In preparing for our Clinical and Translational Science Award (CTSA) UM1 application, we recognized the need to develop a shared understanding of the distinctions between translational science (TS) and translational research (TR). We describe our efforts to develop and evaluate the reliability of a concise instrument that investigators and reviewers could use to distinguish between TS and TR.

Groups of faculty and staff individually reviewed published translational studies to determine whether the project involved TS and, separately, TR. One group (n = 10) first reviewed 14 publications with limited guidance; the same group and a second group (n = 9) then reviewed another set of 14 publications guided by a detailed algorithm. We used kappa statistics to measure agreement in the determinations of TS and TR for each publication.

The overall kappa coefficients in the three sets of TS determinations (two by the first group and one by the second group) were 0.61, 0.33, and 0.18, respectively. The overall kappa coefficients in the three sets of TR determinations were 0.26, 0.11, and 0.40, respectively. The median kappa coefficients for all 42 determinations were 0.39 for TS and 0.22 for TR, both indicating only fair agreement. We found no evidence that the algorithm helped to improve agreement rates.

Our results show gaps in understanding the distinction between TS and TR among CTSA hub faculty and staff. We discuss some reasons for this gap and propose ways that could improve the recognition of TS and TR.

In recent years, there has been a growth in awareness of the importance of equity and community engagement in clinical and translational research. One key limitation of most training programs is that they focus on change at the individual level. While this is important, such an approach is not sufficient to address systemic inequities built into the norms of clinical and translational research. Therefore, it is necessary to provide training that addresses changing scientific norms and culture to ensure inclusivity and health equity in translational research.

We developed, implemented, and assessed a training course that addressed how research norms are based on histories and legacies of white supremacy, colonialism, and patriarchy, ultimately leading to unintentional exclusionary and biased practices in research. Additionally, the course provides resources for trainees to build skills in how to redress this issue and improve the quality and impact of clinical and translational research. In 2022 and 2023, the course was offered to cohorts of pre and postdoctoral scholars in clinical and translational research at a premier health research Institution.

The efficacy and immediate impact of three training modules, based on community engagement, racial diversity in clinical trials, and cancer clusters, were evaluated with data from both participant feedback and assessment from the authors. TL1 scholars indicated increased new knowledge in the field and described potential future actions to integrate community voices in their own research program.

Results indicate that trainings offered new perspectives and knowledge to the scholars.

Over the last couple of decades, there has been a growing awareness of the value of community-engaged research (CEnR). Simultaneously, many academic institutions have established centralized support for CEnR. For example, dozens of academic medical centers in the United States receive National Institutes of Health (NIH)-funded Clinical and Translational Science Awards (CTSAs) and have embedded community engagement programs (CE) whose primary expertise and mission is to advance CEnR at their institutions.

As part of a larger interview study aiming to learn more about how institutional CE programs and HRPPs work together, we analyzed interviews with CE program leaders at academic medical centers that receive funding from the NIH CTSA program to identify barriers and strategies to conducting CEnR at their institutions, primarily focusing on the relationships with Institutional Review Boards (IRBs).

We identified three categories in the interviews: barriers and strategies vis-à-vis IRBs to address 1) CE/IRB relationships; 2) Understanding issues; and 3) Structural and resource issues.

CTSA CE program leaders have experience implementing solutions to common barriers to IRB review faced by CEnR researchers. The barriers they face in these three categories and the strategies they use to overcome them can provide helpful insights to others who hope to facilitate CEnR research at their institutions.

The expansion of electronic health record (EHR) data networks over the last two decades has significantly improved the accessibility and processes around data sharing. However, there lies a gap in meeting the needs of Clinical and Translational Science Award (CTSA) hubs, particularly related to real-world data (RWD) and real-world evidence (RWE).

We adopted a mixed-methods approach to construct a comprehensive needs assessment that included: (1) A Landscape Context analysis to understand the competitive environment; and (2) Customer Discovery to identify stakeholders and the value proposition related to EHR data networks. Methods included surveys, interviews, and a focus group.

Thirty-two CTSA institutions contributed data for analysis. Fifty-four interviews and one focus group were conducted. The synthesis of our findings pivots around five emergent themes: (1) CTSA segmentation needs vary according to resources; (2) Team science is key for success; (3) Quality of data generates trust in the network; (4) Capacity building is defined differently by researcher career stage and CTSA existing resources; and (5) Researchers’ unmet needs.

