Ongoing Seed Funding Projects

Principal Investigator(s)

• Simiao Niu, School of Engineering, Biomedical Engineering
• Yanping Jiang, Institute for Health, Family Medicine and Community Health
• Yen-Tyng Chen, Edward J. Bloustein School of School of Planning and Public Policy, Public Health

Chronic psychological stress is a leading but often overlooked contributor to health problems such as cardiovascular disease, depression, addiction, and substance use disorders, disproportionately affecting underserved populations. Current stress assessments rely primarily on subjective self-reports, which are limited by recall bias and lack real-time insight into the body's physiological state. This project aims to develop a wearable, non-invasive patch that continuously monitors three key physiological stress biomarkers: skin impedance, heart rate variability, and sweat cortisol. By integrating these multimodal signals and applying machine learning algorithms, the patch will provide personalized, real-time stress scores. To validate this system, we will conduct a pilot study using a standardized laboratory stress test (Trier Social Stress Test) in a diverse sample of college students. Gold-standard biological and psychological measures will be used to assess the accuracy of the patch. Our goal is to establish a clinically relevant and equitable tool for early stress detection and personalized intervention. This innovation holds promise not only for improving behavioral health outcomes but also for reducing disparities in stress-related disease burden and expanding applications to chronic disease management and mental health monitoring.

Principal Investigator(s)

• Andrea Spaeth, School of Arts and Sciences, Kinesiology and Health
• Susan Shapses, School of Environmental and Biological Sciences, Nutritional Sciences

Approximately 70% of older adults report having problems with their sleep, and those with overweight/obesity are at increased risk. Sleep disturbances reduce quality of life, impair daily functioning, and increase risk for chronic disease. Thus, interventions are urgently needed to improve sleep in older adults with overweight/obesity. Weight loss interventions have shown promise for improving sleep and calorie restriction is the most common behavioral intervention for weight loss. During calorie restriction, it is important to consider diet composition as certain nutrients have been associated with good sleep quality (i.e., unsaturated fat, protein and fiber) whereas others have been associated with sleep disturbances (i.e., saturated fat, added sugars). This is the first study to examine if weight loss improves sleep health in older adults (50-75 years old) with overweight/obesity and determine if having a daily snack rich in unsaturated fat and protein during calorie restriction has beneficial effects on sleep. Thirty older adults will be randomized to Treatment (daily peanut snack, n=15) or Control (daily granola snack, n=15) conditions and then undergo a six-month calorie restriction intervention for weight loss. Sleep health will be measured multidimensionally via questionnaire, actigraphy, at-home electroencephalography and core body temperature monitoring at pre-, mid-, and post-intervention.

Principal Investigator(s)

• Kristen D. Krause, School of Public Health, Department of Urban-Global Public Health
• Ricardo Kairios, School of Environmental and Biological Sciences, Family and Community Health Sciences

This project, led by faculty at Rutgers University’s School of Public Health and School of Environmental and Biological Sciences in partnership with the New Jersey Performing Arts Center (NJPAC), explores how participation in the arts can improve behavioral health and advance equity in New Jersey communities. Through a mixed-methods evaluation of NJPAC’s ArtsRx Social Prescribing Program, the research team will assess how connecting individuals to arts and cultural activities—such as museum visits, glass blowing classes, and live performances—can boost well-being, reduce loneliness, and foster a sense of belonging. The study combines quantitative analysis of program outcomes with in-depth interviews of participants, non-participants, and key stakeholders to identify what helps or hinders engagement in arts-based social prescribing. Special attention is given to addressing barriers faced by marginalized groups and ensuring that programs are accessible and culturally relevant. By working collaboratively with healthcare providers, community partners, and local arts organizations, the project aims to develop practical resources and recommendations for scaling arts-based health interventions across New Jersey. Ultimately, this initiative seeks to demonstrate the power of creative engagement in promoting mental health, reducing disparities, and building stronger, more connected communities.

