Syntactic complexity in translated eHealth discourse of COVID-19: a comparable parallel corpus approach

Abstract

In the pandemic era, the efficient management of COVID-19 by public health authorities is dependent upon the effective dissemination of health-related information. Due to the global nature of COVID-19, translations of healthcare information from the source language to the languages of target users are common. The current study discusses the findings from a comparative corpus analysis of a self-built corpus based on the translated version of eHealth information and the Coronavirus corpus, which contains 12 million words and serves as a reference corpus. Revealing a significant difference between the two corpora, the study shows that the overall sentence complexity of translated texts is significantly lower than non-translated texts even though it deploys longer length of production. The results also show that the translated e-Health information encompasses less coordination structures. In addition, the findings regarding the use of subordination and specific structures are rather mixed and the translated texts appear to be less complicated in the measure of T-units per sentence and verb phrases per T-unit. This study highlights that critical information such as medication adherence must be communicated clearly and understandably to the general public. The findings of the study offer support for the use of plain English in the dissemination material provided by the websites of the leading healthcare public institutions

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