a Department of Human Oncology , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA.
b Department of Radiation Oncology , H. Lee Moffitt Cancer Center and Research Institute , Tampa , FL , USA.
Med Educ Online. 2018 Dec;23(1):1489691. doi: 10.1080/10872981.2018.1489691.
The Charting Outcomes resource is useful in gauging an applicant's competiveness for a given specialty. However, many variables are not reported in Charting Outcomes that may influence an applicant's ability to match. A significant proportion of applicants record their experiences in an anonymous, self-reported applicant spreadsheet. We analyzed factors associated with a successful match using this dataset to test the hypothesis that research productivity and high academic performance correlates with success rates. A retrospective analysis of "RadOnc Interview Spreadsheet" for the 2015, 2016, and 2017 radiation oncology match was performed. Data were accessed via studentdoctor.net. Board scores, research characteristics, Sub-I participation, and interview invitation rates were available. Mann-Whitney U, Kruskal-Wallis, and chi-square tests were used for statistical analysis. When possible, results were compared to those reported in the National Residency Match Program's "Charting Outcomes" report. A total of 158 applicants were examined for the applicant characteristics. Applicants applied to a median of 61 programs and received a median of 14 interviews. The mean step 1 score was 248 (range: 198 to 272) and most were in the highest grade point average quartile (68.3%). 21.7% participated in additional research year(s), and 19% obtained a PhD. The majority of applicants took three radiation oncology electives (48.7%). On multivariate analysis, alpha-omega-alpha (AOA) honors society status (p=0.033), participating in a research year (p=0.001) and number of journal publications (p=0.047) significantly correlated with higher interview invitation rates. In summary, this study identifies important considerations for radiation oncology applicants that have not been previously reported, such as induction into AOA and number of journal publications.
图表结果资源可用于评估申请人在特定专业中的竞争力。然而,图表结果中并未报告许多可能影响申请人匹配能力的变量。很大一部分申请人在匿名的自我报告的申请人电子表格中记录他们的经历。我们使用此数据集分析与成功匹配相关的因素,以检验研究生产力和高学业成绩与成功率相关的假设。对 2015 年、2016 年和 2017 年放射肿瘤学匹配的“RadOnc 面试电子表格”进行了回顾性分析。通过 studentdoctor.net 访问数据。可获得成绩、研究特征、次实习参与和面试邀请率。使用 Mann-Whitney U、Kruskal-Wallis 和卡方检验进行统计分析。在可能的情况下,将结果与全国住院医师匹配计划的“图表结果”报告中的结果进行比较。共检查了 158 名申请人的申请人特征。申请人平均申请了 61 个项目,平均收到 14 个面试邀请。第 1 步的平均分数为 248(范围:198 至 272),大多数申请人在最高平均绩点四分位数(68.3%)中。21.7%的人参加了额外的研究年,19%的人获得了博士学位。大多数申请人参加了三门放射肿瘤学选修课程(48.7%)。多元分析显示,阿尔法欧米伽阿尔法(AOA)荣誉学会身份(p=0.033)、参加研究年(p=0.001)和期刊出版物数量(p=0.047)与更高的面试邀请率显著相关。总之,这项研究确定了放射肿瘤学申请人以前未报告的重要考虑因素,例如 AOA 入会和期刊出版物数量。