The underlying structure of the Personality Inventory for DSM-5 (PID-5): a general factor of personality psychopathology.

BACKGROUND: The psychopathology of personality is currently undergoing a paradigm shift from a categorical to a dimensional approach. This work aimed to study the underlying structure of pathological personality traits of the DSM-5 Alternative Model for Personality Disorders (AMPD). For this purpose, the internal structure of a version of the Personality Inventory for the DSM-5 (PID-5) was examined by a confirmatory factor analysis. This version assesses the five higher-order pathological personality domains (negative affectivity, detachment, antagonism, disinhibition, and psychoticism) and the 25 lower-order pathological personality facets through a reduced number of items. Four alternative models were compared: five-factor oblique; second-order (five first-order factors and one second-order factor); bifactor (five specific factors and a general factor), and one-factor. PARTICIPANTS AND PROCEDURE: We worked with an Argentinean sample of N = 525 subjects from the general population who answered the Argentine version of the PID-5. RESULTS: The five-factor model was slightly superior to the second order model, and the bifactor model presented the best fit. CONCLUSIONS: These findings, while preliminary, suggest that the PID-5 facets could reflect five specific pathological personality traits (which correspond to AMPD domains) but also a general factor (which would reflect a general propensity for psychopathology).

Mapping potential pathways from polygenic liability through brain structure to psychological problems across the transition to adolescence.

BACKGROUND: We used a polygenic score for externalizing behavior (extPGS) and structural MRI to examine potential pathways from genetic liability to conduct problems via the brain across the adolescent transition. METHODS: Three annual assessments of child conduct problems, attention-deficit/hyperactivity problems, and internalizing problems were conducted across across 9-13 years of age among 4,475 children of European ancestry in the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®). RESULTS: The extPGS predicted conduct problems in each wave (R2 = 2.0%-2.9%). Bifactor models revealed that the extPRS predicted variance specific to conduct problems (R2 = 1.7%-2.1%), but also variance that conduct problems shared with other measured problems (R2 = .8%-1.4%). Longitudinally, extPGS predicted levels of specific conduct problems (R2 = 2.0%), but not their slope of change across age. The extPGS was associated with total gray matter volume (TGMV; R2 = .4%) and lower TGMV predicted both specific conduct problems (R2 = 1.7%-2.1%) and the variance common to all problems in each wave (R2 = 1.6%-3.1%). A modest proportion of the polygenic liability specific to conduct problems in each wave was statistically mediated by TGMV. CONCLUSIONS: Across the adolescent transition, the extPGS predicted both variance specific to conduct problems and variance shared by all measured problems. The extPGS also was associated with TGMV, which robustly predicted conduct problems. Statistical mediation analyses suggested the hypothesis that polygenic variation influences individual differences in brain development that are related to the likelihood of conduct problems during the adolescent transition, justifying new research to test this causal hypothesis.

Does preschool executive control mediate the impact of early environmental unpredictability and deprivation on the general factor of psychopathology a decade later?

BACKGROUND: Although deprivation has been consistently shown to increase risk for psychopathology through impaired executive control, the unique effects of other dimensions of early adversity, such as unpredictability, on executive control development are poorly understood. The current study evaluated whether deprivation and/or unpredictability early in life have unique effects on the general factor of psychopathology through impaired preschool executive control. METHODS: Participants included 312 children (51% female) oversampled for greater sociodemographic risk. Preschool executive control was measured using a battery of nine developmentally appropriate executive control tasks. Dimensions of adversity were measured with observational and caregiver assessments, and psychopathology was measured with caregiver and child reports. RESULTS: In separate models, both deprivation and unpredictability had significant indirect effects on the adolescent general factor of psychopathology through impaired preschool executive control. However, when both dimensions of adversity were included simultaneously, early life deprivation, but not unpredictability, was uniquely associated with the general factor of psychopathology in adolescence through impaired preschool executive control. CONCLUSIONS: Preschool executive control appears to be a transdiagnostic mechanism through which deprivation, but not unpredictability, increases risk for the general factor of psychopathology in adolescence. Results elucidate potential transdiagnostic targets for intervention efforts aimed at reducing the development and maintenance of psychopathology across the life span.

Defining the p-factor: an empirical test of five leading theories.

