Predicting Rehabilitation Outcomes in Bilingual Aphasia Using Computational Modeling
NCT ID: NCT02916524
Last Updated: 2021-04-19
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
48 participants
INTERVENTIONAL
2018-04-20
2023-07-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
TREATMENT
DOUBLE
Study Groups
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Model-based
Semantic Feature Analysis training will be provided in the language that was selected by the computational model.
Semantic Feature Analysis (SFA)
SFA training entails having the speech-language pathologist (SLP) guide the participant through generation of pertinent semantic features for pictured treatment items (e.g., category membership, physical description, location of item in context, action associated with item). Treatment is applied to a set of items in the context of single-subject, multiple baseline designs so that replication of treatment effects could be evaluated within and across participants. Treatment will be administered two times per week until prescribed accuracy levels were met during treatment probes or a maximum number of treatment sessions was completed.
Model-opposite
Semantic Feature Analysis training will be provided in the language opposite to that which was selected by the computational model.
Semantic Feature Analysis (SFA)
SFA training entails having the speech-language pathologist (SLP) guide the participant through generation of pertinent semantic features for pictured treatment items (e.g., category membership, physical description, location of item in context, action associated with item). Treatment is applied to a set of items in the context of single-subject, multiple baseline designs so that replication of treatment effects could be evaluated within and across participants. Treatment will be administered two times per week until prescribed accuracy levels were met during treatment probes or a maximum number of treatment sessions was completed.
Sub-Study: Computational Modeling for Bilingual Dementia and Semantic Decline
This is a sub-study aimed at building a computational model to simulate bilingual dementia and semantic decline.
No interventions assigned to this group
Interventions
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Semantic Feature Analysis (SFA)
SFA training entails having the speech-language pathologist (SLP) guide the participant through generation of pertinent semantic features for pictured treatment items (e.g., category membership, physical description, location of item in context, action associated with item). Treatment is applied to a set of items in the context of single-subject, multiple baseline designs so that replication of treatment effects could be evaluated within and across participants. Treatment will be administered two times per week until prescribed accuracy levels were met during treatment probes or a maximum number of treatment sessions was completed.
Eligibility Criteria
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Inclusion Criteria
* Bilingual: speaking both Spanish and English (or Chinese and English) with any degree of language proficiency prior to stroke
* Aphasia secondary to a left-hemisphere stroke (diagnosed by a neurologist on the basis of clinical CT/MRI imaging or medical reports)
* Aphasia resulting from stroke or dementia
* Naming deficits must be present with concurrent lexical/semantic impairment
* Visual and auditory acuity sufficient for all assessment and treatment procedures
* Ability to understand study and follow study procedures for the entire length of the study
Exclusion Criteria
* Proficient in more than just Spanish and English (or Chinese and English)
* Overt, behaviorally noticeable, attentional limitations that interfere with completing the experimental tasks
* Active medical disease that may compromise participation (e.g., cancer undergoing acute treatment, unstable diabetes, renal or hepatic insufficiency, fluctuating systemic immunological disease such as systemic lupus erythematosis, etc.)
* Currently taking medications that are known to exert significant effects on cognitive processes, such as neuroleptics, steroids, anticholinesterase inhibitors, etc.
* Current drug or alcohol use or dependence that would interfere with adherence to study requirements, in the opinion of the principal investigator
* Inability or unwillingness of individual to give written informed consent
* Diagnosed with mental illness other than active depression
* Neurological condition other than that which resulted in aphasia
18 Years
85 Years
ALL
No
Sponsors
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National Institute on Deafness and Other Communication Disorders (NIDCD)
NIH
Boston University Charles River Campus
OTHER
Responsible Party
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Swathi Kiran
Professor
Principal Investigators
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Swathi Kiran, PhD
Role: PRINCIPAL_INVESTIGATOR
Boston University
Locations
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San Francisco State University
San Francisco, California, United States
Boston University Sargent College
Boston, Massachusetts, United States
Austin Speech Labs
Austin, Texas, United States
Countries
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Central Contacts
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Facility Contacts
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References
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Russell-Meill M, Carpenter E, Marte MJ, Scimeca M, Penaloza C, Kiran S. Measurement of cross-language and cross-domain generalization following semantic feature-based anomia treatment in bilingual aphasia. Neuropsychol Rehabil. 2025 Jun 26:1-27. doi: 10.1080/09602011.2025.2522196. Online ahead of print.
Penaloza C, Dekhtyar M, Scimeca M, Carpenter E, Mukadam N, Kiran S. Predicting treatment outcomes for bilinguals with aphasia using computational modeling: Study protocol for the PROCoM randomised controlled trial. BMJ Open. 2020 Nov 18;10(11):e040495. doi: 10.1136/bmjopen-2020-040495.
Related Links
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Aphasia Research Laboratory website
Other Identifiers
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4492E
Identifier Type: -
Identifier Source: org_study_id
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