Evidence map›Paper›PMID 41737255›Full record

ArticleCJC open2026

Daily Quiz-Based Microlearning Program to Support Electrocardiogram Interpretation Training for Medical Students: A Feasibility Study.

Thibaut Moulin, Nicolas Lellouche, Estelle Gandjbakhch, Mikael Laredo

Abstract read
In one paragraph

Article in CJC open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Thibaut MoulinUniversité Paris-Est Créteil (UPEC), AP-HP Henri Mondor Hospital, Créteil, France.
Nicolas LelloucheUniversité Paris-Est Créteil (UPEC), AP-HP Henri Mondor Hospital, Créteil, France.
Estelle GandjbakhchSorbonne Université, AP-HP, Pitié Salpêtrière Hospital, Paris, France.
Mikael LaredoSorbonne Université, AP-HP, Pitié Salpêtrière Hospital, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electrocardiogram (ECG) interpretation is a critical skill for medical students that requires regular practice to achieve competency. Microlearning is an emerging pedagogical trend that offers students repetitive, short, and focused e-learning sessions. This study aimed to assess the feasibility of a 6-week, daily, digital ECG training program based on microlearning principles among undergraduate medical students. Methods: We conducted a bicentric noncontrolled pilot study. Volunteer medical students received a daily (from Monday to Friday) ECG quiz via commonly used digital platforms, followed by immediate feedback, for 6 weeks. The primary endpoint was the daily participation rate. Skill improvement was evaluated through a baseline test and a final test (20 questions, score ranging from 0-20). Student satisfaction and self-assessment of progression were measured. Results: A total of 47 students were included. The median daily participation rate was high, at 80.9% (iinterquartile range 73.9-86.2), but it tended to decrease over time (weeks 1-2, 87.2%; weeks 3-4, 81.2%; weeks 5-6, 70.2%). A comparison of baseline and final test scores showed a significant improvement, of 1.1 points (95% confidence interval 0.15-2.1; Conclusions: Daily quiz-based microlearning is a feasible method to support ECG training, with high initial adherence. Future controlled studies are required to evaluate the impact of integrating this approach with traditional teaching methods and assess its long-term efficacy and sustainability.

Indexed as

digital learninge-learningElectrocardiogramelectrocardiogram teachingmedical educationmicrolearning

Identifiers

PMID41737255
PMCPMC12925806

What Socratic 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 Socratic graph.