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Record W3155998765 · doi:10.2196/21586

Designing an App to Overcome Language Barriers in the Delivery of Emergency Medical Services: Participatory Development Process

2021· article· en· W3155998765 on OpenAlexvenueno aff
Eva Maria Noack, J. Schulze, Frank Müller

Bibliographic record

VenueJMIR mhealth and uhealth · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsnot available
FundersBundesamt für LandwirtschaftBundesministerium für Ernährung und Landwirtschaft
KeywordsProcess (computing)ConversationLanguage barrierUSableComputer scienceParticipatory designHealth careCitizen journalismMedicineWorld Wide WebPsychologyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: In emergencies, language barriers may have dangerous consequences for the patients. There have been some technical approaches to overcome language barriers in medical care but not yet in the prehospital emergency care setting. The use of digital technologies in health care is expanding rapidly. Involving end users at all stages of the development process may help to ensure such technologies are usable and can be implemented. OBJECTIVE: We aimed to develop a digital communication tool that addresses paramedic needs in the specific circumstances of prehospital emergency care and helps paramedics to overcome language barriers when providing care to foreign-language patients. METHODS: We actively engaged paramedics and software designers in an action-oriented, participatory, iterative development process, which included field observations, workshops, background conversations, questionnaires on rescue missions, studying the literature, and preliminary testing in the field. RESULTS: With input from paramedics, we created an app with 600 fixed phrases supporting 18 languages. The app includes medical history-taking questions, phrases asking for consent, and phrases providing specific additional information. Children as patients, as well as their carers and other third parties, can be addressed with appropriate wording. All phrases can be played back audibly or displayed as text. The comprehensive content is grouped into categories and adapted to diverse scenarios, which makes the tool rapidly usable. The app includes a function to document patient responses and the conversation history. For evaluation in a clinical study, the app is run on a smartphone with extra speakers to be of use in noisy environments. The use of prototypes proved valuable to verify that the content, structure, and functions discussed in theory were of value and genuinely needed in practice and that the various device control elements were intuitive. CONCLUSIONS: The nature of the paramedic work environment places specific demands on the communication options used and need for such devices. The active involvement of paramedics in the development process allowed us to understand and subsequently consider their experience-based knowledge. Software designers could understand the paramedics' work environment and consider respective needs in the menu navigation and design principles of the app. We argue that the development of any medical software product should actively involve both end users and developers in all phases of the development process. Providing the users with the opportunity to influence technology development ensures that the result is closer to their needs, which can be seen as crucial for successful implementation and sustainable use. TRIAL REGISTRATION: German Clinical Trials Register DRKS00016719; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00016719. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12913-020-05098-5.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.408
Teacher spread0.358 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations38
Published2021
Admission routes1
Has abstractyes

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