Evidence map›Paper›PMID 41258309›Full record

ArticleScientific reports2025

Development of a digital peer-feedback tool for clinical skills training: a pilot study with second-year medical students.

Mustafa Onur Yurdal, Remzi Y Kıncal

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

2 authors.

Mustafa Onur YurdalDepartment of Medical Education, Çanakkale Onsekiz Mart University, Çanakkale, Turkey. monuryurdal@comu.edu.tr.ORCID http://orcid.org/0000-0002-9632-7192
Remzi Y KıncalFaculty of Education, Çanakkale Onsekiz Mart University, Çanakkale, Turkey.ORCID http://orcid.org/0000-0002-6258-393X

Funding

Çanakkale Onsekiz Mart University The Scientific Research Coordination Unit SDK-2024-4838
6 · The paper itself

Abstract

Providing structured feedback in medical education is essential for skill development. However, limitations such as increasing student numbers, reducing trainer availability, and a lack of systematic feedback hinder effective learning. Digital peer-feedback tools offer a potential solution by enabling interactive and scalable assessment. This study introduces Medifeeding, a video-based peer-feedback digital tool designed to enhance clinical skills training among medical students. This study employed an exploratory convergent mixed-methods pilot feasibility design. Medifeeding was developed following Moonen's 3-Space model and tested with 31 s-year medical students at Çanakkale Onsekiz Mart University. Data sources: a post-use online form (educational benefit yes/no, a forced ranking of 10 attributes, and a 5-point overall rating), semistructured interviews (n = 24), and one focus group (n = 5). Quantitative analyses included frequency analysis, the Friedman test with Kendall's W and Wilcoxon signed-rank tests (Holm-adjusted). Qualitative data were analyzed thematically (Strauss's framework). Strands were integrated in a joint display to generate meta-inferences on acceptability and usability. 90% (28/31) reported educational benefit. The overall rating averaged 4.13/5 (90% rated 4-5). For the feature ranking, the Friedman test showed an overall difference (**χ

Indexed as

Clinical CompetenceEducation, Medical, UndergraduatePeer GroupStudents, MedicalAdultEducation, MedicalFeedbackFemaleFormative FeedbackHumansMalePilot ProjectsYoung AdultClinical skillsDigital learningMedical educationPeer feedbackStudent engagementVideo-based assessment

Identifiers

PMID41258309
PMCPMC12630813

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.