Evidence map›Paper›PMID 39250155›Full record

Trial reportJAMA network open2024

Error Management Training and Adaptive Expertise in Learning Computed Tomography Interpretation: A Randomized Clinical Trial.

Leonardo Aliaga, Rebecca A Bavolek, Benjamin Cooper, Amy Mariorenzi, James Ahn, Aaron Kraut, David Duong, Catherine Burger, Michael A Gisondi

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05284838 (The FAIL CT Study), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

NCT05284838 nacompletednot on this map

The FAIL CT Study: Facilitating Adaptive Expertise in Learning Computed Tomography, a Multi-center Randomized Controlled Trial

TypeinterventionalSponsorStanford UniversityRan2022 to 2023Enrolled150ConditionsAdaptive Expertise, Error Management Training, LearningArmsError Management Training (Difficult), Error Management Training (Easy), Error Avoidance Training
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Leonardo AliagaDepartment of Emergency Medicine, Stanford University, Stanford, California.
Rebecca A BavolekDepartment of Emergency Medicine, University of California, Los Angeles.
Benjamin CooperDepartment of Emergency Medicine, University of Texas Health Science Center at Houston.
Amy MariorenziDepartment of Emergency Medicine, Brown University, Providence, Rhode Island.
James AhnDivision of the Biological Sciences, University of Chicago, Chicago, Illinois.
Aaron KrautDepartment of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison.
David DuongDepartment of Emergency Medicine, Highland Hospital, Alameda Health System, Oakland, California.
Catherine BurgerDepartment of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Michael A GisondiDepartment of Emergency Medicine, Stanford University, Stanford, California.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Adaptive expertise helps physicians apply their skills to novel clinical cases and reduce preventable errors. Error management training (EMT) has been shown to improve adaptive expertise with procedural skills; however, its application to cognitive skills in medical education is unclear. Objective: To evaluate whether EMT improves adaptive expertise when learning the cognitive skill of head computed tomography (CT) interpretation. Design, Setting, and Participants: This 3-arm randomized clinical trial was conducted from July 8, 2022, to March 30, 2023, in 7 geographically diverse emergency medicine residency programs. Participants were postgraduate year 1 through 4 emergency medicine residents masked to the hypothesis. Interventions: Participants were randomized 1:1:1 to a difficult EMT, easy EMT, or error avoidance training (EAT) control learning strategy for completing an online head CT curriculum. Both EMT cohorts received no didactic instruction before scrolling through head CT cases, whereas the EAT group did. The difficult EMT cohort answered difficult questions about the teaching cases, leading to errors, whereas the easy EMT cohort answered easy questions, leading to fewer errors. All 3 cohorts used the same cases. Main Outcomes and Measures: The primary outcome was a difference in adaptive expertise among the 3 cohorts, as measured using a head CT posttest. Secondary outcomes were (1) differences in routine expertise, (2) whether the quantity of errors during training mediated differences in adaptive expertise, and (3) the interaction between prior residency training and the learning strategies. Results: Among 212 randomized participants (mean [SD] age, 28.8 [2.0] years; 107 men [50.5%]), 70 were allocated to the difficult EMT, 71 to the easy EMT, and 71 to the EAT control cohorts; 150 participants (70.8%) completed the posttest. The difficult EMT cohort outperformed both the easy EMT and EAT cohorts on adaptive expertise cases (60.6% [95% CI, 56.1%-65.1%] vs 45.2% [95% CI, 39.9%-50.6%], vs 40.9% [95% CI, 36.0%-45.7%], respectively; P < .001), with a large effect size (η2 = 0.19). There was no significant difference in routine expertise. The difficult EMT cohort made more errors during training than the easy EMT cohort. Mediation analysis showed that the number of errors during training explained 87.2% of the difficult EMT learning strategy's effect on improving adaptive expertise (P = .01). The difficult EMT learning strategy was more effective in improving adaptive expertise for residents earlier in training, with a large effect size (η2 = 0.25; P = .002). Conclusions and Relevance: In this randomized clinical trial, the findings show that EMT is an effective method to develop physicians' adaptive expertise with cognitive skills. Trial Registration: ClinicalTrials.gov Identifier: NCT05284838.

Indexed as

Clinical CompetenceInternship and ResidencyTomography, X-Ray ComputedAdultCurriculumEducation, Medical, GraduateEmergency MedicineFemaleHumansLearningMaleMedical Errors

Identifiers

PMID39250155
PMCPMC11385054

What OpenQuestion holds

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Registered trials

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.