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The Fluff test: Improved scoring system to account for different degrees of contralesional and ipsilesional personal neglect in brain damaged patients
Neuropsychological Rehabilitation ( IF 2.7 ) Pub Date : 2020-07-29 , DOI: 10.1080/09602011.2020.1797828
Gianna Cocchini 1 , Nicoletta Beschin 2
Affiliation  

ABSTRACT

The Fluff test is a simple test to assess evidence of personal neglect (PN) in brain-damaged patients. While blindfolded, patients are asked to remove targets previously attached to their body and the number of targets detached provides information about possible spatial bias. This test has been widely used for clinical and research purposes. However, the current scoring system presents some limitations, which make difficult to interpret patients’ performance in terms of both contralalesional and ipsilesional PN when they omit targets on the ipsilesional side. Moreover, it does not consider possible confounding variables, such as non-spatial cognitive deficits or lack of compliance that may affect patients’ performance and lead to incorrect diagnosis. The present paper proposes a new scoring method overcoming the limitations mentioned above and it analyses data from a large sample of 243 brain-damaged patients. Findings showed that contralesional PN was significantly more severe, but not more frequent, following right (31%) than left (21%) brain damage. We also found evidence of left ipsilesional PN and cases of potential mis-diagnosis that would have passed unnoticed with the original scoring system. The new scoring method allows to identify different degrees of contralesional and ipsilesional PN and potential confounding variable.



中文翻译:

Fluff 测试:改进的评分系统以解释脑损伤患者不同程度的对侧和同侧个人忽视

摘要

Fluff 测试是一种简单的测试,用于评估脑损伤患者的个人忽视 (PN) 证据。当被蒙住眼睛时,患者被要求移除先前附着在他们身体上的目标,分离的目标数量提供了有关可能的空间偏差的信息。该测试已广泛用于临床和研究目的。然而,当前的评分系统存在一些局限性,当他们忽略同侧的目标时,这使得很难解释患者在对侧和同侧 PN 方面的表现。此外,它没有考虑可能的混杂变量,例如可能影响患者表现并导致错误诊断的非空间认知缺陷或依从性缺乏。本文提出了一种克服上述局限性的新评分方法,并分析了 243 名脑损伤患者的大样本数据。研究结果表明,右侧 (31%) 比左侧 (21%) 脑损伤后对侧 PN 明显更严重,但并不更频繁。我们还发现了左侧同侧 PN 的证据和潜在的误诊病例,这些病例在原始评分系统中会被忽视。新的评分方法允许识别不同程度的对侧和同侧 PN 以及潜在的混杂变量。我们还发现了左侧同侧 PN 的证据和潜在的误诊病例,这些病例在原始评分系统中会被忽视。新的评分方法允许识别不同程度的对侧和同侧 PN 以及潜在的混杂变量。我们还发现了左侧同侧 PN 的证据和潜在的误诊病例,这些病例在原始评分系统中会被忽视。新的评分方法允许识别不同程度的对侧和同侧 PN 以及潜在的混杂变量。

更新日期:2020-07-29
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