System Dynamics Approaches and Collective Action for Community Health: An Integrative Review

Use of systems thinking and adapted group model building methods to understand patterns of technology use among older adults with type 1 diabetes: a preliminary process evaluation

BACKGROUND

A growing number of older adults (ages 65+) live with Type 1 diabetes. Simultaneously, technologies such as continuous glucose monitoring (CGM) have become standard of care. There is thus a need to understand better the complex dynamics that promote use of CGM (and other care innovations) over time in this age group. Our aim was to adapt methods from systems thinking, specifically a participatory approach to system dynamics modeling called group model building (GMB), to model the complex experiences that may underlie different trajectories of CGM use among this population. Herein, we report on the feasibility, strengths, and limitations of this methodology.

METHODS

We conducted a series of GMB workshops and validation interviews to collect data in the form of questionnaires, diagrams, and recordings of group discussion. Data were integrated into a conceptual diagram of the "system" of factors associated with uptake and use of CGM over time. We evaluate the feasibility of each aspect of the study, including the teaching of systems thinking to older adult participants. We collected participant feedback on positive aspects of their experiences and areas for improvement.

RESULTS

We completed nine GMB workshops with older adults and their caregivers (N = 33). Each three-hour in-person workshop comprised: (1) questionnaires; (2) the GMB session, including both didactic components and structured activities; and (3) a brief focus group discussion. Within the GMB session, individual drawing activities proved to be the most challenging for participants, while group activities and discussion of relevant dynamics over time for illustrative (i.e., realistic but not real) patients yielded rich engagement and sufficient information for system diagramming. Study participants liked the opportunity to share experiences with peers, learning and enhancing their knowledge, peer support, age-specific discussions, the workshop pace and structure, and the systems thinking framework. Participants gave mixed feedback on the workshop duration.

CONCLUSIONS

The study demonstrates preliminary feasibility, acceptability, and the value of GMB for engaging older adults about key determinants of complex health behaviors over time. To our knowledge, few studies have extended participatory systems science methods to older adult stakeholders. Future studies may utilize this methodology to inform novel approaches for supporting health across the lifespan.

The common drivers of children and young people's health and wellbeing across 13 local government areas: a systems view

BACKGROUND

System dynamics approaches, including group model building (GMB) and causal loop diagrams (CLDs), can be used to document complex public health problems from a community perspective. This paper aims to apply Social Network Analysis (SNA) methods to combine multiple CLDs created by local communities into a summary CLD, to identify common drivers of the health and wellbeing of children and young people.

METHODS

Thirteen community CLDs regarding children and young people health and wellbeing were merged into one diagram involving three steps: (1) combining variable names; (2) CLD merging, where multiple CLDs were combined into one CLD with a set of unique variables and connections; (3) paring, where the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to generate a cut-point to reduce the number of variables and connections and to rank the overall importance of each variable in the merged CLD.

RESULTS

Combining variable names resulted in 290 variables across the 13 CLDS. A total of 1,042 causal links were identified in the merged CLD. The DEMATEL analysis of the merged CLD identified 23 common variables with a net importance between 1.0 and 4.5 R + C values and 57 causal links. The variables with the highest net importance were 'mental health' and 'social connection & support' classified as high net receivers of influence within the system.

CONCLUSIONS

Combining large CLDs into a simple diagram represents a generalisable model of the drivers of complex health problems.

Community-embedded follow-up management intervention for geriatric primary care: a mixed-methods study of an integrated health services model

BACKGROUND

To propose a community-embedded follow-up management model to provide health services for elderly patients with osteoporosis who live alone.

METHODS

Researchers randomly selected 396 people with osteoporosis living alone from five communities in Nantong, China, for the study. These participants were randomly assigned to control and intervention groups. Twenty-four community physicians in five communities provided professional support based on a community-embedded follow-up management model. Participants completed quantitative questionnaires at baseline and after the 6-month follow-up intervention, and some participants underwent semi-structured face-to-face interviews. The primary outcome is the effectiveness of the community-embedded follow-up management model in improving the quality of life of elderly patients with osteoporosis living alone. Based on an objective quantitative assessment, the qualitative study explains and adds essential components of this community-based follow-up management model.

