Complex systems thinking and current impasses in health disparities research

Supervised Toothbrushing Programmes: Understanding Barriers and Facilitators to Implementation

OBJECTIVES

Supervised toothbrushing programmes (STPs), whereby children brush their teeth at nursery or school with a fluoride toothpaste under staff supervision, are a clinically and cost-effective intervention to reduce dental caries. However, uptake is varied, and the reasons unknown. The aim was to use an implementation science approach to explore the perspectives of key stakeholders on the barriers and facilitators at each level of implementation of STPs.

METHODS

This qualitative study involved individual interviews and focus groups with a purposive sample of stakeholders involved at all levels of implementation of STPs: (1) policymakers; (2) providers of STPs; (3) nursery/school staff; (4) parents/carers; and (5) children (aged 2-6 years old) across England. Data collection and analysis were guided by the Consolidated Framework for Implementation Research (CFIR).

RESULTS

A total of 159 stakeholders were interviewed (40 individual interviews and 17 focus groups) across all levels of implementation. Barriers and facilitators to STP implementation were identified across 35 of the 39 CFIR constructs. Four themes were identified that determined STP implementation: (1) acceptability of STPs; (2) external 'make or break' conditions; (3) the importance of engagement across the system; and (4) desire for centralised support.

CONCLUSIONS

This is the first study to qualitatively explore the barriers and facilitators to STP at all levels of implementation underpinned by an implementation science framework. The findings have strong implications for policymakers who wish to implement STPs, highlighting the need for careful consideration of the adaptability of the programmes, the role of formal and informal engagement systems, and the need for centralised support. This work has facilitated the co-design and piloting of a supervised toothbrushing implementation toolkit, which provides a central hub of resources and good practice to optimise implementation of STPs at scale.

Transition of care readiness among adolescents with chronic pain between 2021-2022 in a Nationally representative sample

Chronic pain impacts 11-33% of children and will continue into adulthood for over half of them. Transition of pain management to adult care is crucial given high risk of interruption of care which is associated with subsequent poor medical, social, and vocational outcomes. Yet the transition experience for these youth is poorly characterized. Using a sample from the 2021 and 2022 National Survey of Children's Health (conducted by parent report), we aimed to determine the prevalence of transition readiness among adolescents with chronic pain in the U.S. and estimate the association of readiness with biopsychosocial-cultural and health system characteristics. Of the 2584 adolescents aged 14-17 with chronic pain, 23.9% of adolescents met criteria for transition readiness. Using Poisson regression, we determined those more likely to meet criteria were older (PR 1.8 95%CI: 1.3, 2.6), female (PR 1.6 95% CI: 1.2, 2.2), White (Asian PR 0.4, 95% CI: 0.2, 0.9, Multi-racial PR 0.6 95% CI: 0.4, 0.9), and experienced shared decision making (aPR 1.7 95% CI: 1.1, 2.8). Fewer than half met criteria for medical home, effective care coordination, and adequate insurance. Poor mental health emerged as a concern with high levels of anxiety and/or depression (48%) and low levels of flourishing (42%). This is an important first step in demonstrating low transition readiness among adolescents with chronic pain and identifying mental health and healthcare continuity concerns. Future research should incorporate stakeholder perspectives and investigate pain specific factors relevant to transition readiness and investigate how readiness relates to transition outcomes. PERSPECTIVE: This article establishes low readiness to transition from pediatric to adult healthcare among adolescents with chronic pain and identifies disparities in readiness. Poor mental health and inadequate healthcare access were identified as factors which may impact transition intervention delivery. These findings can guide development and implementation of a transition intervention.

The epidemiologic case for urban health: conceptualizing and measuring the magnitude of challenges and potential benefits

We discuss how epidemiology has been and can continue to be used to advance understanding of the links between urban areas and health informed by an existing urban-health conceptual framework. This framework considers urban areas as contexts for health, determinants of health and modifiers of health pathways, and part of a complex system that affects health. We highlight opportunities for descriptive epidemiology to inform the context of urban health, for example, by characterizing the social and physical environments that give rise to health and the actions that change those conditions. We then describe inferential tools for evaluating the impact of group-level actions (e.g., interventions, policies) on urban health, providing some examples, and describing assumptions and challenges. Finally, we discuss opportunities and challenges of applying systems thinking and methods to advance urban health. While different conceptual frames lead to different insights, each perspective demonstrates that urban health is a major and growing challenge. The effectiveness of urban health knowledge, action, and policy as the world continues to urbanize can be informed by applying and expanding upon research and surveillance methods described here.

Monitoring and adaptation of a system dynamics approach to prevent childhood overweight and obesity: findings from the LIKE programme

BACKGROUND

There are few examples of public health programmes rooted in system dynamics methodology. The aim of this paper was to broaden the evidence-base on the implementation and evaluation of a system dynamics programme for obesity prevention, using the Lifestyle Innovations based on youth's Knowledge and Experience (LIKE) Programme as a case study. In LIKE, system dynamics principles were operationalized around three central pillars: the action programme is (1) rooted in a system-based understanding; (2) integrated in the local context and (3) dynamic.

METHODS

This study took place in an urban setting in Amsterdam, the Netherlands, as part of the LIKE programme. The action programme consisted of establishing thematic action groups around previously identified leverage points within the system of overweight-related behaviours among adolescents. An action monitoring register was used to monitor action development and implementation, including the targeted system level. To track action implementation and adaptation over time, we conducted an in-depth evaluation using ripple effects mapping and additional interviews for three action groups. This data was analysed by performing a thematic content analysis.

RESULTS

During the 6-year course of LIKE, 63 action ideas were formulated by 12 action groups, and 22 of these actions were implemented. Most of these implemented actions targeted lower system levels. A total of 9 of the 22 implemented actions were incorporated in existing initiatives. We observed that operationalization of system dynamics principles influenced the form of the action programme. Action ideas were dynamic in the sense that they changed over time or were abandoned because of growing system insights and/or factors within the wider context. This required shifting the focus from individual actions to the programme as a whole and formulating action ideas in terms of their function in changing the system, instead of on its form.

CONCLUSIONS

Using LIKE as a case study, this study provides an example of the output of a system dynamics action programme. We show how leverage points can be used as a starting point to develop action ideas that target lower and higher system levels. This demands monitoring and evaluation that facilitates continuous customization of the programme.

Structural Racism, Geographies of Opportunity, and Maternal Health Inequities: A Dynamic Conceptual Framework

Addressing the grave racial inequities in maternal health requires a new generation of research that better operationalizes root causes of these outcomes. Recent frameworks improving the conceptualization of structural racism have illuminated the need for better conceptual clarity when investigating neighborhoods as a site of structural marginalization for Black birthing populations as well. In particular, better conceptualization of dynamic feedback in how neighborhoods are constructed and experienced, especially as they embed vicious cycles of place-based racialization, is integral to producing conceptually relevant and translatable evidence to address inequities in Black maternal health. This study presents a newly developed framework that integrates dynamic insight on neighborhood contexts from multiple disciplines to better conceptualize how it operates during the childbearing window to drive inequitable maternal morbidity rates among Black birthing people. I also compare and contrast this framework with existing frameworks based on how they represent key domains of social and structural determinants, neighborhood context, and dynamic feedback. Illustrating the strengths and weaknesses of each framework can improve researchers' ability to leverage these frameworks when developing project-specific conceptual models on structural racism, neighborhood context, and Black maternal health. Building a comparative repository of frameworks, in conjunction with developing new frameworks, will improve the field's capacity to follow best practices of rooting research in conceptually explicit models that improve operationalization and translation of evidence to eventually eliminate racial inequities in maternal health.

Reconceptualizing rurality: Exploring community capital to identify distinct rural classes in the United States

Background

In population health research, rurality is often defined using broad population density measures, which fail to capture the diverse and complex characteristics of rural areas. While researchers have developed more nuanced approaches to study neighborhood and area effects on health in urban settings, similar methods are rarely applied to rural environments. To address this gap, we aimed to explore dimensions of contextual heterogeneity across rural settings in the US.

Methods

We conducted an exploratory latent class analysis (LCA) to identify distinct classes of rurality. Using the Community Capitals Framework, we collated and analyzed nationally representative data for each domain of rural community capital across all rural census tracts in the US (n = 15,643). Data for this study were sourced from ten publicly available datasets spanning the years 2018-2021. To provide preliminary validation of our findings, we examined the Social Vulnerability Index (SVI) percentile rankings across the identified rural classes.

Results

A four-class model solution provided the best fit for our data. Our LCA results identified four distinct classes of rurality that vary in terms of capital types: Outlying (n = 3,566, 22.7%), Developed (n = 3,210, 20.5%), Well-Resourced (n = 4,896, 31.3%), and Adaptable (n = 3,981, 25.4%). The mean SVI percentile rankings differed significantly across these classes, with Well-Resourced having the lowest and Adaptable the highest mean percentile rankings.

Conclusions

We identified different types of rurality at the census tract level that fall along a social gradient as indicated by variation in SVI percentile rankings. These findings highlight that each rural class has a unique combination of community capitals. This nuanced approach to conceptualizing rurality provides the opportunity to identify interventions that meet specific rural communities' unique strengths and needs.

Validation of a Novel Method to Evaluate Community-Based Interventions That Improve Access to Fruits and Vegetables

BACKGROUND

Current evaluation tools are inadequate for assessing the impact of small-scale interventions, such as farmer's markets or community meal programs, on fruit and vegetable consumption. This study analyzes the pilot data of a novel tool designed to evaluate community-based programs' impact on fruit and vegetable consumption. Our research addresses the gap in effective evaluation methods for dietary behaviors within underserved populations.

METHODS

The survey tool was developed through a participatory research approach involving interest holders and community members. We conducted a pilot survey across four community-based programs, validated the findings, and compared them against the data from the Behavioral Risk Factor Surveillance System.

RESULTS

This pilot survey demonstrated a high completion rate of 98.2%. Notably, 62.5% of respondents reported an increased consumption of fruits and vegetables since participating in the programs and cited cost, time, and accessibility as primary barriers to healthy eating. There is a strong, though not significant, correlation of 0.876 (p = 0.12) between the pilot data of prevalence of daily fruit and vegetable consumption and the national average.

CONCLUSION

Our findings suggest the survey tool effectively captures dietary behaviors and the influence of community-based programs. Further research is required to enhance its applicability in diverse settings and extend robust impact evaluation methods for these programs.

Ethical, Legal, and Social Implications of Gene-Environment Interaction Research

Many complex disorders are impacted by the interplay of genetic and environmental factors. In gene-environment interactions (GxE), an individual's genetic and epigenetic makeup impacts the response to environmental exposures. Understanding GxE can impact health at the individual, community, and population levels. The rapid expansion of GxE research in biomedical studies for complex diseases raises many unique ethical, legal, and social implications (ELSIs) that have not been extensively explored and addressed. This review article builds on discussions originating from a workshop held by the National Institute of Environmental Health Sciences (NIEHS) and the National Human Genome Research Institute (NHGRI) in January 2022, entitled: "Ethical, Legal, and Social Implications of Gene-Environment Interaction Research." We expand upon multiple key themes to inform broad recommendations and general guidance for addressing some of the most unique and challenging ELSI in GxE research. Key takeaways include strategies and approaches for establishing sustainable community partnerships, incorporating social determinants of health and environmental justice considerations into GxE research, effectively communicating and translating GxE findings, and addressing privacy and discrimination concerns in all GxE research going forward. Additional guidelines, resources, approaches, training, and capacity building are required to further support innovative GxE research and multidisciplinary GxE research teams.

Integrating Multi-Cancer Early Detection (MCED) Tests with Standard Cancer Screening: System Dynamics Model Development and Feasibility Testing

BACKGROUND

Cancer screening plays a critical role in early disease detection and improving outcomes. In Australia, established screening protocols for colorectal, breast and cervical cancer have significantly contributed to timely cancer detection. However, the recent introduction of multi-cancer early detection (MCED) tests arguably can disrupt current screening, yet the extent to which these tests provide additional benefits remains uncertain. We present the development and initial validation of a system dynamics (SD) model that estimates the additional cancer detections and costs associated with MCED tests.

AIM

This article describes the development of a simulation model built to evaluate the additional patient diagnoses and the economic impact of incorporating MCED testing alongside Australia's well-established standard of care (SOC) screening programs for colorectal, breast, cervical and lung cancers. The model was designed to estimate the additional number of patients diagnosed at each cancer stage (stage I, II, III, IV, or unknown) and the associated costs. This simulation model allows for the analysis of multiple scenarios under a plausible set of assumptions regarding population-level participation rates.

METHODS

An SD model was developed to represent the existing SOC national cancer screening pathways and to integrate potential clinical pathways that could be introduced by MCED tests. The SD model was built to investigate three scenarios for the use of MCED testing: firstly, to explore the viability of MCED testing as a substitute among individuals who are not opting for SOC screening for any reason; secondly, to implement MCED testing exclusively for individuals ineligible for SOC screening, yet have high-risk characteristics; and thirdly, to employ MCED testing after SOC screening to serve as a triaging/confirmatory tool for individuals receiving inconclusive test results. The three primary scenarios were constructed by varying diagnostic accuracy and uptake rates of MCED tests.

DISCUSSION

The clinical utility and outcomes of MCED testing for screening and early detection still lack comprehensive evidence. Nonetheless, this simulation model facilitates a thorough analysis of MCED tests within the Australian healthcare context, providing insights into potential additional detections and costs to the healthcare system, which may help prioritise future evidence development. The adaptable yet novel SD model presented herein is anticipated to be of considerable interest to industry, policymakers, consumers and clinicians involved in informing clinical and economic decisions regarding integrating MCED tests as cancer screening and early detection tools. The expected results of applying this SD model will determine whether using MCED testing in conjunction with SOC screening offers any potential benefits, possibly guiding policy decisions and clinical practices towards the adoption of MCED tests.

Sport-related concussion research agenda beyond medical science: culture, ethics, science, policy

The Concussion in Sport Group guidelines have successfully brought the attention of brain injuries to the global medical and sport research communities, and has significantly impacted brain injury-related practices and rules of international sport. Despite being the global repository of state-of-the-art science, diagnostic tools and guides to clinical practice, the ensuing consensus statements remain the object of ethical and sociocultural criticism. The purpose of this paper is to bring to bear a broad range of multidisciplinary challenges to the processes and products of sport-related concussion movement. We identify lacunae in scientific research and clinical guidance in relation to age, disability, gender and race. We also identify, through multidisciplinary and interdisciplinary analysis, a range of ethical problems resulting from conflicts of interest, processes of attributing expertise in sport-related concussion, unjustifiably narrow methodological control and insufficient athlete engagement in research and policy development. We argue that the sport and exercise medicine community need to augment the existing research and practice foci to understand these problems more holistically and, in turn, provide guidance and recommendations that help sport clinicians better care for brain-injured athletes.

Analysis of how a complex systems perspective is applied in studies on socioeconomic inequalities in health and health behaviour-a call for reporting guidelines

BACKGROUND

A complex systems perspective is gaining popularity in research on socioeconomic inequalities in health and health behaviour, though there may be a gap between its popularity and the way it is implemented. Building on our recent systematic scoping review, we aim to analyse the application of and reporting on complex systems methods in the literature on socioeconomic inequalities in health and health behaviour.

METHODS

Selected methods and results from the review are presented as a basis for in-depth critical reflection. A traffic light-based instrument was used to assess the extent to which eight key concepts of a complex systems perspective (e.g. feedback loops) were applied. Study characteristics related to the applied value of the models were also extracted, including the model evidence base, the depiction of the model structure, and which characteristics of model relationships (e.g. polarity) were reported on.

RESULTS

Studies that applied more key concepts of a complex systems perspective were also more likely to report the direction and polarity of relationships. The system paradigm, its deepest held beliefs, is seldom identified but may be key to recognize when designing interventions. A clear, complete depiction of the full model structure is also needed to convey the functioning of a complex system. We recommend that authors include these characteristics and level of detail in their reporting.

CONCLUSIONS

Above all, we call for the development of reporting guidelines to increase the transparency and applied value of complex systems models on socioeconomic inequalities in health, health behaviour and beyond.

Participatory Systems Thinking to Elucidate Drivers of Food Access and Diet Disparities among Minoritized Urban Populations

The purpose of this study was to use participatory systems thinking to develop a dynamic conceptual framework of racial/ethnic and other intersecting disparities (e.g., income) in food access and diet in Philadelphia and to identify policy levers to address these disparities. We conducted three group model building workshops, each consisting of a series of scripted activities. Key artifacts or outputs included qualitative system maps, or causal loop diagrams, identifying the variables, relationships, and feedback loops that drive diet disparities in Philadelphia, Pennsylvania. We used semi-structured methods informed by inductive thematic analysis and network measures to synthesize findings into a single causal loop diagram. There were twenty-nine participants with differing vantages and expertise in Philadelphia's food system, broadly representing the policy, community, and research domains. In the synthesis model, participants identified 14 reinforcing feedback loops and one balancing feedback loop that drive diet and food access disparities in Philadelphia. The most highly connected variables were upstream factors, including those related to racism (e.g., residential segregation) and community power (e.g., community land control). Consistent with existing frameworks, addressing disparities will require a focus on upstream social determinants. However, existing frameworks should be adapted to emphasize and disrupt the interdependent, reinforcing feedback loops that maintain and exacerbate disparities in fundamental social causes. Our findings suggest that promising policies include those that empower minoritized communities, address socioeconomic inequities, improve community land control, and increase access to affordable, healthy, and culturally meaningful foods.

Conceptual frameworks for the integration of genetic and social epidemiology in complex diseases

Uncovering the root causes of complex diseases requires complex approaches, yet many studies continue to isolate the effects of genetic and social determinants of disease. Epidemiologic efforts that under-utilize genetic epidemiology methods and findings may lead to incomplete understanding of disease. Meanwhile, genetic epidemiology studies are often conducted without consideration of social and environmental context, limiting the public health impact of genomic discoveries. This divide endures despite shared goals and increases in interdisciplinary data due to a lack of shared theoretical frameworks and differing language. Here, we demonstrate that bridging epidemiological divides does not require entirely new ways of thinking. Existing social epidemiology frameworks including Ecosocial theory and Fundamental Cause Theory, can both be extended to incorporate principles from genetic epidemiology. We show that genetic epidemiology can strengthen, rather than detract from, efforts to understand the impact of social determinants of health. In addition to presenting theoretical synergies, we offer practical examples of how genetics can improve the public health impact of epidemiology studies across the field. Ultimately, we aim to provide a guiding framework for trainees and established epidemiologists to think about diseases and complex systems and foster more fruitful collaboration between genetic and traditional epidemiological disciplines.

Using systems thinking to leverage adolescent sexual and reproductive health in rural Latino communities

Disparities in adolescent sexual and reproductive health (SRH) outcomes in rural areas of the USA persist as a concern in achieving health equity for youth. A growing body of literature recognises that improving adolescents' health necessitates systems thinking to address the culture and environment in which adolescents live. This paper uses systems thinking to identify leverage points to improve adolescent SRH in rural Latino communities in California. We conducted focus group discussions with 22 young people and interviewed 10 adult stakeholders to centre the perspectives of youth and youth-serving professionals. Transcripts were coded and analysed using systems thinking. Five themes were developed: (1) community and cultural norms can be a source of both support and stigma for youth; (2) families are key to supporting health education and services; (3) rural schools provide a central hub for programme delivery; (4) community-based organisations can work to serve rural youth, but limited resources and transport are challenges; and (5) youth face considerable barriers accessing SRH services in their communities. Using systems thinking to identify leverage points and gaps in interactions between system components influencing youth can aid in the development of more holistic and culturally responsive approaches for rural youth SRH.

Assessing the Impact and Cost-Effectiveness of Exposome Interventions on Alzheimer's Disease: A Review of Agent-Based Modeling and Other Data Science Methods for Causal Inference

Background: The exposome (e.g., totality of environmental exposures) and its role in Alzheimer's Disease and Alzheimer's Disease and Related Dementias (AD/ADRD) are increasingly critical areas of study. However, little is known about how interventions on the exposome, including personal behavioral modification or policy-level interventions, may impact AD/ADRD disease burden at the population level in real-world settings and the cost-effectiveness of interventions. Methods: We performed a critical review to discuss the challenges in modeling exposome interventions on population-level AD/ADRD burden and the potential of using agent-based modeling (ABM) and other advanced data science methods for causal inference to achieve this. Results: We describe how ABM can be used for empirical causal inference modeling and provide a virtual laboratory for simulating the impacts of personal and policy-level interventions. These hypothetical experiments can provide insight into the optimal timing, targeting, and duration of interventions, identifying optimal combinations of interventions, and can be augmented with economic analyses to evaluate the cost-effectiveness of interventions. We also discuss other data science methods, including structural equation modeling and Mendelian randomization. Lastly, we discuss challenges in modeling the complex exposome, including high dimensional and sparse data, the need to account for dynamic changes over time and over the life course, and the role of exposome burden scores developed using item response theory models and artificial intelligence to address these challenges. Conclusions: This critical review highlights opportunities and challenges in modeling exposome interventions on population-level AD/ADRD disease burden while considering the cost-effectiveness of different interventions, which can be used to aid data-driven policy decisions.

Nursing in a culture of peace

BACKGROUND

The knowledge and practice in the field of peacebuilding is congruent with nursing and offers important dimensions and insight that can strengthen the work of nurses in building healthy communities and individuals.

PURPOSE

This article summarizes key literature and discussions with faculty in each field to outline impactful opportunities for interprofessional collaboration around peace and health.

METHODS

An iterative process of reviewing theory and practice in each field produces a structured comparison of major commonalities and differences.

DISCUSSION

Collaboration between nurses and peacebuilding practitioners provides a unique opportunity to address the wicked problems of direct and indirect (structural) violence. Shared interests in a holistic systems lens approach to violence prevention and conflict transformation provide for professional synergies.

CONCLUSION

An exemplary case for collaboration between nurses and peacebuilding practitioners is found in the work of understanding and addressing direct and indirect violence locally and globally.

Navigating the complexity of a collaborative, system-wide public health programme: learning from a longitudinal qualitative evaluation of the ActEarly City Collaboratory

BACKGROUND

Addressing the upstream social determinants of health (e.g. built environment, education) can reduce the burden of non-communicable diseases. To do so effectively often requires system-wide collaboration. However, collaborating across multiple sectors, organizations and disciplines within a complex system can be challenging. ActEarly was a public health research consortium that aimed to improve child health by building an interdisciplinary, cross-city partnership to develop and/or evaluate upstream interventions, increase research capacity and improve collaboration between researchers, local authorities and communities. This paper explores ActEarly's experiences of navigating complexity to identify mechanisms that supported its implementation and proposes recommendations for future intersectoral and interdisciplinary population health research collaborations.

METHODS

We conducted a longitudinal qualitative study of ActEarly, integrating findings from inductive documentary analysis of internal documents (mainly meetings minutes and reports) (n = 114) and interviews (n = 70) with 45 consortium members at three different timepoints (2018, 2021, 2023). Participants worked across different organizations, cities, roles and levels of seniority in the consortium.

FINDINGS

Clarity, Unity, Flexibility and Feasibility were seen as the key mechanisms required to support ActEarly's implementation. Clear aims, governance structures and communication were necessary to manage the uncertainty of the complex system. A unified approach, characterized by strong relationships, having a shared vision and communal access to resources supported effective collaboration. Flexibility was required to adjust to different ways of working, respond to wider system events and manage the consortium. Establishing feasible aims that responded to the limitations of the system, the available resources and research infrastructure was required for teams to deliver the work.

CONCLUSIONS

Implementing multi-faceted programmes in a complex system can be challenging. We recommend that future whole-systems consortia seeking to improve population health build Clarity, Unity, Flexibility and Feasibility into their programmes, noting the complex interrelationships between these factors. Iterative reflections from all parties should support delivery amidst the uncertainty that comes with running a population health research collaboration, and strong leadership and governance should play a key role in ensuring that these are built into foundations the programme.

A complex systems lens can help us understand drivers of emerging challenges in work and health

Emergent health challenges related to work Work is not only central to population health but is also a significant driver of social inequality in health (1). In a recent Lancet series on work and health, the authors outlined six emergent challenges concerning work: the impact of technology, the intersection of work with sociodemographic health determinants, migrant work, precarious employment, long working hours, and climate change (1). The authors of the Lancet series also presented recommendations for future research, advocating for the utilization of mixed-methods, innovative analytical approaches (eg, causal modeling), realist evaluation, and interdisciplinary collaboration. Although each of these approaches are highly relevant, their integrated application was only vaguely outlined.

We believe that each of these work and health challenges show features of complex adaptive systems. They are multifaceted, constantly evolving, and emerge from our complex and disordered real world, which is often characterized by interactions, non-linearity, interference, feedback loops, and adaptation. Consequently, future research on work and health may benefit from adopting a complex systems perspective to obtain a comprehensive understanding of the drivers of these challenges (2–4). We have recently developed an interdisciplinary framework for knowledge production aimed at understanding complex health issues within the domain of public health, rooted in complex systems theory (5). This framework can serve to organize our thinking, formulate research questions, and integrate methodologies related to each of these six work and health challenges.

Briefly outlined, the Health Complexity framework relates to three core dimensions in which complex health issues may be conceptualized: patterns, mechanisms, and dynamics (5). Patterns: Looking for specific patterns of disease or risk factors allows us to empirically identify health issues that emerge from the mechanisms and dynamics of the underlying systems, eventually allowing us to discover vulnerable subgroups, and thereby set boundaries for targeted interventions. Mechanisms: Understanding the core mechanisms that give rise to these emergent health patterns and how they are connected across scales through interactions and interference can help us identify potential leverage points for intervention. Dynamics: Building evidence on the dynamics that make patterns and mechanisms change over time will allow us to identify vicious circles associated with particularly high morbidity.

Between them, these dimensions cover seven key features of complex systems (emergence, interactions, non-linearity, interference, feedback loops, adaptation, and evolution), which we have highlighted as central to public health. The Health Complexity framework builds upon the ideas of methodological pluralism (6–8) and is intended to be an overarching framework for interdisciplinary and collaborative research on complex health issues, also in the field of work and health. As an illustration, we will outline the elements needed to examine one of these challenges – precarious employment – through a complex systems lens, particularly highlighting how this approach influences the way we phrase research questions on health problems that do justice to the complexity of the real world.

Precarious employment viewed through a complex systems lens With globalization and technological advancements, there has been a shift towards a gig economy. This has led to an increase in temporary, part-time, and freelance work, which often lacks stability and benefits. Precarious employment specifically refers to such work characterized by employment insecurity, income inadequacy, and lack of rights and protection (9). The lack of stability and benefits associated with precarious employment combined with poor working conditions have been shown to have negative effects on physical and mental health (10–13). Workers may experience higher levels of stress, depression, and other health problems due to financial insecurity and lack of access to healthcare, which collectively may be an important driver of health inequality and of health decline. In a life course perspective, there may also be important feedback mechanisms exacerbating such inequality, with poor health not only being a consequence of precarious employment, but workers with poor health may be more likely to be excluded from stable work (14). Overall, the increasing prevalence of precarious employment represents a substantial challenge for public health, which can be seen as a sort of byproduct of larger societal trends. We believe that employing a complex systems lens can help us generate relevant scientific knowledge about the fundahttps://www.sjweh.fi/editoi.sjweh.fi/pics/update_u_3.gifmental drivers of this problem. This essentially entails three interlinked steps organized around the three core dimensions of the Health Complexity Framework (figure 1).

Patterns: As a first step, we need to zoom out and understand the health effects associated with emergent patterns of precarious employment in their context across time and space, asking questions such as: •How does precarious employment change over time, and how does this changing pattern affect population health? •Are there certain population groups, defined, eg, by socioeconomic status, age, occupation, migrant status, or geographical regions who experience more adverse health effects by precarious employment than others?

