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Although advances have improved our ability to describe the measurement precision of a test, it often remains challenging to summarize how well a test is performing overall. Reliability, for example, provides an overall summary of measurement precision, but it is sample-specific and might not reflect the potential usefulness of a test if the sample is poorly suited for the test's purposes. The test information function, conversely, provides detailed sample-independent information about measurement precision, but it does not provide an overall summary of test performance. Here, the concept of information utility is introduced. Information utility provides an index of how much psychometric information a measure (e.g., item, test) provides about a trait overall. Information utility has a number of important applied implications, including test selection, trait estimation, computerized adaptive testing, and hypothesis testing. Information utility may have particular utility in situations where the accuracy of prior information about trait level is vague or unclear., (PsycINFO Database Record (c) 2013 APA, all rights reserved.)

There has been substantial recent interest in the development of a quantitative, empirically based model of psychopathology. However, the majority of pertinent research has focused on analyses of diagnoses, as described in current official nosologies. This is a significant limitation because existing diagnostic categories are often heterogeneous. In the current research, we aimed to redress this limitation of the existing literature, and to directly compare the fit of categorical, continuous, and hybrid (i.e., combined categorical and continuous) models of syndromes derived from indicators more fine-grained than diagnoses. We analyzed data from a large representative epidemiologic sample (the 2007 Australian National Survey of Mental Health and Wellbeing; N = 8,841). Continuous models provided the best fit for each syndrome we observed (distress, obsessive compulsivity, fear, alcohol problems, drug problems, and psychotic experiences). In addition, the best fitting higher-order model of these syndromes grouped them into three broad spectra: Internalizing, Externalizing, and Psychotic Experiences. We discuss these results in terms of future efforts to refine emerging empirically based, dimensional-spectrum model of psychopathology, and to use the model to frame psychopathology research more broadly., (2013 APA, all rights reserved)

Multivariate comorbidity research indicates mood and anxiety (internalizing) disorders share one or more common liabilities, but categorical, dimensional, and hybrid accounts of these liabilities have not been directly compared. We modeled seven internalizing disorders in a nationally representative sample of 43,093 individuals via confirmatory factor, latent class, exploratory factor mixture, and exploratory structural equation modeling analyses. A two-dimensional (distress-fear) liability structure fit best and replicated across gender, assessment waves, and lifetime/12-month diagnoses. These liabilities, not disorder-specific variation, predicted future internalizing pathology, suicide attempts, angina, and ulcer., (2013 APA, all rights reserved)

A multidimensional trait system has been proposed for representing personality disorder (PD) features in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) to address problematic classification issues such as comorbidity. In this model, which may also assist in providing scaffolding for the underlying structure of major forms of psychopathology more generally, 25 primary traits are organized by 5 higher order dimensions: Negative Affect, Detachment, Antagonism, Disinhibition, and Psychoticism. We examined (a) the generalizability of the structure proposed for DSM-5 PD traits, and (b) the potential for an integrative hierarchy based upon DSM-5 PD traits to represent the dimensions scaffolding psychopathology more generally. A large sample of student participants (N = 2,461) completed the Personality Inventory for DSM-5, which operationalizes the DSM-5 traits. Exploratory factor analysis replicated the initially reported 5-factor structure, as indicated by high factor congruencies. The 2-, 3-, and 4-factor solutions estimated in the hierarchy of the DSM-5 traits bear close resemblance to existing models of common mental disorders, temperament, and personality pathology. Thus, beyond the description of individual differences in personality disorder, the trait dimensions might provide a framework for the metastructure of psychopathology in the DSM-5 and the integration of a number of ostensibly competing models of personality trait covariation., ((PsycINFO Database Record (c) 2012 APA, all rights reserved).)

Background: DSM-IV-TR suggests that clinicians should assess clinically relevant personality traits that do not necessarily constitute a formal personality disorder (PD), and should note these traits on Axis II, but DSM-IV-TR does not provide a trait model to guide the clinician. Our goal was to provide a provisional trait model and a preliminary corresponding assessment instrument, in our roles as members of the DSM-5 Personality and Personality Disorders Workgroup and workgroup advisors., Method: An initial list of specific traits and domains (broader groups of traits) was derived from DSM-5 literature reviews and workgroup deliberations, with a focus on capturing maladaptive personality characteristics deemed clinically salient, including those related to the criteria for DSM-IV-TR PDs. The model and instrument were then developed iteratively using data from community samples of treatment-seeking participants. The analytic approach relied on tools of modern psychometrics (e.g. item response theory models)., Results: A total of 25 reliably measured core elements of personality description emerged that, together, delineate five broad domains of maladaptive personality variation: negative affect, detachment, antagonism, disinhibition, and psychoticism., Conclusions: We developed a maladaptive personality trait model and corresponding instrument as a step on the path toward helping users of DSM-5 assess traits that may or may not constitute a formal PD. The inventory we developed is reprinted in its entirety in the Supplementary online material, with the goal of encouraging additional refinement and development by other investigators prior to the finalization of DSM-5. Continuing discussion should focus on various options for integrating personality traits into DSM-5.

The proposed changes to the personality disorder section of the Diagnostic and statistical manual of mental disorders (5th ed.) places an increased focus on interpersonal impairment as one of the defining features of personality psychopathology. In addition, a proposed trait model has been offered to provide a means of capturing phenotypic variation on the expression of personality disorder. In this study, the authors subject the proposed DSM-5 traits to interpersonal analysis using the inventory of interpersonal problems-circumplex scales via the structural summary method for circumplex data. DSM-5 traits were consistently associated with generalized interpersonal dysfunction suggesting that they are maladaptive in nature, the majority of traits demonstrated discriminant validity with prototypical and differentiated interpersonal problem profiles, and conformed well to a priori hypothesized associations. These results are discussed in the context of the DSM-5 proposal and contemporary interpersonal theory, with a particular focus on potential areas for expansion of the DSM-5 trait model.

Two issues pertinent to the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) proposal for personality pathology, the recovery of DSM-IV personality disorders (PDs) by proposed DSM-5 traits and the validity of the proposed DSM-5 hybrid model, which incorporates both personality pathology symptoms and maladaptive traits, were evaluated in a large undergraduate sample (N = 808). Proposed DSM-5 traits as assessed with the Personality Inventory for DSM-5 explained a substantial proportion of variance in DSM-IV PDs as assessed with the Personality Diagnostic Questionnaire-4+, and trait indicators of the 6 proposed DSM-5 PDs were mostly specific to those disorders with some exceptions. Regression analyses support the DSM-5 hybrid model in that pathological traits, and an indicator of general personality pathology severity provided incremental information about PDs. Findings are discussed in the context of broader issues around the proposed DSM-5 model of personality disorders.

Epidemiological studies of categorical mental disorders consistently report that gender differences exist in many disorder prevalence rates and that disorders are often comorbid. Can a dimensional multivariate liability model be developed to clarify how gender impacts diverse, comorbid mental disorders? We pursued this possibility in the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; N = 43,093). Gender differences in prevalence were systematic such that women showed higher rates of mood and anxiety disorders, and men showed higher rates of antisocial personality and substance use disorders. We next investigated patterns of disorder comorbidity and found that a dimensional internalizing-externalizing liability model fit the data well, where internalizing is characterized by mood and anxiety disorders, and externalizing is characterized by antisocial personality and substance use disorders. This model was gender invariant, indicating that observed gender differences in prevalence rates originate from women and men's different average standings on latent internalizing and externalizing liability dimensions. As hypothesized, women showed a higher mean level of internalizing, while men showed a higher mean level of externalizing. We discuss implications of these findings for understanding gender differences in psychopathology and for classification and intervention., (PsycINFO Database Record (c) 2012 APA, all rights reserved.)

In 2 meta-analyses involving 58 studies and 59,575 participants, we quantitatively summarized the relative reliability and validity of continuous (i.e., dimensional) and discrete (i.e., categorical) measures of psychopathology. Overall, results suggest an expected 15% increase in reliability and 37% increase in validity through adoption of a continuous over discrete measure of psychopathology alone. This increase occurs across all types of samples and forms of psychopathology, with little evidence for exceptions. For typical observed effect sizes, the increase in validity is sufficient to almost halve sample sizes necessary to achieve standard power levels. With important caveats, the current results, considered with previous research, provide sufficient empirical and theoretical basis to assume a priori that continuous measurement of psychopathology is more reliable and valid. Use of continuous measures in psychopathology assessment has widespread theoretical and practical benefits in research and clinical settings., ((PsycINFO Database Record (c) 2011 APA, all rights reserved).)

The transition from the Diagnostic and Statistical Model of Mental Disorders (4th ed., text revision [DSM-IV-TR]; American Psychiatric Association, 2000 ) to the fifth edition (DSM-5) represents an unprecedented opportunity to integrate dimensional personality trait models into the official nosology. Not surprisingly, a variety of issues have arisen in contemplating this challenging integration. In this article, we address how a dimensional personality trait model could be a helpful component of DSM-5, from the perspective of our roles as work group members and advisors involved in the creation of a trait model and corresponding assessment instrument. We focus in particular on two potential roles for a trait model in DSM-5 that are under official consideration. First, a dimensional personality trait model might be helpful in delineating the content of personality disorders. Second, a trait model might assist in organizing the "metastructure" of DSM-5 (i.e., the arrangement of chapters and other broader classificatory rubrics).

Background: Borderline personality disorder (BPD) shows high levels of co-morbidity with an array of psychiatric disorders. The meaning and causes of this co-morbidity are not fully understood. Our objective was to investigate and clarify the complex co-morbidity of BPD by integrating it into the structure of common mental disorders., Method: We conducted exploratory and confirmatory factor analyses on diagnostic interview data from a representative US population-based sample of 34 653 civilian, non-institutionalized individuals aged ≥18 years. We modeled the structure of lifetime DSM-IV diagnoses of BPD and antisocial personality disorder (ASPD), major depressive disorder, dysthymic disorder, panic disorder with agoraphobia, social phobia, specific phobia, generalized anxiety disorder, post-traumatic stress disorder, alcohol dependence, nicotine dependence, marijuana dependence, and any other drug dependence., Results: In both women and men, the internalizing-externalizing structure of common mental disorders captured the co-morbidity among all disorders including BPD. Although BPD was unidimensional in terms of its symptoms, BPD as a disorder showed associations with both the distress subfactor of the internalizing dimension and the externalizing dimension., Conclusions: The complex patterns of co-morbidity observed with BPD represent connections to other disorders at the level of latent internalizing and externalizing dimensions. BPD is meaningfully connected with liabilities shared with common mental disorders, and these liability dimensions provide a beneficial focus for understanding the co-morbidity, etiology and treatment of BPD.

The DSM-IV model of personality disorders is composed of trait sets arranged into 10 theoretically distinct, polythetically assessed categories, with little regard for how the traits comprising these disorders are interrelated and structured. Research since the publication of DSM-III has shown that this model is untenable. The question is not whether this model needs revision; rather, the question is how to move from the existing DSM-IV framework to a model better connected with data. Empirically-based models of personality trait variation provide a starting point for DSM-5, and ongoing research will be used to delineate further the empirical structure of personality traits in the pathological range. The ultimate goal is to frame future DSMs in a way that is maximally useful for clinicians as well as researchers. It is also critical to understand that the DSM-5 is intended to be a living document that will facilitate novel inquiry and clinical applications, as opposed to a document designed to promote and perpetuate a fixed set of constructs. Thus, we view a proposed trait system as a first step on a path to a well-validated, clinically-useful structure.

The literature suggests that internalizing psychopathology relates to impairment incrementally and gradually. However, the form of this relationship has not been characterized. This form is critical to understanding internalizing psychopathology, as it is possible that internalizing may accelerate in effect at some level of severity, defining a natural boundary of abnormality. Here, a novel method-semiparametric structural equation modeling-was used to model the relationship between internalizing and impairment in a sample of 8,580 individuals from the 2000 British Office for National Statistics Survey of Psychiatric Morbidity, a large, population-representative study of psychopathology. This method allows one to model relationships between latent internalizing and impairment without assuming any particular form a priori and to compare models in which the relationship is constant and linear. Results suggest that the relationship between internalizing and impairment is in fact linear and constant across the entire range of internalizing variation and that it is impossible to nonarbitrarily define a specific level of internalizing beyond which consequences suddenly become catastrophic in nature. Results demonstrate the phenomenological continuity of internalizing psychopathology, highlight the importance of impairment as well as symptoms, and have clear implications for defining mental disorder., (Copyright 2010 APA, all rights reserved)

Cramer et al. articulate a novel perspective on comorbidity. However, their network models must be compared with more parsimonious latent variable models before conclusions can be drawn about network models as plausible accounts of comorbidity. Latent variable models have proven generative in studying psychopathology and its external correlates, and we doubt network models will prove as useful for psychopathology research.