BACKGROUND: Despite statistical evidence of a general factor of psychopathology (i.e., p-factor), there is little agreement about what the p-factor represents. Researchers have proposed five theories: dispositional negative emotionality (neuroticism), impulsive responsivity to emotions (impulsivity), thought dysfunction, low cognitive functioning, and impairment. These theories have primarily been inferred from patterns of loadings of diagnoses on p-factors with different sets of diagnoses included in different studies. Researchers who have directly examined these theories of p have examined a subset of the theories in any single sample, limiting the ability to compare the size of their associations with a p-factor. METHODS: In a sample of adults (N = 1833, Mage = 34.20, 54.4% female, 53.3% white) who completed diagnostic assessments, self-report measures, and cognitive tests, we evaluated statistical p-factor structures across modeling approaches and compared the strength of associations among the p-factor and indicators of each of these five theories. RESULTS: We found consistent evidence of the p-factor's unidimensionality across one-factor and bifactor models. The p-factor was most strongly and similarly associated with neuroticism (r = .88), impairment (r = .88), and impulsivity (r = .87), χ2(1)s < .15, ps > .70, and less strongly associated with thought dysfunction (r = .78), χ2(1)s > 3.92, ps < .05, and cognitive functioning (r = -.25), χ2(1)s > 189.56, ps < .01. CONCLUSIONS: We discuss a tripartite definition of p that involves the transaction of impulsive responses to frequent negative emotions leading to impairment that extends and synthesizes previous theories of psychopathology.

On the Meaning of the "P Factor" in Symmetrical Bifactor Models of Psychopathology: Recommendations for Future Research From the Bifactor-(S-1) Perspective.

Symmetrical bifactor models are frequently applied to diverse symptoms of psychopathology to identify a general P factor. This factor is assumed to mark shared liability across all psychopathology dimensions and mental disorders. Despite their popularity, however, symmetrical bifactor models of P often yield anomalous results, including but not limited to nonsignificant or negative specific factor variances and nonsignificant or negative factor loadings. To date, these anomalies have often been treated as nuisances to be explained away. In this article, we demonstrate why these anomalies alter the substantive meaning of P such that it (a) does not reflect general liability to psychopathology and (b) differs in meaning across studies. We then describe an alternative modeling framework, the bifactor-(S-1) approach. This method avoids anomalous results, provides a framework for explaining unexpected findings in published symmetrical bifactor studies, and yields a well-defined general factor that can be compared across studies when researchers hypothesize what construct they consider "transdiagnostically meaningful" and measure it directly. We present an empirical example to illustrate these points and provide concrete recommendations to help researchers decide for or against specific variants of bifactor structure.

How Robust Is the p Factor? Using Multitrait-Multimethod Modeling to Inform the Meaning of General Factors of Youth Psychopathology.

We used multitrait-multimethod (MTMM) modeling to examine general factors of psychopathology in three samples of youth (Ns = 2119, 303, 592) for whom three informants reported on the youth's psychopathology (e.g., child, parent, teacher). Empirical support for the p-factor diminished in multi-informant models compared with mono-informant models: the correlation between externalizing and internalizing factors decreased and the general factor in bifactor models essentially reflected externalizing. Widely used MTMM-informed approaches for modeling multi-informant data cannot distinguish between competing interpretations of the patterns of effects we observed, including that the p-factor reflects, in part, evaluative consistency bias or that psychopathology manifests differently across contexts (e.g., home vs. school). Ultimately, support for the p-factor may be stronger in mono-informant designs, although it is does not entirely vanish in multi-informant models. Instead, the general factor of psychopathology in any given mono-informant model likely reflects a complex mix of variances, some substantive and some methodological.

Associations between psychiatric polygenic risk scores and general and specific psychopathology symptoms in childhood and adolescence between and within dizygotic twin pairs.

BACKGROUND: Although polygenic risk scores (PRS) predict psychiatric problems, these associations might be attributable to indirect pathways including population stratification, assortative mating, or dynastic effects (mediation via parental environments). The goal of this study was to examine whether PRS-psychiatric symptom associations were attributable to indirect versus direct pathways. METHODS: The sample consisted of 3,907 dizygotic (DZ) twin pairs. In childhood, their parents rated them on 98 symptoms. In adolescence (n = 2,393 DZ pairs), both the parents and the twins rated themselves on 20 symptoms. We extracted one general and seven specific factors from the childhood data, and one general and three specific factors from the adolescent data. We then regressed each general factor model onto ten psychiatric PRS simultaneously. We first conducted the regressions between individuals (ß) and then within DZ twin pairs (ßw ), which controls for indirect pathways. RESULTS: In childhood, the PRS for ADHD predicted general psychopathology (ß = 0.09, 95% CI: [0.06, 0.12]; ßw = 0.07 [0.01, 0.12]). Furthermore, the PRS for ADHD predicted specific inattention (ß = 0.04 [0.00, 0.08]; ßw = 0.09 [0.01, 0.17]) and specific hyperactivity (ß = 0.07 [0.04, 0.11]; ßw = 0.09 [0.01, 0.16]); the PRS for schizophrenia predicted specific learning (ß = 0.08 [0.03, 0.13]; ßw = 0.19 [0.08, 0.30]) and specific inattention problems (ß = 0.05 [0.01, 0.09]; ßw = 0.10 [0.02, 0.19]); and the PRS for neuroticism predicted specific anxiety (ß = 0.06 [0.02, 0.10]; ßw = 0.06 [0.00, 0.12]). Overall, the PRS-general factor associations were similar between individuals and within twin pairs, whereas the PRS-specific factors associations amplified by 84% within pairs. CONCLUSIONS: This implies that PRS-psychiatric symptom associations did not appear attributable to indirect pathways such as population stratification, assortative mating, or mediation via parental environments. Rather, genetics appeared to directly influence symptomatology.

