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Enregistrement W2023571174 · doi:10.1111/j.1365-2929.2007.02751.x

Advanced medical communications: support for international residents

2007· article· en· W2023571174 sur OpenAlexaffabout
Mark Goldszmidt, Claude Kortas, Susan Meehan

Notice bibliographique

RevueMedical Education · 2007
Typearticle
Langueen
DomaineHealth Professions
ThématiqueGlobal Health Workforce Issues
Établissements canadiensLondon Health Sciences Centre
Organismes subventionnairesnon disponible
Mots-clésContext (archaeology)Medical educationVocabularyCommunication skillsPsychologyMedicine

Résumé

récupéré en direct d'OpenAlex

Context and settingDespite the acknowledged importance of communication skills in patient care and education, internationally sponsored residents (ISRs) and international medical graduates (IMGs) arriving in Canada from non-English-speaking countries frequently enter residency without any English communications training within the context of their host culture. Although many have learned English medical vocabulary and developed strong academic English skills through their medical studies, few have had significant communicative English experience in the field of medicine. They have also had little or no exposure to the cultural norms of their new home, and the ‘culture’ of the medical profession within it. Why the idea was necessaryCoping with cultural expectations and language differences in North America has been an ongoing challenge for this group of residents. However, there is a paucity of literature indicating how these needs can be met in a way that is acceptable to the residents, who are often very self-conscious when singled out for special training. The purpose of this pilot study was to assess the feasibility of a programme designed specifically to build, in context, the English-language communication skills of this group. What was doneApproximately 4 months into their residency, new ISRs in the Department of Medicine at a Canadian medical school were required to participate in a pilot ‘English for Medical Purposes’ programme. It was also offered on a voluntary basis to 2 Department of Family Medicine IMGs. The primary instructor for the programme was an English-for-specific-purposes (ESP) specialist. A doctor member of the development team also attended each class to offer medical expertise and to help facilitate scenario-based activities. The 18-hour programme, which took place over 6 academic half-days, focused primarily on doctor−patient and doctor–colleague interactions. Participation was encouraged through clinical standardised patient scenarios and case presentation practice. A strong language and culture focus was built into the programme to meet the unique needs of this resident group. Evaluation of results and impact All 5 of the ISRs and 1 of the IMGs completed an anonymous post-programme feedback form consisting of 7 open and 24 7-point Likert scale questions. Although the 5 ISRs had initially been very reluctant to participate, all the participants indicated that the programme should be offered to all incoming international residents. Despite a low rating of pre-participation interest (3.3, standard deviation [SD] 2.3), the mean rating of the value of the programme was high (6.0, SD = 0.9). In addition, the participants' self-evaluation of their communication skills showed significant improvement: self-assessed mean pre-course skills were rated at 3.8 (SD = 0.4) and post-course skills at 6.2 (SD = 0.8) (P = 0.03, 2-tailed t-test). Written comments were all very positive and included a few requests for the programme content to be expanded. Several participants even expressed interest in repeat participation in the programme. The results of this highly successful pilot show that a targeted communications skills programme can be implemented and can achieve high levels of acceptance by international residents. Next steps will involve further programmatic improvements, as well as using harder end-points to assess improvements in communication skills.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil0,081

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0030,001
Communication savante0,0020,001
Science ouverte0,0010,005
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0240,003

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.

Tête enseignante Opus0,048
Tête enseignante GPT0,556
Écart entre enseignants0,507 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations9
Publié2007
Routes d'admission2
Résumé présentoui

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