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首页> 外文期刊>Brain injury: BI >The high-level mobility assessment tool (HiMAT) for traumatic brain injury. Part 2: content validity and discriminability.
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The high-level mobility assessment tool (HiMAT) for traumatic brain injury. Part 2: content validity and discriminability.

机译：用于颅脑外伤的高级流动性评估工具（HiMAT）。第2部分：内容的有效性和可辨别性。

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摘要

PRIMARY OBJECTIVES: (i) To assess the measurement properties of the high-level mobility assessment tool (HiMAT) for people with traumatic brain injury (TBI), (ii) to measure the extent to which the HiMAT is a uni-dimensional, discriminative hierarchical outcome scale. RESEARCH DESIGN: The content validity was assessed using a three-stage process of investigating internal consistency, factor analysis and Rasch analysis. The uni-dimensionality of the HiMAT items was also tested. Discriminability was investigated by correlating raw and logit scores obtained from Rasch analysis. The study was conducted at a major rehabilitation facility using a convenience sample of 103 adults with TBI. MAIN OUTCOMES AND RESULTS: The internal consistency for the high-level items was very high (Cronbach's alpha = 0.99). Principal axis factoring identified several balance items as belonging to a second factor not related to high-level mobility, hence these items were excluded. Rasch analysis identified several misfitting items, such as walking around a figure of eight and stopping from a run, which were also excluded. Logit scores were used to exclude clustered and, therefore, redundant items. Raw scores correlated very highly (r = 0.98) with logit scores, indicating that raw scores provided good discriminability and were suitable for use by clinicians. CONCLUSION: The HiMAT, which assesses higher-level mobility requirements of people with TBI for return to pre-accident social, leisure and sporting activities, is a uni-dimensional and discriminative scale for quantifying therapy outcomes.
机译：主要目标：（i）评估高水平移动性评估工具（HiMAT）对颅脑外伤（TBI）人群的测量特性，（ii）衡量HiMAT在多维度，具有判别力的程度上分级结果量表。研究设计：内容有效性通过调查内部一致性，因素分析和Rasch分析的三个阶段的过程进行评估。还测试了HiMAT项目的一维性。通过关联从Rasch分析获得的原始分数和logit分数来研究可分辨性。该研究是在一家大型康复机构中使用103名TBI成人的便利样本进行的。主要结果和结果：高级项目的内部一致性非常高（Cronbach's alpha = 0.99）。主轴分解确定了几个余额项目，它们属于与高层流动性无关的第二个因素，因此将这些项目排除在外。 Rasch分析确定了一些不合适的项目，例如绕着八字行走并停止奔跑，这些也被排除在外。 Logit分数用于排除聚类的项目，因此不包括冗余项。原始分数与logit分数具有极高的相关性（r = 0.98），这表明原始分数可提供良好的可分辨性，适合临床医生使用。结论：HiMAT评估了TBI患者返回事故前的社交，休闲和体育活动的更高水平的移动需求，它是用于量化治疗结果的单维度和区分性量表。

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