Direct and Indirect Associations of Widespread Individual Differences in Brain White Matter Microstructure With Executive Functioning and General and Specific Dimensions of Psychopathology in Children.

BACKGROUND: Executive functions (EFs) are important partly because they are associated with risk for psychopathology and substance use problems. Because EFs have been linked to white matter microstructure, we tested the prediction that fractional anisotropy (FA) and mean diffusivity (MD) in white matter tracts are associated with EFs and dimensions of psychopathology in children younger than the age of widespread psychoactive substance use. METHODS: Parent symptom ratings, EF test scores, and diffusion tensor parameters from 8588 9- to 10-year-olds in the ABCD Study (Adolescent Brain Cognitive Development Study) were used. RESULTS: A latent factor derived from EF test scores was significantly associated with specific conduct problems and attention-deficit/hyperactivity disorder problems, with dimensions defined in a bifactor model. Furthermore, EFs were associated with FA and MD in 16 of 17 bilateral white matter tracts (range: ß = .05; SE = .17; through ß = -.31; SE = .06). Neither FA nor MD was directly associated with psychopathology, but there were significant indirect associations via EFs of both FA (range: ß = .01; SE = .01; through ß = -.09; SE = .02) and MD (range: ß = .01; SE = .01; through ß = .09; SE = .02) with both specific conduct problems and attention-deficit/hyperactivity disorder in all tracts except the forceps minor. CONCLUSIONS: EFs in children are inversely associated with diffusion tensor imaging measures in nearly all tracts throughout the brain. Furthermore, variance in diffusion tensor measures that is shared with EFs is indirectly shared with attention-deficit/hyperactivity disorder and conduct problems.

Differentiated nomological networks of internalizing, externalizing, and the general factor of psychopathology ('p factor') in emerging adolescence in the ABCD study.

BACKGROUND: Structural models of psychopathology consistently identify internalizing (INT) and externalizing (EXT) specific factors as well as a superordinate factor that captures their shared variance, the p factor. Questions remain, however, about the meaning of these data-driven dimensions and the interpretability and distinguishability of the larger nomological networks in which they are embedded. METHODS: The sample consisted of 10 645 youth aged 9-10 years participating in the multisite Adolescent Brain and Cognitive Development (ABCD) Study. p, INT, and EXT were modeled using the parent-rated Child Behavior Checklist (CBCL). Patterns of associations were examined with variables drawn from diverse domains including demographics, psychopathology, temperament, family history of substance use and psychopathology, school and family environment, and cognitive ability, using instruments based on youth-, parent-, and teacher-report, and behavioral task performance. RESULTS: p exhibited a broad pattern of statistically significant associations with risk variables across all domains assessed, including temperament, neurocognition, and social adversity. The specific factors exhibited more domain-specific patterns of associations, with INT exhibiting greater fear/distress and EXT exhibiting greater impulsivity. CONCLUSIONS: In this largest study of hierarchical models of psychopathology to date, we found that p, INT, and EXT exhibit well-differentiated nomological networks that are interpretable in terms of neurocognition, impulsivity, fear/distress, and social adversity. These networks were, in contrast, obscured when relying on the a priori Internalizing and Externalizing dimensions of the CBCL scales. Our findings add to the evidence for the validity of p, INT, and EXT as theoretically and empirically meaningful broad psychopathology liabilities.

The General Factor of Psychopathology in the Adolescent Brain Cognitive Development (ABCD) Study: A Comparison of Alternative Modeling Approaches.

