中文版躯干损伤量表评定脑卒中患者躯干功能的信度及效度研究
Chinese Journal of Rehabilitation Medicine（2020）
Abstract
目的:探讨中文版躯干损伤量表(TIS)评定脑卒中患者躯干功能的信度及效度,为该量表的临床应用提供客观依据.方法:病例组和对照组各50例参加了本研究,病例组进行TIS、Fugl-Meyer中的平衡部分(FM-B)和Berg平衡量表(BBS)评定,并在2天内完成TIS第二次评定;对照组进行1次的TIS和FM-B评定.将两次TIS的结果做相关性分析测试其信度;将TIS结果与FM-B、BBS作相关性分析检验其效度.结果:TIS两次测试结果高度相关,重测信度组内相关系数(ICC)为0.899-0.971,测量者间ICC为0.843-0.973;TIS与FM-B、BBS总分高度相关(r=0.891,r=0.858);病例组和对照组的TIS总分分别为21.7±1.3分和13.5±4.3分,两者间差异具有显著性(P＜0.01).结论:中文版TIS具有良好的效度、信度和区分度,可用于脑卒中患者躯干功能的评价.
More求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined