Evidence map›Paper›PMID 42603005›Full record

ArticleJournal of graduate medical education2026

More Signals, Fewer Applications: Calibrating Preference Signaling for Residency Application.

Taylor S Erickson, Stephanie Younan, Steven D Pletcher

Abstract read
In one paragraph

Article in Journal of graduate medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Taylor S Ericksonis a Resident Physician, Department of Otolaryngology-Head & Neck Surgery, University of California, San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0001-5289-4251
Stephanie Younanis a Medical Student, Department of Otolaryngology-Head & Neck Surgery, University of California, San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0009-0003-5253-6392
Steven D Pletcheris a Professor, Vice Chair for Education, and Director, Residency Training Program, Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, and San Francisco VA Medical Center, ENT Section, San Francisco, California, USA.ORCID https://orcid.org/0000-0003-0127-927X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Preference signaling in the residency application process was introduced in the 2021 application cycle and, as of the 2026 residency Match cycle, is used by 27 specialties. Originally intended to help applicants indicate genuine interest in programs, its role has expanded to include mitigating overapplication. Objective: To assess how the number of signals allotted influences application numbers across specialties. Methods: We performed a cross-sectional analysis of US Electronic Residency Application Service (ERAS) data from 22 signaling specialties between 2022 and 2026. Specialties were grouped by number of signals allotted: high (≥20), medium (8-19), low (≤7). The primary outcome was change in average applications per applicant within specialty. The secondary outcome was estimated financial impact using the ERAS tiered fee schedule. Results: Among 70 111 applicants across 22 specialties (high n=6; medium n=8; low n=8), high-signal specialties uniformly reduced applications per applicant (mean, -28.3; range, -47.4 to -2.15). Medium and low tiers showed mixed effects, with an increase in applications per applicant in several specialties. Overall, signaling was associated with an estimated net cost reduction of $7,387,754 across all participating specialties. All high-signal specialties generated cost reduction ($2,991,059 total), whereas 8 medium- and low-signal specialties incurred net cost increases. Conclusions: Substantial reductions in application volume and costs have occurred following implementation of preference signaling, with the high-signal approach reliably leading to a decrease in applications submitted.

Indexed as

Internship and ResidencyPersonnel SelectionCross-Sectional StudiesHumansUnited States

Identifiers

PMID42603005
PMCPMC13475771

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.