Enhancing dissemination and implementation research using systems science methods

Application of system dynamics approach in developing health interventions to strengthen health systems to combat obesity: a systematic literature review and critical analysis

BACKGROUND

Obesity is an escalating global public health challenge that is expected to impact a significant portion of the world's population in the coming decades. It leads to severe health conditions such as diabetes, cardiovascular diseases, and cancer, imposing significant economic burdens on health systems. Traditional intervention strategies, which emphasize individual lifestyle changes, fail to address the complex, systemic nature of obesity. This study aims to systematically review the application of system dynamics modelling (SDM) in obesity control, focusing on analyzing modelling methodologies and conducting a quality assessment of the included studies.

METHODS

Employing a comprehensive systematic literature retrieval, we explored terms pertinent to overweight/obesity and system dynamics across three databases, including PubMed, Web of Science, and Scopus. This search culminated in identifying peer-reviewed studies published from the inception of these databases until July 2024. Quality assessment was used to evaluate the SDM for obesity control. The protocol of this systematic review has been registered on PROSPERO (CRD42024554520).

RESULTS

Thirty studies were identified through a systematic review. These studies primarily focus on the effects of SD approaches, such as individual lifestyle changes, policy interventions within populations, and socio-economic and environmental improvements on obesity control. Among them, eleven studies completed the entire SDM process. Twenty-seven studies presented conceptual models, of which twenty-five developed casual loop diagrams (CLD). Seventeen studies conducted computational system dynamics modelling, with thirteen constructing stock-flow diagrams (SFD). Additionally, fourteen studies performed simulation analyses. These models facilitated multi-level strategies to reduce obesity prevalence.

CONCLUSIONS

Using SDM approaches has significant potential to enhance the effectiveness of obesity interventions and optimize resource allocation. Our study into the application of SDM in the design of obesity health interventions revealed its ability to promote multi-level, cross-sectoral cooperation and coordination, thereby enhancing the effectiveness of interventions. Further exploration and optimization of obesity health interventions can significantly advance health systems and welfare.

Using social network analysis to identify peer coaches in the real world of elementary schools: A multi-informant, community science approach

Coaching can increase elementary school teachers' implementation of evidence-based classroom practices, including equity-centered or culturally responsive practices. However, coaching by personnel external to schools can be expensive and difficult to sustain. Community science principles and social network research suggest the potential of influential peer leaders in schools to accelerate implementation. In the first phase of a multi-year project to develop and evaluate tools to help teachers use evidence-based, equity-focused positive behavioral support strategies in K-5 classrooms, we examine a school-partnered, network-informed process for identifying peer coaches, educator satisfaction with this process, and how feedback influenced process modifications. Educators in various roles (n = 85) from three elementary schools in two Central Ohio districts completed social network nomination and satisfaction surveys and interviews; research-practice partnership meeting records and field notes were analyzed. Findings suggest that a network-informed process to identify peer coaches results in distinct coaching teams and requires flexible application due to the unique, changing nature of school contexts (e.g., staff roles, turnover). We discuss the potential promise of harnessing teacher networks to identify peer coaches to fit the real-world contexts of elementary schools and meet the goal of accessible coaching and, ultimately, more equitable and supportive school environments for all students.

The "Mammograms Available Due to Resources and Education" (MADRE) Study: Rationale and Design

BACKGROUND

Latinas suffer disproportionately from breast cancer, partially due to lower uptake of guideline-concordant breast cancer screening. We describe the design of a study to compare two approaches addressing this important public health problem.

DESIGN/METHODS

We are conducting a 5-year randomized controlled trial. From a federally qualified health center network and through community outreach, we are recruiting 400 Latinas from Chicago who are non-adherent with United States Preventive Services Task Force breast cancer screening guidelines. Participants are randomized at a 1:1 ratio to receive one of two phone-based interventions (empowerment, education) administered across 3 weekly sessions. Both interventions provide information about breast cancer early detection. The empowerment intervention additionally teaches participants to share information about breast cancer screening with family and friends, while the education intervention educates patients about breast cancer prevention. Non-adherent Latina participants recruit family and friends eligible for breast cancer screening to take part in the study as network members. Network members do not participate in the intervention. Primary outcomes are initial (any mammogram post-enrollment) and repeat (measured at two-year intervals after enrollment) breast cancer screening among intervention participants and network members. Additionally, we will use multi-level structural equation models to assess potential mediators of the impact of the interventions.

DISCUSSION

This study will inform the development of empowerment approaches to increase participation in breast cancers screening among Latinas and reduce health disparities. NCT05841355.

Advancing and strengthening the study of social networks in community-level dissemination and implementation research: A narrative review

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.

How to leverage implementation research for equity in global health

Implementation research (IR) is important for addressing equity in global health. However, there is limited knowledge on how to operationalize IR for health equity, and pathways for improving health equity through IR in global health settings. This paper provides an overview of guidance and frameworks for thinking about health equity as part of IR while noting the gaps in how this guidance and frameworks apply to global health. It proposes an approach to guide implementation teams in the application of IR for achieving equity in global health considering these gaps. It describes key equity considerations for different aspects of IR (i.e., implementation contexts, strategies, outcomes, and research designs). These considerations can be applied prospectively and retrospectively, and at different stages of IR. The paper further describes causal pathways, intervention levers, and strategies for achieving health equity in global health settings through IR. Central to these pathways is the power asymmetries among different actors involved in IR in global health and how these contribute to health inequities. The paper suggests recommendations and strategies for shifting the balance of power among these actors while addressing the structural and systemic determinants of health inequities as part of IR. Explicit considerations for health equity as part of implementation research and practice are needed for the achievement of global health goals. Such explicit considerations should look back as much as possible, and entail defining and analyzing health inequities and intervening on the underlying causes and mechanisms of health inequities as part of IR on a routine basis.

Bridges and Mechanisms: Integrating Systems Science Thinking into Implementation Research

We present a detailed argument for how to integrate, or bridge, systems science thinking and methods with implementation science. We start by showing how fundamental systems science principles of structure, dynamics, information, and utility are relevant for implementation science. Then we examine the need for implementation science to develop and apply richer theories of complex systems. This can be accomplished by emphasizing a causal mechanisms approach. Identifying causal mechanisms focuses on the "cogs and gears" of public health, clinical, and organizational interventions. A mechanisms approach focuses on how a specific strategy will produce the implementation outcome. We show how connecting systems science to implementation science opens new opportunities for examining and addressing social determinants of health and conducting equitable and ethical implementation research. Finally, we present case studies illustrating successful applications of systems science within implementation science in community health policy, tobacco control, health care access, and breast cancer screening.

Neighborhoods and Cardiovascular Health: A Scientific Statement From the American Heart Association

The neighborhoods where individuals reside shape environmental exposures, access to resources, and opportunities. The inequitable distribution of resources and opportunities across neighborhoods perpetuates and exacerbates cardiovascular health inequities. Thus, interventions that address the neighborhood environment could reduce the inequitable burden of cardiovascular disease in disenfranchised populations. The objective of this scientific statement is to provide a roadmap illustrating how current knowledge regarding the effects of neighborhoods on cardiovascular disease can be used to develop and implement effective interventions to improve cardiovascular health at the population, health system, community, and individual levels. PubMed/Medline, CINAHL, Cochrane Library reviews, and ClinicalTrials.gov were used to identify observational studies and interventions examining or targeting neighborhood conditions in relation to cardiovascular health. The scientific statement summarizes how neighborhoods have been incorporated into the actions of health care systems, interventions in community settings, and policies and interventions that involve modifying the neighborhood environment. This scientific statement presents promising findings that can be expanded and implemented more broadly and identifies methodological challenges in designing studies to evaluate important neighborhood-related policies and interventions. Last, this scientific statement offers recommendations for areas that merit further research to promote a deeper understanding of the contributions of neighborhoods to cardiovascular health and health inequities and to stimulate the development of more effective interventions.

Childhood Sugar-Sweetened Beverage Consumption: an Agent-Based Model of Context-Specific Reduction Efforts

INTRODUCTION

Despite widespread recognition among public health experts that childhood sugar-sweetened beverage consumption should be reduced, doing so has proven to be a challenge. An agent-based model of early childhood sugar-sweetened beverage consumption was applied to data from three high-quality, longitudinal cohort studies to gain insight into potentially effective intervention strategies across contexts.

