Explore the vast range of titles available.

The Science of Team Science (SciTS) has generated a substantial body of work detailing characteristics of effective teams. However, that knowledge has not been widely translated into accessible, active, actionable, evidence-based interventions to help translational teams enhance their team functioning and outcomes. Over the past decade, the field of Implementation Science has rapidly developed methods and approaches to increase the translation of biomedical research findings into clinical care, providing a roadmap for mitigating the challenges of developing interventions while maximizing feasibility and utility. Here, we propose an approach to intervention development using constructs from two Implementation Science frameworks, Consolidated Framework for Implementation Research, and Reach, Effectiveness, Adoption, Implementation, and Maintenance, to extend the Wisconsin Interventions for Team Science framework described in Rolland et al. 2021. These Implementation Science constructs can help SciTS researchers design, build, test, and disseminate interventions that meet the needs of both adopters , the institutional leadership that decides whether to adopt an intervention, and implementers , those actually using the intervention. Systematically considering the impact of design decisions on feasibility and usability may lead to the design of interventions that can quickly move from prototype to pilot test to pragmatic trials to assess their impact.

Achieving the clinical, public health, economic, and policy benefits of translational science requires the integration and application of findings across biomedical, clinical, and behavioral science and health policy, and thus, collaboration across experts in these areas. To do so, translational teams need the skills, knowledge, and attitudes to mitigate challenges and build on strengths of cross-disciplinary collaboration. Though these competencies are not innate to teams, they can be built through the implementation of effective strategies and interventions. The Science of Team Science (SciTS) has contributed robust theories and evidence of empirically-informed strategies and best practices to enhance collaboration. Yet the field lacks methodological approaches to rigorously translate those strategies into evidence-based interventions to improve collaborative translational research. Here, we apply lessons from Implementation Science and Human-Centered Design & Engineering to describe the Wisconsin Interventions in Team Science (WITS) framework, a process for translating established team science strategies into evidence-based interventions to bolster translational team effectiveness. To illustrate our use of WITS, we describe how University of Wisconsin’s Institute for Clinical and Translational Research translated the existing Collaboration Planning framework into a robust, scalable, replicable intervention. We conclude with recommendations for future SciTS research to refine and test the framework.

The impetus for this issue was the relative dearth of evidence-based interventions to support team effectiveness, which can leave translational scientists to fend for themselves in establishing effective teams. Translational research initiatives, by definition, are made up of diverse teams of scientific experts, community partners, policy makers, research staff, funding agencies, and/or industry partners [4]. [...]we need improved methods for developing interventions to ensure scientific rigor and generalizability of our interventions, which will allow us to develop and adapt interventions more rapidly. [...]we must develop common approaches to evaluating the effectiveness of team-based interventions after they have been released into the wild.

Clinical and Translational Research (CTR) requires a team-based approach, with successful teams engaging in skilled management and use of information. Yet we know little about the ways that Translational Teams (TTs) engage with information across the lifecycle of CTR projects. This qualitative study explored the challenges that information management imposes on the conduct of team-based CTR. We conducted interviews with ten members of TTs at University of Wisconsin. Interviews were transcribed and thematic analysis was conducted. TTs' piecemeal and reactive approaches to information management created conflict within the team and slowed scientific progress. The lack of cohesive information management strategies made it more difficult for teams to develop strong team processes like communication, scientific coordination, and project management. While TTs' research was hindered by the institutional challenges of interdisciplinary team information sharing, TTs who had developed shared approaches to information management that foregrounded transparency, accountability, and trust, described substantial benefits to their teamwork. We propose a new model for the Science of Team Science field - a Translational Team Science Hierarchy of Needs - that suggests interventions should be targeted at the appropriate stage of team development in order to maximize a team's scientific potential.

To conduct high-quality, rigorous research, and advance scientific knowledge, Translational Teams (TTs) engage in information behaviors, including seeking, using, creating, sharing, storing, and retrieving information, in ways specific to the translational context. Currently, little is known about TTs' approach to information management. This qualitative pilot study explored how TTs at the University of Wisconsin-Madison interact with information, as well as the scientific and organizational impact of their interactions. We conducted interviews with ten members of UW TTs. Interviews were transcribed and thematic analysis was conducted. Four themes emerged: (1) TT members did not recognize the centrality of information or information behaviors to their scientific work; (2) TT members engaged in similar information behaviors and used similar tools across disciplines and topics; (3) TT members did not receive support or guidance from their institution in managing information; and (4) Individualized choices of TT members conflicted at the team level, causing confusion and increasing the potential for data and information loss. Acting as , TT members made individualized decisions about what tools to use and how to use them, often in a piecemeal manner and without communicating these decisions to other team members. Research institutions should both encourage teams to discuss their information management approaches at the beginning of a project and provide leaders with training on how to have these conversations and what topics should be included. Additionally, institutions can provide researchers with guidelines for using software platforms to help mitigate information management challenges.