RESULTS

The quantitative study showed that scores in physical functioning, ability to perform daily activities, self-efficacy, and mental status were significantly improved in the intervention group compared to the control group (p < 0.05). The most significant improvements were found in "mental status" (p = 0.012) and "self-care skills" (p = 0.003). The qualitative study reported the essential elements of a community healthcare model for older people living alone with osteoporosis, including professional support, personalized services, social support, and empowerment.

CONCLUSIONS

Community-embedded follow-up management meets the need for elderly patients with osteoporosis living alone. It helps to improve health perception, promote physical and mental health, and optimize the quality of life in this population. Personalized services and professional support are two major contributing factors to effective embedded follow-up management in the community.

Supporting the 'lived expertise' of older adults with type 1 diabetes: An applied focus group analysis to characterize barriers, facilitators, and strategies for self-management in a growing and understudied population

INTRODUCTION

There is a growing number of older adults (≥65 years) who live with type 1 diabetes. We qualitatively explored experiences and perspectives regarding type 1 diabetes self-management and treatment decisions among older adults, focusing on adopting care advances such as continuous glucose monitoring (CGM).

METHODS

Among a clinic-based sample of older adults ≥65 years with type 1 diabetes, we conducted a series of literature and expert informed focus groups with structured discussion activities. Groups were transcribed followed by inductive coding, theme identification, and inference verification. Medical records and surveys added clinical information.

RESULTS

Twenty nine older adults (age 73.4 ± 4.5 years; 86% CGM users) and four caregivers (age 73.3 ± 2.9 years) participated. Participants were 58% female and 82% non-Hispanic White. Analysis revealed themes related to attitudes, behaviours, and experiences, as well as interpersonal and contextual factors that shape self-management and outcomes. These factors and their interactions drive variability in diabetes outcomes and optimal treatment strategies between individuals as well as within individuals over time (i.e. with ageing). Participants proposed strategies to address these factors: regular, holistic needs assessments to match people with effective self-care approaches and adapt them over the lifespan; longitudinal support (e.g., education, tactical help, sharing and validating experiences); tailored education and skills training; and leveraging of caregivers, family, and peers as resources.

CONCLUSIONS

Our study of what influences self-management decisions and technology adoption among older adults with type 1 diabetes underscores the importance of ongoing assessments to address dynamic age-specific needs, as well as individualized multi-faceted support that integrates peers and caregivers.

How to use machine learning and fuzzy cognitive maps to test hypothetical scenarios in health behavior change interventions: a case study on fruit intake

BACKGROUND

Intervention planners use logic models to design evidence-based health behavior interventions. Logic models that capture the complexity of health behavior necessitate additional computational techniques to inform decisions with respect to the design of interventions.

OBJECTIVE

Using empirical data from a real intervention, the present paper demonstrates how machine learning can be used together with fuzzy cognitive maps to assist in designing health behavior change interventions.

METHODS

A modified Real Coded Genetic algorithm was applied on longitudinal data from a real intervention study. The dataset contained information about 15 determinants of fruit intake among 257 adults in the Netherlands. Fuzzy cognitive maps were used to analyze the effect of two hypothetical intervention scenarios designed by domain experts.

RESULTS

Simulations showed that the specified hypothetical interventions would have small impact on fruit intake. The results are consistent with the empirical evidence used in this paper.

CONCLUSIONS

Machine learning together with fuzzy cognitive maps can assist in building health behavior interventions with complex logic models. The testing of hypothetical scenarios may help interventionists finetune the intervention components thus increasing their potential effectiveness.

Identifying opportunities for collective action around community nutrition programming through participatory systems science

PURPOSE

To apply principles of group model building (GMB), a participatory systems science approach, to identify barriers and opportunities for collective impact around nutrition programming to reduce cancer risk for immigrant communities in an urban environment.

METHODS

We convened four in-person workshops applying GMB with nine community partners to generate causal loop diagrams (CLDs)-a visual representation of hypothesized causal relationships between variables and feedback structures within a system. GMB workshops prompted participants to collaboratively identify programmatic goals and challenges related to (1) community gardening, (2) nutrition education, (3) food assistance programs, and (4) community-supported agriculture. Participants then attended a plenary session to integrate findings from all workshops and identify cross-cutting ideas for collective action.

