Essential team science skills for biostatisticians on collaborative research teams
Open accessAbstract
Introduction: Despite the critical role that quantitative scientists play in biomedical research, graduate programs in quantitative fields often focus on technical and methodological skills, not on collaborative and leadership skills. In this study, we evaluate the importance of team science skills among collaborative biostatisticians for the purpose of identifying training opportunities to build a skilled workforce of quantitative team scientists. Methods: Our workgroup described 16 essential skills for collaborative biostatisticians. Collaborative biostatisticians were surveyed to assess the relative importance of these skills in their current work. The importance of each skill is summarized overall and compared across career stages, highest degrees earned, and job sectors. Results: Survey respondents were 343 collaborative biostatisticians spanning career stages (early: 24.2%, mid: 33.8%, late: 42.0%) and job sectors (academia: 69.4%, industry: 22.2%, government: 4.4%, self-employed: 4.1%). All 16 skills were rated as at least somewhat important by > 89.0% of respondents. Significant heterogeneity in importance by career stage and by highest degree earned was identified for several skills. Two skills (“regulatory requirements” and “databases, data sources, and data collection tools”) were more likely to be rated as absolutely essential by those working in industry (36.5%, 65.8%, respectively) than by those in academia (19.6%, 51.3%, respectively). Three additional skills were identified as important by survey respondents, for a total of 19 collaborative skills. Conclusions: We identified 19 team science skills that are important to the work of collaborative biostatisticians, laying the groundwork for enhancing graduate programs and establishing effective on-the-job training initiatives to meet workforce needs.
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The framework established by Pomann et al. and validated by Slade et al. defines three core domains of biostatistical practice in collaborative research settings.
“This study used a framework established by Pomann et al. [11] and recently validated by Slade et al. [12], defining three core domains of biostatistical practice in collaborative research settings.”
From Integrating large language models in biostatistical workflows for clinical and translational research (2025) · cites this paper as [12]
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Research works printed but not linked: 15
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Grambow, S. C., Desai, M., Weinfurt, K. P., Lindsell, C. J., Pencina, M. J., Rende, L., & Pomann, G.-M. (2025) · Journal of Clinical and Translational Science · doi:10.1017/cts.2025.10064 · Cited by 7 · see citing works
Self-citation
- Authors
- Slade, E., Brearley, A. M., Coles, A., Hayat, M. J., Kulkarni, P. M., Nowacki, A. S., Oster, R. A., Posner, M. A., Samsa, G., Spratt, H., Troy, J., & Pomann, G.-M.
- Affiliations
- University of Kentucky (US)
- University of Minnesota (US)
- Bristol-Myers Squibb (United States) (US)
- Georgia State University (US)
- Eli Lilly (United States) (US)
- Cleveland Clinic (US)
- University of Alabama at Birmingham (US)
- Villanova University (US)
- Duke University (US)
- The University of Texas Medical Branch at Galveston (US)
- Corresponding author
- Slade, Emily
- ORCID
- Venue
- Journal of Clinical and Translational Science
- Publisher
- Cambridge University Press (CUP)
- Published
- 2023
- Volume
- 7
- Issue
- 1
- Pages
- e243-e243
- ISSN
- 2059-8661 (ISSN-L)
- PMC
- PMC10685263
- OpenAlex
- W4388414774
- Cited by
- 12
- References
- 0
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 4
- FWCI
- 3.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Clinical and Translational Science (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (UL1TR002553, UL1TR003096, UL1TR002494, UL1TR002548, UL1TR001998, UL1TR001439)
- National Center for Advancing Translational Sciences
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Interdisciplinary Research and Collaboration
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Health Sciences › Health Professions › General Health Professions › Interprofessional Education and Collaboration
- Keywords
- graduate education, career stages, regulatory requirements, data management, leadership skills
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