Evidence map›Paper›PMID 33890811›Full record

ArticleThe international journal of lower extremity wounds2022

Web-based Medical Education During COVID-19 Lockdown: A Step Back or a Leap to the Future?

Anna Eleftheriou, Aikaterini Rokou, Christos Argyriou, Nikolaos Papanas, George S Georgiadis

Abstract read
In one paragraph

Article in The international journal of lower extremity wounds, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  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

5 authors.

Anna EleftheriouMedical School, 37791Democritus University of Thrace, Alexandroupolis, Greece.
Aikaterini RokouMedical School, 37791Democritus University of Thrace, Alexandroupolis, Greece.
Christos Argyriou37791Department of Vascular Surgery, Democritus University of Thrace, Alexandroupolis, Greece.
Nikolaos PapanasDiabetes Centre, 387479Democritus University of Thrace, Alexandroupolis, Greece.ORCID https://orcid.org/0000-0002-7320-785X
George S Georgiadis37791Department of Vascular Surgery, Democritus University of Thrace, Alexandroupolis, Greece.ORCID https://orcid.org/0000-0003-1274-3445

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The impact of coronavirus infectious disease (COVID-19) on medical education has been substantial. Medical students require considerable clinical exposure. However, due to the risk of COVID-19, the majority of medical schools globally have discontinued their normal activities. The strengths of virtual teaching now include a variety of web-based resources. New interactive forms of virtual teaching are being developed to enable students to interact with patients from their homes. Conversely, students have received decreased clinical training in certain medical and surgical specialities, which may, in turn, reduce their performance, confidence, and abilities as future physicians. We sought to analyze the effect of telemedicine on the quality of medical education in this new emerging era and highlight the benefits and drawbacks of web-based medical training in building up future physicians. The COVID-19 pandemic has posed an unparalleled challenge to medical schools, which are aiming to deliver quality education to students virtually, balancing between evidence-based and experience-based medicine.

Indexed as

Communicable DiseasesCOVID-19Education, DistanceEducation, MedicalCommunicable Disease ControlHumansInternetPandemicsSARS-CoV-2COVID-19medical educationstudentstelemedicine

Identifiers

PMID33890811
PMCPMC9297065

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.