RESULTS

Several multilevel barriers to nutrition programming emerged: (1) food policies center the diets and practices of White Americans and inhibit culturally tailored food guidelines and funding for culturally appropriate nutrition education; (2) the lack of culturally tailored nutrition education in communities is a missed opportunity for fostering pride in immigrant food culture and sustainment of traditional food practices; and (3) the limited availability of traditional ethnic produce in food assistance programs serving historically marginalized immigrant communities increases food waste and worsens food insecurity.

CONCLUSION

Emergent themes coalesced around the need to embed cultural tailoring into all levels of the food system, while also considering other characteristics of communities being reached (e.g., language needs). These efforts require coordinated actions related to food policy and advocacy, to better institutionalize these practices within the nutrition space.

Strengthening the System Supporting Perinatal People with Substance Use Disorder in the Midwest Using Group Model Building

INTRODUCTION

Providing comprehensive, evidence-based care to perinatal people with substance use disorders (SUD) requires multi-stakeholder collaboration and alignment. The National Maternal and Child Health Workforce Development Center facilitated a system-strengthening process with the Midwest substance use in pregnancy (SUPper) club, a regional collaborative of health care providers, state public health agencies, and community-rooted organizations.

METHODS

Facilitators led a 2 day group model building (GMB) workshop with 20 participants and two semi-structured interviews. Workshop participants were invited to complete an evaluation.

RESULTS

Two primary trends were identified as priorities for change: (1) Birthing people's perception/experience of stigma and (2) The Midwest SUPper Club's reach and influence. Three causal loop diagrams (CLDs) were created to capture the interconnected dynamics of the Midwest perinatal SUD system: (1) the influence of stigma on maternal and infant health outcomes, (2) the role of clinic, organizational, and state policies, and (3) the impact of workforce education and evidence-based practices on care. From the CLDs, four priorities for action emerged: (1) align and promote shared mental models across stakeholders, (2) expand education and training opportunities for the perinatal SUD workforce, (3) strengthen systems infrastructure to support care navigation for patients and providers, and (4) collaboratively identify evidence-based practices that meet regional needs. All evaluation respondents reported that the workshop supported the development of a shared mental model.

DISCUSSION

The GMB process strengthened collaboration and advanced strategic planning for the SUPper Club. GMB can be further utilized among diverse stakeholders across MCH systems to create shared mental models and accelerate collaborative planning efforts.

System dynamics simulation models on overweight and obesity in children and adolescents: A systematic review

It has increasingly been recognized that developing successful obesity prevention policies and interventions requires understanding of the complex mechanisms driving the obesity pandemic and that models could be useful tools for simulating policies. This paper reviews system dynamics simulation models of mechanisms driving childhood overweight and obesity and/or testing of preventive interventions. A systematic literature search was conducted in six databases from inception to January 2023 using terms related to overweight/obesity, children, and system dynamics. Study descriptives, mechanisms, and where to intervene (the leverage points), as well as quality assessments of the simulation models were extracted by two researchers into a predetermined template and narratively synthesized. Seventeen papers describing 15 models were included. Models describing the mechanisms ranged from only intrapersonal factors to models cutting across multiple levels of the ecological model, but mechanisms across levels were lacking. The majority of interventions tested in the simulation models were changes to existing model parameters with less emphasis on models that alter system structure. In conclusion, existing models included mechanisms driving youth obesity at multiple levels of the ecological model. This is useful for developing an integrated simulation model combining mechanisms at multiple levels and allowing for testing fundamental system changes.

