Technology‐enhanced Simulation in Emergency Medicine: A Systematic Review and Meta‐Analysis
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Notice bibliographique
Résumé
OBJECTIVES: Technology-enhanced simulation is used frequently in emergency medicine (EM) training programs. Evidence for its effectiveness, however, remains unclear. The objective of this study was to evaluate the effectiveness of technology-enhanced simulation for training in EM and identify instructional design features associated with improved outcomes by conducting a systematic review. METHODS: The authors systematically searched MEDLINE, EMBASE, CINAHL, ERIC, PsychINFO, Scopus, key journals, and previous review bibliographies through May 2011. Original research articles in any language were selected if they compared simulation to no intervention or another educational activity for the purposes of training EM health professionals (including student and practicing physicians, midlevel providers, nurses, and prehospital providers). Reviewers evaluated study quality and abstracted information on learners, instructional design (curricular integration, feedback, repetitive practice, mastery learning), and outcomes. RESULTS: From a collection of 10,903 articles, 85 eligible studies enrolling 6,099 EM learners were identified. Of these, 56 studies compared simulation to no intervention, 12 compared simulation with another form of instruction, and 19 compared two forms of simulation. Effect sizes were pooled using a random-effects model. Heterogeneity among these studies was large (I(2) ≥ 50%). Among studies comparing simulation to no intervention, pooled effect sizes were large (range = 1.13 to 1.48) for knowledge, time, and skills and small to moderate for behaviors with patients (0.62) and patient effects (0.43; all p < 0.02 except patient effects p = 0.12). Among comparisons between simulation and other forms of instruction, the pooled effect sizes were small (≤ 0.33) for knowledge, time, and process skills (all p > 0.1). Qualitative comparisons of different simulation curricula are limited, although feedback, mastery learning, and higher fidelity were associated with improved learning outcomes. CONCLUSIONS: Technology-enhanced simulation for EM learners is associated with moderate or large favorable effects in comparison with no intervention and generally small and nonsignificant benefits in comparison with other instruction. Future research should investigate the features that lead to effective simulation-based instructional design.
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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 | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,015 | 0,001 |
| Bibliométrie | 0,004 | 0,011 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 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 découle