Cassano G B, Benvenuti A, Miniati M, Calugi S, Mula M, Maggi L, Rucci P, Fagiolini A, Perris F, Frank E
Department of Psychiatry, Neurobiology, Pharmacology and Biotechnology, School of Medicine, University of Pisa, Italy.
J Affect Disord. 2009 May;115(1-2):87-99. doi: 10.1016/j.jad.2008.09.006. Epub 2008 Oct 22.
While previous attempts to elucidate the factor structure of depression tended to agree on a central focus on depressed mood, other factors were not replicated across studies. By examining data from a large number of items covering the range of depressive symptoms, the aim of the present study is to contribute to the identification of the structure of depression on a lifetime perspective.
The study sample consisted of 598 patients with unipolar depression who were administered the Mood Spectrum Self-Report (lifetime version) in Italian (N=415) or English (N=183). In addition to classical exploratory factor analysis using tetrachoric correlation coefficients, an IRT-based factor analysis approach was adopted to analyze the data on 74 items of the instrument that explore cognitive, mood and energy/activity features associated with depression.
Six factors were identified, including 'Depressive Mood', 'Psychomotor Retardation', 'Suicidality', 'Drug/Illness related depression', 'Psychotic Features' and 'Neurovegetative Symptoms', accounting overall for 48.3% of the variance of items.
Clinical information on onset of depression and duration of illness is available only for 350 subjects. Therefore, differences between sites can only be partially accounted using available data.
Our study confirms the central role of depressed mood, psychomotor retardation and suicidality and identifies the factors 'Drug/Illness related depression', 'Psychotic features' and the neurovegetative dysregulation not captured by the instruments most frequently used in previous studies. The identification of patients with specific profiles on multiple factors may be useful in achieving greater precision in neuroimaging studies and in informing treatment selection.
虽然先前阐明抑郁症因子结构的尝试往往在以抑郁情绪为核心焦点上达成一致，但其他因子在各项研究中并未得到重复验证。通过检查涵盖一系列抑郁症状的大量项目的数据，本研究旨在从终生角度为确定抑郁症的结构做出贡献。
研究样本包括598名单相抑郁症患者，他们接受了意大利语（N = 415）或英语（N = 183）的情绪谱自我报告（终生版）。除了使用四分相关系数进行经典探索性因子分析外，还采用了基于项目反应理论的因子分析方法来分析该量表中74个项目的数据，这些项目探索了与抑郁症相关的认知、情绪和能量/活动特征。
确定了六个因子，包括“抑郁情绪”、“精神运动迟缓”、“自杀倾向”、“药物/疾病相关抑郁”、“精神病性特征”和“植物神经症状”，总体上占项目方差的48.3%。
仅350名受试者有抑郁症发作和病程的临床信息。因此，只能用现有数据部分解释各研究点之间的差异。
我们的研究证实了抑郁情绪、精神运动迟缓和自杀倾向的核心作用，并确定了“药物/疾病相关抑郁”、“精神病性特征”以及先前研究中最常用的量表未涵盖的植物神经调节异常等因子。识别具有多种特定特征的患者可能有助于在神经影像学研究中提高精准度，并为治疗选择提供参考。
