Assessing Physicians and other Healthcare Professionals' Awareness of Language Resources and the Feasibility of Setting up a Volunteer Second Language Database at a Family Health Team and Outpatient Clinic
Notice bibliographique
Résumé
Objectives: 1) To assess the awareness of healthcare professionals in resources available to assist patients encounters challenged by language barriers, 2) To explore the feasibility of implementing a voluntary Second Language Database (SLD) comprising of the outpatient clinic’s very own physicians and healthcare professionals to assist with patient encounters facing language barriers. Methods: This was a feasibility study (cross-sectional design), taking place at the Stonechurch Family Health Centre (SFHC), which is a family health team (FHT) located in Hamilton, Ontario. SFHC has a patient population of over 17,000 patients. All personnel at the SFHC were invited to complete the survey from December 2010 to March 2011. Those surveyed included staff physicians, residents, allied healthcare professionals and administrative staff. The outcome measures included: participant demographics, frequency and percentages of patients encounters with language barriers, healthcare professionals’ awareness of available interpretive resources, ability of the participant to communicate in additional languages, participants’ willingness to enlist for a SLD to provide interpretive assistance during patient encounters. Results: Of the 100 participants invited to take part in the survey, 67 completed it (67% response rate). Of the physicians who completed the survey, 94.6% reported having encountered language barriers during patient encounter within the past 12 months. Additionally, 71.1% of physicians surveyed were unaware of any available resources. The majority of physicians (86.8%) thought a SLD would be helpful, and 66% of doctors able to speak a second language were willing to take part in the SLD to assist colleagues in linguistic encounters. All of the surveyed International Medical Graduates/Doctors (IMGs/IMDs) (N=6), knew a second language, with 4 being fluent in additional languages. All of the surveyed IMG’s were willing to volunteer for the SLD. Conclusions: To our knowledge, this is the first study to specifically explore the physicians’ ability and will ingness to volunteer and assist colleagues in linguistic encounters. Physicians were largely unaware of the available resources to overcome patient encounters with language barriers. Given the frequency of healthcare professionals possessing a second language and their willingness to take part in a SLD at outpatient clinics and FHT settings, this may indeed be a feasible proposal to address patient linguistic barriers. IMGs/ IMDs tend to possess multiple languages and may have had previous experience interacting with patients in languages other than English. This, along with their willingness to assist colleagues during such patient encounters enables them to serve as a vital resource for Canadians with language barriers.
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 | 0,017 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».