Mapping Cognitive Patterns:A Network Analysis of Irrational Beliefs, Dysfunctional Attitudes, Automatic Thoughts, and Negative Cognitive Errors in Children

Irrational beliefs, dysfunctional attitudes, automatic thoughts, and negative cognitive errors are key cognitive patterns associated with emotional and behavioral difficulties in children. These constructs are foundational in therapeutic approaches like Cognitive Behavioral Therapy (CBT), but their relationships remain underexplored in child samples. This study examined the associations among these constructs in a sample of 615 children (grades 5–8) using network analysis. Two models were tested: Model A examined total scores of the variables, and Model B analyzed subdomains for irrational beliefs, automatic thoughts, and cognitive errors. Undirected Gaussian Graphical Models (GGMs) and Directed Acyclic Graphs (DAGs) were applied to identify associations and potential directional pathways. In Model A, dysfunctional attitudes emerged as the most central variable, with automatic thoughts acting as a mediator between dysfunctional attitudes and irrational beliefs. Negative cognitive errors were less connected to other variables. Model B revealed personal failure (a subdomain of automatic thoughts) as the most central node, while demand for success (irrational beliefs) was closely linked to dysfunctional attitudes. The DAG analysis suggested that automatic thoughts predict irrational beliefs in children, differing from patterns observed in adults. The findings suggest that dysfunctional attitudes and automatic thoughts play central roles in children’s cognitive patterns. Future studies should examine these relationships including psychopathological factors to deepen understanding.</p

Crohn’s disease and ulcerative colitis exhibit prediagnostic antibody signatures with shared and divergent changes towards disease onset

Background The development of IBD is known to involve early immunological alterations, but our understanding of the changes in antibody epitope repertoires moving from the prediagnostic phase towards disease onset remains incomplete.Objective In this study, we comprehensively characterised systemic antibody responses in patients with IBD before and after disease onset, aiming to identify prediagnostic disease biomarkers.Design Within Lifelines, a population-based cohort study collecting and storing longitudinal samples from 167 000 individuals over∼15 years, we identified 178 individuals with blood samples taken both before and after IBD-onset. In these prediagnosis and postdiagnosis serum samples (median time span 3.9 years), we profiled antibody epitope repertoires against 344 000 rationally selected microbial, food and immune antigens using phage-display immunoprecipitation sequencing.Results Postdiagnosis, we observe reduced antibody frequencies against herpesviruses, particularly for Epstein-Barr virus and varicella zoster virus, and elevated antibody frequencies against specific enteroviruses, including adenovirus C and enterovirus types B and C. Even before diagnosis, individuals who ultimately developed Crohn’s disease (CD) displayed elevated antibody reactivity against flagellins of both commensal and pathogenic bacteria. This CD-specific profile became even more pronounced postdiagnosis, suggesting the formation of IBD-specific antibody responses years before disease onset.Conclusion This study is the first comprehensive high-resolution analysis of the exact antigenic nature of systemic antibody responses during the transition from prediagnostic to established IBD. The antibody signatures we found may represent a route to developing biomarkers that identify individuals at high risk of developing disease

Drug management of TB in the intensive care setting:an international multicentre study

Individuals requiring admission to an intensive care unit (ICU) due to TB have complex clinical presentations and high mortality rates. There is a clear knowledge gap on how to optimally manage treatment.To evaluate the treatment outcomes of TB patients in ICU and explore the potential benefits of intravenous (IV) TB treatment regimens.A retrospective observational multicentre study was conducted by the International Severe TB and Rehabilitation Working Group of the Global Tuberculosis Network (GTN). The study included TB patients aged &gt;15 years admitted to ICUs in Europe, Asia and Latin America from January 1, 2005 to December 31, 2018. Data on demographics, microbiology, clinical information and treatment outcomes were collected and analysed.The study enrolled 434 cases. Over half were sputum smear-positive and 85.7% were culture-positive. Most required invasive mechanical ventilation, vasopressor support and steroids. Only 48.4% had TB medications initiated before or during ICU admission. The overall mortality rate was 54.8%, with 33.4% achieving treatment success. IV anti-TB drugs were administered to 43% of participants, with levofloxacin and amikacin being the most used. IV treatment longer than 10 days was associated with better outcomes. Individuals receiving IV rifampicin had a lower mortality rate (35.7%) compared to those who did not receive it (51.7%), p-value= 0.05.High mortality rates in ICU indicate the need for improved management strategies. The use of IV TB drugs, especially IV rifampicin, show potential benefit, suggesting the need for further prospective studies. Early screening and standardized treatment protocols could improve patient outcomes in high-incidence areas.<p/

Assessing the internal consistency reliability of ecological momentary assessment measures:Insights from the WARN-D study

Intensive longitudinal research has become increasingly popular in the social and clinical sciences in recent years. However, this popularity has brought about many challenges for both methodological and empirical researchers, including challenges regarding measurement. In this preregistered study, we are particularly interested in the assessment of the reliability when multiple items are used to measure the same construct in intensive longitudinal data. This is important because reliability estimates are necessary (albeit not sufficient) to evaluate the quality of measures. Here, we evaluate the internal consistency reliability of scales used during Stage 2 of the WARN-D study, a 3-month period of daily and weekly measurements. The WARN-D study is a prospective 2-year study of approximately 1,750 students conducted in the Netherlands, aiming at building an early warning system for depression. Stage 2 includes 3 months of data on positive and negative affect measured four times a day and depression and anxiety measured once a week. To assess the reliability of each scale, we use six different statistical approaches including three simpler approaches that estimate the reliability at the between-person and within-person levels and three idiographic approaches that estimate person-specific reliability coefficients. This article also serves as a tutorial guide for substantive researchers, providing annotated code to facilitate estimating and reporting the reliability of ecological momentary assessment measures. We encourage all researchers to report the reliability of their data when applying the introduced statistical approaches, contributing to a collaborative effort toward developing more reliable measures in psychological and behavioral science. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p

Stochastic actor-oriented models for the co-evolution of networks and individual outcomes

Stochastic actor-oriented models (SAOMs) originated as models to explain network evolution over time. They have been extended in several directions. This chapter focuses on the extension of SAOMs for analyzing the co-evolution of networks and individual outcomes, such as behaviours, attitudes, and activities. Over the past decade, these models have been widely applied in education to determine the relative contributions of selection and influence processes to explain peer effects and design effective policies. We illustrate the model by analyzing the co-evolution of friendship and academic performance. The chapter ends with a discussion of the strengths and limitations of the introduced models and a brief description of SAOMs' extensions for analyzing multivariate and multilevel network data and their application in education.</p