high risk of bias was identified in all studies, compromising interpretability. Methodological recommendations are provided based on a comprehensive exploration of the studies' machine learning pipelines, and potential fruitful developments are discussed.

Predicting recurrent chat contact in a psychological intervention for the youth using natural language processing.

Chat-based counseling hotlines emerged as a promising low-threshold intervention for youth mental health. However, despite the resulting availability of large text corpora, little work has investigated Natural Language Processing (NLP) applications within this setting. Therefore, this preregistered approach (OSF: XA4PN) utilizes a sample of approximately 19,000 children and young adults that received a chat consultation from a 24/7 crisis service in Germany. Around 800,000 messages were used to predict whether chatters would contact the service again, as this would allow the provision of or redirection to additional treatment. We trained an XGBoost Classifier on the words of the anonymized conversations, using repeated cross-validation and bayesian optimization for hyperparameter search. The best model was able to achieve an AUROC score of 0.68 (p < 0.01) on the previously unseen 3942 newest consultations. A shapely-based explainability approach revealed that words indicating younger age or female gender and terms related to self-harm and suicidal thoughts were associated with a higher chance of recontacting. We conclude that NLP-based predictions of recurrent contact are a promising path toward personalized care at chat hotlines.

Association between resting-state connectivity patterns in the defensive system network and treatment response in spider phobia-a replication approach.

Although highly effective on average, exposure-based treatments do not work equally well for all patients with anxiety disorders. The identification of pre-treatment response-predicting patient characteristics may enable patient stratification. Preliminary research highlights the relevance of inhibitory fronto-limbic networks as such. We aimed to identify pre-treatment neural signatures differing between exposure treatment responders and non-responders in spider phobia and to validate results through rigorous replication. Data of a bi-centric intervention study comprised clinical phenotyping and pre-treatment resting-state functional connectivity (rsFC) data of n = 79 patients with spider phobia (discovery sample) and n = 69 patients (replication sample). RsFC data analyses were accomplished using the Matlab-based CONN-toolbox with harmonized analyses protocols at both sites. Treatment response was defined by a reduction of >30% symptom severity from pre- to post-treatment (Spider Phobia Questionnaire Score, primary outcome). Secondary outcome was defined by a reduction of >50% in a Behavioral Avoidance Test (BAT). Mean within-session fear reduction functioned as a process measure for exposure. Compared to non-responders and pre-treatment, results in the discovery sample seemed to indicate that responders exhibited stronger negative connectivity between frontal and limbic structures and were characterized by heightened connectivity between the amygdala and ventral visual pathway regions. Patients exhibiting high within-session fear reduction showed stronger excitatory connectivity within the prefrontal cortex than patients with low within-session fear reduction. Whereas these results could be replicated by another team using the same data (cross-team replication), cross-site replication of the discovery sample findings in the independent replication sample was unsuccessful. Results seem to support negative fronto-limbic connectivity as promising ingredient to enhance response rates in specific phobia but lack sufficient replication. Further research is needed to obtain a valid basis for clinical decision-making and the development of individually tailored treatment options. Notably, future studies should regularly include replication approaches in their protocols.

Mental health improvement after the COVID-19 pandemic in individuals with psychological distress.

The COVID-19 pandemic and associated countermeasures had an immensely disruptive impact on people's lives. Due to the lack of systematic pre-pandemic data, however, it is still unclear how individuals' psychological health has been affected across this incisive event. In this study, we analyze longitudinal data from two healthy samples (N = 307) to provide quasi-longitudinal insight into the full trajectory of psychological burden before (baseline), during the first peak, and at a relative downturn of the COVID-19 pandemic. Our data indicated a medium rise in psychological strain from baseline to the first peak of the pandemic (d = 0.40). Surprisingly, this was overcompensated by a large decrease of perceived burden until downturn (d = - 0.93), resulting in a positive overall effect of the COVID-19 pandemic on mental health (d = 0.44). Accounting for this paradoxical positive effect, our results reveal that the post-pandemic increase in mental health is driven by individuals that were already facing psychological challenges before the pandemic. These findings suggest that coping with acute challenges such as the COVID-19 pandemic can stabilize previously impaired mental health through reframing processes.

Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms.