Complex systems and participatory approaches to address maternal health disparities: Findings from a system dynamics group model building project in North Texas

Focusing on non-Hispanic Black women (NHBW) in North Texas, this study employed participatory system dynamics modeling to explore three hypotheses: (1) stakeholders will conceptualize structural racism is a pervasive macrostructural force that exerts downstream impacts to shape and perpetuate maternal health disparities among NHBW; (2) stakeholders will identify key causal forces and leverage points that exist across levels of influence; and (3) stakeholders will identify complex interactions, in the form of circular causality, that are present among the key causal forces and leverage points that shape NHBW maternal health disparities. Nine participants engaged in a virtual system dynamics group model-building session that focused on eliciting key variables, behavior-over-time graphs (BOTGs), causal loop diagram (CLD), and targets for action. Participants identified 83 key variables. BOTGs included an average of 6.56 notations and time horizons that, on average, started in 1956. The CLD featured 11 reinforcing and seven balancing feedback loops. Eleven targets for action were identified. Structural racism was revealed as a pervasive macrostructural force that shaped maternal health outcomes among NHBW. Key causal forces and leverage points were identified across levels of influence. Finally, feedback loops within the CLD exhibited circular causality.

"Nothing is linear": Characterizing the determinants and dynamics of CGM use in older adults with type 1 diabetes

AIMS

Continuous glucose monitoring (CGM) can reduce hypoglycemia in older adults with type 1 diabetes (T1D). We aimed to characterize factors that influence effective use in this age group.

METHODS

Older adults with type T1D (age ≥ 65) and their caregivers participated in one of a series of parallel group model building workshops, a participatory approach to system dynamics involving drawing and scripted group activities. Data were synthesized in a qualitative model of the hypothesized system of factors producing distinct patterns of CGM use in older adults. The model was validated through virtual follow-up interviews.

RESULTS

Data were collected from 33 participants (four patient-caregiver dyads, mean age 73.8 ± 4.4 years [range 66-85 years]; 16 % non-CGM users, 79 % pump users). The system model delineates drivers of CGM uptake, drivers of ongoing CGM use, and feedback loops that either reinforce or counteract future CGM use. Participants emphasized the importance of different sets of feedback loops at different points in the duration of CGM use.

CONCLUSIONS

The holistic system model underscores that factors and feedback loops driving effective CGM use in older adults are both individualized and dynamic (e.g., changing over time), suggesting opportunities for staged and tailored age-specific education and support.

System mapping with adolescents: Using group model building to map the complexity of obesity

Public health research and practice is increasingly employing systems thinking to help grapple with complex issues, from obesity to HIV treatment. At the same time, there is growing recognition that to address a given problem it is essential collaborate with those most at risk of or affected by it. Group model building (GMB), a process grounded in system dynamics, combines systems thinking and participatory methods to structure and address complex issues. As part of the CO-CREATE project we conducted GMB sessions with young people in six countries to create causal loop diagrams showing the factors that they believe drive obesity. This paper describes the background to GMB and the process we used to construct causal loop diagrams; it discusses how GMB contributed to generating noteworthy and useful findings, and the strengths and limitations of the method. Using GMB, we identified areas of concern to adolescents in relation to obesity that have so far had little attention in obesity research and policy: mental health and online activity. In using GMB, we also helped answer calls for a more participatory approach to youth involvement in research and policy development.

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.

System dynamics modelling to engage community stakeholders in addressing water and sugar sweetened beverage consumption

Background

Participatory approaches to develop community-based system dynamics models to tackle complexity are promising, but research is needed in how simulation models can be developed with community stakeholders to yield significant system insights. This study presents the results of a community-based system dynamics modelling process to increase water consumption and decrease sugar sweetened beverage consumption in Portland, Victoria, a regional town in Australia.

Methods

A series of group model building workshops with 11 community stakeholders addressing the topic of water and sugar sweetened beverage consumption was conducted in Portland. A simulating system dynamics model was built with stakeholders to inform action planning.

Results

A system dynamics model was created to provide insight into water and sugar sweetened beverage consumption in Portland. The model included six feedback loops describing the causal effects of sugar sweetened beverage consumption habits and norms, water taste, water consumption norms, public water availability, and public health benefits. For example, the sugar sweetened beverage consumption norm loop modelled how people overestimating others’ consumption may motivate an increase in their own consumption, feeding back and further amplifying an increase in sugar sweetened beverage consumption. The model contributed to the foundation of a strong partnership to improve the taste of water and educate the public on water consumption.

Conclusions

Engaging stakeholders in system dynamics modelling about water and sugar sweetened beverage consumption increased engagement and collaboration to address the problem among community stakeholders.

