Chen Guangdong, Li Ranli, Tian Hongjun, Ma Xiaoyan, Sun Yun, Jia Feng, Ping Jing, Cai Ziyao, Zhu Jingjing, Zhuo Chuanjun, Pan Zhi
Department of Psychiatry, Children Center, Wenzhou Seventh Peoples Hospital, Wenzhou, China.
Department of Psychiatry, MECT Center, Tianjin Anding Hospital, Tianjin, China.
Brain Behav. 2023 Oct;13(10):e3185. doi: 10.1002/brb3.3185. Epub 2023 Aug 10.
The Davos Assessment of Cognitive Biases Scale (DACOBS) is widely used to assess cognitive biases in patients who have schizophrenia. However, the lack of a modified Chinese-language version of the DACOBS (MCL-DACOBS) precludes Chinese schizophrenic patients from treatment aimed at normalizing cognitive biases, impacting their prognosis. Here, we aimed to produce a DACOBS for China and test the validity and reliability of the resultant MCL-DACOBS.
Eighteen researchers collaborated to develop the MCL-DACOBS: A total of 15 researchers modified and translated the English version of the DACOBS, 1 native-English-speaking researcher back-translated the scale, and 2 Chinese sinologists localized and optimized the language of the MCL-DACOBS. Forty-two volunteers checked the scale items' comprehensibility, and the two sinologists performed further localization and optimization based on their feedback. The final version of the MCL-DACOBS used in this study was thus derived from the harmonized English-language version of the scale. Confirmatory factor analyses (CFAs) were used to examine the best latent structure of the MCL-DACOBS. Cronbach's α and intraclass correlation coefficients (ICCs) were used to check the reliability. The discriminative ability of the MCL-DACOBS was assessed according to the area under the receiver operating characteristic curve.
The CFA showed that all items loaded onto factors with loadings >0.400. A two-factor structure showed a good model fit (root mean square error of approximation = .018, Tucker-Lewis index = .978, comparative fit index = .984). Promax rotation demonstrated that each item had a high factor load (0.432-0.774). Cronbach's α coefficient and ICC for the MCL-DOCABS were .965 and .957, respectively, indicating that the scale has ideal reliability.
The MCL-DACOBS has good validity and good reliability, and its psychometric properties indicate that it is a valid tool for measuring cognitive biases in Chinese patients with schizophrenia.
达沃斯认知偏差评估量表（DACOBS）被广泛用于评估精神分裂症患者的认知偏差。然而，缺乏经过修订的中文版DACOBS（MCL-DACOBS）使得中国精神分裂症患者无法接受旨在使认知偏差正常化的治疗，从而影响其预后。在此，我们旨在编制一份适用于中国的DACOBS，并检验所得MCL-DACOBS的有效性和可靠性。
18名研究人员合作编制MCL-DACOBS：共有15名研究人员对DACOBS英文版进行修改和翻译，1名以英语为母语的研究人员对该量表进行回译，2名中国汉学家对MCL-DACOBS的语言进行本地化和优化。42名志愿者检查了量表项目的可理解性，两位汉学家根据他们的反馈进行了进一步的本地化和优化。本研究中使用的MCL-DACOBS最终版本由此从该量表的统一英文版衍生而来。采用验证性因素分析（CFA）来检验MCL-DACOBS的最佳潜在结构。使用克朗巴赫α系数和组内相关系数（ICC）来检验可靠性。根据受试者工作特征曲线下的面积评估MCL-DACOBS的区分能力。
CFA显示所有项目在负荷>0.400的因素上有负荷。两因素结构显示出良好的模型拟合（近似均方根误差=0.018，塔克-刘易斯指数=0.978，比较拟合指数=0.984）。斜交旋转表明每个项目都有较高的因素负荷（0.432 - 0.774）。MCL-DOCABS的克朗巴赫α系数和ICC分别为0.965和0.957，表明该量表具有理想的可靠性。
MCL-DACOBS具有良好的有效性和可靠性，其心理测量特性表明它是测量中国精神分裂症患者认知偏差的有效工具。
