Evidence map›Paper›PMID 33680312›Full record

ArticleJournal of graduate medical education2021

Blindfolding Improves Communication in Inexperienced Residents Undergoing ACLS Training.

Emily Scicchitano, Phillip Stark, Paige Koetter, Nathan Michalak, Adrian D Zurca

Abstract read
In one paragraph

Article in Journal of graduate medical education, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Guideline
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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

5 authors.

Emily Scicchitano
Phillip Stark
Paige Koetter
Nathan Michalak
Adrian D Zurca

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
A novel use of web-based software to efficiently triage pre-surgical patients basR44TR000045 · NCATS · MEDSLEUTH, INC. · PI KALAMAS, ALICIA GRUBER · 2012 to 2012
$546k
NCATS NIH HHS R44 TR000045NCATS NIH HHS UL1 TR002014
6 · The paper itself

Abstract

backgroundClosed-loop communication (CLC) is associated with decreased medical errors and improved time-to-task completion during resuscitations. Depriving team leaders of sight during training may accelerate the acquisition of favorable communication skills; however, its effect on the frequency of CLC is unclear, especially with trainees.

objectiveWe assessed the effect of depriving interns of sight during advanced cardiovascular life support (ACLS) on verbal communication patterns and resuscitation confidence.

methodsAll interns undergoing ACLS training in June 2019 at a single center were eligible. Interns were randomized to blindfolded training (BT) or standard training (ST). BT team leaders were blindfolded during practice sessions and permitted to use sight during testing. Testing scenarios were video- and audio-recorded. Recordings were assessed for teams' performance and communication patterns. Participants were surveyed for confidence with resuscitation skills before and after ACLS training.

resultsAll 87 eligible interns participated in the study (100% participation). Eighty-five of 87 (98%) interns were included for analysis; 46 were randomized to BT and 39 to ST. Interns in the BT group were significantly more likely to exhibit CLC (mean: BT 20.3, ST 16.6;

conclusionsBlindfolding trainees results in greater instances of CLC, directed communication, and follower-initiated communication during ACLS training.

Indexed as

Internship and ResidencyClinical CompetenceCommunicationHumansResuscitation

Identifiers

PMID33680312
PMCPMC7901606

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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.