A qualitative study of effective collaboration among nurse home visitors, healthcare providers and community support services in the United States

Collaboration across sectors is needed to improve community health, but little is known about collaborative activities among public health prevention programs. Using the Nurse-Family Partnership® (NFP) home visiting program as context, this qualitative study aimed to describe effective collaboration among nurse home visitors, healthcare providers and community support services to serve families experiencing social and economic adversities. We used grounded theory to characterise collaboration with six purposively sampled NFP sites in the United States through in-depth interviews. We interviewed 73 participants between 2017 and 2019: 50 NFP staff, 18 healthcare providers and 5 other service providers. Interviews were recorded, transcribed, validated and analysed in NVivo 11. Validation steps included inter-coder consistency checks and expert review. Thematic memos were synthesised across sites. Most participants perceived collaboration to be important when serving families with complex needs, but substantial variation existed in the degree to which NFP nurses collaborate with providers dependent on provider type and community context. Factors that contributed to effective collaboration were relational in nature, including leadership commitment and provider champions, shared perceptions of trust, respect and value, and referral partnerships and outreach; organisational in terms of mission congruence between providers; and structural such as policy and system integration that facilitated data sharing and communication channels. These findings provide greater insights into effective cross-sector collaboration and care coordination for families experiencing adversities. Collaboration across sectors to promote health among families experiencing adversities requires intentional efforts by all inter-professional providers and continued commitment among all levels of leadership to coordinate services.

Using systems-mapping to address Adverse Childhood Experiences (ACEs) and trauma: A qualitative study of stakeholder experiences

Adverse childhood experiences (ACEs) and trauma have been linked to decreased psychosocial and physiological health functioning. While various individual and community-level interventions to address ACEs have been reported, one novel approach that has not been explored in detail is a community-engaged causal loop diagramming project, or systems mapping project (SMP), in which diverse stakeholders work together to document the forces that are creating the outcomes and patterns within the community. To better document and understand the impact of participation in an SMP, we conducted in-depth, qualitative interviews with 16 stakeholders who were involved in a systems-mapping process facilitated by a local nonprofit in Eastern North Carolina. We used an iterative, content analysis coding process to generate and analyze themes from these interviews. Three major themes emerged: 1) Recognition and understanding of own trauma, 2) Trauma as both a community issue and an individual issue, and 3) Systems-mapping as a conceptual tool with practical benefits. All participants strongly recommended the systems-mapping approach to other communities and believed that it is a valuable tool for empowerment and provided several considerations for future organizers of similar systems-mapping projects. Our findings suggest that systems mapping is a feasible, transferable, and promising modality for understanding and addressing ACEs at the individual, interpersonal, and community-levels, as well as for putting community voices at the forefront of efforts to address ACEs.

Cross-sector decision landscape in response to COVID-19: A qualitative network mapping analysis of North Carolina decision-makers

Introduction

The COVID-19 pandemic response has demonstrated the interconnectedness of individuals, organizations, and other entities jointly contributing to the production of community health. This response has involved stakeholders from numerous sectors who have been faced with new decisions, objectives, and constraints. We examined the cross-sector organizational decision landscape that formed in response to the COVID-19 pandemic in North Carolina.

Methods

We conducted virtual semi-structured interviews with 44 organizational decision-makers representing nine sectors in North Carolina between October 2020 and January 2021 to understand the decision-making landscape within the first year of the COVID-19 pandemic. In line with a complexity/systems thinking lens, we defined the decision landscape as including decision-maker roles, key decisions, and interrelationships involved in producing community health. We used network mapping and conventional content analysis to analyze transcribed interviews, identifying relationships between stakeholders and synthesizing key themes.

Results

Decision-maker roles were characterized by underlying tensions between balancing organizational mission with employee/community health and navigating organizational vs. individual responsibility for reducing transmission. Decision-makers' roles informed their perspectives and goals, which influenced decision outcomes. Key decisions fell into several broad categories, including how to translate public health guidance into practice; when to institute, and subsequently loosen, public health restrictions; and how to address downstream social and economic impacts of public health restrictions. Lastly, given limited and changing information, as well as limited resources and expertise, the COVID-19 response required cross-sector collaboration, which was commonly coordinated by local health departments who had the most connections of all organization types in the resulting network map.

