德文版精神病学认知障碍筛查量表(SCIP-G)的维度分析

IF 2.3 Q2 PSYCHIATRY
Gabriele Sachs , Gloria Bannick , Eva I.J. Maihofer , Martin Voracek , Scot E. Purdon , Andreas Erfurth
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引用次数: 1

摘要

精神疾病,尤其是精神分裂症,以认知障碍为特征。认知功能障碍的快速检测-也在疾病的过程中-是非常重要的。精神病学认知障碍筛查(SCIP)是为了在临床实践中提供对精神病人的筛查而开发的,有几种语言版本。先前对SCIP维度的心理测量学研究产生了两种不同的模型:一种单因素模型假设SCIP的五个子量表共同负载,而另一种模型认为子量表负载两个因素,即言语记忆和处理速度。我们对德国版SCIP (SCIP- g)进行了验证性因子分析。方法对s323例精神病、双相情感障碍和抑郁症患者进行研究。结果单因素法未得到可接受的模型拟合(χ2检验:χ2 = 109.5, df = 5, p <0.001, χ2/df = 21.9)。以言语学习测验-即时回忆测验、延迟回忆测验和工作记忆测验为第一因子,以言语流畅性测验和精神运动速度测验为第二因子,采用双因子解决方案获得了良好的模型拟合(χ2 = 6.7, df = 3, p = 0.08, χ2/df = 2.2)。结论这些数据表明,对于SCIP,双因素解决方案可以获得良好的模型拟合。本研究首次使用德国SCIP版本进行验证性因子分析,并使用假设检验方法对其维度结构进行检验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dimensionality analysis of the German version of the Screen for Cognitive Impairment in Psychiatry (SCIP-G)

Background

Psychiatric disorders, especially schizophrenia, are characterised by cognitive impairment. The rapid detection of cognitive dysfunction - also in the course of the disease - is of great importance. The Screen for Cognitive Impairment in Psychiatry (SCIP) was developed to provide screening of psychiatric patients in clinical practice and is available in several languages. Prior psychometric investigations into the dimensionality of the SCIP have produced two different models: a one-factor model assumes that the five subscales of the SCIP load together, whereas an alternative model suggests that the subscales load on two factors, namely verbal memory and processing speed. We carried out a confirmatory factor analysis of the German version of the SCIP (SCIP-G).

Methods

323 patients with psychotic, bipolar affective, and depressive disorders were studied.

Results

The one-factor approach did not yield an acceptable model fit (chi-squared test: χ2 = 109.5, df = 5, p < 0.001, χ2/df = 21.9). A two-factor solution, with the subtests Verbal Learning Test-Immediate Recall, Delayed Recall Test of the VLT, and Working Memory Test loading on the first factor, whereas the subtests Verbal Fluency Test and Psychomotor Speed Test loading on the second factor, obtained a good model fit (χ2 = 6.7, df = 3, p = 0.08, χ2/df = 2.2).

Conclusions

These data show that a good model fit can be achieved with a two-factor solution for the SCIP. This study is the first to conduct a confirmatory factor analysis using the German SCIP version and to test its dimensional structure using a hypothesis-testing approach.

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来源期刊
CiteScore
5.60
自引率
10.70%
发文量
54
审稿时长
67 days
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