Evidence map›Paper›PMID 41968328›Full record

Trial reportBMC medical education2026

Randomized comparison of gamified mobile app-based training versus conventional learning for pneumothorax detection in chest radiographs.

Jacob Jalil Hassan, Christian Boschenriedter, Arian Taheri Amin, Silvio Wermelskirchen, Gunther Hempel, Timm Denecke, Hans-Jonas Meyer

Abstract readRandomized Controlled TrialComparative Study
In one paragraph

Trial report in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Jacob Jalil Hassan *Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany. jacob.hassan@medizin.uni-leipzig.de.
Christian Boschenriedter *Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine- University Düsseldorf, Düsseldorf, Germany.
Arian Taheri AminDepartment of Diagnostic and Interventional Radiology, Charité Universitätsmedizin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Campus Virchow-Klinikum (CVK), Berlin, Germany.
Silvio WermelskirchenDepartment of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany.
Gunther HempelDepartment of Anaesthesiology and Intensive Care Medicine, University Hospital Leipzig, Leipzig, Germany.
Timm DeneckeDepartment of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany.
Hans-Jonas MeyerDepartment of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedical education could benefit from the introduction of novel teaching techniques. The present study aimed to assess the effect of a gamified mobile app (LuluRad) to improve pneumothorax detection on chest radiographs (CXRs).

methodsIn this prospective, single-center randomized trial, third-year medical students were individually randomized using a coin toss to app-based learning (n = 60) or script-based learning (n = 66). Participants completed pre- and post-learning intervention CXR pneumothorax tests. The primary study outcome was pre/post diagnostic accuracy change between the app-based and script-based group. Secondary endpoints were changes in sensitivity and specificity.

resultsIn the app group, accuracy increased from 50.8% to 65.0% (p = 0.015) and sensitivity from 53.3% to 67.2% (p = 0.022), while specificity did not change significantly (p = 0.068). In the script group, accuracy did not significantly change (p = 0.132), sensitivity decreased from 64.1% to 41.9% (p < 0.001), and specificity increased from 39.4% to 51.0% (p = 0.006). Between-group change scores demonstrated greater increases in accuracy (Δ + 14.2 vs. − 5.3% points (pp); p < 0.001) and sensitivity (Δ + 13.9 vs. − 22.2 pp; p < 0.001) in the app group, while specificity did not change significantly between groups (p = 0.378).

conclusionApp-based learning was associated with greater increases in pneumothorax detection accuracy compared with conventional self-study among third-year medical students. Given the study design, these findings should be considered exploratory. While confirmation in larger studies is required, this approach appears promising and may represent a valuable adjunct to traditional teaching.

trial registrationThis trial was not prospectively registered due to its educational study design and the absence of any potential harm or disadvantage for participants.

Indexed as

Education, Medical, UndergraduateMobile ApplicationsPneumothoraxRadiography, ThoracicClinical CompetenceFemaleHumansMaleProspective StudiesSensitivity and SpecificityStudents, MedicalChest radiographyChest x-rayGamificationMedical learningPneumothorax

Identifiers

PMID41968328
PMCPMC13091258

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.