A Linguistic Analysis of United States Navy Orthopaedic Surgery Applicant Personal Statements

Author:

Colon-Morillo Reinaldo E1ORCID,Chennupati Nithya1,Tompane Trevor1,Healy Nicholas1,Janney Cory1

Affiliation:

1. Naval Medical Center San Diego , San Diego, CA 92134, USA

Abstract

ABSTRACT Introduction Despite the importance of linguistic analysis, no systematic research has been explored in the form of linguistic analysis on personal statements for military orthopedic surgery residency programs. This study was conducted to analyze U.S. Navy (USN) orthopedic surgery applicants’ personal statements using an automated textual analysis program to assess personal statements for linguistic styles. Methods A retrospective analysis of USN orthopedic applicant personal statements from application years 2016 to 2019 was performed utilizing the Linguistic Inquiry and Word Count (LIWC) software. LIWC analyzed the text for summary variables: analytical thinking, clout, authenticity, and emotional tone. We compared this analysis with Step 1 and Step 2 scores and determined whether an applicant matched. Results A total of 94 personal statements (60,230 words) were analyzed using LIWC. The average word count was 640.7, with an average of 23 words per sentence. The average-matched applicant USMLE Step 1 and Step 2 scores were 240 and 250, respectively. When examining summary traits utilizing multiple logistic regression analysis, only analytical thinking demonstrated a statistically significant difference in matched versus unmatched applicants with a P = .011 (OR = 1.10). Conclusion As the USMLE Step 1 exam transitions from a scoring system to Pass/Fail grading, programs will look at other characteristics to determine who would likely succeed in residency. From a linguistic analysis standpoint, matched applicants’ personal statements demonstrated higher analytical thinking, clout, affiliation, power, and risk focus than unmatched applicants. Unmatched applicants demonstrated higher authenticity than matched applicants.

Publisher

Oxford University Press (OUP)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3