Benefits of Meeting the Healthy People 2030 Youth Sports Participation Target

INTRODUCTION

Healthy People 2030, a U.S. government health initiative, has indicated that increasing youth sports participation to 63.3% is a priority in the U.S. This study quantified the health and economic value of achieving this target.

METHODS

An agent-based model developed in 2023 represents each person aged 6-17 years in the U.S. On each simulated day, agents can participate in sports that affect their metabolic and mental health in the model. Each agent can develop different physical and mental health outcomes, associated with direct and indirect costs.

RESULTS

Increasing the proportion of youth participating in sports from the most recent participation levels (50.7%) to the Healthy People 2030 target (63.3%) could reduce overweight/obesity prevalence by 3.37% (95% CI=3.35%, 3.39%), resulting in 1.71 million fewer cases of overweight/obesity (95% CI=1.64, 1.77 million). This could avert 352,000 (95% CI=336,200, 367,500) cases of weight-related diseases and gain 1.86 million (95% CI=1.86, 1.87 million) quality-adjusted life years, saving $22.55 billion (95% CI=$22.46, $22.63 billion) in direct medical costs and $25.43 billion (95% CI= $25.25, $25.61 billion) in productivity losses. This would also reduce depression/anxiety symptoms, saving $3.61 billion (95% CI=$3.58, $3.63 billion) in direct medical costs and $28.38 billion (95% CI=$28.20, $28.56 billion) in productivity losses.

CONCLUSIONS

This study shows that achieving the Healthy People 2030 objective could save third-party payers, businesses, and society billions of dollars for each cohort of persons aged 6-17 years, savings that would continue to repeat with each new cohort. This suggests that even if a substantial amount is invested toward this objective, such investments could pay for themselves.

Systems mapping of multilevel factors contributing to dental caries in adolescents

Dental caries is a prevalent chronic disease among adolescents. Caries activity increases significantly during adolescence due to an increase in susceptible tooth surfaces, immature permanent tooth enamel, independence in pursuing self-care, and a tendency toward poor diet and oral hygiene. Dental caries in permanent teeth is more prevalent among adolescents in low-income families and racial/ethnic minority groups, and these disparities in adolescent dental caries experience have persisted for decades. Several conceptual and data-driven models have proposed unidirectional mechanisms that contribute to the extant disparities in adolescent dental caries experience. Our objective, using a literature review, is to provide an overview of risk factors contributing to adolescent dental caries. Specifically, we map the interactive relationships of multilevel factors that influence dental caries among adolescents. Such interactive multilevel relationships more closely reflect the complex nature of dental caries experience among the adolescent population. The methods that we use are two-fold: (1) a literature review using PubMed and Cochrane databases to find contributing factors; and (2) the system dynamics approach for mapping feedback mechanisms underlying adolescent dental caries through causal loop diagramming. The results of this study, based on the review of 138 articles, identified individual, family and community-level factors and their interactions contributing to dental caries experience in adolescents. Our results also provide hypotheses about the mechanisms underlying persistence of dental caries among adolescents.

Conclusions

Our findings may contribute to a deeper understanding of the multilevel and interconnected factors that shape the persistence of dental caries experience among adolescents.

Equitable Policies Need Equitable Practices: Alcohol- and Substance-Exposed Pregnancy as a Case Study

There is clear need for more effective public health policies. Coupled with calls for more effective policies, increasing demand to address public health disparities experienced by systemically marginalized and historically oppressed groups emphasizes the long-standing need for policies that improve public health equity. Such need is highlighted when examining public health issues such as alcohol- and substance-exposed pregnancy (ASEP): Current policies are ineffective at reducing ASEP, and marginalized groups experience disproportionately lower benefits and higher negative consequences as a result of such policies. Powerful strategies to develop more effective policies that can account for the complexity of such issues, such as systems science methods (SSMs), are becoming popular. However, current best practices for such methods often do not emphasize the additional efforts that will be required to develop equitable, not just effective policies. Using ASEP as an example of a crucial complex issue requiring new policy, we suggest additional steps to include in SSM projects for developing more effective policies that will also help stakeholders determine high-equity policies to reduce health disparities. These steps include modeling structural differences experienced by marginalized groups via systemic racism and oppression, incorporating existing cultural and community sources of strength and resilience as key areas for policy development, and evaluating the sustainability of policies as a dimension of efficacy. We also discuss using community-based participatory approaches as a framework for all SSM processes to ensure that policy development itself is grounded in equitable shared decision-making for marginalized individuals.

One Health Lens for Antimicrobial Resistance Research and Funding: A Systematic Review

One Health (OH) offers conceptual and applied prospects to advance planetary health and integrative biology in the 21st century. For example, The World Health Organization (WHO) has declared antimicrobial resistance (AMR) one of humanity's top 10 health threats worldwide (AMR). The AMR research, as seen through the OH lens, recognizes the interdependence and the coproduction of the health of humans, nonhuman animals, and the environment (the OH triad). Moreover, research and development (R&D) is required to generate potential solutions to prevent, diagnose, and treat infections and control the spread and emergence of AMR. However, it is still unclear how well the OH approach is integrated into current AMR R&D. In this study, we present a systematic review on the OH funding landscape for cross-sectoral AMR R&D, and its alignment/gaps with the current global strategic agenda on AMR. A systematic literature review was conducted using public databases covering the period between January 2015 and May 2022. We included the studies and reviews on AMR encompassing more than one sector of the OH triad. Out of the 777 included studies, 475 (61%) encompassed the three OH sectors. A key finding of the present systematic review is that the environment was the most neglected sector in the OH triad. AMR surveillance, transmission, and interventions are the most commonly studied priority topics. In addition, both cross-sectoral AMR literature and investments have been increasing since 2017. The operational aspect of AMR is the most researched and funded area. However, certain priority topics in the strategic research and innovation agenda of the Joint Programming Initiative on AMR are underrepresented in OH AMR research, such as diagnosis and therapeutics. To the best of authors' knowledge, this is the first study that systematically reviews the cross-sectoral literature on AMR, classifies it, and aligns and contextualizes it in regard to the funding landscape of AMR. This systematic review identifies neglected areas in AMR R&D and could serve as critical information for policymaking so as to realize the objectives of the Global Action Plan on AMR. Going forward, more cross-sectoral AMR research and funding are needed. As integrative biology and omics systems science are poised to benefit from a rapprochement with the OH lens, the present article highlights the AMR research and funding landscapes.

From parts to whole: Embracing systems science in community psychology

With our field's strong focus on context for understanding and acting on social problems, community psychologists have frequently elevated the importance of employing systems thinking and methods that help us to understand systems more effectively. As a result, community psychologists have adopted some methods from the interdisciplinary field of systems science. In this virtual special issue, we will compare how several of these approaches have been used in publications in the AJCP in the last 50 years. We identify differences in their popularity, implementation with communities, and how they create generative discussion in the field. We conclude by looking to the future to explore ways community psychology can deepen engagement with methods from systems science.

Feminism Is for Everyone: Scientists, Too

Critically informed engagement in politics and the knowledge of social theory help democratize knowledge production, and redress power asymmetries in science and society. A feminist lens is one of the many ways in which power asymmetries in science can be critically unpacked and interrupted. There are many strands of feminism and feminist theory that differ in their approaches to resist patriarchy and injustices in science and society. As an example, I adopt here the definition of feminism of the late cultural critic bell hooks because her works underscore that feminism is an intersectional liberatory methodology for everyone to resist multiple forms of oppression simultaneously. Queer theory is a strand of social theory that came to prominence since the 1990s in particular. Queer feminism continues to shape feminist writing on science cultures and the knowledge-based innovations contemporary science strives to accomplish. Systems science brings about systems thinking, and that includes rethinking science as culture beyond a narrow realm of technology, and being cognizant of the broader social, feminist, queer, and political contexts of science around the world.

Methods to madness: The utility of complex systems science in a mad, mad world

Existing methods in social [oral] epidemiology primarily utilize statistical models that assume static characteristics of individuals and environments. While useful, an over reliance on these methods in the social and behavioural sciences can unnecessarily limit perspective and progress as even the most advanced statistical methods cannot capture complex behaviour over time given that systems evolve, environments respond, and behaviours and beliefs crystalize or deteriorate based on a variety of social, environmental and access variables. The recent consensus statement on Future Directions for the Behavioral and Social Sciences in Oral Health acknowledges that dental, oral and craniofacial health emerge from the complex interplay of multiple factors at multiple levels over time and highlights the need for the incorporation of new and underutilized methodologies. Complex Systems Science offers a suite of tools and methodologies that are responsive to the generative mechanisms and processes that underlie population distributions of oral health and disease. Specifically, they assume intricate, dynamic interactions between individuals and groups, they facilitate the study and synthesis of interconnections between people (e.g. patients, healthcare providers and policy makers), how these change over time, any differences across settings, and provide an opportunity to guide future longitudinal data collection and intervention science more effectively. This paper aims to provide an introduction to foundational principles of complex systems, complex systems thinking, and methods found in complex systems science, including social network analysis, system dynamics models and agent-based models, and offers perspectives on the challenges faced and opportunities afforded in the incorporation of these methods into the population oral health sciences.

How Can We Advance Integrative Biology Research in Animal Science in 21st Century? Experience at University of Ljubljana from 2002 to 2022

In this perspective analysis, we strive to answer the following question: how can we advance integrative biology research in the 21st century with lessons from animal science? At the University of Ljubljana, Biotechnical Faculty, Department of Animal Science, we share here our three lessons learned in the two decades from 2002 to 2022 that we believe could inform integrative biology, systems science, and animal science scholarship in other countries and geographies. Cultivating multiomics knowledge through a conceptual lens of integrative biology is crucial for life sciences research that can stand the test of diverse biological, clinical, and ecological contexts. Moreover, in an era of the current COVID-19 pandemic, animal nutrition and animal science, and the study of their interactions with human health (and vice versa) through integrative biology approaches hold enormous prospects and significance for systems medicine and ecosystem health.

Digital Citizenship: Beyond Big Data, Technical Skills, Industry 4.0, and COVID-19

Big data and data deluge are topics that are well known in the field of systems science. Digital transformation of big data and omics fields is also underway at present. These changes are impacting life sciences broadly, and high-throughput omics inquiries specifically. On the other hand, digital transformation also calls for rethinking citizenship and moving toward critically informed digital citizenship. Past approaches to digital citizenship have tended to frame the digital health issues narrowly, around technocracy, digital literacy, and technical competence in deployment and use of digital technologies. However, digital citizenship also calls for questioning the means and ends of digital transformation, the frames in which knowledge is produced in the current era. In this context, Industry 4.0 has been one of the innovation frameworks for automation through big data, and embedded sensors connected by wireless communication. Industry 4.0 and the attendant "smart" technologies relate to various automation approaches deployed as part of the public health responses to the COVID-19 pandemic as well. This article argues that there is a growing need to steer digital transformation toward critically informed digital citizenship, so that the provenance of digital data and knowledge is held to account from scientific design to implementation science, whether they concern academic or Industry 4.0 paradigms of innovation. There are enormous potentials and expectations from digital transformation in an era of COVID-19 and digital health. For this potential to materialize in ways that are efficient, democratic, and socially just, critical digital citizenship offers new ways forward. Systems science scholarship stands to benefit from a broadening of the focus on high-throughput omics technologies to a realm of critical digital citizenship, so the digital health innovations are well situated in their societal and political contexts.

Conducting Physical Activity Research on Racially and Ethnically Diverse Adolescents Using Social Network Analysis: Case Studies for Practical Use

Adolescent physical activity (PA) is significantly impacted by peer behaviors through peer influence, peer selection, and popularity. However, the scales for these social constructs may not fully capture the detailed social networks and mechanisms responsible for PA behavior changes. This level of detail and granularity can be quantified and analyzed through social network analysis (SNA). To demonstrate the variety, utility, and efficacy of SNA in adolescent PA research, this article aims to provide four case studies on the collection of social network and PA data on ethnically and racially diverse adolescents. Through case studies, this article provides tangible ways in which SNA can be used to evaluate social influences on PA behaviors. Case studies are presented on: (1) Youth Engagement in Sport-an egocentric analysis of middle school youth participation in an experiential sport program with 3- and 6-month follow-ups; (2) Summer care program networks-an egocentric and whole network longitudinal study of adolescents at summer care programs; (3) The Convoy method-a qualitative egocentric discussion activity with adolescents from colonias on the Texas-Mexico border; and (4) A father-focused, family-centered health program-an egocentric experimental analysis of children participating in a health program. Data collection procedures are listed and example surveys are provided. Descriptive analyses are included, as are recommendations on further analysis techniques for each type of network data. Using SNA, researchers can understand social contexts in a more specific manner, better positioning interventions to alter such influences.

Four-Year Accelerometry Outcomes from a Cluster Randomized Whole of Systems Trial of Prevention Strategies for Childhood Obesity

Background: We investigated the effect of the Whole of Systems Trial of Prevention Strategies for Childhood Obesity (WHO STOPS) intervention on children's objectively measured physical activity and sedentary time (ST). Methods: We conducted a cluster randomized controlled trial with children in grades 4 (∼9-10 years old) and grade 6 (∼11-12 years old) from 10 communities in the Great South Coast region of Victoria, Australia. Communities were randomly allocated (1:1) to receive the WHO STOPS intervention in 2015. WHO STOPS was a whole of community systems-based approach to preventing childhood obesity. Outcome data were collected using a repeat cross-sectional design in 2015, 2017, and 2019. Children were asked to wear a hip-mounted accelerometer for 7 days. Age-specific Axis 1 activity counts were converted into duration (minutes/day) spent engaged in moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), and ST. Linear mixed regression models were fitted to estimate the effects of the intervention on the three activity outcomes across the study period. Results: Analyses were based on valid accelerometer data from 1406 children (intervention n = 745; control n = 661). Results for MVPA, LPA, and ST were nonsignificant. Between 2015 and 2017, there were positive, but nonsignificant, changes in mean MVPA favoring intervention boys [3.7 minutes/day; 95% confidence interval (CI): -5.7 to 13.1] and girls (5.5 minutes/day; 95% CI: -1.5 to 12.6). By 2019, these effects had attenuated. Conclusions: Although the WHO STOPS intervention did not significantly change activity levels, the magnitudes of the effects on MVPA suggest that further research with whole-of-community interventions in larger samples would be worthwhile. Clinical trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR.org.au) identifier 12616000980437.

