A 2-year longitudinal study of neuropsychological functioning, psychosocial adjustment and rehospitalisation in schizophrenia and major depression

Neuropsychological functioning turns out to be a rate-limiting factor in psychiatry. However, little is known when comparing neuropsychological and psychosocial functioning in inpatients with schizophrenia or severe depression in their treatment pathways including add-on psychoeducation or the latter combined with cognitive behavioral therapy up to 2-year follow-up. To evaluate this question, we investigated these variables in two randomised controlled trials including 196 patients with DSM-IV schizophrenia and 177 patients with major depression. Outcome measures were assessed in the hospital at pre- and posttreatment and following discharge until 2-year follow-up. We focused on neuropsychological and psychosocial functioning regarding its differences and changes over time in data of two pooled trials. There were significant time effects indicating gains in knowledge about the illness, short and medium-term memory (VLMT) and psychosocial functioning (GAF), however, the latter was the only variable showing a time x study/diagnosis interaction effect at 2-year follow-up, showing significant better outcome in depression compared to schizophrenia. Moderator analysis showed no changes in psychosocial and neuropsychological functioning in schizophrenia and in affective disorders due to age, duration of illness or sex. Looking at the rehospitalisation rates there were no significant differences between both disorders. Both groups treated with psychoeducation or a combination of psychoeducation and CBT improved in neuropsychological and psychosocial functioning as well as knowledge about the illness at 2-year follow-up, however, patients with major depression showed greater gains in psychosocial functioning compared to patients with schizophrenia. Possible implications of these findings were discussed

Effects of bifrontal transcranial direct current stimulation on brain glutamate levels and resting state connectivity: multimodal MRI data for the cathodal stimulation site

Transcranial direct current stimulation (tDCS) over prefrontal cortex (PFC) regions is currently proposed as therapeutic intervention for major depression and other psychiatric disorders. The in-depth mechanistic understanding of this bipolar and non-focal stimulation technique is still incomplete. In a pilot study, we investigated the effects of bifrontal stimulation on brain metabolite levels and resting state connectivity under the cathode using multiparametric MRI techniques and computational tDCS modeling. Within a double-blind cross-over design, 20 subjects (12 women, 23.7 ± 2~years) were randomized to active tDCS with standard bifrontal montage with the anode over the left dorsolateral prefrontal cortex (DLPFC) and the cathode over the right DLPFC. Magnetic resonance spectroscopy (MRS) was acquired before, during, and after prefrontal tDCS to quantify glutamate (Glu), Glu + glutamine (Glx) and gamma aminobutyric acid (GABA) concentration in these areas. Resting-state functional connectivity MRI (rsfcMRI) was acquired before and after the stimulation. The individual distribution of tDCS induced electric fields (efields) within the MRS voxel was computationally modelled using SimNIBS 2.0. There were no significant changes of Glu, Glx and GABA levels across conditions but marked differences in the course of Glu levels between female and male participants~were observed. Further investigation yielded a significantly stronger Glu reduction after active compared to sham stimulation~in female participants, but not in male participants. For rsfcMRI neither significant changes nor correlations with MRS data were observed. Exploratory analyses of the effect of efield intensity distribution on Glu changes showed distinct effects in different efield groups. Our findings are limited by the small sample size, but correspond to previously published results of cathodal tDCS. Future studies should address gender and efield intensity as moderators of tDCS induced effects

Neurofunctional differences and similarities between persistent postural-perceptual dizziness and anxiety disorder

Introduction: Persistent postural-perceptual dizziness (PPPD) (ICD-11) and anxiety disorders (ANX) share behavioural symptoms like anxiety, avoidance, social withdrawal, hyperarousal, or palpitation as well as neurological symptoms like vertigo, stance and gait disorders. Furthermore, previous studies have shown a bidirectional link between vestibulo-spatial and anxiety neural networks. So far, there have been no neuroimaging-studies comparing these groups. Objectives: The aim of this explorative study was to investigate differences and similarities of neural correlates between these two patient groups and to compare their findings with a healthy control group. Methods: 63 participants, divided in two patient groups (ANX = 20 and PPPD = 14) and two sex and age matched healthy control groups (HC-A = 16, HC-P = 13) were included. Anxiety and dizziness related pictures were shown during fMRI-measurements in a block-design in order to induce emotional responses. All subjects filled in questionnaires regarding vertigo (VSS, VHQ), anxiety (STAI), depression (BDI-II), alexithymia (TAS), and illness-perception (IPQ). After modelling the BOLD response with a standard canonical HRF, voxel-wise t-tests between conditions (emotional-negative vs neutral stimuli) were used to generate statistical contrast maps and identify relevant brain areas (pFDR 30 voxels). ROI-analyses were performed for amygdala, cingulate gyrus, hippocampus, inferior frontal gyrus, insula, supramarginal gyrus and thalamus (p ≤ 0.05). Results: Patient groups differed from both HC groups regarding anxiety, dizziness, depression and alexithymia scores; ratings of the PPPD group and the ANX group did differ significantly only in the VSS subscale ‘vertigo and related symptoms’ (VSS-VER). The PPPD group showed increased neural responses in the vestibulo-spatial network, especially in the supramarginal gyrus (SMG), and superior temporal gyrus (STG), compared to ANX and HC-P group. The PPPD group showed increased neural responses compared to the HC-P group in the anxiety network including amygdala, insula, lentiform gyrus, hippocampus, inferior frontal gyrus (IFG) and brainstem. Neuronal responses were enhanced in visual structures, e.g. fusiform gyrus, middle occipital gyrus, and in the medial orbitofrontal cortex (mOFC) in healthy controls compared to patients with ANX and PPPD, and in the ANX group compared to the PPPD group. Conclusions: These findings indicate that neuronal responses to emotional information in the PPPD and the ANX group are comparable in anxiety networks but not in vestibulo-spatial networks. Patients with PPPD revealed a stronger neuronal response especially in SMG and STG compared to the ANX and the HC group. These results might suggest higher sensitivity and poorer adaptation processes in the PPPD group to anxiety and dizziness related pictures. Stronger activation in visual processing areas in HC subjects might be due to less emotional and more visual processing strategies

Loneliness, Social Isolation and Their Difference: A Cross-Diagnostic Study in Persistent Depressive Disorder and Borderline Personality Disorder

Background: Interpersonal difficulties are a key feature of persistent depressive disorder (PDD) and borderline personality disorder (BPD). Caught in a vicious circle of dysfunctional interpersonal transaction, PDD and BPD patients are at great risk of experiencing prolonged loneliness. Loneliness, in turn, has been associated with the development of mental disorders and chronic illness trajectories. Besides, several factors may contribute to the experience of loneliness across the lifespan, such as social network characteristics, a history of childhood maltreatment (CM), and cognitive-affective biases such as rejection sensitivity (RS). This cross-diagnostic study approached the topic of perceived loneliness by comparing PDD and BPD patients with healthy controls (HC) in its interplay with symptom burden, social network characteristics, RS as well as CM. Method: Thirty-four PDD patients (DSM-5; 15 female, Mage = 38.2, SD = 12.3), 36 BPD patients (DSM-5; 19 female, Mage = 28.8, SD = 9.2), and 70 age- and gender-matched HC were assessed cross-sectionally using the following self-report measures: UCLA Loneliness Scale, Social Network Index (SNI; size, diversity, and embeddedness), Beck Depression Inventory (BDI-II), Borderline Symptom List (BSL-23), Childhood Trauma Questionnaire (CTQ), and Rejection Sensitivity Questionnaire (RSQ). Results: Both patient groups reported significantly higher levels of perceived loneliness, symptom severity, and smaller social network characteristics compared to HC. Loneliness was significantly correlated with severity of self-reported clinical symptoms in PDD and at trend level in BPD. Besides, loneliness tended to be related to social network characteristics for all groups except PDD patients. Both PDD and BPD patients showed higher RS as well as CTQ scores than HC. A history of emotional abuse and emotional neglect was associated with loneliness, and this association was mediated by RS as demonstrated by an exploratory mediation analysis. Discussion: Loneliness is highly prevalent in PDD and BPD patients and contributes to the overall symptom burden. Interestingly, loneliness showed an association with prior experiences of CM as well as current RS. We therefore propose a comprehensive model on how intra- und interpersonal aspects may interplay in the dynamics of loneliness in light of CM. Finally, this model may have further implications for psychotherapeutic interventions

Menschen mit Migrationsgeschichte in der COVID-19-Pandemie

Einleitung: Nicht nur Risiken für eine SARS-CoV-2-Infektion und schwere bis tödliche Verläufe sind sozial ungleich verteilt, sondern auch Arbeitsplatz- und Einkommensverluste infolge der Eindämmungsmaßnahmen. Für Menschen mit Migrationsgeschichte zeigen sich ebenfalls erhöhte Risiken, von solchen indirekten sozioökonomischen Pandemiefolgen betroffen zu sein. Ziel dieses Beitrages ist es, Zusammenhänge zwischen indirekten sozioökonomischen Pandemiefolgen und der Lebenszufriedenheit von Menschen mit ausgewählten Staatsangehörigkeiten zu untersuchen. Methoden: Analysiert wurden Daten der multimodalen, mehrsprachigen Befragungsstudie Gesundheit in Deutschland aktuell: Fokus (GEDA Fokus), die von 11/2021 bis 05/2022 unter Menschen mit italienischer, kroatischer, polnischer, syrischer oder türkischer Staatsangehörigkeit deutschlandweit durchgeführt wurde. In multivariablen Poisson-Regressionen werden Zusammenhänge zwischen Geschlecht, Alter, Bildung, Einkommen, Deutschkenntnissen sowie Arbeitsplatz- und Einkommensverlusten und der Lebenszufriedenheit untersucht. Ergebnisse: Von 4114 Teilnehmenden berichten 64,4 % eine hohe Lebenszufriedenheit. Während ein hohes Einkommen positiv mit einer hohen Lebenszufriedenheit assoziiert ist, zeigen sich negative Assoziationen bei selbst als schlecht eingeschätzten Deutschkenntnissen sowie bei mit hoher Wahrscheinlichkeit erwarteten bzw. bereits eingetretenen Arbeitsplatz- und Einkommensverlusten. Diskussion: Der Beitrag zeigt, dass die Lebenszufriedenheit, die für eine Reihe gesundheitlicher Outcomes relevant ist, bei denjenigen geringer ist, die von Arbeitsplatz- und Einkommensverlusten betroffen sind. Es gilt, strukturelle Ursachen sozioökonomischer Benachteiligung abzubauen, um gesundheitliche Ungleichheiten zu adressieren und für künftige Krisen besser gewappnet zu sein.Introduction: It is not only the risks of SARS-CoV‑2 infection and severe to fatal courses of the disease that are socially unequally distributed, but also job and income losses as a result of the containment measures. People with a history of migration are at increased risk of being affected by such indirect socio-economic effects of the pandemic as well. The aim of this article is to investigate the associations between indirect socio-economic effects of the pandemic and life satisfaction among people with selected citizenships. Methods: We analysed data from the multilingual and multimodal interview survey German Health Update Fokus (Gesundheit in Deutschland aktuell: Fokus; GEDA Fokus), which was conducted from November 2021 to May 2022 among people all over Germany with Croatian, Italian, Polish, Syrian or Turkish citizenship. Using multivariable Poisson regression, we analysed associations between sex, age, education, income, German language proficiency and job as well as income losses and life satisfaction. Results: Of the 4114 participants, 64.4% reported a high life satisfaction. While a higher income showed positive associations with life satisfaction, negative associations were found for lower self-assessed German language proficiency and for job and income losses that are anticipated or have already occurred. Discussion: This article shows that life satisfaction, which is relevant for multiple health outcomes, is lower among those that are affected by job and income losses. Structural causes of socio-economic disadvantages need to be reduced to address health inequalities and to be better prepared for future crises

Examining the synergistic effects of a cognitive control video game and a home-based, self-administered non-invasive brain stimulation on alleviating depression : the DiSCoVeR trial protocol

