The role of language familiarity in bilingual stuttering assessment

Abstract

The aim of this study was to evaluate the ability of English-speaking speech-language pathologists (SLPs) to evaluate stuttering behaviour in two Spanish–English bilingual adults who stutter (AWS1 and AWS2). The English-speaking SLPs were asked to judge the frequency, severity, type, duration, and physical concomitants of stuttering in both languages of the two AWS. The combined results from the English-speaking SLPs were then compared to the judgements of three Spanish–English bilingual SLPs. Results indicated that English-speaking SLPs (1) judged stuttering frequency to be greater in Spanish than English for AWS1, and equal in Spanish and English for AWS2, (2) were more accurate at evaluating individual moments of stuttering for the English samples compared to the Spanish samples, (3) identified fewer and less severe stuttering behaviours than the bilingual SLPs in both languages, and (4) were accurate judges of overall stuttering severity in both languages. The results correspond to past research examining the accuracy of stuttering evaluations in unfamiliar languages. Possible explanations for the findings, clinical implications, and future research directions are discussed.

• Assessment
• bilingual
• language
• stuttering

Acknowledgements

The authors would like to acknowledge the bilingual SLP judges – Lucia Habanec, Eliza Hintze, and Chris Fidler – for their contributions to this study. The authors also thank Dr Maria Diana Gonzales for her input.

Notes

¹In the literature, the terms “L1” and “L2” are typically used to refer to order of acquisition, in cases where the languages of bilingual speakers are developed successively (as opposed to simultaneously) (Owens, 2005). Depending on the language history of a bilingual speaker, order of acquisition may or may not correspond to level of proficiency (Owens, 2005). Within the current study, “L1” and “L2” refer to both order of acquisition and level of proficiency (i.e. L1 is the more proficient language) of the AWS speakers.