Systematically evaluating health patterns associated with precariousness can help us define boundaries for targeted prevention. Employing classical epidemiological surveillance methods alongside data science techniques for uncovering patterns within multidimensional large-scale datasets serves as key examples of such pattern identification.

Mechanisms: As a second step, we need to understand what mechanisms underlying the health effects of precariousness and how elements of these mechanisms are connected across scales, from cells to society, asking questions such as: •How do mechanisms interact across biological, behavioral, social, and societal scales to create the rising public health problems associated with precarious employment? •Does precarious employment and its associated health problems cluster and spread across social networks and/or across occupational and economic sectors?

Systematically evaluating the interconnectedness between mechanisms and individuals across various scales can help us identify leverage points for intervention. Whereas biomedical studies can contribute to uncovering the biological mechanisms linked to precarious employment, such as the embodiment of stress (15), the social sciences may offer profound insights into macro-scale mechanisms involving political, economic, and social structures.

Dynamics: As a third step, we need to explore how the health effects of precarious employment change over time due to dynamic processes like adaptation and feedback, asking questions such as: •How do national political and social contexts adapt to historical changes in the labor market including the increase in precarious employment, and what is the impact of this adaptation when it comes to how and to what extent precarious employment can affect the health of individuals and populations? •Is there a reinforcing feedback mechanism between social disadvantage, precarious employment, and health? This mechanism could create a vicious circle—for example, social disadvantage increasing the likelihood of precarious employment, which then leads to health consequences that may further reinforce social disadvantage.

Systematically assessing such dynamism can help us intervene on vicious circles that generate excessive burdens of disease in specific population groups. Systems methodology, including formal conceptual model building and computational simulations, are essential in creating such evidence.

Integrating interdisciplinary knowledge across these dimensions will provide a systematic and comprehensive understanding of the patterns of precarious employment and health, the underlying connected mechanisms generating these patterns, and the dynamics that makes them change over time. Some dimensions, like the patterns of precarious employment and health, may already be well-researched, while other dimensions such as dynamics require further investigation. We argue that it is essential to systematically explore all these dimensions to comprehensively understand a complex issue. Leaving out one of these core dimensions may leave blind spots that will render our understanding of precarious employment and health incomplete and thereby impact the efficiency of future interventions. In this editorial, we have focused on how to phrase research questions when applying a complex systems lens on precarious employment and health. This clearly needs to be matched by the integration of an interdisciplinary set of methods and data. An overview of such methods and data can be found in Rod et al (5).

Are we at the brink of a ‘complexity turn’ in public health? We believe that we are witnessing a shift in public health away from the traditional model of evidence, which primarily focused on empirically testing predefined hypotheses of single exposures and outcomes. Instead, there is a growing recognition of public health issues as complex, involving the complex interactions of biological, social, psychological, economic, and other processes across various levels and time scales (2–5, 16–20). These dynamics may show nonlinearity and adaptability. This paradigm shift is particularly important to our understanding of the relationship between work and health, including the emergent challenges outlined in the Lancet series, where contextual factors and interactions across micro-, meso- and macro-levels emerge as main drivers of dynamic change in employment condition. Formalizing this turn towards complexity in public health requires not only a realignment of our research questions as outlined for precarious employment above, but also necessitates the integration of traditional epidemiological methods with systems methodologies, such as computational simulation modeling (3, 18). Furthermore, it calls for sustained support for interdisciplinary collaboration and substantial investment in a diverse array of data types. These include multi-scale data, spatial data, time-series data, life-course data, network data, and multi-generational data, among others. This shift in our understanding of public health also impacts our approach to evidence synthesis. Traditionally, evidence synthesis has been relatively straightforward, typically summarized in systematic reviews or meta-analyses focusing on single isolated risk factors. However, with a complex systems perspective, we must transition towards a dynamic evidence synthesis framework. This approach involves an ongoing process of data-driven discoveries, hypothesis testing, and theory building. By adopting this dynamic approach, we can effectively synthesize evidence on complex research questions while continuously assessing which dimensions remain unresolved and understudied. These unresolved or understudied aspects should serve as guiding principles for future studies and research programs, also on work and health.

Funding NHR acknowledge funding from the European Union (ERC, LAYERS, project no. 101124807). The views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them.

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How can health systems approach reducing health inequalities? An in-depth qualitative case study in the UK

BACKGROUND

Addressing socioeconomic inequalities in health and healthcare, and reducing avoidable hospital admissions requires integrated strategy and complex intervention across health systems. However, the understanding of how to create effective systems to reduce socio-economic inequalities in health and healthcare is limited. The aim was to explore and develop a system's level understanding of how local areas address health inequalities with a focus on avoidable emergency admissions.

METHODS

In-depth case study using qualitative investigation (documentary analysis and key informant interviews) in an urban UK local authority. Interviewees were identified using snowball sampling. Documents were retrieved via key informants and web searches of relevant organisations. Interviews and documents were analysed independently based on a thematic analysis approach.

RESULTS

Interviews (n = 14) with wide representation from local authority (n = 8), NHS (n = 5) and voluntary, community and social enterprise (VCSE) sector (n = 1) with 75 documents (including from NHS, local authority, VCSE) were included. Cross-referenced themes were understanding the local context, facilitators of how to tackle health inequalities: the assets, and emerging risks and concerns. Addressing health inequalities in avoidable admissions per se was not often explicitly linked by either the interviews or documents and is not yet embedded into practice. However, a strong coherent strategic integrated population health management plan with a system's approach to reducing health inequalities was evident as was collective action and involving people, with links to a "strong third sector". Challenges reported include structural barriers and threats, the analysis and accessibility of data as well as ongoing pressures on the health and care system.

CONCLUSION

We provide an in-depth exploration of how a local area is working to address health and care inequalities. Key elements of this system's working include fostering strategic coherence, cross-agency working, and community-asset based approaches. Areas requiring action included data sharing challenges across organisations and analytical capacity to assist endeavours to reduce health and care inequalities. Other areas were around the resilience of the system including the recruitment and retention of the workforce. More action is required to embed reducing health inequalities in avoidable admissions explicitly in local areas with inaction risking widening the health gap.

Mapping complex public health problems with causal loop diagrams

This paper presents causal loop diagrams (CLDs) as tools for studying complex public health problems like health inequality. These problems often involve feedback loops-a characteristic of complex systems not fully integrated into mainstream epidemiology. CLDs are conceptual models that visualize connections between system variables. They are commonly developed through literature reviews or participatory methods with stakeholder groups. These diagrams often uncover feedback loops among variables across scales (e.g. biological, psychological and social), facilitating cross-disciplinary insights. We illustrate their use through a case example involving the feedback loop between sleep problems and depressive symptoms. We outline a typical step-by-step process for developing CLDs in epidemiology. These steps are defining a specific problem, identifying the key system variables involved, mapping these variables and analysing the CLD to find new insights and possible intervention targets. Throughout this process, we suggest triangulating between diverse sources of evidence, including domain knowledge, scientific literature and empirical data. CLDs can also be evaluated to guide policy changes and future research by revealing knowledge gaps. Finally, CLDs may be iteratively refined as new evidence emerges. We advocate for more widespread use of complex systems tools, like CLDs, in epidemiology to better understand and address complex public health problems.

Urban densification in the Netherlands and its impact on mental health: An expert-based causal loop diagram

Urban densification is a key strategy to accommodate rapid urban population growth, but emerging evidence suggests serious risks of urban densification for individuals' mental health. To better understand the complex pathways from urban densification to mental health, we integrated interdisciplinary expert knowledge in a causal loop diagram via group model building techniques. Six subsystems were identified: five subsystems describing mechanisms on how changes in the urban system caused by urban densification may impact mental health, and one showing how changes in mental health may alter urban densification. The new insights can help to develop resilient, healthier cities for all.

Building a Systems Map: Applying Systems Thinking to Unhealthy Commodity Industry Influence on Public Health Policy

BACKGROUND

Unhealthy commodity industries (UCIs) engage in political practices to influence public health policy, which poses barriers to protecting and promoting public health. Such influence exhibits characteristics of a complex system. Systems thinking would therefore appear to be a useful lens through which to study this phenomenon, potentially deepening our understanding of how UCI influence are interconnected with one another through their underlying political, economic and social structures. As such this study developed a qualitative systems map to depict the complex pathways through which UCIs influence public health policy and how they are interconnected with underlying structures.

METHODS

Online participatory systems mapping workshops were conducted between November 2021 and February 2022. As a starting point for the workshops, a preliminary systems map was developed based on recent research. Twenty-three online workshops were conducted with 52 geographically diverse stakeholders representing academia, civil society (CS), public office, and global governance organisations (CGO). Analysis of workshop data in NVivo and feedback from participants resulted in a final systems map.

RESULTS

The preliminary systems map consisted of 40 elements across six interdependent themes. The final systems map consisted of 64 elements across five interdependent themes, representing key pathways through which UCIs impact health policy-making: (1) direct access to public sector decision-makers; (2) creation of confusion and doubt about policy decisions; (3) corporate prioritisation of commercial profits and growth; (4) industry leveraging the legal and dispute settlement processes; and (5) industry leveraging policy-making, norms, rules, and processes.

