142 research outputs found

    Integrating the Hierarchical Taxonomy of Psychopathology (HiTOP) Into Clinical Practice

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    Objective: Diagnosis is a cornerstone of clinical practice for mental health care providers, yet traditional diagnostic systems have well-known shortcomings, including inadequate reliability, high comorbidity, and marked within-diagnosis heterogeneity. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a data-driven, hierarchically based alternative to traditional classifications that conceptualizes psychopathology as a set of dimensions organized into increasingly broad, transdiagnostic spectra. Prior work has shown that using a dimensional approach improves reliability and validity, but translating a model like HiTOP into a workable system that is useful for health care providers remains a major challenge. / Method: The present work outlines the HiTOP model and describes the core principles to guide its integration into clinical practice. Results: Potential advantages and limitations of the HiTOP model for clinical utility are reviewed, including with respect to case conceptualization and treatment planning. A HiTOP approach to practice is illustrated and contrasted with an approach based on traditional nosology. Common barriers to using HiTOP in real-world health care settings and solutions to these barriers are discussed. / Conclusions: HiTOP represents a viable alternative to classifying mental illness that can be integrated into practice today, although research is needed to further establish its utility

    Attentional control theory in childhood: enhanced attentional capture by non-emotional and emotional distractors in anxiety and depression

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    Attentional control theory (ACT) proposes that anxiety is associated with executive functioning deficits. The theory has been widely investigated in adults. The current study tested whether symptoms of childhood anxiety and depression were associated with experimentally measured attentional control in the context of non-emotional and emotional stimuli. Sixty-one children (mean age = 9.23 years, range = 8.39 - 10.41) reported their trait anxiety and depression symptoms and completed three visual search tasks. The tasks used a variant of an irrelevant singleton paradigm and measured attentional capture by task-irrelevant non-emotional (color) and emotional (facial expressions) distractors. Significant attentional capture by both non-emotional and emotional distractors was observed, and was significantly correlated with trait anxiety and symptoms of depression. The strength of relationship between attentional capture and the symptoms did not differ significantly for non-emotional and emotional distractors. The results suggest that symptoms of childhood anxiety and depression are associated with poorer attentional control both in the presence of emotional and non-emotional stimuli, supporting ACT in younger populations. This attentional deficit in the context of non-emotional information might be as central to childhood internalizing symptoms as attentional biases often observed on tasks investigating processing of emotional stimuli

    A genetically informed cross-lagged analysis of autistic-like traits and affective problems in early childhood

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    A genetically informed cross-lagged model was applied to twin data to explore etiological links between autistic-like traits and affective problems in early childhood. The sample comprised 310 same-sex twin pairs (143 monozygotic and 167 dizygotic; 53% male). Autistic-like traits and affective problems were assessed at ages 2 and 3 using parent ratings. Both constructs were related within and across age (r = .30-.53) and showed moderate stability (r = .45-.54). Autistic-like traits and affective problems showed genetic and environmental influences at both ages. Whereas at age 2, the covariance between autistic-like traits and affective problems was entirely due to environmental influences (shared and nonshared), at age 3, genetic factors also contributed to the covariance between constructs. The stability paths, but not the cross-lagged paths, were significant, indicating that there is stability in both autistic-like traits and affective problems but they do not mutually influence each other across age. Stability effects were due to genetic, shared, and nonshared environmental influences. Substantial novel genetic and nonshared environmental influences emerge at age 3 and suggest change in the etiology of these constructs over time. During early childhood, autistic-like traits tend to occur alongside affective problems and partly overlapping genetic and environmental influences explain this association

    The state-of-the-art determination of urinary nucleosides using chromatographic techniques “hyphenated” with advanced bioinformatic methods

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    Over the last decade metabolomics has gained increasing popularity and significance in life sciences. Together with genomics, transcriptomics and proteomics, metabolomics provides additional information on specific reactions occurring in humans, allowing us to understand some of the metabolic pathways in pathological processes. Abnormal levels of such metabolites as nucleosides in the urine of cancer patients (abnormal in relation to the levels observed in healthy volunteers) seem to be an original potential diagnostic marker of carcinogenesis. However, the expectations regarding the diagnostic value of nucleosides may only be justified once an appropriate analytical procedure has been applied for their determination. The achievement of good specificity, sensitivity and reproducibility of the analysis depends on the right choice of the phases (e.g. sample pretreatment procedure), the analytical technique and the bioinformatic approach. Improving the techniques and methods applied implies greater interest in exploration of reliable diagnostic markers. This review covers the last 11 years of determination of urinary nucleosides conducted with the use of high-performance liquid chromatography in conjunction with various types of detection, sample pretreatment methods as well as bioinformatic data processing procedures

    Generalised Anxiety Disorder – A Twin Study of Genetic Architecture, Genome-Wide Association and Differential Gene Expression

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    Generalised Anxiety Disorder (GAD) is a common anxiety-related diagnosis, affecting approximately 5% of the adult population. One characteristic of GAD is a high degree of anxiety sensitivity (AS), a personality trait which describes the fear of arousal-related sensations. Here we present a genome-wide association study of AS using a cohort of 730 MZ and DZ female twins. The GWAS showed a significant association for a variant within the RBFOX1 gene. A heritability analysis of the same cohort also confirmed a significant genetic component with h2 of 0.42. Additionally, a subset of the cohort (25 MZ twins discordant for AS) was studied for evidence of differential expression using RNA-seq data. Significant differential expression of two exons with the ITM2B gene within the discordant MZ subset was observed, a finding that was replicated in an independent cohort. While previous research has shown that anxiety has a high comorbidity with a variety of psychiatric and neurodegenerative disorders, our analysis suggests a novel etiology specific to AS

    The CogBIAS longitudinal study protocol: cognitive and genetic factors influencing psychological functioning in adolescence.

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    BACKGROUND: Optimal psychological development is dependent upon a complex interplay between individual and situational factors. Investigating the development of these factors in adolescence will help to improve understanding of emotional vulnerability and resilience. The CogBIAS longitudinal study (CogBIAS-L-S) aims to combine cognitive and genetic approaches to investigate risk and protective factors associated with the development of mood and impulsivity-related outcomes in an adolescent sample. METHODS: CogBIAS-L-S is a three-wave longitudinal study of typically developing adolescents conducted over 4 years, with data collection at age 12, 14 and 16. At each wave participants will undergo multiple assessments including a range of selective cognitive processing tasks (e.g. attention bias, interpretation bias, memory bias) and psychological self-report measures (e.g. anxiety, depression, resilience). Saliva samples will also be collected at the baseline assessment for genetic analyses. Multilevel statistical analyses will be performed to investigate the developmental trajectory of cognitive biases on psychological functioning, as well as the influence of genetic moderation on these relationships. DISCUSSION: CogBIAS-L-S represents the first longitudinal study to assess multiple cognitive biases across adolescent development and the largest study of its kind to collect genetic data. It therefore provides a unique opportunity to understand how genes and the environment influence the development and maintenance of cognitive biases and provide insight into risk and protective factors that may be key targets for intervention.This work was supported by the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement no: [324176]

    A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research

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    For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system—the Hierarchical Taxonomy of Psychopathology (HiTOP)—that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.FSW – Publicaties zonder aanstelling Universiteit Leide

    A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research

    Get PDF
    For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness
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