Boosting arousal and cognitive performance through alternating posture: Insights from a multi-method laboratory study.

This study investigated the role of arousal and effort costs in the cognitive benefits of alternating between sitting and standing postures using a sit-stand desk, while measuring executive functions, self-reports, physiology, and neural activity in a 2-h laboratory session aimed to induce mental fatigue. Two sessions were conducted with a one-week gap, during which participants alternated between sitting and standing postures each 20-min block in one session and remained seated in the other. In each block, inhibition, switching, and updating were assessed.

Self-regulation profiles in addictive behaviors among adolescents: A transdiagnostic approach.

Dual-pathway models suggest that poor self-regulation (immature regulatory combined with strong reactive processes) is an important factor underlying addictive behaviors among adolescents. This study examined whether there are different self-regulation profiles among community adolescents, and how these profiles are related to the presence, severity and comorbidity of different addictive behaviors. A community sample of 341 adolescents (54.

Clusterwise Independent Component Analysis (C-ICA): Using fMRI resting state networks to cluster subjects and find neurofunctional subtypes.

Background: FMRI resting state networks (RSNs) are used to characterize brain disorders. They also show extensive heterogeneity across patients. Identifying systematic differences between RSNs in patients, i.

Effectiveness of an online self-help program, expert-patient support, and their combination for eating disorders: Results from a randomized controlled trial.

Objective: Many individuals with an eating disorder do not receive appropriate care. Low-threshold interventions could help bridge this treatment gap. The study aim was to evaluate the effectiveness of Featback, a fully automated online self-help intervention, online expert-patient support and their combination.

The Different Faces of (High) Sensitivity, Toward a More Comprehensive Measurement Instrument. Development and Validation of the Sensory Processing Sensitivity Questionnaire (SPSQ).

The main purpose of the study was the development of the Sensory Processing Sensitivity Questionnaire (SPSQ), designed to measure Sensory Processing Sensitivity, defined as a person's sensitivity to subtle stimuli, the depth with which these stimuli are processed, and its impact on emotional reactivity. The item pool generated for the development of the SPSQ consisted of 60 items. After exploratory factor analysis, 43 items remained, divided into six specific factors: (1) Sensory Sensitivity to Subtle Internal and External Stimuli, (2) Emotional and Physiological Reactivity, (3) Sensory Discomfort, (4) Sensory Comfort, (5) Social-Affective Sensitivity, and (6) Esthetic Sensitivity.

Assessing the Effects of a Real-Life Contact Intervention on Prejudice Toward LGBT People.

Prejudice against sexual and gender minorities (e.g., LGBT people) is quite prevalent and is harmful.

Neurobiological correlates of antisociality across adolescence and young adulthood: a multi-sample, multi-method study.

Background: Antisociality across adolescence and young adulthood puts individuals at high risk of developing a variety of problems. Prior research has linked antisociality to autonomic nervous system and endocrinological functioning. However, there is large heterogeneity in antisocial behaviors, and these neurobiological measures are rarely studied conjointly, limited to small specific studies with narrow age ranges, and yield mixed findings due to the type of behavior examined.

Hybrid Harmony: A Multi-Person Neurofeedback Application for Interpersonal Synchrony.

Recent years have seen a dramatic increase in studies measuring brain activity, physiological responses, and/or movement data from multiple individuals during social interaction. For example, so-called "hyperscanning" research has demonstrated that brain activity may become synchronized across people as a function of a range of factors. Such findings not only underscore the potential of hyperscanning techniques to capture meaningful aspects of naturalistic interactions, but also raise the possibility that hyperscanning can be leveraged as a tool to help improve such naturalistic interactions.

Predictors of quality of life among youths in foster care-a 5-year prospective follow-up study.

Purpose: Few studies have investigated possible predictors of positive outcomes for youths in foster care. The aim of this prospective follow-up study was to examine quality of life (QoL) among youths in foster care and to assess whether contextual and child factors predicted QoL.

Methods: Online questionnaires were completed by carers in Norway in 2012 (T1, n = 236, child age 6-12 years) and by youths and carers in 2017 (T2, n = 405, youth age 11-18 years).

Placebo Effects in the Neuroendocrine System: Conditioning of the Oxytocin Responses.

Objective: There is evidence that placebo effects may influence hormone secretion. However, few studies have examined placebo effects in the endocrine system, including oxytocin placebo effects. We studied whether it is possible to trigger oxytocin placebo effects using a classical conditioning paradigm.

Exploring Mediators of a Guided Web-Based Self-Help Intervention for People With HIV and Depressive Symptoms: Randomized Controlled Trial.

Background: Cognitive behavioral therapy (CBT) is frequently used to treat depressive symptoms in people living with HIV. We developed an internet-based cognitive behavioral intervention for people with HIV and depressive symptoms, which was based on an effective self-help booklet. The Web-based intervention was previously found to be effective.

Fusing metabolomics data sets with heterogeneous measurement errors.

Combining different metabolomics platforms can contribute significantly to the discovery of complementary processes expressed under different conditions. However, analysing the fused data might be hampered by the difference in their quality. In metabolomics data, one often observes that measurement errors increase with increasing measurement level and that different platforms have different measurement error variance.

Heart work after errors: Behavioral adjustment following error commission involves cardiac effort.

Posterror slowing (PES) is the observation that people respond slower on trials subsequent to error commissions than on trials subsequent to correct responses. Different accounts have been proposed to explain PES. On the one hand, it has been suggested that PES arises from an adaptive increase in cognitive control following error commission, thereby making people more cautious after making an error.

Principal Covariates Clusterwise Regression (PCCR): Accounting for Multicollinearity and Population Heterogeneity in Hierarchically Organized Data.

In the behavioral sciences, many research questions pertain to a regression problem in that one wants to predict a criterion on the basis of a number of predictors. Although in many cases, ordinary least squares regression will suffice, sometimes the prediction problem is more challenging, for three reasons: first, multiple highly collinear predictors can be available, making it difficult to grasp their mutual relations as well as their relations to the criterion. In that case, it may be very useful to reduce the predictors to a few summary variables, on which one regresses the criterion and which at the same time yields insight into the predictor structure.

Psychological distress and cognitive coping in pregnant women diagnosed with cancer and their partners.

Objective: A cancer diagnosis during pregnancy may be considered as an emotional challenge for pregnant women and their partners. We aimed to identify women and partners at risk for high levels of distress based on their coping profile.

Methods: Sixty-one pregnant women diagnosed with cancer and their partners filled out the Cognitive Emotion Regulation Questionnaire (CERQ) and the newly constructed Cancer and Pregnancy Questionnaire (CPQ).

Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes.

Protein interaction in cells can be described at different levels. At a low interaction level, proteins function together in small, stable complexes and at a higher level, in sets of interacting complexes. All interaction levels are crucial for the living organism, and one of the challenges in proteomics is to measure the proteins at their different interaction levels.

MultiLevel simultaneous component analysis: A computational shortcut and software package.

MultiLevel Simultaneous Component Analysis (MLSCA) is a data-analytical technique for multivariate two-level data. MLSCA sheds light on the associations between the variables at both levels by specifying separate submodels for each level. Each submodel consists of a component model.

Personality profiles in Eating Disorders: further evidence of the clinical utility of examining subtypes based on temperament.

Despite recent modifications to the DSM-V diagnostic criteria for Eating Disorders (ED; American Psychiatric Association, 2013), sources of variability in the clinical presentation of ED patients remain poorly understood. Consistent with previous research that has used underlying personality dimensions to identify distinct subgroups of ED patients, the present study examined (1) whether we could identify clinically meaningful subgroups of patients based on temperamental factors including Behavioral Inhibition (BIS), Behavioral Activation (BAS) and Effortful Control (EC), and (2) whether the identified subgroups would also differ with respect to ED, Axis-I and Axis-II psychopathology. One hundred and forty five ED inpatients participated in this study.

Temperament subtypes in treatment seeking obese individuals: a latent profile analysis.

Objective: This study aimed to investigate temperament subtypes in obese patients.

Methods: Ninety-three bariatric surgery candidates and 63 obese inpatients from a psychotherapy unit answered the Behavioral Inhibition System/Behavioral Activation System Scale (BIS/BAS), the Effortful Control subscale of the Adult Temperament Questionnaire-Short Form (ATQ-EC), and questionnaires for eating disorder, depressive and attention deficit hyperactivity disorder (ADHD) symptoms and completed neurocognitive testing for executive functions. Binge eating disorder and impulse control disorders were diagnosed using interviews.

Performing DISCO-SCA to search for distinctive and common information in linked data.

Behavioral researchers often obtain information about the same set of entities from different sources. A main challenge in the analysis of such data is to reveal, on the one hand, the mechanisms underlying all of the data blocks under study and, on the other hand, the mechanisms underlying a single data block or a few such blocks only (i.e.

CHull as an alternative to AIC and BIC in the context of mixtures of factor analyzers.

Mixture analysis is commonly used for clustering objects on the basis of multivariate data. When the data contain a large number of variables, regular mixture analysis may become problematic, because a large number of parameters need to be estimated for each cluster. To tackle this problem, the mixtures-of-factor-analyzers (MFA) model was proposed, which combines clustering with exploratory factor analysis.

CHull: a generic convex-hull-based model selection method.

When analyzing data, researchers are often confronted with a model selection problem (e.g., determining the number of components/factors in principal components analysis [PCA]/factor analysis or identifying the most important predictors in a regression analysis).

A flexible framework for sparse simultaneous component based data integration.

Background: High throughput data are complex and methods that reveal structure underlying the data are most useful. Principal component analysis, frequently implemented as a singular value decomposition, is a popular technique in this respect. Nowadays often the challenge is to reveal structure in several sources of information (e.

Simultaneous analysis of coupled data matrices subject to different amounts of noise.

In many areas of science, research questions imply the analysis of a set of coupled data blocks, with, for instance, each block being an experimental unit by variable matrix, and the variables being the same in all matrices. To obtain an overall picture of the mechanisms that play a role in the different data matrices, the information in these matrices needs to be integrated. This may be achieved by applying a data-analytic strategy in which a global model is fitted to all data matrices simultaneously, as in some forms of simultaneous component analysis (SCA).

ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices.

In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e.