CONCLUSION

UCI influence on public health policy is highly complex, involves interlinked practices, and is not reducible to a single point within the system. Instead, pathways to UCI influence emerge from the complex interactions between disparate national and global political, economic and social structures. These pathways provide numerous avenues for UCIs to influence public health policy, which poses challenges to formulating a singular intervention or limited set of interventions capable of effectively countering such influence. Using participatory methods, we made transparent the interconnections that could help identify interventions in future work.

Mapping food system drivers of the double burden of malnutrition using community-based system dynamics: a case study in Peru

BACKGROUND

Peru is facing a double burden of malnutrition (DBM), characterized by the co-existence of undernutrition and overnutrition. Double-duty actions that concurrently target common drivers of undernutrition and overnutrition, while ensuring no unintended side effects, are recommended to effectively address the DBM. To understand these complex common mechanisms and design context-specific double-duty actions, there is a need for participatory systems approaches. This paper provides a case study of applying a community-based system dynamics approach to capture stakeholder perspectives of food system drivers of the DBM in two regions in Peru.

METHODS

We implemented a multi-stage community-based system dynamics approach, which included processes for research capacity building for systems approaches, and the designing, piloting, and implementation of stakeholder workshops. A total of 36 stakeholders, representing diverse perspectives, participated in five group model building workshops. Stakeholder views are presented in a causal loop diagram that showcases the feedback mechanisms between key food system drivers of overweight and stunting in Peru.

RESULTS

The causal loop diagram highlights that prioritization of undernutrition over overnutrition in the policymaking process, due to Peru's historically high levels of undernutrition, may undermine action against the DBM. It also describes potential mechanisms of unintended impacts of undernutrition policies on the DBM in Peru, including impacts related to within-family distribution and quality of food provided through food assistance programs, and unintended impacts due to regional dynamics.

CONCLUSIONS

This paper highlights the importance of a participatory approach to understand local needs and priorities when recommending double-duty actions in Peru and shares practical methodological guidance on applying participatory systems approaches in public health.

Racial disparities in stroke incidence in the Women's Health Initiative: Exploring biological, behavioral, psychosocial, and social risk factors

Background

- Disparities in incident stroke risk among women by race and ethnicity persist. Few studies report the distribution and association of stroke risk factors by age group among a diverse sample of women.

Methods

- Data from the Women's Health Initiative (WHI) Observational Study collected between 1993 and 2010 were used to calculate cumulative stroke incidence and incidence rates among non-Hispanic African American (NHAA), non-Hispanic white (NHW), and Hispanic white or African American (HWAA) women by age group in participants aged ≥50 years at baseline (N = 77,247). Hazard ratios (HRs) and 95% CIs for biological, behavioral, psychosocial, and socioeconomic factors overall and by race or ethnicity were estimated using sequential Cox proportional hazard regression models.

Results

- Average follow-up time was 11.52 (SD, 3.48) years. The incident stroke rate was higher among NHAA (306 per 100,000 person-years) compared to NHW (279/100,000py) and HWAA women (147/100,000py) overall and in each age group. The disparity was largest at ages >75 years. The association between stroke risk factors (e.g., smoking, BMI, physical activity) and incident stroke varied across race and ethnicity groups. Higher social support was significantly associated with decreased stroke risk overall (HR:0.84, 95% CI, 0.76, 0.93); the degree of protection varied across race and ethnicity groups. Socioeconomic factors did not contribute additional stroke risk beyond risk conferred by traditional and psychosocial factors.

Conclusions

- The distribution and association of stroke risk factors differed between NHAA and NHW women. There is a clear need for stroke prevention strategies that address factors driving racial disparities in stroke risk.

Mapping the Dynamic Complexity of Sexual and Gender Minority Healthcare Disparities: A Systems Thinking Approach

Sexual and gender minority (SGM) populations experience extensive health disparities compared to their straight and cisgender counterparts. The importance of addressing these disparities is paramount, as SGM groups often encounter significant barriers to accessing comprehensive healthcare, including societal stigma, provider bias, and financial constraints. This study utilizes a community-based system dynamics approach to understand and visualize the barriers to and facilitators of healthcare engagement for SGM groups across their life course. It aims to identify core constructs, relationships, and dynamic feedback mechanisms related to the experiences of connection/disconnection with physical, mental, and dental healthcare of SGM individuals. Barriers to access, such as discriminatory practices and the limited availability of SGM-informed healthcare professionals, exacerbate these disparities, underscoring the urgency of developing targeted interventions. System dynamics, a complex systems science (CSS) methodology, was used for this research. Group model building sessions were conducted with diverse SGM groups, including youth, older adults, and trans and gender-expansive community members. Causal loop diagrams were developed according to an iterative process, and a meta-model of their collective experiences was created. The study revealed extensive, dynamic, and shifting structural barriers for SGM community members accessing healthcare. Societal and structural stigma, provider bias, and pathologization were identified as significant barriers throughout their life course. Community-led interventions and SGM-focused holistic healthcare were identified as critical facilitators of SGM healthcare connection. The findings highlight the need for SGM-affirming and culturally responsive healthcare settings. This paper calls for a concerted effort from SGM health researchers to use CSS in developing interventions to reduce SGM health disparities.

The current state of complex systems research on socioeconomic inequalities in health and health behavior-a systematic scoping review

BACKGROUND

Interest in applying a complex systems approach to understanding socioeconomic inequalities in health is growing, but an overview of existing research on this topic is lacking. In this systematic scoping review, we summarize the current state of the literature, identify shared drivers of multiple health and health behavior outcomes, and highlight areas ripe for future research.

METHODS

SCOPUS, Web of Science, and PubMed databases were searched in April 2023 for peer-reviewed, English-language studies in high-income OECD countries containing a conceptual systems model or simulation model of socioeconomic inequalities in health or health behavior in the adult general population. Two independent reviewers screened abstracts and full texts. Data on study aim, type of model, all model elements, and all relationships were extracted. Model elements were categorized based on the Commission on Social Determinants of Health framework, and relationships between grouped elements were visualized in a summary conceptual systems map.

RESULTS

A total of 42 publications were included; 18 only contained a simulation model, 20 only contained a conceptual model, and 4 contained both types of models. General health outcomes (e.g., health status, well-being) were modeled more often than specific outcomes like obesity. Dietary behavior and physical activity were by far the most commonly modeled health behaviors. Intermediary determinants of health (e.g., material circumstances, social cohesion) were included in nearly all models, whereas structural determinants (e.g., policies, societal values) were included in about a third of models. Using the summary conceptual systems map, we identified 15 shared drivers of socioeconomic inequalities in multiple health and health behavior outcomes.

CONCLUSIONS

The interconnectedness of socioeconomic position, multiple health and health behavior outcomes, and determinants of socioeconomic inequalities in health is clear from this review. Factors central to the complex system as it is currently understood in the literature (e.g., financial strain) may be both efficient and effective policy levers, and factors less well represented in the literature (e.g., sleep, structural determinants) may warrant more research. Our systematic, comprehensive synthesis of the literature may serve as a basis for, among other things, a complex systems framework for socioeconomic inequalities in health.

Implementation and Evaluation of a mHealth-Based Community Health Worker Feedback Loop for Hispanics with and at Risk for Diabetes

BACKGROUND

Gaps in accessibility and communication hinder diabetes care in poor communities. Combining mobile health (mHealth) and community health workers (CHWs) into models to bridge these gaps has great potential but needs evaluation.

OBJECTIVE

To evaluate a mHealth-based, Participant-CHW-Clinician feedback loop in a real-world setting.

DESIGN

Quasi-experimental feasibility study with intervention and usual care (UC) groups.

PARTICIPANTS

A total of 134 participants (n = 67/group) who were all low-income, uninsured Hispanics with or at-risk for type 2 diabetes.

INTERVENTION

A 15-month study with a weekly to semimonthly mHealth Participant-CHW-Clinician feedback loop to identify participant issues and provide participants monthly diabetes education via YouTube.

MAIN MEASURES

We used pre-defined feasibility measures to evaluate our intervention: (a) implementation, the execution of feedback loops to identify and resolve participant issues, and (b) efficacy, intended effects of the program on clinical outcomes (baseline to 15-month HbA1c, systolic blood pressure (SBP), diastolic blood pressure (DBP), and weight changes) for each group and their subgroups (at-risk; with diabetes, including uncontrolled (HbA1c ≥ 7%)).

KEY RESULTS

CHWs identified 433 participant issues (mean = 6.5 ± 5.3) and resolved 91.9% of these. Most issues were related to supplies, 26.3% (n = 114); physical health, 23.1% (n = 100); and medication access, 20.8% (n = 90). Intervention participants significantly improved HbA1c (- 0.51%, p = 0.03); UC did not (- 0.10%, p = 0.76). UC DBP worsened (1.91 mmHg, p < 0.01). Subgroup analyses revealed HbA1c improvements for uncontrolled diabetes (intervention: - 1.59%, p < 0.01; controlled: - 0.72, p = 0.03). Several variables for UC at-risk participants worsened: HbA1c (0.25%, p < 0.01), SBP (4.05 mmHg, p < 0.01), DBP (3.21 mmHg, p = 0.01). There were no other significant changes for either group.

CONCLUSIONS

A novel mHealth-based, Participant-CHW-Clinician feedback loop was associated with improved HbA1c levels and identification and resolution of participant issues. UC individuals had several areas of clinical deterioration, particularly those at-risk for diabetes, which is concerning for progression to diabetes and disease-related complications.

CLINICAL TRIAL

NCT03394456, accessed at https://clinicaltrials.gov/ct2/show/NCT03394456.

Understanding the pathway between work and health outcomes for women during the preconception, pregnancy, and postpartum periods through the framing of maternal obesity

The link between work and health outcomes for preconception, pregnant, and postpartum (PPP) working women is complex. Further, innovation and enhanced understanding are required to address the work-related determinants of maternal obesity. However, workplace health promotion is not typically systems-based nor attuned to the specific needs and context of individual PPP women. We propose that to improve health outcomes for PPP women, we must understand the pathways between paid work and health for the individual woman by taking a systems-thinking approach. In this paper, we (a) outline the rationale for why the oversimplification or "dilution" of individual context may occur; (b) present a systems-informed pathway model (the "Context-Exposure-Response" Model) and overview of potential work-related impacts on health and wellbeing outcomes for PPP women using maternal obesity to provide context examples; (c) further investigate the role of motivational factors from a systems perspective; and (d) briefly examine the implications for policy, practice, and intervention design. It is anticipated that this research may act as a starting point to assist program developers, researchers, and policymakers to adopt a systems-focused perspective while contributing to the health improvement and obesity prevention of PPP women.

Early Preventive Strategies and CNS Meningioma - Is This Feasible? A Comprehensive Review of the Literature

BACKGROUND

Meningiomas are one of the most common benign primary brain tumors; however, there is a paucity of literature on potential preventability. This comprehensive review aimed to explore the existing evidence for the potential risk factors that may contribute to meningioma development and to discuss early prevention strategies.

METHODS

Literature search was conducted via MEDLINE, Embase, Web of Science, and Cochrane Database to retrieve existing literature on various environmental exposures and lifestyle behaviors that are potential risk factors for the development of meningiomas.

RESULTS

Significant risk factors included exposure to ionizing radiation and certain environmental chemicals. Notably, this study also identified that cigarette smoking and obesity are associated with the development of meningiomas. To date, wireless phone usage, hormonal exposures, dietary factors, and traumatic brain injury remain inconclusive. Early prevention strategies should primarily be family-driven, community-based, and public health-endorsed strategies. Targeting unhealthy behaviors through healthcare organizations could execute a pivotal role in the maintenance of an optimum lifestyle, reducing the development of risk factors pertinent to meningiomas.

CONCLUSIONS

To our knowledge, this is the first study that offers a perspective on prevention of meningiomas. A causal relationship of risk factors in developing meningiomas cannot be directly established with the current evidence. We are aware of the limitations of the hypothesis, but we believe that this study will raise more awareness and our findings could potentially be endorsed by organizations promoting health across the globe. Further prospective and retrospective studies will shed more light on this topic and help establish a definitive relationship.

System dynamics modeling for cancer prevention and control: A systematic review

Cancer prevention and control requires consideration of complex interactions between multilevel factors. System dynamics modeling, which consists of diagramming and simulation approaches for understanding and managing such complexity, is being increasingly applied to cancer prevention and control, but the breadth, characteristics, and quality of these studies is not known. We searched PubMed, Scopus, APA PsycInfo, and eight peer-reviewed journals to identify cancer-related studies that used system dynamics modeling. A dual review process was used to determine eligibility. Included studies were assessed using quality criteria adapted from prior literature and mapped onto the cancer control continuum. Characteristics of studies and models were abstracted and qualitatively synthesized. 32 studies met our inclusion criteria. A mix of simulation and diagramming approaches were used to address diverse topics, including chemotherapy treatments (16%), interventions to reduce tobacco or e-cigarettes use (16%), and cancer risk from environmental contamination (13%). Models spanned all focus areas of the cancer control continuum, with treatment (44%), prevention (34%), and detection (31%) being the most common. The quality assessment of studies was low, particularly for simulation approaches. Diagramming-only studies more often used participatory approaches. Involvement of participants, description of model development processes, and proper calibration and validation of models showed the greatest room for improvement. System dynamics modeling can illustrate complex interactions and help identify potential interventions across the cancer control continuum. Prior efforts have been hampered by a lack of rigor and transparency regarding model development and testing. Supportive infrastructure for increasing awareness, accessibility, and further development of best practices of system dynamics for multidisciplinary cancer research is needed.

[Urban Epidemiology as an Integrative Approach to Sustainable and Healthy Urban Development]

Understanding the complex relationships between the physical and social environment and health in urban areas is essential for the development of appropriate measures of health promotion, disease prevention, and health protection. This article aims to characterize the comparatively new approach of urban epidemiology with its relevance for research and practice of urban health. Research in urban epidemiology provides important data and methodological foundations for integrated reporting, health impact assessments, and evaluation of interventions. Current challenges and solutions are outlined and initial recommendations for research, practice, and education and training are presented for discussion. Methods and findings of urban epidemiology can contribute in many ways to health-promoting, sustainable urban development.

Investigating health and social outcomes of the Big Local community empowerment initiative in England: a mixed method evaluation

Background

Most research on community empowerment provides evidence on engaging communities for health promotion purposes rather than attempts to create empowering conditions. This study addresses this gap.

Intervention

Big Local started in 2010 with £271M from the National Lottery. Ending in 2026, it gives 150 relatively disadvantaged communities in England control over £1M to improve their neighbourhoods.

Objective

To investigate health and social outcomes, at the population level and among engaged residents, of the community engagement approach adopted in a place-based empowerment initiative.

Study design, data sources and outcome variables

This study reports on the third wave of a longitudinal mixed-methods evaluation. Work package 1 used a difference-in-differences design to investigate the impact of Big Local on population outcomes in all 150 Big Local areas compared to matched comparator areas using secondary data. The primary outcome was anxiety; secondary outcomes included a population mental health measure and crime in the neighbourhood. Work package 2 assessed active engagement in Big Local using cross-sectional data and nested cohort data from a biannual survey of Big Local partnership members. The primary outcome was mental well-being and the secondary outcome was self-rated health. Work package 3 conducted qualitative research in 14 Big Local neighbourhoods and nationally to understand pathways to impact. Work package 4 undertook a cost-benefit analysis using the life satisfaction approach to value the benefits of Big Local, which used the work package 1 estimate of Big Local impact on life satisfaction.

Results

At a population level, the impacts on 'reporting high anxiety' (-0.8 percentage points, 95% confidence interval -2.4 to 0.7) and secondary outcomes were not statistically significant, except burglary (-0.054 change in z-score, 95% confidence interval -0.100 to -0.009). There was some effect on reduced anxiety after 2017. Areas progressing fastest had a statistically significant reduction in population mental health measure (-0.053 change in z-score, 95% confidence interval -0.103 to -0.002). Mixed results were found among engaged residents, including a significant increase in mental well-being in Big Local residents in the nested cohort in 2018, but not by 2020; this is likely to be COVID-19. More highly educated residents, and males, were more likely to report a significant improvement in mental well-being. Qualitative accounts of positive impacts on mental well-being are often related to improved social connectivity and physical/material environments. Qualitative data revealed increasing capabilities for residents' collective control. Some negative impacts were reported, with local factors sometimes undermining residents' ability to exercise collective control. Finally, on the most conservative estimate, the cost-benefit calculations generate a net benefit estimate of £64M.

Main limitations

COVID-19 impacted fieldwork and interpretation of survey data. There was a short 4-year follow-up (2016/20), no comparators in work package 2 and a lack of power to look at variations across areas.

Conclusions

Our findings suggest the need for investment to support community organisations to emerge from and work with communities. Residents should lead the prioritisation of issues and design of solutions but not necessarily lead action; rather, agencies should work as equal partners with communities to deliver change.

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research Programme (16/09/13) and will be published in full in Public Health Research; Vol. 11, No. 9. See the NIHR Journals Library website for further project information.

Socioecological determinants of child oral health-A scoping review

OBJECTIVES

Child oral health is a result of interactions between multilevel influences within a complex system. Understanding those interactions informs conceptualizing a socioecological framework of important influences on oral health. This paper aimed to present a scoping review on the determinants of dental caries and their interactions in childhood and adolescence.

METHODS

The two review questions were as follows: Which factors are determinants of child dental caries? and, How do determinants interact within and across socioecological levels? The three main electronic databases for biomedical records, PubMed, Web of Science and Scopus were searched, followed by reference check. The search and screening/selection procedures followed an a priori strategy and inclusion/exclusion criteria were specified in advance. The main components of the strategy were participants, concept and context. Following the final selection, eligible studies were assessed with quality appraisal tools for the risk of methodologic biases. Determinants reported in the included studies were then assigned to the micro-, meso-, exo- or macro-systems levels in a socioecological framework. Interactions between determinants were also identified and reported.

RESULTS

A total of 100 studies were included after removal of duplicates, screening on the title/abstracts and full-text assessment among 3313 records initially identified. A higher number of studies included were cross-sectional studies published in recent years. The majority of determinants found to influence child dental health were assigned to microsystem level within the framework. However, determinants were found at all levels and interactions were reported within and between socioecological levels. Determinants identified in the scoping review represent factors at different socioecological levels that influence child oral health.

CONCLUSION

Application of a socioecological model through a complex systems approach should lead to valid and robust progress towards practical solutions for better child oral health globally.