Principal Investigator(s)

• Carolyn Sartor, Robert Wood Johnson Medical School, Institute for Health, Health Care Policy and Aging Research
• Margaret Swarbrick, Graduate School of Applied and Professional Psychology, Center of Alcohol and Substance Use Studies

Co-Investigator(s)

• Amy Spagnolo, School of Health Professions, ScarletWell
• Sasan Haghani, School of Engineering, Electrical and Computer Engineering

There is a dire need to improve health support and resources for people living with mental health, substance use, and/or co-occurring physical conditions and experiencing poverty. These individuals often face significant barriers to accessing health-related information using digital tools (e.g., navigating patient portals, finding websites with reliable health information). The current project aims to develop a smartphone app, with individuals from this population as co-creators, that will centralize relevant health information and facilitate navigation of healthcare and associated wellness resources. This project will be conducted in peer recovery centers, also known as Community Wellness Centers, which provide critical services, education, and resources to support health and wellness, delivered by peers with lived experience. (https://cspnj.org/cause/cwc/). This low-barrier, one-stop model serves people who often experience a combination of co-occurring mental health, substance use, and physical health challenges in addition to the experiences of being formerly or currently unhoused and living below the poverty line. Community Wellness Centers are ideal spaces to co-develop an app to empower individuals with such challenges to access much-needed health information.

Principal Investigator(s)

• Jeffrey Friedman, Mason Gross School of the Arts, Dance
• Simiao Niu, School of Engineering, Biomedical Engineering
• Roseanne Dobkin, Rutgers Health, Department of Psychiatry

Co-Investigator(s)

• Natalie Schultz-Kahwaty, Mason Gross School of the Arts, Dance
• Pamela Quinn, PD Movement Lab
• Colin O’Connor, PD Movement Lab

People with Parkinson’s disease report that improved walking, including reduced freezing, shuffling, and falling, combined with increased gait stride and stability, is a primary contributor to improved quality-of-life functioning. To address this need, dance artist and Parkinson’s coach Pamela Quinn and colleague Colin O’Connor (PD Movement Lab, New York City) devised an innovative telehealth training video series that uses Ms. Quinn’s 27 years of experience with her Parkinson’s disease diagnosis for developing movement cues that increase walking gait health and wellness. Supported by the Integrated Dance Collaboratory staff, Drs. Jeff Friedman and Natalie Schultz-Kahwaty (Dance Department, Mason Gross School of the Arts), with consulting psychologist Dr. Roseanne Dobkin (Department of Psychiatry, RWJ Medical School), a 2022 pilot Gaitkeeping study shows evidence of 90-95% improvement in gait confidence. This research team will continue measuring additional qualitative measures of gait confidence and overall quality of life, while answering a new research question about how simple and easy-to-use Smartphone technologies can increase the validity of the Gaitkeeping intervention. Led by Dr. Simiao Niu (Department of Biomedical Engineering, School of Engineering), the research team will develop a Parkinson’s-based algorithm to harness smartphone technologies for gathering and downloading a broad range of kinesiological quantitative data that further validate the Gaitkeeping intervention.

Principal Investigator(s)

• Min Xu, School of Arts and Sciences, Statistics
• Jinchuan Xing, School of Arts and Sciences, Genetics

The rapid advancement of machine learning has transformed genetics and genomics. With machine learning and large-scale genome sequencing, every living being is now a treasure trove of data. Despite these advances, extracting clear scientific insights from modern genetic data remains challenging due to their noisy and heterogeneous nature. Genes often function interactively and synergistically, adding to the complexity.

This project aims to develop new interpretable statistical methodologies in gene-gene interaction (GGI) network analysis to advance medical genetics, which seeks to understand the genetic basis of complex diseases and to identify disease-causing mutations. Since genes typically operate through modules and pathways, a common approach in medical genetics is to analyze the network formed by interactions of candidate genes identified from patient data. The challenge of effectively utilizing GGI network information to uncover disease genes is a critical bottleneck in medical genetics research. Our project tackles this problem by using state-of-the-art statistical learning methods for network data. Our methods are based on Markovian network models, which take into account the underlying evolutionary growth process of the GGI network. The strategy developed in this proposal will equip biologists with powerful tools to understand biological systems in ways that are impossible today.