Many models of psychopathology include a single general factor of psychopathology (GFP) or "p factor" to account for covariation across symptoms. The Adolescent Brain Cognitive Development (ABCD) Study provides a rich opportunity to study the development of the GFP. However, a variety of approaches for modeling the GFP have emerged, raising questions about how modeling choices impact estimated GFP scores. We used the ABCD baseline assessment (ages 9-10 years-old; N=11,875) of the parent-rated Child Behavior Checklist (CBCL) to examine the implications of modeling the GFP using items versus scales; using a priori CBCL scales versus data-driven dimensions; and using bifactor, higher-order, or single-factor models. Children's rank-ordering on the GFP was stable across models, with GFP scores similarly related to criterion variables. Results suggest that while theoretical debates about modeling the GFP continue, the practical implications of these choices for rank-ordering children and assessing external associations will often be modest.

Hierarchical models of psychopathology: empirical support, implications, and remaining issues.

There is an ongoing revolution in psychology and psychiatry that will likely change how we conceptualize, study and treat psychological problems.- Many theorists now support viewing psychopathology as consisting of continuous dimensions rather than discrete diagnostic categories. Indeed, recent papers have proposed comprehensive taxonomies of psychopathology dimensions to replace the DSM and ICD taxonomies of categories. The proposed dimensional taxonomies, which portray psychopathology as hierarchically organized correlated dimensions, are now well supported at phenotypic levels. Multiple studies show that both a general factor of psychopathology at the top of the hierarchy and specific factors at lower levels predict different functional outcomes. Our analyses of data on a large representative sample of child and adolescent twins suggested the causal hypothesis that phenotypic correlations among dimensions of psychopathology are the result of many familial influences being pleiotropic. That is, most genetic variants and shared environmental factors are hypothesized to non-specifically influence risk for multiple rather than individual dimensions of psychopathology. In contrast, person-specific experiences tend to be related to individual dimensions. This hierarchical causal hypothesis has been supported by both large-scale family and molecular genetic studies. Current research focuses on three issues. First, the field has not settled on a preferred statistical model for studying the hierarchy of causes and phenotypes. Second, in spite of encouraging progress, the neurobiological correlates of the hierarchy of dimensions of psychopathology are only partially described. Third, although there are potentially important clinical implications of the hierarchical model, insufficient research has been conducted to date to rec-ommend evidence-based clinical practices.

The general factor of psychopathology: a comparison with the general factor of intelligence with respect to magnitude and predictive validity.

In recent years, there has been a surge of interest in the general factor of psychopathology ("p"), which is intended to summarize broad psychiat-ric comorbidity into a single index. In this study, rather than attempting to validate this model using statistical techniques, we compared the magnitude (as indicated by the variance explained in the respective indicators) and the predictive validity of the "p" factor with those of the gen-eral factor of intelligence ("g"). To compare the magnitude, for "g", we analyzed fifteen Wechsler Adult Intelligence Scale subtests (N=1,200). For "p", we analyzed fourteen psychiatric diagnoses in Swedish adults (N=909,699), eight self- and parent-rated psychopathology scales in Swedish adolescents (N=2,069), and sixteen parent-rated psychopathology scales in Swedish children (N=14,589). To compare the predictive validity, we analyzed Swedish male military conscripts (N=414,595, mean age: 18.3 years) with measures on both "g" and "p" (derived from eight psychiatric diagnoses). We then examined their unique associations with three intelligence-related outcomes (annual income, highest education, and university entrance exam scores), and sixteen adverse outcomes (e.g., suicidal behavior, psychotropic medication prescription, and criminality) retrieved from registers (mean age at follow-up = 29.2 years). Results indicated that the magnitudes of "g" and "p" were very similar. Controlling for "p", "g" significantly predicted later education (standardized beta, ß=0.38, SE=0.01) and university entrance exam scores (ß=0.48, SE=0.01). Controlling for "g", "p" significantly predicted all adverse outcomes (mean ß=0.32; range: 0.15 to 0.47). These findings support the notion that psychopathology indicators can be combined into a single score, similar to how intelligence subtests are combined into a general intelligence score. This "p" score might supplement specific diagnoses when formulating a management plan and predicting prognosis.

White matter microstructure correlates of general and specific second-order factors of psychopathology.

