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We are addressing this need in ongoing work.Īcademy of Aphasia 56th Annual Meeting, Montreal, Canada, 21 Oct - 23 Oct, 2018. These findings suggest a need for a more reliable and objective assessment of the underlying components of fluency in aphasia to improve the reliability of aphasia classification and provide more specific information regarding treatment targets. However, the scale may not adequately capture the underlying deficits that give rise to these judgments, such as shorter utterances and reduced verb use. word-finding, content, grammaticality, and effort). To its detriment, the WAB-R fluency scale forces the clinician to choose the best-fitting description based on a number of subjective judgements (e.g. In addition, clinician classifications paid more attention to the lexical composition of aphasic utterances. This seems to be particularly true in detecting nonfluent behaviors, such as speaking at a slower rate and using shorter utterances. Our analysis suggests that clinicians are sensitive to a variety of differences in the spontaneous speech of PwA that the WAB-R fluency scale does not capture. Note that all of the spontaneous speech measures shown in Figure 1 significantly differentiated fluent and nonfluent groups, whether using WAB classifications or clinician judgements. Relative to PwA classified as nonfluent by both WAB and clinicians (n=87), the mismatching PwA produced relatively more verbs and prepositions (p<.05 see Figure 1). Twelve PwA were classified as nonfluent by WAB-R but perceived as fluent by clinicians. These comparisons are illustrated in Figure 1.
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Compared to PwA with matching fluent classifications (n=126), these mismatching cases spoke more slowly, had shorter utterances, and produced relatively fewer prepositions, verbs, and pronouns, but more nouns (all ps<.01). Twenty-four PwA were designated as fluent by WAB-R, but nonfluent by clinicians. WAB fluency scores and all spontaneous speech measures were transformed to z-scores to facilitate comparisons.Īgreement on fluency category was 86% overall, but was considerably higher for participants classified as fluent (91%) than nonfluent (78%) by WAB-R rating. In addition, all had Cinderella story samples, from which we generated spontaneous speech measures. Participants included 249 unique PwA in the AphasiaBank database (MacWhinney, Fromm, Forbes, & Holland, 2011) who had both fluency scale scores from the Western Aphasia Battery-Revised (WAB-R, Kertesz, 2006) and fluency classifications by clinicians, allowing comparison of these two measures. To investigate this, we examined the consistency of fluency classifications, and the spontaneous speech characteristics contributing to those classifications. We propose that the multi-dimensional nature of fluency is a major contributor to its lack of reliability. However, only half of the PwA were rated as fluent or nonfluent by a consensus of at least two‐thirds of the clinicians. Gordon (1998) found that practicing speech‐language pathologists relied primarily on reduced grammaticality, articulatory effort, and word-finding difficulties when rating the fluency of speech samples from 10 participants with aphasia (PwA). Even categorizing aphasia dichotomously by the fluency of language output is not very reliable. The diagnosis of aphasia syndromes has been plagued since its earliest days by variable terminology and a lack of agreement on which dimensions yield the greatest diagnostic accuracy and clinical utility. University of Iowa, Communication Science and Disorders, United States