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Evaluating the Usefulness of Translation Technologies for Emergency Response Communication: A Scenario-Based Study
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Abstract:
BACKGROUND: In the United States, language barriers pose challenges to communication in emergency response and impact emergency care delivery and quality for individuals who are limited English proficient (LEP). There is a growing interest among Emergency Medical Services (EMS) personnel in using automated translation tools to improve communications with LEP individuals in the field. However, little is known about whether automated translation software can be used successfully in EMS settings to improve communication with LEP individuals. OBJECTIVE: The objective of this work is to use scenario-based methods with EMS providers and nonnative English-speaking users who identified themselves as LEP (henceforth referred to as LEP participants) to evaluate the potential of two automated translation technologies in improving emergency communication. METHODS: We developed mock emergency scenarios and enacted them in simulation sessions with EMS personnel and Spanish-speaking and Chinese-speaking (Mandarin) LEP participants using two automated language translation tools: an EMS domain-specific fixed-sentence translation tool (QuickSpeak) and a statistical machine translation tool (Google Translate). At the end of the sessions, we gathered feedback from both groups through a postsession questionnaire. EMS participants also completed the System Usability Scale (SUS). RESULTS: We conducted a total of 5 group sessions (3 Chinese and 2 Spanish) with 12 Chinese-speaking LEP participants, 14 Spanish-speaking LEP participants, and 17 EMS personnel. Overall, communications between EMS and LEP participants remained limited, even with the use of the two translation tools. QuickSpeak had higher mean SUS scores than Google Translate (65.3 vs 48.4; P=.04). Although both tools were deemed less than satisfactory, LEP participants showed preference toward the domain-specific system with fixed questions (QuickSpeak) over the free-text translation tool (Google Translate) in terms of understanding the EMS personnel’s questions (Chinese 11/12, 92% vs 3/12, 25%; Spanish 12/14, 86% vs 4/14, 29%). While both EMS and LEP participants appreciated the flexibility of the free-text tool, multiple translation errors and difficulty responding to questions limited its usefulness. CONCLUSIONS: Technologies are emerging that have the potential to assist with language translation in emergency response; however, improvements in accuracy and usability are needed before these technologies can be used safely in the field.
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Original Paper
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URL: https://doi.org/10.2196/11171
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6369422/
http://www.ncbi.nlm.nih.gov/pubmed/30688652
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Communication in virtual world spaces; an exploration of the layers and resources employed in a multimodal, informal language learning experience.
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Turner, Anne. - : University of Sheffield, 2018. : School of Education (Sheffield), 2018
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PHAST: A Collaborative Machine Translation and Post-Editing Tool for Public Health
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A Conjoint Analysis Framework for Evaluating User Preferences in Machine Translation
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Exploring Local Public Health Workflow in the Context of Automated Translation Technologies
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Local Health Department Translation Processes: Potential of Machine Translation Technologies to Help Meet Needs
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Using Crowdsourcing Technology for Testing Multilingual Public Health Promotion Materials
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Application of statistical machine translation to public health information: a feasibility study
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"The key-stone of the arch": Coleridge's metaphor of joining and some of its consequences
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