Semantic and Phonological Encoding in Adults Who Stutter: Silent Responses to Pictorial Stimuli.

Saved in:

Bibliographic Details
Title:	Semantic and Phonological Encoding in Adults Who Stutter: Silent Responses to Pictorial Stimuli.
Authors:	Vincent, Irena¹ irena.vincent@cortland.edu
Source:	Journal of Speech, Language & Hearing Research. Sep2017, Vol. 60 Issue 9, p2537-2550. 14p. 4 Charts.
Subject Terms:	Phonological encoding, Language planning, *Stuttering, Stutterers, Pictures, Semantics research, Stimulus & response (Biology), Phoneme (Linguistics), Onomasiology, Research funding, Semantics, Data analysis software, Descriptive statistics, One-way analysis of variance
Abstract:	Purpose: Research on language planning in adult stuttering is relatively sparse and offers diverging arguments about a potential causative relationship between semantic and phonological encoding and fluency breakdowns. This study further investigated semantic and phonological encoding efficiency in adults who stutter (AWS) by means of silent category and phoneme identification, respectively. Method: Fifteen AWS and 15 age- and sex-matched adults who do not stutter (ANS) participated. The groups were compared on the basis of the accuracy and speed of superordinate category (animal vs. object) and initial phoneme (vowel vs. consonant) decisions, which were indicated manually during silent viewing of pictorial stimuli. Movement execution latency was accounted for, and no other cognitive, linguistic, or motor demands were posed on participants' responses. Therefore, category identification accuracy and speed were considered indirect measures of semantic encoding efficiency and phoneme identification accuracy and speed of phonological encoding efficiency. Results: For category decisions, AWS were slower but not less accurate than ANS, with objects eliciting more errors and slower responses than animals in both groups. For phoneme decisions, the groups did not differ in accuracy, with consonant errors outnumbering vowel errors in both groups, and AWS were slower than ANS in consonant but not vowel identification, with consonant response time lagging behind vowel response time in AWS only. Conclusions: AWS were less efficient than ANS in semantic encoding, and they might harbor a consonantspecific phonological encoding weakness. Future independent studies are warranted to discover if these positive findings are replicable and a marker for persistent stuttering. [ABSTRACT FROM AUTHOR]
	Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database:	Education Research Complete

Description
Abstract:	Purpose: Research on language planning in adult stuttering is relatively sparse and offers diverging arguments about a potential causative relationship between semantic and phonological encoding and fluency breakdowns. This study further investigated semantic and phonological encoding efficiency in adults who stutter (AWS) by means of silent category and phoneme identification, respectively. Method: Fifteen AWS and 15 age- and sex-matched adults who do not stutter (ANS) participated. The groups were compared on the basis of the accuracy and speed of superordinate category (animal vs. object) and initial phoneme (vowel vs. consonant) decisions, which were indicated manually during silent viewing of pictorial stimuli. Movement execution latency was accounted for, and no other cognitive, linguistic, or motor demands were posed on participants' responses. Therefore, category identification accuracy and speed were considered indirect measures of semantic encoding efficiency and phoneme identification accuracy and speed of phonological encoding efficiency. Results: For category decisions, AWS were slower but not less accurate than ANS, with objects eliciting more errors and slower responses than animals in both groups. For phoneme decisions, the groups did not differ in accuracy, with consonant errors outnumbering vowel errors in both groups, and AWS were slower than ANS in consonant but not vowel identification, with consonant response time lagging behind vowel response time in AWS only. Conclusions: AWS were less efficient than ANS in semantic encoding, and they might harbor a consonantspecific phonological encoding weakness. Future independent studies are warranted to discover if these positive findings are replicable and a marker for persistent stuttering. [ABSTRACT FROM AUTHOR]
ISSN:	10924388
DOI:	10.1044/2017_JSLHR-S-16-0323