Background: Analyses of co-morbidity patterns among common mental disorders have repeatedly indicated that relationships among disorders can be understood in terms of broad superordinate dimensions. However, these analyses have been based on syndromal-level indicators, which are often heterogeneous, rather than on symptoms, which are presumably more homogeneous., Method: Symptom-level exploratory and confirmatory analyses were used to explore the joint hierarchical organization of Axis I and II psychopathology, using data on 8405 individuals from the 2000 British Psychiatric Morbidity Survey., Results: Analyses indicated that 20 identified subordinate dimensions of psychopathology could be organized into four broad superordinate dimensions: Internalizing, Externalizing, Thought Disorder, and Pathological Introversion., Conclusions: These results extend existing model frameworks 'downward' as well as 'outward', by analyzing symptoms rather than diagnoses, and by integrating symptoms from Axis I and II disorders in a common framework. This model demonstrates the importance of hierarchy in psychopathology structure, comprises replicable features of psychopathology structure, and has important implications for understanding the nature and organization of mental disorders.

Antisocial behavior, substance use, and impulsive and aggressive personality traits often co-occur, forming a coherent spectrum of personality and psychopathology. In the current research, the authors developed a novel quantitative model of this spectrum. Over 3 waves of iterative data collection, 1,787 adult participants selected to represent a range across the externalizing spectrum provided extensive data about specific externalizing behaviors. Statistical methods such as item response theory and semiparametric factor analysis were used to model these data. The model and assessment instrument that emerged from the research shows how externalizing phenomena are organized hierarchically and cover a wide range of individual differences. The authors discuss the utility of this model for framing research on the correlates and the etiology of externalizing phenomena., ((c) 2007 APA)

Distinguishing between discrete and continuous latent variable distributions has become increasingly important in numerous domains of behavioral science. Here, the authors explore an information-theoretic approach to latent distribution modeling, in which the ability of latent distribution models to represent statistical information in observed data is emphasized. The authors conclude that loss of statistical information with a decrease in the number of latent values provides an attractive basis for comparing discrete and continuous latent variable models. Theoretical considerations as well as the results of 2 Monte Carlo simulations indicate that information theory provides a sound basis for modeling latent distributions and distinguishing between discrete and continuous latent variable models in particular., (Copyright 2006 APA)

Nonnormal phenotypic distributions introduce significant problems in the estimation and selection of genetic models. Here, a semiparametric maximum likelihood approach to analyzing nonnormal phenotypes is described. In this approach, distributions are explicitly modeled together with genetic and environmental effects. Distributional parameters are introduced through mixture constraints, where the distribution of effects are discretized and freely estimated rather than assumed to be normal. Semiparametric maximum likelihood estimation can be used with a variety of genetic models, can be extended to a variety of pedigree structures, and has various advantages over other approaches to modeling nonnormal data.

Research on psychopathology is at a historical crossroads. New technologies offer the promise of lasting advances in our understanding of the causes of human psychological suffering. Making the best use of these technologies, however, requires an empirically accurate model of psychopathology. Much current research is framed by the model of psychopathology portrayed in current versions of the Diagnostic and Statistical Manual of Mental Disorders (DSM; American Psychiatric Association, 2000). Although the modern DSMs have been fundamental in advancing psychopathology research, recent research also challenges some assumptions made in the DSM-for example, the assumption that all forms of psychopathology are well conceived of as discrete categories. Psychological science has a critical role to play in working through the implications of this research and the challenges it presents. In particular, behavior-genetic, personality, and quantitative-psychological research perspectives can be melded to inform the development of an empirically based model of psychopathology that would constitute an evolution of the DSM.

Comorbidity has presented a persistent puzzle for psychopathology research. We review recent literature indicating that the puzzle of comorbidity is being solved by research fitting explicit quantitative models to data on comorbidity. We present a meta-analysis of a liability spectrum model of comorbidity, in which specific mental disorders are understood as manifestations of latent liability factors that explain comorbidity by virtue of their impact on multiple disorders. Nosological, structural, etiological, and psychological aspects of this liability spectrum approach to understanding comorbidity are discussed.

