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新手评估者运用运动系统损伤方法对腰痛患者进行分类的可靠性。

Reliability of novice raters in using the movement system impairment approach to classify people with low back pain.

作者信息

Henry Sharon M, Van Dillen Linda R, Trombley Andrea R, Dee Justine M, Bunn Janice Y

机构信息

Department of Rehabilitation Science, 305 Rowell Building, University of Vermont, Burlington, VT 05401, USA.

出版信息

Man Ther. 2013 Feb;18(1):35-40. doi: 10.1016/j.math.2012.06.008. Epub 2012 Jul 15.

Abstract

Observational cross sectional study. To examine the inter-rater reliability of novice raters in using the Movement System Impairment (MSI) approach system and to explore the patterns of disagreement in classification errors. The inter-rater reliability of individual tests items used in the MSI approach is moderate to good; however, the reliability of the classification algorithm has been tested only preliminarily. Using previously recorded patient data (n = 21), 13 novice raters classified patients according to the MSI schema. The overall percent agreement using the kappa statistic as well as the agreement/disagreement among pair-wise comparisons in classification assignments were examined. There was an overall 87.4% agreement in the pairs of classification judgments with a kappa coefficient of 0.81 (95% CI: 0.79, 0.83). Raters were most likely to agree on the classification of Flexion (100%) and least likely to agree on the classification of Rotation (84%). The MSI classification algorithm can be learned by novice users and with training, their inter-rater reliability in applying the algorithm for classification judgments is good and similar to that reported in other studies. However, some degree of error persists in the classification decision-making associated with the MSI system, in particular for the Rotation category.

摘要

观察性横断面研究。旨在检验新手评估者使用运动系统损伤(MSI)评估系统时的评分者间信度,并探究分类错误中的不一致模式。MSI评估中各个测试项目的评分者间信度为中等至良好;然而,分类算法的信度仅经过初步测试。利用之前记录的患者数据(n = 21),13名新手评估者根据MSI模式对患者进行分类。使用kappa统计量检验了总体一致百分比以及分类任务中两两比较之间的一致/不一致情况。分类判断对之间的总体一致率为87.4%,kappa系数为0.81(95% CI:0.79,0.83)。评估者在屈曲分类上最容易达成一致(100%),而在旋转分类上最不容易达成一致(84%)。新手用户能够学会MSI分类算法,并且经过培训后,他们在应用该算法进行分类判断时的评分者间信度良好,与其他研究报告的情况相似。然而,与MSI系统相关的分类决策中仍存在一定程度的误差,特别是在旋转类别上。

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