RESIDENTS’ AND RECENT GRADUATES’ PERSPECTIVES ON SIMULATION TRAINING IN NEONATAL RESUSCITATION COMPETENCY ACQUISITION
Notice bibliographique
Résumé
Abstract BACKGROUND Simulation training has been incorporated into Canadian residency programs in order to teach both the technical and behavioral skills of resuscitation. Current literature speaks to ‘improvement’ in skills following a simulation encounter. Residents’ perspectives on competency acquisition through simulation training have not been previously reported. OBJECTIVES To explore the perspectives of residents and recent graduates on simulation as an educational modality for competency acquisition in neonatal resuscitation DESIGN/METHODS This project employed an interpretive design qualitative methodology, using an a priori educational theory incorporating the principles of social cognitive theory, deliberate practice, distributive practice, and ‘choke phenomenon’. Semi structured focus groups of residents and paediatricians were used for data collection. Interpretive analysis in the style of Crabtree and Miller was employed. Data validity was optimized through member checking and triangulation of themes across investigators. Validity criteria as described by Lincoln and Guba were applied. Institutional ethics board approval was obtained. RESULTS Participants recognized the important role of simulation which allowed for a safe space to practice in order to become familiar with the algorithm and the equipment of resuscitation. Strengths associated with simulation training included: teaching geared toward the junior learner on the team, the opportunity to build and consolidate learning, and ideal preparation for examinations. In particular, given the current limited neonatal clinical exposure (constraints of reduced workload and hours), simulation was often seen as the trainee’s only opportunity for leading resuscitation. However, both groups of participants highlighted that for neonatal resuscitation the technology was less important than the scenario itself, i.e. ‘high fidelity is not the doll, it’s the stress of the situation’. They identified a lack of the ‘fear’ element in simulated scenarios, with a controlled comfortable environment, artificial ‘time component’, and ‘hypothetical resolution’ of every scenario. Finally, participants identified another potential pitfall of simulation which led to overconfidence and a false sense of expertise that cannot be translated to the ‘real baby’. CONCLUSION Participants perceived simulation to be a useful training modality for aspects of competency acquisition in neonatal resuscitation but highlighted a number of challenges and gaps toward preparedness for practice. In the development of future curricula in competency based training models, educators should consider in the design, graduated levels of simulation aimed toward transition to practice.
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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 | 0,006 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».