4 research outputs found
Classification of comorbidity in obsessiveācompulsive disorder: A latent class analysis
Objective: Patients with OCD differ markedly from one another in both number and kind of comorbid disorders. In this study, we set out to identify and characterize homogeneous subgroups of OCD patients based on their comorbidity profile. Methods: In a cohort of 419 adult subjects with OCD, the lifetime presence of fifteen comorbid disorders was assessed. Latent class analysis was used to identify comorbidity-based subgroups. Groups were compared with regard to core clinical characteristics: familiality, childhood trauma, age at onset, illness severity, OCD symptom dimensions, personality characteristics, and course of illness. Results: The study sample could be divided in a large group (nĀ =Ā 311) with a low amount of comorbidity that could be further subdivided into two subgroups: OCD simplex (nĀ =Ā 147) and OCD with lifetime major depressive disorder (nĀ =Ā 186), and a group (nĀ =Ā 108) with a high amount of comorbidity that could be further subdivided into a general anxiety-related subgroup (nĀ =Ā 49), an autism/social phobia-related subgroup (nĀ =Ā 27), and a psychosis/bipolar-related subgroup (nĀ =Ā 10). Membership of the high-comorbid subgroup was associated with higher scores on childhood trauma, illness severity, and the aggression/checking symptom dimension and lower scores on several personality characteristics. Conclusion: Grouping OCD patients based on their comorbidity profile might provide more homogeneous, and therefore, more suitable categories for future studies aimed at unraveling the etiological mechanisms underlying this debilitating disorder
Classification of comorbidity in obsessiveācompulsive disorder:A latent class analysis
Objective: Patients with OCD differ markedly from one another in both number and kind of comorbid disorders. In this study, we set out to identify and characterize homogeneous subgroups of OCD patients based on their comorbidity profile. Methods: In a cohort of 419 adult subjects with OCD, the lifetime presence of fifteen comorbid disorders was assessed. Latent class analysis was used to identify comorbidity-based subgroups. Groups were compared with regard to core clinical characteristics: familiality, childhood trauma, age at onset, illness severity, OCD symptom dimensions, personality characteristics, and course of illness. Results: The study sample could be divided in a large group (nĀ =Ā 311) with a low amount of comorbidity that could be further subdivided into two subgroups: OCD simplex (nĀ =Ā 147) and OCD with lifetime major depressive disorder (nĀ =Ā 186), and a group (nĀ =Ā 108) with a high amount of comorbidity that could be further subdivided into a general anxiety-related subgroup (nĀ =Ā 49), an autism/social phobia-related subgroup (nĀ =Ā 27), and a psychosis/bipolar-related subgroup (nĀ =Ā 10). Membership of the high-comorbid subgroup was associated with higher scores on childhood trauma, illness severity, and the aggression/checking symptom dimension and lower scores on several personality characteristics. Conclusion: Grouping OCD patients based on their comorbidity profile might provide more homogeneous, and therefore, more suitable categories for future studies aimed at unraveling the etiological mechanisms underlying this debilitating disorder
Inference-Based Approach versus Cognitive Behavioral Therapy in the Treatment of Obsessive-Compulsive Disorder with Poor Insight: A 24-Session Randomized Controlled Trial
Classification of comorbidity in obsessiveācompulsive disorder: A latent class analysis
Objective: Patients with OCD differ markedly from one another in both number and kind of comorbid disorders. In this study, we set out to identify and characterize homogeneous subgroups of OCD patients based on their comorbidity profile. Methods: In a cohort of 419 adult subjects with OCD, the lifetime presence of fifteen comorbid disorders was assessed. Latent class analysis was used to identify comorbidity-based subgroups. Groups were compared with regard to core clinical characteristics: familiality, childhood trauma, age at onset, illness severity, OCD symptom dimensions, personality characteristics, and course of illness. Results: The study sample could be divided in a large group (nĀ =Ā 311) with a low amount of comorbidity that could be further subdivided into two subgroups: OCD simplex (nĀ =Ā 147) and OCD with lifetime major depressive disorder (nĀ =Ā 186), and a group (nĀ =Ā 108) with a high amount of comorbidity that could be further subdivided into a general anxiety-related subgroup (nĀ =Ā 49), an autism/social phobia-related subgroup (nĀ =Ā 27), and a psychosis/bipolar-related subgroup (nĀ =Ā 10). Membership of the high-comorbid subgroup was associated with higher scores on childhood trauma, illness severity, and the aggression/checking symptom dimension and lower scores on several personality characteristics. Conclusion: Grouping OCD patients based on their comorbidity profile might provide more homogeneous, and therefore, more suitable categories for future studies aimed at unraveling the etiological mechanisms underlying this debilitating disorder