Usage of Multilingual Mobile Translation Applications in Clinical Settings
Notice bibliographique
Résumé
BACKGROUND: Communication between patients and medical staff can be challenging if both parties have different cultural and linguistic backgrounds. Specialized applications can potentially alleviate these problems and significantly contribute to an effective, improved care process when foreign language patients are involved. OBJECTIVE: The objective for this paper was to discuss the experiences gained from a study carried out at the Hannover Medical School regarding the use of a mobile translation application in hospital wards. The conditions for successfully integrating these technologies in the care process are discussed. METHODS: iPads with a preinstalled copy of an exemplary multilingual assistance tool ("xprompt") designed for use in medical care were deployed on 10 wards. Over a period of 6 weeks, approximately 160 employees of the care staff had the opportunity to gather experiences with the devices while putting them to use during their work. Afterwards, the participants were asked to fill out an anonymous, paper-based questionnaire (17 questions) covering the usability of the iPads, translation apps in general, and the exemplary chosen application specifically. For questions requiring a rating, Likert scales were employed. The retained data were entered into an electronic survey system and exported to Microsoft Excel 2007 for further descriptive analysis. RESULTS: Of 160 possible participants, 42 returned the questionnaire and 39 completed the questions concerning the chosen app. The demographic data acquired via the questionnaire (ie, age, professional experience, gender) corresponded to the values for the entire care staff at the Hannover Medical School. Most respondents (35/39, 90%) had no previous experience with an iPad. On a 7-point scale, the participants generally rated mobile translation tools as helpful for communicating with foreign language patients (36/39, 92%; median=5, IQR=2). They were less enthusiastic about xprompt's practical use (36/39, median=4, IQR=2.5), although the app was perceived as easy-to-use (36/39, median=6, IQR=3) and there were no obvious problems with the usability of the device (36/39, median=6, IQR=2). CONCLUSIONS: The discrepancy between the expert ratings for xprompt (collected from the App Store and online) and the opinions of the study's participants can probably be explained by the differing approaches of the two user groups. The experts had clear expectations, whereas, without a more thorough introduction, our study participants perceived using the app as too time consuming in relation to the expected benefit. The introduction of such tools in today's busy care settings should therefore be more carefully planned to heighten acceptance of new tools. Still, the low return rate of the questionnaires only allows for speculations on the data, and further research is necessary. TRIAL REGISTRATION: This study was approved by the local institutional review board (IRB), Trial ID number: 1145-2011.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».