Evidence map›Paper›PMID 39988956›Full record

ArticleJMIR medical education2025

Comparison of an Emergency Medicine Asynchronous Learning Platform Usage Before and During the COVID-19 Pandemic: Retrospective Analysis Study.

Blake Briggs, Madhuri Mulekar, Hannah Morales, Iltifat Husain

Abstract readComparative Study
In one paragraph

Article in JMIR medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Blake Briggs *Division of Emergency Medicine, Department of Surgery, University of Tennessee Graduate School of Medicine, 1924 Alcoa Highway, Knoxville, TN, 37920, United States, 1 865-696-7221.ORCID 0000-0002-5524-3291
Madhuri Mulekar *Department of Mathematics, University of South Alabama, Mobile, AL, United States.ORCID 0000-0001-8659-728X
Hannah Morales *Division of Emergency Medicine, Department of Surgery, University of Tennessee Graduate School of Medicine, 1924 Alcoa Highway, Knoxville, TN, 37920, United States, 1 865-696-7221.ORCID 0009-0004-1823-8882
Iltifat Husain *Department of Emergency Medicine, Wake Forest School of Medicine, Winston-Salem, NC, United States.ORCID 0000-0002-9465-4931

Funding

UAB Center for Clinical and Translational Science (CCTS)UL1TR001417 · NCATS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI KIMBERLY, ROBERT P. · 2015 to 2018
$31.4M
NCATS NIH HHS UL1 TR001417
6 · The paper itself

Abstract

Background: The COVID-19 pandemic challenged medical educators due to social distancing. Podcasts and asynchronous learning platforms help distill medical education in a socially distanced environment. Medical educators interested in providing asynchronous teaching should know how these methods performed during the pandemic. Objective: The purpose of this study was to assess the level of engagement for an emergency medicine (EM) board review podcast and website platform, before and during the COVID-19 pandemic. We measured engagement via website traffic, including such metrics as visits, bounce rate, unique visitors, and page views. We also evaluated podcast analytics, which included total listeners, engaged listeners, and number of plays. Methods: Content was designed after the American Board of EM Model, covering only 1 review question per episode. Website traffic and podcast analytics were studied monthly from 2 time periods of 20 months each, before the pandemic (July 11, 2018, to February 31, 2020) and during the pandemic (May 1, 2020, to December 31, 2021). March and April 2020 data were omitted from the analysis due to variations in closure at various domestic and international locations. Results underwent statistical analysis in March 2022. Results: A total of 132 podcast episodes and 93 handouts were released from July 11, 2018, to December 31, 2021. The mean number of listeners per podcast increased significantly from 2.11 (SD 1.19) to 3.77 (SD 0.76; t test, P<.001), the mean number engaged per podcast increased from 1.72 (SD 1.00) to 3.09 (SD 0.62; t test, P<.001), and the mean number of plays per podcast increased from 42.54 (SD 40.66) to 69.23 (SD 17.54; t test, P=.012). Similarly, the mean number of visits per posting increased from 5.85 (SD 3.28) to 15.39 (SD 3.06; t test, P<.001), the mean number of unique visitors per posting increased from 3.74 (SD 1.83) to 10.41 (SD 2.33; t test, P<.001), and the mean number of page views per posting increased from 17.13 (SD 10.63) to 33.32 (SD 7.01; t test, P<.001). Note that, all measures showed a decrease from November 2021 to December 2021. Conclusions: During the COVID-19 pandemic, there was an increased engagement for our EM board review podcast and website platform over a long-term period, specifically through website visitors and the number of podcast plays. Medical educators should be aware of the increasing usage of web-based education tools, and that asynchronous learning is favorably viewed by learners. Limitations include the inability to view Spotify (Spotify Technology S.A.) analytics during the study period, and confounding factors like increased popularity of social media inadvertently promoting the podcast.

Indexed as

COVID-19Education, DistanceEducation, MedicalEmergency MedicineWebcasts as TopicHumansPandemicsRetrospective StudiesSARS-CoV-2assessmentasynchronous learningchallengesCOVID-19effectivenessemergency medicineengagementknowledge retentionmedical educationonline classonline learningonline studyperformancepodcastpost-pandemicpre-pandemicvideoconferencingvirtual learningweb-based

Identifiers

PMID39988956
PMCPMC11870596

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.