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Debriefing for technology-enhanced simulation: a systematic review and meta-analysis
Abstract
Objectives: Debriefing is a common feature of technology‐enhanced simulation ( TES ) education. However, evidence for its effectiveness remains unclear. We sought to characterise how debriefing is reported in the TES literature, identify debriefing features that are associated with improved outcomes, and evaluate the effectiveness of debriefing when combined with TES . Methods: We systematically searched databases, including MEDLINE , EMBASE and Scopus, and reviewed previous bibliographies for original comparative studies investigating the use of TES with debriefing in training health care providers. Reviewers, in duplicate, evaluated study quality and abstracted information on instructional design, debriefing and outcomes. Effect sizes ( ES ) were pooled using random‐effects meta‐analysis. Results: From 10 903 potentially eligible studies, we identified 177 studies (11 511 learners) that employed debriefing as part of TES . Key characteristics of debriefing (e.g. duration, educator presence and characteristics, content, structure/method, timing, use of video) were usually incompletely reported. A meta‐analysis of four studies demonstrated that video‐assisted debriefing has negligible and non‐significant effects for time skills ( ES = 0.10) compared with non‐video‐assisted debriefing. Meta‐analysis demonstrated non‐significant effects in favour of expert modelling with short debriefing in comparison with long debriefing (ES range = 0.21–0.74). Among studies comparing terminal with concurrent debriefing, results were variable depending on outcome measures and the context of training (e.g. medical resuscitation versus technical skills). Eight additional studies revealed insight into the roles of other debriefing‐related factors (e.g. multimedia debriefing, learner‐led debriefing, debriefing duration, content of debriefing). Among studies that compared simulation plus debriefing with no intervention, pooled ES s were favourable for all outcomes (ES range = 0.28–2.16). Conclusions: Limited evidence suggests that video‐assisted debriefing yields outcomes similar to those of non‐video‐assisted debriefing. Other debriefing design features show mixed or non‐significant results. As debriefing characteristics are usually incompletely reported, future debriefing research should describe all the key debriefing characteristics along with their associated descriptors.
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“Cheng et al [53] demonstrated that structured debriefing is an influential instructional component, facilitating reflection, performance analysis, and knowledge transfer to clinical contexts.”
From Enhancing Psychiatry Training Using an Agentic AI Simulated Consultation Tool: Prospective Cohort Study (2026) · cites this paper as [53]
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Breaking news from Emergency Medicine School: is research in simulation possible?
Cascio, M. (2022) · Italian Journal of Emergency Medicine · doi:10.23736/s2532-1285.22.00148-3
Capogna, G., Ingrassia, P. L., Capogna, E., Bernardini, M., Valteroni, E., Pietrabissa, G., & Nardone, G. (2022) · Springer eBooks · doi:10.1007/978-3-031-06104-2_2
On the Validation of Multi-Level Personalised Health Condition Model
Taimoor, N., & Rehman, S. (2022) · Euromicro Conference on Digital System Design (DSD) · doi:10.1109/dsd57027.2022.00086
“The other approaches [4]–[6] employ simulation techniques to validate the model by executing various simulation runs based on different configurations of the model and by observing any runs that accept false estimations.”
MethodОСВІТНІ ТЕОРІЇ СИМУЛЯЦІЙНОГО НАВЧАННЯ В МЕДИЦИНІ
Флуд, В. В., & Савченко, А. (2023) · Наука і техніка сьогодні · doi:10.52058/2786-6025-2023-3(17)-451-457
Tytarenko, N. V., Кукуруза, І. Л., Kostyuchenko, А. V., Zasadnyuk, O. P., & Vozniuk, А. V. (2023) · Reports of Vinnytsia National Medical University · doi:10.31393/reports-vnmedical-2023-27(1)-18
Khattabi, L., Laafou, M., & Raghay, K. (2023) · Revue Francophone Internationale de Recherche Infirmière · doi:10.1016/j.refiri.2023.100304
Kielty, J., Garry, S., O’Sullivan, E., & Lavelle, A. (2024) · International Journal of Healthcare Simulation · doi:10.54531/olur7767
Lapierre, A., Lavoie, P., & Arbour, C. (2023) · Soins d’urgence La revue de l’Association des infirmières et infirmiers d’urgence du Québec · doi:10.7202/1102107ar
Metadata
- Authors
- Cheng, A., Eppich, W., Grant, V., Sherbino, J., Zendejas, B., & Cook, D. A.
- Affiliations
- University of Calgary (CA)
- Northwestern University (US)
- McMaster University (CA)
- Mayo Clinic (US)
- Corresponding author
- Cheng, Adam
- Venue
- Medical Education
- Publisher
- Wiley
- Published
- 2014-06-09
- Volume
- 48
- Issue
- 7
- Pages
- 657-666
- ISSN
- 0308-0110 (ISSN-L)
- 1365-2923
- OpenAlex
- W1986133144
- Cited by
- 481
- References
- 48
- Citations by year
- 2026: 51 · 2025: 34 · 2024: 42 · 2023: 24 · 2022: 27 · 2021: 48 · 2020: 58 · 2019: 43 · 2018: 42 · 2017: 35 · 2016: 44 · 2015: 27 · 2014: 5
- FWCI
- 4.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medical Education (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Education › Simulation-Based Education in Healthcare
- Health Sciences › Medicine › Surgery › Surgical Simulation and Training
- Social Sciences › Education › Innovations in Medical Education
- Keywords
- debriefing, simulation-based medical education, video-assisted debriefing
- MeSH terms
- Computer Simulation, Education, Medical, Education, Professional, Health Personnel, Humans, Teaching, Time Factors, Video Recording, Databases, Bibliographic, Problem-Based Learning
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