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

Abstract

Medical 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). In 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. In 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). App-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. This trial was not prospectively registered due to its educational study design and the absence of any potential harm or disadvantage for participants.

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