Evidence map›Paper›PMID 32297866›Full record

ArticleJMIR medical education2020

A Cardiology Handbook App to Improve Medical Education for Internal Medicine Residents: Development and Usability Study.

Asad Torabi, Abhishek Khemka, Pantila V Bateman

Abstract read
In one paragraph

Article in JMIR medical education, 2020. 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. Pooled it
  2. 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

3 authors.

Asad TorabiIndiana University School of Medicine, Indianapolis, IN, United States.ORCID https://orcid.org/0000-0002-1011-0209
Abhishek KhemkaKrannert Institute of Cardiology, Indiana University School of Medicine, Indianapolis, IN, United States.ORCID https://orcid.org/0000-0002-2976-7104
Pantila V BatemanKrannert Institute of Cardiology, Indiana University School of Medicine, Indianapolis, IN, United States.ORCID https://orcid.org/0000-0002-5809-2513

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAt most institutions, internal medicine residents struggle with balancing clinical duties and learning opportunities, particularly during busy cardiology ward rotations. To improve learning experiences for residents, we helped develop a cardiology handbook app to supplement cardiology education.

objectiveThe aim of this study was to report the development, implementation, and preliminary impact of the Krannert Cardiology Handbook app on graduate medical education.

methodsIn June 2017, 122 residents at Indiana University were invited to download the digital handbook in the Krannert app. The Krannert app featured a total of 13 chapters written by cardiology fellows and faculty at Indiana University. Residents were surveyed on their self-reported improvement in cardiology knowledge and level of satisfaction after using the Krannert app. Residents were also surveyed regarding their preference for a digital handbook app versus a paper handbook.

resultsOf the 122 residents, 38 trainees (31.1%) participated in survey evaluations. Among all respondents, 31 app users (82%) reported that the app helped improve their cardiology knowledge base. The app had an overall favorable response.

conclusionsThe Krannert app shows promise in augmenting clinical education in cardiology with mobile learning. Future work includes adding new topics, updating the content, and comparing the app to other learning modalities.

Indexed as

cardiologyinternal medicinemedical reference appmobile learning

Identifiers

PMID32297866
PMCPMC7193443

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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.