Journal of Otolaryngology - Head and Neck Surgery (Apr 2017)
Does medical school research productivity predict a resident’s research productivity during residency?
Abstract
Abstract Background Research productivity is an important component of the CanMEDS Scholar role and is an accreditation requirement of Canadian Otolaryngology training programs. Our objective was to determine if an association exists between publication rates before and during Otolaryngology residency. Methods We obtained the names for all certified Canadian Otolaryngologists who graduated between 1998 and 2013 inclusive, and conducted a Medline search for all of their publications. Otolaryngologists were subgrouped based on year of residency graduation and the number of articles published pre-residency and during residency (0 or ≥1). Chi-squared analyses were used to evaluate whether publications pre-residency and year of graduation were associated with publications during residency. Results We obtained data for 312 Canadian Otolaryngologists. Of those 312 graduates, 46 (14.7%) had no identifiable publications on PubMed and were excluded from the final data analysis. Otolaryngology residents had a mean 0.65 (95% CI 0.50-0.80) publications before residency and 3.35 (95% CI 2.90-3.80) publications during residency. Between 1998 and 2013, mean publication rates before and during residency both increased significantly (R 2 = 0.594 and R 2 = 0.759, respectively), whereas publication rates after residency graduation has stagnated (R 2 = 0.023). The odds of publishing during residency was 5.85 times higher (95% CI 2.69-12.71) if a resident published prior to residency (p < 0.0001). The Spearman correlation coefficient between publications before and during residency is 0.472 (p < 0.0001). Conclusion Residents who publish at least one paper before residency are nearly six times as likely to publish during residency than those who did not publish before residency. These findings may help guide Otolaryngology program selection committees in ranking the best CaRMS candidates.
Keywords