How fluent? Part B. Underlying contributors to continuous measures of fluency in aphasia
How fluent? Part B. Underlying contributors to continuous measures of fluency in aphasia
复制标题
有多流利？
DOI：
10.1080/02687038.2020.1712586
复制
发表时间：
2020
期刊：
影响因子：
2
通讯作者：
Sharice Clough
中科院分区：
文献类型：
--
作者：
J. Gordon;Sharice Clough
摘要背景虽然失语症（PwA）患者通常被分为流利或不流利，但人们一致认为流利性不是一个全有或全无的结构，因此使用连续变量作为量化流利性的一种方法，如多维评级量表、语速和话语长度。虽然这些措施经常被用于研究，他们提供的基本流畅性缺陷的信息很少。目的本研究的目的是确定如何以及常用的连续措施的流畅性捕获变化的自发语音变量在词汇，语法和语音生产水平。方法与步骤从失语症数据库中选取254名英语PwA的语音样本，分析四个连续的流畅性指标的分布：WAB-R流畅性量表、话语长度、回溯和语速。线性回归被用来确定自发言语预测有助于每个流畅性的结果测量。结果与结果所有的结果指标反映了多个潜在维度的影响，尽管预测因素各不相同。的WAB-R流畅性量表，语音速率，和追溯的影响，语法能力，词汇检索和语音生产的措施，而话语长度的影响，只有语法能力和词汇检索的措施。WAB-R流畅性的最强预测因素是失语症的严重程度，而所有其他流畅性代理措施的最强预测因素是语法复杂性。结论：连续测量允许各种方式来客观地量化语言流畅性，然而，它们反映了流畅性的表面表现，可能会受到多种潜在缺陷的影响。此外，不同的措施，这可能会降低流畅性诊断的可靠性的缺陷不同。在个体水平上捕捉这些差异对于准确诊断和适当的靶向治疗至关重要。
ABSTRACT Background While persons with aphasia (PwA) are often dichotomised as fluent or nonfluent, agreement that fluency is not an all-or-nothing construct has led to the use of continuous variables as a way to quantify fluency, such as multi-dimensional rating scales, speech rate, and utterance length. Though these measures are often used in research, they provide little information about the underlying fluency deficit. Aim The aim of the study was to identify how well commonly used continuous measures of fluency capture variability in spontaneous speech variables at lexical, grammatical, and speech production levels. Methods & Procedures Speech samples of 254 English-speaking PwA from the AphasiaBank database were analyzed to examine the distributions of four continuous measures of fluency: the WAB-R fluency scale, utterance length, retracing, and speech rate. Linear regression was used to identify spontaneous speech predictors contributing to each fluency outcome measure. Outcomes & Results All the outcome measures reflected the influence of multiple underlying dimensions, although the predictors varied. The WAB-R fluency scale, speech rate, and retracing were influenced by measures of grammatical competence, lexical retrieval, and speech production, whereas utterance length was influenced only by measures of grammatical competence and lexical retrieval. The strongest predictor of WAB-R fluency was aphasia severity, whereas the strongest predictor for all other fluency proxy measures was grammatical complexity. Conclusions Continuous measures allow a variety of ways to objectively quantify speech fluency; however, they reflect superficial manifestations of fluency that may be affected by multiple underlying deficits. Furthermore, the deficits underlying different measures vary, which may reduce the reliability of fluency diagnoses. Capturing these differences at the individual level is critical to accurate diagnosis and appropriately targeted therapy.
影响因子：
14.5
作者：
Fridriksson, Julius;Guo, Dazhou;Rorden, Chris
通讯作者：
Rorden, Chris
影响因子：
14.5
作者：
Wilson, Stephen M.;Henry, Maya L.;Gorno-Tempini, Maria Luisa
通讯作者：
Gorno-Tempini, Maria Luisa
影响因子：
14.5
作者：
Fridriksson, Julius;Hubbard, H. Isabel;Rorden, Chris
通讯作者：
Rorden, Chris