This study aimed to determine whether words used in medical school admissions essays can predict physician empathy.
A 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.
After
correcting for multiple comparisons and controlling for gender, the Jefferson
Scale of Empathy scores significantly correlated with a linguistic topic (
This 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.
Initiatives to improve interpersonal aspects of patient care often forefront the empathy of medical providers.
Teaching empathy has been included in the curriculum of several medical schools. Over the past few decades, educational programs have been initiated with varying degrees of success.
Some medical educators have suggested that empathy should be included as a selection criterion for medical school applicants.
Computational linguistic analysis, a quantitative method of corpus analysis, has been used in recent years to predict health issues such as heart disease mortality at the county level using language from posts on Twitter.
In this study, we aimed to identify the words used in medical school admissions essays that are associated with self-reported physician empathy. The association of language use with physician empathy fills a knowledge gap by determining whether high empathy applicants can be detected through words used in medical school application essays. Our objective was to provide particular words from admissions essays that are most predictive of physician empathy.
We used data from The Jefferson Longitudinal Study of Medical Education, an on-going study that surveys medical students on a yearly basis across a number of topics, including physician empathy.
Research participants included
The study sample comprised 893 (49.5%) men and 912 (50.5%) women, with a mean age of 23.5 years. The gender composition and age of the study sample were similar to the total matriculants in the study period. Due to the reduced reliability of entries with lower word counts, participants must have written at least 500 words in their essays to be included in the sample. The 500-word cut-off also removed applicants from the sample for whom a full personal statement was not required.
Jefferson Scale of Empathy: We used the Jefferson Scale of Empathy (JSE), a 20-item, validated instrument specifically developed to measure empathy in the context of patient care in medical and other health professions students and practitioners. We used the 'S-version' of the JSE, which was developed for administration to medical students. Evidence in support of the JSE's validity and reliability
We used the process of Differential Language Analysis (DLA)
For linguistic feature extraction, we first broke the admissions essays into words using DLATK's tokenizer, which separates sentences into words by spaces or other white space and punctuation.
Based on power analyses for effect sizes of
For correlation analysis, the usage scores for the 20 topics were then treated as independent variables and were then associated with scores on the JSE, which was the dependent variable, using multivariate linear regression. Specifically, ordinary least squares linear regression was used with input variables standardized and with gender included as a covariate since it has been shown to be a significant factor in empathy in previous research.
A linguistic topic was correlated with physician empathy (
This study shows that some language used in medical school application essays predicts physician empathy. This finding could inform medical school admissions contexts, which are increasingly interested in selecting for more empathetic future physicians. Further, the observed linguistic findings provide insight into how empathy is expressed in language by future physicians more generally.
The words that were associated with empathy may suggest a primary focus on the experience of the patient. The top three words associated with empathy in our sample were "health," "patient," and "care." While these findings may seem nonspecific in a sample of students pursuing a career in medicine, they suggest an interest in patients rather than other aspects of medical practice such as technology, financial gain, professional prestige, or career-related motivations. This finding is interesting in the context of healthcare's current emphasis on patient-centered medicine. Where the physician's role was once to dictate a diagnosis and course of treatment, practitioners are now encouraged to understand and address the individual values and needs of patients in clinical contexts.
These language results are in line with several specific findings in the research literature on physician empathy. Empathy in medical students is correlated with sociability,
Our study had several limitations. First, we had a relatively small sample size by linguistic analysis standards. While the study includes 1,805 participants, a larger than average sample size in most educational studies, many studies using computational linguistic analysis involve an order of magnitude more participants (closer to
Language topic correlated with high physician empathy.
Third, while effect sizes are within standard ranges in linguistic analysis studies, they are relatively low in absolute magnitude. These small effect sizes may be due to a self-presentation bias in responses to the empathy scale and within the essays themselves, resulting in a ceiling effect which together may have constrained variance and decreased signal in the language data. In other words, the task of an admissions essay is to represent oneself in the best possible light; therefore, other more spontaneously generated sources of natural language might provide more variance in empathy and should be explored in future studies. Fourth, because our sample included students that were accepted and chose to attend medical school at a single institution, the variation could be limited by admission selection criteria.
Despite these limitations, the present study represents a step toward better understanding and selecting for more empathic medical students. Previous research has shown that there are no formal criteria for readers of medical school personal statements.
Computational linguistic analysis is a method currently used in evaluating job applications at large companies
Empathy assessments have received increasingly widespread attention in medical education. The language findings in the present study shed light on the words correlated with empathy and suggest that physician empathy can be identified in medical school admission essays using these methods. Demonstration of this technological capability to associate empathic orientation with linguistic features is the first step towards admissions committees selecting for more empathetic medical school applicants. Specific language themes identified in this study should be followed by future research to further specify their relationship with empathy. These linguistic insights may impact not only our understanding of physician empathy but inform selection committees responsible for medical student admissions.
Contributors: The authors would like to thank Dr. Elizabeth Y. Brooks, DPM for her enthusiasm and support of this project as well as Dr. Martin E. P. Seligman, PhD.
Funders: This publication was made possible through the support of a grant from the Templeton Religion Trust. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the Templeton Religion Trust. We also thank the Noguchi Medical Research Institute in Tokyo, Japan.
The authors declare that they have no conflict of interest.