Experiential learning methods for biostatistics students: A model for embedding student interns in academic health centres. Issue 1 (25th December 2022)

• Record Type: Journal Article
• Authors: Pomann, Gina‐Maria; Boulware, L. Ebony; Chan, Cliburn; Grambow, Steven C.; Hanlon, Alexandra L.; Neely, Megan L.; Peskoe, Sarah B.; Samsa, Greg; Troy, Jesse D.; Yang, Lexie Zidanyue; Thomas, Samantha M.
• Is Part Of: Stat. Volume 11:Issue 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-25
• Subjects: collaborative biostatistician -- collaboration and consultation -- experiential learning -- internship model -- training biostatisticians; Statistics -- Periodicals; 519.2
• DOI: 10.1002/sta4.506
• Languages: English
• ISSNs: 2049-1573

Abstract

Abstract: This manuscript describes an experiential learning programme for future collaborative biostatisticians (CBs) developed within an academic medical centre. The programme is a collaborative effort between the Biostatistics, Epidemiology, and Research Design (BERD) Methods Core and the Master of Biostatistics (MB) programme, both housed in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine and supported in partnership with the Duke Clinical and Translational Science Institute. To date, the BERD Core Training and Internship Program (BCTIP) has formally trained over 80 students to work on collaborative teams that are integrated throughout the Duke School of Medicine. This manuscript focuses on the setting for the training programme, the experiential learning model on which it is based, the structure of the programme, and lessons learned to date.