First Year Medical Student Peer Nominations of Professionalism: A Methodological Detective Story about Making Sense of Non-Sense.
Journal Article (Journal Article)
This article explores the assessment of professionalism within a cohort of medical students during a sequential 13-week medical school histology and anatomy course. Across seven data points, students were asked to identify a professionalism role model from amongst their peers and to score Likert-structured rationales for their decision. Based on density scores, an initial social network analysis identified six peer-nomination "stars." However, analysis of these stars revealed considerable variability and random-like "noise" in both the nomination and explanation data sets. Subsequent analyses of both data sets explored the possibility of underlying patterns in this noise using tests of reliability, principal components factor analysis, and fixed-effects regression analysis. These explorations revealed the presence of two dimensions (professional vs. supportive) in how students sought to explain their nomination decisions. Although data variability remained quite high, significantly less variability was present in the professional than in the supportive dimension, suggesting that academic helpfulness rationales are both empirically distinct and more mutable than rationales grounded in professionalism-related factors. In addition, data showed that the greater the stability in one's choice of a professionalism role model nomination over the T1-T7 data periods, the more stable one's reasons for that nomination-both for professionalism and supportive dimensions. Results indicate that while peer assessment of professionalism by first-year medical students may not be very reliable, students can differentiate between more personal and professional factors, even at this early stage in their professional development. Formal instruction within the pre-clinical curriculum should recognize and address this distinction. Anat Sci Educ. © 2018 American Association of Anatomists.
- Mullikin, TC; Shahi, V; Grbic, D; Pawlina, W; Hafferty, FW
- January 2019
Volume / Issue
- 12 / 1
Start / End Page
- 20 - 31
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)
- United States