Toward a clinically-oriented model of anxiety disorders

The Diagnostic and Statistical Manual of Mental Disorders (DSM) model of psychopathology has generally been the accepted standard in North America for understanding and diagnosing psychological disorders for over half a century. This classification model, particularly since DSM-III, has been formulated around the goals of aiding diagnosis, enhancing communication among professionals, fostering psychopathology research and informing treatment. However, all classification systems are inherently dependent on the purpose for the classification. In this paper, an argument is made for a clinically-relevant diagnostic system of mental disorders to support a primary goal of informing treatment. Several lines of research are examined, including studies on diagnostic reliability, dimensional vs categorical nature of anxiety disorders, co-morbidity, and psychotherapeutic and pharmacological treatment outcome as they relate to current and proposed diagnostic models of anxiety disorders. Based on the evidence, suggestions are made for revising diagnostic models of anxiety, and key lines of future research are proposed.     

Diagnostic categories or dimensions? A question for the Diagnostic And Statistical Manual Of Mental Disorders--fifth edition

The question of whether mental disorders are discrete clinical conditions or arbitrary distinctions along dimensions of functioning is a long-standing issue, but its importance is escalating with the growing recognition of the frustrations and limitations engendered by the categorical model. The authors provide an overview of some of the dilemmas of the categorical model, followed by a discussion of research that addresses whether mental disorders are accurately or optimally classified categorically or dimensionally. The authors' intention is to document the importance of this issue and to suggest that future editions of the Diagnostic and Statistical Manual of Mental Disorders give more recognition to dimensional models of classification. They conclude with a dimensional mental disorder classification that they suggest provides a useful model.     

An invariant dimensional liability model of gender differences in mental disorder prevalence: evidence from a national sample

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.     

Introduction to the special section: toward a dimensionally based taxonomy of psychopathology

Much current psychopathology research is framed by categorical constructs. Limitations of categorical constructs have been articulated, and dimensional constructs are often proposed as viable alternatives to categories of psychopathology. The purpose of this Special Section is to articulate and discuss diverse issues that arise in contemplating dimensional constructs as targets for psychopathology research.     

Dimensional analysis of a categorical diagnostic interview: the DICA-IV

The aim of this study is to obtain dimensions from a categorical diagnostic interview. 512 children aged 8 to 17 attending public centers for children's mental health and presenting some form of psychological disorder were interviewed with the "Diagnostic Interview for Children and Adolescents" (DICA-IV). Analysis of the principal components indicate that a two-dimensional model (externalizing-internalizing) satisfactorily explain the data collected from the children and their parents. The data from the adolescents are better represented by a three-dimensional model (attention problems-internalizing-antisocial behavior). The factor scales show good internal consistency and significantly relate to other criteria of psychopathology and incapacity (concurrent validity). These results show that it is possible to use DICA-IV to obtain categorical and dimensional indicators simultaneously. The latter are particularly sensitive for measuring changes over the course of disorders.     

Progress and innovation: personality disorders and the vanguard of psychopathology research

Important progress in our understanding of the natural course of personality disorders (PDs) is documented in the articles for this special section. This progress could set the stage for ideas developed in the study of PDs to play a central role in research on psychopathology more broadly conceived. The Collaborative Longitudinal Personality Disorders Study (Skodol et al., this issue), the Children in the Community Study (Cohen, Crawford, Johnson, & Kasen, this issue), and the McLean Study of Adult Development (Zanarini, Frankenburg, Hennen, Reich, & Silk, this issue) reveal the importance of personality in understanding psychopathology, and point toward a dimensional approach to conceptualizing psychopathology that could also frame categorical clinical decision making processes.     

Dimensional models of psychopathology: research agenda and clinical utility

This commentary emphasizes the implications for a mental health research agenda that stem from the papers in this special section on dimensional models of psychopathology. These include the need to extend dimensional models to a wider range of psychopathology; the relationship of the dimensions described in these papers, largely based on symptom and self-report measures, to findings from current research in genetics, neuroimaging, and other domains of neuroscience; the need for new scales that can assess the entire range of relevant dimensions with modern psychometric techniques; and ways to employ these dimensions in applied clinical situations. It is concluded that hierarchical dimensional models offer powerful ways of organizing our thinking about psychopathology and will serve to guide many promising avenues of future research.     

