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Research Article

Evolution of word production errors after typicality-based semantic naming treatment in individuals with aphasia

ORCID Icon, , &
Received 21 Jan 2024, Accepted 03 Jul 2024, Published online: 18 Jul 2024
 

ABSTRACT

Background

The Complexity Account for Treatment Efficacy (CATE) has been applied to semantic typicality in aphasia naming therapy, i.e. training atypical items of a category would improve naming of typical untrained-related items. However, most aphasia treatment studies have implemented a binary scoring system to measure response accuracy, which may not thoroughly reveal linguistic mechanisms underlying aphasia recovery.

Aims

The current study investigated the evolution of error patterns following typicality-based Semantic Features Analysis (SFA) treatment in individuals with post-stroke aphasia.

Methods & Procedures

Thirty individuals with chronic aphasia participated in a typicality-based SFA treatment, and ten individuals with chronic aphasia served as controls. The treatment participants and controls completed a naming screener before and after either a treatment period or a no-treatment period, respectively. Responses were coded using an error coding scale and analyzed with mixed-effects models.

Outcomes & Results

Treatment participants demonstrated significant treatment and generalization effects, as captured by significant improvements on the error coding system for both trained and untrained items. However, the group-level analysis did not reveal significant generalization from training atypical items to untrained typical items. Subgroup analyses based on participants’ performance in treatment showed significant gains in naming untrained typical items from training atypical items in responders, but improved naming of untrained atypical items from training typical items in nonresponders.

Conclusions

These findings suggest different linguistic mechanisms underlying aphasia recovery and highlight the importance of investigating treatment and generalization effects using a fine-grained error coding system as a complement to a binary scoring system.

Acknowledgements

We would like to thank the individuals with aphasia who participated in this study. We additionally thank members of the Boston University Aphasia Research Laboratory (now Center for Brain Recovery) for their assistance in data collection and contributions to this project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available on request from the corresponding author, SK. The data are not publicly available due to their containing information that could compromise the privacy of research participants.

Notes

1. Seven of these natural history control patients served as controls before they were enrolled in the treatment group.

Additional information

Funding

This work was supported by National Institute on Deafness and Other Communication Disorders of the National Institutes of Health (USA) under grant [1P50DC012283].

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