Mark Zimmerman

Axis I diagnostic comorbidity and borderline personality disorder

Borderline personality disorder (PD) has been the most studied PD. Research has examined the relationship between borderline PD and most axis I diagnostic classes such as eating disorders, mood disorders, and substance use disorders. However, there is little information regarding the relationship of borderline PD and overall comorbidity with all classes of axis I disorders assessed simultaneously. In the present study, 409 patients were evaluated with semistructured diagnostic interviews for axis I and axis II disorders. Patients with a diagnosis of borderline PD versus those who did not receive the diagnosis were assigned significantly more current axis I diagnoses (3.4 v 2.0). Borderline PD patients were twice as likely to receive a diagnosis of three or more current axis I disorders (69.5% v 31.1%) and nearly four times as likely to have a diagnosis of four or more disorders 147.5% v 13.7%). In comparison to nonborderline PD patients, borderline PD patients more frequently received a diagnosis of current major depressive disorder (MDD), bipolar I and II disorder, panic disorder with agoraphobia, social and specific phobia, posttraumatic stress disorder (PTSD), obsessive-compulsive disorder (OCD), eating disorder NOS, and any somatoform disorder. Similar results were observed for lifetime diagnoses. Overall, borderline PD patients were more likely to have multiple axis I disorders than nonborderline PD patients, and the differences between the two groups were present across mood, anxiety, substance use, eating, and somatoform disorder categories. These findings highlight the importance of performing thorough evaluations of axis I pathology in patients with borderline PD in order not to overlook syndromes that are potentially treatment-responsive.

Psychiatric diagnosis in clinical practice: is comorbidity being missed?

The recognition of comorbidity has important clinical significance. Comorbidity predicts a poorer outcome for patients with depressive and anxiety disorders, and the presence of multiple psychiatric disorders is associated with greater psychosocial impairment. In routine clinical settings, an unstructured interview is typically used to assess patients. However, unstructured interviews may result in missed diagnoses, with potential negative clinical consequences. The goal of the present study was to examine whether diagnostic comorbidity is less frequently identified during a routine clinical evaluation versus a semistructured diagnostic interview. Axis I diagnoses derived from structured and unstructured clinical interviews were compared in two groups of psychiatric outpatients in the same practice setting. Five hundred individuals presenting for an intake appointment to a general adult psychiatric practice underwent a routine unstructured clinical interview. Subsequent to completion of the first study, the method of conducting diagnostic evaluations was changed and 500 individuals were interviewed with the Structural Clinical Interview for DSM-IV Axis I Disorders (SCID). The two groups had similar demographic characteristics and scored similarly on symptom questionnaires. Individuals interviewed with the SCID were assigned significantly more axis I diagnoses than individuals assessed with an unstructured interview. More than one third of the patients interviewed with the SCID were diagnosed with three or more disorders, in contrast to fewer than 10% of the patients assessed with an unstructured interview. Fifteen disorders were more frequently diagnosed in the SCID sample, and these differences occurred across mood, anxiety, eating, somatoform, and impulse-control disorder categories. The results suggest that in routine clinical practice, clinicians underrecognize diagnostic comorbidity. Anxiety, somatoform, and not otherwise specified (NOS) disorders were the most frequently underdetected disorders. The implications of underdiagnosis for the treatment outcome are discussed.

The Implications of DSM-III Personality Disorders for Patients with Major Depression

We studied 78 inpatients with DSM-III major depression. Forty-one (53%) had a concurrent personality disorder (PD) according to a detailed structured interview for DSM-III personality disorders. The patients with depression plus PD differed from patients with depression alone on numerous measures. The PD patients had earlier onset; higher HRS scores; poorer social support; more life stressors; more frequent separation and divorce; more frequent nonserious suicide attempts, less frequent dexamethasone nonsuppression; poorer response to antidepressant medication; and higher risk for depression, alcoholism and antisocial personality among first-degree relatives. The PD subgroup shares many attributes with Winokurs subtype of depression spectrum disorder and Akiskals character spectrum disorder. An attempt to identify a subgroup of personality disorders which might be an atypical affective disorder was inconclusive. However, patients in DSM-III cluster III were similar to the patients with no-PD on the dexamethasone suppression test, response to treatment, and familial risk for depression and antisocial personality.

Severity classification on the Hamilton depression rating scale

BACKGROUND Symptom severity as a moderator of treatment response has been the subject of debate over the past 20 years. Each of the meta- and mega-analyses examining the treatment significance of depression severity used the Hamilton Depression Rating Scale (HAMD), wholly, or in part, to define severity, though the cutoff used to define severe depression varied. There is limited empirical research establishing cutoff scores for bands of severity on the HAMD. The goal of the study is to empirically establish cutoff scores on the HAMD in their allocation of patients to severity groups. METHODS Six hundred twenty-seven outpatients with current major depressive disorder were evaluated with a semi-structured diagnostic interview. Scores on the 17-item HAMD were derived from ratings according to the conversion method described by Endicott et al. (1981). The patients were also rated on the Clinical Global Index of Severity (CGI). Receiver operating curves were computed to identify the cutoff that optimally discriminated between patients with mild vs. moderate and moderate vs. severe depression. RESULTS HAMD scores were significantly lower in patients with mild depression than patients with moderate depression, and patients with moderate depression scored significantly lower than patients with severe depression. The cutoff score on the HAMD that maximized the sum of sensitivity and specificity was 17 for the comparison of mild vs. moderate depression and 24 for the comparison of moderate vs. severe depression. LIMITATIONS The present study was conducted in a single outpatient practice in which the majority of patients were white, female, and had health insurance. Although the study was limited to a single site, a strength of the recruitment procedure was that the sample was not selected for participation in a treatment study, and exclusion and inclusion criteria did not reduce the representativeness of the patient groups. The analyses were based on HAMD scores extracted from ratings on the SADS. However, we used Endicott et al.s (1981) empirically established formula for deriving a HAMD score from SADS ratings, and our results concurred with other small studies of the mean and median HAMD scores in severity groups. CONCLUSIONS Based on this large study of psychiatric outpatients with major depressive disorder we recommend the following severity ranges for the HAMD: no depression (0-7); mild depression (8-16); moderate depression (17-23); and severe depression (≥24).

