Roman Kotov

Linking “big” personality traits to anxiety, depressive, and substance use disorders: A meta-analysis.

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 Cohens 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 Eysencks 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.

New Dimensions in the Quantitative Classification of Mental Illness

CONTEXT Patterns of comorbidity among mental disorders are thought to reflect the natural organization of mental illness. Factor analysis can be used to investigate this structure and construct a quantitative classification system. Prior studies identified 3 dimensions of psychopathology: internalizing, externalizing, and thought disorder. However, research has largely relied on common disorders and community samples. Consequently, it is unclear how well the identified organization applies to patients and how other major disorders fit into it. OBJECTIVE To analyze comorbidity among a wide range of Axis I disorders and personality disorders (PDs) in the general outpatient population. DESIGN Clinical cohort study. SETTING A general outpatient practice, the Rhode Island Methods to Improve Diagnostic Assessment and Services (MIDAS) project. PARTICIPANTS Outpatients (N = 2900) seeking psychiatric treatment. MAIN OUTCOME MEASURES The Structured Clinical Interview for DSM-IV and the Structured Interview for DSM-IV Personality. RESULTS We tested several alternative groupings of the 25 target disorders. The DSM-IV organization fit the data poorly. The best-fitting model consisted of 5 factors: internalizing (anxiety and eating disorders, major depressive episode, and cluster C, borderline, and paranoid PDs), externalizing (substance use disorders and antisocial PD), thought disorder (psychosis, mania, and cluster A PDs), somatoform (somatoform disorders), and antagonism (cluster B and paranoid PDs). CONCLUSIONS We confirmed the validity of the 3 previously found spectra in an outpatient population. We also found novel somatoform and antagonism dimensions, which this investigation was able to detect because, to our knowledge, this is the first study to include a variety of somatoform and personality disorders. The findings suggest that many PDs can be placed in Axis I with related clinical disorders. They also suggest that unipolar depression may be better placed with anxiety disorders than with bipolar disorders. The emerging quantitative nosology promises to provide a more useful guide to clinicians and researchers.

The Hierarchical Taxonomy of Psychopathology (HiTOP) : A Dimensional Alternative to Traditional Nosologies

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.

Neuroticism and common mental disorders: meaning and utility of a complex relationship.

Neuroticisms 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 neuroticisms 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.

Cannabis use and the course of schizophrenia: 10-year follow-up after first hospitalization

OBJECTIVE The authors examined the relationship between cannabis use and the course of illness in schizophrenia over 10 years of follow-up after first psychiatric hospitalization. METHOD The authors assessed 229 patients with a schizophrenia spectrum disorder five times: during the first admission and 6 months, 2 years, 4 years, and 10 years later. Ratings of cannabis use and psychiatric symptoms (psychotic, negative, disorganized, and depressive) were made at each assessment. RESULTS The lifetime rate of cannabis use was 66.2%, and survival analysis revealed that lifetime use was associated with an earlier onset of psychosis. The rates of current use ranged from 10% to 18% across assessments. Cannabis status was moderately stable, with tetrachoric correlation coefficients between waves ranging from 0.48 to 0.78. Mixed-effects logistic regression revealed that changes in cannabis use were associated with changes in psychotic symptoms over time even after gender, age, socioeconomic status, other drug use, antipsychotic medication use, and other symptoms were controlled for. Structural equation modeling indicated that the association with psychotic symptoms was bidirectional. CONCLUSIONS Cannabis use is associated with an adverse course of psychotic symptoms in schizophrenia, and vice versa, even after taking into account other clinical, substance use, and demographic variables.

DSM―IV personality disorders in the WHO World Mental Health Surveys

BACKGROUND Little is known about the cross-national population prevalence or correlates of personality disorders. AIMS To estimate prevalence and correlates of DSM-IV personality disorder clusters in the World Health Organization World Mental Health (WMH) Surveys. METHOD International Personality Disorder Examination (IPDE) screening questions in 13 countries (n = 21 162) were calibrated to masked IPDE clinical diagnoses. Prevalence and correlates were estimated using multiple imputation. RESULTS Prevalence estimates are 6.1% (s.e. = 0.3) for any personality disorder and 3.6% (s.e. = 0.3), 1.5% (s.e. = 0.1) and 2.7% (s.e. = 0.2) for Clusters A, B and C respectively. Personality disorders are significantly elevated among males, the previously married (Cluster C), unemployed (Cluster C), the young (Clusters A and B) and the poorly educated. Personality disorders are highly comorbid with Axis I disorders. Impairments associated with personality disorders are only partially explained by comorbidity. CONCLUSIONS Personality disorders are relatively common disorders that often co-occur with Axis I disorders and are associated with significant role impairments beyond those due to comorbidity.

