Evaluating the Usefulness of Translation Technologies for Emergency Response Communication: A Scenario-Based Study (Preprint) Article Swipe
YOU?
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· 2018
· Open Access
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· DOI: https://doi.org/10.2196/preprints.11171
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.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.2196/preprints.11171
- OA Status
- gold
- References
- 13
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- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4249598644Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2196/preprints.11171Digital Object Identifier
- Title
-
Evaluating the Usefulness of Translation Technologies for Emergency Response Communication: A Scenario-Based Study (Preprint)Work title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
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2018-05-31Full publication date if available
- Authors
-
Anne M. Turner, Yong Kyung Choi, Kristin Dew, Ming-Tse Tsai, Alyssa Bosold, Esther Wu, Donahue Smith, Hendrika MeischkeList of authors in order
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-
https://doi.org/10.2196/preprints.11171Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.2196/preprints.11171Direct OA link when available
- Concepts
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Usability, Machine translation, Language barrier, Computer science, Language translation, Natural language processing, Human–computer interaction, Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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13Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Technologies | 325 |
| abstract_inverted_index.improvements | 341 |
| abstract_inverted_index.individuals. | 76 |
| abstract_inverted_index.participants | 144, 183, 226, 260, 303 |
| abstract_inverted_index.successfully | 67 |
| abstract_inverted_index.technologies | 116, 350 |
| abstract_inverted_index.communication | 11, 73 |
| abstract_inverted_index.participants) | 107 |
| abstract_inverted_index.participants, | 211, 215 |
| abstract_inverted_index.personnel’s | 284 |
| abstract_inverted_index.satisfactory, | 258 |
| abstract_inverted_index.understanding | 281 |
| abstract_inverted_index.communication. | 120 |
| abstract_inverted_index.communications | 48, 221 |
| abstract_inverted_index.fixed-sentence | 154 |
| abstract_inverted_index.questionnaire. | 181 |
| abstract_inverted_index.scenario-based | 88 |
| abstract_inverted_index.domain-specific | 153, 265 |
| abstract_inverted_index.Chinese-speaking | 141, 209 |
| abstract_inverted_index.English-speaking | 95 |
| abstract_inverted_index.Spanish-speaking | 139, 213 |
| abstract_inverted_index.<title>METHODS</title> | 123 |
| abstract_inverted_index.<title>RESULTS</title> | 193 |
| abstract_inverted_index.<title>OBJECTIVE</title> | 79 |
| abstract_inverted_index.<title>BACKGROUND</title> | 1 |
| abstract_inverted_index.<title>CONCLUSIONS</title> | 324 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.6800000071525574 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.55821358 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |