scholarly journals The Effects of Semantic Feature Analysis Treatment on Naming Performance in Korean Individuals with Early Dementia of the Alzheimer’s Type: Using a Familiarity of Nouns Scale

2015 ◽  
Vol 20 (1) ◽  
pp. 34-47 ◽  
Author(s):  
Kyeong Ok Mo ◽  
Jee Eun Sung ◽  
Jee Hyang Jeong
Keyword(s):  
Semantic Feature ◽  
Feature Analysis ◽  
Early Dementia ◽  
Semantic Feature Analysis ◽  
Naming Performance

scholarly journals Semantic Feature Analysis: Further Examination of Outcomes

2015 ◽  
Vol 24 (4) ◽  
Author(s):  
Catharine DeLong ◽  
Christina Nessler ◽  
Sandra Wright ◽  
Julie Wambaugh
Keyword(s):  
Semantic Information ◽  
Semantic Category ◽  
Semantic Content ◽  
Category Membership ◽  
Semantic Feature ◽  
Word Retrieval ◽  
Multiple Baseline ◽  
Feature Analysis ◽  
Semantic Feature Analysis ◽  
Naming Performance

Purpose The purpose of this investigation was to systematically examine outcomes associated with Semantic feature analysis, which is an established treatment for word-retrieval deficits in aphasia. Attributes of the experimental design and stimuli were manipulated to evaluate generalized naming of semantically related and unrelated items. In addition, the study was designed to examine changes in production of semantic information. Method Semantic feature analysis was applied in the context of multiple-baseline designs with 5 persons with chronic aphasia. Experimental items were controlled for semantic category membership, number of naming attempts, and provision of item names. Acquisition, generalization, and maintenance effects were measured in probes of naming performance. Production of semantic information was also measured in response to experimental items and in discourse tasks. Results Treatment was associated with systematic increases in naming of trained items for 4 of the 5 participants. Positive generalization to untrained exemplars of trained categories was found for repeatedly exposed items but not for limited-exposure items. Slight increases in production of semantic content were observed. Conclusion Repeated attempts to name untreated items appeared to play a role in generalization. Provision of the names of untrained items may have enhanced generalized responding for 2 participants.

Acquisition and Generalization Responses in Aphasia Naming Treatment: A Meta-Analysis of Semantic Feature Analysis Outcomes

2019 ◽  
Vol 28 (1S) ◽  
pp. 230-246 ◽  
Author(s):  
Yina M. Quique ◽  
William S. Evans ◽  
Michael Walsh Dickey
Keyword(s):  
Language Impairment ◽  
Meta Analysis ◽  
Treatment Phase ◽  
Demographic Variables ◽  
Semantic Feature ◽  
Feature Analysis ◽  
Statistical Tool ◽  
Number Of Treatment ◽  
Semantic Feature Analysis ◽  
Naming Performance

Purpose This meta-analysis synthesizes results from published studies that used semantic feature analysis (SFA) treatment to improve naming for people with aphasia. It examines how both person- and treatment-related variables affected the likelihood of correct naming responses in individual probe sessions for both acquisition (treated) and generalization (untreated) stimuli. Method The meta-analysis compiled data from 12 studies analyzing a total of 35 participants with aphasia. It used mixed-effects models as a novel statistical tool to examine the effects of 2 sets of variables on naming performance: treatment-related variables, including treatment phase (baseline vs. treatment), dosage (number of treatment sessions), and stimulus type (treated vs. untreated, semantically related vs. unrelated items), and person-specific variables, including degree of language impairment and demographic variables (age, time poststroke). Results Results of the meta-analysis revealed that SFA intervention promoted increased naming accuracy during naming probes when comparing baseline and treatment phases. In addition, increased dosages of SFA were associated with increased naming accuracy, and treatment-related gains were larger for acquisition (treated) than generalization (untreated) stimuli, likewise for related versus unrelated generalization stimuli. Furthermore, a subset of person-specific variables was predictive of SFA-related gains: Language impairment variables were related to treatment-related changes in naming performance, but demographic variables were not. Conclusion These results provide group-level evidence for the efficacy of SFA as well as preliminary estimates of how much naming performance benefit is engendered by varying dosages of SFA. The results also provide promising and previously unobserved evidence of potential person-level predictors of SFA treatment response.

