Evidence map›Paper›PMID 32949231›Full record

ArticleInternational journal of medical education2020

Linguistic analysis of empathy in medical school admission essays.

Mary Yaden, David Yaden, Anneke Buffone, Johannes Eichstaedt, Patrick Crutchley, Laura Smith, Jonathan Cass, Clara Callahan, Susan Rosenthal, Lyle Ungar and 2 more

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Article in International journal of medical education, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Mary YadenDepartment of Psychiatry at the University of Pennsylvania, Philadelphia, PA, USA.
David YadenDepartment of Psychiatry and Behavioral Sciences at Johns Hopkins Medicine, Baltimore, MD, USA.
Anneke BuffoneDepartment of Psychology at the University of Pennsylvania, Philadelphia, PA, USA.
Johannes EichstaedtDepartment of Psychology at the University of Pennsylvania, Philadelphia, PA, USA.
Patrick CrutchleyDepartment of Psychology at the University of Pennsylvania, Philadelphia, PA, USA.
Laura SmithDepartment of Psychology at the University of Pennsylvania, Philadelphia, PA, USA.
Jonathan CassSidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA.
Clara CallahanSidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA.
Susan RosenthalSidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA.
Lyle UngarDepartment of Computer and Information Science at the University of Pennsylvania, Philadelphia, PA, USA.
Andrew SchwartzDepartment of Computer Science at Stony Brook University, Stony Brook, New York, USA.
Mohammadreza HojatSidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA.

Funding

Educating Physician Scientists in Psychiatry (EPSP): Firing up the next generation of translational and clinical neuroscientistsR25MH119043 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Mariella De Biasi, MATTHEW S KAYSER · 2019 to 2026
$1.6M
NIMH NIH HHS R25 MH119043
6 · The paper itself

Abstract

objectivesThis study aimed to determine whether words used in medical school admissions essays can predict physician empathy.

methodsA computational form of linguistic analysis was used for the content analysis of medical school admissions essays. Words in medical school admissions essays were computationally grouped into 20 'topics' which were then correlated with scores on the Jefferson Scale of Empathy. The study sample included 1,805 matriculants (between 2008-2015) at a single medical college in the North East of the United States who wrote an admissions essay and completed the Jefferson Scale of Empathy at matriculation.

resultsAfter correcting for multiple comparisons and controlling for gender, the Jefferson Scale of Empathy scores significantly correlated with a linguistic topic (r = .074, p < .05). This topic was comprised of specific words used in essays such as "understanding," "compassion," "empathy," "feeling," and "trust." These words are related to themes emphasized in both theoretical writing and empirical studies on physician empathy.

conclusionsThis study demonstrates that physician empathy can be predicted from medical school admission essays. The implications of this methodological capability, i.e. to quantitatively associate linguistic features or words with psychometric outcomes, bears on the future of medical education research and admissions. In particular, these findings suggest that those responsible for medical school admissions could identify more empathetic applicants based on the language of their application essays.

Indexed as

EmpathySchool Admission CriteriaSchools, MedicalEducation, MedicalFemaleHumansLinguisticsMalePhysiciansStudents, MedicalWritingYoung Adultadmissionempathylinguistic analysismedical educationpatient-centered care

Identifiers

PMID32949231
PMCPMC7882128

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