Natural Language Processing of Learners' Evaluations of Attendings to Identify Professionalism Lapses.

ABSTRACT: Unprofessional faculty behaviors negatively impact the well-being of trainees yet are infrequently reported through established reporting systems. Manual review of narrative faculty evaluations provides an additional avenue for identifying unprofessional behavior but is time- and resource-intensive, and therefore of limited value for identifying and remediating faculty with professionalism concerns. Natural language processing (NLP) techniques may provide a mechanism for streamlining manual review processes to identify faculty professionalism lapses. In this retrospective cohort study of 15,432 narrative evaluations of medical faculty by medical trainees, we identified professionalism lapses using automated analysis of the text of faculty evaluations. We used multiple NLP approaches to dev

SUBMITTER: Heath JK 

PROVIDER: S-EPMC10443919 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature