NCT02916524

Predicting Rehabilitation Outcomes in Bilingual Aphasia Using Computational Modeling

Double-blind Randomized Trial Investigating the Use of Computational Modeling to Predict Rehabilitation Outcomes in Bilingual Aphasia

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 48 (estimated)
• Sponsor: Boston University Charles River Campus · Academic / Other
• Sex: All
• Age: 18 Years – 85 Years
• Healthy volunteers: Not accepted

Summary

The purpose of this investigation is to implement a computational model that can predict and optimize training and cross-language generalization patterns for bilingual persons with aphasia (BPA). The proposed work will determine the best possible treatment program for each individual patient even before they are rehabilitated. In addition, the computational model allows specification of variables such as age of acquisition, language exposure/proficiency, impairment and their systematic influence on a range of language rehabilitation outcomes.

Conditions

• Aphasia

Interventions

Type	Name	Description
BEHAVIORAL	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.

Timeline

• Start date: 2018-04-20
• Primary completion: 2021-07-31
• Completion: 2023-07-31
• First posted: 2016-09-27
• Last updated: 2021-04-19

Locations

3 sites across 1 country: United States