Communication in healthcare contexts: Multilingual technological resources to improve the communicative effectiveness of the Informed Consent
DOI:
https://doi.org/10.5007/2175-7968.2024.e95247Keywords:
health communication, writing and translation in clinical contexts, language technologies, informed consent, exploitation of multilingual corporaAbstract
Scientific advances and the complexity of the sociological context in which medicine is practised in an increasingly globalised and interconnected world raise new ethical and legal questions about the rights and obligations of patients, health professionals and public health care services. Despite the significant and undeniable progress brought about by the paradigm shift in the doctor-patient relationship and the great development of medical law and bioethics in recent years, patients continue to encounter serious linguistic and cultural obstacles to exercising their right to information and decision-making in relation to their health. In this paper we present part of the results of the HIPOCRATES research project of the Spanish GENTT group, aimed at humanising health care by improving doctor-patient communication in multilingual environments. Specifically, we will focus on the advances made in the textual analysis of the Informed Consent (IC), a medical genre of great relevance in clinical translation and writing due to its ethical and legal implications. Its lexical-syntactic complexity and the lack of standardised patterns in its writing hinder its comprehensibility and makes it difficult to identify the rhetorical sequences in which the communicative and legal functions of this genre are embodied. We present a textual analysis tool (ProText GENTT), which uses machine learning to exploit corpora with traditional techniques and artificial intelligence and with which we have analysed a multilingual (Spanish, Catalan and English) corpus of IC texts compiled by our research group (GENTT_Corpus). This analysis has allowed us to identify the linguistic-textual and rhetorical elements that hinder comprehension. From these results, our team is currently working on proposing optimized models with different levels of complexity both in printed and digital formats (e-consent).
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