Evidence map›Paper›PMID 41555889›Full record

ArticleMedical science educator2025

Understanding Score Trends in Clinical Science Subject Exams: A Longitudinal Study.

Francis O'Donnell, Irina Grabovsky, Annie Kochersberger

Abstract read
In one paragraph

Article in Medical science educator, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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.

Francis O'DonnellNBME, Philadelphia, PA USA.ORCID 0000-0002-2742-3439
Irina GrabovskyNBME, Philadelphia, PA USA.ORCID 0000-0002-3695-0572
Annie KochersbergerNBME, Philadelphia, PA USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The purpose of this study was to analyze performance on Clinical Science Subject Exams from academic years 2018-2019 through 2020-2021, across a large national sample of medical schools, to identify score trends and assess the impact of the COVID-19 pandemic on exam performance. Methods: Using descriptive statistics, data visualization, and a series of multilevel models, we investigated patterns for neurology, family medicine, internal medicine, obstetrics and gynecology, pediatrics, psychiatry, and surgery. The analysis sample ranged from 36,791 to 54,770 examinees across specialties. Results: In 2018-2019, Subject Exam scores for almost all specialties followed a pattern of gradual increase as the academic year progressed. The average score was 2 to 3 points higher in May than in August of the previous calendar year for pediatrics, family medicine, internal medicine, and surgery. The averages for psychiatry and neurology also partially followed this trend. Patterns were somewhat more varied in Spring 2020 and Spring 2021. Despite some disruptions, the largest differences in average scores were around two points on the 0-100 scale. There were no major and sustained decreases. Conclusion: Scores remained relatively stable over the three academic years studied, with small and intermittent score pattern disruptions appearing after March 2020. These disruptions included both higher-than-expected increases and decreases. Possible explanations include the intermittent nature of COVID-19 surges as well as changes in clerkship structure and resources. Scores did not decrease across the board, indicating a level of stability in exam performance despite the challenges posed by the pandemic. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-025-02458-w.

Indexed as

Clerkship assessmentClinical Science Subject ExamsCOVID-19 pandemicLongitudinalMultilevel models

Identifiers

PMID41555889
PMCPMC12812130

What OpenQuestion holds

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Registered trials

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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.