Assessment of Gender-Based Linguistic Differences in Physician Trainee Evaluations of Medical Faculty Using Automated Text Mining

• Published in: JAMA network open 2019-05, Vol.2 (5), p.e193520-e193520
• Main Authors: Heath, Janae K, Weissman, Gary E, Clancy, Caitlin B, Shou, Haochang, Farrar, John T, Dine, C Jessica
• Format: Article
• Language: English
• Subjects: Academic Medical Centers - statistics & numerical data; Adult; Automation; Cohort Studies; Data Mining; Education, Medical, Graduate - standards; Education, Medical, Graduate - statistics & numerical data; Faculty, Medical - standards; Female; Gender; Humans; Linguistics; Longitudinal Studies; Male; Medical Education; Middle Aged; Online Only; Original Investigation; Pennsylvania; Physicians, Women - psychology; Physicians, Women - standards; Physicians, Women - statistics & numerical data; Professional Competence - standards; Professional Competence - statistics & numerical data; Retrospective Studies; Sexism - statistics & numerical data; Students, Medical - psychology; Young Adult
• ISSN: 2574-3805; 2574-3805
• DOI: 10.1001/jamanetworkopen.2019.3520

Women are underrepresented at higher ranks in academic medicine. However, the factors contributing to this disparity have not been fully elucidated. Implicit bias and unconscious mental attitudes toward a person or group may be factors. Although academic medical centers use physician trainee evaluations of faculty to inform promotion decisions, little is known about gender bias in these evaluations. To date, no studies have examined narrative evaluations of medical faculty by physician trainees for differences based on gender. To characterize gender-associated linguistic differences in narrative evaluations of medical faculty written by physician trainees. This retrospective cohort study included all faculty teaching evaluations completed for the department of medicine faculty by medical students, residents, and fellows at a large academic center in Pennsylvania from July 1, 2015, through June 30, 2016. Data analysis was performed from June 1, 2018, through July 31, 2018. Word use in faculty evaluations was quantified using automated text mining by converting free-text comments into unique 1- and 2-word phrases. Mixed-effects logistic regression analysis was performed to assess associations of faculty gender with frequencies of specific words and phrases present in a physician trainee evaluation. A total of 7326 unique evaluations were collected for 521 faculty (325 men [62.4%] and 196 women [37.6%]). The individual words art (odds ratio [OR], 7.78; 95% CI, 1.01-59.89), trials (OR, 4.43; 95% CI, 1.34-14.69), master (OR, 4.24; 95% CI, 1.69-10.63), and humor (OR, 2.32; 95% CI, 1.44-3.73) were significantly associated with evaluations of male faculty, whereas the words empathetic (OR, 4.34; 95% CI, 1.56-12.07), delight (OR, 4.26; 95% CI, 1.35-13.40), and warm (OR, 3.45; 95% CI, 1.83-6.49) were significantly associated with evaluations of female faculty. Two-word phrases associated with male faculty evaluations included run rounds (OR, 7.78; 95% CI, 1.01-59.84), big picture (OR, 7.15; 95% CI, 1.68-30.42), and master clinician (OR, 4.02; 95% CI, 1.21-13.36), whereas evaluations of female faculty were more likely to be associated with model physician (OR, 7.75; 95% CI, 1.70-35.39), just right (OR, 6.97; 95% CI, 1.51-32.30), and attention (to) detail (OR, 4.26; 95% CI, 1.36-13.40). The data showed quantifiable linguistic differences between free-text comments about male and female faculty in physician trainee evaluations. Further evaluation of these differences,