Details

Autor(en) / Beteiligte

• Yin, Helen L
• Gabrilove, Janice
• Jackson, Rebecca
• Sweeney, Carol
• Fair, Alecia M
• Toto, Robert

Titel

Sustaining the Clinical and Translational Research Workforce: Training and Empowering the Next Generation of Investigators

Ist Teil von

• Academic medicine, 2015-07, Vol.90 (7), p.861-865

Ort / Verlag

United States

Erscheinungsjahr

2015

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• There is mounting concern that clinician-scientists are a vanishing species and that the pipeline for clinical and translational research (CTR) investigators is in jeopardy. For the majority of current junior CTR investigators, the career path involves first obtaining a National Institutes of Health (NIH)-funded K-type career development award, particularly K08 and K23, and subsequently an NIH R01. This transition, popularly referred to as K2R, is a major hurdle with a low success rate and gaps in funding. In this Perspective, the authors identify factors that facilitate K2R transition and important aspects of increasing and sustaining the pipeline of CTR investigators. They also highlight significant differences in success rates of women and those underrepresented in biomedical research. Early career exposure to research methodology, protected time, multidisciplinary mentoring, and institutional "culture shift" are important for fostering and rewarding team science. Mentoring is the single most important contributor to K2R success, and emerging evidence suggests that formal mentor training and team mentoring are effective. Leadership training can empower junior investigators to thrive as independent CTR investigators. Future research should focus on delineating the difference between essential and supplemental factors to achieve this transition, and mentoring methods that foster success, including those that promote K2R transition of women and those underrepresented in biomedical research. The Clinical and Translational Science Awards National Consortium is well positioned to test existing models aimed at shortening the time frame, increasing the rate of K2R transition, and identifying strategies that improve success.