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Record W3027973683 · doi:10.1080/02687038.2020.1763908

Naming gains and within-intervention progression following semantic feature analysis (SFA) and phonological components analysis (PCA) in adults with chronic post-stroke aphasia

2020· article· en· W3027973683 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAphasiology · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalCentre for Research on Brain Language and MusicMcGill University
FundersFonds de Recherche du Québec - Santé
KeywordsAphasiaPsychologyGeneralizationContext (archaeology)Semantic featureCognitive psychologyStroke (engine)Psychological interventionIntervention (counseling)Natural language processingComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

Background: Up to 60% of people with aphasia experience persistent word-finding difficulties into the chronic stage, starting six months after the stroke. Semantic Feature Analysis (SFA) and Phonological Components Analysis (PCA) are two common word-finding interventions that use the generation of semantic features for SFA (e.g. category) and phonological features for PCA (e.g. first sound) to improve naming. Despite inconsistent support for the generalization to untreated items, studies have shown improvements on probe word naming for treated items. However, research concerning within-intervention effects and generalization to alternative contexts has been limited.Aim: This study investigated the effect of treatment for SFA and PCA probe word naming as well as their within-intervention effects in four individuals with chronic post-stroke aphasia.Methods & Procedures: Baseline and follow-up measures included standardized assessments and image naming tasks. The image naming task was used to generate three lists: an SFA treated list, a PCA treated list, and an untreated list. One SFA session and one PCA session per week were then provided concurrently to each participant for a period of six weeks.Outcomes & Results: While only one participant experienced significant gains on treated probe word naming, these gains were maintained four weeks after the intervention. Exploratory results suggested that effects could transfer to two types of generalization items: different pictures of the same items and pictures of items shown in a natural context. Furthermore, while generalization to untreated items did not reach significance for any participant, some generalization of gains to standardized assessments was observed. Although rarely equivalent for SFA and PCA interventions, all participants also experienced some degree of within-intervention improvement over the progression of sessions. These improvements included a reduction in the number of forced choices required for feature generation and/or a reduction in the number of words never named during intervention sessions.Conclusion: The results support additional avenues of investigation for SFA and PCA therapies for individuals with post-stroke aphasia, namely within intervention effects and the potential for generalization to different contexts.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.293
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it