Development of a computer-adaptive test for depression (D-CAT)
Development of a computer-adaptive test for depression (D-CAT)
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DOI：
10.1007/s11136-005-6651-9
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发表时间：
2005-12-01
影响因子：
3.5
通讯作者：
Rose, M
中科院分区：
文献类型：
--
作者：
Fliege, H;Becker, J;Rose, M
抑郁症是最普遍的心理健康问题之一，测量抑郁症状在科学和医疗实践中变得越来越重要。基于项目反应理论（IRT）的计算机自适应测验（CAT）有望提高测量精度，减轻被试负担。我们的目标是开发一个CAT应用程序来测量抑郁症状。在柏林的大学诊所，3270名心身患者回答了总共11份心理健康问卷。三位独立的评审员将这些问卷中的144项评定为抑郁症状的指标。所有项目经过六个实证步骤，分析单维度，局部独立性和项目歧视。最后，64个项目可以用来计算项目参数应用广义部分信用模型（GPCM）。CAT评分使用“预期后验”算法（EAP）进行估计。两个模拟实验表明，对于在平均值周围的2SD范围内的θ值（98%的情况），可以从大约六个项目中估计潜在特质，预定义的标准误差= 0.90）。CAT评分与所有抑郁项目评分（r = 0.95）、Beck抑郁量表评分（r = 0.79）和CES-D 8项目简表评分（r = 0.76）高度相关。我们的结论是抑郁症CAT措施抑郁症状的高精度和低应答负担。
Depression is one of the most prevalent mental health problems and measuring depressive symptoms becomes increasingly important in science as well as medical practice. Computer Adaptive Tests (CAT) based on the Item Response Theory (IRT) promise to enhance measurement precision and reduce respondent's burden. Our aim was to develop a CAT application to measure depressive symptoms. Three thousand two hundred seventy psychosomatic patients answered an overall of 11 mental health questionnaires at the University Clinic in Berlin. Three independent reviewers rated 144 items out of these questionnaires as indicative of depressive symptoms. All items underwent six empirical steps to analyze unidimensionality, local independence and item discrimination. Finally 64 items could be used to calculate item parameters applying a Generalized Partial Credit Model (GPCM). CAT scores were estimated using an 'expected a posteriori' algorithm (EAP). Two simulation experiments showed that for theta values within the range of 2SD around the mean (98% of the cases), the latent trait can be estimated out of approximately six items with a predefined standard error of = 0.90). The CAT-scores correlated high with scores of all depression items (r = 0.95), with the Beck Depression Inventory (r = 0.79) and with a CES-D 8 item short form (r = 0.76). We conclude that the Depression-CAT measures depressive symptoms with high precision and low respondent burden.