Boland David M, Neufeld Eric V, Ruddell Jack, Dolezal Brett A, Cooper Christopher B
Exercise Physiology Research Laboratory, Departments of Medicine and Physiology, David Geffen School of Medicine at the University of California, Los Angeles, USA.
J Phys Ther Sci. 2016 Dec;28(12):3398-3402. doi: 10.1589/jpts.28.3398. Epub 2016 Dec 27.
[Purpose] To determine the intra- and inter-rater agreement of a mobile application, PostureScreen Mobile (PSM), that assesses static standing posture. [Subjects and Methods] Three examiners with different levels of experience of assessing posture, one licensed physical therapist and two untrained undergraduate students, performed repeated postural assessments of 10 subjects, fully clothed or minimally clothed, using PSM on two nonconsecutive days. Anterior and right lateral images were captured and seventeen landmarks were identified on them. Intraclass correlation coefficients (ICCs) were calculated for each of 13 postural measures to evaluate inter-rater agreement on the first visit (fully or minimally clothed), as well as intra-rater agreement between the first and second visits (minimally clothed). [Results] Eleven postural measures were ultimately analyzed for inter- and intra-rater agreement. Inter-rater agreement was almost perfect (ICC≥0.81) for four measures and substantial (0.60<ICC≤0.80) for three measures during the fully clothed exam. During the minimally clothed exam, inter-rater agreement was almost perfect for four measures and substantial for four measures. Intra-rater agreement between two minimally clothed exams was almost perfect for two measures and substantial for five measures. [Conclusion] PSM is a widely available, inexpensive postural screening tool that requires little formal training. To maximize inter- and intra-rater agreement, postural screening using this mobile application should be conducted with subjects wearing minimal clothing. Assessing static standing posture via PSM gives repeatable measures for anatomical landmarks that were found to have substantial or almost perfect agreement. Our data also suggest that this technology may also be useful for diagnosing forward head posture.
[目的] 确定一款用于评估静态站立姿势的移动应用程序PostureScreen Mobile(PSM)在评估者内部和评估者之间的一致性。[受试者与方法] 三名具有不同姿势评估经验水平的检查者,一名持牌物理治疗师和两名未经训练的本科生,在两个非连续的日子里,使用PSM对10名受试者(穿着全套衣服或最少的衣服)进行重复的姿势评估。拍摄了前视图和右侧视图图像,并在上面识别出17个标志点。计算了13项姿势测量指标中每项的组内相关系数(ICC),以评估首次就诊时(穿着全套衣服或最少的衣服)评估者之间的一致性,以及首次和第二次就诊(穿着最少的衣服)时评估者内部的一致性。[结果] 最终对11项姿势测量指标进行了评估者间和评估者内一致性分析。在穿着全套衣服的检查中,四项指标的评估者间一致性几乎完美(ICC≥0.81),三项指标的一致性较高(0.60<ICC≤0.80)。在穿着最少衣服的检查中,四项指标的评估者间一致性几乎完美,四项指标的一致性较高。两次穿着最少衣服检查之间的评估者内一致性,两项指标几乎完美,五项指标较高。[结论] PSM是一种广泛可用、价格低廉的姿势筛查工具,几乎不需要正式培训。为了最大限度地提高评估者间和评估者内的一致性,使用这款移动应用程序进行姿势筛查时,受试者应穿着最少的衣服。通过PSM评估静态站立姿势可为解剖标志点提供可重复的测量结果,这些结果显示出较高或几乎完美的一致性。我们的数据还表明,这项技术可能也有助于诊断头部前倾姿势。