Initiatives to improve interpersonal aspects of patient care often forefront the empathy of medical providers.¹ Empathy has been variously defined, with a rich theoretical and empirical literature.^2-5 In patient care contexts, physician empathy has been defined as a predominantly cognitive attribute to understand patient experiences, combined with a capacity to communicate this understanding to patients, and an intention to help.^6-7 Physician empathy measurably affects patient outcomes. Decades of theoretical and qualitative work in physician empathy preceded the development of quantitative measures of physician empathy,^8-10 such as the Jefferson Scale of Empathy (JSE).^7,11  Illustrative examples of empathy impacting patient outcomes include diabetic patients under the care of more empathic physicians have lower rates of metabolic complications.¹² Diabetic patients who were treated by more empathic physicians show better control of their disease indicated by the results of laboratory tests of glycemic control and cholesterol.¹² More empathic physician communication is also associated with improved patient satisfaction and patient compliance.¹³  Further, medical students with higher empathy do better during their clinical clerkships¹⁴ and are rated as more competent in the patient encounters.¹⁵ In sum, there is good evidence that physician empathy is linked to better patient outcomes and patient satisfaction. Research indicates that both patients and clinicians can benefit from empathic engagement.⁶

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.^16-21 Medical humanities programs have also been implemented with the intention of increasing empathy.²² Despite these initiatives, a significant drop in empathy occurs during the third year of medical school.²³

Some medical educators have suggested that empathy should be included as a selection criterion for medical school applicants.^24,25 Similar proposals have been made to adjust selection criteria for applicants with interest in primary care²⁶ or to favor those with some background in the arts or humanities.²⁷ However, self-reported measures of empathy can be influenced by social desirability response bias. An unobtrusive measure of physician empathy would be ideal, but developing unobtrusive measures presents a methodological challenge. A knowledge gap exists within medical education for measuring traits such as empathy using methods other than self-report.

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.²⁸ A number of demographic and personality characteristics have also been explored using this technique with language from Facebook posts.²⁹ In general, in cases where a link exists between language data and an outcome variable of interest in a given population, then this linguistic analysis method can identify the words that most correlate with scores on a given outcome measure.

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.

A linguistic topic was correlated with physician empathy (r = .074, p < .05), after correcting for multiple comparisons and controlling for gender. This topic consisted of words associated with key features of empathic engagement in patient care, such as "empathy", "understanding," "compassion," "perspective," "caring," and "trust." Figure 1 shows the language topic extracted by linguistic analysis of admission essays that were significantly correlated with scores on the JSE.

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.³⁸ Further research might explore how teaching patient-centered approaches to medicine impact the empathy of medical students in their clinical training. The other words associated with high empathy scores also reflect key components of empathic engagement in patient care such as "understanding," "compassion," "human," "feeling," "knowledge," and "trust." In general, our findings provide further support for current characterizations of empathy in healthcare as a cognitive attribute that involves understanding of patient's experiences, coupled with compassionate concern to minimize suffering.

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,³⁸ emotional intelligence,³⁹ and conscientiousness.⁴⁰ Empathic concern has been linked to prosocial behaviors such as higher rates of organ donation.⁴¹ More empathic healthcare practitioners also have more positive attitudes toward integrative care, and cooperative attitudes towards one another.⁴² Medical students nominated by their classmates for excellence in clinical competence had higher than average empathy scores.⁴³ More empathic medical students also tended to choose people-oriented over technology-oriented specialties.⁴⁴ These findings complement the language results in the present study by suggesting a link between higher levels of empathy and an orientation towards others, compassionate concern, and emotional intelligence.

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 N = 10,000). Second, this study was conducted at a single private medical school in the northeast of the United States, so care should be taken when generalizing beyond this context, especially in regard to the international medical education community.

Figure 1. Language topic correlated with high physician empathy. This linguistic topic positively correlated with scores on the Jefferson Empathy Scale (r = .074, p < .05). Note that the larger size of the words indicates a higher correlation strength.

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.⁴⁵ In one study, ratings of personal statements had no predictive validity for future success.⁴⁶ For these reasons, some have suggested that a more quantitative assessment should complement the essay reading process.⁴⁷ While most self-report measures are subject to social desirability bias, linguistic analysis offers one method of bypassing some of these demand characteristics, particularly if applicants are not aware of the traits being considered or the language models that are associated with them.

Computational linguistic analysis is a method currently used in evaluating job applications at large companies⁴⁸ and may soon be used for admissions purposes in many academic contexts. Computational linguistic models are capable of predicting scores related to a variety of outcome measures based on language alone.⁴⁹ In other words, our findings suggest that an empathy score could, through future linguistic modeling and validation work, be automatically generated for each medical school admissions essay using this technology.

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.