Suppr超能文献

功能动作筛查用于识别肌肉骨骼损伤风险升高个体的准确性。

The accuracy of the functional movement screen to identify individuals with an elevated risk of musculoskeletal injury.

作者信息

Krumrei Kirk, Flanagan Molly, Bruner Josh, Durall Chris

机构信息

Dept of Health Professions, University of Wisconsin-LaCrosse.

出版信息

J Sport Rehabil. 2014 Nov;23(4):360-4. doi: 10.1123/jsr.2013-0027. Epub 2014 Jan 21.

Abstract

CLINICAL SCENARIO

Injuries are somewhat commonplace in highly active populations. One strategy for reducing injuries is to identify individuals with an elevated injury risk before participation so that remediative interventions can be provided. Preparticipation screenings have traditionally entailed strength and flexibility measures thought to be indicative of inflated injury risk. Some researchers, however, have suggested that functional movements/tasks should be assessed to help identify individuals with a high risk of future injury. One assessment tool used for this purpose is the Functional Movement Screen (FMS). The FMS generates a numeric score based on performance attributes during 7 dynamic tasks; this score is purported to reflect future injury risk. Expanding interest in the FMS has led researchers to investigate how accurately it can identify individuals with an increased risk of injury.

FOCUSED CLINICAL QUESTION

Can the Functional Movement Screen accurately identify highly active individuals with an elevated risk of injury?

摘要

临床案例

在高活动量人群中,受伤情况较为常见。减少受伤的一种策略是在参与活动前识别出受伤风险较高的个体,以便提供补救性干预措施。传统上,参与前筛查包括力量和柔韧性测量,这些被认为能表明受伤风险增加。然而,一些研究人员建议应评估功能性动作/任务,以帮助识别未来受伤风险较高的个体。用于此目的的一种评估工具是功能性动作筛查(FMS)。FMS根据7项动态任务中的表现属性生成一个数字分数;这个分数据称能反映未来的受伤风险。对FMS兴趣的增加促使研究人员调查它能多准确地识别出受伤风险增加的个体。

重点临床问题

功能性动作筛查能否准确识别出受伤风险较高的高活动量个体?

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验