Understanding the Influence of Community-Level Determinants on Children's Social and Emotional Well-Being: A Systems Science and Participatory Approach

Healthy social and emotional development and longer-term outcomes for children are shaped by factors across the multiple levels (micro, meso, exo, macro) of a child’s environment. By employing a novel systems science and participatory approach, we were able to co-produce a series of causal loop diagrams that detail the complex relationships between variables operating at the community or neighborhood environment level (e.g., features of the built environment such as: housing type, access, availability, and location; parks and greenspace, facilities such as community services, and other service infrastructure such as transit), and highlight the individual and collective impacts these relationships can have on the subsystem surrounding a child’s social and emotional well-being. Our approach provides a unique lens of knowledge through which communities can identify key leverage points for action and (re)design of community spaces, practices, and policy.

Exploring the Impact of Policies to Improve Geographic and Economic Access to Vegetables among Low-Income, Predominantly Latino Urban Residents: An Agent-Based Model

Modifying the food environment of cities is a promising strategy for improving dietary behaviors, but using traditional empirical methods to test the effectiveness of these strategies remains challenging. We developed an agent-based model to simulate the food environment of Austin, Texas, USA, and to test the impact of different food access policies on vegetable consumption among low-income, predominantly Latino residents. The model was developed and calibrated using empirical data from the FRESH-Austin Study, a natural experiment. We simulated five policy scenarios: (1) business as usual; (2)−(4) expanding geographic and/or economic healthy food access via the Fresh for Less program (i.e., through farm stands, mobile markets, and healthy corner stores); and (5) expanding economic access to vegetables in supermarkets and small grocers. The model predicted that increasing geographic and/or economic access to healthy corner stores will not meaningfully improve vegetable intake, whilst implementing high discounts (>85%) on the cost of vegetables, or jointly increasing geographic and economic access to mobile markets or farm stands, will increase vegetable intake among low-income groups. Implementing discounts at supermarkets and small grocers is also predicted to be an effective policy for increasing vegetable consumption. This work highlights the utility of agent-based modeling for informing food access policies.

Association of Physician Referrals with Timely Cancer Care Using Tumor Registry and Claims Data

More Americans are being screened for and more are surviving colorectal cancer due to advanced treatments and better quality of care; however, these benefits are not equitably distributed among diverse or older populations. Differential care delivery outcomes are driven by multiple factors, including access to timely treatment that comes from high-quality care coordination. Providers help ensure such coordinated care, which includes timely referrals to specialists. Variation in referrals between providers can also result in differences in treatment plans and outcomes. Patients who are more often referred between the same diagnosing and treating providers may benefit from more timely care compared to those who are not. Our objective is to examine patterns of referral, or patient-sharing networks (PSNs), and our outcome, treatment delay of 30-days (yes/no). We hypothesize that if a patient is in a PSN they will have lower odds of a 30-day treatment initiation delay. Our observational population-based analysis using the National Cancer Institute (NCI)-linked tumor registry and Medicare claims database includes records for 27,689 patients diagnosed with colorectal cancer from 2001 to 2013, and treated with either chemotherapy, radiotherapy, or surgery. We modeled the adjusted odds of a delay and found 17.04% of patients experienced a 30-day delay in initial treatment. Factors that increased odds of a delay were lack of membership in a PSN (adjusted odds ratio [AOR]: 2.20; 95% confidence interval [CI]: 1.71-2.84), racial/ethnic minority status, and having multiple comorbidities. Provider characteristics significantly associated with greater odds of a delay were if dyads were not in the same facility (AOR: 1.95; 95% CI: 1.81-2.10), if providers were different genders, most notably male (diagnosing) and female (treating) [AOR: 1.23; 95% CI: 1.08-1.40, p = 0.0015]. PSNs appear to be associated with reduced of a care delay. The associations observed in our study address the demand for developing multilevel interventions to improve the delivery and coordination of high-quality of care for older cancer patients.

Perspective: A Framework for Addressing Dynamic Food Consumption Processes

The study of food consumption, diet, and related concepts is motivated by diverse goals, including understanding why food consumption impacts our health, and why we eat the foods we do. These varied motivations can make it challenging to define and measure consumption, as it can be specified across nearly infinite dimensions-from micronutrients to carbon footprint to food preparation. This challenge is amplified by the dynamic nature of food consumption processes, with the underlying phenomena of interest often based on the nature of repeated interactions with food occurring over time. This complexity underscores a need to not only improve how we measure food consumption but is also a call to support theoreticians in better specifying what, how, and why food consumption occurs as part of processes, as a prerequisite step to rigorous measurement. The purpose of this Perspective article is to offer a framework, the consumption process framework, as a tool that researchers in a theoretician role can use to support these more robust definitions of consumption processes. In doing so, the framework invites theoreticians to be a bridge between practitioners who wish to measure various aspects of food consumption and methodologists who can develop measurement protocols and technologies that can support measurement when consumption processes are clearly defined. In the paper we justify the need for such a framework, introduce the consumption process framework, illustrate the framework via a use case, and discuss existing technologies that enable the use of this framework and, by extension, more rigorous study of consumption. This consumption process framework demonstrates how theoreticians could fundamentally shift how food consumption is defined and measured towards more rigorous study of what, how, and why food is eaten as part of dynamic processes and a deeper understanding of linkages between behavior, food, and health.

Top Trends in Multiomics Research: Evaluation of 52 Published Studies and New Ways of Thinking Terminology and Visual Displays

Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, Arabidopsis thaliana, Saccharomyces cerevisiae, and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.

Physical Activity Promotion and the United Nations Sustainable Development Goals: Building Synergies to Maximize Impact

BACKGROUND

Many of the known solutions to the physical inactivity pandemic operate across sectors relevant to the United Nations Sustainable Development Goals (SDGs).

METHODS

The authors examined the contribution of physical activity promotion strategies toward achieving the SDGs through a conceptual linkage exercise, a scoping review, and an agent-based model.

RESULTS

Possible benefits of physical activity promotion were identified for 15 of the 17 SDGs, with more robust evidence supporting benefits for SDGs 3 (good health and well-being), 9 (industry, innovation, and infrastructure), 11 (sustainable cities and communities), 13 (climate action), and 16 (peace, justice, and strong institutions). Current evidence supports prioritizing at-scale physical activity-promoting transport and urban design strategies and community-based programs. Expected physical activity gains are greater for low-and middle-income countries. In high-income countries with high car dependency, physical activity promotion strategies may help reduce air pollution and traffic-related deaths, but shifts toward more active forms of travel and recreation, and climate change mitigation, may require complementary policies that disincentivize driving.

CONCLUSIONS

The authors call for a synergistic approach to physical activity promotion and SDG achievement, involving multiple sectors beyond health around their goals and values, using physical activity promotion as a lever for a healthier planet.

A science of collaborative learning health systems

INTRODUCTION

Improving the U.S. healthcare system and health outcomes is one of the most pressing public health challenges of our time. Previously described Collaborative Learning Health Systems (CLHSs) are a promising approach to outcomes improvement. In order to fully realize this promise, a deeper understanding of this phenomenon is necessary.

METHODS

We drew on our experience over the past decade with CLHSs as well as qualitative literature review to answer three questions: What kind of phenomena are CLHSs? and what is an appropriate scientific approach? How might we frame CLHSs conceptually? What are potential mechanisms of action?

RESULTS

CLHSs are complex adaptive systems in which all stakeholders are able to collaborate, at scale, to create and share resources to satisfy a variety of needs. This is accomplished by providing infrastructure and services that enable stakeholders to act on their inherent motivations. This framing has implications for both research and practice.

CONCLUSION

Articulating this framework and potential mechanisms of action should facilitate research to test and refine hypotheses as well as guide practice to develop and optimize this promising approach to improving healthcare systems.

An action-oriented framework for systems-based solutions aimed at childhood obesity prevention in US Latinx and Latin American populations

Childhood obesity in US Latinx and Latin American populations is a persistent, complex public health issue and, as such, requires solutions grounded on systems science theory and methods. In this paper, we introduce an action-oriented framework to design, implement, evaluate, and sustain whole-of-community systems changes for childhood obesity prevention in US Latinx and Latin American populations. Our framework covers six action steps: (1) foster multisectoral team; (2) map the system, its context, and drivers; (3) envision system-wide changes; (4) effect system-wide changes; (5) monitor, learn, and adapt; and (6) scale and sustain. We also propose 10 principles that put human and environmental rights and systems thinking at the center of these systems-based solutions. For each action step, we provide a list of concrete activities, methods, approaches, and examples that can be used to guide and inform the work needed to achieve the expected outputs. Finally, we discuss how a wider adoption of systems science for childhood obesity prevention among US Latinx and Latin American populations can be encouraged and sustained.

MS2Compound: A User-Friendly Compound Identification Tool for LC-MS/MS-Based Metabolomics Data

Metabolomics is a leading frontier of systems science and biomedical innovation. However, metabolite identification in mass spectrometry (MS)-based global metabolomics investigations remains a formidable challenge. Moreover, lack of comprehensive spectral databases hinders accurate identification of compounds in global MS-based metabolomics. Creating experiment-derived metabolite spectral libraries tailored to each experiment is labor-intensive. Therefore, predicted spectral libraries could serve as a better alternative. User-friendly tools are much needed, as the currently available metabolomic analysis tools do not offer adequate provision for users to create or choose context-specific databases. Here, we introduce the MS2Compound, a metabolite identification tool, which can be used to generate a custom database of predicted spectra using the Competitive Fragmentation Modeling-ID (CFM-ID) algorithm, and identify metabolites or compounds from the generated database. The database generator can create databases of the model/context/species used in the metabolomics study. The MS2Compound is also powered with mS-score, a scoring function for matching raw fragment spectra to a predicted spectra database. We demonstrated that mS-score is robust in par with dot product and hypergeometric score in identifying metabolites using benchmarking datasets. We evaluated and highlight here the unique features of the MS2Compound by a re-analysis of a publicly available metabolomic dataset (MassIVE id: MSV000086784) for a complex traditional drug formulation called Triphala. In conclusion, we believe that the omics systems science and biomedical research and innovation community in the field of metabolomics will find the MS2Compound as a user-friendly analysis tool of choice to accelerate future metabolomic analyses.

The Action Scales Model: A conceptual tool to identify key points for action within complex adaptive systems

BACKGROUND

Systems thinking is integral to working effectively within complex systems, such as those which drive the current population levels of overweight and obesity. It is increasingly recognised that a systems approach - which corrals public, private, voluntary and community sector organisations to make their actions and efforts coherent - is necessary to address the complex drivers of obesity. Identifying, implementing and evaluating actions within complex adaptive systems is challenging, and may differ from previous approaches used in public health.

METHODS

Within this conceptual article, we present the Action Scales Model (ASM). The ASM is a simple tool to help policymakers, practitioners and evaluators to conceptualise, identify and appraise actions within complex adaptive systems. We developed this model using our collective expertise and experience in working with local government authority stakeholders on the Public Health England Whole Systems Obesity programme. It aligns with, and expands upon, previous models such as the Intervention Level Framework, the Iceberg Model and Donella Meadows' 12 places to intervene within a system.

RESULTS

The ASM describes four levels (synonymous with leverage points) to intervene within a system, with deeper levels providing greater potential for changing how the system functions. Levels include events, structures, goals and beliefs. We also present how the ASM can be used to support practice and policy, and finish by highlighting its utility as an evaluative aid.

DISCUSSION

This practical tool was designed to support those working at the front line of systems change efforts, and while we use the population prevalence of obesity as an outcome of a complex adaptive system, the ASM and the associated principles can be applied to other issues. We hope that the ASM encourages people to think differently about the systems that they work within and to identify new and potentially more impactful opportunities to leverage change.

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.

COVID-19 and Preparing Planetary Health for Future Ecological Crises: Hopes from Glycomics for Vaccine Innovation

A key lesson emerging from COVID-19 is that pandemic proofing planetary health against future ecological crises calls for systems science and preventive medicine innovations. With greater proximity of the human and animal natural habitats in the 21st century, it is also noteworthy that zoonotic infections such as COVID-19 that jump from animals to humans are increasingly plausible in the coming decades. In this context, glycomics technologies and the third alphabet of life, the sugar code, offer veritable prospects to move omics systems science from discovery to diverse applications of relevance to global public health and preventive medicine. In this expert review, we discuss the science of glycomics, its importance in vaccine development, and the recent progress toward discoveries on the sugar code that can help prevent future infectious outbreaks that are looming on the horizon in the 21st century. Glycomics offers veritable prospects to boost planetary health, not to mention the global scientific capacity for vaccine innovation against novel and existing infectious agents.

Applications of Systems Science to Understand and Manage Multiple Influences within Children's Environmental Health in Least Developed Countries: A Causal Loop Diagram Approach

Least developed countries (LDCs) are home to over a billion people throughout Africa, Asia-Pacific, and the Caribbean. The people who live in LDCs represent just 13% of the global population but 40% of its growth rate. Characterised by low incomes and low education levels, high proportions of the population practising subsistence living, inadequate infrastructure, and lack of economic diversity and resilience, LDCs face serious health, environmental, social, and economic challenges. Many communities in LDCs have very limited access to adequate sanitation, safe water, and clean cooking fuel. LDCs are environmentally vulnerable; facing depletion of natural resources, the effects of unsustainable urbanization, and the impacts of climate change, leaving them unable to safeguard their children’s lifetime health and wellbeing. This paper reviews and describes the complexity of the causal relationships between children’s health and its environmental, social, and economic influences in LDCs using a causal loop diagram (CLD). The results identify some critical feedbacks between poverty, family size, population growth, children’s and adults’ health, inadequate water, sanitation and hygiene (WASH), air pollution, and education levels in LDCs and suggest leverage points for potential interventions. A CLD can also be a starting point for quantitative systems science approaches in the field, which can predict and compare the effects of interventions.

Implementation methodology from a social systems informatics and engineering perspective applied to a parenting training program

OBJECTIVE

For implementation of an evidence-based program to be effective, efficient, and equitable across diverse populations, we propose that researchers adopt a systems approach that is often absent in efficacy studies. To this end, we describe how a computer-based monitoring system can support the delivery of the New Beginnings Program (NBP), a parent-focused evidence-based prevention program for divorcing parents.

METHOD

We present NBP from a novel systems approach that incorporates social system informatics and engineering, both necessary when utilizing feedback loops, ubiquitous in implementation research and practice. Examples of two methodological challenges are presented: how to monitor implementation, and how to provide feedback by evaluating system-level changes due to implementation.

RESULTS

We introduce and relate systems concepts to these two methodologic issues that are at the center of implementation methods. We explore how these system-level feedback loops address effectiveness, efficiency, and equity principles. These key principles are provided for designing an automated, low-burden, low-intrusive measurement system to aid fidelity monitoring and feedback that can be used in practice.

DISCUSSION

As the COVID-19 pandemic now demands fewer face-to-face delivery systems, their replacement with more virtual systems for parent training interventions requires constructing new implementation measurement systems based on social system informatics approaches. These approaches include the automatic monitoring of quality and fidelity in parent training interventions. Finally, we present parallels of producing generalizable and local knowledge bridging systems science and engineering method. This comparison improves our understanding of system-level changes, facilitates a program's implementation, and produces knowledge for the field. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Leveraging Systems Science to Promote the Implementation and Sustainability of Mental Health and Psychosocial Interventions in Low- and Middle-Income Countries

Advancements in global mental health implementation research have revealed promising strategies for improving access to evidence-based mental health care. These advancements have not translated, however, into a reduced prevalence of mental disorders. In this review we examine the relationships between determinants (i.e., barriers and facilitators) and outcomes of mental health services in low- and middle-income countries to identify opportunities for improving the population-level impact and sustainability of innovations in global mental health. We identified three key implementation and services outcomes that influenced the prevalence of mental disorders in the 56 included review articles: supply (access, implementation), demand (help seeking, utilization), and quality (effectiveness, quality of care) of mental health services. Determinants of these outcomes revealed seven themes: community stakeholder engagement; cultural relevance; stigma; human resource capacity; organization of services; governance, policy, and financing; and sociopolitical and community context. We developed a causal loop diagram to illustrate the relationships among these determinants and outcomes. The causal loop diagram revealed the central role of community stakeholder engagement in bridging implementation and patient outcomes, the importance of addressing stigma and social determinants of mental health, and the need to complement supply-side implementation strategies with approaches to equilibrate demand and improve the quality of services. Applying systems science methodologies to global mental health research presents an opportunity to examine the complex relationships among community and health system factors that influence implementation of evidence-based interventions in order to identify sustainable approaches to improve the population-level impact of mental health services in low- and middle-income countries.

Using Digital Technologies to Facilitate Care Coordination Between Youth Mental Health Services: A Guide for Implementation

Enhanced care coordination is essential to improving access to and navigation between youth mental health services. By facilitating better communication and coordination within and between youth mental health services, the goal is to guide young people quickly to the level of care they need and reduce instances of those receiving inappropriate care (too much or too little), or no care at all. Yet, it is often unclear how this goal can be achieved in a scalable way in local regions. We recommend using technology-enabled care coordination to facilitate streamlined transitions for young people across primary, secondary, more specialised or hospital-based care. First, we describe how technology-enabled care coordination could be achieved through two fundamental shifts in current service provisions; a model of care which puts the person at the centre of their care; and a technology infrastructure that facilitates this model. Second, we detail how dynamic simulation modelling can be used to rapidly test the operational features of implementation and the likely impacts of technology-enabled care coordination in a local service environment. Combined with traditional implementation research, dynamic simulation modelling can facilitate the transformation of real-world services. This work demonstrates the benefits of creating a smart health service infrastructure with embedded dynamic simulation modelling to improve operational efficiency and clinical outcomes through participatory and data driven health service planning.

Trends in Energy Imbalance Gap and Body Weight Status in the Japanese Adult Population: A System Dynamics Approach

Background

The double burden of malnutrition is a growing public health problem in Japan. We estimated the dynamics of the energy imbalance gap (EIG) (average daily difference between energy intake and expenditure) to explain trends in the prevalence of underweight, overweight, and obese Japanese adults.

Methods

We used individual-level data on body height and weight from the National Health and Nutrition Surveys from 1975 to 2015. We calibrated a validated system dynamics model to estimate the EIG for Japanese adults aged 20 to 74 years by survey year, sex, and weight status classified by the body mass index (BMI).

Results

The overall EIG for men increased from 2.3 kcal/day in 1975 to 4.7 kcal/day in 1987 and then decreased to 2.3 kcal/day in 2015. The overall EIG for women consistently decreased from 4.3 kcal/day in 1975 to −0.5 kcal/day in 2015. By BMI class, the EIG for men with a BMI of <30 kg/m² began to decrease around 1990, indicating a deceleration in the prevalence of overweight and obese men. The EIG consistently decreased for women with a BMI of <25 kg/m² and reached negative values from the late 2000s to early 2010s, indicating a gradual decrease in the prevalence of overweight and obese women.

Conclusions

The dynamics of the EIG were different across sex and weight groups. Public health interventions should target a further decrease in the EIG for normal-weight, overweight, and obese men and a stop in the decreasing trends of the EIG in underweight and normal-weight women.

Using Collective Intelligence to identify barriers to implementing and sustaining effective Fundamental Movement Skill interventions: A rationale and application example

To have population-level impact, interventions must be effectively implemented and sustained under real-world conditions. Few Fundamental Movement Skill (FMS) interventions are implemented at scale, and even fewer are sustained in a way that allows for ongoing evaluation. There has been increasing recognition of applying systems thinking to investigate the multitude of influences on interventions. To improve research-practice translations, investigations need to incorporate synthesised perspective and collective input from intervention stakeholders. This study trials Collective Intelligence (CI) - an applied systems science approach - to understand barriers to the adoption, implementation and institutionalisation of effective FMS interventions for children and adolescents. A total of 58 barriers were generated and organised into 13 barrier categories. Participants voted to select 10 critical barriers and generated a structural map among the barriers to guide future action mapping. Barriers related to Government and Institutional factors and Curricular Conflicts were structured as fundamental drivers of the system of barriers. By presenting this application example, we aim to underline the considerations and alleviate barriers to conducting much needed implementation and sustainability studies in FMS interventions. CI also adds to the "tool box" to understand the complexity and functioning of public health interventions, such as those targeting physical activity behaviours.

Stakeholder Experiences With Gender Identity Data Capture in Electronic Health Records: Implementation Effectiveness and a Visibility Paradox

BACKGROUND

Advocates have endorsed transgender visibility via gender identity (GI) data capture with the advent of the Affordable Care Act and electronic health record (EHR) requirements. Visibility in data in order to enumerate a population contrasts with ways in which other LGBT and public health scholars have deployed these concepts.

AIMS

The article aims to assess the effectiveness of GI data capture in EHRs and implications for trans health care quality improvements and research.

METHOD

Semistructured interviews were conducted with 27 stakeholders from prominent gender-affirming care providers across the United States. A range of informants shared their experiences with GI data capture. Interviews were coded, themes were identified, and the extended case method was used to contextualize data in relation to key concepts.

RESULTS

Data capture is effective for increasing patient counts and making quality improvements but limited in terms of enhancing gender-affirming care depending on provider size, type, and competencies. Many challenges were highlighted regarding use of GI data for research, sharing GI data across systems, as well the ways data capture erases the dynamism of GI. These issues create conditions for limited kinds of disclosure, capture of particular categories, and care and treatment barriers.

DISCUSSION

Stakeholders exposed a visibility paradox emerging from GI data capture. While data fields are created to increase the visibility of trans persons in medical settings and in health research, they work to increase the visibility of some while reducing the visibility of other gender diverse persons, including trans, nonbinary, and cisgender.

CONCLUSION

New approaches are needed to explore implications of GI data standardization and the logics of health care in the face of gender expansiveness.

Context and the evidence-based paradigm: The potential for participatory research and systems thinking in oral health

The implementation of research evidence to promote oral health is critical, given the intransigent and emerging challenges for policymakers at a population level. Despite this, little attention has been paid to implementation research within the evidence-based paradigm. This is important as getting research evidence into clinical practice is not a linear path that consists of simple sequential steps. In this article, we argue that we need to consider a broader range of conceptual and methodological approaches to increase the value of information generated. This should be undertaken either in parallel with empirical and experimental designs, or in some cases, instead of. This is important if we are going to understand the complexity and contextual knowledge of the 'system', within which interventions are implemented. Involving key stakeholders alongside empirical and experimental designs is one helpful approach. Examples of these approaches include Patient and Public Involvement and the development of Core Outcome Sets, where the views of those that will be potentially affected by the research, are included. The use of theoretical frameworks and process evaluations alongside trials are also important, if they are fully integrated into the approach taken to address the research question. A more radical approach is using participatory designs and 'systems thinking'. Participatory approaches include subject matter 'experts by experience'. These include patients, their families, carers, healthcare professionals, services managers, policymakers, commissioners and researchers. Participatory approaches raise important questions about who facilitates the process, when it should happen and how the diverse actors become meaningfully engaged so that their involvement is active, democratic and ongoing. We argue that the issues of control, power and language are central to this and represent a paradigmatic shift to conventional approaches. Systems thinking captures the idea that public health problems commonly involve multiple interdependent and interconnected factors, which interact with each other dynamically. This approach challenges the simplicity of the hierarchy of evidence and linear sequential logic, when it does not account for context. In contrast, systems thinking accepts complexity de novo and emphasizes the need to understand the whole system rather than its individual component parts. We conclude with the idea that participatory and systems thinking help to unpack the diverse agents that are often involved in the generation and translation of evidence into clinical dental practice. It moves our conception of research away from a simple exchange between 'knowledge producers' and 'knowledge users' and raises both methodological and epistemological challenges.

The opioid crisis: need for systems science research

The opioid epidemic in the United States has had a devastating impact on millions of people as well as on their families and communities. The increased prevalence of opioid misuse, use disorder and overdose in recent years has highlighted the need for improved public health approaches for reducing the tremendous harms of this illness. In this paper, we explain and call for the need for more systems science approaches, which can uncover the complexities of the opioid crisis, and help evaluate, analyse and forecast the effectiveness of ongoing and new policy interventions. Similar to how a stream of systems science research helped policy development in infectious diseases and obesity, more systems science research is needed in opioids.

Integrating complex systems science into road safety research and practice, part 1: review of formative concepts

Many of our most persistent public health problems are complex problems. They arise from a web of factors that interact and change over time and may exhibit resistance to intervention efforts. The domain of systems science provides several tools to help injury prevention researchers and practitioners examine deep, complex and persistent problems and identify opportunities to intervene. Using the increase in pedestrian death rates as an example, we provide (1) an accessible overview of how complex systems science approaches can augment established injury prevention frameworks and (2) a straightforward example of how specific systems science tools can deepen understanding, with a goal of ultimately informing action.

Invited Commentary: Making Causal Inference More Social and (Social) Epidemiology More Causal

A society's social structure and the interactions of its members determine when key drivers of health occur, for how long they last, and how they operate. Yet, it has been unclear whether causal inference methods can help us find meaningful interventions on these fundamental social drivers of health. Galea and Hernán propose we place hypothetical interventions on a spectrum and estimate their effects by emulating trials, either through individual-level data analysis or systems science modeling (Am J Epidemiol. 2020;189(3):167-170). In this commentary, by way of example in health disparities research, we probe this "closer engagement of social epidemiology with formal causal inference approaches." The formidable, but not insurmountable, tensions call for causal reasoning and effect estimation in social epidemiology that should always be enveloped by a thorough understanding of how systems and the social exposome shape risk factor and health distributions. We argue that one way toward progress is a true partnership of social epidemiology and causal inference with bilateral feedback aimed at integrating social epidemiologic theory, causal identification and modeling methods, systems thinking, and improved study design and data. To produce consequential work, we must make social epidemiology more causal and causal inference more social.

Integrating Complex Systems Methods to Advance Obesity Prevention Intervention Research

Background. Whole-of-community interventions have been recommended and show promise for preventing obesity; however, research to understand the mechanisms underlying their success or failure is lacking. Complex systems approaches may be useful to address this gap. Purpose. To describe the evolution and utilization of qualitative and quantitative complex systems methods to understand and model whole-of-community obesity prevention interventions. Approach. We illustrate the retrospective qualitative development of a systems map representing community change dynamic within the Shape Up Somerville (SUS) intervention. We then describe how this systems map, and complementary work of other successful obesity prevention interventions (Romp & Chomp intervention), informed the COMPACT (childhood obesity modeling for prevention and community transformation) study. COMPACT's design aligns complex systems science principles and community-engaged research to better understand stakeholders' leadership roles in whole-of-community interventions. We provide an overview of the complex systems tools used in COMPACT: agent-based modeling, group model building, and social network analysis and describe how whole-of-community intervention stakeholders ("agents") use their social networks to diffuse knowledge about and engagement with childhood obesity prevention efforts, laying the groundwork for community readiness for sustainable change. Conclusion. Complex systems approaches appear feasible and useful to study whole-of-community obesity prevention interventions and provide novel insights that expand on those gained from traditional approaches. Use of multiple methods, both qualitative and quantitative, from the complex systems toolkit working together can be important to success.

Using Group Model Building to Describe the System Driving Unhealthy Eating and Identify Intervention Points: A Participatory, Stakeholder Engagement Approach in the Caribbean

Many Small Island Developing States of the Caribbean experience a triple burden of malnutrition with high rates of obesity, undernutrition in children, and iron deficiency anemia in women of reproductive age, driven by an inadequate, unhealthy diet. This study aimed to map the complex dynamic systems driving unhealthy eating and to identify potential points for intervention in three dissimilar countries. Stakeholders from across the food system in Jamaica (n = 16), St. Kitts and Nevis (n = 19), and St. Vincent and the Grenadines (n = 6) engaged with researchers in two group model building (GMB) workshops in 2018. Participants described and mapped the system driving unhealthy eating, identified points of intervention, and created a prioritized list of intervention strategies. Stakeholders were also interviewed before and after the workshops to provide their perspectives on the utility of this approach. Stakeholders described similar underlying systems driving unhealthy eating across the three countries, with a series of dominant feedback loops identified at multiple levels. Participants emphasized the importance of the relative availability and price of unhealthy foods, shifting cultural norms on eating, and aggressive advertising from the food industry as dominant drivers. They saw opportunities for governments to better regulate advertising, disincentivize unhealthy food options, and bolster the local agricultural sector to promote food sovereignty. They also identified the need for better coordinated policy making across multiple sectors at national and regional levels to deliver more integrated approaches to improving nutrition. GMB proved to be an effective tool for engaging a highly diverse group of stakeholders in better collective understanding of a complex problem and potential interventions.