Funding Information: Open Access funding enabled and organized by Projekt DEAL. The DisCoVeR project is funded by ERA NET NEURON. The NEURON ‘Network of European Funding for Neuroscience Research is established under the organization of the ERA-NET ‘European Research Area Networks’ of the European Commission. National funding agencies are the Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung [BMBF]) for LMU Munich, the Ministry of Health (MOH) for HUJI and Hadassah, the Swiss National Science Foundation (SNSF) for UNIGE and EPFL and the State Education and Development Agency (VIAA) of Latvia for RSU. Funding Information: This project was funded by the European Research Area Network (ERA-NET) NEURON 2018 Mental Disorders program. Publisher Copyright: © 2022, The Author(s).Enhanced behavioral interventions are gaining increasing interest as innovative treatment strategies for major depressive disorder (MDD). In this study protocol, we propose to examine the synergistic effects of a self-administered home-treatment, encompassing transcranial direct current stimulation (tDCS) along with a video game based training of attentional control. The study is designed as a two-arm, double-blind, randomized and placebo-controlled multi-center trial (ClinicalTrials.gov: NCT04953208). At three study sites (Israel, Latvia, and Germany), 114 patients with a primary diagnosis of MDD undergo 6 weeks of intervention (30 × 30 min sessions). Patients assigned to the intervention group receive active tDCS (anode F3 and cathode F4; 2 mA intensity) and an action-like video game, while those assigned to the control group receive sham tDCS along with a control video game. An electrode-positioning algorithm is used to standardize tDCS electrode positioning. Participants perform their designated treatment at the clinical center (sessions 1-5) and continue treatment at home under remote supervision (sessions 6-30). The endpoints are feasibility (primary) and safety, treatment efficacy (secondary, i.e., change of Montgomery-Åsberg Depression Rating Scale (MADRS) scores at week six from baseline, clinical response and remission, measures of social, occupational, and psychological functioning, quality of life, and cognitive control (tertiary). Demonstrating the feasibility, safety, and efficacy of this novel combined intervention could expand the range of available treatments for MDD to neuromodulation enhanced interventions providing cost-effective, easily accessible, and low-risk treatment options.ClinicalTrials.gov: NCT04953208.publishersversionPeer reviewe

Empowerment group therapy for refugees with affective disorders: results of a multi-center randomized controlled trial

Background Against the background of missing culturally sensitive mental health care services for refugees, we developed a group intervention (Empowerment) for refugees at level 3 within the stratified Stepped and Collaborative Care Model of the project Mental Health in Refugees and Asylum Seekers (MEHIRA). We aim to evaluate the effectiveness of the Empowerment group intervention with its focus on psychoeducation, stress management, and emotion regulation strategies in a culturally sensitive context for refugees with affective disorders compared to treatment-as-usual (TAU). Method At level 3 of the MEHIRA project, 149 refugees and asylum seekers with clinically relevant depressive symptoms were randomized to the Empowerment group intervention or TAU. Treatment comprised 16 therapy sessions conducted over 12 weeks. Effects were measured with the Patient Health Questionnaire-9 (PHQ-9) and the Montgomery–Åsberg Depression Rating Scale (MÅDRS). Further scales included assessed emotional distress, self-efficacy, resilience, and quality of life. Results Intention-to-treat analyses show significant cross-level interactions on both self-rated depressive symptoms (PHQ-9; F(1,147) = 13.32, p < 0.001) and clinician-rated depressive symptoms (MÅDRS; F(1,147) = 6.91, p = 0.01), indicating an improvement in depressive symptoms from baseline to post-intervention in the treatment group compared to the control group. The effect sizes for both scales were moderate (d = 0.68, 95% CI 0.21–1.15 for PHQ-9 and d = 0.51, 95% CI 0.04–0.99 for MÅDRS). Conclusion In the MEHIRA project comparing an SCCM approach versus TAU, the Empowerment group intervention at level 3 showed effectiveness for refugees with moderately severe depressive symptoms

Personalizing transcranial direct current stimulation for treating major depressive disorder

