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Enregistrement W3041822806 · doi:10.1177/2382120520913270

Mapping the Expert Mind: Integration Method for Revising the ACES Medical Simulation Curriculum

2020· article· en· W3041822806 sur OpenAlex
Pierre Cardinal, Glenn Barton, Kirk DesRosier, Sharon Yamashita, Angèle Landriault, Aimee Sarti, Stephanie Sutherland, Susan Brien, Kevin McCarragher, Tobias Witter

Pourquoi ce travail est dans la base

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affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
aboutLe titre ou le résumé porte un signal canadien du lexique géographique.

Notice bibliographique

RevueJournal of Medical Education and Curricular Development · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueSimulation-Based Education in Healthcare
Établissements canadiensDalhousie UniversitySunnybrook Health Science CentreHealth Sciences CentreRoyal College of Physicians and Surgeons of CanadaOttawa Hospital
Organismes subventionnairesnon disponible
Mots-clésCurriculumPsychological interventionMedical educationProcess (computing)Task (project management)PsychologyComputer scienceNursingMedicineEngineeringPedagogy

Résumé

récupéré en direct d'OpenAlex

PURPOSE: This article shares our experience developing an integrated curriculum for the ACES (Acute Critical Event Simulation) program. The purpose of the ACES program is to ensure that health care providers develop proficiency in the early management of critically ill patients. The program includes multiple different types of educational interventions (mostly simulation-based) and targets both specialty and family physicians practicing in tertiary and community hospitals. METHODS: To facilitate integration between different educational interventions, we developed a knowledge repository consisting of cognitive sequence maps that make explicit the flow of cognitive activities carried out by experts facing different situations - the sequence maps then serving as the foundation upon which multimodal simulation scenarios would be built. To encourage participation of experts, we produced this repository as a peer-reviewed ebook. Five national organizations collaborated with the Royal College of Physicians and Surgeons of Canada to identify and recruit expert authors and reviewers. Foundational chapters, centered on goals/interventions, were first developed to comprehensively address most tasks conducted in the early management of a critically ill patient. Tasks from the foundational chapters were then used to complete the curriculum with situations. The curriculum development consisted of two-phases each followed by a peer-review process. In the first phase, focus groups using web-conferencing were conducted to map clinical practice approaches and in the second, authors completed the body of the chapter (e.g., introduction, definition, concepts, etc.) then provided a more detailed description of each task linked to supporting evidence. RESULTS: Sixty-seven authors and thirty-five peer reviewers from various backgrounds (physicians, pharmacists, nurses, respiratory therapists) were recruited. On average, there were 32 tasks and 15 situations per chapter. The average number of focus group meetings needed to develop a map (one map per chapter) was 6.7 (SD ± 3.6). We found that the method greatly facilitated integration between different chapters especially for situations which are not limited to a single goal or intervention. For example, almost half of the tasks of the Hypercapnic Ventilatory Failure chapter map were borrowed from other maps with some modifications, which significantly reduced the authors' workload and enhanced content integration. This chapter was also linked to 6 other chapters. CONCLUSIONS: To facilitate curriculum integration, we have developed a knowledge repository consisting of cognitive maps which organize time-sensitive tasks in the proper sequence; the repository serving as the foundation upon which other educational interventions are then built. While this methodology is demanding, authors welcomed the challenge given the scholarly value of their work, thus creating an interprofessional network of educators across 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.

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)0,003
score de la tête « metaresearch » (Gemma)0,006
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,931
Score d'incertitude au seuil0,772

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,072
Tête enseignante GPT0,437
Écart entre enseignants0,365 · 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