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The Link between Syntactic Complexity and Stuttering-Like Disfluencies in French Speaking Adults

Title: The Link between Syntactic Complexity and Stuttering-Like Disfluencies in French Speaking Adults
Language: English
Authors: Alice Le Dévic; Sascha Diwersy; Ivana Didirková (ORCID 0000-0001-8107-2361)
Source: International Journal of Language & Communication Disorders. 2026 61(2).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 11
Publication Date: 2026
Document Type: Journal Articles; Reports - Research
Descriptors: Stuttering; Syntax; Correlation; Adults; French; Sentences; Speech Impairments; Foreign Countries
Geographic Terms: France
DOI: 10.1111/1460-6984.70218
ISSN: 1368-2822; 1460-6984
Abstract: Background: Stuttering is a neurodevelopmental disorder characterized by speech disfluencies. While studies have shown a link between syntactic complexity and stuttering in children, its role in adults who stutter (AWS) remains unclear. This study investigates whether increased syntactic complexity correlates with stuttering-like disfluencies (SLDs) in AWS and evaluates three syntactic complexity indices. Methods: Participants included 24 French-speaking adults (12 AWS, 12 controls), matched for age, gender, and education. Participants completed a sentence description task using sentences of varying syntactic complexity. Syntactic complexity was quantified using three measures: Mean Length of Utterance (MLU), Index of Syntactic Complexity (ISC), and Index of Productive Syntax (IPSyn). Disfluencies were categorized as SLDs or other disfluencies (ODs). Statistical analyses examined the relationship between syntactic complexity and disfluencies across participant groups. Results: AWS produced significantly more SLDs than controls across all levels of syntactic complexity. The number of disfluencies increased with syntactic complexity in AWS but not in controls. MLU was the most sensitive index for predicting disfluencies. Severe stutterers exhibited higher disfluency rates compared to mild and moderate stutterers. Conclusion: Increased syntactic complexity exacerbates stuttering in AWS. MLU, a measure of sentence length, proved most effective for explaining disfluency rates, suggesting its clinical utility. Findings support the demands and capacities model, indicating that reducing syntactic demands may alleviate stuttering.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1500585
Database: ERIC