A prospective observational study of machine translation software to overcome the challenge of including ethnic diversity in healthcare research

Journal article


Taylor, RM, Crichton, N, Moult, B and Gibson, F (2015). A prospective observational study of machine translation software to overcome the challenge of including ethnic diversity in healthcare research. Nursing Open. 2 (1), pp. 14-23. https://doi.org/10.1002/nop2.13
AuthorsTaylor, RM, Crichton, N, Moult, B and Gibson, F
Abstract

Aim

This study investigates whether machine translation could help with the challenge of enabling the inclusion of ethnic diversity in healthcare research.
Design

A two phase, prospective observational study.
Methods

Two machine translators, Google Translate and Babylon 9, were tested. Translation of the Strengths and Difficulties Questionnaire (SDQ) from 24 languages into English and translation of an English information sheet into Spanish and Chinese were quality scored. Quality was assessed using the Translation Assessment Quality Tool.
Results

Only six of the 48 translations of the SDQ were rated as acceptable, all from Google Translate. The mean number of acceptably translated sentences was higher (P = 0·001) for Google Translate 17·1 (sd 7·2) than for Babylon 9 11 (sd 7·9). Translation by Google Translate was better for Spanish and Chinese, although no score was in the acceptable range. Machine translation is not currently sufficiently accurate without editing to provide translation of materials for use in healthcare research.

KeywordsCommunication; consent; outcomes; translation
Year2015
JournalNursing Open
Journal citation2 (1), pp. 14-23
PublisherWiley
Digital Object Identifier (DOI)https://doi.org/10.1002/nop2.13
Publication dates
Print29 Jan 2015
Publication process dates
Deposited30 Nov 2017
Accepted29 Dec 2014
Accepted author manuscript
License
File Access Level
Open
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https://openresearch.lsbu.ac.uk/item/87729

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