METHODS

From 2021 to 2023, a single agent-based model design was applied to data sets derived from three separate cohorts of children followed from infancy to childhood, with very different populations and environments (participants recruited in 1999-2002; 2003-2010; and 2009-2014). After assessing its ability to reproduce observed consumption patterns across cohorts, it was used to simulate potential impacts of multiple intervention strategies across contexts.

RESULTS

Interventions reducing home availability of sugar-sweetened beverages consistently had the largest potential effects. Impact differed between cohort settings: a complete decrease in availability resulted in an estimated 87% decrease in overall early childhood consumption for one of the cohorts, compared with 61% and 54% in the others. Reducing availability in center-based child care resulted in substantially greater reduction in one cohort relative to the other two.

CONCLUSIONS

There is untapped potential for strategies targeting children's sugar-sweetened beverage consumption in the home, but in some instances, other approaches might also yield meaningful effects. Tailoring approach to setting may be important, and agent-based models can be informative for doing so. This agent-based model has broad generalizability and potential to serve as a tool for designing effective, context-specific strategies to reduce childhood sugar-sweetened beverage consumption.

Understanding Misimplementation in U.S. State Health Departments: An Agent-Based Model

INTRODUCTION

The research goal of this study is to explore why misimplementation occurs in public health agencies and how it can be reduced. Misimplementation is ending effective activities prematurely or continuing ineffective ones, which contributes to wasted resources and suboptimal health outcomes.

METHODS

The study team created an agent-based model that represents how information flow, filtered through organizational structure, capacity, culture, and leadership priorities, shapes continuation decisions. This agent-based model used survey data and interviews with state health department personnel across the U.S. between 2014 and 2020; model design and analyses were conducted with substantial input from stakeholders between 2019 and 2021. The model was used experimentally to identify potential approaches for reducing misimplementation.

RESULTS

Simulations showed that increasing either organizational evidence-based decision-making capacity or information sharing could reduce misimplementation. Shifting leadership priorities to emphasize effectiveness resulted in the largest reduction, whereas organizational restructuring did not reduce misimplementation.

CONCLUSIONS

The model identifies for the first time a specific set of factors and dynamic pathways most likely driving misimplementation and suggests a number of actionable strategies for reducing it. Priorities for training the public health workforce include evidence-based decision making and effective communication. Organizations will also benefit from an intentional shift in leadership decision-making processes. On the basis of this initial, successful application of agent-based model to misimplementation, this work provides a framework for further analyses.

Success of community-based system dynamics in prevention interventions: A systematic review of the literature

Systems thinking approaches are increasingly being used to help communities understand and develop responses to preventing complex health problems. Less is known about how success is characterized and what influences success in these approaches. We present a systematic review of how concepts of success are understood and evaluated in the peer reviewed literature of studies using systems thinking in community prevention. We searched five databases for peer-reviewed literature published between 2000 and 2022, with search terms related to systems thinking, prevention and community. Studies were included if they; reported using community-based systems thinking to prevent a public health problem; described the engagement and empowerment of community members to address a public health issue; and, were published in English. Thirty-four articles were identified from 10 countries. Twenty-one aimed to prevent a chronic disease (e.g., obesity) and 16 measured success using specific tools, 10 of which used semi-structured interviews or surveys. Measures of success included implementation processes, cultural appropriateness, the number or type of actions implemented, effectiveness of community action, and changes in individual thinking or mental models, population health outcomes, data collected, or systems level measures. Implementation factors influencing success included the capacity to engage participants, composition and experience of facilitators, strength of coordination teams, allocation of resources, adaptation to participant feedback, use of multiple systems approaches, workshop process providing time and methods to allow new insights, flexible delivery, and diversity of perspectives. Findings from each of the articles indicated that approaches increased a range of outcomes including community action, strategic thinking, future planning and evaluation, community buy-in, community voice, contribution and leadership, in addition to developing shared visions and goals and creating new, ongoing collaborations, among many others. Measures of success varied, suggesting more empirical reporting of proposed outcomes of system science in communities would be valuable. While the measurement of success in the use of systems thinking in community-based prevention efforts is limited, there are helpful examples we can look to for future measurement of success.

Promises and pitfalls in implementation science from the perspective of US-based researchers: learning from a pre-mortem

BACKGROUND

Implementation science is at a sufficiently advanced stage that it is appropriate for the field to reflect on progress thus far in achieving its vision, with a goal of charting a path forward. In this debate, we offer such reflections and report on potential threats that might stymie progress, as well as opportunities to enhance the success and impact of the field, from the perspective of a group of US-based researchers.

MAIN BODY

Ten mid-career extramurally funded US-based researchers completed a "pre-mortem" or a group brainstorming exercise that leverages prospective hindsight to imagine that an event has already occurred and to generate an explanation for it - to reduce the likelihood of a poor outcome. We came to consensus on six key themes related to threats and opportunities for the field: (1) insufficient impact, (2) too much emphasis on being a "legitimate science," (3) re-creation of the evidence-to-practice gap, (4) difficulty balancing accessibility and field coherence, (5) inability to align timelines and priorities with partners, and (6) overly complex implementation strategies and approaches.

CONCLUSION

We submit this debate piece to generate further discussion with other implementation partners as our field continues to develop and evolve. We hope the key opportunities identified will enhance the future of implementation research in the USA and spark discussion across international groups. We will continue to learn with humility about how best to implement with the goal of achieving equitable population health impact at scale.

Methods to improve the translation of evidence-based interventions: A primer on dissemination and implementation science for occupational safety and health researchers and practitioners

Objective

A limited focus on dissemination and implementation (D&I) science has hindered the uptake of evidence-based interventions (EBIs) that reduce workplace morbidity and mortality. D&I science methods can be used in the occupational safety and health (OSH) field to advance the adoption, implementation, and sustainment of EBIs for complex workplaces. These approaches should be responsive to contextual factors, including the needs of partners and beneficiaries (such as employers, employees, and intermediaries).

Methods

By synthesizing seminal literature and texts and leveraging our collective knowledge as D&I science and/or OSH researchers, we developed a D&I science primer for OSH. First, we provide an overview of common D&I terminology and concepts. Second, we describe several key and evolving issues in D&I science: balancing adaptation with intervention fidelity and specifying implementation outcomes and strategies. Next, we review D&I theories, models, and frameworks and offer examples for applying these to OSH research. We also discuss widely used D&I research designs, methods, and measures. Finally, we discuss future directions for D&I science application to OSH and provide resources for further exploration.

Results

We compiled a D&I science primer for OSH appropriate for practitioners and evaluators, especially those newer to the field.

Conclusion

This article fills a gap in the OSH research by providing an overview of D&I science to enhance understanding of key concepts, issues, models, designs, methods and measures for the translation into practice of effective OSH interventions to advance the safety, health and well-being of workers.

Using decision analysis to support implementation planning in research and practice

BACKGROUND

The process of implementing evidence-based interventions, programs, and policies is difficult and complex. Planning for implementation is critical and likely plays a key role in the long-term impact and sustainability of interventions in practice. However, implementation planning is also difficult. Implementors must choose what to implement and how best to implement it, and each choice has costs and consequences to consider. As a step towards supporting structured and organized implementation planning, we advocate for increased use of decision analysis.

MAIN TEXT

When applied to implementation planning, decision analysis guides users to explicitly define the problem of interest, outline different plans (e.g., interventions/actions, implementation strategies, timelines), and assess the potential outcomes under each alternative in their context. We ground our discussion of decision analysis in the PROACTIVE framework, which guides teams through key steps in decision analyses. This framework includes three phases: (1) definition of the decision problems and overall objectives with purposeful stakeholder engagement, (2) identification and comparison of different alternatives, and (3) synthesis of information on each alternative, incorporating uncertainty. We present three examples to illustrate the breadth of relevant decision analysis approaches to implementation planning.

CONCLUSION

To further the use of decision analysis for implementation planning, we suggest areas for future research and practice: embrace model thinking; build the business case for decision analysis; identify when, how, and for whom decision analysis is more or less useful; improve reporting and transparency of cost data; and increase collaborative opportunities and training.

A systems thinking approach to understanding youth active recreation

Background

Active recreation contributes to child and adolescent physical activity, however, factors affecting uptake are poorly understood at the systems level. The aims of this study were: (1) to use systems analysis methods to understand youth active recreation in Victoria, Australia, (ii) identify potential system leverage points to enhance active recreation, and (iii) explore stakeholder views of systems analysis methods for informing practice and policy decision-making.

Methods

Phase 1: Umbrella review of systematic reviews (2013–2018), synthesising evidence for correlates, determinants and intervention evidence for promoting active recreation. Phase 2: Development of three systems models (ActorMap and two ActivMaps), depicting active recreation actors/organisations, correlates, determinants and intervention evidence. Phase 3: Development of causal loop diagrams (CLDs) and identification of leverage points based on the Action Scales Model. Phase 4: Model feedback via stakeholder interviews (n = 23; 16 organisations).

Results

From the literature, 93 correlates and determinants, and 49 intervention strategies were associated with child and adolescent active recreation; the majority located at a social or individual level. Ten potential system leverage points were identified in the CLDs, which differed for pre-schoolers versus children and adolescents. Only time outdoors (an event leverage point) emerged for all age groups. Changes to the built and natural environment (i.e., land use planning, urban design) as a complete domain was a key structural leverage point for influencing active recreation in children and adolescents. Subject matter experts and stakeholder interviews identified 125 actors operating across seven hierarchical active recreation system levels in Victoria. Stakeholder interviews identified 12 areas for future consideration and recommendations for practice/policy influence.

Conclusions

Our findings underscore the need for dynamic models of system behaviour in active recreation, and to capture stakeholder influence as more than a transactional role in evidence generation and use. Effective responses to youth inactivity require a network of interventions that target specific leverage points across the system. Our models illustrate areas that may have the greatest system-level impact, such as changes to the built and natural environment, and they provide a tool for policy, appraisal, advocacy, and decision-making within and outside of government.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01292-2.

Internet Search Results for Older Adult Physical Activity Guidelines: Scoping Review

BACKGROUND

Older adults seek health-related information through casual internet searches. Yet, researchers focus on peer-reviewed journals and conference presentations as primary dissemination strategies. Representatives of mass media are alerted (passive diffusion) of new studies or recommendations, but the veracity of the information shared is not often analyzed, and when it is, the analysis is often not comprehensive. However, most older adults do not have access to peer-reviewed journal articles or paid subscription services for more reputable media outlets.

OBJECTIVE

We aimed to determine what information was readily available (ie, open access) to older adults who may casually search the internet for physical activity recommendations.

METHODS

We performed a 6-part scoping review to determine the research question and available evidence, and extract data within open-access top hits using popular online search engines. Results were categorized by a dissemination model that has categories of sources, channels, audience, and messages.

RESULTS

After the iterative search process, 92 unique articles were included and coded. Only 5 (5%) cited physical activity guidelines, and most were coded as promoting healthy aging (82/92, 89%) and positive framing (84/92, 91%). Most articles were posed as educational, but the authors' credentials were rarely reported (ie, 22% of the time). Muscle strengthening and balance components of the physical activity guidelines for older adults were rarely reported (72/92, 78% and 80/92, 87%, respectively) or inaccurately reported (3/92, 3% and 3/92, 3%, respectively).

CONCLUSIONS

Inconsistent messages lead to mistrust of science and public health representatives. This work highlights the lack of evidence within existing open-access resources. Further efforts are needed to ensure evidence-based public health messages are in the sources and channels older adults are using to inform their knowledge and behaviors.

The Application of Systems Science in Nutrition-Related Behaviors and Outcomes Implementation Research: A Scoping Review

Use of systems science can improve the dissemination and implementation (D&I) process. However, little is known about use of systems science in nutrition D&I research. The purpose of this article is to synthesize the ways in which systems science methodology is applied in nutrition D&I research. Scoping review methodology involved searching 6 academic databases for full-text, peer-reviewed, English articles published between 1970 and 2020 that employed systems science within nutrition D&I research. Data extraction included intervention type, population, study aim, methods, theoretical approach, outcomes, and results. Descriptive statistics and qualitative thematic analysis followed. Thirty-four retained articles qualitatively identified benefits (successful planning and organization of complex interventions) and challenges (limited resources, trainings, and lack of knowledge) to utilizing systems science in nutrition D&I research. Future research should work toward building knowledge capacity among nutrition practitioners by increasing available trainings and resources to enhance the utilization of systems science in nutrition D&I research.

Leveraging Complex Systems Science to Advance Sexual and Gender Minority Youth Health Research and Equity

Over the past two decades, sexual and gender minority (SGM) youth health inequities have remained the same or widened, highlighting the need for new approaches to foster health equity. Complex systems science (CSS) techniques must be added to our armamentarium because of the following: CSS techniques can model cyclical feedback loops inherent in the relationships between SGM youth health outcomes and their multilevel causes, thereby enhancing the integration of real-world complexity in scientific models; and CSS can simulate multiple hypothetical interventions, thereby identifying future interventions with great potential impact. We describe four promising CSS techniques for advancing SGM youth health equity.

Agent-Based Modeling for Implementation Research: An Application to Tobacco Smoking Cessation for Persons with Serious Mental Illness

Background

Implementation researchers have sought ways to use simulations to support the core components of implementation, which typically include assessing the need for change, designing implementation strategies, executing the strategies, and evaluating outcomes. The goal of this paper is to explain how agent-based modeling could fulfill this role.

Methods

We describe agent-based modeling with respect to other simulation methods that have been used in implementation science, using non-technical language that is broadly accessible. We then provide a stepwise procedure for developing agent-based models of implementation processes. We use, as a case study to illustrate the procedure, the implementation of evidence-based smoking cessation practices for persons with serious mental illness (SMI) in community mental health clinics.

Results

For our case study, we present descriptions of the motivating research questions, specific models used to answer these questions, and a summary of the insights that can be obtained from the models. In the first example, we use a simple form of agent-based modeling to simulate the observed smoking behaviors of persons with SMI in a recently completed trial (IDEAL, Comprehensive Cardiovascular Risk Reduction Trial in Persons with SMI). In the second example, we illustrate how a more complex agent-based approach that includes interactions between patients, providers and site administrators can be used to provide guidance for an implementation intervention that includes training and organizational strategies. This example is based in part on an ongoing project focused on scaling up evidence-based tobacco smoking cessation practices in community mental health clinics in Maryland.

Conclusion

In this paper we explain how agent-based models can be used to address implementation science research questions and provide a procedure for setting up simulation models. Through our examples, we show how what-if scenarios can be examined in the implementation process, which are particularly useful in implementation frameworks with adaptive components.

Dietary Policies and Programs: Moving Beyond Efficacy and Into "Real-World" Settings

Purpose: Dietary behaviors are key modifiable risk factors in averting cardiovascular disease (CVD), the leading cause of morbidity, mortality, and disability in the United States. Before investing in adoption and implementation, community-based organizations, public health practitioners, and policymakers—often working with limited resources—need to compare the population health impacts of different food policies and programs to determine priorities, build capacity, and maximize resources. Numerous reports, reviews, and policy briefs have synthesized across evidence-based policies and programs to make recommendations, but few have made a deep acknowledgment that dietary policies and programs are not implemented in a vacuum, and that “real-world” settings are complex, multifaceted and dynamic.

Methods: A narrative review was conducted of currently recommended evidence-based approaches to improving dietary behaviors, to describe and characterize applied and practical factors for consideration when adopting and implementing these dietary policies and programs across diverse settings.

Results: From the narrative review, six key considerations emerged to guide community-based organizations, public health practitioners, and policymakers on moving from the evidence base, toward implementation in local and community settings.

Conclusions: Considerations of “real-world” contextual factors are necessary and important when adopting and selecting evidence-based policies and programs to improve dietary behaviors and ultimately improve CVD outcomes. Promising approaches include those that apply community-partnered research and systems science to examine the equitable implementation of evidence-based dietary policies and programs.

