Related Experiment Video
Updated: Dec 10, 2025

Utilizing a 3D Printed Laparoscopic Nissen Fundoplication Model to Shorten a Resident's Learning Curve
Published on: August 15, 2025
Unraveling the medical residency selection game
Lokke M Gennissen1, Karen M Stegers-Jager2, Jacqueline de Graaf3,4
1Institute of Medical Education Research Rotterdam (iMERR), Room Ae-227, Erasmus MC, Postbus 2040, 3000 CA, Rotterdam, The Netherlands. L.Gennissen@erasmusmc.nl.
Abstract:
The diversity of modern society is often not represented in the medical workforce. This might be partly due to selection practices. We need to better understand decision-making processes by selection committees in order to improve selection procedures with regard to diversity. This paper reports on a qualitative study with a socio-constructivist perspective conducted in 2015 that explored how residency selection decision-making occurred within four specialties in two regions in the Netherlands. Data included transcripts of the decision-making meetings and of one-on-one interviews with committee members before and after the group decision-making meetings. Candidates struggled to portray themselves favorably as they had to balance playing by the rules and being authentic; between fitting in and standing out. Although admissions committees had a welcoming stance to diversity, their practices were unintentionally preventing them from hiring underrepresented minority (URM) candidates. While negotiating admissions is difficult for all candidates, it is presumably even more complicated for URM candidates. This seems to be having a negative influence on attaining workforce diversity. Current beliefs, which make committees mistakenly feel they are acting fairly, might actually justify biased practices. Awareness of the role of committee members in these processes is an essential first step.
More Related Videos
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
12:18A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Related Concept Videos
Woodward–Hoffmann Selection Rules and Microscopic Reversibility
Analysis of Population Pharmacokinetic Data
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Response Surface Methodology
The process of RSM involves several key steps:
Types of Selection