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Recent initiatives have focused on integrating transdiagnostic biobehavioral processes or dispositions with dimensional models of psychopathology. Toward this goal, biobehavioral traits of affiliative capacity (AFF) and inhibitory control (INH) hold particular promise as they demonstrate transdiagnostic stability and predictive validity across developmental stages and differing measurement modalities. The current study employed data from different modes of measurement in a sample of 1830 children aged 5–10 years to test for associations of AFF and INH, individually and interactively, with broad dimensions of psychopathology. Low AFF, assessed via parent-report, evidenced predictive relations with distress- and externalizing-related problems. INH as assessed by cognitive-task performance did not relate itself to either psychopathology dimension, but it moderated the effects observed for low AFF, such that high INH protected against distress symptoms in low-AFF participants, whereas low INH amplified distress and externalizing symptoms in low-AFF participants. Results are discussed in the context of the interface of general trait transdiagnostic risk factors with quantitatively derived dimensional models of psychopathology. [ABSTRACT FROM AUTHOR]

Recent initiatives emphasize the need to consider developmental and transdiagnostic contributions of temperamental variation to psychopathological expression. Triarchic neurobehavioral trait dimensions (boldness, meanness, disinhibition), which demonstrate compatibility with established temperament models and can be quantified using items from different existing inventories, are well-suited to pursuing these goals. We undertook to develop item-based scales for indexing these traits in 285 children (ages 5-10) tested in the Child Mind Institute's Healthy Brain Network (HBN) study, and evaluated their psychometric properties in two separate samples of similar-aged children: 519 others from the HBN study and 261 for whom parental-informant ratings were obtained through MTurk. Associations with psychopathology measures provided evidence for a) transdiagnostic utility of the triarchic scales, b) (reversed) boldness as the strongest predictor of internalizing problems, c) meanness as related to both internalizing and externalizing problems, d) disinhibition as the strongest predictor of externalizing problems, and e)a moderating effect of meanness level on disinhibition's relationship with externalizing problems. This research demonstrates that the triarchic traits can be effectively represented in young children and show expected relations with clinical outcome measures. As such, this work provides a foundation for developmental research clarifying the role that core neurobehavioral dispositions play in mental health. [ABSTRACT FROM AUTHOR]

The biobehavioral traits of the triarchic model of psychopathy have well-known correlates with externalizing psychopathology. Although evidence also suggests associations with internalizing disorders, research has yet to formally model relationships between dimensions of internalizing psychopathology and triarchic traits. Employing a sample of 218 adults (50.2% female), the current study used confirmatory factor analysis to characterize how triarchic trait dimensions—delineated using different scale operationalizations—relate to internalizing when modeled as a single broad factor, and as distinct fear and distress subfactors. Findings demonstrated (a) robust opposing relations for triarchic boldness (+) and disinhibition (−), and an interactive association for the two, with general internalizing, along with a modest negative relationship for meanness; and (b) distinct associations for the three triarchic trait dimensions with fear and distress subfactors of internalizing. This work clarifies how facets of psychopathy relate to the internalizing psychopathology spectrum and provides a means for interfacing this spectrum with biological variables. [ABSTRACT FROM AUTHOR]

Understanding the neurobiological mechanisms involved in psychopathology has been hindered by the limitations of categorical nosologies. The Hierarchical Taxonomy of Psychopathology (HiTOP) is an alternative dimensional system for characterizing psychopathology, derived from quantitative studies of covariation among diagnoses and symptoms. HiTOP provides more promising targets for clinical neuroscience than traditional psychiatric diagnoses and can facilitate cumulative integration of existing research. We systematically reviewed 164 human neuroimaging studies with sample sizes of 194 or greater that have investigated dimensions of psychopathology classified within HiTOP. Replicated results were identified for constructs at five different levels of the hierarchy, including the overarching p-factor, the externalizing superspectrum, the thought disorder and internalizing spectra, the distress subfactor, and the depression symptom dimension. Our review highlights the potential of dimensional clinical neuroscience research and the usefulness of HiTOP while also suggesting limitations of existing work in this relatively young field. We discuss how HiTOP can be integrated synergistically with neuroscience-oriented, transdiagnostic frameworks developed by the National Institutes of Health, including the Research Domain Criteria, Addictions Neuroclinical Assessment, and the National Institute on Drug Abuse's Phenotyping Assessment Battery, and how researchers can use HiTOP to accelerate clinical neuroscience research in humans and other species. General Scientific Summary: Clinical scientists have discovered that mental disorders are not discrete categorical entities, as assumed by traditional diagnostic models, but rather reflect variation on a number of symptom dimensions varying continuously in the general population. In response, clinical neuroscience research has increasingly studied associations of neural variables with dimensional assessments of psychopathology, which can be organized by the Hierarchical Taxonomy of Psychopathology (HiTOP). Using HiTOP as our framework, we review findings from 164 neuroimaging studies with reasonably large samples, highlighting replicated results, and we provide suggestions and guidelines for future HiTOP-informed neuroscience research. [ABSTRACT FROM AUTHOR]