Delineating and validating higher-order dimensions of psychopathology in the Adolescent Brain Cognitive Development (ABCD) study

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Abstract

Hierarchical dimensional systems of psychopathology promise more informative descriptions for understanding risk and predicting outcome than traditional diagnostic systems, but it is unclear how many major dimensions they should include. We delineated the hierarchy of childhood and adult psychopathology and validated it against clinically relevant measures. Participants were 9987 9- and 10-year-old children and their parents from the Adolescent Brain Cognitive Development (ABCD) study. Factor analyses of items from the Child Behavior Checklist and Adult Self-Report were run to delineate hierarchies of dimensions. We examined the familial aggregation of the psychopathology dimensions, and the ability of different factor solutions to account for risk factors, real-world functioning, cognitive functioning, and physical and mental health service utilization. A hierarchical structure with a general psychopathology (‘p’) factor at the apex and five specific factors (internalizing, somatoform, detachment, neurodevelopmental, and externalizing) emerged in children. Five similar dimensions emerged also in the parents. Child and parent p-factors correlated highly ( r = 0.61, p < 0.001), and smaller but significant correlations emerged for convergent dimensions between parents and children after controlling for p-factors ( r = 0.09−0.21, p < 0.001). A model with child p-factor alone explained mental health service utilization ( R ² = 0.23, p < 0.001), but up to five dimensions provided incremental validity to account for developmental risk and current functioning in children ( R ² = 0.03−0.19, p < 0.001). In this first investigation comprehensively mapping the psychopathology hierarchy in children and adults, we delineated a hierarchy of higher-order dimensions associated with a range of clinically relevant validators. These findings hold important implications for psychiatric nosology and future research in this sample.

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Mental Disorders, Comorbidity and Suicidal Behavior: Results from the National Comorbidity Survey Replication

MK Nock, Irene I. L. Hwang, NA Sampson … (2009)

Mental disorders are among the strongest predictors of suicide attempts. However, little is known about which disorders are uniquely associated with suicidal behavior due to high levels of psychiatric comorbidity. We examined the unique associations between individual disorders and subsequent suicidal behavior (suicide ideation, plans, and attempts) using data from the National Comorbidity Survey Replication, a nationally representative household survey of 9,282 US adults. Results revealed that approximately 80% of suicide attempters in the US have a temporally prior mental disorder. Anxiety, mood, impulse-control, and substance disorders all significantly predict subsequent suicide attempts in bivariate analyses (odds ratios=2.7-6.7); however, these associations decrease substantially in multivariate analyses controlling for comorbidity (odds ratios=1.5-2.3) but remain statistically significant in most cases. Disaggregation of the observed effects reveals that depression predicts suicide ideation, but not suicide plans or attempts among those with ideation. Instead, disorders characterized by severe anxiety/agitation (e.g., PTSD) and poor impulse-control (e.g., conduct disorder, substance disorders) predict which suicide ideators go on to make a plan or attempt. These results advance understanding of the unique associations between mental disorders and different forms of suicidal behavior. Future research must further delineate the mechanisms through which people come to think about suicide and progress from suicidal thoughts to attempts.

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All for One and One for All: Mental Disorders in One Dimension

Terrie E Moffitt, Avshalom Caspi (2018)

In both child and adult psychiatry, empirical evidence has now accrued to suggest that a single dimension is able to measure a person's liability to mental disorder, comorbidity among disorders, persistence of disorders over time, and severity of symptoms. This single dimension of general psychopathology has been termed "p," because it conceptually parallels a dimension already familiar to behavioral scientists and clinicians: the "g" factor of general intelligence. As the g dimension reflects low to high mental ability, the p dimension represents low to high psychopathology severity, with thought disorder at the extreme. The dimension of p unites all disorders. It influences present/absent status on hundreds of psychiatric symptoms, which modern nosological systems typically aggregate into dozens of distinct diagnoses, which in turn aggregate into three overarching domains, namely, the externalizing, internalizing, and psychotic experience domains, which finally aggregate into one dimension of psychopathology from low to high: p. Studies show that the higher a person scores on p, the worse that person fares on measures of family history of psychiatric illness, brain function, childhood developmental history, and adult life impairment. A dimension of p may help account for ubiquitous nonspecificity in psychiatry: multiple disorders share the same risk factors and biomarkers and often respond to the same therapies. Here, the authors summarize the history of the unidimensional idea, review modern research into p, demystify statistical models, articulate some implications of p for prevention and clinical practice, and outline a transdiagnostic research agenda. [AJP AT 175: Remembering Our Past As We Envision Our Future October 1910: A Study of Association in Insanity Grace Helen Kent and A.J. Rosanoff: "No sharp distinction can be drawn between mental health and mental disease; a large collection of material shows a gradual and not an abrupt transition from the normal state to pathological states."(Am J Psychiatry 1910; 67(2):317-390 )].

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Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description

Deanna Barch, Matthew Albaugh, Shelli Avenevoli … (2017)

The Adolescent Brain and Cognitive Development (ABCD) Study incorporates a comprehensive range of measures assessing predictors and outcomes related to both mental and physical health across childhood and adolescence. The workgroup developed a battery that would assess a comprehensive range of domains that address study aims while minimizing participant and family burden. We review the major considerations that went into deciding what constructs to cover in the demographics, physical health and mental health domains, as well as the process of selecting measures, piloting and refining the originally proposed battery. We present a description of the baseline battery, as well as the six-month interim assessments and the one-year follow-up assessments. This battery includes assessments from the perspectives of both the parent and the target youth, as well as teacher reports. This battery will provide a foundational baseline assessment of the youth’s current function so as to permit characterization of stability and change in key domains over time. The findings from this battery will also be utilized to identify both resilience markers that predict healthy development and risk factors for later adverse outcomes in physical health, mental health, and substance use and abuse.

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Author and article information

Contributors

Giorgia Michelini: +1 631-638-1923 , Giorgia.Michelini@stonybrookmedicine.edu

Journal

Journal ID (nlm-ta): Transl Psychiatry

Journal ID (iso-abbrev): Transl Psychiatry

Title: Translational Psychiatry

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2158-3188

Publication date (Electronic): 17 October 2019

Publication date PMC-release: 17 October 2019

Publication date Collection: 2019

Volume: 9

Electronic Location Identifier: 261

Affiliations

[1 ]ISNI 0000 0001 2216 9681, GRID grid.36425.36, Department of Psychiatry & Behavioral Health, , Stony Brook University, ; Stony Brook, NY USA

[2 ]ISNI 0000 0001 2355 7002, GRID grid.4367.6, Departments of Psychological & Brain Sciences, Psychiatry and Radiology, , Washington University, ; St. Louis, MO USA

[3 ]ISNI 0000 0001 2216 9681, GRID grid.36425.36, Department of Applied Mathematics and Statistics, , Stony Brook University, ; Stony Brook, NY USA

[4 ]ISNI 0000 0001 2168 0066, GRID grid.131063.6, Department of Psychology, , University of Notre Dame, ; Notre Dame, IN USA

[5 ]ISNI 0000 0001 2216 9681, GRID grid.36425.36, Department of Psychology, , Stony Brook University, ; Stony Brook, NY USA

Author information

Deanna M. Barch http://orcid.org/0000-0003-1693-8506

Article

Publisher ID: 593

DOI: 10.1038/s41398-019-0593-4

PMC ID: 6797772

PubMed ID: 31624235

SO-VID: 12b134dd-8259-431c-be62-fa6eb1b63a0e

License:

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