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Heterogeneity of emotional experience in schizophrenia: Trait affect profiles predict clinical presentation and functional outcome.
Journal of Psychopathology and Clinical Science ( IF 4.6 ) Pub Date : 2020-10-01 , DOI: 10.1037/abn0000554
Henry R Cowan 1 , Vijay A Mittal 1 , Daniel N Allen 1 , James M Gold 2 , Gregory P Strauss 1
Affiliation  

The current study examined whether subgroups of individuals with schizophrenia could be identified based on their profiles of trait positive and negative emotional experience, and whether those subgroups differed in their symptom presentation and functional outcome. Participants included 192 outpatients diagnosed with schizophrenia or schizoaffective disorder (SZ) and 149 demographically matched healthy controls who completed the trait version of the Positive and Negative Affect Scale, as well as symptom and functional outcome assessments. Cluster analysis determined whether patients could be separated into meaningful subgroups based on their trait emotional experience profiles, and discriminant function analysis determined whether these groups were valid and adequately separated. Forty-two percent of the patients fell into an affectively normal cluster, whereas 28% and 30% fell into low positive affect (PA) and high negative affect (NA) clusters, respectively. These subgroups differed significantly on positive symptoms, negative symptoms, Diagnostic and Statistical Manual of Mental Disorders diagnoses, and functional outcomes. Trait emotional experience is heterogeneous in outpatients with psychotic disorders, and meaningful subgroups of patients with different profiles of PA and NA can be identified. These subgroups show meaningful differences in clinical presentation, which may necessitate different treatment approaches. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

中文翻译:

精神分裂症情绪体验的异质性:特质影响概况预测临床表现和功能结果。

目前的研究检查了精神分裂症患者的亚组是否可以根据他们的正面和负面情绪体验特征来识别,以及这些亚组的症状表现和功能结果是否不同。参与者包括 192 名被诊断患有精神分裂症或分裂情感障碍 (SZ) 的门诊患者和 149 名人口匹配的健康对照,他们完成了正面和负面影响量表的特征版本,以及症状和功能结果评估。聚类分析确定是否可以根据患者的特质情绪体验档案将患者分成有意义的亚组,判别函数分析确定这些组是否有效并充分分离。42% 的患者属于情感正常集群,而 28% 和 30% 的患者分别属于低积极情绪 (PA) 和高消极情绪 (NA) 集群。这些亚组在阳性症状、阴性症状、精神疾病诊断和统计手册诊断以及功能结果方面存在显着差异。精神病门诊患者的情绪体验特征是异质的,可以识别出具有不同 PA 和 NA 特征的有意义的患者亚组。这些亚组在临床表现上表现出有意义的差异,这可能需要不同的治疗方法。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。这些亚组在阳性症状、阴性症状、精神疾病诊断和统计手册诊断以及功能结果方面存在显着差异。精神病门诊患者的情绪体验特征是异质的,可以识别出具有不同 PA 和 NA 特征的有意义的患者亚组。这些亚组在临床表现上表现出有意义的差异,这可能需要不同的治疗方法。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。这些亚组在阳性症状、阴性症状、精神疾病诊断和统计手册诊断以及功能结果方面存在显着差异。精神病门诊患者的情绪体验特征是异质的,可以识别出具有不同 PA 和 NA 特征的有意义的患者亚组。这些亚组在临床表现上表现出有意义的差异,这可能需要不同的治疗方法。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。这些亚组在临床表现上表现出有意义的差异,这可能需要不同的治疗方法。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。这些亚组在临床表现上表现出有意义的差异,这可能需要不同的治疗方法。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。
更新日期:2020-10-01
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