收稿日期: 2025-02-18
网络出版日期: 2025-08-14
Analysis of the structure and research direction of nursing postgraduate supervisors in China
目的 了解中国内地护理研究生导师队伍结构及研究方向，为护理教育的发展提供参考。 方法 使用Python语言的Selenium爬虫框架收集并整理64所护理院校的研究生导师的公开信息数据，分析专职护理研究生导师年龄、学位、职称等个人一般资料情况及数量、研究方向、结构分布等总体情况，并对导师的一般资料特征进行潜在类别分析。 结果 在64所院校中共纳入1 158名护理研究生导师。导师的年龄、职称、学位特征被分为3个潜在类别，分别为新锐高知型（25.8%）、资深经验型（43.5%）和中坚精英型（30.7%）。Logistic回归分析结果显示，导师类型、院校层次、所在地区及工作单位是护理研究生导师潜在类别的影响因素（P<0.05）。 结论 护理研究生导师特征具有较强的异质性，可分为3个潜在类别。护理院校和附属医院可根据不同潜在类别的影响因素，对护理研究生导师进行统筹规划，以优化护理研究生导师队伍的结构和配置。
陈莉 , 王玉琼 , 汪张毅 . 我国护理学研究生导师队伍和研究方向情况分析[J]. 中华护理教育, 2025 , 22(8) : 936 -942 . DOI: 10.3761/j.issn.1672-9234.2025.08.007
Objective To understand the structure and research directions of nursing graduate tutor teams in China，so as to provide references for the development of nursing education. Methods The public information of graduate tutors from 64 nursing colleges was collected and sorted using the Selenium crawler framework in Python. The personal general data（age，degree，professional title，etc.） and overall conditions（quantity，research directions，structural distribution，etc.） of full-time nursing graduate tutors were analyzed，and latent class analysis was conducted on the general data characteristics of the tutors. Results A total of 1，158 nursing graduate tutors from 64 colleges were included. The general data characteristics of the tutors were divided into three latent categories：cutting-edge highly educated type（25.8%），senior experienced type（43.5%），and core elite type（30.7%）. The logistic regression analysis showed that tutor type，college level，region，and work unit were significant factors influencing the latent categories of the general data of nursing graduate tutors（P<0.05）. Conclusion Nursing postgraduate supervisors are heterogeneous in their general profile characteristics and can be classed into three potential categories. Nursing colleges and affiliated hospitals can plan nursing postgraduate supervisors in an integrated manner according to the influencing factors of different potential classes in order to optimize the nursing postgraduate supervisory workforce.
Key words： Nursing; Postgraduate; Python; Mentors; Research direction
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