Moving beyond Aim Three: a need for a transdisciplinary approach to build capacity for economic evaluations in implementation science

Background Understanding the costs and economic benefits of implementation has been identified by policymakers and researchers as critical to increase the uptake and sustainment of evidence-based practices, but this topic remains relatively understudied. Conducting team science with health economists has been proposed as a solution to increase economic evaluation in implementation science; however, these recommendations ignore the differences in goals and perspectives in these two fields. Our recent qualitative research identified that implementation researchers predominantly approach health economists to examine costs, whereas the majority of health economists expressed limited interest in conducting economic evaluations and a desire to be more integrated within implementation science initiatives. These interviews pointed to challenges in establishing fruitful partnerships when health economists are relegated to the “Third Aim” (i.e., lowest-priority research objective) in implementation science projects by their research partners. Discussion In this debate paper, we argue that implementation researchers and health economists need to focus on team science research principles to expand capacity to address pressing research questions that cut across the two fields. Specifically, we use the four-phase model of transdisciplinary research to outline the goals and processes needed to build capacity in this area (Hall et al., Transl Behav Med 2:415–30, 2012). The first phase focuses on the development of transdisciplinary research teams, including identifying appropriate partners (e.g., considering policy or public health researchers in addition to health economists) and building trust. The conceptual phase focuses on strategies to consider when developing joint research questions and methodology across fields. In the implementation phase, we outline the effective processes for conducting research projects, such as team learning. Finally, in the translation phase, we highlight how a transdisciplinary approach between health economists and implementation researchers can impact real-world practice and policy. Summary The importance of investigating the economic impact of evidence-based practice implementation is widely recognized, but efforts have been limited due to the challenges in conducting team science across disciplines. Training in team science can help advance transdisciplinary efforts, which has the potential to increase the rigor and impact of economic evaluations in implementation science while expanding the roles taken by health economists.

Bringing Transdisciplinary Aging Research From Theory to Practice

There is a growing emphasis to use a transdisciplinary team approach to accelerate innovations in science to solve complex conditions associated with aging. However, the optimal organizational structure and process for how to accomplish transdisciplinary team science are unclear. In this study, we illustrate our team’s experience using transdisciplinary approaches to solve challenging and persistent problems for older adults living in urban communities. We describe our challenges and successes using the National Institutes of Health four-phase model of transdisciplinary team-based research. Using a de-identified survey, the team conducted an internal evaluation to identify features that created challenges including structural incongruities, interprofessional blind spots, group function, and group dynamics. The team then identified responses to address the features that created challenges and determined indicators for success. Indicators for success were identified by the team as a place for continued evaluation of the teams’ collaborative effectiveness, transdisciplinary integration, and impact on the university and aging community. This work resulted in the creation of the team’s Transdisciplinary Conceptual Model. This model became essential to understanding the complex interplay between societal factors, community partners, and academic partners. Conducting internal evaluations of transdisciplinary team processes is integral for teams to move beyond the multi- and interdisciplinary niche and to reach true transdisciplinary success. More research is needed to develop measures that assess team transdisciplinary integration. Once the process of transdisciplinary integration can be reliably assessed, the next step would be to determine the impact of transdisciplinary team science initiatives on aging communities.

Beyond online participant crowdsourcing: The benefits and opportunities of big team addiction science

Participant crowdsourcing platforms (e.g., MTurk, Prolific) offer numerous advantages to addiction science, permitting access to hard-to-reach populations and enhancing the feasibility of complex experimental, longitudinal and intervention studies. Yet these are met with equal concerns about participant non-naivety, motivation, and careless responding, which if not considered can greatly compromise data quality. In this article, we discuss an alternative crowdsourcing avenue that overcomes these issues whilst presenting its own unique advantages – crowdsourcing researchers through big team science. First, we review several contemporary efforts within psychology (e.g., ManyLabs, Psychological Science Accelerator) and the benefits these would yield if they were more widely implemented in addiction science. We then outline our own consortium-based approach to empirical dissertations: a grassroots initiative that trains students in reproducible big team addiction science. In doing so, we discuss potential challenges and their remedies, as well as providing resources to help addiction researchers develop these initiatives. Through researcher crowdsourcing, together we can answer fundamental scientific questions about substance use and addiction, build a literature that is representative of a diverse population of researchers and participants, and ultimately achieve our goal of promoting better global health.

A field guide to cultivating computational biology

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.