Institute of Medical Psychology and Medical Sociology, University Hospital of RWTH Aachen, Germany.
J Psychosom Res. 2013 Nov;75(5):437-43. doi: 10.1016/j.jpsychores.2013.08.022. Epub 2013 Sep 4.
This study conducted a simulation study for computer-adaptive testing based on the Aachen Depression Item Bank (ADIB), which was developed for the assessment of depression in persons with somatic diseases. Prior to computer-adaptive test simulation, the ADIB was newly calibrated.
Recalibration was performed in a sample of 161 patients treated for a depressive syndrome, 103 patients from cardiology, and 103 patients from otorhinolaryngology (mean age 44.1, SD=14.0; 44.7% female) and was cross-validated in a sample of 117 patients undergoing rehabilitation for cardiac diseases (mean age 58.4, SD=10.5; 24.8% women). Unidimensionality of the itembank was checked and a Rasch analysis was performed that evaluated local dependency (LD), differential item functioning (DIF), item fit and reliability. CAT-simulation was conducted with the total sample and additional simulated data.
Recalibration resulted in a strictly unidimensional item bank with 36 items, showing good Rasch model fit (item fit residuals<|2.5|) and no DIF or LD. CAT simulation revealed that 13 items on average were necessary to estimate depression in the range of -2 and +2 logits when terminating at SE≤0.32 and 4 items if using SE≤0.50. Receiver Operating Characteristics analysis showed that θ estimates based on the CAT algorithm have good criterion validity with regard to depression diagnoses (Area Under the Curve≥.78 for all cut-off criteria).
The recalibration of the ADIB succeeded and the simulation studies conducted suggest that it has good screening performance in the samples investigated and that it may reasonably add to the improvement of depression assessment.
本研究对基于阿亨抑郁条目库(ADIB)的计算机自适应测试进行了模拟研究,ADIB 是为评估躯体疾病患者的抑郁而开发的。在进行计算机自适应测试模拟之前,对 ADIB 进行了重新校准。
在 161 名接受抑郁综合征治疗的患者、103 名心脏病学患者和 103 名耳鼻喉科患者(平均年龄 44.1,SD=14.0;44.7%女性)的样本中进行了重新校准,并在 117 名接受心脏疾病康复治疗的患者(平均年龄 58.4,SD=10.5;24.8%女性)的样本中进行了交叉验证。检查了条目库的单维性,并进行了 Rasch 分析,评估了局部依赖(LD)、差异项目功能(DIF)、项目拟合和可靠性。使用总样本和额外的模拟数据进行了 CAT 模拟。
重新校准产生了一个严格的单维条目库,共有 36 个条目,显示出良好的 Rasch 模型拟合(项目拟合残差<|2.5|),没有 DIF 或 LD。CAT 模拟表明,当终止于 SE≤0.32 时,平均需要 13 个项目来估计 -2 和+2 对数范围内的抑郁,而如果使用 SE≤0.50,则需要 4 个项目。接收者操作特征分析表明,基于 CAT 算法的θ估计值在所有截止标准下对抑郁诊断都具有良好的标准有效性(曲线下面积≥.78)。
ADIB 的重新校准取得了成功,模拟研究表明,它在调查样本中具有良好的筛选性能,并且可能合理地提高了抑郁评估的准确性。