Abstract: Objective To explore the mediating role of deep learning in the relationship between professional identity and competency in medical students. Methods The students were those enrolled in 2018 into West China School of Medicine in Sichuan University and were surveyed by the questionnaires regarding their professional identity, deep learning and competency. Pearson correlation analysis was used to explore the correlation between potential variables. The structural equation modeling (SEM) was applied to test the relationship among the variables. Results The score of competency, professional identity and deep learning of medical students was (66.38±11.67), (12.68±2.32), (43.97±6.43) respectively. Professional identity (r=0.50) and deep leaning (r=0.51) were positive correlated with competency, professional identity was positive correlated with deep learning (r=0.34), all P＜0.001. Professional identity (β=0.39, P＜0.001) and deep learning (β=0.41, P＜0.001) had a direct positive effect on competency, Professional identity had a direct positive effect on deep learning (β=0.28, P＜0.001), and professional identity had indirect positive effect (β=0.12, P<0.001) on competency through the mediating role of deep learning. Conclusions Professional identity and deep learning may improve the competency of medical students. The effect of professional identity on competency should be more recognized by strengthening deep learning.

Key words: Students, Medical, Competency, Professional identity, Deep learning, Mediating role