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
Authors | Taylor, RM, Crichton, N, Moult, B and Gibson, F |
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Abstract | Aim This study investigates whether machine translation could help with the challenge of enabling the inclusion of ethnic diversity in healthcare research. A two phase, prospective observational study. 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. 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. |
Keywords | Communication; consent; outcomes; translation |
Year | 2015 |
Journal | Nursing Open |
Journal citation | 2 (1), pp. 14-23 |
Publisher | Wiley |
Digital Object Identifier (DOI) | https://doi.org/10.1002/nop2.13 |
Publication dates | |
29 Jan 2015 | |
Publication process dates | |
Deposited | 30 Nov 2017 |
Accepted | 29 Dec 2014 |
Accepted author manuscript | License File Access Level Open |
https://openresearch.lsbu.ac.uk/item/87729
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Accepted author manuscript
A prospective observational study of machine translation software to overcome the challenge of including ethnic diversity in healthcare research.pdf | ||
License: CC BY 4.0 | ||
File access level: Open |
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