Linking antisocial behavior, substance use, and personality: an integrative quantitative model of the adult externalizing spectrum

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.

Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology

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.

Information-theoretic latent distribution modeling: distinguishing discrete and continuous latent variable models

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.

Semiparametric maximum likelihood variance component estimation using mixture moment structure models

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.

Semiparametric Maximum Likelihood Variance Component Estimation Using Mixture Moment Structure Models

Nonnormal phenotypic distributions introduce significant problems in the estimation and selection of genetic models. Here, a semiparametric maximum likelihood approach to analyzing non-normal 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.

Categorical and continuous models of liability to externalizing disorders: a direct comparison in NESARC

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.

Externalizing psychopathology in adulthood: a dimensional-spectrum conceptualization and its implications for DSM-V

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.

Delineating the structure of normal and abnormal personality: an integrative hierarchical approach

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.

An empirical comparison of information-theoretic selection criteria for multivariate behavior genetic models

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.

Delineating the structure of normal and abnormal personality: an integrative hierarchical approach

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.

Identifying Psychopathy Subtypes on the Basis of Personality Structure

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.

Using latent trait modeling to conceptualize an alcohol problems continuum

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.

Structural models of comorbidity among common mental disorders: connections to chronic pain

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.

The extended genotype: the heritability of personality accounts for the heritability of recalled family environments in twins reared apart

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.

A cross-cultural study of the structure of comorbidity among common psychopathological syndromes in the general health care setting

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.

Normal and abnormal personality traits: evidence for genetic and environmental relationships in the Minnesota Study of Twins Reared Apart

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.