中华医学教育杂志

中华医学教育杂志 ›› 2022, Vol. 42 ›› Issue (3): 220-223.DOI: 10.3760/cma.j.cn115259-20210726-00932

• 心理健康教育 • 上一篇    下一篇

深层学习策略在医学生职业认同与胜任力之间的中介作用

张文婕, 赖亚宁, 卿平   

  1. 四川大学华西临床医学院/华西医院教务部,成都 610041
  • 收稿日期:2021-07-26 出版日期:2022-03-01 发布日期:2022-02-23
  • 通讯作者: 卿平, Email: qingping@scu.edu.cn

The mediating role of deep learning in the relationship between professional identity and competency in medical students

Zhang Wenjie, Lai Yaning, Qing Ping   

  1. Department of Academic Affairs, West China School of Medicine & West China Hospital, Sichuan University, Chengdu 610041, China
  • Received:2021-07-26 Online:2022-03-01 Published:2022-02-23
  • Contact: Qing Ping, Email: qingping@scu.edu.cn

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摘要： 目的 探索深层学习策略在医学生职业认同与胜任力之间的中介作用。方法 选择四川大学华西临床医学院2018级五年制临床医学专业212名学生作为研究对象,进行职业认同、深层学习策略和胜任力问卷调查,采用Pearson相关分析探究各潜变量间的相关关系,假设作用路径并利用结构方程模型验证。结果 医学生的胜任力、职业认同和深层学习策略评分分别为(66.38±11.67)分、(12.68±2.32)分和(43.97±6.43)分。职业认同与胜任力呈正相关(r=0.50),深层学习策略与胜任力呈正相关(r=0.51),职业认同与深层学习策略呈正相关(r=0.34),其差异均具有统计学意义(均P＜0.001)。职业认同和深层学习策略均对胜任力存在直接正向作用(β=0.39、0.41,均P＜0.001),职业认同对深层学习策略存在直接正向作用(β=0.28,P＜0.001),职业认同经过深层学习策略对胜任力存在间接正向作用(β=0.12,P＜0.001)。结论 深层学习策略能够中介医学生职业认同对胜任力的作用路径,可以通过提高医学生职业认同水平,培养深层学习策略,实现早期对临床医学专业学生的胜任力导向。

关键词: 医学生, 胜任力, 职业认同, 深层学习策略, 中介作用

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

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