Based on the results, EHR data networks like ENACT that would like to meet the expectations of academic research centers within the CTSA consortium need to consider filling the gaps identified by our study: foster team science, improve workforce capacity, achieve data governance trust and efficiency of operation, and aid Learning Health Systems with validating, applying, and scaling the evidence to support quality improvement and high-value care. These findings align with the NIH NCATS Strategic Plan for Data Science.

The Institute of Translational Health Sciences (Clinical and Translational Science Awards Program hub) developed a program coined Community Voices to invite communities to submit project ideas and be matched with academic researchers. We describe formative research to understand community and academic researcher perspectives on how the program could facilitate collaborations addressing community priorities.

We conducted four focus groups with 31 community-based organization (CBO) representatives and 11 semi-structured interviews with academic researchers in the Washington, Wyoming, Alaska, Montana, and Idaho regions. Questions included the appeal of Community Voices to engage community and academic partners, potential program usefulness, and Community Voices’ potential role in building community–academic partnerships. We used an inductive, constant comparison approach to code transcripts and thematic analysis to generate themes.

Most CBO representatives were female (87.1%) and Hispanic/Latino (61.3%). Most academic researchers had a PhD (63.6%) and worked at a university (81.8%). The themes were: (1) community–academic partnerships built on trust will offer mutual benefit, (2) community-initiated project ideas should prioritize community needs, (3) matchmaking will accelerate connections but should not replace time to foster partnership, (4) Community Voices should go beyond matchmaking and provide ongoing support/training, and (5) fostering effective communication is key to partnership success.

Community Voices is a novel, bidirectional community engagement program model that advances current practices of prioritizing researchers’ project ideas. This community-driven program may shift the future direction of community engagement practices where prioritizing community’s ideas becomes the norm of community–academic partnerships in clinical and translational science.

Evaluating clinical and translational research (CTR) mentored training programs is challenging because no two programs are alike. Careful selection of appropriate metrics is required to make valid comparisons between individuals and between programs. The KL2 program provides mentored-training for early-stage CTR investigators. Clinical and Translational Awards across the country have unique KL2 programs. The evaluation of KL2 programs has begun to incorporate bibliometrics to measure KL2 scholar and program impact.

This study investigated demographic differences in bibliometric performance and post-K award funding of KL2 scholars and compared the bibliometric performance and post-K award federal funding of KL2 scholars and other mentored-K awardees at the same institution. Data for this study included SciVal and iCite bibliometrics and National Institutions of Health RePORTER grant information for mentored-K awardees (K08, K23, and KL2) at Case Western Reserve University between 2005 and 2013.

Results showed no demographics differences within the KL2 program scholars. Bibliometric differences between KL2 and other mentored-K awardee indicated an initial KL2 advantage for the number of publications at 5 years’ post-matriculation (i.e., the start of the K award). Regression analyses indicated the number of initial publications was a significant predictor of federal grant funding at the same time point. Analysis beyond the 5-year post-matriculation point did not result in a sustained, significant KL2 advantage.

Factors that contributed to the grant funding advantage need to be determined. Additionally, differences between translational and clinical bibliometrics must be interpreted with caution, and appropriate metrics for translational science must be established.

This paper reports on the baseline stage of a qualitative evaluation of the application of the Innovative Scorecard (ISC) to the Clinical and Translational Science Award (CTSA) at the University of Texas Medical Branch (UTMB) at Galveston. The ISC is adopted from the established Balanced Scorecard system for strategic planning and performance management. In formulating the evaluation, we focused on the organizational identity literature.

The initial evaluation consisted of a series of semi-structured interviews with 22 participants of the ISC Boot Camp conducted in July 2015.

The logic of grounded theory pointed to the clustering of perceptions of the ISC around respondents’ occupational locations at UTMB. Administrators anticipate the expansion of planning activities to include a wider range of participants under the current CTSA award period (2015–2020) than under our first CTSA approval period (2009–2014). A common viewpoint among the senior scientists was that the scientific value of their work will continue to speak for itself without requiring the language of business. Junior scientists looked forward to the ISC’s emphasis on increasingly horizontal leadership that will give them more access to and more control over their work and resources. Postdocs and senior staff welcomed increased involvement in the total research process at UTMB.

The report concludes with strategies for future follow-up.