The ICD-11 personality disorder model is the first fully dimensional assessment of personality pathology. It consists of a personality disorder (PD) dysfunction-severity dimension, which encompasses both self- and interpersonal dysfunction, and six optional qualifiers for five prominent personality traits—Negative Affectivity (NA), Detachment (DET), Dissociality (DSL), Disinhibition (DSN), and Anankastia (ANK)—plus a borderline pattern that is defined by the criteria of DSM-IV borderline PD. This article reports on the development of a new self-report measure to assess self- and interpersonal dysfunction and the five trait qualifiers. It is the first comprehensive measure of the ICD-11 PD model in that (a) it is the only one to include both PD dysfunction-severity as well as trait scales and because (b) it is based on the Clinical Description and Diagnostic Guidelines, which are more detailed than the “statistical” model description that is currently on the ICD-11 website. The authors wrote 992 items and then reduced the pool to 300 items by eliminating redundancy and selecting the consensus best few items for each subconstruct. Data were collected using an online sample of 383 Prolific workers. Using exploratory factor analysis, seven domain scales were developed, each of which contained two to four scales assessing components of the domain. These preliminary scales’ psychometrics were excellent, as were the domains’ and their components’ convergent and discriminant validity, with a few generally minor exceptions. Structural analyses at the component level revealed a three-factor structure consisting of two moderately correlated Internalizing factors, one centered on Self Dysfunction with two NA components and a DSN component (Distractibility) and the other on Interpersonal Dysfunction with DET and ANK components; as well as an Externalizing factor with DSL and a DSN component (Reckless Impulsivity) that was uncorrelated with the other two factors. Two aspects of the results in particular are striking: (1) ANK was not the opposite end of a DSN dimension, but rather contributed to an Internalizing Interpersonal Dysfunction dimension and (2) DSN had both an Internalizing and an Externalizing component. Implications of the findings and study limitations are discussed.

Extraversion shows both negative and positive associations with psychopathology. Previous work in this area has focused largely on either a broad higher order extraversion domain score or on specific lower-order extraversion facets. The goal of this study was to explicate how two intermediate aspects of the trait—communal extraversion and agentic extraversion—relate to psychopathology. We examined these relations using the Communal Extraversion (e.g., enjoy spending time with people, would describe myself as cheerful, like places that are crowded and exciting) and Agentic Extraversion (e.g., speak my mind, take charge in a group of people, like the sensation of going really fast) scales from the Faceted Inventory of the Five-Factor Model (FI-FFM; Watson, Nus, & Wu, 2019). As expected, Communal Extraversion generally showed negative associations with psychopathology; it had particularly strong links to indicators of internalizing, including depression symptoms (correlations generally ranged from −.40 to −.60) and various forms of social dysfunction (most correlations ranged from −.35 to −.60). In marked contrast, Agentic Extraversion tended to have positive associations with psychopathology; it displayed particularly substantial links to indicators of mania, narcissism/narcissistic personality disorder, and traits related to externalizing (correlations generally ranged from .25 to .50). Regression results demonstrated that aspect-level analyses generated substantial increases in predictive power over the FI-FFM Extraversion domain score. This basic pattern of results replicated over time, across gender, and across both self-rated and interview-based indicators of psychopathology. These findings establish the value of examining relations with extraversion at the aspect level.

As part of a broader project to create a comprehensive self-report measure for the Hierarchical Taxonomy of Psychopathology consortium, we developed preliminary scales to assess internalizing symptoms. The item pool was created in four steps: (a) clarifying the range of content to be assessed, (b) identifying target constructs to guide item writing, (c) developing formal definitions for each construct, and (d) writing multiple items for each construct. This yielded 430 items assessing 57 target constructs. Responses from a heterogeneous scale development sample ( N = 1,870) were subjected to item-level factor analyses based on polychoric correlations. This resulted in 39 scales representing a total of 213 items. The psychometric properties of these scales replicated well across the development sample and an independent validation sample ( N = 496 adults). Internal consistency analyses established that most scales assess relatively narrow forms of psychopathology. Structural analyses demonstrated the presence of a strong general factor. Additional analyses of the 35 nonsexual dysfunction scales revealed a replicable four-factor structure with dimensions we labeled Distress, Fear, Body Dysmorphia, and Mania. A final set of analyses established that the internalizing scales varied widely—and consistently—in the strength of their associations with neuroticism and extraversion.

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Extensive research has been conducted to isolate features that distinguish bipolar spectrum disorders from unipolar depression. Therefore, we identified latent symptom dimensions that are unique versus shared across these disorders by examining the joint structure of hypomanic/manic and depressive symptoms in two large samples (i.e., 647 community adults; 1,370 outpatients with unipolar depression or bipolar disorder history). Results across studies suggested that (a) many hypomanic/manic and depressive symptoms (e.g., irritability) are transdiagnostic, but also that (b) symptoms such as increased energy and euphoric mood define a latent specific positive activation dimension that appears more specific to bipolar disorder. We discuss how these results indicate that some symptoms may be more optimal to target than others when trying to distinguish bipolar disorder from unipolar depression, as well as how the identification of relatively disorder-specific symptom types may optimally guide future research on key mechanisms linked to hypomania/mania and depression.