Adrenal vein sampling (AVS) is a complicated procedure requiring clinical expertise, collaboration, and patient involvement to ensure it occurs successfully. Implementation science offers unique insights into the barriers and enablers of service delivery of AVS. The primary aim of this review was to identify implementation components as described within clinical studies, that contribute to a successful AVS procedure. The secondary aim was to inform practice considerations to support the scale-up of AVS. A scoping review of clinical papers that discussed factors contributing to effective AVS implementation was included. A phased approach was employed to extract implementation science data from clinical studies. Implementation strategies were named and defined, allowing for implementation learnings to be synthesized, in the absence of dedicated research examining implementation process and findings only. Ten implementation components reported as contributing to a successful AVS procedure were identified. These components were categorized according to actions required pre-AVS, during AVS, and post-AVS. Using an implementation science approach, the findings of this review and analysis provide practical considerations to facilitate AVS service delivery design. Extracting implementation science information from clinical research has provided a mechanism that accelerates the translation of evidence into practice where implementation research is not yet available.

The dissemination and implementation (D&I) of evidence at the community level is critical to improve health and advance health equity. Social networks are considered essential to D&I efforts, but there lacks clarity regarding how best to study and leverage networks. We examined networks in community-level D&I frameworks to characterize the range of network actors, activities, and change approaches. We conducted a narrative review of 66 frameworks. Among frameworks that explicitly addressed networks – that is, elaborated on network characteristics, structure, and/or activities – we extracted and synthesized network concepts using descriptive statistics and narrative summaries. A total of 24 (36%) frameworks explicitly addressed networks. Commonly included actors were implementers, adopters/decision-makers, innovation developers, implementation support professionals, and innovation recipients. Network activities included the exchange of resources, knowledge, trust, and norms. Most network-explicit frameworks characterized ties within and across organizations and considered element(s) of network structure – for example, size, centrality, and density. The most common network change strategy was identifying individuals to champion D&I efforts. We discuss opportunities to expand network inquiry in D&I science, including understanding networks as implementation determinants, leveraging network change approaches as implementation strategies, and exploring network change as an implementation outcome.

Translational research needs to show value through impact on measures that matter to the public, including health and societal benefits. To this end, the Translational Science Benefits Model (TSBM) identified four categories of impact: Clinical, Community, Economic, and Policy. However, TSBM offers limited guidance on how these areas of impact relate to equity. Central to the structure of our Center for American Indian and Alaska Native Diabetes Translation Research are seven regional, independent Satellite Centers dedicated to community-engaged research. Drawing on our collective experience, we provide empirical evidence about how TSBM applies to equity-focused research that centers community partnerships and recognizes Indigenous knowledge. For this special issue – “Advancing Understanding and Use of Impact Measures in Implementation Science” – our objective is to describe and critically evaluate gaps in the fit of TSBM as an evaluation approach with sensitivity to health equity issues. Accordingly, we suggest refinements to the original TSBM Logic model to add: 1) community representation as an indicator of providing community partners “a seat at the table” across the research life cycle to generate solutions (innovations) that influence equity and to prioritize what to evaluate, and 2) assessments of the representativeness of the measured outcomes and benefits.

Traditional approaches for evaluating the impact of scientific research – mainly scholarship (i.e., publications, presentations) and grant funding – fail to capture the full extent of contributions that come from larger scientific initiatives. The Translational Science Benefits Model (TSBM) was developed to support more comprehensive evaluations of scientific endeavors, especially research designed to translate scientific discoveries into innovations in clinical or public health practice and policy-level changes. Here, we present the domains of the TSBM, including how it was expanded by researchers within the Implementation Science Centers in Cancer Control (ISC3) program supported by the National Cancer Institute. Next, we describe five studies supported by the Penn ISC3, each focused on testing implementation strategies informed by behavioral economics to reduce key practice gaps in the context of cancer care and identify how each study yields broader impacts consistent with TSBM domains. These indicators include Capacity Building, Methods Development (within the Implementation Field) and Rapid Cycle Approaches, implementing Software Technologies, and improving Health Care Delivery and Health Care Accessibility. The examples highlighted here can help guide other similar scientific initiatives to conceive and measure broader scientific impact to fully articulate the translation and effects of their work at the population level.

Engaging diverse partners in each phase of the research process is the gold standard of community-engaged research and adds value to the impact of implementation science. However, partner engagement in dissemination, particularly meaningful involvement in developing peer-reviewed manuscripts, is lacking. The Implementation Science Centers in Cancer Control are using the Translational Science Benefits Model to demonstrate the impact of our work beyond traditional metrics, including building capacity and promoting community engagement. This paper presents a case example of one center that has developed a policy for including community partners as coauthors. Standard practices are used to foster clear communications and bidirectional collaboration. Of published papers focused on center infrastructure and implementation research pilots, 92% have community partner coauthors. This includes 21 individuals in roles ranging from physician assistant to medical director to quality manager. Through this intentional experience of co-creation, community partners have strengthened implementation science expertise. Community coauthors have also ensured that data interpretation and dissemination reflect real-world practice environments and offer sustainable strategies for rapid translation to practice improvements. Funders, academic journals, and researchers all have important roles to play in supporting community coauthors as critical thought partners who can help to narrow the gap between research and practice.