A translational team (TT) is a specific type of interdisciplinary team that seeks to improve human health. Because high-performing TTs are critical to accomplishing CTSA goals, a greater understanding of how to promote TT performance is needed. Previous work by a CTSA Workgroup formulated a taxonomy of 5 interrelated team-emergent competency “domains” for successful translation: 1). affect, 2). communication, 3). management, 4). collaborative problem-solving, and 5). leadership. These Knowledge Skills and Attitudes (KSAs) develop within teams from the team’s interactions. However, understanding how practice in these domains enhance team performance was unaddressed. To fill this gap, we conducted a scoping literature review of empirical team studies from the broader Science of Team Science literature domains. We identified specific team-emergent KSAs that enhance TT performance, mapped these to the earlier “domain” taxonomy, and developed a rubric for their assessment. This work identifies important areas of intersection of practices in specific competencies across other competency domains. We find that inclusive environment, openness to transdisciplinary knowledge sharing, and situational leadership are a core triad of team-emergent competencies that reinforce each other and are highly linked to team performance. Finally, we identify strategies for enhancing these competencies. This work provides a grounded approach for training interventions in the CTSA context.

Successful translation involves the coupled application of knowledge - generating research with product development to advance a device, drug, diagnostic, or evidence-based intervention for clinical adoption to improve human health. Critical to the success of the CTSA consortium, translation can be more effectively accomplished by training approaches that focus on improving team-emergent knowledge skills and attitudes (KSAs) linked to performance. We earlier identified 15 specific evidence-informed, team-emergent competencies that facilitate translational team (TT) performance. Here, we examine the SciTS literature describing developmental, temporal dynamics, and adaptive learning stages of interdisciplinary teams and integrate these with real-world observations on TT maturation pathways. We propose that TTs undergo ordered developmental phases, each representing a learning cycle that we call Formation , Knowledge Generation , and Translation . We identify major activities of each phase linked to development goals. Transition to subsequent phases is associated with a team learning cycle, resulting in adaptations that enabling progression towards clinical translation. We present known antecedents of stage-dependent competencies and rubrics for their assessment. Application of this model will ease assessment, facilitate goal identification and align relevant training interventions to improve performance of TTs in the CTSA context.

The study aimed to examine the impact of the researcher-centered Basic Fit Translational Model and Delivery Design framework on outcomes such as visualization, progression, and self-reflection. We collected data through questionnaires, with thirty researchers participating in individual training sessions. The Wilcoxon signed-rank test's statistically significant results (3.0-7.0) demonstrated the ease of model adaptability and the need for researcher-centered model building. The basic fit model helps researchers identify their research type, visualize shortcomings, and collaborate in an extended network, leading to successful completion. The delivery design framework helps parallel-process multiple workflows, reducing translational lag time for patients and the pharma industry.

The Clinical and Translational Science Awards (CTSA) Program supports a national network of medical research institutions working to expedite the development of treatments and interventions. High-performing translational teams (TTs) involving inter-institutional collaborations are critical for advancing these evidence-based approaches. However, management of these complex teams can be difficult, and tailored project management may help TTs overcome the unique challenges they face. We conducted qualitative interviews with 14 dedicated project managers (PMs) from six CTSAs to learn more about their experiences with TTs. Information derived from the thematic analysis of the data was used to identify barriers and facilitators for effective project management. Barriers included a lack of institutional support, communication issues, pushback, role confusion, and a need for agility. Facilitators included transparent communication, supportive team environments, shared leadership with autonomy, and opportunities for professional development. The PMs interviewed for this study provided descriptions of their work that depicted a more expansive view of project management than the more traditional approach focused on meeting deadlines and managing deliverables. Our findings have been used to inform development, training, and guidance for an innovative project management resource, the Project Management Innovation Center of Excellence (PROMICE) recently launched at the UW-Madison Institute for Clinical and Translational Research (ICTR). Through the development of a dedicated career path, PROMICE recognizes the value that PMs bring to translational science and provides the support that they need to be innovative, leading their teams to success.