Systems thinking in practice when implementing a national policy program for the improvement of women's healthcare

Introduction

Interest in applying systems thinking (ST) in public health and healthcare improvement has increased in the past decade, but its practical use is still unclear. ST has been found useful in addressing the complexity and dynamics of organizations and welfare systems during periods of change. Exploring how ST is used in practice in national policy programs addressing complex and ill-structured problems can increase the knowledge of the use and eventually the usefulness of ST during complex changes. In ST, a multi-level approach is suggested to coordinate interventions over individual, organizational, and community levels, but most attempts to operationalize ST focus on the individual level. This study aimed to investigate how ST is expressed in policy programs addressing wicked problems and describe the specific action strategies used in practice in a national program in Sweden, using a new conceptual framework comprising ST principles on the organizational level as an analytical tool. The program addresses several challenges and aims to achieve systems change within women's healthcare.

Methods

The case study used a rich set of qualitative, longitudinal data on individual, group, and organizational levels, collected during the implementation of the program. Deductive content analysis provided narrative descriptions of how the ST principles were expressed in actions, based on interviews, observations, and archival data.

Results

The results showed that the program management team used various strategies and activities corresponding to organizational level ST. The team convened numerous types of actors and used collaborative approaches and many different information sources in striving to create a joint and holistic understanding of the program and its context. Visualization tools and adaptive approaches were used to support regional contact persons and staff in their development work. Efforts were made to identify high-leverage solutions to problems influencing the quality and coordination of care before, during, and after childbirth, solutions adaptable to regional conditions.

Discussion/conclusions

The organizational level ST framework was useful for identifying ST in practice in the policy program, but to increase further understanding of how ST is applied within policy programs, we suggest a multi-dimensional model to identify ST on several levels.

Systems science methods in public health: what can they contribute to our understanding of and response to the cost-of-living crisis?

BACKGROUND

Many complex public health evidence gaps cannot be fully resolved using only conventional public health methods. We aim to familiarise public health researchers with selected systems science methods that may contribute to a better understanding of complex phenomena and lead to more impactful interventions. As a case study, we choose the current cost-of-living crisis, which affects disposable income as a key structural determinant of health.

METHODS

We first outline the potential role of systems science methods for public health research more generally, then provide an overview of the complexity of the cost-of-living crisis as a specific case study. We propose how four systems science methods (soft systems, microsimulation, agent-based and system dynamics models) could be applied to provide more in-depth understanding. For each method, we illustrate its unique knowledge contributions, and set out one or more options for studies that could help inform policy and practice responses.

RESULTS

Due to its fundamental impact on the determinants of health, while limiting resources for population-level interventions, the cost-of-living crisis presents a complex public health challenge. When confronted with complexity, non-linearity, feedback loops and adaptation processes, systems methods allow a deeper understanding and forecasting of the interactions and spill-over effects common with real-world interventions and policies.

CONCLUSIONS

Systems science methods provide a rich methodological toolbox that complements our traditional public health methods. This toolbox may be particularly useful in early stages of the current cost-of-living crisis: for understanding the situation, developing solutions and sandboxing potential responses to improve population health.

Healthy home food environments of pregnant Black women are shaped by food outlet access and participation in nutrition assistance programs

OBJECTIVES

Improving access to healthy food in Black communities is imperative to combat intergenerational health disparities. Pregnant Black women represent an especially vulnerable population to multiple (and overlapping) sources of socioeconomic and political disenfranchisement and thus for whom maternal nutrition is crucial. This study aimed to (1) define household food environment types, (2) determine whether the distribution of community food outlets is associated with these household food environment types, and (3) determine whether the community-household food environment relationship differs by maternal education or participation in nutrition assistance programs.

METHODS

Cross-sectional data for pregnant Black women in North Carolina (n = 429) come from the Mothers & Others study, an obesity-prevention randomized control trial, with linked spatial data on all community food outlets (n = 6312) in the study area in 2015. Factor analysis was used to define household food environment types. These factor scores were regressed on access metrics to community food outlets. Adjusted linear regressions tested interaction by maternal education and nutrition assistance programs.

RESULTS

Four household food environment types were defined: Factor 1 (fresh fruits and vegetables (F/V), low snack), Factor 2 (canned F/V, sweet drinks), Factor 3 (dried/frozen F/V, candy), and Factor 4 (low F/V, soda). Having more convenience stores within 0.25 miles was associated with higher Factor 4 scores. No food outlets were associated with higher Factor 1 scores overall. However, SNAP or WIC participating households saw higher Factor 1 scores with increased access to supermarkets, convenience stores, and dollar stores.

CONCLUSIONS

Nutrition assistance programs play an important role as buffers against unhealthy community food environments which influence household food environments and maternal nutrition.

Increasing use of systems science in cardiovascular disease prevention to understand how to address geographic health disparities in communities with a disproportionate burden of risk

Objective

Marginalized communities shoulder a disproportionate burden of cardiovascular disease (CVD) driven by concentrated neighborhood social risk factors. We provide a case study of systems science application to address geographic CVD health disparities at the community level - informing the science of CVD health disparities research.

Methods

We conducted a two-phased, multi-methods needs assessment in the Denver, Colorado area. Phase I consisted of a social network analysis to map a two-mode network of existing CVD prevention interventions and their implementing organizations. In Phase II, group model building (GMB) sessions with key community, public health, and healthcare provider stakeholders, were utilized to identify and visualize community factors contributing to disparities in CVD risk, producing a consensus-based causal loop diagram.

Results

Between May 2021 and June 2022, we conducted 24 virtual, semi-structured interviews in Phase I to describe CVD prevention interventions, and 7 virtual GMB sessions in Phase II to describe experiences of disparities in CVD risk. For the purposes of this paper, we focus on a subset of results for both phases. In Phase I we identified 89 active CVD prevention interventions, 29 of which addressed tobacco use. In Phase II, causal loop diagrams revealed root causes of disparities in CVD risk. We provide an example of a causal loop diagram that focuses on the community prevalence of tobacco use, identifying stress as a key underlying factor driving disparities. The integration of findings from both phases highlighted the alignment and misalignment between quit tobacco intervention goals and how they are being experienced in marginalized communities.

Conclusion

Systems science methods were useful to organize a large number of CVD prevention efforts, and evaluate the root causes of CVD health disparities in a high risk community. By integrating these two aspects, interventions may be reoriented to more effectively address the root causes of CVD health disparities.

The use of participatory systems mapping as a research method in the context of non-communicable diseases and risk factors: a scoping review

CONTEXT

Participatory systems mapping is increasingly used to gain insight into the complex systems surrounding non-communicable diseases (NCDs) and their risk factors.

OBJECTIVES

To identify and synthesize studies that used participatory systems mapping in the context of non-communicable diseases.

DESIGN

Scoping review.

ELIGIBILITY CRITERIA

Peer-reviewed studies published between 2000 and 2022.

STUDY SELECTION

Studies that focused on NCDs and/or related risk factors, and included participants at any stage of their system's mapping process, were included.

CATEGORIES FOR ANALYSIS

The main categories for analysis were: (1) problem definition and goal-setting, (2) participant involvement, (3) structure of the mapping process, (4) validation of the systems map, and (5) evaluation of the mapping process.

RESULTS

We identified 57 studies that used participatory systems mapping for a variety of purposes, including to inform or evaluate policies or interventions and to identify potential leverage points within a system. The number of participants ranged from 6 to 590. While policymakers and professionals were the stakeholder groups most often included, some studies described significant added value from including marginalized communities. There was a general lack of formal evaluation in most studies. However, reported benefits related mostly to individual and group learning, whereas limitations described included a lack of concrete actions following from systems mapping exercises.

CONCLUSIONS

Based on the findings of this review, we argue that research using participatory systems mapping would benefit from considering three different but intertwined actions: explicitly considering how different participants and the power imbalances between them may influence the participatory process, considering how the results from a systems mapping exercise may effectively inform policy or translate into action, and including and reporting on evaluation and outcomes of the process, wherever possible.

Complexity in Epidemiology and Public Health. Addressing Complex Health Problems Through a Mix of Epidemiologic Methods and Data

Public health and the underlying disease processes are complex, often involving the interaction of biologic, social, psychologic, economic, and other processes that may be nonlinear and adaptive and have other features of complex systems. There is therefore a need to push the boundaries of public health beyond single-factor data analysis and expand the capacity of research methodology to tackle real-world complexities. This article sets out a way to operationalize complex systems thinking in public health, with a particular focus on how epidemiologic methods and data can contribute towards this end. Our proposed framework comprises three core dimensions-patterns, mechanisms, and dynamics-along which complex systems may be conceptualized. These dimensions cover seven key features of complex systems-emergence, interactions, nonlinearity, interference, feedback loops, adaptation, and evolution. We relate this framework to examples of methods and data traditionally used in epidemiology. We conclude that systematic production of knowledge on complex health issues may benefit from: formulation of research questions and programs in terms of the core dimensions we identify, as a comprehensive way to capture crucial features of complex systems; integration of traditional epidemiologic methods with systems methodology such as computational simulation modeling; interdisciplinary work; and continued investment in a wide range of data types. We believe that the proposed framework can support the systematic production of knowledge on complex health problems, with the use of epidemiology and other disciplines. This will help us understand emergent health phenomena, identify vulnerable population groups, and detect leverage points for promoting public health.

Guidance on the use of complex systems models for economic evaluations of public health interventions

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Putting the system in systemic racism: A systems thinking approach to advancing equity

Generations of scholars and activists have argued that racial inequities emerge not only because of racist ideologies but also from a hierarchical system of racial oppression. This theoretical tradition has highlighted numerous ways in which systemic racism manifests itself, from racist policies to differential access to material conditions and power. However, given that by definition systemic racism is focused on systems, theories of systemic racism would be more comprehensive and actionable by drawing on scholarship related to systems thinking. Systems thinking is a conceptual orientation that aims to understand how different types of systems function over time. This paper builds on the work of previous scholars to propose a systems thinking approach to understand and strategically disrupt racist systems. We provide a typology of system characteristics (organized into the categories of paradigms, structures, elements, and feedback loops) that together can be used to help understand the operation of systemic racism in different system contexts. The paper also provides an approach to identify and strategically target multiple system leverage points to simultaneously disrupt the status quo of racial inequity and promote the emergence of conditions enabling racial equity. This systems thinking approach can be used to guide learning and action within an ongoing process of antiracist praxis.

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.

TRIPLE C reporting principles for case study evaluations of the role of context in complex interventions

BACKGROUND

Guidance and reporting principles such as CONSORT (for randomised trials) and PRISMA (for systematic reviews) have greatly improved the reporting, discoverability, transparency and consistency of published research. We sought to develop similar guidance for case study evaluations undertaken to explore the influence of context on the processes and outcomes of complex interventions.

METHODS

A range of experts were recruited to an online Delphi panel, sampling for maximum diversity in disciplines (e.g. public health, health services research, organisational studies), settings (e.g. country), and sectors (e.g. academic, policy, third sector). To inform panel deliberations, we prepared background materials based on: [a] a systematic meta-narrative review of empirical and methodological literatures on case study, context and complex interventions; [b] the collective experience of a network of health systems and public health researchers; and [c] the established RAMESES II standards (which cover one kind of case study). We developed a list of topics and issues based on these sources and encouraged panel members to provide free text comments. Their feedback informed development of a set of items in the form of questions for potential inclusion in the reporting principles. We circulated these by email, asking panel members to rank each potential item twice (for relevance and validity) on a 7-point Likert scale. This sequence was repeated twice.

RESULTS

We recruited 51 panel members from 50 organisations across 12 countries, who brought experience of a range of case study research methods and applications. 26 completed all three Delphi rounds, reaching over 80% consensus on 16 items covering title, abstract, definitions of terms, philosophical assumptions, research question(s), rationale, how context and complexity relates to the intervention, ethical approval, empirical methods, findings, use of theory, generalisability and transferability, researcher perspective and influence, conclusions and recommendations, and funding and conflicts of interest.

CONCLUSION

The 'Triple C' (Case study, Context, Complex interventions) reporting principles recognise that case studies are undertaken in different ways for different purposes and based on different philosophical assumptions. They are designed to be enabling rather than prescriptive, and to make case study evaluation reporting on context and complex health interventions more comprehensive, accessible and useable.

Relationship between characteristics of large national regions and individual alcohol consumption: a scoping review

OBJECTIVE

The goal of our article was to systematise studies that investigated the impact of living conditions in large national regions on individual alcohol consumption.

METHODS

The objectives of the scoping review, the criteria and methods for selecting articles were defined in advance and recorded in the protocol PROSPERO CRD42021234874. We sought publications on the research topic in PubMed, Google Scholar, OpenGrey, Crossref and eLibrary databases from the moment they were created until December 31, 2021. The final sample included 81 publications.

RESULTS

The majority of ultimately selected papers were published after 2010 (62 articles), represented the USA (68 articles), and considered samples of children and youths, either the younger population or the general adult population (65 articles). High quality was characteristic for 19 studies, whereas satisfactory quality was exhibited by 46 publications. The most consistent associations with individual alcohol consumption were revealed for the legislative environment (especially for integral scales and indices), alcohol pricing policy, the prevalence of alcohol consumption and binge drinking in the population, and unemployment rate.

CONCLUSION

The review made it possible to systematise the results of studies on the impact of the characteristics of large national regions on alcohol consumption, including a description of these characteristics and results, samples and designs of studies, their quality, as well as to summarise the results of these studies.

The Application of Systems Thinking to the Prevention and Control of Sexually Transmissible Infections among Adolescents and Adults: A Scoping Review

Systems thinking is a mechanism for making sense of complex systems that challenge linear explanations of cause-and-effect. While the prevention and control of sexually transmissible infections (STIs) has been identified as an area that may benefit from systems-level analyses, no review on the subject currently exists. The aim of this study is to conduct a scoping review to identify literature in which systems thinking has been applied to the prevention and control of STIs among adolescent and adult populations. Joanna Briggs Institute guidelines for the conduct of scoping reviews were followed. Five databases were searched for English-language studies published after 2011. A total of n = 6102 studies were screened against inclusion criteria and n = 70 were included in the review. The majority of studies (n = 34) were conducted in African nations. Few studies focused on priority sub-populations, and 93% were focused on HIV (n = 65). The most commonly applied systems thinking method was system dynamics modelling (n = 28). The review highlights areas for future research, including the need for more STI systems thinking studies focused on: (1) migrant and Indigenous populations; (2) conditions such as syphilis; and (3) innovations such as pre-exposure prophylaxis and at-home testing for HIV. The need for conceptual clarity around 'systems thinking' is also highlighted.

Understanding how to create healthier places: A qualitative study exploring the complex system of urban development decision-making

Tackling complex system challenges like creating healthy environments requires understanding priorities and structures affecting multiple actors. This qualitative study, involving 132 multi-sectoral stakeholders spanning the urban development decision-making system, explores how to influence healthier place-making. Using thematic analysis we develop themes around competing stakeholder priorities; structural 'rules' and influential relationships; and justifying a focus on health, requiring greater clarity and consensus around definitions of 'healthy' urban development. Building on the socio-ecological model we highlight how a multi-faceted approach is required for change at multiple levels in the complex system to target individual actor motivations, organisational priorities and structural 'rules'.

Development of the Systems Thinking for Health Actions framework: a literature review and a case study

BACKGROUND

Systems thinking is an approach that views systems with a holistic lens, focusing on how components of systems are interconnected. Specifically, the application of systems thinking has proven to be beneficial when applied to health systems. Although there is plenty of theory surrounding systems thinking, there is a gap between the theoretical use of systems thinking and its actual application to tackle health challenges. This study aimed to create a framework to expose systems thinking characteristics in the design and implementation of actions to improve health.

METHODS

A systematised literature review was conducted and a Taxonomy of Systems Thinking Objectives was adapted to develop the new 'Systems Thinking for Health Actions' (STHA) framework. The applicability of the framework was tested using the COVID-19 response in Pakistan as a case study.

RESULTS

The framework identifies six key characteristics of systems thinking: (1) recognising and understanding interconnections and system structure, (2) identifying and understanding feedback, (3) identifying leverage points, (4) understanding dynamic behaviour, (5) using mental models to suggest possible solutions to a problem and (6) creating simulation models to test policies. The STHA framework proved beneficial in identifying systems thinking characteristics in the COVID-19 national health response in Pakistan.

CONCLUSION

The proposed framework can provide support for those aiming to applying systems thinking while developing and implementing health actions. We also envision this framework as a retrospective tool that can help assess if systems thinking was applied in health actions.

Promoting the health of vulnerable populations: Three steps towards a systems-based re-orientation of public health intervention research

This paper proposes a novel framework for the development of interventions in vulnerable populations. The framework combines a complex systems lens with syndemic theory. Whereas funding bodies, research organizations and reporting guidelines tend to encourage intervention research that (i) focuses on singular and predefined health outcomes, (ii) searches for generalizable cause-effect relationships, and (iii) aims to identify universally effective interventions, the paper suggests that a different direction is needed for addressing health inequities: We need to (i) start with exploratory analysis of population-level data, and (ii) invest in contextualized in-depth knowledge of the complex dynamics that produce health inequities in specific populations and settings, while we (iii) work with stakeholders at multiple levels to create change within systems.

How to not revert to type: Complexity-informed learnings from the pandemic response for health system reform and universal access to integrated care

This article is part of the Research Topic 'Health Systems Recovery in the Context of COVID-19 and Protracted Conflict'.

Background

COVID-19 has highlighted existing health inequalities and health system deficiencies both in Ireland and internationally; however, understanding of the critical opportunities for health system change that have arisen during the pandemic is still emerging and largely descriptive. This research is situated in the Irish health reform context of Sláintecare, the reform programme which aims to deliver universal healthcare by strengthening public health, primary and community healthcare functions as well as tackling system and societal health inequities.

Aims and objectives

This study set out to advance understanding of how and to what extent COVID-19 has highlighted opportunities for change that enabled better access to universal, integrated care in Ireland, with a view to informing universal health system reform and implementation.

Methods

The study, which is qualitative, was underpinned by a co-production approach with Irish health system leadership. Semi-structured interviews were conducted with sixteen health system professionals (including managers and frontline workers) from a range of responses to explore their experiences and interpretations of social processes of change that enabled (or hindered) better access to universal integrated care during the pandemic. A complexity-informed approach was mobilized to theorize the processes that impacted on access to universal, integrated care in Ireland in the COVID-19 context.

Findings

A range of circumstances, strategies and mechanisms that created favorable system conditions in which new integrated care trajectories emerged during the crisis. Three key learnings from the pandemic response are presented: (1) nurturing whole-system thinking through a clear, common goal and shared information base; (2) harnessing, sharing and supporting innovation; and (3) prioritizing trust and relationship-building in a social, human-centered health system. Policy and practice implications for health reform are discussed.

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.