Test-Retest Reliability and Preliminary Reference Data for the Virtual Eggs Test in Healthy Adults

IF 6.6 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Lucia Angelini;Michele Piazzini;Marco Baccini;Tommaso Ciappetti;Francesca Cecchi;Marco Controzzi
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引用次数: 0

Abstract

Rehabilitation professionals rely on hand assessment to select the proper therapy and monitor the recovery process over time. The Virtual Eggs Test (VET) is a unique assessment tool that evaluates both fine and gross hand dexterity, taking into account not only the speed in performing an action but also the accuracy in regulating the grip force. The VET was preliminary validated with amputees and healthy individuals, demonstrating construct validity, but also highlighting some weaknesses that required a protocol revision. Here, we present the update version of the protocol and of the outcomes measure (Fine Dexterity Index–FDI - and Gross Dexterity Index - GDI). We carried on a clinical trial involving 79 healthy participants, stratified by age groups, to collect normative data and evaluate test-retest reliability. The FDI and the GDI demonstrate no significant difference between test and retest. FDI showed excellent reliability (ICC was 0.90 and 0.91 for the dominant and non-dominant hand, respectively). While GDI demonstrated moderate reliability (ICC was equal to 0.63 and 0.64 for the dominant and non-dominant hand, respectively). The findings indicate that the VET is reliable over time for the evaluation of hand function in tasks involving fragile objects.
虚拟卵子试验在健康成人中的测试-重测信度和初步参考数据。
康复专业人员依靠手部评估来选择合适的治疗方法,并长期监测康复过程。虚拟鸡蛋测试(VET)是一种独特的评估工具,评估精细和粗糙的手灵巧性,不仅考虑到执行动作的速度,而且考虑到调节握力的准确性。在截肢者和健康个体中对VET进行了初步验证,证明了构建的有效性,但也强调了一些需要修改方案的弱点。在这里,我们提出了更新版本的方案和结果测量(精细灵巧指数- FDI -和总灵巧指数- GDI)。我们进行了一项涉及79名健康参与者的临床试验,按年龄组分层,以收集规范数据并评估重测信度。FDI和GDI在两次检验之间没有显著差异。FDI表现出优异的信度(优势手和非优势手的ICC分别为0.90和0.91)。而GDI表现出中等信度(优势手和非优势手的ICC分别为0.63和0.64)。研究结果表明,随着时间的推移,VET对于评估涉及易碎物体的手功能是可靠的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
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