Board 317 - Research Abstract Debriefing for Simulation-Based Medical Education
Notice bibliographique
Résumé
Introduction/Background Debriefing is a common feature of technology-enhanced simulation (TES) education. Evidence for its effectiveness, however, remains unclear. The authors sought to characterize how debriefing is reported in the TES literature, evaluate the effectiveness of debriefing in TES and identify features of debriefing that are associated with improved outcomes. Methods This review was planned, conducted and reported in adherence to PRISMA standards of quality for reported meta-analyses. In this systematic review, we sought to answer the following questions: 1) To what extent is debriefing reported as a component of simulation-based educational interventions?, 2) To what extent is debriefing in TES for training health care professionals associated with improved outcomes in comparison to no intervention? and 3) How do outcomes vary for different debriefing instructional designs? Studies published in any language were included if they: (a) Investigated the use of TES in which a debriefing was done and labeled as a debriefing, OR in which there is another term/descriptor that indicates a discussion/dialogue between two or more individuals (eg. two learners or at least one learner and a facilitator); and (b) involved health professionals at any stage in training or practice, in comparison with no intervention or with a study intervention, using outcomes of learning, behaviours or effects on patients. We excluded studies where feedback was delivered but there was no indication of discussion or dialogue between two individuals. We searched MEDLINE, EMBASE, CINAHL, PsychINFO, ERIC, Web of Science and Scopus using search terms for the intervention (eg. simulator, simulation, manikin), topic (eg. surgery, anesthesia, trauma) and learners (eg. education medical, education nursing, education professional). No beginning date cutoff was used and the last date of the search was May 11, 2011. This search was supplemented by adding the entire reference lists for several published reviews of health professions simulation and all article published in two journals devoted to health professions simulation (Simulation in Healthcare and Clinical Simulation in Nursing). Inclusion and exclusion criteria were applied to identify studies of interest. The authors worked independently and in duplicate to screen all titles and abstracts for inclusion. In the event of disagreement or insufficient information in the abstract, the full text of potential articles was reviewed independently and in duplicate. All conflicts were resolved by consensus. For each study, we extracted the training level of learners, clinical topic, training location, study design, method of group assignment, outcomes and methodological quality of the studies (graded using the Medical Education Research Study Quality Instrument (MERSQI)), along with several items related specifically to debriefing (eg. number of learners, facilitator presence, debriefing theory, debriefing structure, duration of debriefing, timing of debriefing). Results From a pool of 10903 studies, the authors identified 177 studies (11,483 learners) employing debriefing as part of TES. Effect sizes (ES) were pooled using a random-effects model. Among studies comparing simulation with debriefing to no intervention, ES were large for knowledge, process skills (eg. performance in simulated setting), and time skills (eg. time to complete task) outcomes (range=0.86-2.16) and small to moderate for outcomes of product skills (eg. successful task completion), behaviors with patients and patient effects (range=0.28-0.55). Studies comparing different types of debriefing revealed differences of negligible to moderate magnitude. Key characteristics of debriefing were often incompletely reported. Conclusion TES with debriefing is associated with moderate to large effect sizes in comparison with no intervention. Studies comparing different approaches to debriefing showed negligible to moderate differences. Debriefing characteristics are often incompletely reported in studies of TES with debriefing. Disclosures Laerdal Foundation for Acute Medicine, Heart and Stroke Foundation of Canada Royal College of Physicians and Surgeons of Canada SSH Board of Directors Salary Support from Center for Medical Simulation to teach on simulation courses none Per dien honoraria from PAEDSIM e.V. to teach on pediatric simulation courses.
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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 | 0,010 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».