Multilevel factors predict treatment response following semantic feature-based intervention in bilingual aphasia
Open accessAbstract
Semantic feature-based treatments (SFTs) are effective rehabilitation strategies for word retrieval deficits in bilinguals with aphasia (BWA). However, few studies have prospectively evaluated the effects of key parameters of these interventions on treatment outcomes. This study examined the influence of intervention-level (i.e., treatment language and treatment sessions), individual-level (baseline naming severity and age), and stimulus-level (i.e., lexical frequency, phonological length, and phonological neighborhood density) factors on naming improvement in a treated and untreated language for 34 Spanish–English BWA who completed 40 hours of SFT. Results revealed significant improvement over time in both languages. In the treated language, individuals who received therapy in their L1 improved more. Additionally, higher pre-treatment naming scores predicted greater response to treatment. Finally, a frequency effect on baseline naming accuracy and phonological effects on accuracy over time were associated with differential treatment gains. These findings indicate that multilevel factors are influential predictors of bilingual treatment outcomes.
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Other studies focusing solely on bilingual persons with aphasia have reported conflicting findings regarding the influence of aphasia severity in the treated and untreated languages on treated language improvement and cross-language generalization.
“However, other studies focusing solely on bPWA have reported conflicting findings regarding the influence of aphasia severity in the treated and untreated languages on TLI and CLG7,10,29 underscoring the need for further research to clarify the contribution of these factors to treatment outcomes.”
From Machine Learning Predictions of Recovery in Bilingual Poststroke Aphasia: Aligning Insights With Clinical Evidence (2025) · cites this paper as [7]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredIn semantic feature therapy (SFT), greater language system integrity may facilitate the spread of activation to related semantic nodes, promoting generalization to untreated items and cross-language transfer.
“In SFT, greater language system integrity may facilitate the spread of activation to related semantic nodes, promoting generalization to untreated items and cross-language transfer7,11.”
From Machine Learning Predictions of Recovery in Bilingual Poststroke Aphasia: Aligning Insights With Clinical Evidence (2025) · cites this paper as [7]
The Treatment type section proposes spreading activation as a mechanism for cross-language generalization after SFT. Outcomes in the untreated language reports greater generalization among participants with better baseline naming performance. But the Items section says this study did not analyze semantically related untreated items, so it does not establish spread to those items or semantic nodes; the observed cross-language gains concerned translations of trained items, not distinct untreated words. (LLM, conf=0.88)
Experimental — accuracy not yet measuredVarious approaches, including cognitive-based, cognate-based, and semantic-feature-based treatments, have shown efficacy in producing treated language improvement.
“Various approaches, including cognitive-based4, cognate-based4,5, and semantic-featured-based treatments (SFT)6–11 have shown efficacy in producing treated language improvement (TLI).”
From Machine Learning Predictions of Recovery in Bilingual Poststroke Aphasia: Aligning Insights With Clinical Evidence (2025) · cites this paper as [7]
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Marte, M. J., Carpenter, E., Scimeca, M., Russell-Meill, M., Peñaloza, C., Grasemann, U., Miikkulainen, R., & Kiran, S. (2025) · Stroke · doi:10.1161/strokeaha.124.047867 · Cited by 9 · see citing works
“Although aligning with research in monolingual 11,14,15,20,21 and bilingual aphasia, 7,10,29 our findings diverge from the results of a recent meta-analysis.”
InfluentialSelf-citation
- Authors
- Scimeca, M., Peñaloza, C., & Kiran, S.
- Affiliations
- Boston University (US)
- Institut d'Investigació Biomédica de Bellvitge (ES)
- Corresponding author
- Scimeca, Michael
- Venue
- Bilingualism: Language and Cognition
- Publisher
- Cambridge University Press (CUP)
- Published
- 2023-08-22
- Volume
- 27
- Issue
- 2
- Pages
- 246-262
- ISSN
- 1366-7289 (ISSN-L)
- 1469-1841
- PMC
- PMC10993298
- OpenAlex
- W4386073747
- Cited by
- 11
- References
- 84
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 2
- FWCI
- 1.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Bilingualism Language and Cognition (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OpenBU (Boston University) (publishedVersion, cc-by)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Deafness and Other Communication Disorders (U01 DC014922)
- Ministerio de Ciencia e Innovación (IJC2018-037818)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
- Keywords
- bilingual aphasia, word retrieval, naming, Spanish-English bilinguals, word frequency, phonological neighborhood density, predictors of treatment response, multilevel factors, aphasia rehabilitation
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