This study describes a needs assessment of clinical and translational research (CTR) scientists at a large, distributed, School of Medicine within a public university and affiliated clinics.

We performed an Exploratory Conversion Mixed-Methods analysis using a quantitative survey and qualitative interviews with CTR scientists across the training continuum, from early-career scholars, mid-career mentors, and senior administrators at the University of Wisconsin and Marshfield Clinics. Qualitative findings were confirmed using epistemic network analysis (ENA). A survey was distributed to CTR scientists in training.

Analyses supported that early-career and senior-career scientists have unique needs. Scientists who identified as non-White or female reported needs that differed from White male scientists. Scientists expressed the needs for educational training in CTR, for institutional support of career development, and trainings for building stronger relationships with community stakeholders. The tension between meeting tenure clocks and building deep community connections was particularly meaningful for scholars who identified as under-represented, including based on race, gender, and discipline.

This study yielded clear differences in support needs between scientists based upon their years in research and diversity of identities. The validation of qualitative findings, through quantification with ENA, enables robust identification of unique needs of CTR investigators. It is critically important to the future of CTR that scientists are provided with supports throughout the career. Delivery of that support in efficient and timely ways improves scientific outcomes. Advocacy at the level of the institution for under-represented scientists is of utmost importance.

The science of team science (SciTS) is an emerging research area that studies the processes and outcomes of team-based research. A well-established conceptual framework and appropriate methodology for examining the effectiveness of team science are critically important for promoting and advancing collaborative and interdisciplinary research. Although many instruments have been developed and used in the SciTS field, psychometric evidence has not been routinely assessed or reported for these scales. In addition, commonly used psychometric methods were mainly limited to internal consistency and factor analysis. To fill the gaps, this study introduces a framework based on Rasch measurement theory for creating and evaluating measures for team sciences.

We illustrate the application of Rasch measurement theory through the creation of valid measures to evaluate the processes of interdisciplinary scientific teams. Data were collected from 16 interdisciplinary teams through a university-wide initiative for promoting interdisciplinary team collaboration. Psychometric evidence based on a many-facet Rasch model was obtained for assessing the quality of the measures.

The interdisciplinary teams differed in their clarity measures. Significant differences were also found between gender groups, racial groups, and academic ranks. We reported the reliability of measures and identified items that do not fit the model and may present potential threat to validity and fairness of SciTS measures.

This study shows the great potential of using Rasch measurement theory for developing and evaluating SciTS measures. Applying Rasch measurement theory produces objective measures that are comparable across individuals, interdisciplinary teams, institutions, time, and various demographic groups.

Federal grant funding to support infrastructure development of translational biomedical research centers is a form of public health intervention. Establishing rigorous methods for measuring center success and outcomes is essential to justify continued funding.

Bibliometric data compiled from a 5-year funding cycle of neurodegeneration and translational neuroscience research center were analyzed using the package bibliometrix for open-source software R and the NIH-developed research tool iCite.

The research team and their collaborators (n = 485) produced 157 grant-citing publications from 2015–2020. The science was produced by small research teams clustered around three main communities of topics: Alzheimer’s Disease, brain imaging, and neuropsychological testing in the elderly. Using the relative citation ratio, the publications produced by the research team were found to be influential when compared to other R01-funded publications.

Recent developments in bibliometric analysis expand beyond traditional measurement capabilities to better understand the characteristics, outcomes, and influences of research teams. These findings can be used to inform researchers and institutions about research team composition, productivity, and success. Measures of research influence may be used to justify return on investment to funders.