Literature Update

Abstract

Introduction: Bipolar disorder patients (BP) with comorbid Substance Use Disorder (SUD) may present clinical features that could compromise adherence and response to pharmacological treatment. The purpose of this study was to examine clinical and psychopathological features of BP with and without comorbid SUD in a real-world setting. Methods: The sample was composed by 131 affective patients. Sixty-five patients were affected by Bipolar Disorder I (BP-I, 49.2%), 29 by Bipolar Disorder II (BP-II, 22.3%) and 37 by Cyclothymic Disorder (CtD, 28.5%), according to DSM-IV. Sixty-six patients were diagnosed for a comorbid SUD. All patients have been submitted to psychometric assessment with Hamilton Depression Rating Scale (HDRS), Hamilton Anxiety Rating Scale (HARS), Young Mania Rating Scale (YMRS), Global Assessment Scale (GAS), Social Adjustment Self-reported Scale (SASS), Quality of Life Scale (QoL), at baseline and repeated follow-up periods (1, 3, 6, 12 months). Results: BP comorbid for SUD were more likely diagnosed as BP-II and CtD and were less likely to present a moderate-severe manic symptomatology. Furthermore, personality disorders were more frequent in SUD patients than in non-comorbid BP. BP with SUD were not different for primary outcome measure (HDRS, HARS, YMRS, GAS) from non-comorbid BP; however, BP with SUD were significantly more impaired in social functioning (SASS) at any stage of the follow-up and poor functioning increased the risk of relapse in substance use during treatment. Finally, SUD comorbidity did not represent a risk factor for treatment drop-out, while in our sample young age, low treatment dosage and BP-I diagnosis were significantly associated with drop-out. Discussion: The primary finding of this work is that BP with comorbid SUD are significantly more compromised in social functioning. Second, these patients were less likely to be diagnosed for BP-I and to present a severe manic symptomatology. Finally, we found that the diagnosis of SUD, but young age, low treatment dosage and BP-I diagnosis to be risk factors for treatment drop-out. Physicians should be alert to these differences in their clinical practice. © 2008 Elsevier B.V. All rights reserved.

Abstract

Background: Bipolar disorder type II (BDII) has been considered since its distinction from bipolar disorder type I (BDI) as a milder form, on the basis of cross-sectional symptoms intensity. Longitudinal data, on the contrary, do suggest that it is at least as severe as BDI, if not even more chronic and impairing. Few studies investigated differences in Axis II comorbidity in bipolar disorder patients according to bipolar subtypes, and none examined patients during prolonged euthymia. The aim of the study was to determine comorbidity rates for personality disorders in euthymic bipolar subjects, comparing bipolar type I and II disorders (BDI and BDII). Methods: 186 DSM-IV (SCID-I) bipolar disorder subjects were enrolled; all patients were euthymic for at least two months, as confirmed by a HAM-D < 8 and a YMRS < 6. Axis II comorbidity was evaluated through SCID-II. Differences in Axis II comorbidity rates were examined with the Pearson's Chi-square test. Results: Of the subjects included, 71 had BDI and 115 BDII. At least a personality disorder was present in 42.5% of all bipolars, 43.7% of BDI and 41.7% of BDII. No differences were detected between the two subgroups for any single personality disorder. Limitations: We relied only on the patients' reports in assessing personality disorders; the sample was made of subjects referred to a tertiary centre who were able to maintain euthymia. Conclusions: Our study confirms the high comorbidity rates for personality disorders in bipolar subjects and provides evidence that BDII, with regard to Axis II comorbidity, is as severe as BDI.

Abstract

Background: Bipolar disorder type II (BDII) has been considered since its distinction from bipolar disorder type I (BDI) as a milder form, on the basis of cross-sectional symptoms intensity. Longitudinal data, on the contrary, do suggest that it is at least as severe as BDI, if not even more chronic and impairing. Few studies investigated differences in Axis II comorbidity in bipolar disorder patients according to bipolar subtypes, and none examined patients during prolonged euthymia. The aim of the study was to determine comorbidity rates for personality disorders in euthymic bipolar subjects, comparing bipolar type I and II disorders (BDI and BDII). Methods: 186 DSM-IV (SCID-I) bipolar disorder subjects were enrolled; all patients were euthymic for at least two months, as confirmed by a HAM-D < 8 and a YMRS < 6. Axis II comorbidity was evaluated through SCID-II. Differences in Axis II comorbidity rates were examined with the Pearson's Chi-square test. Results: Of the subjects included, 71 had BDI and 115 BDII. At least a personality disorder was present in 42.5% of all bipolars, 43.7% of BDI and 41.7% of BDII. No differences were detected between the two subgroups for any single personality disorder. Limitations: We relied only on the patients' reports in assessing personality disorders; the sample was made of subjects referred to a tertiary centre who were able to maintain euthymia. Conclusions: Our study confirms the high comorbidity rates for personality disorders in bipolar subjects and provides evidence that BDII, with regard to Axis II comorbidity, is as severe as BDI.

Abstract

We investigated methodological and sample-based characteristics that might contribute to discrepancies in the structure of the 22-scale Personality Assessment Inventory (PAI; Morey, 1991, 2007). In Study 1, we used parallel analysis, Velicer's minimum average partial procedure, and random variables to determine the appropriate number of principal components to retain in a clinical sample (N = 227). We retained 3 oblique dimensions that broadly emphasized (a) general distress, (b) elevated mood and dominance, and (c) substance abuse and psychopathy. In Study 2, we applied the same uniform criteria and procedures to 5 previously published samples and conducted orthogonal vector matrix comparisons to determine how congruent 3- and 4-dimensional structures were across samples. Results suggested the PAI has 3 dimensions that are highly congruent across samples. Using Morey's normative sample, we provide the formulas needed to compute T scores for each component so they can be used in clinical work with patients. We discuss clinical implications and directions for future PAI research.

Abstract

The aim of the study was to evaluate the relative contributions of cannabis use, alcohol use, psychopathic and borderline personality traits, and depressive symptoms in the prediction of delinquent behaviors. Participants were 312 high-school students who completed self-report questionnaires. Hierarchical multiple regression analyses were conducted to investigate the contribution of cannabis use and potential confounding variables to delinquent behaviors in the total sample and in cannabis users. Cannabis use was no more a significant independent predictor of delinquent behaviors after adjustment for alcohol use and psychopathological variables. However, among users, frequency of use remained a significant predictor of delinquency after adjustment for those confounders.