Evidence map›Paper›PMID 36918946›Full record

ArticleAdvances in simulation (London, England)2023

The Debriefing Assessment in Real Time (DART) tool for simulation-based medical education.

Kaushik Baliga, Louis P Halamek, Sandra Warburton, Divya Mathias, Nicole K Yamada, Janene H Fuerch, Andrew Coggins

Full text read
In one paragraph

Article in Advances in simulation (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Exploring the Meta-debrief: Developing a Toolbox for Debriefing the Debrief.Simulation in healthcare : journal of the Society for Simulation in Healthcare · 2025
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Kaushik BaligaSydney Medical School, Westmead Hospital, Block K, Level 6, Sydney, NSW, 2145, Australia.
Louis P HalamekDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Sandra WarburtonSimulated Learning Environment for Clinical Training (SiLECT), Westmead Hospital, Sydney, NSW, 2145, Australia.
Divya MathiasThe Australian Institute of Medical Simulation and Innovation (AIMSi), Blacktown Hospital, Sydney, NSW, 2148, Australia.
Nicole K YamadaDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Janene H FuerchDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Andrew CogginsSimulated Learning Environment for Clinical Training (SiLECT), Westmead Hospital, Sydney, NSW, 2145, Australia. andrew.coggins@health.nsw.gov.au.ORCID http://orcid.org/0000-0002-5652-6920

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDebriefing is crucial for enhancing learning following healthcare simulation. Various validated tools have been shown to have contextual value for assessing debriefers. The Debriefing Assessment in Real Time (DART) tool may offer an alternative or additional assessment of conversational dynamics during debriefings.

methodsThis is a multi-method international study investigating reliability and validity. Enrolled raters (n = 12) were active simulation educators. Following tool training, the raters were asked to score a mixed sample of debriefings. Descriptive statistics are recorded, with coefficient of variation (CV%) and Cronbach's α used to estimate reliability. Raters returned a detailed reflective survey following their contribution. Kane's framework was used to construct validity arguments.

resultsThe 8 debriefings (μ = 15.4 min (SD 2.7)) included 45 interdisciplinary learners at various levels of training. Reliability (mean CV%) for key components was as follows: instructor questions μ = 14.7%, instructor statements μ = 34.1%, and trainee responses μ = 29.0%. Cronbach α ranged from 0.852 to 0.978 across the debriefings. Post-experience responses suggested that DARTs can highlight suboptimal practices including unqualified lecturing by debriefers.

conclusionThe DART demonstrated acceptable reliability and may have a limited role in assessment of healthcare simulation debriefing. Inherent complexity and emergent properties of debriefing practice should be accounted for when using this tool.

Indexed as

Educational measurementFeedbackSimulation trainingStaff development

Identifiers

PMID36918946
PMCPMC10013984

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read1
measurements read37
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.