Diagnostic shifts during the decade following first admission for psychosis.

OBJECTIVE Diagnostic shifts have been prospectively examined in the short term, but the long-term stability of diagnoses has rarely been evaluated. The authors examined diagnostic shifts over a 10-year follow-up period. METHOD A cohort of 470 first-admission patients with psychotic disorders was systematically assessed at baseline and at 6-month, 2-year, and 10-year follow-ups. Longitudinal best-estimate consensus diagnoses were formulated after each assessment. RESULTS At baseline, the diagnostic distribution was 29.6% schizophrenia spectrum disorders, 21.1% bipolar disorder with psychotic features, 17.0% major depression with psychotic features, 2.4% substance-induced psychosis, and 27.9% other psychoses. At year 10, the distribution changed to 49.8%, 24.0%, 11.1%, 7.0%, and 8.1%, respectively. Overall, diagnoses were changed for 50.7% of study participants at some point during the study. Most participants who were initially diagnosed with schizophrenia or bipolar disorder retained the diagnosis at year 10 (89.2% and 77.8%, respectively). However, 32.0% of participants (N=98) originally given a non-schizophrenia diagnosis had gradually shifted to a schizophrenia diagnosis by year 10. The second largest shift was to bipolar disorder (10.7% of those not given this diagnosis at baseline). Changes in the clinical picture explained many diagnostic shifts. In particular, poorer functioning and greater negative and psychotic symptom ratings predicted a subsequent shift to schizophrenia. Better functioning and lower negative and depressive symptom ratings predicted the shift to bipolar disorder. CONCLUSIONS First-admission patients with psychotic disorders run the risk of being misclassified at early stages in the illness course, including more than 2 years after first hospitalization. Diagnosis should be reassessed at all follow-up points.

Blunted neural response to rewards prospectively predicts depression in adolescent girls.

The prevalence of depression increases substantially during adolescence. Several predictors of major depressive disorder have been established, but their predictive power is limited. In the current study, the feedback negativity (FN), an event-related potential component elicited by feedback indicating monetary gain versus loss, was recorded in 68 never-depressed adolescent girls. Over the following 2 years, 24% of participants developed a major depressive episode (MDE); illness onset was predicted by blunted FN at initial evaluation. Lower FN amplitude predicted more depressive symptoms during the follow-up period, even after controlling for neuroticism and depressive symptoms at baseline. This is the first prospective study to demonstrate a link between a neural measure of reward sensitivity and the first onset of an MDE. The current results suggest that low reward sensitivity may be an important factor in the development of depression.

Hopelessness as a Predictor of Attempted Suicide among First Admission Patients with Psychosis: A 10-Year Cohort Study.

Little is known about the longitudinal relationship of hopelessness to attempted suicide in psychotic disorders. This study addresses this gap by assessing hopelessness and attempted suicide at multiple time-points over 10 years in a first-admission cohort with psychosis (n = 414). Approximately one in five participants attempted suicide during the 10-year follow-up, and those who attempted suicide scored significantly higher at baseline on the Beck Hopelessness Scale. In general, a given assessment of hopelessness (i.e., baseline, 6, 24, and 48 months) reliably predicted attempted suicide up to 4 to 6 years later, but not beyond. Structural equation modeling indicated that hopelessness prospectively predicted attempted suicide even when controlling for previous attempts. Notably, a cut-point of 3 or greater on the Beck Hopelessness Scale yielded sensitivity and specificity values similar to those found in nonpsychotic populations using a cut-point of 9. Results suggest that hopelessness in individuals with psychotic disorders confers information about suicide risk above and beyond history of attempted suicide. Moreover, in comparison with nonpsychotic populations, even relatively modest levels of hopelessness appear to confer risk for suicide in psychotic disorders.

Development and Validation of New Anxiety and Bipolar Symptom Scales for an Expanded Version of the IDAS (the IDAS-II)

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.