Conclusions

By documenting the local, cross-sector decision landscape that formed in response to COVID-19, we illuminate the impacts different organizations may have on information/misinformation, prevention behaviors, and, ultimately, health. Public health researchers and practitioners must understand, and work within, this complex decision landscape when responding to COVID-19 and future community health challenges.

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.

Community-based system dynamics modelling of stigmatized public health issues: Increasing diverse representation of individuals with personal experiences

Utility of community-based system dynamics (CBSD) models on stigmatized public health issues and health disparities depends upon how representative the model is to real-world experience within the community. "Personal experience" participants (PEP), especially from marginalized groups, are essential model contributors, but are often underrepresented in modeling groups due to multiple barriers. This study details a method to increase PEP representation for models on stigmatized issues. We use a case study from a CBSD project on health disparities within the association between alcohol misuse (AM) and intimate partner violence (IPV) for Northern Plains Indigenous women. Short group model building sessions were held at three community organizations providing relevant resources. Each model contributed unique system components, and there were few similarities between models. A consolidated model provided a rich picture of the complex system. Adding brief PEP-based group modeling sessions can enhance PEP representation in model development for stigmatized public health issues.

The Public Health 12 framework: interpreting the 'Meadows 12 places to act in a system' for use in public health

BACKGROUND

Systems science approaches have demonstrated effectiveness in identifying underlying drivers of complex problems and facilitating the emergence of potential interventions that are locally tailored, feasible, sustainable and evidence informed. Despite the potential usefulness of system dynamics simulation modelling and other systems science modelling techniques in guiding implementation, time and cost constraints have limited its ability to provide strong guidance on how to implement complex interventions in communities. Guidance is required to ensure systems interventions lead to impactful systems solutions, implemented utilising strategies from the intersecting fields of systems science and implementation science. To provide cost-effective guidance on how and where to implement in systems, we offer a translation of the 'Meadows 12 places to act in a system' (Meadows 12) into language useful for public health.

METHODS

This translation of Meadows 12 was informed by our experience in working with 31 communities across two complex large scale randomised control trials and one large whole of community case study. These research projects utilised systems science and implementation science to co-create childhood obesity prevention interventions. The team undertaking this translation comprised research academics, implementation specialists and practitioners, practice-based researchers and a systems dynamicist. Our translation of each of the Meadows 12 levels to act in the system maintains the fidelity and nuance of the 12 distinct levels. We provide examples of each level of the Public Health 12 framework (PH12) drawn from 31 communities. All research was conducted in Victoria, Australia between 2016 and 2020.

RESULTS

PH12 provides a framework to guide both research and practice in real world contexts to implement targeted system level interventions. PH12 can be used with existing implementation science theory to identify relevant strategies for implementation of these interventions to impact the system at each of the leverage points.

CONCLUSION

To date little guidance for public health practitioners and researchers exists regarding how to implement systems change in community-led public health interventions. PH12 enables operationalisation Meadows 12 systems theory into public health interventions. PH12 can help research and practice determine where leverage can be applied in the system to optimise public health systems level interventions and identify gaps in existing efforts.

TRIAL REGISTRATION

WHO STOPS: ANZCTR: 12616000980437 .

RESPOND

ANZCTR: 12618001986268p .

Tools for Supporting the MCH Workforce in Addressing Complex Challenges: A Scoping Review of System Dynamics Modeling in Maternal and Child Health

Objectives

System Dynamics (SD) is a promising decision support modeling approach for growing shared understanding of complex maternal and child health (MCH) trends. We sought to inventory published applications of SD to MCH topics and introduce the MCH workforce to these approaches through examples to support further iteration and use.

Methods

We conducted a systematic search (1958–2018) for applications of SD to MCH topics and characterized identified articles, following PRISMA guidelines. Pairs of experts abstracted information on SD approach and MCH relevance.

Results

We identified 101 articles describing applications of SD to MCH topics. Approach: 27 articles present qualitative diagrams, 10 introduce concept models that begin to quantify dynamics, and 67 present more fully tested/analyzed models. Purpose: The most common purposes described were to increase understanding (n = 55) and support strategic planning (n = 26). While the majority of studies (n = 53) did not involve stakeholders, 40 included what we considered to be a high level of stakeholder engagement – a strength of SD for MCH. Topics: The two Healthy People 2020 topics addressed most frequently were early and middle childhood (n = 30) and access to health services (n = 26). The most commonly addressed SDG goals were “End disease epidemics” (n = 26) and “End preventable deaths” (n = 26).

Conclusions for Practice

While several excellent examples of the application of SD in MCH were found, SD is still underutilized in MCH. Because SD is particularly well-suited to studying and addressing complex challenges with stakeholders, its expanded use by the MCH workforce could inform an understanding of contemporary MCH challenges.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10995-022-03376-8.

Fixes that Fail: A system archetype for examining racialized structures within the food system

Access to fresh and healthy food within a neighborhood has been identified as a social mechanism contributing to community health. Grounded in the understanding that challenges related to equity within a food system are both structural and systemic, our research demonstrates how systems thinking can further understandings of food system complexity. Within systems thinking, we provide an illustration of how system archetypes offer an analytic tool for examining complex community issues. We map semi-structured interview data from community stakeholders (N = 22) to the "Fixes that Fail" system archetype to illuminate systemic challenges, such as incarceration and poverty, that structure food system inequity in urban communities. Within our research, the "Fixes that Fail" archetype provided a narrative interpretive tool for unveiling complexity within the food system and interdependencies with racialized systems such as criminal justice and labor markets. This system archetype provided an accessible approach for generating narratives about systemic complexity, the production of inequity through racialized forces, and opportunities for transformation.

New directions for participatory modelling in health: Redistributing expertise in relation to localised matters of concern

Participatory modelling seeks to foster stakeholder engagement to better attune models to their decision-making and policy contexts. Such approaches are increasingly advocated for use in the field of health. We review the instrumental and epistemological claims made in support of participatory modelling approaches. These accentuate participatory models as offering a better evidence-base for health policy decisions. By drawing attention to recent modelling experiments in a sector outside of health, that of water management, we outline a different way of thinking about participation and modelling. Here, the participatory model is configured in relation to matters of 'knowledge controversy', with modelling constituted as an 'evidence-making intervention' in relation to the making of science and expertise. Rather than presenting participatory models as an improved technical solution to addressing given policy problems within an evidence-based intervention approach, models are alternatively potentiated as sites for the redistribution of expertise among actor networks as they seek to engage politically in a matter of concern. This leads us to consider possible new directions for participatory modelling in the field of health.

Advancing sustainable development goals through immunization: a literature review

BACKGROUND

Immunization directly impacts health (SDG3) and brings a contribution to 14 out of the 17 Sustainable Development Goals (SDGs), such as ending poverty, reducing hunger, and reducing inequalities. Therefore, immunization is recognized to play a central role in reaching the SDGs, especially in low- and middle-income countries (LMICs). Despite continuous interventions to strengthen immunization systems and to adequately respond to emergency immunization during epidemics, the immunization-related indicators for SDG3 lag behind in sub-Saharan Africa. Especially taking into account the current Covid19 pandemic, the current performance on the connected SDGs is both a cause and a result of this.

METHODS

We conduct a literature review through a keyword search strategy complemented with handpicking and snowballing from earlier reviews. After title and abstract screening, we conducted a qualitative analysis of key insights and categorized them according to showing the impact of immunization on SDGs, sustainability challenges, and model-based solutions to these challenges.

RESULTS

We reveal the leveraging mechanisms triggered by immunization and position them vis-à-vis the SDGs, within the framework of Public Health and Planetary Health. Several challenges for sustainable control of vaccine-preventable diseases are identified: access to immunization services, global vaccine availability to LMICs, context-dependent vaccine effectiveness, safe and affordable vaccines, local/regional vaccine production, public-private partnerships, and immunization capacity/capability building. Model-based approaches that support SDG-promoting interventions concerning immunization systems are analyzed in light of the strategic priorities of the Immunization Agenda 2030.

