Evidence map›Paper›PMID 41925867›Full record

Trial reportEuropean journal of trauma and emergency surgery : official publication of the European Trauma Society2026

Checklist- and algorithm-based simulation training produce comparable improvements in teamwork-related shared mental models: a cluster-randomized study in trauma resuscitation teams.

Yvonne Beaugé, Simon Kusch, Lukas Thorsson, Michael Zentgraf, Julian Schauwienold, Matthias Muenzberg, Rene Verboket, Rolf Lefering, Uwe Schweigkofler, Philipp Faul and 2 more

Abstract readRandomized Controlled TrialMulticenter Study
In one paragraph

Trial report in European journal of trauma and emergency surgery : official publication of the European Trauma Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

12 authors.

Yvonne BeaugéGoethe University Frankfurt, Medical Faculty, Institute for Medical Education and Clinical Simulation, Theodor-Stern Kai 7, 60590, Frankfurt/Main, Germany.
Simon KuschGoethe University Frankfurt, Medical Faculty, Institute for Medical Education and Clinical Simulation, Theodor-Stern Kai 7, 60590, Frankfurt/Main, Germany.
Lukas ThorssonGoethe University Frankfurt, Medical Faculty, Institute for Medical Education and Clinical Simulation, Theodor-Stern Kai 7, 60590, Frankfurt/Main, Germany.
Michael ZentgrafGoethe University Frankfurt, Medical Faculty, Institute for Medical Education and Clinical Simulation, Theodor-Stern Kai 7, 60590, Frankfurt/Main, Germany.
Julian SchauwienoldGoethe University Frankfurt, Medical Faculty, Institute for Medical Education and Clinical Simulation, Theodor-Stern Kai 7, 60590, Frankfurt/Main, Germany.
Matthias MuenzbergBerufsgenossenschaftliche Unfallklinik, 60389, Frankfurt/Main, Germany.
Rene VerboketGoethe University Frankfurt, University Hospital, Department for Trauma and Orthopedic Surgery, Theodor Stern Kai 7, 60590, Frankfurt/Main, Germany.
Rolf LeferingInstitute for Research in Operative Medicine, Faculty of Health, Ostmerheimer Str. 200, 51109, Köln, Germany.
Uwe SchweigkoflerBerufsgenossenschaftliche Unfallklinik, 60389, Frankfurt/Main, Germany.
Philipp FaulBerufsgenossenschaftliche Unfallklinik, 60389, Frankfurt/Main, Germany.
Jasmina SterzGoethe University Frankfurt, Medical Faculty, Institute for Medical Education and Clinical Simulation, Theodor-Stern Kai 7, 60590, Frankfurt/Main, Germany.
Miriam RuesselerGoethe University Frankfurt, Medical Faculty, Institute for Medical Education and Clinical Simulation, Theodor-Stern Kai 7, 60590, Frankfurt/Main, Germany. ruesseler@em.uni-frankfurt.de.ORCID http://orcid.org/0000-0001-7494-0159

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeShared mental models (SMMs) reflect the extent to which team members hold a similar understanding of roles and team processes. In trauma resuscitation, higher SMM alignment is considered a prerequisite for coordinated interprofessional teamwork. This study compared the effects of checklist-based versus algorithm-based in situ simulation training on teamwork-related SMMs in trauma room teams.

methodsIn this multicenter, cluster-randomized pre–post study, 29 interprofessional trauma teams (186 participants) from six hospitals received either checklist-based training (n = 15 teams) incorporating the Trauma Room Manual checklists or algorithm-based training (n = 14 teams), both grounded in ATLS principles. Teams completed an SMM questionnaire adapted to the trauma setting, based on a previously published instrument, assessing similarity in (1) task responsibility and (2) team communication. Team-level similarity scores were calculated pre- and post-training. Training effects were analyzed using mixed repeated-measures ANOVA.

resultsAcross both training formats, teamwork-related shared mental models increased significantly from pre- to post-training in total similarity, task responsibility, and communication. No significant between-group differences or time × group interactions were observed. The interaction for task responsibility approached significance (p =.06; η²p =.12).

conclusionA single-day in situ simulation training improved teamwork-related shared mental models in interprofessional trauma teams. Checklist- and algorithm-based formats produced similar short-term gains. Future studies should evaluate long-term retention, implementation fidelity, and whether improved SMM alignment translates into measurable team performance and patient-safety outcomes.

Indexed as

AlgorithmsChecklistPatient Care TeamResuscitationSimulation TrainingAdultCommunicationCooperative BehaviorFemaleHumansInterprofessional RelationsMaleTrauma CentersAlgorithm-based trainingChecklistsInterprofessional teamworkShared mental modelsSimulation trainingTrauma resuscitation

Identifiers

PMID41925867
PMCPMC13046582

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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.