Identifying Potential Attrition during the Residency Applicant Screening Process Using a Situational Judgment Test

Objective: As USMLE Step 1 moves to pass/fail, residency programs are seeking alternate interview selection processes. Attrition in general surgery is reported as high as 26%. Thus, it is important to ensure that programs are selecting and matching applicants with shared values. Situational judgment tests (SJTs) measure educational and cultural values by posing ambiguous situations and individuals rate the effectiveness of possible reactions. SJTs have previously been shown to identify job applicants with shared values while promoting diversity. Scoring categories are high, moderate, or low values congruence. We sought to explore predictive validity of the SJT relative to program attrition.

Design: Residents who matched into our program between 2018 and 2021 completed the SJT. We tracked attrition.

Setting: UT Health San Antonio, Texas PARTICIPANTS: Fifty-six categorical general surgery residents RESULTS: Per SJT ratings, the numbers of residents who had high, moderate, and low values congruence were 27, 16, and 13, respectively. Attrition numbers for residents who scored high and moderate congruence were similar, indicating that these ratings were indistinguishable. As such, we combined those 2 categories to create a 2 × 2 matrix and used signal detection theory as a framework for analysis. Overall attrition was 16.1% (9/56). Of the 43 residents who scored high or moderate congruence, 90.7% remained in the program. There was a 9.3% chance of attrition for these residents. Of the 13 residents who scored low congruence, 38.5% attrited. While scoring as low congruence on the SJT does not definitively indicate attrition, it does indicate that attrition is 4.14 times more likely for these residents (chi-square, p = 0.0121).

Conclusions: One of the most important aspects of residency applicant selection and interviewing is mitigating risk by identifying applicants who carry a high risk of attrition. The SJT significantly identifies at-risk applicants.