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.
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.
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