Principal Investigator(s)

• Debashish Bhattacharya, School of Environmental and Biological Sciences, Biochemistry and Microbiology
• Mehdi Javanmard, School of Engineering, Electrical and Computer Engineering
• Xiaoyang Su, Rutgers Health, Department of Medicine
• David Sleat, Rutgers Health, Department of Biochemistry and Molecular Biology
• Haiyan Zheng, Rutgers Health, Center for Advanced Biotechnology and Medicine

Coral reefs cover less than 1% of the ocean floor but support nearly 25% of all marine life, making them vital centers of biodiversity. Rising seawater temperatures have led to frequent and intense events of coral reef "bleaching” and “Coral Mass Spawning Asynchrony” (CMSA). Almost 80% of corals reproduce by mass spawning, i.e., the synchronized release of gametes into the water column to maximize fertilization and larval settlement success. CMSA may abolish coordinated spawning, leading to inviable gametes, low fertilization success, and reduced genetic mixing. To understand the biological underpinnings of CMSA, we will use sophisticated genomic tools to create a robust model of coral sexual reproduction and mass spawning over the annual cycle. Based on preliminary data, we hypothesize that thermal stress impairs or delays coral steroid hormone biosynthesis, causing CMSA. Furthermore, there is a significant need for rapid, cost-effective, portable, and easy-to-deploy diagnostic tools to aid conservation efforts, because timely and accurate data are essential to underpin proactive restoration actions and policies. The Bhattacharya Lab and their Rutgers partners will develop and deploy coral sex hormone biomarkers with the support of our network of coral reef conservation partners.

Principal Investigator(s)

• Konstantinos Michmizos, School of Arts and Sciences, Computer Science
• Philip Parker, School of Arts and Sciences, Psychology

Co-Investigator(s)

• Jack Klawitter, School of Arts and Sciences, Computer Science
• Cassandra Cavazos, School of Arts and Sciences, Psychology

Modern artificial intelligence (AI) has long surpassed human performance in several isolated tasks, even though it operates in ways that fundamentally differ from how intelligent behavior naturally emerges in brain networks. The proposal’s goal is to better understand how simple and complex brain functions emerge from the neural activity across several brain sites and translate this knowledge into neuro-inspired AI models that can be used to explain neuropathophysiology. To achieve this goal, the PIs and their PhD students, Jack Klawitter and Cassandra Cavazos, will co-develop advanced animal brain studies and innovative brain-inspired AI models to discover how neural networks modulate behavior. This rather heretic connection between neuromorphic AI models and microelectrode neuronal recordings will reveal on the one hand how animal behavior is mediated by multiple brain networks and on the other hand how this knowledge can be translated to neurophysiologically interpretable artificial networks. The use of specialized neuromorphic hardware will pave the way for a series of fascinating experiments where in silico networks are mapped to their in vivo counterparts, establishing a hybrid computational-experimental framework aimed at emulating, understanding, and restoring brain function.

Principal Investigator(s)

• Dr. Maribel Vazquez, School of Engineering, Biomedical Engineering

Co-Investigator(s)

• Dr. Nicholas Bello, School of Environmental and Biological Sciences, Animal Science
• Dr. Bonnie L. Firestein, School of Arts and Sciences, Cell Biology & Neuroscience

Obesity and type II diabetes mellitus (T2DM) are interrelated major health concerns. Excessive caloric intake through overconsumption of a high-fat and high-sugar diet contributes to metabolic alterations that result in obesity and T2DM. The contributing mechanisms that lead to these chronic, diet-induced metabolic changes are linked to the accumulation of harmful, pro-inflammatory compounds in the blood, called advanced glycation end products (AGEs). Many AGEs are produced from Maillard reactions, which enhance color and taste when foods are cooked, and stimulate neuroinflammation via altered balance of intestinal microbiota, accelerated neuronal metabolism, and activated inflammatory signaling pathways. Alarmingly, AGEs can alter protein structure/function and work in concert with hyperglycemia to promote neurodegeneration. The long-term goal of our research is to develop a systematic and interdisciplinary approach to examine the effects of diet-induced AGEs on neurosensory behavior, integrity of neurovascular barriers, and neuronal function. Our grand challenge is to develop a targeted therapeutic strategy to prevent and/or retard the detrimental neural effects of diet-induced AGEs using the visual system as a model. The retina is an ideal system for this project because its high metabolic demands for vision rely exclusively on the transport of blood-borne molecules. Further, the shared signaling mechanisms/pathways of cortical neurons will help examine the neural impacts of AGEs more broadly. A critical interaction in AGEs-induced metabolic dysregulation is activation of the immune system. Indeed, activation of components of the innate immune system, such as toll-like receptor signaling pathways, results in inflammatory conditions that further promote the harmful effects of AGEs. Toll-like receptor-4 (TLR-4) has been of specific interest because its signaling pathway is involved in the production of pro-inflammatory cytokines and is activated by dietary fats. In addition, TLR-4 signaling has been implicated in the formation of high-fat diet-induced obesity and persistent hyperglycemia. Notably, TLR-4 knockout (KO) mice are resistant to high-fat diet and age-related weight gain and insulin resistance. Although there is considerable evidence on the metabolic consequences of high-fat diets, a gap in knowledge exists on the relationship between diet-induced AGEs and TLR-4 in neuroinflammation. The primary objective of this pilot project is to examine the detrimental neural effects of AGEs in TLR-4 KO mice in response to chronic, high-fat diets. Tests will first use a chemical agent (alloxan) to ablate the insulin-producing pancreatic cells in TLR-4 KO and wildtype (WT) mice and evaluate changes in sensory motor gating and metabolomics due to blood-borne, high-fat diet-AGEs. We will next correlate diet-induced AGEs with anatomical and neuronal changes in cortex tissue using brain and retinal slices to examine neuronal morphology, synapses, and inflammation. Last, tests will examine the effects of diet-induced AGEs on neurovascular integrity using microfluidic models of inner blood retinal barrier (iBRB) to measure changes in TEER resistivity and low lipoprotein receptor (LPR1) signaling. The secondary objective is to establish a working collaborative group across the life sciences at Rutgers–New Brunswick to address critical issues related to diet-induced diabetes and neuroinflammation.

