Learning pediatric emergency medicine over time: A realist evaluation of a longitudinal pediatric emergency medicine clinical experience
Notice bibliographique
Résumé
Introduction: Emergency medicine (EM) practitioners must be proficient at caring for patients of all ages, including pediatric patients. Traditionally, EM trainees learn pediatric emergency medicine (PEM) through block rotations. This is problematic due to the seasonal nature of pediatric diseases and infrequent critical events. Spaced repetition learning theory suggests PEM would be better learned through longitudinal rotations. The transition to competency-based medical education (CBME) in Canada is accelerating the need to find novel ways to attain competencies in postgraduate training. At McMaster University, senior EM trainees can choose either traditional PEM blocks or longitudinal rotations. Our objective was to understand how learners experience these different rotations given the transition to CBME in Canada. Methods: Using a realist framework of program evaluation, we conducted semistructured interviews with key stakeholders (trainees, program directors, attending physicians) in EM. The realist framework was used to understand how context interacts with theoretical mechanisms to produce outcomes of interest. Data were analyzed using inductive, conventional content analysis. All investigators coded a subset of transcripts independently and in duplicate to achieve intercoder agreement. Results: = 2). The learning experience exists within an educational and clinical context, which are logistically distinct but inseparable. The longitudinal learning experience appears to improve learning through spaced repetition, which prevents atrophy of skills and knowledge while also benefitting from the offsetting of seasonal variability associated with many pediatric diseases. Improved feedback and entrustment are facilitated through the building of coaching relationships over time. Barriers to the learning experience are related mainly to logistical difficulties associated with resolving longitudinal and blocked learning experiences. Improved relationships with the interprofessional team may provide distinct learning opportunities and improved team functioning. Block rotations were identified as more valuable to junior trainees learning fundamental concepts. Conclusions: Longitudinal learning provides numerous advantages to learning PEM, including increased case variety, spaced repetition of core concepts, and a perception of greater entrustment of the learner through formation of coaching relationships over time. Future projects looking to quantify the differences between longitudinal and block learning to objectively show a difference in skills and knowledge are needed.
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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 | 0,006 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,032 | 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 ».