Effects of Errorless Learning-based Semantic Feature Analysis Treatment on Naming and Cognitive Abilities for Individuals with Alzheimer’s Disease

Abstract

Objectives: Alzheimer’s Disease (AD) patients characteristically show a decline in various cognitive functions, including memory and language skills. Additionally, naming deficits are evident from the early stages of dementia in AD patients. This study aimed to consider these characteristics of AD patients and develop a semantic feature analysis based on errorless learning. The effect of this naming treatment on the language and cognitive abilities of AD patients was examined, with participants divided into treatment group and control groups. Methods: Ten patients with early to severe AD were divided into a treatment group and a control group. The noun list was individualized for each participant, and to prevent the production of errors, the researcher provided the names and semantic features of the nouns, which the AD patients then learned. Results: The treatment group showed statistically significant improvements in naming trained nouns, semantically related non-treatment nouns, and semantically unrelated non-treatment nouns. The control group did not show statistically significant improvements in overall noun naming. In the treatment group, the performance in the Controlled Oral Word Association Test (COWAT), specifically in naming animals, significantly increased post-treatment compared to pretreatment. In contrast, the control group showed a significant decrease in digit span test performance post-treatment compared to pre-treatment. Conclusion: A semantic feature analysis based on errorless learning was effective in improving naming performance in AD patients. It also had a positive impact on the enhancement and maintenance of performance in language and cognitive tests.