We performed a quantitative review of associations between the higher order personality traits in the Big Three and Big Five models (i.e., neuroticism, extraversion, disinhibition, conscientiousness, agreeableness, and openness) and specific depressive, anxiety, and substance use disorders (SUD) in adults. This approach resulted in 66 meta-analyses. The review included 175 studies published from 1980 to 2007, which yielded 851 effect sizes. For a given analysis, the number of studies ranged from three to 63 (total sample size ranged from 1,076 to 75,229). All diagnostic groups were high on neuroticism (mean Cohen's d = 1.65) and low on conscientiousness (mean d = -1.01). Many disorders also showed low extraversion, with the largest effect sizes for dysthymic disorder (d = -1.47) and social phobia (d = -1.31). Disinhibition was linked to only a few conditions, including SUD (d = 0.72). Finally, agreeableness and openness were largely unrelated to the analyzed diagnoses. Two conditions showed particularly distinct profiles: SUD, which was less related to neuroticism but more elevated on disinhibition and disagreeableness, and specific phobia, which displayed weaker links to all traits. Moderator analyses indicated that epidemiologic samples produced smaller effects than patient samples and that Eysenck's inventories showed weaker associations than NEO scales. In sum, we found that common mental disorders are strongly linked to personality and have similar trait profiles. Neuroticism was the strongest correlate across the board, but several other traits showed substantial effects independent of neuroticism. Greater attention to these constructs can significantly benefit psychopathology research and clinical practice.

The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures.

The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures.

Understanding the association between personality and depression has implications for elucidating etiology and comorbidity, identifying at-risk individuals, and tailoring treatment. We discuss seven major models that have been proposed to explain the relation between personality and depression, and we review key methodological issues, including study design, the heterogeneity of mood disorders, and the assessment of personality. We then selectively review the extensive empirical literature on the role of personality traits in depression in adults and children. Current evidence suggests that depression is linked to traits such as neuroticism/negative emotionality, extraversion/positive emotionality, and conscientiousness. Moreover, personality characteristics appear to contribute to the onset and course of depression through a variety of pathways. Implications for prevention and prediction of treatment response are discussed, as well as specific considerations to guide future research on the relation between personality and depression.

We describe a new self-report instrument, the Inventory of Depression and Anxiety Symptoms (IDAS), which was designed to assess specific symptom dimensions related to major depression and related anxiety disorders. We created the IDAS by conducting principal factor analyses in three large samples (college students, psychiatric patients, community adults); we also examined the robustness of its psychometric properties in five additional samples (high school students, college students, young adults, postpartum women, psychiatric patients) that were not involved in the scale development process. The IDAS contains 10 specific symptom scales: Suicidality, Lassitude, Insomnia, Appetite Loss, Appetite Gain, Ill Temper, Well-Being, Panic, Social Anxiety, and Traumatic Intrusions. It also includes two broader scales: General Depression (which contains items overlapping with several other IDAS scales) and Dysphoria (which does not). The scales (a) are internally consistent, (b) capture the target dimensions well, and (c) define a single underlying factor. They show strong short-term stability, and display excellent convergent validity and good discriminant validity in relation to other self-report and interviewbased measures of depression and anxiety.

The original Inventory of Depression and Anxiety Symptoms (IDAS) contains 11 nonoverlapping scales assessing specific depression and anxiety symptoms. In creating the expanded version of the IDAS (the IDAS-II), our goal was to create new scales assessing other important aspects of the anxiety disorders as well as key symptoms of bipolar disorder. Factor analyses of the IDAS-II item pool led to the creation of seven new scales (Traumatic Avoidance, Checking, Ordering, Cleaning, Claustrophobia, Mania, Euphoria) plus an expanded version of Social Anxiety. These scales are internally consistent and show strong convergent and significant discriminant validity in relation to other self-report and interview-based measures of anxiety, depression, and mania. Furthermore, the scales demonstrate substantial criterion and incremental validity in relation to interview-based measures of DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, fourth edition) symptoms and disorders. Thus, the expanded IDAS-II now assesses a broad range of depression, anxiety, and bipolar symptoms.

Neuroticism's prospective association with common mental disorders (CMDs) has fueled the assumption that neuroticism is an independent etiologically informative risk factor. This vulnerability model postulates that neuroticism sets in motion processes that lead to CMDs. However, four other models seek to explain the association, including the spectrum model (manifestations of the same process), common cause model (shared determinants), state and scar models (CMD episode adds temporary / permanent neuroticism). To examine their validity we reviewed literature on confounding, operational overlap, stability and change, determinants, and treatment effects. None of the models is able to account for (virtually) all findings. The state and scar model cannot explain the prospective association. The spectrum model has some relevance, especially for internalizing disorders. Common causes are most important but the vulnerability model cannot be excluded although confounding of the prospective association by baseline symptoms and psychiatric history is substantial. In fact, some of the findings, such as interactions with stress and the small decay of neuroticism's effect over time, are consistent with the vulnerability model. We describe research designs that discriminate the remaining models and plea for deconstruction of neuroticism. Neuroticism is etiologically not informative yet but useful as an efficient marker of non-specified general risk.

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.