Sarah J Greeven, Andrew M Medellin, Janette M Watkins, Cassandra J Coble, Julia E Brunnemer, Paola A Fernández Solá, Sandeep Dutta, James M Hobson, Justin M Evanovich, Vanessa M Martinez Kercher, Kyle A Kercher
Multilevel needs assessment of physical activity, sport, psychological needs, and nutrition in rural children and adults
Frontiers in public health
increasing interest understanding potential bias medical education used natural language processing nlp evaluate potential bias clinical clerkship evaluations data medical evaluations administrative databases medical students enrolled thirdyear clinical clerkship rotations across two academic years collected demographic information students faculty evaluators determine genderracial concordance ie whether student faculty identified demographic used multinomial loglinear model final clerkship grades using predictors numerical evaluation scores genderracial concordance sentiment scores narrative evaluations using sentimentintensityanalyzer tool python 2037 evaluations 198 students analyzed statistical significance defined p 005 sentiment scores evaluations vary significantly student gender race ethnicity p 088 064 006 respectively word choices similar across faculty student demographic groups modeling showed narrative evaluation sentiment scores predictive honors grade odds ratio 123 p 058 numerical evaluation average 145 p 0001 gender concordance faculty student 132 p 0049 significant predictors receiving honors lack disparities narrative text study contrasts prior findings institutions ongoing efforts include comparative analyses institutions understand institutional factors may contribute bias nlp enables systematic approach investigating bias insights gained lack association word choices sentiment scores final grades show potential opportunities improve feedback processes students