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Board 317 - Research Abstract Debriefing for Simulation-Based Medical Education

2013· article· en· W2328468341 on OpenAlexaffabout
Adam Cheng, Walter Eppich, Vincent Grant, Jonathan Sherbino, Dave Cook

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2013
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDebriefingCINAHLFacilitatorPsychological interventionIntervention (counseling)MEDLINEMedical educationPsychologyMedicineApplied psychologyNursingSocial psychology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.114
GPT teacher head0.485
Teacher spread0.371 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2013
Admission routes2
Has abstractyes

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Same venueSimulation in Healthcare The Journal of the Society for Simulation in HealthcareSame topicSimulation-Based Education in HealthcareFrench-language works237,207