Bjorner Jakob B, Kosinski Mark, Ware John E
QualityMetric Incorporated, Lincoln, RI 02895, USA.
Qual Life Res. 2003 Dec;12(8):913-33. doi: 10.1023/a:1026163113446.
Measurement of headache impact is important in clinical trials, case detection, and the clinical monitoring of patients. Computerized adaptive testing (CAT) of headache impact has potential advantages over traditional fixed-length tests in terms of precision, relevance, real-time quality control and flexibility.
To develop an item pool that can be used for a computerized adaptive test of headache impact.
We analyzed responses to four well-known tests of headache impact from a population-based sample of recent headache sufferers (n = 1016). We used confirmatory factor analysis for categorical data and analyses based on item response theory (IRT).
In factor analyses, we found very high correlations between the factors hypothesized by the original test constructers, both within and between the original questionnaires. These results suggest that a single score of headache impact is sufficient. We established a pool of 47 items which fitted the generalized partial credit IRT model. By simulating a computerized adaptive health test we showed that an adaptive test of only five items had a very high concordance with the score based on all items and that different worst-case item selection scenarios did not lead to bias.
We have established a headache impact item pool that can be used in CAT of headache impact.
头痛影响的测量在临床试验、病例检测以及患者的临床监测中具有重要意义。与传统的固定长度测试相比,头痛影响的计算机自适应测试(CAT)在精度、相关性、实时质量控制和灵活性方面具有潜在优势。
开发一个可用于头痛影响计算机自适应测试的项目库。
我们分析了来自近期头痛患者的基于人群样本(n = 1016)对四项著名头痛影响测试的回答。我们对分类数据使用验证性因素分析,并基于项目反应理论(IRT)进行分析。
在因素分析中,我们发现原始测试构建者假设的因素之间在原始问卷内部和之间都具有非常高的相关性。这些结果表明单一的头痛影响评分就足够了。我们建立了一个由47个项目组成的库,这些项目符合广义部分计分IRT模型。通过模拟计算机自适应健康测试,我们表明仅五项的自适应测试与基于所有项目的分数具有非常高的一致性,并且不同的最坏情况项目选择方案不会导致偏差。
我们已经建立了一个可用于头痛影响CAT的头痛影响项目库。