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针对肩部损伤患者的模拟计算机自适应测试效率高,且能有效测量功能。

Simulated computerized adaptive test for patients with shoulder impairments was efficient and produced valid measures of function.

作者信息

Hart Dennis L, Cook Karon F, Mioduski Jerome E, Teal Cayla R, Crane Paul K

机构信息

Focus On Therapeutic Outcomes, Inc., 551 Yopps Cove Road, White Stone, VA 22578, USA.

出版信息

J Clin Epidemiol. 2006 Mar;59(3):290-8. doi: 10.1016/j.jclinepi.2005.08.006. Epub 2005 Dec 27.

Abstract

BACKGROUND AND OBJECTIVE

To test unidimensionality and local independence of a set of shoulder functional status (SFS) items, develop a computerized adaptive test (CAT) of the items using a rating scale item response theory model (RSM), and compare discriminant validity of measures generated using all items (theta(IRT)) and measures generated using the simulated CAT (theta(CAT)).

STUDY DESIGN AND SETTING

We performed a secondary analysis of data collected prospectively during rehabilitation of 400 patients with shoulder impairments who completed 60 SFS items.

RESULTS

Factor analytic techniques supported that the 42 SFS items formed a unidimensional scale and were locally independent. Except for five items, which were deleted, the RSM fit the data well. The remaining 37 SFS items were used to generate the CAT. On average, 6 items were needed to estimate precise measures of function using the SFS CAT, compared with all 37 SFS items. The theta(IRT) and theta(CAT) measures were highly correlated (r = .96) and resulted in similar classifications of patients.

CONCLUSION

The simulated SFS CAT was efficient and produced precise, clinically relevant measures of functional status with good discriminating ability.

摘要

背景与目的

检验一组肩部功能状态(SFS)项目的单维性和局部独立性,使用等级量表项目反应理论模型(RSM)开发这些项目的计算机自适应测试(CAT),并比较使用所有项目生成的测量值(θ(IRT))和使用模拟CAT生成的测量值(θ(CAT))的判别效度。

研究设计与设置

我们对400例肩部损伤患者康复期间前瞻性收集的数据进行了二次分析,这些患者完成了60个SFS项目。

结果

因子分析技术支持42个SFS项目形成一个单维量表且具有局部独立性。除了5个被删除的项目外,RSM与数据拟合良好。其余37个SFS项目用于生成CAT。平均而言,使用SFS CAT估计功能的精确测量值需要6个项目,而使用所有37个SFS项目。θ(IRT)和θ(CAT)测量值高度相关(r = 0.96),并导致对患者的类似分类。

结论

模拟的SFS CAT效率高,能产生精确的、具有临床相关性的功能状态测量值,且具有良好的判别能力。

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