Applying the Nedelsky Defensible Standard Setting Method in Undergraduate Obstetrics and Gynecology Assessment: A...

Defensible standard setting is a cornerstone of competency-based medical education. However, many institutions still use arbitrary pass marks such as 50% without empirical justification. This study aimed to apply the Nedelsky method-a defensible, criterion-referenced standard setting approach-to determine the minimal passing score for the final examination of the Obstetrics and Gynecology (OBGYN) course at Pham Ngoc Thach University of Medicine, Vietnam, and to compare it with the conventional Cohen method.

A four-step Nedelsky procedure was implemented to establish a defensible passing standard for a 50-item multiple-choice examination administered to fourth-year medical students on December 3, 2022. Three trained assessors independently estimated the number of distractors that a minimally competent candidate (MCC) could eliminate for each question, from which the Minimal Passing Level (MPL) was calculated. Subsequently, a cross-sectional analysis was conducted on 808 students to determine the pass and fail rates using both Nedelsky and Cohen methods. Statistical comparison was performed using the McNemar's test for paired categorical data.

The mean MPL derived from three assessors was 65%, corresponding to 33 correct answers as the passing score. According to this standard, 183 of 808 students (23%) passed the examination, while 625 (77%) failed. In contrast, using the Cohen method (cut-off = 55%), 416 students (51%) failed. McNemar's test showed a statistically significant difference between the two methods (χ² = 207.0, p < 0.001), with moderate agreement (Cohen's κ = 0.47).

The relative Cohen method underestimated the minimal competency threshold, resulting in a substantial "failure to fail" phenomenon. The Nedelsky method provided a more defensible, transparent, and evidence-based approach for setting pass standards in resource-limited medical education contexts. Adoption of defensible standard setting methods such as Nedelsky can enhance fairness, validity, and accountability in competency-based assessments.