Evidence map›Paper›PMID 32915154›Full record

ArticleJMIR medical education2020

Medical Student Training in eHealth: Scoping Review.

Jean-François Echelard, François Méthot, Hue-Anh Nguyen, Marie-Pascale Pomey

Open access · goldAbstract readScoping Review
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 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

27 citing papers in PubMed, 61 citations in OpenAlex.

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  13. Necessity and Importance of Developing AI in Anesthesia from the Perspective of Clinical Safety and Information Security.Medical science monitor : international medical journal of experimental and clinical research · 2023
    Review
  14. Clinical informatics training in medical school education curricula: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  15. Observational
  16. Virtual Care and the Inverse Care Law: Implications for Policy, Practice, Research, Public and Patients.International journal of environmental research and public health · 2022
    Article
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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

4 authors at 1 institution in 1 country.

Jean-François EchelardFaculty of Medicine, Université de Montréal, Montréal, QC, Canada.ORCID https://orcid.org/0000-0002-7078-4256
François Méthot *Faculty of Medicine, Université de Montréal, Montréal, QC, Canada.ORCID https://orcid.org/0000-0002-2752-5523
Hue-Anh Nguyen *Faculty of Medicine, Université de Montréal, Montréal, QC, Canada.ORCID https://orcid.org/0000-0001-6024-4179
Marie-Pascale PomeyResearch Centre, University of Montreal Hospital Center, Montreal, QC, Canada, University of Montreal Hospital Center, Montreal, QC, Canada.ORCID https://orcid.org/0000-0001-5180-8139
Université de Montréal · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundeHealth is the use of information and communication technologies to enable and improve health and health care services. It is crucial that medical students receive adequate training in eHealth as they will work in clinical environments that are increasingly being enabled by technology. This trend is especially accelerated by the COVID-19 pandemic as it complicates traditional face-to-face medical consultations and highlights the need for innovative approaches in health care.

objectiveThis review aims to evaluate the extent and nature of the existing literature on medical student training in eHealth. In detail, it aims to examine what this education consists of, the barriers, enhancing factors, and propositions for improving the medical curriculum. This review focuses primarily on some key technologies such as mobile health (mHealth), the internet of things (IoT), telehealth, and artificial intelligence (AI).

methodsSearches were performed on 4 databases, and articles were selected based on the eligibility criteria. Studies had to be related to the training of medical students in eHealth. The eligibility criteria were studies published since 2014, from a peer-reviewed journal, and written in either English or French. A grid was used to extract and chart data.

resultsThe search resulted in 25 articles. The most studied aspect was mHealth. eHealth as a broad concept, the IoT, AI, and programming were least covered. A total of 52% (13/25) of all studies contained an intervention, mostly regarding mHealth, electronic health records, web-based medical resources, and programming. The findings included various barriers, enhancing factors, and propositions for improving the medical curriculum.

conclusionsTrends have emerged regarding the suboptimal present state of eHealth training and barriers, enhancing factors, and propositions for optimal training. We recommend that additional studies be conducted on the following themes: barriers, enhancing factors, propositions for optimal training, competencies that medical students should acquire, learning outcomes from eHealth training, and patient care outcomes from this training. Additional studies should be conducted on eHealth and each of its aspects, especially on the IoT, AI, programming, and eHealth as a broad concept. Training in eHealth is critical to medical practice in clinical environments that are increasingly being enabled by technology. The need for innovative approaches in health care during the COVID-19 pandemic further highlights the relevance of this training.

Indexed as

artificial intelligencedigital healtheHealthelectronic health recordshealth appsinternet of thingsmedical educationmHealthprogrammingtelehealth

Identifiers

PMID32915154
PMCPMC7519432
OpenAlexW3043265868

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.