Research career development awards (CDAs) facilitate development of clinician-scientists. This study compared the academic achievements of individuals in a structured institutional “pre-K” CDA program, the Mayo Clinic Kern Scholars program, with individuals who applied for but were not admitted to the Kern program (“Kern applicants”), and awardees of other unstructured internal CDAs.

This was a longitudinal cohort study of clinicians engaged in research at Mayo Clinic between 2010 and 2019. The primary outcome was time to the 15th new peer-reviewed publication after the program start, adjusted for baseline number of publications. Secondarily, we described successful awarding of federal funding by the NIH or VA.

The median (IQR) number of baseline publications was highest among Kern Scholars compared to Kern Applicants or other CDA awardees [16 (12, 29) vs 5 (1, 11) and 8 (5, 16); P < 0.001]. After adjustment for baseline publications, the time to 15th new publication was significantly shorter for Kern Scholars than for the two comparator groups (P<0.001). Similar findings were observed with total new publications within 5 years (P < 0.001), as well as number of new first-/last-author publications within 5 years (P < 0.001). The overall frequency of K-awards, R-awards (or equivalent), or any funding were similar between groups, with the exception of R03 awards, which were significantly more common among Kern Scholars (P = 0.002).

The Kern Scholars program is a successful training model for clinician-scientists that demonstrated comparatively greater acceleration of scholarly productivity than other internal CDA programs.

Statistical literacy is essential in clinical and translational science (CTS). Statistical competencies have been published to guide coursework design and selection for graduate students in CTS. Here, we describe common elements of graduate curricula for CTS and identify gaps in the statistical competencies.

We surveyed statistics educators using e-mail solicitation sent through four professional organizations. Respondents rated the degree to which 24 educational statistical competencies were included in required and elective coursework in doctoral-level and master’s-level programs for CTS learners. We report competency results from institutions with Clinical and Translational Science Awards (CTSAs), reflecting institutions that have invested in CTS training.

There were 24 CTSA-funded respondents representing 13 doctoral-level programs and 23 master’s-level programs. For doctoral-level programs, competencies covered extensively in required coursework for all doctoral-level programs were basic principles of probability and hypothesis testing, understanding the implications of selecting appropriate statistical methods, and computing appropriate descriptive statistics. The only competency extensively covered in required coursework for all master’s-level programs was understanding the implications of selecting appropriate statistical methods. The least covered competencies included understanding the purpose of meta-analysis and the uses of early stopping rules in clinical trials. Competencies considered to be less fundamental and more specialized tended to be covered less frequently in graduate courses.

While graduate courses in CTS tend to cover many statistical fundamentals, learning gaps exist, particularly for more specialized competencies. Educational material to fill these gaps is necessary for learners pursuing these activities.

This study examined the effectiveness of a formal postdoctoral education program designed to teach skills in clinical and translational science, using scholar publication rates as a measure of research productivity.

Participants included 70 clinical fellows who were admitted to a master’s or certificate training program in clinical and translational science from 1999 to 2015 and 70 matched control peers. The primary outcomes were the number of publications 5 years post-fellowship matriculation and time to publishing 15 peer-reviewed manuscripts post-matriculation.

Clinical and translational science program graduates published significantly more peer-reviewed manuscripts at 5 years post-matriculation (median 8 vs 5, p=0.041) and had a faster time to publication of 15 peer-reviewed manuscripts (matched hazard ratio = 2.91, p=0.002). Additionally, program graduates’ publications yielded a significantly higher average H-index (11 vs. 7, p=0.013).

These findings support the effectiveness of formal training programs in clinical and translational science by increasing academic productivity.

It is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from ‘fundamental’ (necessary for all) to ‘specialized’ (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized.

We surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by ‘fundamental’ and ‘specialized.’

There were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one’s own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%).

We have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature.