Using qualitative system dynamics modeling to understand overdose bystander behavior in the context of Connecticut's Good Samaritan Laws and identify effective policy options

BACKGROUND

Good Samaritan Laws are a harm reduction policy intended to facilitate a reduction in fatal opioid overdoses by enabling bystanders, first responders, and health care providers to assist individuals experiencing an overdose without facing civil or criminal liability. However, Good Samaritan Laws may not be reaching their full impact in many communities due to a lack of knowledge of protections under these laws, distrust in law enforcement, and fear of legal consequences among potential bystanders. The purpose of this study was to develop a systems-level understanding of the factors influencing bystander responses to opioid overdose in the context of Connecticut's Good Samaritan Laws and identify high-leverage policies for improving opioid-related outcomes and implementation of these laws in Connecticut (CT).

METHODS

We conducted six group model building (GMB) workshops that engaged a diverse set of participants with medical and community expertise and lived bystander experience. Through an iterative, stakeholder-engaged process, we developed, refined, and validated a qualitative system dynamics (SD) model in the form of a causal loop diagram (CLD).

RESULTS

Our resulting qualitative SD model captures our GMB participants' collective understanding of the dynamics driving bystander behavior and other factors influencing the effectiveness of Good Samaritan Laws in the state of CT. In this model, we identified seven balancing (B) and eight reinforcing (R) feedback loops within four narrative domains: Narrative 1 - Overdose, Calling 911, and First Responder Burnout; Narrative 2 - Naloxone Use, Acceptability, and Linking Patients to Services; Narrative 3 - Drug Arrests, Belief in Good Samaritan Laws, and Community Trust in Police; and Narrative 4 - Bystander Naloxone Use, Community Participation in Harm Reduction, and Cultural Change Towards Carrying Naloxone.

CONCLUSIONS

Our qualitative SD model brings a nuanced systems perspective to the literature on bystander behavior in the context of Good Samaritan Laws. Our model, grounded in local knowledge and experience, shows how the hypothesized non-linear interdependencies of the social, structural, and policy determinants of bystander behavior collectively form endogenous feedback loops that can be leveraged to design policies to advance and sustain systems change.

Prevention Adaptation of an Evidence-Based Treatment for Parents Involved With Child Welfare Who Use Substances

Background: Parental substance use, especially opioid misuse and/or methamphetamine use, is a key driver for recent increases in family involvement with child welfare and foster care placements in the United States. There is an urgent need for programs that prevent parental substance use disorders, yet few prevention programs exist that target parents' unique needs and strengths. Adapting evidence-based treatment approaches for prevention might be an efficient, effective way to address this gap. The current study informed the rigorous adaptation of an evidence-based treatment that supports families involved with child welfare due to substance use, Families Actively Improving Relationships (FAIR), to a prevention-oriented intervention: "PRE-FAIR." FAIR entails four treatment domains: substance use, parenting, mental health, and ancillary services (e.g., housing, medical care, and food). FAIR significantly improved parenting and reduced parental substance use in three rigorous treatment trials, but FAIR's effectiveness in preventing the initiation or escalation of opioid misuse and/or methamphetamine use is untested. To inform adaptation, particular attention was paid to operationalizing strategies underlying a key hypothesized mediator of successful parent outcomes-engagement. Methods: Graduated FAIR parents (n = 9) and FAIR administrators, clinical supervisors, and clinicians (n = 11) participated in semi-structured interviews. Content analysis was used to identify key variables driving FAIR engagement and parent outcomes. Causal loop diagramming, a qualitative systems science method, was employed to operationalize emergent themes, and describe how causal links between key variables interrelated dynamically over time. Results: Themes reinforced the value of FAIR's treatment domains for supporting parent's sobriety and parenting skills within a prevention orientation. Ancillary supports and strong relationships were particularly crucial for helping parents cope with stressors leading to substance use. Five engagement strategies were identified as essential to parent success: 24/7 clinician availability, in-person clinician advocacy, in-home delivery, strengths-based interactions, and urinalysis. Implications for PRE-FAIR engagement strategies and dosage were identified. Discussion: Traditional qualitative analyses and qualitative analyses based in systems science can inform rigorous adaptations of evidence-based treatment programs for prevention. Future research will explore additional required, fidelity-consistent prevention adaptations to FAIR, and the impact of PRE-FAIR on parental substance use and child welfare case outcomes.

Grandmothers - a neglected family resource for saving newborn lives

Across the globe, the well-being of newborns is significantly influenced by the knowledge and practices of family members, yet global health policies and interventions primarily focus on strengthening health services to save newborn lives. Predominant approaches to promote newborn survival in non-western cultures across the Global South are based on a western, nuclear family model and ignore the roles of caregivers within wider family systems, whose attitudes and practices are determined by culturally prescribed strategies. In this paper, I review evidence of a neglected facet of newborn care, the role and influence of senior women or grandmothers.Based on a family systems frame, I reviewed research from numerous settings in Africa, Asia and Latin America that provides insight into family roles related to newborn care, specifically of grandmothers. I identified primarily published studies which provide evidence of grandmothers' role as culturally designated and influential newborn advisors to young mothers and direct caregivers. Research from all three continents reveals that grandmothers play similar core roles in newborn care while their culturally specific practices vary. This review supports two main conclusions. First, future newborn research should be conceptualised within a family systems framework that reflects the structure and dynamics of non-western collectivist cultures. Second, newborn interventions should aim not only to strengthen health services but also influential family caregivers, particularly grandmothers and the indigenous social support networks of which they are a part, in order to improve family-level newborn practices and save newborn lives.

Complex Systems Model of Dynamic Mechanisms of Early Childhood Caries Development

Early childhood caries (ECC) is a largely preventable condition that occurs when children develop caries in their primary teeth before the age of six. National trends of ECC indicate that prevalence is decreasing, but disparities between various sociodemographic groups may be increasing, despite intervention efforts. Dynamic mechanisms in caries development are hypothesized to be responsible for the observed population distributions of disease. Agent-based models (ABMs) have been utilized to explore similar hypotheses in many areas of health research. Therefore, we developed an ABM of ECC development mechanisms and examined population outcomes of hypothetical preventive intervention scenarios. We found that risk-based targeting had minimal impact on population averages or disparities and was largely due to the strength of the dynamic mechanisms among those considered to be at high caries risk. Universally increasing intervention access reduced population caries prevalence, but increased disparities between different groups of caries risk profiles. We show that population distributions of ECC can emerge as a result of dynamic mechanisms that have been shown to drive disease development. Understanding the effectiveness of a proposed intervention in relation to the hypothesized mechanism(s) that contributes to the outcome of interest is critical to future efforts to address population disparities in ECC.

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

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

Building a systems thinking prevention workforce

ISSUE ADDRESSED

Healthy Together Victoria (HTV) was a large-scale intervention that adopted a systems approach to prevention. It established the capability of an inexperienced workforce by cultivating their understanding of systems theories, tools and practice. This paper explores how this capacity was developed and what helped and hindered the process.

METHODS

This qualitative research included 31 primary semi-structured interviews that focused on participants' understanding of systems thinking. Deductive thematic analysis was undertaken. A workforce development framework informed the coding that was used to create a causal loop diagram.

RESULTS

The findings display the multiple influencers on capacity-building. Practice change was enabled with training-although it lacked coordination and participation was limited. Yet, the systems approach was strengthened with governance arrangements, policies, funding, team support and leadership that empowered practitioners to trial systems methods. Capacity-building was hindered by HTV's unspecified theory that made it harder for novice practitioners to grasp. Funding cuts due to political changes reduced the initiative's duration and prompted resignations, causing the newfound experience to exit the workforce.

CONCLUSION

Capacity-building for systems practice requires a holistic approach of simultaneous, complimentary actions that address the individual and environmental influences of workforce development, especially the drivers of organisational culture that facilitate new practice. SO WHAT?: Effective training methods should specifically teach skills and knowledge that help practitioners to implement systems thinking. The workforce development requirements of other contributors also need to be considered, in addition to the policies, opportunities and resources that embed practice change.

Developing a Systems Mindset in Community-Based Prevention

Background. A systems mindset is the ability to see problems in their wider context and in terms of their underlying structure. This research describes how a systems mindset was understood and applied by prevention practitioners in a large-scale community-based initiative that employed a systems thinking approach. Method. This qualitative research included 31 primary semistructured interviews. Deductive thematic analysis was based on Braun and Clarke's analysis framework and was guided by Senge and Scharmer's knowledge-creating system. Results. The practitioners had been introduced to systems theory and were aware of complex problems and the need for equally sophisticated solutions. Their knowledge was not in-depth, although this may be adequate, as a theoretical overview seemed to be sufficient to support practice. A range of tools was available to practitioners to guide their systems mindset; however, none were preferred. Practitioners' awareness of the tools varied, as did their feelings toward them as some found them helpful and others did not. A narrower focus on tools could have benefited those who had not yet grasped systems theory. The use of projects within a systems approach confused some practitioners, yet others saw them as platforms to leverage change from. Implications for practice. With a systems mindset practitioners are able to develop systemic solutions to difficult problems. To do this, they require an overview of complex adaptive systems theory, an applied understanding of systems tools, and an experiential learning opportunity to shift their knowledge into practical know-how.

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

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

Participatory System Dynamics Modeling: Increasing Stakeholder Engagement and Precision to Improve Implementation Planning in Systems

Implementation planning typically incorporates stakeholder input. Quality improvement efforts provide data-based feedback regarding progress. Participatory system dynamics modeling (PSD) triangulates stakeholder expertise, data and simulation of implementation plans prior to attempting change. Frontline staff in one VA outpatient mental health system used PSD to examine policy and procedural "mechanisms" they believe underlie local capacity to implement evidence-based psychotherapies (EBPs) for PTSD and depression. We piloted the PSD process, simulating implementation plans to improve EBP reach. Findings indicate PSD is a feasible, useful strategy for building stakeholder consensus, and may save time and effort as compared to trial-and-error EBP implementation planning.

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

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

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Nutrition and the science of disease prevention: a systems approach to support metabolic health

Progress in nutritional science, genetics, computer science, and behavioral economics can be leveraged to address the challenge of noncommunicable disease. This report highlights the connection between nutrition and the complex science of preventing disease and discusses the promotion of optimal metabolic health, building on input from several complementary disciplines. The discussion focuses on (1) the basic science of optimal metabolic health, including data from gene-diet interactions, microbiome, and epidemiological research in nutrition, with the goal of defining better targets and interventions, and (2) how nutrition, from pharma to lifestyle, can build on systems science to address complex issues.

Synthesizing Marketing, Community Engagement, and Systems Science Approaches for Advancing Translational Research

The adoption and implementation of evidence-based interventions (EBIs) are the goals of translational research; however, potential end-users' perceptions of an EBI value have contributed to low rates of adoption. In this article, we describe our application of emerging dissemination and implementation science theoretical perspectives, community engagement, and systems science principles to develop a novel EBI dissemination approach. Using consumer-driven, graphics-rich simulation, the approach demonstrates predicted implementation effects on health and employment outcomes for socioeconomically disadvantaged women at the local level and is designed to increase adoption interest of county program managers accountable for improving these outcomes in their communities.