Dataset Information

Typicality-based semantic treatment for anomia results in multiple levels of generalisation.

ABSTRACT: This study investigated the effects of typicality-based semantic feature analysis (SFA) treatment on generalisation across three levels: untrained related items, semantic/phonological processing tasks, and measures of global language function. Using a single-subject design with group-level analyses, 27 persons with aphasia (PWA) received typicality-based SFA to improve their naming of atypical and/or typical exemplars. Progress on trained, untrained, and monitored items was measured weekly. Pre- and post-treatment assessments were administered to evaluate semantic/phonological processing and overall language ability. Ten PWA served as controls. For the treatment participants, the likelihood of naming trained items accurately was significantly higher than for monitored items over time. When features of atypical items were trained, the likelihood of naming untrained typical items accurately was significantly higher than for untrained atypical items over time. Significant gains were observed on semantic/phonological processing tasks and standardised assessments after therapy. Different patterns of near and far transfer were seen across treatment response groups. Performance was also compared between responders and controls. Responders demonstrated significantly more improvement on a semantic processing task than controls, but no other significant change score differences were found between groups. In addition to positive treatment effects, typicality-based SFA naming therapy resulted in generalisation across multiple levels.

SUBMITTER: Gilmore N

PROVIDER: S-EPMC6339853 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:PurposeThis study evaluated the effects of a linguistic characteristic, typicality, and a processing variable, working memory on the abilities of people with aphasia (PWA) and neurologically intact adults to process semantic representations. This was accomplished using a newly developed assessment task, the Category Typicality Test, which was created for the Temple Assessment of Language and Short-Term Memory in Aphasia.MethodA post hoc quasi-experimental design was used. Participants included 27 PWA and 14 neurologically intact adults who completed the picture and word versions of the Category Typicality Test, which required them to determine if two items are in the same category. Memory load was altered by increasing the number of items to be compared, and the typicality of items was altered to increase linguistic complexity.ResultsA four-way mixed analysis of covariance was conducted. There was a significant interaction between working memory load and category typicality with performance accuracy decreasing as working memory load increased and category typicality decreased. There was also a significant interaction for typicality and stimuli with better performance in the picture condition and a significant interaction for working memory and group with lower performance accuracy for PWA. Post hoc pairwise comparisons revealed differences between memory load, typicality, stimuli conditions, and group. PWA also showed greater magnitude of change than neurologically intact adults when comparing high and low working memory load conditions, but not typicality conditions.DiscussionIncreasing working memory load had the most substantial impact on the accuracy of category judgments in PWA, but the interaction between increased working memory load and decreased category typicality of items to be compared resulted in reduced accuracy in both groups. These findings suggest that manipulation of processing and linguistic variables in assessment will provide insight into the nature of linguistic breakdown in aphasia. Supplemental Material https://doi.org/10.23641/asha.14781996.

Dataset Information

Typicality-based semantic treatment for anomia results in multiple levels of generalisation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure