Development of a taxonomy of unprofessional behavior in clinical learning environments using learner-generated critical incidents

Purpose: Few studies have examined medical residents’ and fellows’ (trainees) direct experience of unprofessional behavior in clinical learning environments (CLE). The purpose of this study was to create a taxonomy of unprofessional behavior in CLEs using critical incidents gathered from trainees. Method: In step 1 (data collection), the authors collected 382 critical incidents from trainees at more than a dozen CLEs over a six-year period (2013–2019). In step 2 (model generation), nine subject matter experts (SMEs) sorted the incidents into homogenous clusters and this structure was tested with principal components analysis (PCA). In step 3 (model evaluation), two new groups of SMEs each re-sorted half of the incidents into the PCA-derived categories. Results: A 13-component solution accounted for 62.46% of the variance in the critical incidents collected. The SMEs who re-sorted the critical incidents demonstrated good agreement with each other and with the 13-component PCA solution. The resulting taxonomy included 13 dimensions, with 48.7% of behaviors focused on displays of aggression or discriminatory conduct. Conclusions: Critical incident methodology can provide unique insights into the dimensionality of unprofessional behavior in the CLE. Future research should leverage the taxonomy created to inform professionalism assessment development in the CLE.