Phonomotor Versus Semantic Feature Analysis Treatment for Anomia in 58 Persons With Aphasia: A Randomized Controlled Trial

2019 ◽  
Vol 62 (12) ◽  
pp. 4464-4482 ◽  
Author(s):  
Diane L. Kendall ◽  
Megan Oelke Moldestad ◽  
Wesley Allen ◽  
Janaki Torrence ◽  
Stephen E. Nadeau
Keyword(s):  
Randomized Controlled Trial ◽  
Response Latency ◽  
Controlled Trial ◽  
Semantic Knowledge ◽  
Semantic Feature ◽  
Feature Analysis ◽  
Group Differences ◽  
Randomized Controlled ◽  
Confrontation Naming ◽  
Semantic Feature Analysis

Purpose The ultimate goal of anomia treatment should be to achieve gains in exemplars trained in the therapy session, as well as generalization to untrained exemplars and contexts. The purpose of this study was to test the efficacy of phonomotor treatment, a treatment focusing on enhancement of phonological sequence knowledge, against semantic feature analysis (SFA), a lexical-semantic therapy that focuses on enhancement of semantic knowledge and is well known and commonly used to treat anomia in aphasia. Method In a between-groups randomized controlled trial, 58 persons with aphasia characterized by anomia and phonological dysfunction were randomized to receive 56–60 hr of intensively delivered treatment over 6 weeks with testing pretreatment, posttreatment, and 3 months posttreatment termination. Results There was no significant between-groups difference on the primary outcome measure (untrained nouns phonologically and semantically unrelated to each treatment) at 3 months posttreatment. Significant within-group immediately posttreatment acquisition effects for confrontation naming and response latency were observed for both groups. Treatment-specific generalization effects for confrontation naming were observed for both groups immediately and 3 months posttreatment; a significant decrease in response latency was observed at both time points for the SFA group only. Finally, significant within-group differences on the Comprehensive Aphasia Test–Disability Questionnaire ( Swinburn, Porter, & Howard, 2004 ) were observed both immediately and 3 months posttreatment for the SFA group, and significant within-group differences on the Functional Outcome Questionnaire ( Glueckauf et al., 2003 ) were found for both treatment groups 3 months posttreatment. Discussion Our results are consistent with those of prior studies that have shown that SFA treatment and phonomotor treatment generalize to untrained words that share features (semantic or phonological sequence, respectively) with the training set. However, they show that there is no significant generalization to untrained words that do not share semantic features or phonological sequence features.

Take Time For Action: Reasoning about Linear Equations

2002 ◽  
Vol 8 (3) ◽  
pp. 146-148
Author(s):  
A.Susan Gay ◽  
Charlotte J. Keith
Keyword(s):  
Linear Equations ◽  
Semantic Feature ◽  
Feature Analysis ◽  
Mathematics Classrooms ◽  
Literacy Strategy ◽  
Semantic Feature Analysis

Have you heard of or used semantic feature analysis? It is a literacy strategy that can help students determine relationships among related vocabulary terms (Cooter and Flynt 1996). In mathematics classrooms, the use of semantic feature analysis is relatively new.

Semantic Models and Translating

Target ◽  
1994 ◽  
Vol 6 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Paul Kussmaul
Keyword(s):  
Word Meaning ◽  
Semantic Feature ◽  
Feature Analysis ◽  
Semantic Features ◽  
Word Meanings ◽  
The Core ◽  
Semantic Models ◽  
Structural Semantics ◽  
Semantic Feature Analysis

Abstract This paper examines the relevance of three semantic models for translation. Structural semantics, more specifically semantic feature analysis, has given rise to the maxim that we should translate "bundles of semantic features". Prototype semantics suggests that word-meanings have cores and fuzzy edges which are influenced by culture. For translation this means that we do not necessarily translate bundles of features but have to decide whether to focus on the core or the fuzzy edges of the meaning of a particular word. Scenesand-frames semantics suggests that word meaning is influenced by context and the situation we are in. Word-meaning is thus not static but dynamic, and it is this dynamism which should govern our decisions as translators.

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