From Need to Policy: Community Supported Development and Implementation of the South Carolina Vulnerable Adult Guardian Ad Litem (SC VAGAL) Program

Adult guardian ad litem programs are a necessary public service to protect adults from abuse and neglect. This article describes the development and implementation of an adult guardian ad litem program. We discuss the program's impetus, pilot testing, evaluation, and implementation of the program. Our experience highlights the vital role of diverse inter-sectoral stakeholders. Furthermore, the development process highlights the need for flexibility in program development, tension negotiation among stakeholders, and engagement of aging stakeholders in nontraditional arenas.

Qualitative process evaluation from a complex systems perspective: A systematic review and framework for public health evaluators

BACKGROUND

Public health evaluation methods have been criticized for being overly reductionist and failing to generate suitable evidence for public health decision-making. A "complex systems approach" has been advocated to account for real world complexity. Qualitative methods may be well suited to understanding change in complex social environments, but guidance on applying a complex systems approach to inform qualitative research remains limited and underdeveloped. This systematic review aims to analyze published examples of process evaluations that utilize qualitative methods that involve a complex systems perspective and proposes a framework for qualitative complex system process evaluations.

METHODS AND FINDINGS

We conducted a systematic search to identify complex system process evaluations that involve qualitative methods by searching electronic databases from January 1, 2014-September 30, 2019 (Scopus, MEDLINE, Web of Science), citation searching, and expert consultations. Process evaluations were included if they self-identified as taking a systems- or complexity-oriented approach, integrated qualitative methods, reported empirical findings, and evaluated public health interventions. Two reviewers independently assessed each study to identify concepts associated with the systems thinking and complexity science traditions. Twenty-one unique studies were identified evaluating a wide range of public health interventions in, for example, urban planning, sexual health, violence prevention, substance use, and community transformation. Evaluations were conducted in settings such as schools, workplaces, and neighborhoods in 13 different countries (9 high-income and 4 middle-income). All reported some utilization of complex systems concepts in the analysis of qualitative data. In 14 evaluations, the consideration of complex systems influenced intervention design, evaluation planning, or fieldwork. The identified studies used systems concepts to depict and describe a system at one point in time. Only 4 evaluations explicitly utilized a range of complexity concepts to assess changes within the system resulting from, or co-occurring with, intervention implementation over time. Limitations to our approach are including only English-language papers, reliance on study authors reporting their utilization of complex systems concepts, and subjective judgment from the reviewers relating to which concepts featured in each study.

CONCLUSION

This study found no consensus on what bringing a complex systems perspective to public health process evaluations with qualitative methods looks like in practice and that many studies of this nature describe static systems at a single time point. We suggest future studies use a 2-phase framework for qualitative process evaluations that seek to assess changes over time from a complex systems perspective. The first phase involves producing a description of the system and identifying hypotheses about how the system may change in response to the intervention. The second phase involves following the pathway of emergent findings in an adaptive evaluation approach.

Systems Science Approaches for Global Environmental Health Research: Enhancing Intervention Design and Implementation for Household Air Pollution (HAP) and Water, Sanitation, and Hygiene (WASH) Programs

BACKGROUND

Two of the most important causes of global disease fall in the realm of environmental health: household air pollution (HAP) and poor water, sanitation, and hygiene (WASH) conditions. Interventions, such as clean cookstoves, household water treatment, and improved sanitation facilities, have great potential to yield reductions in disease burden. However, in recent trials and implementation efforts, interventions to improve HAP and WASH conditions have shown few of the desired health gains, raising fundamental questions about current approaches.

OBJECTIVES

We describe how the failure to consider the complex systems that characterize diverse real-world conditions may doom promising new approaches prematurely. We provide examples of the application of systems approaches, including system dynamics, network analysis, and agent-based modeling, to the global environmental health priorities of HAP and WASH research and programs. Finally, we offer suggestions on how to approach systems science.

METHODS

Systems science applied to environmental health can address major challenges by a) enhancing understanding of existing system structures and behaviors that accelerate or impede aims; b) developing understanding and agreement on a problem among stakeholders; and c) guiding intervention and policy formulation. When employed in participatory processes that engage study populations, policy makers, and implementers, systems science helps ensure that research is responsive to local priorities and reflect real-world conditions. Systems approaches also help interpret unexpected outcomes by revealing emergent properties of the system due to interactions among variables, yielding complex behaviors and sometimes counterintuitive results.

DISCUSSION

Systems science offers powerful and underused tools to accelerate our ability to identify barriers and facilitators to success in environmental health interventions. This approach is especially useful in the context of implementation research because it explicitly accounts for the interaction of processes occurring at multiple scales, across social and environmental dimensions, with a particular emphasis on linkages and feedback among these processes. https://doi.org/10.1289/EHP7010.

Determinants of Implementing Evidence-Based Trauma-Focused Interventions for Children and Youth: A Systematic Review

A systematic review was conducted to identify determinants (barriers and facilitators) of implementing evidence-based psychosocial interventions for children and youth who experience emotional or behavioral difficulties due to trauma exposure. Determinants were coded, abstracted, and synthesized using the Exploration, Preparation, Implementation, and Sustainment framework. Twenty-three articles were included, all of which examined implementation of Trauma-Focused Cognitive Behavioral Therapy or Cognitive-Behavioral Intervention for Trauma in Schools. This review identified multilevel and multiphase determinants that can be addressed by implementation strategies to improve implementation and clinical outcomes, and suggests how future studies might address gaps in the evidence base.

Health system decision-makers at the helm of implementation research: development of a framework to evaluate the processes and effectiveness of embedded approaches

Background

Embedded approaches to implementation research (IR), whereby health system decision-makers participate actively in the research process, are gaining traction as effective approaches to optimise the delivery of health programmes and policies. However, the evidence base on the processes and effectiveness of such collaborative research remains inchoate. Standardised approaches to evaluate these initiatives are needed to identify core elements of ‘embeddedness’, unveil the underlying pathways of change, and assess contribution to evidence uptake in decision-making and overall outcomes of effect. The framework presented in this paper responds to this need, designed to guide the systematic evaluation of embedded IR.

Methods

This evaluation framework for embedded IR approaches is based on the experience of a joint initiative by the Pan American Health Organization/Alliance for Health Policy and Systems Research, which has supported 19 IR grants in 10 Latin American and Caribbean countries from 2014 to 2017. The conceptualisation of this framework drew on various sources of information, including empirical evidence and conceptual insights from the literature, interviews with content experts, and a prospective evaluation of the 2016 cohort that included semi-structured key informant interviews, document analysis, and a research team survey to examine key aspects of embedded research.

Results

We developed a widely applicable conceptual framework to guide the evaluation of embedded IR in various contexts. Focused on uncovering how this collaborative research approach influences programme improvement, it outlines expected processes and intermediate outcomes. It also highlights constructs with which to assess ‘embeddedness’ as well as critical contextual factors. The framework is intended to provide a structure by which to systematically examine such embedded research initiatives, proposing three key stages of evidence-informed decision-making – co-production of evidence, engagement with research, and enactment of programme changes.

Conclusion

Rigorous evaluation of embedded IR is needed to build the evidence on its processes and effectiveness in influencing decision-making. The evaluation framework presented here addresses this gap with consideration of the complexity of such efforts. Its applicability to similar initiatives is bolstered by virtue of being founded on real-world experience; its potential to contribute to a nuanced understanding of embedded IR is significant.

'Turning the tide' on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling

INTRODUCTION

Hyperglycemia in pregnancy (HIP, including gestational diabetes and pre-existing type 1 and type 2 diabetes) is increasing, with associated risks to the health of women and their babies. Strategies to manage and prevent this condition are contested. Dynamic simulation models (DSM) can test policy and program scenarios before implementation in the real world. This paper reports the development and use of an advanced DSM exploring the impact of maternal weight status interventions on incidence of HIP.

METHODS

A consortium of experts collaboratively developed a hybrid DSM of HIP, comprising system dynamics, agent-based and discrete event model components. The structure and parameterization drew on a range of evidence and data sources. Scenarios comparing population-level and targeted prevention interventions were simulated from 2018 to identify the intervention combination that would deliver the greatest impact.

