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Food craving (FC) peaks are highly context-dependent and variable. Accurate prediction of FC might help preventing disadvantageous eating behavior. Here, we examine whether data from 2 weeks of ecological momentary assessment (EMA) questionnaires on stress and emotions (active EMA, aEMA) alongside temporal features and smartphone sensor data (passive EMA, pEMA) are able to predict FCs ~2.5 h into the future in N = 46 individuals. A logistic prediction approach with feature dimension reduction via Best Item Scale that is Cross-Validated, Weighted, Informative and Transparent (BISCWIT) was performed. While overall prediction accuracy was acceptable, passive sensing data alone was equally predictive to psychometric data. The frequency of which single predictors were considered for a model was rather balanced, indicating that aEMA and pEMA models were fully idiosyncratic.
Complex problem solving (CPS) can be interpreted as the number of psychological mechanisms that allow us to reach our targets in difficult situations, that can be classified as complex, dynamic, non-transparent, interconnected, and multilayered, and also polytelic. The previous results demonstrated associations between the personality dimensions neuroticism, conscientiousness, and extraversion and problem-solving performance. However, there are no studies dealing with personality disorders in connection with CPS skills. Therefore, the current study examines a clinical sample consisting of people with personality and/or depressive disorders. As we have data for all the potential personality disorders and also data from each patient regarding to potential depression, we meet the whole range from healthy to impaired for each personality disorder and for depression. We make use of a unique operationalization: CPS was surveyed in a simulation game, making use of the microworld approach. This study was designed to investigate the hypothesis that personality traits are related to CPS performance. Results show that schizotypal, histrionic, dependent, and depressive persons are less likely to successfully solve problems, while persons having the additional behavioral characteristics of resilience, action orientation, and motivation for creation are more likely to successfully solve complex problems.
Objective
Obesity, often associated with non-alcoholic fatty liver disease (NAFLD), is characterized by an imbalance between energy expenditure and food intake, which is also reflected by desensitization of fibroblast growth factor 21 (FGF21). FGF21 is strongly influenced, among others, by TNFα, which is known to be upregulated in obesity-induced inflammation. Successful long-term treatments of NAFLD might be dietary modification, exercise, or fasting.
Materials and methods
Whether succeeded NAFLD recovery is linked with improved FGF21 sensitivity and finally reverted FGF21 resistance was the focus of the present study. For this purpose, mice received a high-fat diet (HFD) for 6 months to establish obesity. Afterward, the mice were subjected to three different weight loss interventions, namely, dietary change to low-fat diet (LFD), treadmill training, and/or time-restricted feeding for additional 6 months, whereas one group remained on HFD.
Results
In addition to the expected decrease in NAFLD activity with dietary change, this was also observed in the HFD group with additional time-restricted feeding. There was also an associated decrease in hepatic TNFα and FGF21 expression and an increase in ß-klotho expression, demonstrated mainly by using principal component analysis. Pearson correlation analysis shows that independent of any intervention, TNFα expression decreased with improved NAFLD recovery. This was accompanied with higher FGF21 sensitivity, as expressed by an increase in β-klotho and FGFR1c expression and concomitantly decreased FGF21 levels.
Conclusion
In summary, we conclude that successful NAFLD therapy is associated with a reversion of the TNFα-triggered FGF21-resistant state or desensitization.
The early-life microbiome (ELM) interacts with the psychosocial environment, in particular during early-life adversity (ELA), defining life-long health trajectories. The ELM also plays a significant role in the maturation of the immune system. We hypothesised that, in this context, the resilience of the oral microbiomes, despite being composed of diverse and distinct communities, allows them to retain an imprint of the early environment. Using 16S amplicon sequencing on the EpiPath cohort, we demonstrate that ELA leaves an imprint on both the salivary and buccal oral microbiome 24 years after exposure to adversity. Furthermore, the changes in both communities were associated with increased activation, maturation, and senescence of both innate and adaptive immune cells, although the interaction was partly dependent on prior herpesviridae exposure and current smoking. Our data suggest the presence of multiple links between ELA, Immunosenescence, and cytotoxicity that occur through long-term changes in the microbiome.
Figural matrices tasks are one of the most prominent item formats used in intelligence tests, and their relevance for the assessment of cognitive abilities is unquestionable. However, despite endeavors of the open science movement to make scientific research accessible on all levels, there is a lack of royalty-free figural matrices tests. The Open Matrices Item Bank (OMIB) closes this gap by providing free and unlimited access (GPLv3 license) to a large set of empirically validated figural matrices items. We developed a set of 220 figural matrices based on well-established construction principles commonly used in matrices tests and administered them to a sample of N = 2572 applicants to medical schools. The results of item response models and reliability analyses demonstrate the excellent psychometric properties of the items. In the discussion, we elucidate how researchers can already use the OMIB to gain access to high-quality matrices tests for their studies. Furthermore, we provide perspectives for features that could additionally improve the utility of the OMIB.
The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.
For the goal of individualized medicine, it is critical to have clinical phenotypes at hand which represent the individual pathophysiology. However, for most of the utilized phenotypes, two individuals with the same phenotype assignment may differ strongly in their underlying biological traits. In this paper, we propose a definition for individualization and a corresponding statistical operationalization, delivering thereby a statistical framework in which the usefulness of a variable in the meaningful differentiation of individuals with the same phenotype can be assessed. Based on this framework, we develop a statistical workflow to derive individualized phenotypes, demonstrating that under specific statistical constraints the prediction error of prediction scores contains information about hidden biological traits not represented in the modeled phenotype of interest, allowing thereby internal differentiation of individuals with the same assigned phenotypic manifestation. We applied our procedure to data of the population-based Study of Health in Pomerania to construct a refined definition of obesity, demonstrating the utility of the definition in prospective survival analyses. Summarizing, we propose a framework for the individualization of phenotypes aiding personalized medicine by shifting the focus in the assessment of prediction models from the model fit to the informational content of the prediction error.
Despite effective treatment approaches within the cognitive behavioral framework general treatment effects for chronic pain are rather small to very small. Translation from efficacy trials to naturalistic settings is questionable. There is an urgent need to improve the effectiveness of well-established treatments, such as cognitive-behavior therapy (CBT) and the investigation of mechanisms of change is a promising opportunity. We performed secondary data analysis from routine data of 1,440 chronic pain patients. Patients received CBT in a multidisciplinary setting in two inpatient clinics. Effect sizes and reliable change indices were computed for pain-related disability and depression. The associations between changes in the use of different pain coping skills (cognitive restructuring, activity despite pain, relaxation techniques and mental distraction) and changes in clinical outcomes were analyzed in structural equation models. Pre–post effect sizes range from g = 0.47 (disability) to g = 0.89 (depression). Changes in the use of cognitive restructuring, relaxation and to a lesser degree mental distraction were associated with changes in disability and depression. Effects from randomized trials can be translated to naturalistic settings. The results complement experimental research on mechanisms of change in the treatment of chronic pain and indicate an important role of cognitive change and relaxation as mechanisms of change. Our findings cautiously suggest that clinicians should optimize these processes in chronic pain patients to reduce their physical and emotional disability.
Abstract
During fear conditioning, a cue (CS) signals an inevitable distal threat (US) and evokes a conditioned response that can be described as attentive immobility (freezing). The organism remains motionless and monitors the source of danger while startle responses are potentiated, indicating a state of defensive hypervigilance. Although in animals vagally mediated fear bradycardia is also reliably observed under such circumstances, results are mixed in human fear conditioning. Using a single‐cue fear conditioning and extinction protocol, we tested cardiac reactivity and startle potentiation indexing low‐level defensive strategies in a fear‐conditioned (n = 40; paired presentations of CS and US) compared with a non‐conditioned control group (n = 40; unpaired presentations of CS and US). Additionally, we assessed shock expectancy ratings on a trial‐by‐trial basis indexing declarative knowledge of the previous contingencies. Half of each group underwent extinction under sham or active transcutaneous vagus nerve stimulation (tVNS), serving as additional proof of concept. We found stronger cardiac deceleration during CS presentation in the fear learning relative to the control group. This learned fear bradycardia was positively correlated with conditioned startle potentiation but not with declarative knowledge of CS‐US contingencies. TVNS abolished differences in heart rate changes between both groups and removed the significant correlation between late cardiac deceleration and startle potentiation in the fear learning group. Results suggest, fear‐conditioned cues evoke attentive immobility in humans, characterized by cardiac deceleration and startle potentiation. Such defensive response pattern is elicited by cues predicting inevitable distal threat and resembles conditioned fear responses observed in rodents.
Background: Alexithymia is a personality trait characterized by difficulties in identifying and describing emotions and associated with various psychiatric disorders. Neuroimaging studies found evidence for morphological and functional brain alterations in alexithymic subjects. However, the neurobiological mechanisms underlying alexithymia remain incompletely understood. Methods: We study the association of alexithymia with cortical correlation networks in a large community-dwelling sample of the Study of Health in Pomerania. Our analysis includes data of n = 2,199 individuals (49.4% females, age = 52.1 ± 13.6 years) which were divided into a low and high alexithymic group by a median split of the Toronto Alexithymia Scale. Cortical correlation networks were constructed based on the mean thicknesses of 68 regions, and differences in centralities were investigated. Results: We found a significantly increased centrality of the right paracentral lobule in the high alexithymia network after correction for multiple testing. Several other regions with motoric and sensory functions showed altered centrality on a nominally significant level. Conclusions: Finding increased centrality of the paracentral lobule, a brain area with sensory as well as motoric features and involvement in bowel and bladder voiding, may contribute to explain the association of alexithymia with functional somatic disorders and chronic pain syndromes.
In Germany, large, population-based cohort studies have been implemented in order to identify risk and protective factors for maintaining health across the life span. The purpose of this systematic review is to analyse findings from three large ongoing cohorts and to identify sex-specific prevalence rates, risk and protective factors for mental health. Published studies from the Cooperative Health Research in the Region Augsburg (KORA), the Study of Health in Pomerania (SHIP) and the Gutenberg Health Study (GHS)), representing the southern, north-eastern and middle parts of Germany, were identified through searches of the databases PubMed and Web of Science. A total of 52 articles was identified from the start of each cohort until June 2019. Articles reporting prevalence rates of mental health [N = 22], explanatory factors for mental health [N = 25], or both [N = 5] were identified. Consistent across cohorts, higher prevalence rates of internalizing disorders were found for women and more externalizing disorders for men. Risk and protective factors for mental health included social factors, lifestyle, physical health, body mass index (BMI), diabetes, genetic and biological factors. In all areas, differences and similarities were found between women and men. The most evident were the sex-specific risk profiles for depression with mostly external risk factors for men and internal risk factors for women. Gender was not assessed directly, therefore we examined whether socioeconomic and family-related factors reflecting gender roles or institutionalized gender could be used as a proxy for gender. Overall, this systematic review shows differences and similarities in prevalence rates and determinants of mental health indicators between women and men. They underline the importance of focussing on sex specific approaches in mental health research and in the development of prevention measures. Current research on mental health still lacks focus on gender aspects. Therefore, an increased focus on sex and gender in mental health research is of great importance.
Objective: Little is known about the specific psychological features that differentiate persistent depressive disorder (PDD) and episodic depression (ED). Thus, the present study aimed to investigate differences in social cognition and interpersonal problems between these two forms of depression and healthy controls. In addition, we aimed to examine childhood maltreatment (CM) as a possible origin of these alterations.
Methods: In a cross-sectional study, adult patients with a current PDD (n = 34) or in a current episode of ED (n = 38), and healthy controls (n = 39) completed questionnaires about depression severity, empathy, interpersonal problems, and CM, as well as tests of affective theory of mind and facial emotion recognition.
Results: Patients with PDD reported higher empathic distress than patients with ED and healthy controls. Both depressive groups recognized angry faces with higher accuracy and reported more interpersonal problems, with no differences between PDD and ED. Empathic distress and interpersonal problems mediated the link between CM and depression in the combined sample.
Limitations: Patient groups were not drug-naïve and antidepressant intake might have influenced social-cognitive functions. Self-report measures of empathy and interpersonal problems are vulnerable to bias. The cross-sectional design does not allow causal conclusions.
Conclusion: Depressed patients may not show deficits in decoding the affective states of others and in feeling with others. However, depressed individuals—in particular patients with PDD—may feel easily overwhelmed by emotionally tense situations, resulting in empathic distress and avoidant/submissive interpersonal behavior. Exposure to CM might be an origin of alterations in social cognition and interpersonal problems.
Patient-reported outcomes (PROs) refer to any report coming directly from patients about how they function or feel in relation to a health condition or its therapy. PROs have been applied in medicine for the assessment of the impact of clinical phenomena. Self-report scales and procedures for assessing physical pain in adults have been developed and used in clinical trials. However, insufficient attention has been dedicated to the assessment of mental pain. The aim of this paper is to outline the implications that assessment of mental pain may entail in psychiatry and medicine, with particular reference to a clinimetric index. A simple 10-item self-rating questionnaire, the Mental Pain Questionnaire (MPQ), encompasses the specific clinical features of mental pain and shows good clinimetric properties (i.e., sensitivity, discriminant and incremental validity). The preliminary data suggest that the MPQ may qualify as a PRO measure to be included in clinical trials. Assessment of mental pain may have important clinical implications in intervention research, both in psychopharmacology and psychotherapy. The transdiagnostic features of mental pain are supported by its association with a number of psychiatric disorders, such as depression, anxiety, eating disorders, as well as borderline personality disorder. Further, addressing mental pain may be an important pathway to prevent and diminish the opioid epidemic. The data summarized here indicate that mental pain can be incorporated into current psychiatric assessment and included as a PRO measure in treatment outcome studies.