Introduction: Personalization is a much-discussed approach to improve adherence and outcomes for Digital Mental Health interventions (DMHIs). Yet, major questions remain open, such as (1) what personalization is, (2) how prevalent it is in practice, and (3) what benefits it truly has. Methods: We address this gap by performing a systematic literature review identifying all empirical studies on DMHIs targeting depressive symptoms in adults from 2015 to September 2022. The search in Pubmed, SCOPUS and Psycinfo led to the inclusion of 138 articles, describing 94 distinct DMHIs provided to an overall sample of approximately 24,300 individuals. Results: Our investigation results in the conceptualization of personalization as purposefully designed variation between individuals in an intervention's therapeutic elements or its structure. We propose to further differentiate personalization by what is personalized (i.e., intervention content, content order, level of guidance or communication) and the underlying mechanism [i.e., user choice, provider choice, decision rules, and machine-learning (ML) based approaches]. Applying this concept, we identified personalization in 66% of the interventions for depressive symptoms, with personalized intervention content (32% of interventions) and communication with the user (30%) being particularly popular. Personalization via decision rules (48%) and user choice (36%) were the most used mechanisms, while the utilization of ML was rare (3%). Two-thirds of personalized interventions only tailored one dimension of the intervention. Discussion: We conclude that future interventions could provide even more personalized experiences and especially benefit from using ML models. Finally, empirical evidence for personalization was scarce and inconclusive, making further evidence for the benefits of personalization highly needed. Systematic Review Registration: Identifier: CRD42022357408.

Effective-and Tolerable: Acceptance and Side Effects of Intensified Exposure for Anxiety Disorders.

Despite striking empirical support, exposure-based treatments for anxiety disorders are underutilized. This is partially due to clinicians' concerns that patients may reject exposure or experience severe side effects, particularly in intensive forms of exposure. We examined acceptance and side effects of two randomly assigned variants of prediction error-based exposure treatment differing in temporal density (1 vs. 3 sessions/week) in 681 patients with panic disorder, agoraphobia, social anxiety disorder, and multiple specific phobias. Treatment acceptance included treatment satisfaction and credibility, engagement (i.e., homework completion), and tolerability (i.e., side effects, dropout, and perceived treatment burden). Side effects were measured with the Inventory for the Balanced Assessment of Negative Effects of Psychotherapy (INEP). We found treatment satisfaction, credibility, and engagement to be equally high in both variants of exposure-based treatment, despite higher treatment burden (ß = 0.25) and stronger side effects (ß = 0.15) in intensified treatment. 94.1% of patients reported positive effects in the INEP. 42.2% reported side effects, with treatment stigma (16.6%), low mood (14.8%) and the experience to depend on the therapist (10.9%) being the most frequently reported. The mean intensity of side effects was low. We conclude that prediction error-based exposure treatment is well accepted by patients with different anxiety disorders and that patients also tolerate temporally intensified treatment, despite higher perceived treatment burden and stronger side effects. Clinicians should be aware of the most frequent side effects to take appropriate countermeasures. In sum, temporal intensification appears to be an acceptable strategy to achieve faster symptom reduction, given patients' well-informed consent.

Mechanisms of action underlying virtual reality exposure treatment in spider phobia: Pivotal role of within-session fear reduction.

Although virtual-reality exposure treatment (VRET) for anxiety disorders is an efficient treatment option for specific phobia, mechanisms of action for immediate and sustained treatment response need to be elucidated. Towards this aim, core therapy process variables were assessed as predictors for short- and long-term VR treatment outcomes. In a bi-centric study, n = 186 patients with spider phobia completed a baseline-assessment, a one-session VRET, a post-therapy assessment, and a 6-month-follow-up assessment (ClinicalTrials.gov, ID: NCT03208400). Short- and long-term outcomes regarding self-reported symptoms in the spider phobia questionnaire (SPQ) and final patient-spider distance in the behavioral avoidance test (BAT) were predicted via logistic regression models with the corresponding baseline score, age, initial fear activation, within-session fear reduction and fear expectancy violation as predictors. To predict long-term remission status at 6-month-follow-up, dimensional short-term changes in the SPQ and BAT were additionally included. Higher within-session fear reductions predicted better treatment outcomes (long-term SPQ; short- and long-term BAT). Lower initial fear activation tended to be associated with better long-term outcomes (SPQ), while fear expectancy violation was not associated with any outcome measure. Short-term change in the SPQ predicted remission status. Findings highlight that in VRET for spider phobia, the experience of fear reduction is central for short- and long-term treatment success and should be focused by therapists.