Evidence map›Paper›PMID 37818446›Full record

ArticleAcademic pathology

Increasing medical student awareness of pathology through a virtual, asynchronous pathology elective.

Karen Tew, Jesse Kresak, Stacy G Beal

Open access · goldAbstract read
In one paragraph

Article in Academic pathology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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 at 1 institution in 1 country.

Karen TewCollege of Medicine, University of Florida, Gainesville, FL, USA.
Jesse KresakDepartment of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA.
Stacy G BealDepartment of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA.
University of Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Faculty from the University of Florida Department of Pathology, Immunology, and Laboratory Medicine developed an asynchronous, fully virtual pathology elective for medical students that emphasizes both foundational pathology concepts as well as the role of pathologists in the broader health system. The program includes ten core modules as well as several selective modules which allows students to tailor their coursework to better align with their desired specialty. After completing each module, students were required to concisely summarize the topic in the form of a 280-character tweet. Students were surveyed immediately after finishing the course and again one year after finishing the course to assess the effectiveness of the course in teaching students about pathology. Survey results showed significant improvement in student knowledge about the field of pathology and high levels of satisfaction with the course content and delivery. The tweet summaries required in the course provided a unique challenge for students. Although the course was initially developed in response to the COVID-19 pandemic, enrollment has continued steadily through 2023. Our study suggests that online pathology electives can be an effective way to increase medical student exposure to pathology and facilitate learning about the field of pathology, especially among students who may not ultimately pursue a career in pathology.

Indexed as

COVID-19CurriculumMedical educationPathologyRemoteRotationVirtual

Identifiers

PMID37818446
PMCPMC10560767
OpenAlexW4387328240

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.