42 Language interpretation and translation in emergency care: A scoping review
Notice bibliographique
Résumé
Abstract Background Families with preferred languages other than English experience poorer communication and care quality in English-speaking emergency settings. While professional interpretation can bridge this gap, uptake is sparse, suggesting the need for improved implementation and more accessible modalities. Objectives We sought to map the existing literature on interpretation/translation in emergency care, with a focus on modalities, barriers/facilitators to implementation, and outcomes used. Design/Methods Utilizing the Joanna Briggs Institute methodology, we conducted a scoping review and searched 8 databases from inception to May 2024 without any language or country restrictions. Primary research articles involving interpretation/translation between English and a non-English language during emergency healthcare encounters were included. Screening and data extraction were completed by two team members. Results were descriptively summarized and barriers/facilitators to implementation were mapped according to the Consolidated Framework for Implementation Research (CFIR). Results Out of 1809 search results, 82 studies were included, of which 12 (15%) were randomized controlled trials. The majority of studies (70/82, 85%) were single centre and 30 (37%) included children. No studies directly asked paediatric patients about their perspectives. Professional telephonic interpretation was the most commonly studied modality (50/82, 61%). Only four studies (4.9%) examined websites/apps and only one study (1.2%) examined simultaneous interpretation. Mapped to the CFIR, barriers and facilitators primarily centered around information technology infrastructure, resources, and access to knowledge in the local healthcare environment, as well as the perceptions and motivations of healthcare workers and patients. 16 (20%) studies examined healthcare utilization outcomes and 22 (27%) examined communication/interpretation accuracy. Amongst implementation outcomes, only adoption (58/82, 71%) and acceptability (19/82, 23%) were consistently examined (n≥10 studies). Conclusion Interpretation/translation in emergency care has mostly been examined through single centre studies, with few randomized trials and paediatric studies. Importantly, the experience of children themselves has yet to be explored. Information technology infrastructure and resources were some of the most commonly cited barriers and facilitators to language interpretation/translation, highlighting the need to expand testing and implementation of novel modalities. Future studies should consider the unique experiences and needs of both children and their caregivers.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,066 | 0,212 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,007 | 0,008 |
| Bibliométrie | 0,026 | 0,027 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,009 | 0,009 |
| Science ouverte | 0,003 | 0,007 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».