Evidence map›Paper›PMID 39695901›Full record

ArticleAdvances in simulation (London, England)2024

When common cognitive biases impact debriefing conversations.

Michael J Meguerdichian, Dana George Trottier, Kimberly Campbell-Taylor, Suzanne Bentley, Kellie Bryant, Michaela Kolbe, Vincent Grant, Adam Cheng

Abstract read
In one paragraph

Article in Advances in simulation (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Michael J MeguerdichianInstitute for Simulation and Advanced Learning, 1400 Pelham Parkway S, Bronx, NY, 10461, USA. michael.meguerdichian@nychhc.org.
Dana George TrottierInstitute for Simulation and Advanced Learning, 1400 Pelham Parkway S, Bronx, NY, 10461, USA.
Kimberly Campbell-TaylorNYC Health+Hospitals, 50 Waters Street, New York, NY, 10004, USA.
Suzanne BentleyIcahn School of Medicine at Mt. Sinai, Gustave L. Levy Pl, Elmhurst Hospital Center, 79-01 Broadway, Queens, New York, NY, 10029, USA.
Kellie BryantNational League of Nursing, 2600 Virginia Ave NW, Washington D.C, 20037, USA.
Michaela KolbeSimulation Centre, University Hospital Zurich, Zurich, Switzerland.
Vincent GranteSim Provincial Simulation Program for Alberta Health Services, Alberta, Canada.
Adam ChengDepartment of Pediatrics and Emergency Medicine, University of Calgary, 28 Oki Drive NW, Calgary, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare debriefing is a cognitively demanding conversation after a simulation or clinical experience that promotes reflection, underpinned by psychological safety and attention to learner needs. The process of debriefing requires mental processing that engages both "fast" or unconscious thinking and "slow" intentional thinking to be able to navigate the conversation. "Fast" thinking has the potential to surface cognitive biases that impact reflection and may negatively influence debriefer behaviors, debriefing strategies, and debriefing foundations. As a result, negative cognitive biases risk undermining learning outcomes from debriefing conversations. As the use of healthcare simulation is expanding, the need for faculty development specific to the roles bias plays is imperative. In this article, we hope to build awareness about common cognitive biases that may present in debriefing conversations so debriefers have the chance to begin the hard work of identifying and attending to their potential detrimental impacts.

Identifiers

PMID39695901
PMCPMC11656545

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.