Temporal challenges are not only contextual in nature but manifest internally in teams when members enter the team with different temporal orientations (e.g., time urgency and pacing style). Researchers have demonstrated that temporal diversity has important implications for key team outcomes (performance, timeliness, and team conflict) across a range of samples and countries. Unfortunately, the practical implications of this research have yet to be unpacked. We respond to this need by developing an approach to translate temporal diversity research studies into actionable, evidence-based team interventions. Because journal articles are often deficient on actionable steps, whereas practitioner-friendly outlets tend to be deficient on scientific rigor, incorporating both criteria necessitates merging these literatures. Specifically, we delineate four main steps: (1) identify significant moderators, (2) match the moderators to scientifically based interventions, (3) design intervention tools with specific, actionable procedures, and (4) evaluate the effectiveness of the intervention tools by designing research studies. We believe the process we outline to marry actionable and evidence-based benchmarks is applicable to other research domains in team science beyond temporal research. It is our hope that this research will be a catalyst for further exploration of interventions that can help team members navigate temporal differences.

As the need to tackle complex clinical and societal problems rises, researchers are increasingly taking on a translational approach. This approach, which seeks to integrate theories, methodologies, and frameworks from various disciplines across a team of researchers, places emphasis on translation of findings in order to offer practical solutions to real-world problems. While translational research leads to a number of positive outcomes, there are also a multitude of barriers to conducting effective team science, such as effective coordination and communication across the organizational, disciplinary, and even geographic boundaries of science teams. Given these barriers to success, there is a significant need to establish team interventions that increase science team effectiveness as translational research becomes the new face of science. This review is intended to provide translational scientists with an understanding of barriers to effective team science and equip them with the necessary tools to overcome such barriers. We provide an overview of translational science teams, discuss barriers to science team effectiveness, demonstrate the lacking state of current interventions, and present recommendations for improving interventions in science teams by applying best practices from the teams and groups literature across the four phases of transdisciplinary research.

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.

Funding agencies are increasingly seeking team-based approaches to tackling complex research questions, but there is a need to mobilize translational teams and create shared visions and strategic action plans long before specific funding opportunities are considered or even released. This is particularly evident for teams who want to pursue large-scale grants, where cross-disciplinary synergy is often required. In response, we created Research Jams, which are engaging yet structured brainstorming sessions that bring together groups for the first time to collectively generate novel research ideas, critically map the future of initiatives, prioritize opportunities and next steps, and build community. Research Jams leveraged various aspects of design thinking, including divergence and convergence, visual thinking, and amplifying diversity. We piloted seven Research Jams for a collective 129 researchers, staff, and partners across 50 University of Michigan units and external organizations. Feedback was overwhelmingly positive, with the vast majority of survey respondents indicating that the sessions were helpful for surfacing shared ideas or visions and that opportunities emerged they would like to pursue. Research Jams were ideal for cross-disciplinary groups who wanted to collaboratively ideate and strategize around complex problems in translational research. Importantly, these models have the potential for implementation with groups in any disciplinary domain who want to spur collaborations to address challenging problems. Our ultimate goal is for Research Jams to be the first intervention within a comprehensive support pathway that extends from early brainstorming all the way to grant submission.

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 internal research program of the National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health aims to fundamentally transform the preclinical translational research process to get more treatments to more people more quickly. The program develops and implements innovative scientific and operational approaches that accelerate and enhance translation across many diverse projects. Cross-disciplinary team science is a defining feature of our organization, with scientists at all levels engaged in multiple research teams. Here, we share our systems approach to nurturing cross-disciplinary team science, which leverages organizational policies, structures, and processes. Policies including the organizational mission statement, principles for ethical conduct of research, performance review criteria, and training program objectives and approaches reinforce the value of team science to achieve the program’s scientific goals. Structures including an organizational structure designed around solving translational problems, co-location of employees in a single state-of-the-art scientific facility, and shared-use laboratories, expertise and instrumentation facilitate collaboration. Processes including fluid team assembly, specialized project management, cross-agency partnerships, and decision making based on clear screening criteria and milestones enable effective team assembly and functioning. We share evidence of the impact of these approaches on the science and commercialization of findings and discuss pathways to broad adoption of similar approaches.

Large translational research initiatives can strengthen efficiencies and support science with enhanced impact when practical conceptual models guide their design, implementation, and evaluation. The National Institutes of Health (NIH) Environmental influences on Child Health Outcomes (ECHO) program brings together data from 72 ongoing maternal–child cohort studies – involving more than 50,000 children and over 1200 investigators – to conduct transdisciplinary solution-oriented research that addresses how early environmental exposures influence child health. ECHO uses a multi-team system approach to consortium-wide data collection and analysis to generate original research that informs programs, policies, and practices to enhance children’s health. Here, we share two conceptual models informed by ECHO’s experiences and the Science of Team Science. The first conceptual model illuminates a system of teams and associated tasks that support collaboration toward shared scientific goals. The second conceptual model provides a framework for designing evaluations for continuous quality improvement of manuscript writing teams. Together, the two conceptual models offer guidance for the design, implementation, and evaluation of translational and transdisciplinary multi-team research initiatives.

The Motivation Assessment for Team Readiness, Integration, and Collaboration (MATRICx) is a psychometric instrument that measures individual motivation for collaboration. It was validated using Rasch Analysis to create an indicator hierarchy on two dimensions: cooperation and collaboration. Six domains provide the basis for the tool to identify team member readiness for collaboration and a means by which to understand motivational strengths in a team based on degree of past self-reported experience. This brief report provides an overview of the development of the tool, how science teams may use it, and how to interpret results to advance team member readiness for greater collaboration. The paper also draws attention to ongoing work in progress to develop learning interventions to accompany the MATRICx instrument.