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Computerized Adaptive Testing Provides Reliable and Efficient Depression Measurement Using the CES-D Scale

机译:计算机化自适应测试使用CES-D刻度提供可靠和高效的抑郁测量

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Background The Center for Epidemiologic Studies Depression Scale (CES-D) is a measure of depressive symptomatology which is widely used internationally. Though previous attempts were made to shorten the CES-D scale, few have attempted to develop a Computerized Adaptive Test (CAT) version for the CES-D. Objective The aim of this study was to provide evidence on the efficiency and accuracy of the CES-D when administered using CAT using an American sample group. Methods We obtained a sample of 2060 responses to the CESD-D from US participants using the myPersonality application. The average age of participants was 26 years (range 19-77). We randomly split the sample into two groups to evaluate and validate the psychometric models. We used evaluation group data (n=1018) to assess dimensionality with both confirmatory factor and Mokken analysis. We conducted further psychometric assessments using item response theory (IRT), including assessments of item and scale fit to Samejima’s graded response model (GRM), local dependency and differential item functioning. We subsequently conducted two CAT simulations to evaluate the CES-D CAT using the validation group (n=1042). Results Initial CFA results indicated a poor fit to the model and Mokken analysis revealed 3 items which did not conform to the same dimension as the rest of the items. We removed the 3 items and fit the remaining 17 items to GRM. We found no evidence of differential item functioning (DIF) between age and gender groups. Estimates of the level of CES-D trait score provided by the simulated CAT algorithm and the original CES-D trait score derived from original scale were correlated highly. The second CAT simulation conducted using real participant data demonstrated higher precision at the higher levels of depression spectrum. Conclusions Depression assessments using the CES-D CAT can be more accurate and efficient than those made using the fixed-length assessment.
机译:背景技术流行病学研究中心抑郁症(CES-D)是一种抑郁症状学的衡量标准,其广泛使用在国际上。虽然之前尝试缩小CES-D规模,但很少有人试图为CES-D开发一个计算机化的自适应测试(CAT)版本。目的本研究的目的是提供有关使用美国样本组使用猫类施用时CES-D的效率和准确性的证据。方法使用MyPerseNality应用程序从美国参与者获得2060对CESD-D的响应的样本。参与者的平均年龄是26年(19-77个)。我们将样本随机分成两组以评估和验证心理模型。我们使用评估组数据(n = 1018)来评估验证因素和Mokken分析的维度。我们使用物品响应理论(IRT)进行了进一步的心理评估,包括项目和规模的评估,适合同盟的分级响应模型(GRM),局部依赖和差分项目功能。我们随后进行了两只CAT模拟以使用验证组(n = 1042)评估CES-D Cat。结果初始CFA结果表明,拟合模型和Mokken分析揭示了3个项目,该项目不符合与其他物品相同的维度。我们删除了3项,并将其余17项适合GRM。我们没有发现年龄和性别团体之间的差异项目(DIF)的证据。由模拟CAT算法提供的CES-D特征分数的估计和源自原始刻度的原始CES-D得分提供高度相关性。使用真实参与者数据进行的第二个Cat模拟在更高级别的抑郁频谱上表现出更高的精度。结论使用CES-D CAT的抑郁评估比使用固定长度评估制造的抑郁症评估可能更准确和高效。

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