ArticleNigerian medical journal : journal of the Nigeria Medical Association
Associatqion of Depression with Phenomenology and Insight Among Patients with Obsessive-Compulsive Disorder.
Article in Nigerian medical journal : journal of the Nigeria Medical Association. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The phenomenology of obsessive-compulsive disorder (OCD) is influenced by culture; its understanding can enhance case identification. Insight levels and depressive symptoms may vary with OCD phenomenology, affecting management and outcomes. This study assessed the association of depression with phenomenology and insight among patients with OCD and predictors of comorbid depression severity. Methodology: This observational study enrolled 146 participants after receiving ethical approval and consent. Obsession and compulsion were assessed using the Yale-Brown Obsessive Compulsive Scale (YBOCS). Insight and depression were assessed with the Over Valued Ideas Scale (OVIS) and the Hamilton Depression Rating Scale (HDRS). Linear regression was employed to identify predictors of the severity of depression. Result: The sample consisted of 68.5% males, with a mean age of 31.5 years. The mean duration of OCD was 63 months. Contamination was the most common obsession; while washing or cleaning was the most frequent compulsion. Aggressive, sexual, and religious obsessions were more prevalent in males. Notably, 73.2% of patients experienced depression. Those with depression exhibited longer and more severe OCD. The severity of depression had a significant positive correlation with the duration of OCD, the YBOCS score, and the OVIS score. Female gender and higher OVIS scores were significant predictors of the severity of depression, with gender being the most important predictor. Conclusion: Depression is quite common among patients with OCD, particularly those experiencing longer and more severe illnesses. Being female and having lower insight significantly predict the severity of depression.
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