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围产期女性队列中差异性抑郁症状模式的检测:采用稳健统计方法的探索性因素分析

Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach.

作者信息

Nieser Kenneth J, Stowe Zachary N, Newport D Jeffrey, Coker Jessica L, Cochran Amy L

机构信息

Department of Population Health Sciences, University of Wisconsin-Madison, United States.

Department of Psychiatry, University of Wisconsin-Madison, United States.

出版信息

EClinicalMedicine. 2023 Feb 1;57:101830. doi: 10.1016/j.eclinm.2023.101830. eCollection 2023 Mar.

Abstract

BACKGROUND

Postpartum depression can take many forms. Different symptom patterns could have divergent implications for how we screen, diagnose, and treat postpartum depression. We sought to utilise a recently developed robust estimation algorithm to automatically identify differential patterns in depressive symptoms and subsequently characterise the individuals who exhibit different patterns.

METHODS

Depressive symptom data (N = 548) were collected from women with neuropsychiatric illnesses at two U.S. urban sites participating in a longitudinal observational study of stress across the perinatal period. Data were collected from Emory University between 1994 and 2012 and from the University of Arkansas for Medical Sciences between 2012 and 2017. We conducted an exploratory factor analysis of Beck Depression Inventory (BDI) items using a robust expectation-maximization algorithm, rather than a conventional expectation-maximization algorithm. This recently developed method enabled automatic detection of differential symptom patterns. We described differences in symptom patterns and conducted unadjusted and adjusted analyses of associations of symptom patterns with demographics and psychiatric histories.

FINDINGS

53 (9.7%) participants were identified by the algorithm as having a different pattern of reported symptoms compared to other participants. This group had more severe symptoms across all items-especially items related to thoughts of self-harm and self-judgement-and differed in how their symptoms related to underlying psychological constructs. History of social anxiety disorder (OR: 4.0; 95% CI [1.9, 8.1]) and history of childhood trauma (for each 5-point increase, OR: 1.2; 95% CI [1.1, 1.3]) were significantly associated with this differential pattern after adjustment for other covariates.

INTERPRETATION

Social anxiety disorder and childhood trauma are associated with differential patterns of severe postpartum depressive symptoms, which might warrant tailored strategies for screening, diagnosis, and treatment to address these comorbid conditions.

FUNDING

There are no funding sources to declare.

摘要

背景

产后抑郁症有多种形式。不同的症状模式对于我们如何筛查、诊断和治疗产后抑郁症可能有不同的影响。我们试图利用一种最近开发的稳健估计算法来自动识别抑郁症状的差异模式,并随后对表现出不同模式的个体进行特征描述。

方法

从参与围产期压力纵向观察研究的美国两个城市地点的患有神经精神疾病的女性中收集抑郁症状数据(N = 548)。数据于1994年至2012年从埃默里大学收集,2012年至2017年从阿肯色大学医学科学分校收集。我们使用稳健期望最大化算法而非传统期望最大化算法对贝克抑郁量表(BDI)项目进行探索性因素分析。这种最近开发的方法能够自动检测差异症状模式。我们描述了症状模式的差异,并对症状模式与人口统计学和精神病史的关联进行了未调整和调整分析。

结果

该算法识别出53名(9.7%)参与者报告的症状模式与其他参与者不同。该组在所有项目上症状更严重,尤其是与自我伤害和自我评判想法相关的项目,并且其症状与潜在心理结构的关联方式也有所不同。在对其他协变量进行调整后,社交焦虑症病史(比值比:4.0;95%置信区间[1.9, 8.1])和童年创伤史(每增加5分,比值比:1.2;95%置信区间[1.1, 1.3])与这种差异模式显著相关。

解读

社交焦虑症和童年创伤与严重产后抑郁症状的差异模式相关,这可能需要针对这些共病情况制定量身定制的筛查诊断和治疗策略。

资金来源

无资金来源需要申报。

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