System Dynamics Modeling for Traumatic Brain Injury: Mini-review of Applications

Traumatic brain injury (TBI) is a highly complex phenomenon involving a cascade of disruptions across biomechanical, neurochemical, neurological, cognitive, emotional, and social systems. Researchers and clinicians urgently need a rigorous conceptualization of brain injury that encompasses nonlinear and mutually causal relations among the factors involved, as well as sources of individual variation in recovery trajectories. System dynamics, an approach from systems science, has been used for decades in fields such as management and ecology to model nonlinear feedback dynamics in complex systems. In this mini-review, we summarize some recent uses of this approach to better understand acute injury mechanisms, recovery dynamics, and care delivery for TBI. We conclude that diagram-based approaches like causal-loop diagramming have the potential to support the development of a shared paradigm of TBI that incorporates social support aspects of recovery. When developed using adequate data from large-scale studies, simulation modeling presents opportunities for improving individualized treatment and care delivery

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

Mapping Mental Models Through an Improved Method for Identifying Causal Structures in Qualitative Data

Qualitative data are commonly used in the development of system dynamicsmodels, but methods for systematically identifying causal structures in qualita-tive data have not been widely established. This article presents a modifiedprocess for identifying causal structures (e.g., feedback loops) that are commu-nicated implicitly or explicitly and utilizes software to make coding, tracking,and model rendering more efficient. This approach draws from existingmethods, system dynamics best practice, and qualitative data analysis tech-niques. Steps of this method are presented along with a description of causalstructures for an audience new to system dynamics. The method is applied to aset of interviews describing mental models of clinical practice transformationfrom an implementation study of screening and treatment for unhealthy alco-hol use in primary care. This approach has the potential to increase rigour andtransparency in the use of qualitative data for model building and to broadenthe user base for causal-loop diagramming

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Using Systems Methods to Create a Dynamic Model of Concussion Recovery

Presented at the 2016 American Association of Neurological Surgeons Annual Scientific Meeting, Chicago, IL

Constructing a Dynamic Model of Concussion

Aim: To construct a causal-loop diagram and corresponding system dynamics model of concussion pathology and recovery at the individual scale. These models will contribute to a greater understanding of the factors involved in concussion recovery and will inform the development of a new classification system for traumatic brain injury

Diverse Autonomic Nervous System Stress Response Patterns in Childhood Sensory Modulation

The specific role of the autonomic nervous system (ANS) in emotional and behavioral regulation—particularly in relation to automatic processes—has gained increased attention in the sensory modulation literature. This mini-review article summarizes current knowledge about the role of the ANS in sensory modulation, with a focus on the integrated functions of the ANS and the hypothalamic-pituitary-adrenal (HPA) axis and their measurement. Research from the past decade illustrates that sympathetic and parasympathetic interactions are more complex than previously assumed. Patterns of ANS activation vary across individuals, with distinct physiological response profiles influencing the reactivity underlying automatic behavioral responses. This review article advances a deeper understanding of stress and the complex stress patterns within the ANS and HPA axis that contribute to allostatic load (AL). We argue that using multiple physiological measurements to capture individual ANS response variation is critical for effectively treating children with sensory modulation disorder (SMD) and sensory differences.We consider the relative contributions of automatic vs. deliberately controlled processes across large-scale neural networks in the development of sensorimotor function and their associated links with arousal patterns and sensory over- and under-responsivity

Concussion As a Multi-Scale Complex System: An Interdisciplinary Synthesis of Current Knowledge

Traumatic brain injury (TBI) has been called “the most complicated disease of the most complex organ of the body” and is an increasingly high-profile public health issue. Many patients report long-term impairments following even “mild” injuries, but reliable criteria for diagnosis and prognosis are lacking. Every clinical trial for TBI treatment to date has failed to demonstrate reliable and safe improvement in outcomes, and the existing body of literature is insufficient to support the creation of a new classification system. Concussion, or mild TBI, is a highly heterogeneous phenomenon, and numerous factors interact dynamically to influence an individual’s recovery trajectory. Many of the obstacles faced in research and clinical practice related to TBI and concussion, including observed heterogeneity, arguably stem from the complexity of the condition itself. To improve understanding of this complexity, we review the current state of research through the lens provided by the interdisciplinary field of systems science, which has been increasingly applied to biomedical issues. The review was conducted iteratively, through multiple phases of literature review, expert interviews, and systems diagramming and represents the first phase in an effort to develop systems models of concussion. The primary focus of this work was to examine concepts and ways of thinking about concussion that currently impede research design and block advancements in care of TBI. Results are presented in the form of a multi-scale conceptual framework intended to synthesize knowledge across disciplines, improve research design, and provide a broader, multi-scale model for understanding concussion pathophysiology, classification, and treatment

The Dynamics of Concussion: Mapping Pathophysiology, Persistence, and Recovery with Causal-loop Diagramming

Concussion, also known as mild traumatic brain injury (mTBI),1 is a significant public health issue responsible for a variety of cognitive, emotional, and somatic symptoms and deficits (3). It is unclear why some individuals appear to recover relatively quickly while others suffer prolonged symptoms and impairments (4–7). Robust clinical means of diagnosis, prognosis, and treatment are also lacking (8–11). Research is hindered by an inadequate classification system for traumatic brain injury (TBI) (12), “poor” study quality (13, 14), disagreement about appropriate inclusion and exclusion criteria for concussion (8, 15), and an incomplete understanding of underlying pathophysiology (16–18). The heterogeneity and complexity seen in concussion further complicate research, particularly efforts to individualize treatment (19–22)

A Systems Thinking Approach for Eliciting Mental Models from Visual Boundary Objects in Hydropolitical Contexts: a Case Study from the Pilcomayo River Basin

Transboundary collaborations related to international freshwater are critical for ensuring equitable, efficient, and sustainable shared access to our planet’s most fundamental resources. Visual artifacts, such as knowledge maps, functioning as boundary objects, are used in hydropolitical contexts to convey understandings and facilitate discussion across scales about challenges and opportunities from multiple perspectives. Such focal points for discussion are valuable in creating shared, socially negotiated priorities and integrating diverse and often disparate cultural perspectives that naturally exist in the context of international transboundary water resources. Visual boundary objects can also represent the collective mental models of the actor countries and transboundary institutions and encompass their perspectives on the complex hydro-social cycles within specific “problem-shed” regions of the shared resources. To investigate and synthesize these multiple concepts, we developed a novel method of eliciting mental models from visual boundary objects in social-ecological contexts by combining content analysis with theoretical frameworks for boundary objects and systems thinking. Using this method, we analyzed visual boundary objects represented in publicly available documents formally related to decision making in the Pilcomayo River Basin in South America. The Pilcomayo River Basin is a unique case for investigating decision making in international collaboration among represented states, given the unique social and biophysical challenges that have plagued the region for over a century. Using our framework, we were able to develop insight into the collective mental models of stakeholders, organizations, and decision-making institutions, related to priorities, vulnerabilities, and adaptation strategies among the various socioeconomic, cultural, political, and biophysical drivers for different regions and scales of the basin