Debriefing for technology‐enhanced simulation: a systematic review and meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
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 ESs 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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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it