Sachs Gabriele, Bannick Gloria, Maihofer Eva I J, Voracek Martin, Purdon Scot E, Erfurth Andreas
Medical University of Vienna, Vienna, Austria.
1 Department of Psychiatry and Psychotherapeutic Medicine, Klinik Hietzing, Vienna, Austria.
Schizophr Res Cogn. 2022 Jun 6;29:100259. doi: 10.1016/j.scog.2022.100259. eCollection 2022 Sep.
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).
323 patients with psychotic, bipolar affective, and depressive disorders were studied.
The one-factor approach did not yield an acceptable model fit (chi-squared test: χ = 109.5, df = 5, < 0.001, χ/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 (χ = 6.7, df = 3, = 0.08, χ/df = 2.2).
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.
精神疾病,尤其是精神分裂症,其特征为认知障碍。在疾病过程中快速检测认知功能障碍至关重要。精神病认知损害筛查量表(SCIP)旨在为临床实践中的精神病患者提供筛查,并且有多种语言版本。先前对SCIP维度的心理测量学研究产生了两种不同模型:单因素模型假设SCIP的五个子量表共同负荷,而另一种模型则表明子量表负荷于两个因素,即言语记忆和处理速度。我们对SCIP德文版(SCIP-G)进行了验证性因素分析。
对323例患有精神病性、双相情感性和抑郁性障碍的患者进行了研究。
单因素方法未产生可接受的模型拟合度(卡方检验:χ = 109.5,自由度 = 5,<0.001,χ/自由度 = 21.9)。双因素解决方案中,言语学习测试-即时回忆、言语学习测试的延迟回忆测试和工作记忆测试这些子测试负荷于第一个因素,而言语流畅性测试和精神运动速度测试子测试负荷于第二个因素,该方案获得了良好的模型拟合度(χ = 6.7,自由度 = 3, = 0.08,χ/自由度 = 2.2)。
这些数据表明,SCIP采用双因素解决方案可实现良好的模型拟合度。本研究首次使用德文版SCIP进行验证性因素分析,并采用假设检验方法测试其维度结构。