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Advancing chest radiograph interpretation training via e-learning: A study on radiography students
Taku Kuramoto1, Nao Ichikawa1, Shinya Takarabe1
1Department of Radiological Technology, Faculty of Health Sciences, Kobe Tokiwa University, 2-6-2 Otanicho, Nagata-ku, Kobe 653-0838, Japan.
Introduction:
The rising demand for radiological examinations, coupled with a shortage of radiologists, highlights the need for innovative educational approaches to train radiography students effectively. This study quantitatively assessed the impact of an e-learning platform on chest radiograph interpretation skills among radiography students.
Methods:
Twenty fourth-year radiography students were recruited. After excluding four outliers based on Grade Point Average to ensure group comparability, sixteen participants were divided into learning and non-learning groups with comparable academic performance matched-pair design based on Grade Point Average (n = 8 each). The learning group used an e-learning platform specifically designed for chest radiograph interpretation, whereas the non-learning group received no additional training. Both groups were assessed with a standardized test tool at three time points: baseline, 50 days, and 100 days.
Results:
The learning group showed significant improvement, with correct responses increasing from 51% to 80% (p < 0.001). In contrast, the non-learning group demonstrated a modest, non-significant increase from 54% to 60% (p> 0.01). The learning group also exhibited a reduction in response time, decreasing from 29.3 min to 17.5 min (p < 0.01). This improvement reflects greater efficiency and confidence in diagnostic decision-making, demonstrating consistent gains in both accuracy and speed.
Conclusions:
E-learning platforms enhance the accuracy and efficiency of medical image interpretation among radiography students. These results provide insights for developing digital curricula to strengthen clinical pattern recognition. However, the study's generalizability is limited by the small sample size and potential recall bias due to the use of identical clinical cases for training and testing.
Plain Language Summary:
Many people need chest X rays, but there are not enough trained professionals to read them. This study looked at whether an online learning tool could help radiography students read chest images more accurately. This study found that students who used the tool improved their accuracy and worked faster compared to those who did not receive extra training. These findings matter because better training can help future radiographers feel more confident and support safer patient care.
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