Diagnosis of personality disorders: a case study

In this article, I report a case highlighting diagnostic uncertainty about psychopathology on both Axes I and II. It concerns in part the problem of comorbidity in relation to diagnostic classification of Axis II personality disorders. After commenting on these uncertainties in relation to categorical and dimensional models, I also consider a psychoanalytic explanation to illustrate an example in which a theoretical model informs diagnostic interviewing. I emphasize how the clinical information that unfolds from an interview based on this theoretical model generates inferences about psychopathology that extend clinical understanding beyond the formal diagnostic assessment of Axes I and II disorders and assessment by self-report.     

Diagnosis of Personality Disorders: A Case Study

In this article, I report a case highlighting diagnostic uncertainty about psychopathology on both Axes I and II. It concerns in part the problem of comorbidity in relation to diagnostic classification of Axis II personality disorders. After commenting on these uncertainties in relation to categorical and dimensional models, I also consider a psychoanalytic explanation to illustrate an example in which a theoretical model informs diagnostic interviewing. I emphasize how the clinical information that unfolds from an interview based on this theoretical model generates inferences about psychopathology that extend clinical understanding beyond the formal diagnostic assessment of Axes I and II disorders and assessment by self-report.     

Geology 102: More Thoughts on a Shift to a Dimensional Model of Personality Disorders

The classification of personality disorders is at a critical stage. The categorical model presented in the official diagnostic manual of mental disorders has serious limitations, and it is time for a shift to a dimensional model of personality disorder. Although the evidence in favor of switching to a dimensional model of personality disorder is compelling, the fields of clinical psychology and psychiatry have been reluctant to make the shift. We think some of this reluctance is due to a misunderstanding of the current state of dimensional models of personality and personality disorders. We address three major myths about dimensional models and provide responses to each.     

Endophenotypes and the diagnosis of personality disorders

It has been suggested that psychiatric diagnosis should come to depend on endophenotypes, in order to define more precisely the mechanisms behind mental disorders. This construct is associated with the assumption that mental processes can be reduced to activity at a neuronal level. The approach has had a strong influence on the conceptual basis of proposals for DSM-5, but could be consistent either with categorical or dimensional diagnosis. However, application of endophenotypes to personality disorders is unlikely for the foreseeable future, given an insufficient knowledge of etiology and pathogenesis.     

Dimensional and Cross‐Cutting Assessment in the DSM‐5

A significant proposed change to the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM‐5) that will significantly affect the way counselors diagnose mental disorders is the addition of dimensional assessments to the categorical diagnoses. The author reviews the current DSM's (4th ed., text rev.; American Psychiatric Association, 2000 ) categorical classification system, describes the proposed dimensional and cross‐cutting assessments, and provides implications about clinical utility and user acceptability of a dimensional diagnostic approach.     

Between-group differences and taxometrics

In psychological research it can be of interest to differentiate between the categorical (taxonic) vs dimensional (nontaxonic) nature of phenomena, for example in the field of psychopathology. For categorical (taxonic) structures a further differentiation is possible: between categorical structures with dimensional equivalence and a substantial main effect, and structures without dimensional equivalence (independent of the main effect). Previous taxometric studies have not concentrated in an explicit way on the case of nonequivalence. It is shown here that under favorable circumstances both types of categorical structures can be detected using the taxometric procedure L-Mode, but that they cannot be differentiated from one another.     

心理病理学网络理论、方法与挑战

对于精神障碍这一概念的理解, 传统DSM-ICD分类诊断系统和研究领域标准RDoC均基于潜变量视角, 认为精神障碍的症状由其潜在共同原因所致。这2种观点都忽略了症状间的相互作用。不同于分类和维度视角, Borsboom在2008年对精神障碍的概念化提出了的全新视角——心理病理学网络理论。此理论的核心观点是症状之间的动态因果关系构成了精神障碍。基于心理病理学网络理论的网络分析方法, 主要以结合EBIC的glasso算法估计症状间的偏相关网络, 并通过网络中节点中心性与网络连接性等指标, 来考查精神障碍症状的不同特性。近几年来, 研究者发现心理病理学网络分析方法在对症状间因果关系的推断、核心症状的识别和网络结构的可靠性与可重复性方面仍面临一些挑战。这些挑战为心理病理学网络理论与方法指明了未来可能的发展方向。     

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.     