CONCLUSIONS

In general terms, it can be concluded that relevant future research requires (i) design for system resilience, (ii) transdisciplinary modeling, (iii) connecting interventions in immunization with SDG outcomes, (iv) designing interventions and their implementation simultaneously, (v) offering tailored solutions, and (vi) model coordination and integration of services and partnerships. The research and health community is called upon to join forces to activate existing knowledge, generate new insights and develop decision-supporting tools for Low-and Middle-Income Countries' health authorities and communities to leverage immunization in its transformational role toward successfully meeting the SDGs in 2030.

County-level correlates of dental service utilization for low income pregnant women. Ecologic study of the North Carolina Medicaid for Pregnant Women (MPW) program

Background

Dental care utilization for low income pregnant women is met with challenges in the traditional dentist-centered model of care. County-level measures provide insights for policy and roles for stakeholders that extend beyond the dentist-patient relationship. We examined county-level data to generate hypotheses about factors that influence utilization of dental services in North Carolina’s Medicaid for Pregnant Women (MPW) program.

Methods

County-level Medicaid utilization data for dental services for 2014–2016 were pooled to get mean county estimates of dental utilization in the MPW program. Descriptive statistics and multivariate regression models of dental utilization and county-level measures are presented. Data used were collected by NC Child and the Robert Wood Johnson Foundation’s County Health Rankings Reports. USDA Economic Research Service data were used to categorize counties in terms of Farming, Recreation, Persistent Poverty, and metro/non-metro status using Rural Urban Continuum Codes.

Results

Dental utilization ranged from 1–26% with a median of 8.5% across the 100 counties of North Carolina. Strong patterns linking utilization of dental services in the MPW program to contextual social measures of well-being emerged, specifically, increased reporting of child abuse and neglect, elevated infant mortality, poor quality of life, and worse ranking in years of potential life lost. Counties with persistent poverty had lower rates of dental utilization.

Conclusions

Utilization of dental services in the MPW program is generally low. Patterns identify the potential for enhancing community-clinical linkages to improve birth outcomes and care coordination for pregnant women to enhance dental utilization in this population.

Dental coverage in the Medicaid program in most states is administered separately from medical coverage. The separation of the funding mechanisms adds a further layer of complexity to care integration. Efforts to enhance dental care for pregnant women in the Medicaid program may benefit from policy that aligns incentives for care coordination within the community. Policy that extends the window of eligibility for dental benefits to 24 months after the birth of the child will help women complete the dental treatment that is needed. This also leverages the value of care coordination for community stakeholders from diverse child health sectors.

Effectiveness of Social Measures against COVID-19 Outbreaks in Selected Japanese Regions Analyzed by System Dynamic Modeling

In Japan’s response to the coronavirus disease 2019 (COVID-19), virus testing was limited to symptomatic patients due to limited capacity, resulting in uncertainty regarding the spread of infection and the appropriateness of countermeasures. System dynamic modelling, comprised of stock flow and infection modelling, was used to describe regional population dynamics and estimate assumed region-specific transmission rates. The estimated regional transmission rates were then mapped against actual patient data throughout the course of the interventions. This modelling, together with simulation studies, demonstrated the effectiveness of inbound traveler quarantine and resident self-isolation policies and practices. A causal loop approach was taken to link societal factors to infection control measures. This causal loop modelling suggested that the only effective measure against COVID-19 transmission in the Japanese context was intervention in the early stages of the outbreak by national and regional governments, and no social self-strengthening dynamics were demonstrated. These findings may contribute to an understanding of how social resilience to future infectious disease threats can be developed.

A System Dynamics Simulation Applied to Healthcare: A Systematic Review

In recent years, there has been significant interest in developing system dynamics simulation models to analyze complex healthcare problems. However, there is a lack of studies seeking to summarize the available papers in healthcare and present evidence on the effectiveness of system dynamics simulation in this area. The present paper draws on a systematic selection of published literature from 2000 to 2019, in order to form a comprehensive view of current applications of system dynamics methodology that address complex healthcare issues. The results indicate that the application of system dynamics has attracted significant attention from healthcare researchers since 2013. To date, articles on system dynamics have focused on a variety of healthcare topics. The most popular research areas among the reviewed papers included the topics of patient flow, obesity, workforce demand, and HIV/AIDS. Finally, the quality of the included papers was assessed based on a proposed ranking system, and ways to improve the system dynamics models' quality were discussed.