ArticleJMIR public health and surveillance2019
Evaluating the Usefulness of Translation Technologies for Emergency Response Communication: A Scenario-Based Study.
Article in JMIR public health and surveillance, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Bridging language gaps in healthcare: a systematic review of the practical implementation of neural machine translation technologies in clinical settings.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- A systematic review of whether the number of linguistic errors in medical interpretation is associated with the use of professional vs ad hoc interpreters.Archives of public health = Archives belges de sante publique · 2024Pooled it
- Leveraging Cultural-Language Translation Apps to Support and Promote Equitable Older Adult Care: A Scoping Review.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2026Review
- MedCOD: Enhancing English-to-Spanish Medical Translation of Large Language Models Using Enriched Chain-of-Dictionary Framework.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2025Article
- Adapting "Listen N Talk": Developing a Personalized Communication App with Culturally and Linguistically Diverse Residents in Aged Care.Clinical interventions in aging · 2025Article
- Artificial intelligence in clinical settings: a systematic review of its role in language translation and interpretation.Annals of translational medicine · 2024Review
- Using Voice-to-Voice Machine Translation to Overcome Language Barriers in Clinical Communication: An Exploratory Study.Journal of general internal medicine · 2024Article
- Using Voice-to-Voice Machine Translation to Overcome Language Barriers in Clinical Communication: An Exploratory Study.Journal of general internal medicine · 2024Article
- Uncovering communication strategies used in language-discordant consultations with people who are migrants: Qualitative interviews with healthcare providers.Health expectations : an international journal of public participation in health care and health policy · 2024Article
- Overcoming Language Barriers in Paramedic Care With an App Designed to Improve Communication With Foreign-Language Patients: Nonrandomized Controlled Pilot Study.JMIR formative research · 2023Article
- Perceptions of Prehospital Care for Patients With Limited English Proficiency Among Emergency Medical Technicians and Paramedics.JAMA network open · 2023Article
- Language Assistance Services in Nonfederally Funded Safety-Net Medical Clinics in the United States.Health equity · 2022Article
- Evaluation of a Language Translation App in an Undergraduate Medical Communication Course: Proof-of-Concept and Usability Study.JMIR mHealth and uHealth · 2021Article
- Care Staff Perspectives on Using Mobile Technology to Support Communication in Long-Term Care: Mixed Methods Study.JMIR nursing · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundIn 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.
objectiveThe 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.
methodsWe 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).
resultsWe 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.
conclusionsTechnologies 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.