Colin G. DeYoung

The purpose of this paper is to define and describe impairment from the perspective of theHierarchical Taxonomy of Psychopathology (HiTOP). This work is intended to establish afoundation for the development of a system for assessing impairment to complement HiTOPmeasures of psychopathology. We define impairment as the direct or indirect impact ofpsychopathology that is not itself part of psychopathology, involving (a) difficulty achievingimportant and reasonable personal goals and/or (b) direct or indirect interference with the goalsof others. We articulate seven specific assessment features of a HiTOP-optimal impairmentmeasurement approach and, having found no existing measures with all seven features in areview of the literature, sketch a prototype approach using a case example and outline a planfor generating a suite of tools for assessing impairment from a HiTOP perspective.

Intelligence is multidimensional—individuals differ in their level of general intelligence ( g ) and specific abilities. g is known to shape aspects of socioeconomic status (SES); however, little is known about how specific abilities shape SES. We evaluated the role of specific abilities in two large, representative samples: the National Longitudinal Studies of Youth 1979 and 1997. Using ten tests from the Armed Services Vocational Aptitude Battery, we identified general intelligence and orthogonal variation in three specific abilities, which we labeled tech, speed, and math-verbal. Performance on specific abilities in youth (14–22 years old) predicted later-life education, income, and occupational status. These associations held even between siblings. In contrast to the common claim that specific abilities add little more explanatory power to g , we concluded that specific abilities have 30–57% of the importance of g . We also examined how specific abilities shape occupations. The average ability profiles across occupations generally followed stereotypes. Metal workers, mechanics, and engineers scored high in tech ability, while religious workers and lawyers scored low. Engineers, doctors, and computer scientists had a high level of math-verbal ability. We estimated the degree of occupational clustering—the multiple correlation of occupations with a cognitive ability. While the strongest clustering was on g , there was also substantial clustering on specific abilities. The most influential specific ability for occupations was tech ability, especially in men, where clustering on tech ability was around 80% as large as the clustering on g .

The Big Five were originally conceived as orthogonal dimensions and the top of the personality trait hierarchy, but they have been found to be regularly correlated, and two higher-order factors or metatraits have been identified above them, often labeled Stability (conscientiousness, agreeableness, and low neuroticism) and Plasticity (extraversion and openness/intellect). Skeptics have argued that the metatraits are likely to be method artifacts rather than substantive trait dimensions. In meta-analytic data and in American and Croatian samples, using both lexical data and purpose-built measures of the Big Five, we investigated whether correlations among the Big Five remain after controlling for three sources of artifactual correlation among variables: (a) acquiescence bias, which we controlled through ipsatization; (b) evaluative consistency bias (social desirability) and other rater biases, which we controlled through the use of multiple raters; and (c) blended variables, which we controlled through the use of exploratory factor models that allow cross-loadings, thereby allowing blended variance in a given item or scale to be accounted for in the factor loadings rather than in the correlations among factors. Even after controlling for all sources of artifact simultaneously, the Big Five remained correlated at the latent level, and the correlations revealed the standard metatraits. The metatraits were not consistently correlated, providing some evidence against a general factor of personality. Our results suggest that the Big Five are genuinely correlated and that Stability and Plasticity are real trait tendencies. Hence, research aimed at understanding correlates, causes, and consequences of the metatraits remains important for psychology. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Personality psychology seeks to understand not only individuals’ dispositional traits, but also components of personality like self-defining life narratives. Past studies correlating traits to narrative themes have largely focused on the Big Five. In the current study, two U.S. undergraduate samples (Study 1, N = 219; Study 2, N = 107) completed the Big Five Aspect Scales, which measure the Big Five domains and ten lower-order aspects (two per domain; e.g., Conscientiousness: Industriousness and Orderliness). Participants’ 2-page life stories (Study 1) and life high point, low point, and turning point narratives (Study 2) were coded for motivational, affective, structural, and autobiographical-reasoning themes. A mini meta-analysis across the two studies revealed several aspect-specific associations with motivational themes. For example, when controlling for shared variance between the aspects, Industriousness was positively associated with agency whereas Orderliness was negatively associated with agency. Trait associations with other narrative themes varied based on narrative methodology. In particular, the open-ended prompts and expanded coding schemes implemented in Study 1 may have allowed participants to better express their dispositional traits through narrative.

Background: Personality psychology seeks to understand individuals' dispositional traits and other components of personality including self‐defining life narratives. Past studies correlating traits and narrative themes have largely focused on the Big Five. Methods: In the current study, two U.S. undergraduate samples (Sample 1, N = 219; Sample 2, N = 107) completed the Big Five Aspect Scales, which measure the Big Five domains and ten lower‐order traits (two per domain; e.g., Conscientiousness: Industriousness and Orderliness). Participants' two‐page open‐ended descriptions of their life histories and/or personal characteristics (Sample 1) and life high point, low point, and turning point narratives (Sample 2) were coded for motivational, affective, structural, and autobiographical‐reasoning themes. Results and Discussion: An exploratory mini meta‐analysis across the two studies revealed several aspect‐specific associations with motivational themes. For example, when controlling for shared variance between the aspects, Industriousness was positively associated with agency whereas Orderliness was negatively associated with agency. Trait associations with other narrative themes varied based on narrative methodology: the open‐ended prompts and expanded coding schemes implemented in Sample 1 may have allowed participants to better express their dispositional traits through narrative. Conclusion: This study advances our understanding of how traits and life narratives are interconnected and the utility of the Big Five Aspect Scales in revealing nuances of this relationship.

Although development and maintenance of relationships is an essential part of mental health and well-being and nearly universal among humans, people vary in their tendency to affiliate with others. Affiliation represents an interstitial personality trait falling between the Compassion aspect of Agreeableness and the Enthusiasm aspect of Extraversion. Though interpersonal behavior has been studied extensively, the field lacks validated questionnaires measuring individual differences in Affiliation. Here, we document the construction and validation of a new Trait Affiliation Scale. Data were taken from six samples (ntotal = 27,198). Study 1 focuses on scale creation, including identification of 24 candidate items and initial tests of convergent validity. Study 2 focuses on scale refinement including the application of item response theory to create a ten-item scale. Study 3 investigates reliability and construct validity. Study 4 provides evidence of test-retest reliability in a four-wave longitudinal dataset. Finally, Study 5 provides evidence for criterion and incremental validity, testing associations of affiliation with outcome variables (e.g., social behaviors, social network size, social cognition, and affiliative states) above and beyond Agreeableness, Extraversion, and their aspects. We discuss the importance of affiliation as a trait and provide recommendations for future research using this new scale.

The Hierarchical Taxonomy of Psychopathology (HiTOP) provides a dimensional framework for connecting psychological disorders to neural systems/processes. We examined how neurophysiological measures of cognitive-attentional (oddball P300) and perceptual-emotional processing (fear-face N170/P200) relate to dimensions of the HiTOP externalizing spectrum. Employing 666 community participants, we fit a model in which antagonistic externalizing and substance-problems subfactors, defined via symptom and questionnaire-scale measures, loaded with a disinhibitory trait scale onto a higher-order externalizing factor. Hierarchical regression was used to evaluate how much observed relations of each neural measure with the two subfactors reflected their unique variance versus their covariance (reflected in the general factor). P300’s relations were fully accounted for by the general factor, suggesting that impaired cognitive processing characterizes broad risk for externalizing problems. Neural indicators of sensitivity to others’ distress (N170, P200) were uniquely related to antagonistic externalizing. Findings highlight the HiTOP framework’s potential to advance biobehavioral understanding of psychopathology.

For decades, advancements in understanding and treating mental illness have been hindered by a categorical psychiatric nosology that fails to describe and explain how symptoms emerge and relate to one another. In response, two separate initiatives have contributed to a renewed sense of optimism for scientific and translational discovery. First, quantitative models of psychopathology improve clinical description by relying on empirical data to provide a more accurate representation of the structure of mental illness. Chief among these approaches is the Hierarchical Taxonomy of Psychopathology (HiTOP), which organizes psychopathology based on patterns of symptom covariation observed across numerous studies. In parallel, computational psychiatry seeks to identify neurocognitive processes that give rise to psychopathology and leverage them to forecast important clinical and functional outcomes. Here, we highlight points of convergence and complementarity between HiTOP and computational psychiatry and propose further integration. HiTOP provides an empirically based approach to understanding the structure of psychopathology, but lacks strong explanations of how symptom dimensions are connected to underlying neurocognitive processes. Conversely, computational psychiatry’s emphasis on cognitive processes and multivariate prediction make it well-suited to linking lower level dynamics with symptom variability. Yet, many contemporary computational psychiatry findings lack specificity and validity as a result of a continued reliance on categorical diagnoses. We conclude by highlighting potential barriers that will need to be addressed to maximize the productivity of future collaborative efforts between these initiatives.