Context: Patterns of genetic, environmental, and phenotypic relationships among antisocial behavior and substance use disorders indicate the presence of a common externalizing liability. However, whether this liability is relatively continuous and graded, or categorical and class-like, has not been well established., Objectives: To compare the fit of categorical and continuous models of externalizing liability in a large, nationally representative sample., Design: Categorical and continuous models of externalizing liability were compared using interview data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC)., Setting: Face-to-face interviews conducted in the United States., Participants: Random sample of 43 093 noninstitutionalized adult civilians living in the United States., Main Outcome Measures: Lifetime and current (past 12 months) diagnoses of antisocial personality disorder, nicotine dependence, alcohol dependence, marijuana dependence, cocaine dependence, and other substance dependence., Results: In the entire sample, as well as for males and females separately, using either lifetime or current diagnoses, the best-fitting model of externalizing liability was a continuous normal model. Moreover, there was a general trend toward latent trait models fitting better than latent class models, indicating that externalizing liability was continuous and graded, rather than categorical and class-like., Conclusions: Liability to externalizing spectrum disorders is graded and continuous normal in distribution. Research regarding etiology, assessment, and treatment of externalizing disorders should target externalizing liability over a range of severity. Current diagnoses represent extremes of this continuous liability distribution, indicating that conditions currently classified as subthreshold are likely to provide important information regarding liability to externalizing phenomena.

Mental disorders involving antisocial behavior and substance use are genetically linked and vary continuously. The authors present a review and integrative conceptualization of these observations in terms of a dimensional and hierarchically organized externalizing spectrum. As a foundation for this conceptualization, the authors introduce a quantitative, model-based approach to comparing categorical and continuous conceptions of psychopathology and apply this approach in an empirical study of patterns of comorbidity among externalizing disorders as defined in the Diagnostic and Statistical Manual of Mental Disorders. The authors present evidence that comorbidity among externalizing disorders is best modeled by an underlying normally distributed continuum of risk for multiple disorders within the externalizing spectrum. The authors conclude by discussing implications of the externalizing spectrum conceptualization for classification of disorders in the upcoming 5th edition of the Diagnostic and Statistical Manual of Mental Disorders., (Copyright (c) 2005 APA, all rights reserved.)

Increasing evidence indicates that normal and abnormal personality can be treated within a single structural framework. However, identification of a single integrated structure of normal and abnormal personality has remained elusive. Here, a constructive replication approach was used to delineate an integrative hierarchical account of the structure of normal and abnormal personality. This hierarchical structure, which integrates many Big Trait models proposed in the literature, replicated across a meta-analysis as well as an empirical study, and across samples of participants as well as measures. The proposed structure resembles previously suggested accounts of personality hierarchy and provides insight into the nature of personality hierarchy more generally. Potential directions for future research on personality and psychopathology are discussed.

Information theory provides an attractive basis for statistical inference and model selection. However, little is known about the relative performance of different information-theoretic criteria in covariance structure modeling, especially in behavioral genetic contexts. To explore these issues, information-theoretic fit criteria were compared with regard to their ability to discriminate between multivariate behavioral genetic models under various model, distribution, and sample size conditions. Results indicate that performance depends on sample size, model complexity, and distributional specification. The Bayesian Information Criterion (BIC) is more robust to distributional misspecification than Akaike's Information Criterion (AIC) under certain conditions, and outperforms AIC in larger samples and when comparing more complex models. An approximation to the Minimum Description Length (MDL; Rissanen, J. (1996). IEEE Transactions on Information Theory 42:40-47, Rissanen, J. (2001). IEEE Transactions on Information Theory 47:1712-1717) criterion, involving the empirical Fisher information matrix, exhibits variable patterns of performance due to the complexity of estimating Fisher information matrices. Results indicate that a relatively new information-theoretic criterion, Draper's Information Criterion (DIC; Draper, 1995), which shares features of the Bayesian and MDL criteria, performs similarly to or better than BIC. Results emphasize the importance of further research into theory and computation of information-theoretic criteria.