Background: Self-stigma is a result of internalizing negative stereotypes by the affected person. Research on self-stigma in substance use disorders (SUD) is still scarce, especially regarding the role of childhood trauma and subsequent posttraumatic disorders. Objectives: The present study investigated the progressive model of self-stigma in women with SUD and posttraumatic stress disorder (PTSD), and the predictive value of PTSD severity and childhood trauma experiences on self-stigma. Method: In a cross-sectional study with 343 women with SUD and PTSD, we used the Self-Stigma in Alcohol Dependency Scale, the Childhood Trauma Questionnaire (CTQ), the PTSD Symptom Scale Interview (PSS-I), and to control for SUD severity and depression, the Addiction Severity Index Lite and the Beck Depression Inventory-II. Hierarchical regression analyses were conducted for each stage of self-stigma (aware-agree-apply-harm). Results: The interrelated successive stages of self-stigma were largely confirmed. In the regression models, no significant effects of the PSS-I- and the CTQ-scores were observed at any stage of self-stigma. Agreeing with negative stereotypes was solely predicted by younger age, applying these stereotypes to oneself was higher in women with younger age, higher depression and SUD severity, and suffering from the application (harm) was only predicted by depression. Conclusions: The progressive model of self-stigma could be confirmed in women with SUD and PTSD, but PTSD severity and childhood trauma did not directly affect this process. Self-stigma appears to be related to depression in a stronger way than PTSD is related to women with SUD and PTSD.
Background: Self-stigma is a result of internalizing negative stereotypes by the affected person. Research on self-stigma in substance use disorders (SUD) is still scarce, especially regarding the role of childhood trauma and subsequent posttraumatic disorders. Objectives: The present study investigated the progressive model of self-stigma in women with SUD and posttraumatic stress disorder (PTSD), and the predictive value of PTSD severity and childhood trauma experiences on self-stigma. Method: In a cross-sectional study with 343 women with SUD and PTSD, we used the Self-Stigma in Alcohol Dependency Scale, the Childhood Trauma Questionnaire (CTQ), the PTSD Symptom Scale Interview (PSS-I), and to control for SUD severity and depression, the Addiction Severity Index Lite and the Beck Depression Inventory-II. Hierarchical regression analyses were conducted for each stage of self-stigma (aware-agree-apply-harm). Results: The interrelated successive stages of self-stigma were largely confirmed. In the regression models, no significant effects of the PSS-I- and the CTQ-scores were observed at any stage of self-stigma. Agreeing with negative stereotypes was solely predicted by younger age, applying these stereotypes to oneself was higher in women with younger age, higher depression and SUD severity, and suffering from the application (harm) was only predicted by depression. Conclusions: The progressive model of self-stigma could be confirmed in women with SUD and PTSD, but PTSD severity and childhood trauma did not directly affect this process. Self-stigma appears to be related to depression in a stronger way than PTSD is related to women with SUD and PTSD.
Introduction: It has been shown that Alzheimer’s disease (AD) is accompanied by marked structural brain changes that can be detected several years before clinical diagnosis via structural magnetic resonance (MR) imaging. In this study, we developed a structural MR-based biomarker for in vivo detection of AD using a supervised machine learning approach. Based on an individual’s pattern of brain atrophy a continuous AD score is assigned which measures the similarity with brain atrophy patterns seen in clinical cases of AD.
Methods: The underlying statistical model was trained with MR scans of patients and healthy controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI-1 screening). Validation was performed within ADNI-1 and in an independent patient sample from the Open Access Series of Imaging Studies (OASIS-1). In addition, our analyses included data from a large general population sample of the Study of Health in Pomerania (SHIP-Trend).
Results: Based on the proposed AD score we were able to differentiate patients from healthy controls in ADNI-1 and OASIS-1 with an accuracy of 89% (AUC = 95%) and 87% (AUC = 93%), respectively. Moreover, we found the AD score to be significantly associated with cognitive functioning as assessed by the Mini-Mental State Examination in the OASIS-1 sample after correcting for diagnosis, age, sex, age·sex, and total intracranial volume (Cohen’s f2 = 0.13). Additional analyses showed that the prediction accuracy of AD status based on both the AD score and the MMSE score is significantly higher than when using just one of them. In SHIP-Trend we found the AD score to be weakly but significantly associated with a test of verbal memory consisting of an immediate and a delayed word list recall (again after correcting for age, sex, age·sex, and total intracranial volume, Cohen’s f2 = 0.009). This association was mainly driven by the immediate recall performance.
Discussion: In summary, our proposed biomarker well differentiated between patients and healthy controls in an independent test sample. It was associated with measures of cognitive functioning both in a patient sample and a general population sample. Our approach might be useful for defining robust MR-based biomarkers for other neurodegenerative diseases, too.