Evidence map›Paper›PMID 42087259›Full record

ReviewAdvances in simulation (London, England)2026

Teaching raters to see: A faculty development innovation for robust assessment in health professions education.

Lon Setnik, Yoon Soo Park, Clément Buleon, Demian Szyld, Jenny Rudolph

Abstract readReview
In one paragraph

Review in Advances in simulation (London, England), 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

5 authors.

Lon SetnikCenter for Medical Simulation, 100 First Avenue Suite 400, Boston, MA, 02129, USA. lsetnik@harvardmedsim.org.
Yoon Soo ParkDepartment of Medical Educatio, University of Illinois College of Medicine, 808 South Wood Street, Chicago, IL, 60612, USA.
Clément BuleonCenter for Medical Simulation, 100 First Avenue Suite 400, Boston, MA, 02129, USA.
Demian SzyldCenter for Medical Simulation, 100 First Avenue Suite 400, Boston, MA, 02129, USA.
Jenny RudolphCenter for Medical Simulation, 100 First Avenue Suite 400, Boston, MA, 02129, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Trustworthy simulation-based assessment depends on capable raters-but current approaches to rater training are often resource-intensive, inconsistently effective, and conceptually muddled. In practice, many programs focus on delivering training activities (e.g., frame-of-reference or behavioral observation training) without a clear model of the steps that build reliable, trustworthy assessments.We clarify the pathway to reliable, trustworthy assessment skills by distinguishing rater cognition-the cognitive work of recognizing, interpreting, and judging performance-from rater training, the educational processes intended to develop that capability. Rating is not a mechanical act of applying a rubric; it is a skilled perceptual and interpretive process. As we argue, a rubric does not do the seeing for you. While rubrics externalize expert judgment, raters must be trained to recognize and apply that expertise-learning to distinguish observable data from inference and to "see through the eyes of the rubric." Traditional rater training approaches can be reframed as mechanisms that build this underlying cognitive skill.Building on this conceptual clarification, we introduce a staged learning framework for rater readiness. Rather than treating training as a one-time intervention, we propose that raters must be prepared developmentally: first through foundational deliberate practice, then through situational application, and finally through expert-facilitated calibration and ongoing feedback.We illustrate this model through a pilot of an interactive, technology-enabled, partially asynchronous rater training program for the Advocacy-Inquiry Rubric. This pilot shows how simulation programs can greatly reduce the time required from experts to train raters, while also demonstrating feasibility, strong usability, and promising reliability outcomes.

Indexed as

Competency-based educationDebriefingDebriefing assessmentDigital rater trainingFaculty developmentMedical education assessmentOnline trainingRater trainingStaged learning

Identifiers

PMID42087259
PMCPMC13289436

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.