Division of Physical Medicine and Rehabilitation, Istituti Clinici Scientifici Maugeri IRCCS, Scientific Institute of Veruno, Gattico-Veruno (NO), Italy.
Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet, Huddinge, Sweden.
Phys Ther. 2021 Oct 1;101(10). doi: 10.1093/ptj/pzab180.
The Mini-Balance Evaluation Systems Test (Mini-BESTest) is a balance scale common to clinical practice, but different scoring has been proposed, that is, total score and/or subsections. This study aimed to investigate Mini-BESTest validity by comparing 6 structural models and to establish the best model for discriminating fallers from nonfallers, that is, those who did or did not report at least 2 falls in the 6 months before evaluation.
In this cross-sectional validation study, data from 709 individuals with idiopathic Parkinson disease (Hoehn and Yahr stages 1-3) were analyzed. Individuals were evaluated with the Mini-BESTest, and fall history was recorded. Construct, convergent, and discriminant validity and reliability of the 6 models were analyzed. The ability of the models to adequately identify individuals with or without a history of falls was tested with receiving operating characteristic curves.
Confirmatory factor analysis showed that the unidimensional models and the 4-factor solutions showed the best fit indexes. Conversely, second-order models, which allowed reporting of both total and subsections, did not converge. Most models and factors showed a low convergent validity (average variance extracted values <0.5). Correlations among the anticipatory postural adjustments factor with both the sensory orientation and the dynamic gait factors of multidimensional models were high (r ≥ 0.85). Unidimensional model reliability was good, whereas low values were found in one-half of the subsections. Finally, both unidimensional models showed a large area under the receiving operating characteristic curve (0.81).
The original unidimensional Mini-BESTest model-with a total score of 28-showed the highest validity and reliability and was best at discriminating fallers from nonfallers. Conversely, its 4 subsections should not be reported separately, because they were highly correlated and had low reliability; therefore, they are not actually capable of measuring different aspects of balance.
This study shows that the Mini-BESTest should be used only with the original unidimensional scoring system in people with Parkinson disease.
Mini-Balance Evaluation Systems Test（Mini-BESTest）是一种常用于临床实践的平衡量表，但已提出不同的评分方法，即总分和/或各分项。本研究旨在通过比较 6 种结构模型来研究 Mini-BESTest 的有效性，并为区分跌倒者和非跌倒者建立最佳模型，即那些在评估前 6 个月至少报告 2 次跌倒的人。
在这项横断面验证研究中，分析了 709 名特发性帕金森病患者（Hoehn 和 Yahr 分期 1-3）的数据。对患者进行 Mini-BESTest 评估，并记录跌倒史。分析了 6 种模型的结构、收敛和判别有效性和可靠性。使用接受者操作特征曲线测试模型区分有无跌倒史的能力。
验证性因子分析显示，单维模型和 4 因素解决方案具有最佳的拟合指标。相反，允许报告总分和分项的二阶模型没有收敛。大多数模型和因素的收敛有效性较低（平均方差提取值<0.5）。多维模型中预测性姿势调整因子与感觉定向和动态步态因子之间的相关性较高（r≥0.85）。单维模型的可靠性良好，而一半的分项则可靠性较低。最后，两个单维模型的接收者操作特征曲线下面积均较大（0.81）。
原始的单维 Mini-BESTest 模型（总分 28 分）显示出最高的有效性和可靠性，最能区分跌倒者和非跌倒者。相反，其 4 个分项不应单独报告，因为它们高度相关且可靠性较低；因此，它们实际上并不能测量平衡的不同方面。
本研究表明，在帕金森病患者中，Mini-BESTest 应仅使用原始的单维评分系统。