Integrating complex systems science into road safety research and practice, Part 2: applying systems tools to the problem of increasing pedestrian death rates

OBJECTIVES

To provide a specific example of how systems dynamics tools can increase understanding of stakeholder 'mental models' and generate robust systems-based hypotheses about the escalating problem of rising pedestrian death rates in the USA.

METHODS

We designed and facilitated two group model building (GMB) workshops. Participants generated causal loop diagrams (CLDs) individually and in small groups to explore hypotheses concerning time-dynamic interacting factors underlying the increasing rates of pedestrian deaths. Using a grounded theory approach, research team members synthesised the structures and hypotheses into a single CLD.

RESULTS

CLDs from the 41 participants indicated four core factors hypothesised to have a direct impact on pedestrian fatalities: pedestrian-vehicle crashes, vehicle speed at the time of the crash, vehicle size/dimensions and emergency response time. Participants diagrammed how actions and reactions impacted these proximal factors over time and led to ripple effects throughout a larger system to generate an increase in pedestrian deaths. Hypothesised contributing mechanisms fell within the following broad categories: community responses; research, policy and industry influence; potential unintended consequences of responses to pedestrian deaths; and the role of sprawl.

CONCLUSIONS

This application of systems science tools suggested several strategies for advancing injury prevention research and practice. The project generated robust hypotheses and advanced stakeholder communication and depth of understanding and engagement in this key issue. The CLD and GMB process detailed in this study provides a concrete example of how systems tools can be adopted and applied to a transportation safety topic.

The SMART Framework: Integration of Citizen Science, Community-Based Participatory Research, and Systems Science for Population Health Science in the Digital Age

Citizen science enables citizens to actively contribute to all aspects of the research process, from conceptualization and data collection, to knowledge translation and evaluation. Citizen science is gradually emerging as a pertinent approach in population health research. Given that citizen science has intrinsic links with community-based research, where participatory action drives the research agenda, these two approaches could be integrated to address complex population health issues. Community-based participatory research has a strong record of application across multiple disciplines and sectors to address health inequities. Citizen science can use the structure of community-based participatory research to take local approaches of problem solving to a global scale, because citizen science emerged through individual environmental activism that is not limited by geography. This synergy has significant implications for population health research if combined with systems science, which can offer theoretical and methodological strength to citizen science and community-based participatory research. Systems science applies a holistic perspective to understand the complex mechanisms underlying causal relationships within and between systems, as it goes beyond linear relationships by utilizing big data–driven advanced computational models. However, to truly integrate citizen science, community-based participatory research, and systems science, it is time to realize the power of ubiquitous digital tools, such as smartphones, for connecting us all and providing big data. Smartphones have the potential to not only create equity by providing a voice to disenfranchised citizens but smartphone-based apps also have the reach and power to source big data to inform policies. An imminent challenge in legitimizing citizen science is minimizing bias, which can be achieved by standardizing methods and enhancing data quality—a rigorous process that requires researchers to collaborate with citizen scientists utilizing the principles of community-based participatory research action. This study advances SMART, an evidence-based framework that integrates citizen science, community-based participatory research, and systems science through ubiquitous tools by addressing core challenges such as citizen engagement, data management, and internet inequity to legitimize this integration.

Complex System Approaches for Animal Health Surveillance

Many new and highly variable data are currently being produced by the many participants in farmed animal productions systems. These data hold the promise of new information with potential value for animal health surveillance. The current analytical paradigm for dealing with these new data is to implement syndromic surveillance systems, which focus mainly on univariate event detection methods applied to individual time series, with the goal of identifying epidemics in the population. This approach is relatively limited in the scope and not well-suited for extracting much of the additional information that is contained within these data. These approaches have value and should not be abandoned. However, an additional, new analytical paradigm will be needed if surveillance and disease control agencies wish to extract additional information from these data. We propose a more holistic analytical approach borrowed from complex system science that considers animal disease to be a product of the complex interactions between the many individuals, organizations and other factors that are involved in, or influence food production systems. We will discuss the characteristics of farmed animal food production systems that make them complex adaptive systems and propose practical applications of methods borrowed from complex system science to help animal health surveillance practitioners extract additional information from these new data.

Systems Modeling to Advance the Promise of Data Science in Epidemiology

Systems science models use computer-based algorithms to model dynamic interactions between study units within and across levels and are characterized by nonlinear and feedback processes. They are particularly valuable approaches that complement the traditional epidemiologic toolbox in cases in which real data are not available and in cases in which traditional epidemiologic methods are limited by issues such as interference, spatial dependence, and dynamic feedback processes. In this commentary, we propose 2 key contributions that systems models can make to epidemiology: 1) the ability to test assumptions about underlying mechanisms that give rise to population distributions of disease; and 2) help in identifying the types of interventions that have the greatest potential to reduce population rates of disease in the future or in new sites where they have not yet been implemented. We discuss central challenges in the application of systems science approaches in epidemiology, propose potential solutions, and predict future developments in the role that systems science can play in epidemiology.

Service supply chains for population health: Overcoming fragmentation of service delivery ecosystems

INTRODUCTION

Population health involves integration of health, education, and social services to keep a defined population healthy, to address health challenges holistically, and to assist with the realities of being mortal. The fragmentation of the US population health delivery system is addressed. The impacts of this fragmentation on the treatment of substance abuse in the United States are considered. Innovations needed to overcome this fragmentation are proposed.

APPROACH

Treatment capacity issues, including scheduling practices, are discussed. Costs of treatment and lack of treatment are considered. Models of integrated care delivery are reviewed. Potential innovations from systems science, behavioral economics, and social networks are considered. The implications of these innovations are discussed in terms of information technology (IT) systems and governance.

CONCLUSIONS

Enormous savings are possible with more integrated treatment. Based on a range of empirical findings, it is argued that investments of these resources in integrated delivery of care have the potential to dramatically improve health outcomes, thereby significantly reducing the costs of population health.

Grappling With Complex Food Systems to Reduce Obesity: A US Public Health Challenge

Despite 2 decades of effort by the public health community to combat obesity, obesity rates in the United States continue to rise. This lack of progress raises fundamental questions about the adequacy of our current approaches. Although the causes of population-wide obesity are multifactorial, attention to food systems as potential drivers of obesity has been prominent. However, the relationships between broader food systems and obesity are not always well understood. Our efforts to address obesity can be advanced and improved by the use of systems approaches that consider outcomes of the interconnected global food system, including undernutrition, climate change, the environmental sustainability of agriculture, and other social and economic concerns. By implementing innovative local and state programs, taking new approaches to overcome political obstacles to effect policy, and reconceptualizing research needs, we can improve obesity prevention efforts that target the food systems, maximize positive outcomes, and minimize adverse consequences. We recommend strengthening innovative local policies and programs, particularly those that involve community members in identifying problems and potential solutions and that embrace a broad set of goals beyond making eating patterns healthier. We also recommend undertaking interdisciplinary research projects that go beyond testing targeted interventions in specific populations and aim to build an understanding of the broader social, political, and economic context.