RESULTS

Population interventions promoting weight loss in early adulthood were found to be effective, reducing the population incidence of HIP by 17.3% by 2030 (baseline ('business as usual' scenario)=16.1%, 95% CI 15.8 to 16.4; population intervention=13.3%, 95% CI 13.0 to 13.6), more than targeted prepregnancy (5.2% reduction; incidence=15.3%, 95% CI 15.0 to 15.6) and interpregnancy (4.2% reduction; incidence=15.5%, 95% CI 15.2 to 15.8) interventions. Combining targeted interventions for high-risk groups with population interventions promoting healthy weight was most effective in reducing HIP incidence (28.8% reduction by 2030; incidence=11.5, 95% CI 11.2 to 11.8). Scenarios exploring the effect of childhood weight status on entry to adulthood demonstrated significant impact in the selected outcome measure for glycemic regulation, insulin sensitivity in the short term and HIP in the long term.

DISCUSSION

Population-level weight reduction interventions will be necessary to 'turn the tide' on HIP. Weight reduction interventions targeting high-risk individuals, while beneficial for those individuals, did not significantly impact forecasted HIP incidence rates. The importance of maintaining interventions promoting healthy weight in childhood was demonstrated.

Introduction to the Theme Issue on Dynamics of Health Behavior: Revisiting Systems Science for Population Health

Systems science can help public health professionals to better understand the complex dynamics between factors affecting health behaviors and outcomes and to identify intervention opportunities. Despite their demonstrated utility in addressing health topics such influenza, tobacco control, and obesity, the associated methods continue to be underutilized by researchers and practitioners addressing health behaviors. This article discusses the growth of systems science methods (e.g., system dynamics, social network analysis, and agent-based modeling) in health research, provides a frame for the articles included in this themed issue, and closes with recommendations for enhancing the future of systems science and health behavior research. We argue that integrating systems sciences methods into health behavior research and practice is essential for improved population health and look forward to supporting the evolution of the field.

Commentary on Scaling-up Evidence-based Interventions in US Public Systems to Prevent Behavioral Health Problems

As evidence-based interventions (EBIs) to prevent mental, emotional, and behavioral health problems continue to become available, approaches for implementation in systems and settings, at scale, are needed. The article, Scaling-up Evidence-based Interventions in U.S. Public Systems to Prevent Behavioral Health Problems: Challenges and Opportunities (Fagan et al. 2019) examines five large, complex public systems (behavioral health, child welfare, education, juvenile justice, and public health) that have adopted and implemented EBIs in various ways and presents common factors that support scale-up in these systems. This commentary builds on the authors' strategic approach to offer a few additional considerations-issues of sustainability, ways of thinking about knowledge creation, and use of systems science/modeling approaches-to address scale-up in public systems. Moreover, the focus on public systems provides an opportunity to consider how the implementation and sustainment of EBIs might more directly address social determinants of health that are relevant across policy areas and public systems.

Social network interventions for health behaviours and outcomes: A systematic review and meta-analysis

BACKGROUND

There has been a growing interest in understanding the effects of social networks on health-related behaviour, with a particular backdrop being the emerging prominence of complexity or systems science in public health. Social network interventions specifically use or alter the characteristics of social networks to generate, accelerate, or maintain health behaviours. We conducted a systematic review and meta-analysis to investigate health behaviour outcomes of social network interventions.

METHODS AND FINDINGS

We searched eight databases and two trial registries from 1990 to May 28, 2019, for English-language reports of randomised controlled trials (RCTs) and before-and-after studies investigating social network interventions for health behaviours and outcomes. Trials that did not specifically use social networks or that did not include a comparator group were excluded. We screened studies and extracted data from published reports independently. The primary outcome of health behaviours or outcomes at ≤6 months was assessed by random-effects meta-analysis. Secondary outcomes included those measures at >6-12 months and >12 months. This study is registered with the International Prospective Register of Systematic Reviews, PROSPERO: CRD42015023541. We identified 26,503 reports; after exclusion, 37 studies, conducted between 1996 and 2018 from 11 countries, were eligible for analysis, with a total of 53,891 participants (mean age 32.4 years [SD 12.7]; 45.5% females). A range of study designs were included: 27 used RCT/cluster RCT designs, and 10 used other study designs. Eligible studies addressed a variety of health outcomes, in particular sexual health and substance use. Social network interventions showed a significant intervention effect compared with comparator groups for sexual health outcomes. The pooled odds ratio (OR) was 1.46 (95% confidence interval [CI] 1.01-2.11; I2 = 76%) for sexual health outcomes at ≤6 months and OR 1.51 (95% CI 1.27-1.81; I2 = 40%) for sexual health outcomes at >6-12 months. Intervention effects for drug risk outcomes at each time point were not significant. There were also significant intervention effects for some other health outcomes including alcohol misuse, well-being, change in haemoglobin A1c (HbA1c), and smoking cessation. Because of clinical and measurement heterogeneity, it was not appropriate to pool data on these other behaviours in a meta-analysis. For sexual health outcomes, prespecified subgroup analyses were significant for intervention approach (p < 0.001), mean age of participants (p = 0.002), and intervention length (p = 0.05). Overall, 22 of the 37 studies demonstrated a high risk of bias, as measured by the Cochrane Risk of Bias tool. The main study limitations identified were the inclusion of studies of variable quality; difficulty in isolating the effects of specific social network intervention components on health outcomes, as interventions included other active components; and reliance on self-reported outcomes, which have inherent recall and desirability biases.

CONCLUSIONS

Our findings suggest that social network interventions can be effective in the short term (<6 months) and longer term (>6 months) for sexual health outcomes. Intervention effects for drug risk outcomes at each time point were not significant. There were also significant intervention effects for some other health outcomes including alcohol misuse, well-being, change in HbA1c, and smoking cessation.

Leveraging system sciences methods in clinical trial evaluation: An example concerning African American women diagnosed with breast cancer via the Patient Navigation in Medically Underserved Areas study

BACKGROUND

Systems science methodologies offer a promising assessment approach for clinical trials by: 1) providing an in-silico laboratory to conduct investigations where purely empirical research may be infeasible or unethical; and, 2) offering a more precise measurement of intervention benefits across individual, network, and population levels. We propose to assess the potential of systems sciences methodologies by quantifying the spillover effects of randomized controlled trial via empirical social network analysis and agent-based models (ABM).

DESIGN/METHODS

We will evaluate the effects of the Patient Navigation in Medically Underserved Areas (PNMUA) study on adult African American participants diagnosed with breast cancer and their networks through social network analysis and agent-based modeling. First, we will survey 100 original trial participants (50 navigated, 50 non-navigated) and 150 of members of their social networks (75 from navigated, 75 non-navigated) to assess if navigation results in: 1) greater dissemination of breast health information and breast healthcare utilization throughout the trial participants' networks; and, 2) lower incremental costs, when incorporating navigation effects on trial participants and network members. Second, we will compare cost-effectiveness models, using a provider perspective, incorporating effects on trial participants versus trial participants and network members. Third, we will develop an ABM platform, parameterized using published data sources and PNMUA data, to examine if navigation increases the proportion of early stage breast cancer diagnoses.

DISCUSSION

Our study results will provide promising venues for leveraging systems science methodologies in clinical trial evaluation.

Complex Systems Approaches to Diet: A Systematic Review

CONTEXT

Complex systems approaches can help to elucidate mechanisms that shape population-level patterns in diet and inform policy approaches. This study reports results of a structured review of key design elements and methods used by existing complex systems models of diet.

EVIDENCE ACQUISITION

The authors conducted systematic searches of the PubMed, Web of Science, and LILACS databases between May and September 2018 to identify peer-reviewed manuscripts that used agent-based models or system dynamics models to explore diet. Searches occurred between November 2017 and May 2018. The authors extracted relevant data regarding each study's diet and nutrition outcomes; use of data for parameterization, calibration, and validation; results; and generated insights. The literature search adhered to PRISMA guidelines.

EVIDENCE SYNTHESIS

Twenty-two agent-based model studies and five system dynamics model studies met the inclusion criteria. Mechanistic studies explored neighborhood- (e.g., residential segregation), interpersonal- (e.g., social influence) and individual-level (e.g., heuristics that guide food purchasing decisions) mechanisms that influence diet. Policy-oriented studies examined policies related to food pricing, the food environment, advertising, nutrition labels, and social norms. Most studies used empirical data to inform values of key parameters; studies varied in their approaches to calibration and validation.

