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A Multidimensional Rasch Analysis of the Functional Independence Measure Based on the National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems National Database

机译:基于国家残疾人,独立生活与康复研究所创伤性脑损伤模型系统国家数据库的功能独立性测度的多维Rasch分析

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A number of studies have evaluated the psychometric properties of the Functional Independence Measure (FIM (TM)) using Rasch analysis, although none has done so using the National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems National Database, a longitudinal database that captures demographic and outcome information on persons with moderate to severe traumatic brain injury across the United States. In the current study, we examine the psychometric properties of the FIM as represented by persons within this database and demonstrate that the FIM comprises three subscales representing cognitive, self-care, and mobility domains. These subscales were analyzed simultaneously using a multivariate Rasch model in combination with a time dependent concurrent calibration scheme with the goal of creating a raw score-to-logit transformation that can be used to improve the accuracy of parametric statistical analyses. The bowel and bladder function items were removed because of misfit with the motor and cognitive items. Some motor items exhibited step disorder, which was addressed by collapsing Categories 1-3 for Toileting, Stairs, Locomotion, Tub/Shower Transfers; Categories 1 and 2 for Toilet and Bed Transfers; and Categories 2 and 3 for Grooming. The strong correlations (r = 0.82-0.96) among the three subscales suggest they should be modeled together. Coefficient alpha of 0.98 indicates high internal consistency. Keyform maps are provided to enhance clinical interpretation and application of study results.
机译:许多研究使用Rasch分析评估了功能独立性测度(FIM(TM))的心理测量特性,尽管没有使用美国国家残疾人,独立生活与康复研究所创伤性脑损伤模型系统国家数据库进行评估,一个纵向数据库,可捕获全美中度至重度颅脑外伤患者的人口统计和结果信息。在当前的研究中,我们检查了该数据库中人物所代表的FIM的心理计量特性,并证明FIM包括代表认知,自我护理和行动领域的三个子量表。使用多变量Rasch模型并结合时间依赖的并发校准方案同时分析这些子量表,目的是创建可用于提高参数统计分析准确性的原始得分到逻辑转换。肠和膀胱功能项目因与运动和认知项目不匹配而被移除。一些运动用品表现出步调障碍,可以通过折叠厕所,楼梯,运动,浴缸/淋浴间转移的类别1-3来解决。洗手间和床类的分类1和2;以及修饰的类别2和3。三个子量表之间的强相关性(r = 0.82-0.96)表明应该将它们一起建模。系数α为0.98表示较高的内部一致性。提供了关键形式图以增强临床解释和研究结果的应用。

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