Aligning systems science and community-based participatory research: A case example of the Community Health Advocacy and Research Alliance (CHARA)

Partnered research may help bridge the gap between research and practice. Community-based participatory research (CBPR) supports collaboration between scientific researchers and community members that is designed to improve capacity, enhance trust, and address health disparities. Systems science aims to understand the complex ways human-ecological coupled systems interact and apply knowledge to management practices. Although CBPR and systems science display complementary principles, only a few articles describe synergies between these 2 approaches. In this article, we explore opportunities to utilize concepts from systems science to understand the development, evolution, and sustainability of 1 CBPR partnership: The Community Health Advocacy and Research Alliance (CHARA). Systems science tools may help CHARA and other CBPR partnerships sustain their core identities while co-evolving in conjunction with individual members, community priorities, and a changing healthcare landscape. Our goal is to highlight CHARA as a case for applying the complementary approaches of CBPR and systems science to (1) improve academic/community partnership functioning and sustainability, (2) ensure that research addresses the priorities and needs of end users, and (3) support more timely application of scientific discoveries into routine practice.

How new concepts become universal scientific approaches: insights from citation network analysis of agent-based complex systems science

Progress in understanding and managing complex systems comprised of decision-making agents, such as cells, organisms, ecosystems or societies, is-like many scientific endeavours-limited by disciplinary boundaries. These boundaries, however, are moving and can actively be made porous or even disappear. To study this process, I advanced an original bibliometric approach based on network analysis to track and understand the development of the model-based science of agent-based complex systems (ACS). I analysed research citations between the two communities devoted to ACS research, namely agent-based (ABM) and individual-based modelling (IBM). Both terms refer to the same approach, yet the former is preferred in engineering and social sciences, while the latter prevails in natural sciences. This situation provided a unique case study for grasping how a new concept evolves distinctly across scientific domains and how to foster convergence into a universal scientific approach. The present analysis based on novel hetero-citation metrics revealed the historical development of ABM and IBM, confirmed their past disjointedness, and detected their progressive merger. The separation between these synonymous disciplines had silently opposed the free flow of knowledge among ACS practitioners and thereby hindered the transfer of methodological advances and the emergence of general systems theories. A surprisingly small number of key publications sparked the ongoing fusion between ABM and IBM research. Beside reviews raising awareness of broad-spectrum issues, generic protocols for model formulation and boundary-transcending inference strategies were critical means of science integration. Accessible broad-spectrum software similarly contributed to this change. From the modelling viewpoint, the discovery of the unification of ABM and IBM demonstrates that a wide variety of systems substantiate the premise of ACS research that microscale behaviours of agents and system-level dynamics are inseparably bound.

Comparing complex perspectives on obesity drivers: action-driven communities and evidence-oriented experts

INTRODUCTION

The Foresight obesity map represents an expert-developed systems map describing the complex drivers of obesity. Recently, community-led causal loop diagrams have been developed to support community-based obesity prevention interventions. This paper presents a quantitative comparison between the Foresight obesity systems map and a community-developed map of the drivers of obesity.

METHODS

Variables from a community-developed map were coded against the thematic clusters defined in the Foresight map to allow comparison of their sizes and strength of adjoining causal relationships. Central variables were identified using techniques from network analysis. These properties were compared to understand the similarities and differences between the systems as defined by the two groups.

RESULTS

The community map focused on environmental influences, such as built physical activity environment (18% of variables) and social psychology (38%). The Foresight map's largest cluster was physiology (23%), a minimal focus in the community map (2%). Network analysis highlighted media and available time within both maps, but variables related to school and sporting club environments were unique to the community map.

CONCLUSION

Community stakeholders focus on modifiable social and environmental drivers of obesity. Capturing local perspectives is critical when using systems maps to guide community-based obesity prevention.

The Dynamics of Concussion: Mapping Pathophysiology, Persistence, and Recovery With Causal-Loop Diagramming

Despite increasing public awareness and a growing body of literature on the subject of concussion, or mild traumatic brain injury, an urgent need still exists for reliable diagnostic measures, clinical care guidelines, and effective treatments for the condition. Complexity and heterogeneity complicate research efforts and indicate the need for innovative approaches to synthesize current knowledge in order to improve clinical outcomes. Methods from the interdisciplinary field of systems science, including models of complex systems, have been increasingly applied to biomedical applications and show promise for generating insight for traumatic brain injury. The current study uses causal-loop diagramming to visualize relationships between factors influencing the pathophysiology and recovery trajectories of concussive injury, including persistence of symptoms and deficits. The primary output is a series of preliminary systems maps detailing feedback loops, intrinsic dynamics, exogenous drivers, and hubs across several scales, from micro-level cellular processes to social influences. Key system features, such as the role of specific restorative feedback processes and cross-scale connections, are examined and discussed in the context of recovery trajectories. This systems approach integrates research findings across disciplines and allows components to be considered in relation to larger system influences, which enables the identification of research gaps, supports classification efforts, and provides a framework for interdisciplinary collaboration and communication-all strides that would benefit diagnosis, prognosis, and treatment in the clinic.

Adherence to Oral Anticancer Medications: Evolving Interprofessional Roles and Pharmacist Workforce Considerations

Interprofessional care is exhibited in outpatient oncology practices where practitioners from a myriad of specialties (e.g., oncology, nursing, pharmacy, health informatics and others) work collectively with patients to enhance therapeutic outcomes and minimize adverse effects. Historically, most ambulatory-based anticancer medication therapies have been administrated in infusion clinics or physician offices. Oral anticancer medications (OAMs) have become increasingly prevalent and preferred by patients for use in residential or other non-clinic settings. Self-administration of OAMs represents a significant shift in the management of cancer care and role responsibilities for patients and clinicians. While patients have a greater sense of empowerment and convenience when taking OAMs, adherence is a greater challenge than with intravenous therapies. This paper proposes use of a qualitative systems evaluation, based on theoretical frameworks for interdisciplinary team collaboration and systems science, to examine the social interactionism involved with the use of intravenous anticancer treatments and OAMs (as treatment technologies) by describing patient, organizational, and social systems considerations in communication, care, control, and context (i.e., Kaplan’s 4Cs). This conceptualization can help the healthcare system prepare for substantial workforce changes in cancer management, including increased utilization of oncology pharmacists.

Agent-Based Modeling in Public Health: Current Applications and Future Directions

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

Steps Toward an Integrative Clinical Systems Psychology

Clinical fields of the "sciences of the mind" (psychotherapy, psychiatry, etc.) lack integrative conceptual frameworks that have explanatory power. Mainly descriptive-classificatory taxonomies like DSM dominate the field. New taxonomies such as Research Domain Criteria (RDoC) aim to collect scientific knowledge regarding "systems" for "processes" of the brain. These terms have a supradisciplinary" meaning if they are considered in context of Systems Science. This field emerges as a platform of theories like general systems theory, catastrophe theory, synergetics, chaos theory, etc. It provides a lot of abstract concepts, constructs, methods and models. We assume that these tools also enable theoretical integration in the diversified field of clinical practice in the sciences of the mind. Additionally, systems thinking in clinical psychology improves conceptual links to currently network-oriented neurobiology. However, clear definitions of systemic terms are necessary to emerge from their mainly metaphorical use. Here we revise mainly terms like "structure", "process" and "dynamics" as they are used already in psychology, psychoanalysis, psychopathology and psychiatry in an ill-defined way. For instance, affective-cognitive structures like "life space" or "object representations" can be seen as products of mental processing. These structures, in turn, modulate dynamics of mental processes. Additionally, we suggest a coupled network concept of emotions and motivations as the main subsystem that modulates mental dynamics that results in a qualitative systemic model of the mind. Finally, we assume that a revisited systemic approach could improve interdisciplinary understanding of the mental.