Increasing data indicate that prevalent forms of psychopathology can be organized into second-order dimensions based on their correlations, including a general factor of psychopathology that explains the common variance among all disorders and specific second-order externalizing and internalizing factors. Nevertheless, most existing studies on the neural correlates of psychopathology employ case-control designs that treat diagnoses as independent categories, ignoring the highly correlated nature of psychopathology. Thus, for instance, although perturbations in white matter microstructure have been identified across a range of mental disorders, nearly all such studies used case-control designs, leaving it unclear whether observed relations reflect disorder-specific characteristics or transdiagnostic associations. Using a representative sample of 410 young adult twins oversampled for psychopathology risk, we tested the hypothesis that some previously observed relations between white matter microstructure properties in major tracts and specific disorders are related to second-order factors of psychopathology. We examined fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD). White matter correlates of all second-order factors were identified after controlling for multiple statistical tests, including the general factor (FA in the body of the corpus callosum), specific internalizing (AD in the fornix), and specific externalizing (AD in the splenium of the corpus callosum, sagittal stratum, anterior corona radiata, and internal capsule). These findings suggest that some features of white matter within specific tracts may be transdiagnostically associated multiple forms of psychopathology through second-order factors of psychopathology rather with than individual mental disorders.

Criterion Validity and Utility of the General Factor of Psychopathology in Childhood: Predictive Associations With Independently Measured Severe Adverse Mental Health Outcomes in Adolescence.

OBJECTIVE: We examined whether a parent-rated general factor of psychopathology in childhood would predict independently measured, severe adverse mental health outcomes in adolescence. METHOD: We used the Child and Adolescent Twin Study in Sweden, which targets all twin children in Sweden. Parents rated their children (N = 16,806) on 43 symptoms of inattention, hyperactivity/impulsivity, conduct problems, and anxiety/emotionality when the twins turned 9 or 12 years of age. Adverse mental health outcomes in adolescence were retrieved from national registers, and included psychiatric diagnoses, prescription of anxiolytic or antidepressant medication, court convictions of crimes, and failure to achieve eligibility for high school. RESULTS: Parent-rated inattention, hyperactivity/impulsivity, conduct problems, and anxiety/emotionality in childhood predicted all adverse mental health outcomes in adolescence (mean odds ratio = 1.76; range = 1.41-2.18; all p < .05). However, several of these associations were nonsignificant in a multiple regression framework, suggesting the influence of common variance. A general factor of psychopathology uniquely predicted all outcomes (mean odds ratio = 1.58; range = 1.34-1.84; all p < .05), whereas the specific factors predicted only a subset of the outcomes. CONCLUSION: Mental health problems in childhood are associated with a host of adverse outcomes in adolescence, and, to a considerable extent, these associations are driven by a general factor of psychopathology. The general factor may therefore be important to clinical prognosis, which informs clinical decision making for children.

Measuring the hierarchical general factor model of psychopathology in young adults.

There is evidence that models of psychopathology specifying a general factor and specific second-order factors fit better than competing structural models. Nonetheless, additional tests are needed to examine the generality and boundaries of the general factor model. In a selected second wave of a cohort study, first-order dimensions of psychopathology symptoms in 499 23- to 31-year-old twins were analyzed. Using confirmatory factor analysis, a bifactor model specifying a general factor and specific internalizing and externalizing factors fit better than competing models. Factor loadings in this model were sex invariant despite greater variances in the specific internalizing factor among females and greater variances in the general and specific externalizing factors among males. The bifactor structure was robust to the exclusion of any single first-order dimension of psychopathology. Furthermore, the results were essentially unchanged when all overlapping symptoms that define multiple disorders were excluded from symptom dimensions. Furthermore, the best-fitting bifactor model also emerged in exploratory structural equation modeling with freely estimated cross-loadings. The general factor of psychopathology was robust across variations in measurement and analysis.

The Development of the General Factor of Psychopathology 'p Factor' Through Childhood and Adolescence.

Recent studies have suggested that the structure of psychopathology may be usefully represented in terms of a general factor of psychopathology (p-factor) capturing variance common to a broad range of symptoms transcending diagnostic domains in addition to specific factors capturing variance common to smaller subsets of more closely related symptoms. Little is known about how the general co-morbidity captured by this p-factor develops and whether general co-morbidity increases or decreases over childhood and adolescence. We evaluated two competing hypotheses: 1) dynamic mutualism which predicts growth in general co-morbidity and associated p-factor strength over time and 2) p-differentiation which predicts that manifestations of liabilities towards psychopathology become increasingly specific over time. Data came from the Zurich Project on the Social Development of Children and Youths (z-proso), a longitudinal study of a normative sample (approx. 50 % male) measured at 8 time points from ages 7 to 15. We operationalised general co-morbidity as p-factor strength in a bi-factor model and used omega hierarchical to track how this changed over development. In contrast to the predictions of both dynamic mutualism and p-differentiation, p-factor strength remained relatively constant over the studied period suggesting that such processes do not govern the interplay between psychopathological symptoms during this phase of development. Future research should focus on earlier phases of development and on factors that maintain the consistency of symptom-general covariation across this period.