CONCLUSIONS

Opportunities remain to advance the state of the science of complex systems approaches to diet and nutrition. These include using models to better understand mechanisms driving population-level diet, increasing use of models for policy decision support, and leveraging the wide availability of epidemiologic and policy evaluation data to improve model validation.

Turning conceptual systems maps into dynamic simulation models: An Australian case study for diabetes in pregnancy

BACKGROUND

System science approaches are increasingly used to explore complex public health problems. Quantitative methods, such as participatory dynamic simulation modelling, can mobilise knowledge to inform health policy decisions. However, the analytic and practical steps required to turn collaboratively developed, qualitative system maps into rigorous and policy-relevant quantified dynamic simulation models are not well described. This paper reports on the processes, interactions and decisions that occurred at the interface between modellers and end-user participants in an applied health sector case study focusing on diabetes in pregnancy.

METHODS

An analysis was conducted using qualitative data from a participatory dynamic simulation modelling case study in an Australian health policy setting. Recordings of participatory model development workshops and subsequent meetings were analysed and triangulated with field notes and other written records of discussions and decisions. Case study vignettes were collated to illustrate the deliberations and decisions made throughout the model development process.

RESULTS

The key analytic objectives and decision-making processes included: defining the model scope; analysing and refining the model structure to maximise local relevance and utility; reviewing and incorporating evidence to inform model parameters and assumptions; focusing the model on priority policy questions; communicating results and applying the models to policy processes. These stages did not occur sequentially; the model development was cyclical and iterative with decisions being re-visited and refined throughout the process. Storytelling was an effective strategy to both communicate and resolve concerns about the model logic and structure, and to communicate the outputs of the model to a broader audience.

CONCLUSION

The in-depth analysis reported here examined the application of participatory modelling methods to move beyond qualitative conceptual mapping to the development of a rigorously quantified and policy relevant, complex dynamic simulation model. The analytic objectives and decision-making themes identified provide guidance for interpreting, understanding and reporting future participatory modelling projects and methods.

Application of System Dynamics to Inform a Model of Adolescent SBIRT Implementation in Primary Care Settings

System dynamics (SD) modeling is used to compare and contrast strategies for effective implementation of an evidence-based adolescent behavioral health treatment in primary care settings. With qualitative and quantitative data from an on-going cluster-randomized trial in 7 federally qualified health center sites, two implementation conditions were compared: generalist vs. specialist. In the generalist approach, the primary care provider (PCP) delivered brief intervention (BI) for substance misuse (n = 4 clinics). In the specialist approach, BIs were delivered by behavioral health counselors (BHCs) (n = 3 clinics). The resultant SD model compared 'basecase' dynamics to strategic approaches to deploying continuous technical assistance (TA) and performance feedback reporting (PFR). The basecase effectively represented the SBIRT intervention, which reflected actual monthly volume of adolescent primary care visits (N = 9639), screenings (N = 5937), positive screenings (N = 246), and brief interventions (BIs; N = 50) over the 20-month implementation period. Insights gained suggest that implementation outcomes are sensitive to frequency of PFR, with bimonthly events generating the most rapid and sustained screening results. Simulated trends indicated that availability of the BHC directly impacts success of the specialist model. Similarly, understanding PCPs' perception of severity of need for intervention is key to outcomes in either condition.

A scoping review of simulation modeling in built environment and physical activity research: Current status, gaps, and future directions for improving translation

Existing reviews have suggested that simulation studies of physical activity and environments are an emerging area, but none have explored findings in this area systematically. We used a scoping review framework to assess the use of simulation modeling to inform decision-making about built environment influences on physical activity. A systematic literature search was conducted in multiple databases in January 2018. Sixteen articles met the inclusion criteria. The studies evaluated interventions and features that were related to neighborhood safety (crime or traffic), active transportation, land use design, and walking and biking infrastructure. All of the studies focused on urban areas and most considered heterogeneity of outcomes based on local context. The majority of studies (70%) did not appear to have engaged or been used by practitioners or policy-makers to inform real-world decisions. There has been a growth of simulation modeling studies, but there remain gaps. The studies evaluated built environment interventions that have been recommended by expert panels, but more were of interventions related to active transportation; few considered recommended interventions to support recreational activity. Furthermore, studies have all focused on urban settings and there is a need to consider non-urban settings and how heterogeneity could reduce or exacerbate health disparities. More work to involve and evaluate practices for engaging stakeholders in model development and interpretation is also needed to overcome the translation of simulation research to practice gap, and realize its potential impact on the built environment and physical activity.

Building capacity for Public Health 3.0: introducing implementation science into an MPH curriculum

Background

Many public health programs fail because of an inability to implement tested interventions in diverse, complex settings. The field of implementation science is engaged in developing strategies for successful implementation, but current training is primarily researcher-focused. To tackle the challenges of the twenty-first century, public health leaders are promoting a new model titled Public Health 3.0 where public health practitioners become “chief health strategists” and develop interdisciplinary skills for multisector engagement to achieve impact. This requires broad training for public health practitioners in implementation science that includes the allied fields of systems and design thinking, quality improvement, and innovative evaluation methods. At UNC Chapel Hill’s Gillings School of Global Public Health, we created an interdisciplinary set of courses in applied implementation science for Master of Public Health (MPH) students and public health practitioners. We describe our rationale, conceptual approach, pedagogy, courses, and initial results to assist other schools contemplating similar programs.

Methods

Our conceptual approach recognized the vital relationship between implementation research and practice. We conducted a literature review of thought leaders in public health to identify skill areas related to implementation science that are priorities for the future workforce. We also reviewed currently available training programs in implementation science to understand their scope and objectives and to assess whether any of these would be a fit for these priorities. We used a design focused implementation framework to create four linked courses drawing from multiple fields such as engineering, management, and the social sciences and emphasizing application through case studies. We validated the course content by mapping them to implementation science competencies in the literature.

Results

To date, there is no other program that provides comprehensive interdisciplinary skills in applied implementation science for MPH students. As of April 2018, we have offered a total of eleven sections of the four courses, with a total enrollment of 142, of whom 127 have been master’s-level students in the school of public health. Using Kirkpatrick’s Model, we found positive student reaction, learning, and behavior. Many students have completed applied implementation science focused practicums, master’s papers, and special studies.

Conclusions

A systematically designed interdisciplinary curriculum in applied implementation science for MPH students has been found by students to be a useful set of skills. Students have demonstrated the capability to master this material and incorporate it into their practicums and master’s papers.

Electronic supplementary material

The online version of this article (10.1186/s13012-019-0866-6) contains supplementary material, which is available to authorized users.

Implementation science to reduce the prevalence and burden of MSK disorders following sport and exercise-related injury

Although safety in sports and physical activity is an important prerequisite for continuing participation and maintenance of a healthy, physically active lifestyle, to date little effort has been placed upon moving evidence into preventive practice. Amongst researchers it is still often assumed that a program will disseminate itself after proven to be effective. Recently, however, there has been an increased recognition of the importance of theory-driven approaches to enhance implementation research. This manuscript aims to provide guidance for sports and physical activity injury researchers and practitioners to perform implementation research and practice. First, we will discuss the differences between research questions across the research spectrum and explain the 'drop' in effect when moving controlled evidence to a practical context. We will discuss two ways of increasing real-world effectiveness of preventive programs, i.e. through targeting the users' behaviour or through revising the intervention. Finally, we will present various implementation frameworks and tools that can guide the reader in their own efforts towards implementation practice and research.

Enhancing the Impact of Implementation Strategies in Healthcare: A Research Agenda

The field of implementation science was developed to better understand the factors that facilitate or impede implementation and generate evidence for implementation strategies. In this article, we briefly review progress in implementation science, and suggest five priorities for enhancing the impact of implementation strategies. Specifically, we suggest the need to: (1) enhance methods for designing and tailoring implementation strategies; (2) specify and test mechanisms of change; (3) conduct more effectiveness research on discrete, multi-faceted, and tailored implementation strategies; (4) increase economic evaluations of implementation strategies; and (5) improve the tracking and reporting of implementation strategies. We believe that pursuing these priorities will advance implementation science by helping us to understand when, where, why, and how implementation strategies improve implementation effectiveness and subsequent health outcomes.

