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人人皆非凡:普通外科住院医师选拔过程中推荐信的分析。

Everyone Is Awesome: Analyzing Letters of Reference in a General Surgery Residency Selection Process.

出版信息

J Grad Med Educ. 2020 Oct;12(5):566-570. doi: 10.4300/JGME-D-20-00034.1.

Abstract

BACKGROUND

The resident selection process involves the analysis of multiple data points, including letters of reference (LORs), which are inherently subjective in nature.

OBJECTIVE

We assessed the frequency with which LORs use quantitative terms to describe applicants and to assess whether the use of these terms reflects the ranking of trainees in the final selection process.

METHODS

A descriptive study analyzing LORs submitted by Canadian medical graduate applicants to the University of Ottawa General Surgery Program in 2019 was completed. We collected demographic information about applicants and referees and recorded the use of preidentified quantitative descriptors (eg, best, above average). A 10% audit of the data was performed. Descriptive statistics were used to analyze the demographics of our letters as well as the frequency of use of the quantitative descriptors.

RESULTS

Three hundred forty-three LORs for 114 applicants were analyzed. Eighty-five percent (291 of 343) of LORs used quantitative descriptors. Eighty-four percent (95 of 113) of applicants were described as above average, and 45% (51 of 113) were described as the "best" by at least 1 letter. The candidates described as the "best" ranked anywhere from second to 108th in our ranking system.

CONCLUSIONS

Most LORs use quantitative descriptors. These terms are generally positive, and while the use does discriminate between different applicants, it was not helpful in the context of ranking applicants in our file review process.

摘要

背景

住院医师选拔过程涉及对多个数据点的分析,包括推荐信(LOR),而这些推荐信本质上是主观的。

目的

我们评估了LOR 描述申请人时使用定量术语的频率,并评估这些术语的使用是否反映了在最终选拔过程中对学员的排名。

方法

完成了对 2019 年加拿大医学研究生申请人提交给渥太华大学普通外科项目的 LOR 的描述性研究。我们收集了申请人和推荐人的人口统计学信息,并记录了使用预先确定的定量描述符(例如,最好,高于平均水平)的情况。对数据进行了 10%的审核。使用描述性统计分析了我们的信件的人口统计学特征以及定量描述符的使用频率。

结果

分析了 114 名申请人的 343 封 LOR。85%(291/343)的 LOR 使用了定量描述符。84%(95/113)的申请人被描述为高于平均水平,而 45%(51/113)的申请人至少有一封被描述为“最好”。在我们的排名系统中,被描述为“最好”的候选人排名从第二到第一百零八。

结论

大多数 LOR 使用定量描述符。这些术语通常是积极的,虽然它们确实可以区分不同的申请人,但在我们的文件审查过程中对申请人进行排名方面并没有帮助。

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