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April 12, 2026npj Digital Medicine0 citationsOpen Access

Predicting bilingual aphasia treatment outcomes using digital twins: a double-blind randomized controlled trial

SKSwathi KiranECErin CarpenterUGUli Grasemann

Key Points

  • The research aims to determine which language to target in bilingual aphasia therapy to enhance recovery outcomes using the BiLex model.
  • Double-blind randomized controlled trial design
  • Inclusion of 48 Spanish–English bilinguals with chronic aphasia
  • Participants received 40 hours of semantic feature-based treatment
  • Comparison of outcomes between model-recommended language and opposite language
  • No significant difference in treated-language naming gains between groups
  • Model-opposite group exhibited significantly greater cross-language generalization
  • Model-assigned group showed advantages in all but the lowest performing subgroups
  • Results aligned with predictions made by the BiLex model

Abstract

Bilingual aphasia rehabilitation faces the challenge of determining which language to target in therapy to maximize recovery across both languages. This double-blind randomized controlled trial (48 Spanish–English bilinguals with chronic aphasia; NCT02916524) evaluated whether the BiLex computational model could predict the optimal language for aphasia therapy. Participants received 40 h of semantic feature-based treatment in either the BiLex-recommended language or the opposite language. Both groups showed similar gains in treated-language naming, with no significant difference in proportion of maximal improvement (Difference (SE) = –0.03 (0.07); t = –0.46; p = 0.65). However, the model-opposite group showed significantly greater cross-language generalization (Difference (SE) = –0.16 (0.07); t = –2.38; p = 0.02), though with higher response variability. Further, when the participants were divided into subgroups according to performance, the model-assigned group had a significant advantage in all but the lowest performing subgroups. All these differences were consistent with BiLex model predictions.

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Cite This Study

Kiran et al. (2026) studied this question.

synapsesocial.com/papers/69db388e4fe01fead37c6ab1https://doi.org/10.1038/s41746-026-02583-9
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