Clinical correlates of self-mutilation in a sample of general psychiatric patients.

The aims of this study were to examine whether certain axis I disorders characterized by impulsive aggression were associated with self-mutilative behavior and to evaluate the clinical correlates of self-mutilation in a sample of general psychiatric outpatients. Two hundred fifty-six outpatients were administered diagnostic interviews for axis I and axis II disorders. In addition, questionnaires that measured self-mutilative acts within the last 3 months, dissociation, and childhood abuse were completed. This study found that axis I disorders of substance abuse, posttraumatic stress disorder, and intermittent explosive disorder were significantly related to self-mutilative behavior, independent of borderline personality disorder and antisocial personality disorder. Also, a higher level of dissociation was related to self-mutilation, controlling for borderline personality disorder and childhood abuse. Outpatients with certain axis I disorders and those who dissociate may represent a sizable group of patients who are at risk for self-mutilative behavior.

Rapid Onset of Pathological Gambling in Machine Gamblers

A particularly rapid onset of pathological gambling (PG-onset) through the use of gambling machines has been widely alluded to, but this is the first study to empirically examine the phenomenon. This study compared the latency of PG-onset in those who gambled primarily on machines, compared to those who gambled primarily on more “traditional” forms of gambling at PG-onset. Subjects were 44 adult pathological gamblers (PGs) seeking outpatient treatment in Rhode Island (17 females; mean age = 46.9). Subjects completed questionnaires and a diagnostic interview including a complete history of gambling activities and the course of PG. The “latency” of PG-onset was defined as the time (in years) elapsed between the age of regular involvement in the primary form of gambling and the age at which DSM-IV criteria were first met. “Machine” PGs (n = 25) had a significantly shorter latency of onset than did “traditional” PGs (1.08 years vs. 3.58 years). Females and machine PGs had a significantly older age of onset, but gender was not associated with latency of PG-onset. Lifetime comorbidity of either substance use disorders (SUDS) or depressive disorders (DDS) was also not associated with the latency of PG-onset. The results of the current study suggest that intrapersonal variables such as gender and comorbid disorders do not generally affect the speed with which people develop PG. Rather, the social, environmental, and stimulus features of mechanized gambling are implicated. Prospective longitudinal studies on the onset and course of PG are needed, as well as more basic research on the features of machine gambling that may contribute to rapid onset.

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.

DSM-III personality disorders: Diagnostic overlap and internal consistency of individual DSM-III criteria

Abstract We rated the presence or absence of every DSM-III personality criteria in a cohort of 131 non-psychotic subjects. Ratings were based on the Structured Interview for DSM-III Personality Disorders (SIDP) which was administered to each patient and a knowledgable informant. Diagnositc overlap of the personality disorders (PD) was examined. Sensitivity, specificity, predictive value—positive and negative, and interrater reliability was calculated for each criteria item of each personality disorder. Problems in reliability of DSM-III personality disorders can be traced to specific criteria within those disorders that are associated with low reliability and/or low predictive value positive when compared to the other criteria used to define the personality disorder. Improvements are suggested. We were unable to demonstrate a significantly greater enhancement of reliability among criteria structures using a polythetic classification over those using monothetic classification despite a trend favoring the former. This study agrees with others that find a great deal of overlap between borderline PD and histrionic PD as defined in DSM-III. Passive-aggressive PD is very rare in the absence of some other PD. Paranoid and schizoid personality disorders were also rare though this may reflect the fact that individuals with these disorders rarely seek treatment.

The inventory to diagnose depression lifetime version

ABSTRACT— The lifetime version of the Inventory to Diagnose Depression (IDDL) is a 22‐item self‐report scale designed to diagnose a lifetime history of DSM‐III major depressive disorder (MDD). One hundred and sixty‐four first‐degree relatives of healthy control probands completed the IDDL and were interviewed with the Diagnostic Interview Schedule (DIS). The IDDL had good internal consistency (Cronbachs alpha = 0.92), split‐half reliability (Spearman‐Brown coefficient = 0.90), and all of the item total correlations were significant. The lifetime prevalence of MDD was nonsignificantly higher in the IDDL than the DIS (14.8% vs. 11.7%). Using the DIS as the criterion measure, the sensitivity of the IDDL was 74% and its specificity was 93% and the chance corrected agreement between the two measures was kappa = 0.60.

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.