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BESTest量表在神经系统疾病患者中的测量属性:一项荟萃分析的系统评价

Measurement Properties of the BESTest Scale in People With Neurological Conditions: A Systematic Review With Meta-Analysis.

作者信息

Arcolin Ilaria, Giardini Marica, Tagliabue Federica, Belluscio Valeria, Horak Fay, Godi Marco

机构信息

Department of Physical Medicine and Rehabiitation of Veruno Institute, Istituti Clinici Scientifici Maugeri IRCCS, Gattico-Veruno 28013, Italy.

Department of Human Movement and Sport Science, University of Rome "Foro Italico", Rome 00135, Italy.

出版信息

Phys Ther. 2025 Mar 3;105(3). doi: 10.1093/ptj/pzae178.

Abstract

OBJECTIVE

People with neurological conditions (PwNC) frequently fall, mainly due to balance impairments. Among the scales assessing balance, the Balance Evaluation System Test (BESTest) is one of the most comprehensive in evaluating all components of postural control. This study aimed to systematically review and summarize the measurement properties of the BESTest in PwNC.

METHODS

Embase, MEDLINE, ScienceDirect, Scopus, and PEDro were searched up to December 2023. Studies assessing at least 1 BESTest measurement property in PwNC were included. Methodological quality of studies was assessed with the COSMIN Risk of Bias checklist. Overall rating and level of evidence for each property were given according to COSMIN criteria. Where possible, meta-analysis was performed.

RESULTS

Thirty-six studies (1749 PwNC) were included. The BESTest demonstrated a high quality of evidence supporting good reliability (intraclass correlation coefficients = 0.96-0.98 for total score, and 0.70-0.98 for subsections), internal consistency, and measurement error. High quality levels of responsiveness, and content and construct validity were also found. However, evidence for structural validity was insufficient to be sure the BESTest actually tests several, or 1, balance constructs. Criterion validity cannot be evaluated. While translated into different languages, cross-cultural validity has never been assessed in PwNC. Evidence to support use of the BESTest for specific neurological conditions is limited to Parkinson disease and stroke, due to the small sample sizes and number of studies in other populations.

CONCLUSION

This systematic review provided high quality evidence supporting the reliability, content and construct validity, and responsiveness of the BESTest to intervention, being able to detect balance changes and to differentiate heterogeneous PwNC based on fall history, falling risk, and physical performance. However, low-quality evidence was found when considering each neurological condition alone. To comprehensively understand the BESTest measurement properties, future studies are needed with larger samples for each neurological condition, especially assessing cross-cultural and structural validity.

IMPACT

Assessing balance is crucial for fall risk prevention. The BESTest has been demonstrated to be a reliable, responsive, and valid scale usable in clinical setting for assessing balance in PwNC.

LAY SUMMARY

Assessing balance is crucial for fall risk prevention. The BESTest has been demonstrated to be a reliable, responsive, and valid scale usable in clinical setting for assessing balance in PwNC.

摘要

目的

患有神经系统疾病的人(PwNC)经常跌倒,主要原因是平衡功能受损。在评估平衡的量表中,平衡评估系统测试(BESTest)是评估姿势控制所有组成部分最全面的量表之一。本研究旨在系统回顾和总结BESTest在PwNC中的测量特性。

方法

检索截至2023年12月的Embase、MEDLINE、ScienceDirect、Scopus和PEDro数据库。纳入评估PwNC中至少一项BESTest测量特性的研究。采用COSMIN偏倚风险清单评估研究的方法学质量。根据COSMIN标准给出每个特性的总体评分和证据水平。在可能的情况下,进行荟萃分析。

结果

纳入36项研究(1749名PwNC)。BESTest显示出高质量的证据支持良好的信度(总分的组内相关系数=0.96 - 0.98,各子部分的组内相关系数为0.70 - 0.98)、内部一致性和测量误差。还发现了高质量水平的反应度、内容效度和结构效度。然而,结构效度的证据不足以确定BESTest实际上测试的是几种还是一种平衡结构。无法评估标准效度。虽然已翻译成不同语言,但从未在PwNC中评估过跨文化效度。由于其他人群的样本量小和研究数量有限,支持将BESTest用于特定神经系统疾病的证据仅限于帕金森病和中风。

结论

本系统评价提供了高质量证据,支持BESTest的信度、内容效度和结构效度以及对干预的反应度,能够检测平衡变化,并根据跌倒史、跌倒风险和身体表现区分不同的PwNC。然而,单独考虑每种神经系统疾病时,发现证据质量较低。为全面了解BESTest的测量特性,未来需要针对每种神经系统疾病进行更大样本量的研究,特别是评估跨文化效度和结构效度。

影响

评估平衡对于预防跌倒风险至关重要。BESTest已被证明是一种可靠、灵敏且有效的量表,可用于临床环境中评估PwNC的平衡。

简要概述

评估平衡对于预防跌倒风险至关重要。BESTest已被证明是一种可靠、灵敏且有效的量表,可用于临床环境中评估PwNC的平衡。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c79e/11890282/c40f0c72cb05/pzae178f1.jpg

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