Principal Investigator(s)

• Nicole Fahrenfeld, School of Engineering, Civil & Environmental Engineering

Co-Investigator(s)

• Gediminas “Gedi” Mainelis, School of Environmental and Biological Sciences, Environmental Sciences
• Maria Gloria Dominquez-Bello, School of Environmental and Biological Sciences, Biochemistry and Microbiology
• Taewon Han, School of Environmental and Biological Sciences, Environmental Sciences

His proposal’s main objective is to characterize the microbiome, antibiotic resistome, and mobilome of bioaerosols (e.g., airborne microorganisms) in comparison to other environmental media allowing for determining the extent to which the microbiome of agricultural and utility workers’ microbiomes, antibiotic resistomes, and mobilomes are reflective of their respective work environments. The inexorable link between human, animal, and environmental health (One Health) is exemplified by one of our most pressing public health issues: antibiotic resistance. Wastewater collection and treatment systems and livestock operations are environmental hotspots of antibiotic resistance. There is limited epidemiological evidence linking workers in these environments to higher rates of infectious illness and antibiotic resistance, and few cross-industry comparisons are available. Likewise, the linkage between these work environments and the worker microbiome is poorly understood, despite its potential to effect on worker wellbeing.

Our long-term goal is informing human health risk assessment and the need for and design of engineering controls and/or personal protective equipment (PPE) guidelines. Our central hypothesis is that the human microbiome of workers in each environment is distinct and reflective of the bioaerosol microbiome including its antibiotic resistome and mobilome. The rationale for this work is that a One Health approach is needed to tackle antibiotic resistance and to understand workplace exposures in environmental hotspots. One of targeted hotspots is especially understudied for worker health in the US (i.e., wastewater collection systems and treatment plants). This project will leverage funded research to generate original results for publication as well as to serve as preliminary data for future collaborative funding proposals. Specifically, a comparative field study is proposed to include collection of environmental microbiome, resistome, and mobilome data that can be used for source tracking the microbiome, resistome, and mobilome of workers in key environmental hotspots of antibiotic resistance and to inform the relative hazard workers in each environment experience.

Principal Investigators 

• Xiangmin (Helen) Liu, Rutgers–New Brunswick School of Management and Labor Relations, Human Resource Management, Labor Studies and Employment Relations
• Youngfeng Zhang, Rutgers–New Brunswick School of Arts and Sciences, Computer Science

Co-Investigators

• Adrienne Eaton, Rutgers–New Brunswick School of Management and Labor Relations, Labor Studies and Employment Relations
• Todd E. Vachon, Rutgers–New Brunswick School of Management and Labor Relations, Labor Studies and Employment Relations

Through recruitment and hiring processes, employers play a critical role in shaping economic opportunities for workers and their families by matching job candidates with vacancies. The integration of recommender systems in hiring practices has the potential to uncover the hidden workforce, reduce search costs for job seekers, and mitigate certain human biases. However, the pervasive use of data-driven recommender systems in hiring and recruitment has radically transformed the way we recognize, assess, and address fairness issues in employment decisions. In this project, our interdisciplinary team aims to develop a human-AI collaborative approach that seeks to enhance fairness throughout the entire lifecycle of job recommender systems, encompassing their development, adoption, and deployment. 

Principal Investigators   

• Tawfiq Ammari, Rutgers–New Brunswick School of Communication and Information, Library and Information Science  
• Emily A. Greenfield, Rutgers–New Brunswick School of Social Work, Hub for Aging Collaboration  

Co-Investigators  

• Natalie E. Pope, Rutgers–New Brunswick School of Social Work, Hub for Aging Collaboration  

 Age-friendly communities (AFC) are a global movement to make the places where we live, work, and play better for long and healthy lives. Recent studies have highlighted that the work of AFC leaders is highly complex, requiring the coordination of various types of capital within dynamic inter-organizational contexts spanning multiple levels of place-based communities and broader social systems. Given the agile and complex nature of AFC work, digital technologies offer strong potential to jump start, fortify, and systematize these efforts.

This mixed-method project will explore how AFC initiative leaders use digital tools to facilitate key operations in multisectoral and multilevel contexts. First, we will conduct a national survey of AFC initiative leaders to identify trends across their use of digital tools and how they access such digital tools. Second, we will conduct semi-structured interviews with AFC practitioners across the United States to explore the socio-technical fractures in collaborations concerning the core operations of AFC initiatives. Together, the mixed-methods findings will advance understandings of participants’ mental models of the use of technology in their AFC work—both the types of digital tools that comprise their work and the ways digital tools enhance/frustrate their collaborative practice toward long-term social impact.

Principal Investigators   

• Andrea Hetling, Rutgers–New Brunswick Bloustein School of Planning and Public Policy, Heldrich Center for Workforce Development   
• Rupa Khetarpal, Rutgers–New Brunswick School of Social Work, Center for Research on Ending Violence   

Co-Investigators  

• David Cohen, Rutgers Robert Wood Johnson Medical School, Department of Medicine  
• Gabrielle Gault, Rutgers–New Brunswick School of Social Work, Center for Research on Ending Violence  
• Sarah McMahon, Rutgers–New Brunswick School of Social Work, Center for Research on Ending Violence   
• Sharifa Z. Williams, Rutgers–New Brunswick Edward J. Bloustein School of Planning and Public Policy, Public Health   

As the COVID-19 pandemic highlighted, workers in healthcare and other human service fields are confronted daily with challenges related to their clients’, students’, and patients’ experiences with trauma. Consistent exposure to such trauma can result in secondary trauma stress, compassion fatigue, and burnout. A growing body of evidence indicates that trauma informed care (TIC), an approach with known benefits for clients and patients, is also effective in addressing secondary traumatic stress among frontline workers. TIC refers to systems of care that establish the importance of understanding trauma as both interpersonal and sociopolitical, emphasize the impact on human functioning, and develop effective service delivery models.

This research project aims to understand the extent to which TIC is understood and implemented in the healthcare workplace and where gaps may exist. Using the Rutgers Robert Wood Johnson Medical School Department of Medicine as a case study, we will conduct a TIC needs assessment. The study will develop a tool that documents the current understanding of TIC as well as worker needs and experiences of secondary traumatic stress. Findings have implications for future research on TIC in human and health services and immediate practice directions in staff training and policy development in hospitals.   

Principal Investigators   

• Meiyin Liu, Rutgers-New Brunswick School of Engineering, Department of Civil & Environmental Engineering  

 Co-Investigators  

• Dake Zhang, Rutgers-New Brunswick Graduate School of Education, Department of Educational Psychology  

 Assessment biases widely exist in higher education and are understudied, especially for problem types that do not have standard answers and/or require multi-step reasoning, such as word problem-solving in college engineering disciplines. A common bias comes from human graders’ limited capacity to identify and understand students’ usual and low-frequent problem-solving strategies, which are more commonly observed in students with under-represented minority backgrounds.  These unusual and low-frequent strategies represent students’ mathematical reasoning. However, they are often neglected by human graders, thus making evaluations biased against minority students.

To enhance Diversity, Equity, and Inclusion (DEI) in higher education engineering disciplines, this research proposes an automatic grading system for evaluating students’ word problems, particularly for detecting and understanding unusual and low-frequent problem-solving strategies. Additionally, instead of only assigning a score, this proposed project will contribute to the field by taking an initial effort to generate feedback with human-interpretable justifications. Specifically, this research will leverage visual representation of reasoning processes in learning sciences and graph technology in artificial intelligence. This research will develop a prototype web application hosted on Rutgers’ eLearning platform and adopt it in real engineering classes at Rutgers University.  

Principal Investigators

• Waheed U. Bajwa, Rutgers–New Brunswick School of Engineering; Electrical and Computer Engineering 
• David Zald, Center for Advanced Human Brain Imaging Research, Robert Wood Johnson Medical School 
• Linden Parkes, Center for Advanced Human Brain Imaging Research, Robert Wood Johnson Medical School 
• Avram Holmes, Center for Advanced Human Brain Imaging Research, Robert Wood Johnson Medical School 

Principal Investigators

• Adam Gormley, Rutgers–New Brunswick School of Engineering; Biomedical Engineering
• David Sleat, Center for Advanced Biotechnology and Medicine, Robert Wood Johnson Medical School

Co-Investigator

• Peter Lobel, Center for Advanced Biotechnology and Medicine, Robert Wood Johnson Medical School

Principal Investigators 

• Mark van der Maas, Rutgers–New Brunswick School of Social Work, Center for Gambling Studies 
• Jim Samuel, Rutgers–New Brunswick Edward J. Bloustein School of Planning and Public Policy; Informatics 

Principal Investigators 

• Ahmed Aziz Ezzat, Rutgers–New Brunswick School of Engineering; Industrial and Systems Engineering
• Josh Kohut, Rutgers–New Brunswick School of Environmental and Biological Sciences; Marine and Coastal Sciences 

Principal Investigators 

• Woojin Jung, Rutgers–New Brunswick School of Social Work, Global Health Institute
• Dimitris Metaxas, Rutgers–New Brunswick School of Arts and Sciences; Computer Science
• Dimitrios Ntarlagiannis, Rutgers–Newark School of Arts and Sciences; Earth and Environmental Sciences
• Min Xu, Rutgers–New Brunswick School of Arts and Sciences; Statistics
• Yuan Liao, Rutgers–New Brunswick School of Arts and Sciences; Economics

Co-Investigators 

• Quentin Stoeffler, University of Bordeaux School of Economics
• Maryam Hosseini, Massachusetts Institute of Technology, City Form Lab
• Simone Nsutezo, Microsoft Research, AI for Good Lab
• Anthony Ortiz, Microsoft Research, AI for Good Lab

Principal Investigators

• Jessica Leigh Hamilton, PhD (Rutgers–New Brunswick School of Arts and Sciences; Psychology);
• Daniel Charles Semenza, PhD (Rutgers–Camden Faculty of Arts and Sciences; Sociology, Anthropology, and Criminal Justice; Rutgers Biomedical and Health Sciences School of Public Health; Urban-Global Health)

Co-Investigators

• Paul Boxer, PhD (Rutgers–Newark School of Arts and Sciences-Newark; Psychology)
• Jeffrey Lane, PhD (Rutgers–New Brunswick School of Communication and Information; Communication)
• Linda Oshin, PhD (Rutgers–New Brunswick Graduate School of Applied and Professional Psychology; Clinical Psychology)

Youth are exposed to an alarming amount of gun violence in their homes, schools, communities, and media. The prevalence and ubiquity of smartphones and social media also have increased potential exposure to gun violence among youth in the United States. This study aims to evaluate the nature and impact of gun violence on youth mental health. The study team includes investigators across Rutgers campuses (New Brunswick, Camden, Newark), career stages, and departments of psychology, criminal justice, and communication. First, focus groups with adolescents (N = 20) will be conducted to better understand the nature of gun-related violence on social media. Second, the study team will investigate the frequency of gun violence exposure on social media, and whether it is associated with mental health problems concurrently and three months later using a survey design with 500 adolescents nationwide. Third, we will then evaluate these relationships with a subset of adolescents (N = 50) on a daily basis using intensive monitoring approaches of ecological momentary assessment and smartphone sensing. Findings have the potential to inform policy, education, and research conducted on the far-reaching effects of gun violence on youth across the United States.

