Evidence map›Paper›PMID 34457756›Full record

ArticleMedical science educator2020

Becoming Clinician-Animators: a Toolkit and Pilot Study for Novel Animated Content Development in a Medical Education Curriculum.

Bryan Brown, Catherine Gao, Donna Windish, Jeremy Moeller, Emilie O'Neill, Sarita Soares

Open access · greenAbstract read
In one paragraph

Article in Medical science educator, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

7 citing papers in PubMed, 25 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Bryan BrownDepartment of Internal Medicine, Yale University School of Medicine, New Haven, CT USA.
Catherine GaoDivision of Pulmonary & Critical Care, Northwestern Feinberg School of Medicine, Chicago, IL USA.
Donna WindishDepartment of Internal Medicine, Yale University School of Medicine, New Haven, CT USA.
Jeremy MoellerDepartment of Neurology, Yale University School of Medicine, New Haven, CT USA.
Emilie O'NeillDepartment of Internal Medicine, Yale University School of Medicine, New Haven, CT USA.
Sarita SoaresDepartment of Internal Medicine, Yale University School of Medicine, New Haven, CT USA.
Yale University · USNorthwestern University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Animation is increasingly incorporated into multimedia teaching tools in medical education. Despite enthusiasm about animation among learners and educators, evidence is limited and conflicting regarding the effectiveness of animation in medical education. In this how-to guide and pilot study, a team of clinician-educators have cataloged their efforts to learn the art of animation and understand how to most effectively integrate animation into a flipped classroom curriculum. In this pilot, internal medicine residents responded that an animated video series using anthropomorphic characters and metaphorical dialogue and narrative was an accessible, acceptable, and effective method of teaching the antihyperglycemic medications for type 2 diabetes mellitus. This study paves a path for further exploration of the intersection between multimedia, entertainment, and cognitive theory in graduate medical education.

Indexed as

Advance organizersAnimationCognitive loadGraduate medical educationMultimedia learning

Identifiers

PMID34457756
PMCPMC8368584
OpenAlexW3019444856

What OpenQuestion holds

Textmetadata
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.