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推特足迹与新冠时代的匹配:了解申请人在线活动与住院医师匹配成功之间的关系。

Twitter Footprint and the Match in the COVID-19 Era: Understanding the Relationship between Applicant Online Activity and Residency Match Success.

机构信息

Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, Ohio.

Case Western School of Medicine, Cleveland, Ohio.

出版信息

Urol Pract. 2022 Jul;9(4):331-339. doi: 10.1097/UPJ.0000000000000306. Epub 2022 Apr 28.

Abstract

INTRODUCTION

The dramatic reduction of clinical and research activities within medical and surgical departments during COVID-19, coupled with the inability of medical students to engage in research, away rotations and academic meetings, have all posed important implications on residency match.

METHODS

Using Twitter application programming interface available data, 83,000 program-specific and 28,500 candidate-specific tweets were extracted for the analysis. Applicants to urology residency were identified as matched vs unmatched based on 3-level identification and verification. All elements of microblogging were captured through Anaconda Navigator. The primary endpoint was residency match, assessed as correlation to Twitter analytics (ie retweets, tweets). The final list of matched/unmatched applicants through this process was cross-referenced with internal validation of information obtained from the American Urological Association.

RESULTS

A total of 28,500 English language posts from 250 matched and 45 unmatched applicants were included in the analysis. Matched applicants generally showed higher number of followers (median 171 [IQR 88-317.5] vs 83 [42-192], p=0.001), tweet likes (2.57 [1.53-4.52] vs 1.5 [0.35-3.03], p=0.048), and recent and total manuscripts (1 [0-2] vs 0 [0-1], p=0.006); 1 [0-3] vs 0 [0-1], p=0.016) in comparison to the unmatched cohort. On multivariable analysis, after adjusting for location, total number of citations and manuscripts, being a female (OR 4.95), having more followers (OR 1.01), individual tweet likes (OR 1.011) and total number of tweets (OR 1.02) increased overall odds of matching into a urology residency.

CONCLUSIONS

Our study of the 2021 urology residency application cycle and use of Twitter highlighted distinct differences among matched and unmatched applicants and their respective Twitter analytics, highlighting a potential professional development opportunity offered by social media in underscoring applicants' profiles.

摘要

简介

在 COVID-19 期间,医学和外科部门的临床和研究活动大幅减少,医学生无法参与研究、轮岗和学术会议,这对住院医师匹配产生了重要影响。

方法

使用 Twitter 应用程序编程接口提供的数据,提取了 83000 个特定项目和 28500 个特定申请人的推文进行分析。根据 3 级识别和验证,将泌尿科住院医师申请人确定为匹配或不匹配。通过 Anaconda Navigator 捕获微博的所有元素。主要终点是住院医师匹配,通过与 Twitter 分析(即转发、推文)的相关性进行评估。通过这一过程确定的匹配/不匹配申请人的最终名单与从美国泌尿科协会获得的信息的内部验证进行了交叉参考。

结果

共有 28500 份来自 250 名匹配和 45 名不匹配申请人的英语帖子被纳入分析。匹配的申请人通常具有更高数量的关注者(中位数 171[88-317.5]与 83[42-192],p=0.001)、推文点赞(2.57[1.53-4.52]与 1.5[0.35-3.03],p=0.048)和最近及总稿件(1[0-2]与 0[0-1],p=0.006);1[0-3]与 0[0-1],p=0.016)与不匹配组相比。在多变量分析中,在校正位置、总引用和稿件数量后,女性(OR 4.95)、更多关注者(OR 1.01)、个人推文点赞(OR 1.011)和总推文数量(OR 1.02)增加了整体匹配泌尿科住院医师的几率。

结论

我们对 2021 年泌尿科住院医师申请周期的研究和 Twitter 的使用突出了匹配和不匹配申请人及其各自的 Twitter 分析之间的明显差异,突出了社交媒体在强调申请人个人资料方面提供的潜在专业发展机会。

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