Engaging African American Men as Citizen Scientists to Validate a Prostate Cancer Biomarker: Work-in-Progress

BACKGROUND

African American men (AAM) are under-represented in prostate cancer (PCa) research despite known disparities. Screening with prostate-specific antigen (PSA) has low specificity for high-grade PCa leading to PCa over diagnosis. The Prostate Health Index (PHI) has higher specificity for lethal PCa but needs validation in AAM. Engaging AAM as citizen scientists (CSs) may improve participation of AAM in PCa research.Results and Lessons Learned: Eight CSs completed all training modules and 139 AAM were recruited. Challenges included equity in research leadership among multiple principal investigators (PIs) and coordinating CSs trainings.

CONCLUSIONS

Engaging AAM CSs can support engaging/recruiting AAM in PCa biomarker validation research. Equity among multiple stakeholders can be challenging, but proves beneficial in engaging AAM in research.

OBJECTIVES

Assess feasibility of mobilizing CSs to recruit AAM as controls for PHI PCa validation biomarker study.

METHODS

We highlight social networks/assets of stakeholders, CSs curriculum development/implementation, and recruitment of healthy controls for PHI validation.

eB4CAST: An Evidence-Based Tool to Promote Dissemination and Implementation in Community-Based, Public Health Research

eB4CAST, evidence-Based forecast C-capture, A-assemble, S-sustain, T-timelessness (eB4CAST), framework was developed from existing dissemination and implementation (D & I) constructs as a dissemination tool to promote community-based program usability and future application in targeted populations. eB4CAST captures and transforms research findings into a dissemination report that shows program need and impact to endorse program continuation and expansion. This is achieved through direct and indirect data collection of community factors and program impact that can showcase the need for program sustainability and potential for future dissemination sites. Testimonials, individual feedback, and program process and outcomes contribute to the direct data while data collected from census, county, and state databases and reports allow for indirect information to be captured and analyzed. Capturing data in the two levels allow eB4CAST to forecast program need and highlight program impact through a footprint. eB4CAST framework for dissemination tool creation is organized into four sections: Capture, Assemble, Sustainability, and Timelessness. Capture encompasses the collection of indirect and direct data related to intervention goals. Assemble is the compilation of the data into a visually appealing and easily understood media. Sustainability encourages the use of dissemination tools to provide forecast of program need and footprint of program impact back to community participants, program leaders, and key stakeholders to endorse program sustainability. Lastly, timelessness encourages cyclic movement through these constructs to continue program monitoring and data sharing to ensure timeless program evaluation and conformation to change in needs. The eB4CAST framework provides a systematic method to capture justification of program need and impact of community-based research that can be modified to fit diverse public health interventions providing a necessary D & I tool.

Implementation and scale up of population physical activity interventions for clinical and community settings: the PRACTIS guide

Background

Few efficacious physical activity interventions are successfully translated and sustained in practice. We propose a practical guide for researchers to increase the likelihood of successful implementation and scale up of physical activity interventions in practice contexts. The guide is based on two principles: (i) differences between the research and practice context can be addressed during intervention development and implementation planning by focusing on system, delivery personnel, and intervention characteristics; and (ii) early planning for implementation barriers and facilitators can improve subsequent translation into practice.

Methods

From the published literature, we identified evidence of strategies to improve research-practice translation, along with narrative descriptions of different approaches to addressing translational challenges. These, along with constructs taken from widely cited implementation outcome, process, and mechanistic models were collated and inform the guide.

Results

The resultant PRACTIS guide (PRACTical planning for Implementation and Scale-up) comprised the following four iterative steps: Step 1) Characterize the parameters of the implementation setting; Step 2) Identify and engage key stakeholders across multiple levels within the delivery system(s); Step 3) Identify contextual barriers and facilitators to implementation, and; Step 4) Address potential barriers to effective implementation.

Conclusions

A lack of practical guidance for researchers on how to effectively plan implementation and scale up of physical activity interventions prevents us moving quickly from evidence to action. We recommend that intervention development and adaptation for broad and sustained implementation be prioritized early in intervention planning and include active engagement from delivery organizations and stakeholders. The PRACTIS guide is also relevant for clinical and public health researchers in other areas of prevention.

Electronic supplementary material

The online version of this article (10.1186/s12966-018-0678-0) contains supplementary material, which is available to authorized users.

Toward optimal implementation of cancer prevention and control programs in public health: a study protocol on mis-implementation

BACKGROUND

Much of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes.

METHODS

This is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation.

DISCUSSION

This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas.

Consensus modeling to develop the farmers' market readiness assessment and decision instrument

Nutrition-related policy, system, and environmental (PSE) interventions such as farmers' markets have been recommended as effective strategies for promoting healthy diet for chronic disease prevention. Tools are needed to assess community readiness and capacity factors influencing successful farmers' market implementation among diverse practitioners in different community contexts. We describe a multiphase consensus modeling approach used to develop a diagnostic tool for assessing readiness and capacity to implement farmers' market interventions among public health and community nutrition practitioners working with low-income populations in diverse contexts. Modeling methods included the following: phase 1, qualitative study with community stakeholders to explore facilitators and barriers influencing successful implementation of farmers' market interventions in low-income communities; phase 2, development of indicators based on operationalization of qualitative findings; phase 3, assessment of relevance and importance of indicators and themes through consensus conference with expert panel; phase 4, refinement of indicators based on consensus conference; and phase 5, pilot test of the assessment tool. Findings illuminate a range of implementation factors influencing farmers' market PSE interventions and offer guidance for tailoring intervention delivery based on levels of community, practitioner, and organizational readiness and capacity.

Variation in Research Designs Used to Test the Effectiveness of Dissemination and Implementation Strategies: A Review

Background

The need for optimal study designs in dissemination and implementation (D&I) research is increasingly recognized. Despite the wide range of study designs available for D&I research, we lack understanding of the types of designs and methodologies that are routinely used in the field. This review assesses the designs and methodologies in recently proposed D&I studies and provides resources to guide design decisions.

Methods

We reviewed 404 study protocols published in the journal Implementation Science from 2/2006 to 9/2017. Eligible studies tested the efficacy or effectiveness of D&I strategies (i.e., not effectiveness of the underlying clinical or public health intervention); had a comparison by group and/or time; and used ≥1 quantitative measure. Several design elements were extracted: design category (e.g., randomized); design type [e.g., cluster randomized controlled trial (RCT)]; data type (e.g., quantitative); D&I theoretical framework; levels of treatment assignment, intervention, and measurement; and country in which the research was conducted. Each protocol was double-coded, and discrepancies were resolved through discussion.

Results

Of the 404 protocols reviewed, 212 (52%) studies tested one or more implementation strategy across 208 manuscripts, therefore meeting inclusion criteria. Of the included studies, 77% utilized randomized designs, primarily cluster RCTs. The use of alternative designs (e.g., stepped wedge) increased over time. Fewer studies were quasi-experimental (17%) or observational (6%). Many study design categories (e.g., controlled pre-post, matched pair cluster design) were represented by only one or two studies. Most articles proposed quantitative and qualitative methods (61%), with the remaining 39% proposing only quantitative. Half of protocols (52%) reported using a theoretical framework to guide the study. The four most frequently reported frameworks were Consolidated Framework for Implementing Research and RE-AIM (n = 16 each), followed by Promoting Action on Research Implementation in Health Services and Theoretical Domains Framework (n = 12 each).

Conclusion

While several novel designs for D&I research have been proposed (e.g., stepped wedge, adaptive designs), the majority of the studies in our sample employed RCT designs. Alternative study designs are increasing in use but may be underutilized for a variety of reasons, including preference of funders or lack of awareness of these designs. Promisingly, the prevalent use of quantitative and qualitative methods together reflects methodological innovation in newer D&I research.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling

BACKGROUND

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools.

OBJECTIVE

This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings.