Complex food retail settings, where multiple food retail outlets operate in close proximity are common. Despite their ubiquity, there remains a significant knowledge gap regarding healthy food retail interventions implemented within these settings. Furthermore, understanding the factors affecting the implementation of interventions in these settings remains limited. This systematic review aimed to (1) identify and describe complex food retail settings where interventions were implemented to promote the healthiness of foods purchased, (2) synthesise the evidence on the effectiveness of the interventions implemented, and (3) identify enablers and barriers to the implementation of the interventions in these settings. Four databases, namely, MEDLINE Complete, Global Health, Embase, and Business Source Complete, were searched until December 2022. The Effective Public Health Practice Project quality assessment tool was used. Six studies reported on the implementation of interventions promoting healthy food purchases across multiple food retail outlets. Three studies each described two complex food retail settings: university and hospital. Interventions including promotion and promotion plus price improved the healthiness of foods purchased. There was limited description of institutional food policies, conceptual frameworks, formative research, or evaluation outcomes to inform the implementation of interventions in these settings. No study analysed enablers and barriers to the implementation of interventions. No study identified their settings as complex food retail settings. There is limited evidence describing complex food retail settings, their impact on intervention effectiveness, and associated enablers or barriers. Investigating factors influencing the effectiveness of interventions implemented within complex food retail settings is critical to support their implementation at scale.

Challenges in implementing digital health in clinical practice hinder its potential. The complexities posed by implementation could benefit from using design practices. To explore the current role of design practices in digital health implementation, designers in the Netherlands were interviewed. The preliminary results indicate that designers contribute to digital health implementation processes, especially in the early stages. Design practices are mainly used for engaging the users, testing concepts, aligning the ideas of stakeholders, and adapting interventions to fit within the contexts.

The effects of deliberately and selectively manipulating instructional conditions are at the heart of instructed second language acquisition (ISLA) research and, ideally, are designed to inform practice. Knowing how an intervention works, by what mechanisms and processes the treatment is beneficial—and for whom—are complex questions. In this piece, we problematize intervention-based research paradigms that do not account for context, individuals and their proactivity, or temporal variation. We highlight several key challenges that remain for ISLA research and propose a more reflexive approach to intervention that attends to these central considerations in implementing study designs.

In this article, we celebrate Dante Cicchetti’s extensive contributions to the discipline of developmental psychopathology. In his seminal article, he articulated why developmental psychopathology was imperative to create research portfolios that could inform the causes, consequences, and trajectories for adults often initiated by early lived experiences (Cicchetti, 1984). In this three-part article, we share our transdisciplinary efforts to use developmental psychopathology as a foundational theory from which to develop, implement, and evaluate interventions for populations who experienced early adversity or who were at risk for child abuse and neglect. After describing interventions conducted at Mt. Hope Family Center that spanned over three decades, we highlight the criticality of disseminating results and address policy implications of this work. We conclude by discussing future directions to facilitate work in developmental psychopathology. Currently, one of three national National Institute of Child Health and Human Development-funded child abuse and neglect centers, we look forward to continuing to build upon Dante’s efforts to disseminate this important work to improve society for our children, our nation’s often most vulnerable and forgotten citizens.

With disparate rates of morbidity and mortality among minoritized communities, COVID-19 illuminated the need for equity-informed practices in public health. Pacia et al posit FQHCs as entities that addressed inequity when others failed. This commentary further situates how FQHCs address the public health crisis of institutional racism and related health inequities every day and presents a FQHC-led Ethics and Equity Framework and Workflow Checklist to guide ethical and equitable engagement with FQHCs.

Cardiovascular disease (CVD) is largely preventable, and the leading cause of death for men and women. Though women have increased life expectancy compared to men, there are marked sex disparities in prevalence and risk of CVD-associated mortality and dementia. Yet, the basis for these and female-male differences is not completely understood. It is increasingly recognized that heart and brain health represent a lifetime of exposures to shared risk factors (including obesity, hyperlipidemia, diabetes, and hypertension) that compromise cerebrovascular health. We describe the process and resources for establishing a new research Center for Women’s Cardiovascular and Brain Health at the University of California, Davis as a model for: (1) use of the cy pres principle for funding science to improve health; (2) transdisciplinary collaboration to leapfrog progress in a convergence science approach that acknowledges and addresses social determinants of health; and (3) training the next generation of diverse researchers. This may serve as a blueprint for future Centers in academic health institutions, as the cy pres mechanism for funding research is a unique mechanism to leverage residual legal settlement funds to catalyze the pace of scientific discovery, maximize innovation, and promote health equity in addressing society’s most vexing health problems.

Researchers and practitioners are increasingly embracing systems approaches to deal with the complexity of public service delivery and policy evaluation. However, there is little agreement on what exactly constitutes a systems approach, conceptually or methodologically. We review and critically synthesize systems literature from the fields of health, education, and infrastructure. We argue that the common theoretical core of systems approaches is the idea that multi-dimensional complementarities between a policy and other aspects of the policy context are the first-order problem of policy design and evaluation. We distinguish between macro-systems approaches, which focus on the collective coherence of a set of policies or institutions, and micro-systems approaches, which focus on how a single policy interacts with the context in which it operates. We develop a typology of micro-systems approaches and discuss their relationship to standard impact evaluation methods as well as to work in external validity, implementation science, and complexity theory.