Practical Tips for Undergraduate Medical Education Advisors in Residency Application Signaling.

Abstract

The residency application process has become increasingly complex for medical students and advisors to navigate. Program signaling was piloted to improve applicants' abilities to obtain interview offers at programs they were strongly interested in. The initial positive results led to expansion of signaling to additional specialties over the next two application cycles. Despite the benefits of program signaling, the variation in signaling practices among specialties has presented challenges for both advisors and students when determining how to best allocate signals. The aim of this study is to identify students' perceptions of the signaling process, how this may impact outcomes, and to guide future educational programming. This is an exploratory original survey study of students in a US allopathic medical school applying in ERAS for the 2023 residency cycle. The survey was developed to determine students' understanding of how programs would use signals in the application process and assess strategies students used to allocate signals. We compared program signals to student interview offers and match outcomes using descriptive statistics. 57 of 96 eligible students completed the survey. 51% signaled a range of programs based on their perceived competitiveness for the program while 40% signaled programs of interest regardless of perceived competitiveness. 53% of students thought sending a signal would increase their chance of an interview, while 42% were unsure how the signal would be used by residency programs. Students received interviews at 49% of the programs signaled, which increased to 56.5% when specialties offering more than 7 signals were excluded. 35% of students matched at a signaled program. Students' perceptions and strategies related to the signaling process are varied and may impact interview offers. Advisors should monitor and review internal institutional trends to help inform future educational programming to optimize signal allocation for their students.