The Dimensional Nature of Externalizing Behaviors in Adolescence: Evidence from a Direct Comparison of Categorical,Dimensional, and Hybrid Models

Researchers have recognized the importance of developing an accurate classification system for externalizing disorders, though much of this work has been framed by a priori preferences for categorical vs. dimensional constructs. Newer statistical technologies now allow categorical and dimensional models of psychopathology to be compared empirically. In this study, we directly compared the fit of categorical and dimensional models of externalizing behaviors in a large and representative community sample of adolescents at two time points separated by nearly 2.5 years (N = 2027; mean age at Time 1 = 11.09 years; 50.8% female). Delinquent and aggressive behaviors were assessed with child and parent Child Behavior Checklist reports. Latent trait, latent class, and factor mixture models were fit to the data, and at both time points, the latent trait model provided the best fit to the data. The item parameters were inspected and interpreted, and it was determined that the items were differentially sensitive across all regions of the dimension. We conclude that classification models can be based on empirical evidence rather than a priori preferences, and while current classification systems conceptualize externalizing problems in terms of discrete groups, they can be better conceptualized as dimensions.     

Clarifying the Placement of Obsessive-Compulsive Disorder in the Empirical Structure of Psychopathology

Recent work on the empirical structure of psychopathology has aimed to address some limitations that can arise from traditional categorical classification approaches. This research has focused on modeling patterns of co-occurrence among traditional diagnoses, uncovering a variety of well-validated dimensions (or spectra) of psychopathology, spanning common and uncommon mental disorders. A model integrating these empirically derived spectra (the Hierarchical Taxonomy of Psychopathology; HiTOP) has been proposed. However, the placement of obsessive-compulsive disorder (OCD) within this model remains unclear, as studies have variably found OCD to fit best as part of the Fear, Distress or Thought Disorder spectra. One reason for this may be the heterogeneity of symptoms experienced by individuals with OCD, which is lost when analysing categorical diagnoses. For example, different symptom clusters within OCD—such as washing and contamination versus obsessions and checking—may be differentially associated with different spectra in the HiTOP model. The aim of this study was to test this hypothesis. Data were collected in an anonymous online survey from community participants (n?=?609), largely with elevated symptoms of mental illness, and analyzed in a factor analytic framework treating OCD as a unitary construct and as four separate symptom clusters. The results indicated that OCD and its constituent symptom clusters had significant loadings of varying strength on the Fear and Thought Disorder spectra. These findings suggest that OCD may be best characterized as cross-loading on both the Fear and Thought Disorder spectra, and highlight the importance of accounting for diagnostic heterogeneity in future research.

     

Dimensional Assessment of Emotional Disorder Outcomes in Transdiagnostic Treatment: A Clinical Case Study

Current classification systems for mental disorders emphasize categorical assessment. In the domain of emotional disorders, this is inconsistent with a growing consensus that anxiety, depressive, and related disorders are best conceptualized as variations on shared underlying processes, chiefly heightened negative affect, and aversion to unwanted emotional experiences. Dimensional assessment of transdiagnostic emotional disorder constructs offers advantages for clinical and research applications, including increased parsimony and improved validity, yet there are drawbacks to many dimensional assessment systems for emotional disorders. The case presented in this paper illustrates the potential clinical utility of a new self-report instrument—the Multidimensional Emotional Disorders Inventory (MEDI)—which assesses nine dimensions characteristic of emotional disorders. MEDI scores for a highly comorbid patient are examined over the course of transdiagnostic emotion-focused cognitive-behavioral treatment. At baseline, midtreatment, and posttreatment, the MEDI offered information above and beyond DSM categorical assessment, including detection of subclinical symptoms and symptom change, while remaining parsimonious. Implications for possible use as a treatment planning instrument, integration with categorical assessment, and future research directions are discussed.     

Beliefs about essences and the reality of mental disorders

Do people believe mental disorders are real and possess underlying essences? The current study found that both novices and practicing clinicians held weaker essentialist beliefs about mental disorders than about medical disorders. They were also unwilling to endorse the idea that mental disorders are real and natural. Furthermore, compared with novices, mental health clinicians were less likely to endorse the view that there is a shared cause underlying a mental disorder and that one needs to remove the cause to get rid of the mental disorder. Clinicians were polarized on their views about whether mental disorders are categorical or dimensional. These findings reflect current controversies about mental disorders in the field at large.     

Taxometrics in psychopathology research: an introduction to some of the procedures and related methodological issues

This article introduces a special section on the use of taxometrics to examine the categorical versus the dimensional structure of various forms of psychopathology. Paving the way into the special section, this introduction briefly describes 3 taxometric methods--mean above minus below a sliding cut (MAMBAC), maximum covariation (MAXCOV), and maximum eigenvalue (MAXEIG)--and discusses possible threats to statistical conclusion validity that often emerge when such techniques are applied in psychopathology research.