Current Practices and Use of Simulation in Neonatal Resuscitation Program Courses Across Canada
Notice bibliographique
Résumé
Abstract BACKGROUND: Simulation is an effective tool in medical education. The extent and manner in which simulation is used within Neonatal Resuscitation Program (NRP) courses across Canada is currently unknown. In order to improve NRP education, current practices must be better understood. OBJECTIVES: To characterize current practices and use of simulation in NRP courses across Canada. DESIGN/METHODS: A REDCap survey, consisting of questions about instructor demographics, practices in NRP instruction and use of simulation, was developed and distributed to all NRP instructors across Canada. Simple statistics were used to tabulate responses and the chi-squared test was used to assess differences in simulation use between different types of instructors. RESULTS: Five hundred sixty nine of 1390 (40.9%) NRP instructors completed the survey. Participants included 88 (15.5%) physicians, 74 (13.0%) respiratory therapists, 345 (60.6%) registered nurses and 28 (4.9%) nurse practitioners. Two hundred fifty eight (45.4%) worked in institutions providing Level III care. Overall, 560 (98.4%) respondents used simulation, of which only 176 (31.4%) reported using high-technology simulation. Only 180 (31.6%) instructors who used simulation reported having received formal training in high-technology simulation. When asked about the role of simulation in NRP instruction, 545 (95.8%) agreed or strongly agreed that simulation is a valuable educational tool in NRP instruction, but only 219 (39.1%) felt comfortable using high-technology simulation. There was no difference in use of high-technology simulation between physician and non-physician instructors (I2 0.90, p=0.34). Of the instructors who used high-technology simulation, 160 (90.9%) and 134 (76.1%) had learners and instructors, respectively, from multiple healthcare disciplines present in some or all sessions. There was a non-significant trend towards higher use of interprofessional learners among physician instructors (I2 3.8, p=0.052). An impressive 554 (98.9%) debriefed after some or all simulation sessions, with only 295 (51.8%) instructors having received formal training in debriefing techniques. CONCLUSION: Almost all NRP instructors use simulation and feel that it is valuable, though few have received formal training and feel comfortable using high-technology simulation. Most simulation use is low-technology, in keeping with the Canadian Paediatric Society (CPS) recommendations, though the optimal methods of use of simulation in NRP instruction are not known. The majority of instructors debrief with learners, as recommended by the CPS, though only half have had training in debriefing. The results of this study support further investigation into the optimal type of simulation in NRP teaching and more formal education in simulation and debriefing for NRP instructors.
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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 | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».