Understanding social forces involved in diabetes outcomes: a systems science approach to quality-of-life research

Lounsbury, David W.; Hirsch, Gary B.; Vega, Chawntel; Schwartz, Carolyn E.

doi:10.1007/s11136-013-0532-4

Cited by 23 publications

(21 citation statements)

References 96 publications

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“…These diagrams are for illustration only and actual application of them to the real world would require further testing and iteration [32]. While system dynamics methods have been used to study tobacco control [21,22,[39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56] and even to inform implementation of evidence into practice broadly [21], this is the first attempt to apply the method to illustrate dynamic complexity and efforts within each translational stage.…”

Section: Methods: Diagramming Complex Systems Problems Using System Dmentioning

confidence: 99%

Translating research into prevention of high-risk behaviors in the presence of complex systems: definitions and systems frameworks

Lich

Frerichs

Fishbein

et al. 2016

Behav. Med. Pract. Policy Res.

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To impact population health, it is critical to collaborate across disciplinary and practice-based silos and integrate resources, experiences, and knowledge to exert positive change. Complex systems shape both the prevention outcomes researchers, practitioners, and policymakers seek to impact and how research is translated and can either impede or support movement from basic scientific discovery to impactful and scaled-up prevention practice. Systems science methods can be used to facilitate designing translation support that is grounded in a richer understanding of the many interacting forces affecting prevention outcomes across contexts. In this paper, we illustrate how one systems science method, system dynamics, could be used to advance research, practice, and policy initiatives in each stage of translation from discovery to translation of innovation into global communities (T0-T5), with tobacco prevention as an example. System dynamics can be applied to each translational stage to integrate disciplinary knowledge and document testable hypotheses to inform translation research and practice.

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Section: Methods: Diagramming Complex Systems Problems Using System Dmentioning

confidence: 99%

Translating research into prevention of high-risk behaviors in the presence of complex systems: definitions and systems frameworks

Lich

Frerichs

Fishbein

et al. 2016

Behav. Med. Pract. Policy Res.

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“…A frequently cited priority is for nutrition science to adopt a systems approach, which is needed to deal with the complexity of interacting factors that are inevitably brought into focus in interdisciplinary science (1,49,54). This is all the more apparent considering the high degree of complexity even within the boundaries of conventional nutrition science, due in part to the large number of nutrients, foods, diets, and dietary patterns that constitute human nutrition (1).…”

Section: The Need For Systems Sciencementioning

confidence: 99%

Nutritional Ecology and Human Health

2016

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In contrast to the spectacular advances in the first half of the twentieth century with micronutrient-related diseases, human nutrition science has failed to stem the more recent rise of obesity and associated cardiometabolic disease (OACD). This failure has triggered debate on the problems and limitations of the field and what change is needed to address these. We briefly review the two broad historical phases of human nutrition science and then provide an overview of the main problems that have been implicated in the poor progress of the field with solving OACD. We next introduce the field of nutritional ecology and show how its ecological-evolutionary foundations can enrich human nutrition science by providing the theory to help address its limitations. We end by introducing a modeling approach from nutritional ecology, termed nutritional geometry, and demonstrate how it can help to implement ecological and evolutionary theory in human nutrition to provide new direction and to better understand and manage OACD.

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“…While human behaviors are complex and cannot be predicted with certainty, tools such as SD can elucidate tendencies and patterns of expected behavior, based on evidence. SD modeling has been used to explore interrelated health and behavioral problems in the past (e.g., Miller et al 2011;Lounsbury et al 2014). However, we are not aware of another SD modeling project used to display syndemic risk, as we have defined it, prior to this project.…”

Section: Introductionmentioning

confidence: 99%

A Social Ecological Model of Syndemic Risk affecting Women with and At‐Risk for HIV in Impoverished Urban Communities

Batchelder

Gonzalez

Palma

et al. 2015

American J of Comm Psychol

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Syndemic risk is an ecological construct, defined by co-occurring interdependent socio-environmental, interpersonal and intrapersonal determinants. We posited syndemic risk to be a function of violence, substance use, perceived financial hardship, emotional distress and self-worth among women with and at-risk for HIV in an impoverished urban community. In order to better understand these interrelationships, we developed and validated a system dynamics (SD) model based upon peer-reviewed literature; secondary data analyses of a cohort dataset including women living with and at-risk of HIV in Bronx, NY (N = 620); and input from a Bronx-based community advisory board. Simulated model output revealed divergent levels and patterns of syndemic risk over time across different sample profiles. Outputs generated new insights about how to effectively explore multicomponent multi-level programs in order to strategically develop more effective services for this population. Specifically, the model indicated that effective multi-level interventions might bolster women's resilience by increasing self-worth, which may result in decreased perceived financial hardship and risk of violence. Overall, our stakeholder-informed model depicts how self-worth may be a major driver of vulnerability and a meaningful addition to syndemic theory affecting this population.

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Understanding social forces involved in diabetes outcomes: a systems science approach to quality-of-life research

Abstract: The policy implications of the causal loop diagrams are discussed, and empirical next steps to validate the diagrams and quantify the relationships are described.

Cited by 23 publications

References 96 publications

Translating research into prevention of high-risk behaviors in the presence of complex systems: definitions and systems frameworks

Translating research into prevention of high-risk behaviors in the presence of complex systems: definitions and systems frameworks

Nutritional Ecology and Human Health

A Social Ecological Model of Syndemic Risk affecting Women with and At‐Risk for HIV in Impoverished Urban Communities

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