Principal Investigators

• Evan Kleiman, PhD (Rutgers–New Brunswick School of Arts and Sciences; Psychology)
• Shireen Rizvi, PhD (Rutgers–New Brunswick Graduate School of Applied and Professional Psychology; Clinical Psychology);
• Paul Duberstein, PhD (Rutgers Biomedical and Health Sciences; Health Behavior, Society and Policy)

Co-Investigator

• Andrew Falzon, MD (Chief State Medical Examiner for the State of New Jersey; Rutgers Biomedical and Health Sciences; Pathology & Laboratory Medicine)

Someone dies by suicide via firearm every other day in New Jersey. The aim of this grant is to better characterize suicides in New Jersey through a collaboration between the Rutgers Suicide Prevention and Research Center (SPARC) and the New Jersey Office of the Chief State Medical Examiner (OCSME). We will conduct two projects. The first project involves coding existing data from death records. We will use established methods to code life stressors (e.g., death of a partner, recent police involvement, domestic violence) prior to suicide. We will compare stressors prior to firearm suicide with stressors prior to suicide by other means (hanging, overdose, etc.). Second, we will train members of our team to conduct psychological autopsies on those who die by suicide in NJ. Team members will conduct structured interviews with family members and friends of individuals who died by suicide. The aim of this project is to increase awareness of the importance of psychological autopsies as part of the work-up of suspected suicides, and to promote its use in the Medical Examiner community in New Jersey. In turn, this will help us gain unparalleled insight into the factors that may contribute to deaths by suicide within our state.

*Please note that this project has been partially funded by the New Jersey Gun Violence Research Center.

Principal Investigators

• Valerie Tutwiler, PhD (Rutgers–New Brunswick School of Engineering; Biomedical Engineering)
• Joseph Hanna, MD, PhD, FACS (Rutgers Biomedical and Health Sciences Robert Wood Johnson Medical School; Surgery Critical Care)

Trauma is the leading cause of death of young healthy people worldwide, with over 40,000 of these deaths occurring due to gunshot injuries. Coagulopathy, or impaired blood coagulation, is common after trauma and is associated with a 4-fold increased risk of death. Coagulopathy contributes to early death from acute bleeding and also increases risk of later death from delayed complications. However, it is not known how injury type influences early coagulopathy phenotype and how that interplays with prolonged inflammation and mortality after gunshot injuries. We will examine blood clotting and mechanics from patients admitted to Robert Wood Johnson University Hospital with traumatic injuries including gunshot victims. Using these patient sample profiles as a guide, we will develop an in vitro model of coagulation following gunshot injury. This will be utilized to test the efficacy of treatments and guide clinical care.

Principal Investigators

• Rachel Choron, MD, FACS (Rutgers Biomedical and Health Sciences; Robert Wood Johnson Medical School Surgery)
• Chiara Sabina, PhD, MA (Rutgers–New Brunswick School of Social Work; Social Work)

Co-Investigators

• Elaine Hewins, CSW, DVS (Robert Wood Johnson University Hospital)
• Nazsa S. Baker, PhD, MA (Rutgers Biomedical and Health Sciences; NJ Gun Violence Research Center; School of Public Health)
• Jennifer Geller (Rutgers Biomedical and Health Sciences; Medical Student)
• Diana Starace, BS (Rutgers Biomedical and Health Sciences; Robert Wood Johnson University Hospital)
• Amanda Teichman, MD, FACS (Rutgers Biomedical and Health Sciences; Robert Wood Johnson Medical School Surgery)
• Zachary Englert, DO, FACS (Rutgers Biomedical and Health Sciences; Robert Wood Johnson Medical School Surgery)

The greatest burden of firearm violence falls upon young men, specifically in the Black and Hispanic communities. These gun violence survivors are an underserved population and it has only recently been recognized that additional medical/surgical, socioeconomic, and mental health supports are desperately needed and desired beyond inpatient care following discharge from the hospital. Therefore, the aim of this project is to establish the Rutgers Gun Violence Care Center (RGVCC) which involves extensive collaboration among surgeons, interventionalists, primary care practitioners, behavior health specialists, and Hospital Violence Intervention Program social workers to provide better clinical outpatient care and improve socioeconomic and mental health resources to survivors. A RWJ medical student will be dedicating a year to fill the role of clinical navigator and researcher; she will coordinate the multidisciplinary collaboration and research efforts. The RGVCC impact and proof of concept will be studied by assessing patient follow up and long-term outcomes among patients utilizing the RGVCC compared to those who did not prior to RGVCC initiation. Additionally, the psychology of violence and complex trauma symptoms experienced by survivors will be evaluated to gain better insight into the psychological, cognitive, and behavioral functioning of the survivors to ultimately provide better trauma informed care.