Domain adaptation remains a major challenge for machine translation, par-ticularly in institutional communica-tion. This paper presents the MULTI-TRAD project , which develops English–Spanish parallel corpora for the Third Social Sector communication. The project integrates three comple-mentary objectives: (i) the compilation of a domain-specific parallel corpus, (ii) the analysis of linguistic variation across human translation (HT), ma-chine translation (MT), and post-edited (PE) texts using Multidimensional Analysis (Biber, 1988), and (iii) the development of a domain-adapted neu-ral machine translation system. In par-ticular, the project investigates how dif-ferent translation processes give rise to distinct functional profiles, related to phenomena such as translationese and post-editese. This paper presents the project design and initial progress.

Clear communication between patients and healthcare providers is crucial, particularly in informed consent forms (ICFs), which are often written in complex, technical language. This paper explores the effectiveness of generative artificial intelligence (AI) for simplifying ICFs into Plain Language (PL), aiming to enhance patient comprehension and informed decision-making. Using a corpus of 100 cancer-related ICFs, two distinct prompt engineering strategies (Simple AI Edit and Complex AI Edit) were evaluated through readability metrics: Flesch Reading Ease, Gunning Fog Index, and SMOG Index. Statistical analyses revealed statistically significant improvements in readability for AI-simplified texts compared to original documents. Interestingly, the Simple AI Edit strategy consistently outperformed the Complex AI Edit across all metrics. These findings suggest that minimalistic prompt strategies may be optimal, democratizing AI-driven text simplification in healthcare by requiring less expertise and resources. The study underscores the potential for AI to significantly improve patient-provider communication, highlighting future research directions for qualitative assessments and multilingual applications.