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一款用于姿势分析的移动应用程序的评分者信度和结构效度。

Rater reliability and construct validity of a mobile application for posture analysis.

作者信息

Szucs Kimberly A, Brown Elena V Donoso

机构信息

Department of Occupational Therapy, Duquesne University: 600 Forbes Avenue, Pittsburgh, PA, USA.

出版信息

J Phys Ther Sci. 2018 Jan;30(1):31-36. doi: 10.1589/jpts.30.31. Epub 2018 Jan 27.

DOI:10.1589/jpts.30.31
PMID:29410561
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5788770/
Abstract

[Purpose] Measurement of posture is important for those with a clinical diagnosis as well as researchers aiming to understand the impact of faulty postures on the development of musculoskeletal disorders. A reliable, cost-effective and low tech posture measure may be beneficial for research and clinical applications. The purpose of this study was to determine rater reliability and construct validity of a posture screening mobile application in healthy young adults. [Subjects and Methods] Pictures of subjects were taken in three standing positions. Two raters independently digitized the static standing posture image twice. The app calculated posture variables, including sagittal and coronal plane translations and angulations. Intra- and inter-rater reliability were calculated using the appropriate ICC models for complete agreement. Construct validity was determined through comparison of known groups using repeated measures ANOVA. [Results] Intra-rater reliability ranged from 0.71 to 0.99. Inter-rater reliability was good to excellent for all translations. ICCs were stronger for translations versus angulations. The construct validity analysis found that the app was able to detect the change in the four variables selected. [Conclusion] The posture mobile application has demonstrated strong rater reliability and preliminary evidence of construct validity. This application may have utility in clinical and research settings.

摘要

[目的] 姿势测量对于临床诊断患者以及旨在了解不良姿势对肌肉骨骼疾病发展影响的研究人员而言至关重要。一种可靠、经济高效且技术要求低的姿势测量方法可能对研究和临床应用有益。本研究的目的是确定一款姿势筛查移动应用程序在健康年轻成年人中的评分者信度和结构效度。[对象与方法] 拍摄受试者在三种站立姿势下的照片。两名评分者独立对静态站立姿势图像进行两次数字化处理。该应用程序计算姿势变量,包括矢状面和冠状面平移及角度。使用适用于完全一致性的ICC模型计算评分者内信度和评分者间信度。通过重复测量方差分析比较已知组来确定结构效度。[结果] 评分者内信度范围为0.71至0.99。所有平移的评分者间信度良好至优秀。与角度相比,平移的ICC更强。结构效度分析发现该应用程序能够检测所选四个变量的变化。[结论] 姿势移动应用程序已证明具有较高的评分者信度和结构效度的初步证据。该应用程序可能在临床和研究环境中有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62c5/5788770/4da56345ead1/jpts-30-031-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62c5/5788770/4da56345ead1/jpts-30-031-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62c5/5788770/4da56345ead1/jpts-30-031-g001.jpg

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