How Prominent Is Score Inflation, Gender, and Racial Bias in Orthopaedic Surgery Residency Recommendation Letters? A Systematic Review

Robert J. Burkhart, Monish S. Lavu, Christian J. Hecht II, Jason G. Ina, Robert J. Gillespie, Raymond W. Liu
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However, disparate and inconsistent findings have made it difficult to draw meaningful conclusions from individual studies on the SLOR and narrative letter of recommendation.\n \n \n \n In this systematic review we asked: (1) What is the distribution of applicant SLOR rating among nine domains and summative scores? (2) Are there applicant characteristics associated with SLOR ratings? (3) Is there gender and racial bias in the SLOR and narrative letter of recommendation?\n \n \n \n PubMed, EBSCO, and Google Scholar electronic databases were queried on March 20, 2023, to identify all studies evaluating SLOR and narrative letter of recommendations between January 1, 2017, and March 20, 2023. Articles that evaluated orthopaedic SLOR or narrative LORs were included. Systematic reviews, case reports, duplicate studies between databases, and grey literature such as abstracts and articles on preprint servers were excluded. Eight studies including 6179 applicants and 18,987 letters of recommendation were included in the final analysis. The applicant classes ranged from years 2014 to 2020. Two reviewers independently evaluated the quality of the included studies using the Joanna Briggs Institute (JBI) tool for cross-sectional studies. The mean JBI score of included studies was 7.4 out of a maximum of 8, with higher scores indicating better quality. The primary outcome was to determine the distribution of applicant SLOR rankings in their summative score. Summative scores were separated into ranked to match, top one-third, middle one-third, lower one-third, and not a fit. Four studies reported the summative SLOR scores of applicants. Our secondary study goal was to assess applicant characteristics associated with SLOR summative scores and assess any bias present in the SLOR or narrative recommendation. Five studies compared SLOR ratings across applicant characteristics including gender, race, USMLE Step 1 score, USMLE Step 2 score, Alpha Omega Alpha (AΩA) membership, clerkship grades, and publications. Gender and racial bias were also assessed across five studies. Four studies utilized a linguistic analysis software to search letters of recommendation for differences in word category use by gender and race.\n \n \n \n Studies consistently found that a higher percentage of candidates were identified in the top percentile blocks than is mathematically possible. For example, the two studies that tallied the proportion of candidates ranking in the top 10% of applicants found that 36% and 42% were rated as being in the top 10%. Similarly, articles found more than 87% of applicants scored in the top one-third. Studies had mixed results, but in general, they suggested that AΩA status, higher Step 1 scores, and more research publications have a slightly positive association with increased SLOR scores. We found no evidence of gender bias against women, and in fact, most studies evaluating word choices found word choices for women candidates generally were stronger. Similarly, no consistent disparities were identified in word categories utilized in SLORs based on applicant race.\n \n \n \n Most notably, a mathematically impossible proportion of applicants were counted in the top percentiles in letters of recommendation. This compromises readers’ abilities to differentiate candidates. Factors like AOA status and research publications displayed a modest positive correlation with SLOR scores. 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Abstract

Letters of recommendation are considered an important factor in the holistic ranking of orthopaedic residency applications. The standardized letter of recommendation (SLOR) was introduced in 2017 in response to the inherent bias and limited comparative value of traditional LORs. It includes standardized questions about an applicant’s orthopaedic qualifications, designed to enable fair comparisons among candidates. However, disparate and inconsistent findings have made it difficult to draw meaningful conclusions from individual studies on the SLOR and narrative letter of recommendation. In this systematic review we asked: (1) What is the distribution of applicant SLOR rating among nine domains and summative scores? (2) Are there applicant characteristics associated with SLOR ratings? (3) Is there gender and racial bias in the SLOR and narrative letter of recommendation? PubMed, EBSCO, and Google Scholar electronic databases were queried on March 20, 2023, to identify all studies evaluating SLOR and narrative letter of recommendations between January 1, 2017, and March 20, 2023. Articles that evaluated orthopaedic SLOR or narrative LORs were included. Systematic reviews, case reports, duplicate studies between databases, and grey literature such as abstracts and articles on preprint servers were excluded. Eight studies including 6179 applicants and 18,987 letters of recommendation were included in the final analysis. The applicant classes ranged from years 2014 to 2020. Two reviewers independently evaluated the quality of the included studies using the Joanna Briggs Institute (JBI) tool for cross-sectional studies. The mean JBI score of included studies was 7.4 out of a maximum of 8, with higher scores indicating better quality. The primary outcome was to determine the distribution of applicant SLOR rankings in their summative score. Summative scores were separated into ranked to match, top one-third, middle one-third, lower one-third, and not a fit. Four studies reported the summative SLOR scores of applicants. Our secondary study goal was to assess applicant characteristics associated with SLOR summative scores and assess any bias present in the SLOR or narrative recommendation. Five studies compared SLOR ratings across applicant characteristics including gender, race, USMLE Step 1 score, USMLE Step 2 score, Alpha Omega Alpha (AΩA) membership, clerkship grades, and publications. Gender and racial bias were also assessed across five studies. Four studies utilized a linguistic analysis software to search letters of recommendation for differences in word category use by gender and race. Studies consistently found that a higher percentage of candidates were identified in the top percentile blocks than is mathematically possible. For example, the two studies that tallied the proportion of candidates ranking in the top 10% of applicants found that 36% and 42% were rated as being in the top 10%. Similarly, articles found more than 87% of applicants scored in the top one-third. Studies had mixed results, but in general, they suggested that AΩA status, higher Step 1 scores, and more research publications have a slightly positive association with increased SLOR scores. We found no evidence of gender bias against women, and in fact, most studies evaluating word choices found word choices for women candidates generally were stronger. Similarly, no consistent disparities were identified in word categories utilized in SLORs based on applicant race. Most notably, a mathematically impossible proportion of applicants were counted in the top percentiles in letters of recommendation. This compromises readers’ abilities to differentiate candidates. Factors like AOA status and research publications displayed a modest positive correlation with SLOR scores. Gender bias against women or candidates from racial minority groups was not evident. We suggest that group SLOR authorship, with a consensus assessment by clerkship or residency directors, should be considered. We also recommend the incorporation of mean and SD scores for each letter writer (or group) alongside their letters. Furthermore, studies indicate that submitting all four SLOR letters can substantially improve an applicant’s chances of success. We advise students to choose strategically and submit the maximum allowable number of SLORs.