CONCLUSION

Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Using Systems Science to Inform Population Health Strategies in Local Health Departments: A Case Study in San Antonio, Texas

OBJECTIVES

Because of state and federal health care reform, local health departments play an increasingly prominent role leading and coordinating disease prevention programs in the United States. This case study shows how a local health department working in chronic disease prevention and management can use systems science and evidence-based decision making to inform program selection, implementation, and assessment; enhance engagement with local health systems and organizations; and possibly optimize health care delivery and population health.

METHODS

The authors built a systems-science agent-based simulation model of diabetes progression for the San Antonio Metropolitan Health District, a local health department, to simulate health and cost outcomes for the population of San Antonio for a 20-year period (2015-2034) using 2 scenarios: 1 in which hemoglobin A1c (HbA1c) values for a population were similar to the current distribution of values in San Antonio, and the other with a hypothetical 1-percentage-point reduction in HbA1c values.

RESULTS

They projected that a 1-percentage-point reduction in HbA1c would lead to a decrease in the 20-year prevalence of end-stage renal disease from 1.7% to 0.9%, lower extremity amputation from 4.6% to 2.9%, blindness from 15.1% to 10.7%, myocardial infarction from 23.8% to 17.9%, and stroke from 9.8% to 7.2%. They estimated annual direct medical cost savings (in 2015 US dollars) from reducing HbA1c by 1 percentage point ranging from $6842 (myocardial infarction) to $39 800 (end-stage renal disease) for each averted case of diabetes complications.

CONCLUSIONS

Local health departments could benefit from the use of systems science and evidence-based decision making to estimate public health program effectiveness and costs, calculate return on investment, and develop a business case for adopting programs.

Are general and strategic measures of organizational context and leadership associated with knowledge and attitudes toward evidence-based practices in public behavioral health settings? A cross-sectional observational study

BACKGROUND

Examining the role of modifiable barriers and facilitators is a necessary step toward developing effective implementation strategies. This study examines whether both general (organizational culture, organizational climate, and transformational leadership) and strategic (implementation climate and implementation leadership) organizational-level factors predict therapist-level determinants of implementation (knowledge of and attitudes toward evidence-based practices).

METHODS

Within the context of a system-wide effort to increase the use of evidence-based practices (EBPs) and recovery-oriented care, we conducted an observational, cross-sectional study of 19 child-serving agencies in the City of Philadelphia, including 23 sites, 130 therapists, 36 supervisors, and 22 executive administrators. Organizational variables included characteristics such as EBP initiative participation, program size, and proportion of independent contractor therapists; general factors such as organizational culture and climate (Organizational Social Context Measurement System) and transformational leadership (Multifactor Leadership Questionnaire); and strategic factors such as implementation climate (Implementation Climate Scale) and implementation leadership (Implementation Leadership Scale). Therapist-level variables included demographics, attitudes toward EBPs (Evidence-Based Practice Attitudes Scale), and knowledge of EBPs (Knowledge of Evidence-Based Services Questionnaire). We used linear mixed-effects regression models to estimate the associations between the predictor (organizational characteristics, general and strategic factors) and dependent (knowledge of and attitudes toward EBPs) variables.

RESULTS

Several variables were associated with therapists' knowledge of EBPs. Clinicians in organizations with more proficient cultures or higher levels of transformational leadership (idealized influence) had greater knowledge of EBPs; conversely, clinicians in organizations with more resistant cultures, more functional organizational climates, and implementation climates characterized by higher levels of financial reward for EBPs had less knowledge of EBPs. A number of organizational factors were associated with the therapists' attitudes toward EBPs. For example, more engaged organizational cultures, implementation climates characterized by higher levels of educational support, and more proactive implementation leadership were all associated with more positive attitudes toward EBPs.

CONCLUSIONS

This study provides evidence for the importance of both general and strategic organizational determinants as predictors of knowledge of and attitudes toward EBPs. The findings highlight the need for longitudinal and mixed-methods studies that examine the influence of organizational factors on implementation.

Home visitation programs: an untapped opportunity for the delivery of early childhood obesity prevention

BACKGROUND

Extant obesity efforts have had limited impact among low-income underserved children, in part because of limitations inherent to existing programs: (i) short duration and low intensity; (ii) late timing of implementation, when children are already overweight or obese; (iii) intervention delivery limiting their accessibility and sustainability; and (iv) failure to address barriers such as a lack of culturally competent services, poverty and housing instability, which interfere with healthy lifestyle changes.

OBJECTIVE

This concept paper proposes an innovative model of obesity prevention implemented in infancy and sustained throughout early childhood to address the limitations of current obesity prevention efforts. Specifically, we propose to integrate sustained, weekly, in-home obesity prevention as part of the services already delivered by ongoing Home Visitation Programs, which currently do not target obesity prevention.

CONCLUSION

The home visiting structure represents an ideal model for impactful obesity prevention as home visitation programs: (i) already provide comprehensive services to diverse low-income infants and families who are most at risk for obesity and poor health because of socio-economic and structural conditions; (ii) services are initiated in infancy and sustained throughout critical developmental periods for the formation of healthy/unhealthy behaviors; and (iii) have been in place for more than 40 years, with a widespread presence across the United States and nationwide, which is critical for the scalability and sustainability of obesity prevention.

Extending systems thinking in planning and evaluation using group concept mapping and system dynamics to tackle complex problems

Group concept mapping (GCM) has been successfully employed in program planning and evaluation for over 25 years. The broader set of systems thinking methodologies (of which GCM is one), have only recently found their way into the field. We present an overview of systems thinking emerging from a system dynamics (SD) perspective, and illustrate the potential synergy between GCM and SD. As with GCM, participatory processes are frequently employed when building SD models; however, it can be challenging to engage a large and diverse group of stakeholders in the iterative cycles of divergent thinking and consensus building required, while maintaining a broad perspective on the issue being studied. GCM provides a compelling resource for overcoming this challenge, by richly engaging a diverse set of stakeholders in broad exploration, structuring, and prioritization. SD provides an opportunity to extend GCM findings by embedding constructs in a testable hypothesis (SD model) describing how system structure and changes in constructs affect outcomes over time. SD can be used to simulate the hypothesized dynamics inherent in GCM concept maps. We illustrate the potential of the marriage of these methodologies in a case study of BECOMING, a federally-funded program aimed at strengthening the cross-sector system of care for youth with severe emotional disturbances.

Enhancing implementation science by applying best principles of systems science

Background

Implementation science holds promise for better ensuring that research is translated into evidence-based policy and practice, but interventions often fail or even worsen the problems they are intended to solve due to a lack of understanding of real world structures and dynamic complexity. While systems science alone cannot possibly solve the major challenges in public health, systems-based approaches may contribute to changing the language and methods for conceptualising and acting within complex systems. The overarching goal of this paper is to improve the modelling used in dissemination and implementation research by applying best principles of systems science.

Discussion

Best principles, as distinct from the more customary term ‘best practices’, are used to underscore the need to extract the core issues from the context in which they are embedded in order to better ensure that they are transferable across settings. Toward meaningfully grappling with the complex and challenging problems faced in adopting and integrating evidence-based health interventions and changing practice patterns within specific settings, we propose and illustrate four best principles derived from our systems science experience: (1) model the problem, not the system; (2) pay attention to what is important, not just what is quantifiable; (3) leverage the utility of models as boundary objects; and (4) adopt a portfolio approach to model building. To improve our mental models of the real world, system scientists have created methodologies such as system dynamics, agent-based modelling, geographic information science and social network simulation. To understand dynamic complexity, we need the ability to simulate. Otherwise, our understanding will be limited. The practice of dynamic systems modelling, as discussed herein, is the art and science of linking system structure to behaviour for the purpose of changing structure to improve behaviour. A useful computer model creates a knowledge repository and a virtual library for internally consistent exploration of alternative assumptions.

Conclusion

Among the benefits of systems modelling are iterative practice, participatory potential and possibility thinking. We trust that the best principles proposed here will resonate with implementation scientists; applying them to the modelling process may abet the translation of research into effective policy and practice.

Electronic supplementary material

The online version of this article (doi:10.1186/s12961-016-0146-8) contains supplementary material, which is available to authorized users.