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A Comparative Study of Learning Outcomes between Journal Club of a Face-to-Face and an Online E-learning Course

Ohara, H.; Ito, T.; Odanaka, K.; Nobushi, Y.; Kishikawa, Y.; Shimanuki, E.; Nakagawa, N.

2025-08-05 medical education
10.1101/2025.08.01.25332759 medRxiv
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ObjectiveEvidence-based medicine requires pharmacists to critically read research papers. Journal clubs provide opportunities to develop these skills. This study compared learning outcomes between a face-to-face journal club and an online e-learning course. In evidence-based medicine, pharmacists are required to constantly read the latest clinical research papers critically and apply the knowledge gained to appropriate drug therapy. Journal clubs provide an opportunity to develop these skills. This study compared the learning outcomes of a face-to-face journal club and an online journal club using e-learning. MethodA face-to-face journal club was held monthly from January to July 2019, while an e-learning course with audiovisual materials on critical appraisal was delivered from September to December 2020. Participants in both courses completed a pre- and post-course exam (5 questions) assessing critical appraisal skills and a questionnaire (five 7-level Likert items) evaluating attitudes toward critical reading. ResultsBoth methods produced similar knowledge gains. However, the face-to-face journal club was more effective in improving attitudes toward critical appraisal, with all survey scores significantly increasing. In contrast, the e-learning group showed significant improvement in only two areas. ConclusionsWhile both approaches enhanced knowledge, the face-to-face journal club led to greater improvement in awareness toward critical appraisal, suggesting e-learning may be less effective in this regard.

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The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.