scholarly journals Personality disorders and normal personality dimensions in obsessive-compulsive disorder

2000 ◽  
Vol 177 (5) ◽  
pp. 457-462 ◽  
Author(s):  
Jack Samuels ◽  
Gerald Nestadt ◽  
O. Joseph Bienvenu ◽  
Paul T. Costa ◽  
Mark A. Riddle ◽  
...  

BackgroundLittle is known about personality disorders and normal personality dimensions in relatives of patients with obsessive-compulsive disorder (OCD).AimsTo determine whether specific personality characteristics are part of a familial spectrum of OCD.MethodClinicians evaluated personality disorders in 72 OCD case and 72 control probands and 198 case and 207 control first-degree relatives. The self-completed Revised NEO Personality Inventory was used for assessment of normal personality dimensions. The prevalence of personality disorders and scores on normal personality dimensions were compared between case and control probands and between case and control relatives.ResultsCase probands and case relatives had a high prevalence of obsessive-compulsive personality disorder (OCPD) and high neuroticism scores. Neuroticism was associated with OCPD in case but not control relatives.ConclusionsNeuroticism and OCPD may share a common familial aetiology with OCD.

Author(s):  
Michael G. Wheaton ◽  
Anthony Pinto

This chapter reviews the literature on personality pathology in obsessive-compulsive disorder (OCD). It begins by comparing and contrasting OCD with obsessive-compulsive personality disorder (OCPD). These two conditions have a longstanding yet frequently misunderstood relationship. Though they share some overlapping features, recent research has established OCD and OCPD as distinct conditions. Even so, OCD and OCPD frequently cooccur. The chapter reviews the literature on comorbidity and the impact of OCPD on the clinical course and treatment of OCD, including evidence that OCPD may complicate OCD treatment. It also describes other personality disorders observed in OCD. Finally, it describes recent advances in the conceptualization of personality disorders, including dimensional approaches, and concludes with directions for future research.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Josep Pena-Garijo ◽  
Silvia Edo Villamón ◽  
Amanda Meliá de Alba ◽  
M. Ángeles Ruipérez

Objective. The purpose of this paper is to provide evidence for the relationship between personality disorders (PDs), obsessive compulsive disorder (OCD), and other anxiety disorders different from OCD (non-OCD) symptomatology.Method. The sample consisted of a group of 122 individuals divided into three groups (41 OCD; 40 non-OCD, and 41 controls) matched by sex, age, and educational level. All the individuals answered the IPDE questionnaire and were evaluated by means of the SCID-I and SCID-II interviews.Results. Patients with OCD and non-OCD present a higher presence of PD. There was an increase in cluster C diagnoses in both groups, with no statistically significant differences between them.Conclusions. Presenting anxiety disorder seems to cause a specific vulnerability for PD. Most of the PDs that were presented belonged to cluster C. Obsessive Compulsive Personality Disorder (OCPD) is the most common among OCD. However, it does not occur more frequently among OCD patients than among other anxious patients, which does not confirm the continuum between obsessive personality and OCD. Implications for categorical and dimensional diagnoses are discussed.


Author(s):  
Pinar Ozel ◽  
Ali Olamat ◽  
Aydin Akan

This research presents a new method for detecting obsessive–compulsive disorder (OCD) based on time–frequency analysis of multi-channel electroencephalogram (EEG) signals using the multi-variate synchrosqueezing transform (MSST). With the evolution of multi-channel sensor implementations, the employment of multi-channel techniques for the extraction of features arising from multi-channel dependency and mono-channel characteristics has become common. MSST has recently been proposed as a method for modeling the combined oscillatory mechanisms of multi-channel signals. It makes use of the concepts of instantaneous frequency (IF) and bandwidth. Electrophysiological data, like other nonstationary signals, necessitates both joint time–frequency analysis and independent time and frequency domain studies. The usefulness and effectiveness of a multi-variate, wavelet-based synchrosqueezing algorithm paired with a band extraction method are tested using electroencephalography data obtained from OCD patients and control groups in this research. The proposed methodology yields substantial results when analyzing differences between patient and control groups.


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