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

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 40hofsemanticfeature-basedtreatmentineitherthe BiLex-recommendedlanguageortheopposite 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.