Transcranial direct current stimulation (tDCS) is a safe and efficient intervention for treating major depressive disorder (MDD). However, research has suggested heterogeneity of response between patients. The emerging field of precision psychiatry aims to use statistical modeling of multi-modal data to tailor treatment to the single patient. To this end, more in-depth analysis of randomized controlled trials (RCTs) will be relevant (1) due to limited availability of other large datasets with high phenotypic detail and (2) to develop tools for personalization within counterfactually controlled environments (i.e. experimental designs with sham intervention and/or active treatment comparison) to distinguish specific vs. non-specific patterns in treatment data. Previous research has aimed at identifying patient-related factors associated with better response. However, most analyses have operated on the group-level, ignoring natural clusters within the patients' constituting factors, their individual trajectories of symptom improvement, and their presented symptoms. Furthermore, group-based modeling strategies were limited to explanatory approaches using in-sample hypothesis-testing, that are ill-suited to prognosticate outcomes of single patients. This dissertation provides a methodological framework for reevaluation of existing clinical trial data (1) to provide future investigations with more differentiated units of analysis and (2) to complement explanatory approaches with predictive modeling strategies enabling prediction of single-patient outcomes. Using data from a landmark 3-arm clinical trial paradigmatic for a rigorously controlled experimental design (10-week treatment of tDCS vs. escitalopram vs. placebo) the dissertation provides three blueprint studies for modeling heterogeneity of tDCS response: Study 1 characterized response to tDCS by considering patient-individual dynamics of symptom change over the course of treatment. Distinct trajectories of tDCS response could be identified (rapid-, slow-, and no/minimal improvement), representing patient subgroups with varying strength and speed of improvement. These results suggest development of individualized treatment protocols and exploration of prolonged treatment courses. Study 2 reevaluated the efficacy of tDCS, in distinct, naturally occurring clusters of depressive symptoms. Using unsupervised machine learning (ML), a global depression measure (HAM-D) was parsed into 4 distinct symptom clusters. Analysis of cluster-scores showed superiority of tDCS and escitalopram over placebo in core depressive symptoms, but only tDCS was superior in improving sleep and only escitalopram was superior in improving guilt/anxiety symptoms, suggesting treatment selection based on patients' symptom profiles. In Study 3 supervised ML algorithms were employed to predict response to tDCS. In this proof-of-concept approach, response could be predicted above chance on the single-patient level, but overall accuracy was modest. Features employed for model training were explored using interpretable ML methods. Trained algorithms were provided to the field for expansion as well as tests of generalizability and incremental utility. The presented studies illustrate how in-depth secondary analyses of clinical trial data can aid personalization of treatment. The provided methodological framework can be expanded (options are discussed) and generalized to other contexts and interventions that show heterogeneity of treatment effects. Yet, the empirical studies also epitomize challenges precision psychiatry is faced with, including low data availability, low outcome granularity, and limited external validation opportunities. The dissertation concludes with a discussion of challenges and future directions resulting from infrastructural demands in data acquisition, data management, data sharing, and interdisciplinary collaboration

A combined local search and integer programming approach to the traveling tournament problem

The traveling tournament problem is a well-known combinatorial optimization problem with direct applications to sport leagues scheduling, that sparked intensive algorithmic research over the last decade. With the Challenge Traveling Tournament Instances as an established benchmark, the most successful approaches to the problem use meta-heuristics like tabu search or simulated annealing, partially heavily parallelized. Integer programming based methods on the other hand are hardly able to tackle larger benchmark instances. In this work we present a hybrid approach that draws on the power of commercial integer programming solvers as well as the speed of local search heuristics. Our proposed method feeds the solution of one algorithm phase to the other one, until no further improvements can be made. The applicability of this method is demonstrated experimentally on the galaxy instance set, resulting in currently best known solutions for most of the considered instances

Solving the traveling tournament problem by packing three-vertex paths

The Traveling Tournament Problem (TTP) is a complex problem in sports scheduling whose solution is a schedule of home and away games meeting specific feasibility requirements, while minimizing the total distance traveled by all the teams. A recently-developed "hybrid" algorithm, combining local search and integer programming, has resulted in best-known solutions for many TTP instances. In this paper, we tackle the TTP from a graph-theoretic perspective, by generating a new "canonical" schedule in which each team's threegame road trips match up with the underlying graph's minimum-weight P3-packing. By using this new schedule as the initial input for the hybrid algorithm, we develop tournament schedules for five benchmark TTP instances that beat all previously-known solutions