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Enregistrement W4411779196 · doi:10.22605/rrh9355

A rural practice affinity model: recognizing the role of emergency medicine competency

2025· article· en· W4411779196 sur OpenAlexafffundabout
Eliseo Orrantia, Theresa J. B. Kline, Lindsay Nutbrown, Erin K. Cameron, Margaret Cousins

Notice bibliographique

RevueRural and Remote Health · 2025
Typearticle
Langueen
DomaineHealth Professions
ThématiqueGlobal Health Workforce Issues
Établissements canadiensUniversity of CalgaryNOSM University
Organismes subventionnairesNorthern Ontario Academic Medicine Association
Mots-clésMedical educationMedicine

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Rural Canadians have poorer health indices than their urban counterparts and struggle with worse access to care due to an undersupply of physicians. Research has identified personal factors, such as being raised in a rural environment, and traits, such as lower harm avoidance, among those drawn to rural practice. As well, the impact of aspects of medical training, such as rural rotations, have been recognized in creating rural practice intentions, but the role of specific clinical competencies here has yet to be determined. Emergency medicine is often one of the most challenging components of rural practice and thought by some to have its competencies poorly developed in family practice training. We hypothesized a model for rural practice affinity in which a strong sense of general self-efficacy would be independently mediated by the development of emergency medicine competence and rural practice self-efficacy, leading to stronger intentions to embark on a rural practice career. METHODS: This model was tested using the data from a survey of all family medicine residents nearing graduation from 14 of the 17 Canadian medical schools. Demographics and data on factors known to influence a rural career choice were collected and accounted for when determining the strength of the hypothesized relationships. Both existing and specifically designed survey tools were used to assess model components. A partial correlation matrix between the variables of interest (general self-efficacy, emergency medicine competency, rural practice self-efficacy, and rural practice intentions) - controlling for the effects of relationships, financial aspects, personal aspects, and social desirability - was created and subjected to a structural equation model. RESULTS: Our initial rural practice affinity model resulted in a poor fit of the model to the data. However, the addition of a pathway from emergency medicine competence to rural practice self-efficacy improved the model to one showing significant paths as hypothesized as well as excellent measures of fit. DISCUSSION: The importance of general self-efficacy is recognized and is itself mediated by the more specific rural practice self-efficacy to rural practice intentions, consistent with the literature. Emergency medicine competency has a central role in both mediating general self-efficacy to rural practice intentions, while also being mediated itself by rural practice self-efficacy to rural practice intentions. This provides new understanding in the development of rural practice self-efficacy. The link of emergency medicine competency to both rural practice self-efficacy and rural practice intentions suggests that this is a curricular area that deserves greater focus and consideration of how to ensure that residents are meeting emergency medicine requirements and receiving robust training in this area. This is especially important as there have been significant concerns from various groups on the efficacy of emergency medicine training in family medicine residency. CONCLUSION: These findings will help inform residency program curriculum and pedagogies, underlining the critical role of emergency medicine competence to support rural physician identity formation and to improve physician recruitment to rural Canada.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,698
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

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

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.

Tête enseignante Opus0,047
Tête enseignante GPT0,445
Écart entre enseignants0,397 · 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 tête enseignante, pas un consensus.

Devis d'étudeAutre devis
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

Citations0
Publié2025
Routes d'admission3
Résumé présentoui

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