矫形外科住院医师推荐信中的分数膨胀、性别和种族偏见有多严重?系统回顾
推荐信被认为是骨科住院医师申请综合排名的一个重要因素。针对传统推荐信固有的偏见和有限的比较价值,2017 年推出了标准化推荐信(SLOR)。它包括有关申请人骨科资质的标准化问题,旨在实现候选人之间的公平比较。然而,由于研究结果存在差异和不一致,因此很难从有关 SLOR 和叙述性推荐信的单项研究中得出有意义的结论。 在本系统综述中,我们提出了以下问题:(1) 申请人的 SLOR 评级在九个领域和总分中的分布情况如何? (2) SLOR 评级是否与申请人的特征相关?(3) SLOR 和叙述性推荐信中是否存在性别和种族偏见? 于 2023 年 3 月 20 日查询了 PubMed、EBSCO 和 Google Scholar 电子数据库,以确定 2017 年 1 月 1 日至 2023 年 3 月 20 日期间评估 SLOR 和叙述性推荐信的所有研究。纳入了评估骨科 SLOR 或叙述性 LOR 的文章。系统综述、病例报告、数据库间的重复研究以及灰色文献(如摘要和预印本服务器上的文章)均被排除在外。最终分析纳入了 8 项研究,包括 6179 名申请人和 18987 封推荐信。申请人类别从 2014 年到 2020 年不等。两位审稿人使用乔安娜-布里格斯研究所(Joanna Briggs Institute,JBI)的横断面研究工具对纳入研究的质量进行了独立评估。纳入研究的平均 JBI 得分为 7.4 分(满分为 8 分),得分越高表示质量越好。主要研究结果是确定申请者 SLOR 在总分中的排名分布。汇总得分分为匹配、前三分之一、中间三分之一、后三分之一和不匹配。有四项研究报告了申请人的 SLOR 总分。我们的次要研究目标是评估与 SLOR 总分相关的申请人特征,并评估 SLOR 或叙述性推荐中存在的任何偏差。有五项研究比较了不同申请人特征的 SLOR 评分,包括性别、种族、USMLE 第 1 步分数、USMLE 第 2 步分数、Alpha Omega Alpha (AΩA) 会员资格、实习成绩和发表的论文。五项研究还对性别和种族偏见进行了评估。四项研究利用语言分析软件搜索推荐信,以发现不同性别和种族在用词类别上的差异。 研究一致发现,在前百分位数区块中被识别的候选人比例高于数学上的可能比例。例如,有两项研究统计了申请者中排名前 10%的候选人比例,发现分别有 36% 和 42% 的候选人被评为前 10%。同样,有文章发现超过 87% 的申请人得分在前三分之一。研究结果不一,但总的来说,这些研究表明,AΩA 身份、更高的步骤 1 分数和更多的研究论文与 SLOR 分数的增加略有正相关。我们没有发现对女性有性别偏见的证据,事实上,大多数对选词进行评估的研究发现,女性考生的选词一般都更强。同样,在 SLOR 中使用的词语类别中,也没有发现基于申请人种族的一致差异。 最值得注意的是,在推荐信中,在数学上不可能有一定比例的申请人被计入最高百分位数。这影响了读者区分候选人的能力。AOA资格和研究论文等因素与SLOR分数呈适度正相关。针对女性或少数民族候选人的性别偏见并不明显。 我们建议,应考虑由实习医生或住院医生主任对 SLOR 作者进行集体评估,并达成共识。我们还建议将每位写信者(或每组)的平均分和 SD 分与他们的信件放在一起。此外,研究表明,提交所有四封 SLOR 信件可大大提高申请人的成功机会。我们建议学生有策略地选择并提交允许的最大数量的 SLOR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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