The authors used model-based cluster analysis to identify subtypes of criminal psychopaths on the basis of differences in personality structure. Participants included 96 male prisoners diagnosed as psychopathic, using the Psychopathy Checklist Revised (PCL-R; R. D. Hare, 1991). Personality was assessed using the brief form of the Multidimensional Personality Questionnaire (MPQ-BF; C. J. Patrick, J. J. Curtin, and A. Tellegen, 2002). The best-fitting model yielded two clusters. Emotionally stable psychopaths were characterized by low Stress Reaction and high Agency. Aggressive psychopaths were characterized by high Negative Emotionality, low Constraint, and low Communion. These results suggest that psychopaths as defined by the PCL-R includes distinct subtypes, distinguishable in terms of personality structure, that may reflect different etiologies.

Recent research points toward the viability of conceptualizing alcohol problems as arrayed along a continuum. Nevertheless, modern statistical techniques designed to scale multiple problems along a continuum (latent trait modeling; LTM) have rarely been applied to alcohol problems. This study applies LTM methods to data on 110 problems reported during in-person interviews of 1,348 middle-aged men (mean age=43) from the general population. The results revealed a continuum of severity linking the 110 problems, ranging from heavy and abusive drinking, through tolerance and withdrawal, to serious complications of alcoholism. These results indicate that alcohol problems can be arrayed along a dimension of severity and emphasize the relevance of LTM to informing the conceptualization and assessment of alcohol problems., (((c) 2004 APA, all rights reserved))

Patterns of comorbidity among common mental disorders can be understood from the perspective of a model that regards mood, anxiety and somatization disorders as elements within an internalizing spectrum of disorder, and substance use and antisocial behavior disorders as elements within a separate externalizing spectrum of disorder. In this chapter, we evaluate the possibility of linking this model to literature on chronic pain. Evidence from psychosocial and biological perspectives points towards mechanisms that link chronic pain to internalizing disorders. Such evidence indicates that the internalizing-externalizing model may provide a useful framework for suggesting new directions for research on connections between chronic pain and mood, anxiety, and related disorders and traits.

How are retrospective accounts of family rearing environments linked to adult personality? We addressed this question by measuring both domains in a sample of 180 reared-apart twins. Twins completed extensive measures of rearing environments (the Minnesota-Briggs History Record, the Block Environmental Questionnaire, the Family Environment Scale, and the Physical Facilities Questionnaire) and an omnibus measure of adult personality (the Multidimensional Personality Questionnaire). Retrospective accounts of family environments were partially heritable and all the heritable variance in environmental measures could be accounted for by heritable variance in personality. In addition, differences between twins in their accounts of their rearing environments (nonshared environmental factors) were not significantly linked to differences between twins in their personalities. Hence, family environmental measures appear to be heritable because personality genes influence the way people shape and recall their rearing environments. In addition, differences in reared-apart twins' retrospectively recalled rearing environments appear to have little impact on differences in their personalities in adulthood.

This study presents analyses of 7 common psychopathological syndromes in the World Health Organization (WHO) Collaborative Study of Psychological Problems in General Health Care (T. B. Ustun & N. Sartorius, 1995). Data on depression, somatization, hypochondriasis, neurasthenia, anxious worry, anxious arousal, and hazardous use of alcohol were analyzed for 14 countries (Ns for each country ranged from 196 to 800). Four models were evaluated: a 1-factor model; a 2-factor model in which all syndromes except hazardous use of alcohol represented internalizing problems; and two 3-factor models. The 2-factor model fit best. These results extend previous research on the 2-factor model to the current complaints of attendees of general health care clinics, to a new set of syndromes, and to a variety of both Western and non-Western countries.

Recent studies have demonstrated substantial correlations between normal and abnormal personality traits. Yet little is known about how these correlations are mediated genetically and environmentally: Do normal and abnormal personality traits stem from the same underlying genes and environments? We addressed this question using data from 128 monozygotic and dizygotic twin pairs in the Minnesota Study of Twins Reared Apart (MISTRA). Additive genetic and nonshared environmental correlations between scales of the Minnesota Multiphasic Personality Inventory (MMPI)--an index of abnormal personality--and the Multidimensional Personality Questionnaire (MPQ)--an index of normal personality--were estimated. Results indicated that phenotypic correlations between normal and abnormal personality were mediated by genetic as well as environmental factors, although the magnitude of genetic mediation tended to be larger overall. Moreover, the patterns of phenotypic, genetic, and environmental relationships among the scales were similar, suggesting that influences on normal and abnormal personality act through systems common to both. It is suggested that future research focus on the neurogenetic substrates of these shared systems and how dysfunction in these systems influences development of disordered personality.