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一项关于医学教育中结构化指导计划不同匹配程序的前瞻性随机试验。

A prospective, randomised trial of different matching procedures for structured mentoring programmes in medical education.

作者信息

Schäfer Matthias, Pander Tanja, Pinilla Severin, Fischer Martin R, von der Borch Philip, Dimitriadis Konstantinos

机构信息

a Klinikum der Ludwig-Maximilians-Universität (LMU) , Germany.

出版信息

Med Teach. 2016 Sep;38(9):921-9. doi: 10.3109/0142159X.2015.1132834. Epub 2016 Jan 28.

Abstract

BACKGROUND

Spontaneous formation of mentoring relationships can be seen as the gold standard in mentoring. Unfortunately, it happens very infrequently. The purpose of structured mentoring programmes is to facilitate the formation of mentoring relationships. This remains a challenging task, especially for large institutions.

AIMS

We set out to investigate and compare three methods of matchmaking in the setting of our structured mentoring programme. In a prospective, randomised trial we compared personal matching (PM) by an experienced expert to two different electronic data processing (EDP)-supported matching procedures: "online algorithm" (OA) versus "online search" (OS).

METHODS

PM was performed after structured interviews of prospective protégés by one founder of our mentoring programme. The OA provides students with a choice of 10 potential mentors based on comparison of online profiles. OS lets students filter and search through all available mentor profiles. One hundred and ninty medical students were randomised into the three groups. One year later, we evaluated the endpoints 1. "establishment of a mentoring relationship" and 2. "satisfaction with the mentoring relationship". Satisfaction with the mentoring relationship was assessed using Munich-Evaluation-of-Mentoring-Questionnaire (MEMeQ).

RESULTS

One hundred sixty-five out of the 190 study participants found a mentor. With regards to endpoint one we found an advantage of PM compared to both EDP-supported matching procedures. There was no significant difference between OA and OS. Concerning endpoint two the differences between the investigated matching procedures were not significant.

CONCLUSION

PM is superior as to the number of mentoring relationships formed per participating student compared to EDP-supported methods. In our data, there was no significant difference in the level of satisfaction. Considering the high investments associated with PM of mentors and protégés, EDP-supported matching procedures seem a viable compromise between effectiveness and efficiency especially for large-scale structured mentoring programmes in medical education.

摘要

背景

指导关系的自发形成可被视为指导的黄金标准。不幸的是,这种情况很少发生。结构化指导计划的目的是促进指导关系的形成。这仍然是一项具有挑战性的任务,尤其是对于大型机构而言。

目的

我们着手在结构化指导计划中调查和比较三种配对方法。在一项前瞻性随机试验中,我们将由经验丰富的专家进行的个人配对(PM)与两种不同的电子数据处理(EDP)支持的配对程序进行了比较:“在线算法”(OA)与“在线搜索”(OS)。

方法

我们的指导计划的一位创始人在对潜在学员进行结构化访谈后进行了个人配对。在线算法根据在线资料的比较为学生提供10位潜在导师供其选择。在线搜索让学生筛选并浏览所有可用的导师资料。190名医学生被随机分为三组。一年后,我们评估了两个终点指标:1. “建立指导关系”和2. “对指导关系的满意度”。使用慕尼黑指导评估问卷(MEMeQ)评估对指导关系的满意度。

结果

190名研究参与者中有165人找到了导师。关于第一个终点指标,我们发现与两种电子数据处理支持的配对程序相比,个人配对具有优势。在线算法和在线搜索之间没有显著差异。关于第二个终点指标,所研究的配对程序之间的差异不显著。

结论

与电子数据处理支持的方法相比,就每位参与学生形成的指导关系数量而言,个人配对更具优势。在我们的数据中,满意度水平没有显著差异。考虑到导师和学员进行个人配对所需的高投入,电子数据处理支持的配对程序似乎是有效性和效率之间的可行折衷方案,特别是对于医学教育中的大规模结构化指导计划。

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