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高级移动性评估工具(HiMAT)的进一步开发。

Further development of the High-level Mobility Assessment Tool (HiMAT).

作者信息

Williams Gavin, Pallant Julie, Greenwood Ken

机构信息

Physiotherapy Department, Epworth Hospital, 89 Bridge Rd., Richmond, 3121 Victoria, Australia.

出版信息

Brain Inj. 2010;24(7-8):1027-31. doi: 10.3109/02699052.2010.490517.

DOI:10.3109/02699052.2010.490517
PMID:20545456
Abstract

PRIMARY OBJECTIVES

The high-level mobility assessment tool (HiMAT) was developed to measure high-level mobility limitations following traumatic brain injury (TBI). Rasch analysis was used in the development to ensure cognitive deficits would have a minimal impact on performance. The main aim of this study was to investigate the dimensionality of the HiMAT using recently developed advanced testing procedures.

RESEARCH DESIGN

Results from the original sample of 103 adults with TBI used to develop the HiMAT were re-analysed using the RUMM2020 program. Revised minimal detectable change (MDC(95)) scores were also calculated.

MAIN OUTCOMES AND RESULTS

Rasch analysis of all 13 HiMAT items suggested that the scale was multidimensional, showing a clear separation between the stair and non-stair items. The nine non-stair items of the HiMAT showed good overall fit, excellent internal consistency, with no disordered thresholds or misfitting items, however removal of one item was required to ensure a unidimensional scale. The final 8-item solution showed good model fit (p = 0.93), excellent internal consistency (PSI = 0.96), no disordered thresholds, no misfitting items and no differential item functioning for age or sex. The revised HiMAT total score is 32 points and the MDC(95) was calculated to be +/-2 points.

CONCLUSION

The results of this study demonstrate that the revised HiMAT is unidimensional and valid to use in rehabilitation and community settings where there is no access to stairs.

摘要

主要目标

高级运动能力评估工具(HiMAT)旨在测量创伤性脑损伤(TBI)后的高级运动能力受限情况。在开发过程中使用了拉施分析,以确保认知缺陷对测试表现的影响最小。本研究的主要目的是使用最近开发的先进测试程序来研究HiMAT的维度。

研究设计

使用RUMM2020程序对用于开发HiMAT的103名成年TBI患者的原始样本结果进行重新分析。还计算了修订后的最小可检测变化(MDC(95))分数。

主要结果

对HiMAT的所有13个项目进行拉施分析表明,该量表是多维的,楼梯项目和非楼梯项目之间有明显区分。HiMAT的九个非楼梯项目总体拟合良好,内部一致性极佳,没有无序阈值或拟合不佳的项目,然而需要删除一个项目以确保量表为单维。最终的8个项目解决方案显示出良好的模型拟合(p = 0.93),出色的内部一致性(PSI = 0.96),没有无序阈值,没有拟合不佳的项目,并且年龄或性别方面没有项目功能差异。修订后的HiMAT总分是32分,MDC(95)计算为±2分。

结论

本研究结果表明,修订后的HiMAT是单维的,可有效用于无法使用楼梯的康复和社区环境。

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