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Communication and Hospice Online with Optimal Support and Engagement (CHOOSE)
Abstract Drawing upon the principles of social identity theory, existing literature, and our initial findings from family caregiver (FCG) online support groups (OSGs), our objective is to identify fundamental facilitator communication strategies that promote safe communication engage participants, and strengthen mechanisms of action (MOAs) within OSGs, ultimately enhancing health outcomes for hospice FCGs. Our pioneering initiative, Communication and Hospice Online with Optimal Support and Engagement (CHOOSE) is backed by compelling evidence highlighting the critical role of facilitator communication in reinforcing MOAs (a shared identity, social support, and social networks) in OSGs. Preliminary research underscores the transformative power of these MOAs in improving health outcomes for FCGs, yet current studies lack generalizability and statistical robustness. CHOOSE represents the first major, multisite, rigorously designed, and theoretically informed OSG intervention explicitly tailored for hospice FCGs of cancer patients. We aim to strengthen MOAs to enhance FCG well-being, reduce depression and anxiety, improve quality of life, and diminish loneliness. By advancing this critical research, we seek to provide a well-founded, evidence-based solution to the urgent needs of FCGs, making a significant impact on their health and well-being. We have outlined the following study aims: Aim 1. Determine the effect of the CHOOSE intervention on FCGs’ health outcomes compared to usual OSGs and usual hospice care. Aim 2. Examine direct and mediational relationships between CHOOSE participation, MOAs, and health outcomes. Aim 3. Explore the relationship between facilitator communication strategies and the FCG experience of the MOA to allow for future calibration of the intervention 1
Mentoring investigators in patient-oriented research on HIV and public health
PROJECT SUMMARY/ABSTRACT Despite marked progress in treatment and prevention, HIV remains a significant public health threat in the US and globally. Innovative strategies are needed to effectively deploy interventions and reduce HIV incidence, which requires a sustained and committed workforce. Dr. Dennis is an infectious disease physician and researcher at the University of North Carolina (UNC) at Chapel Hill, Division of Infectious Diseases. She seeks the protected time of the K24 award to ensure adequate time and effort to provide mentorship in patient- oriented HIV research focused on applied public health strategies. Dr. Dennis has a track record of performing high-quality patient-oriented research supported by independent funding. Her research bridges basic, clinical, and epidemiologic science by using HIV-1 molecular epidemiology and phylogenetics to understand HIV transmission at the population level and to use this information to direct prevention. She has expanded this work to optimize strategies to detect and respond to HIV networks using mixed-methods approaches. The overall goal of this work is to uncover the links between these sub-epidemics - which are overlapping sub- epidemics defined by risk groups, geography, social interaction - to facilitate the design of timely, effective interventions. The research specific aims are 1) Investigate HIV transmission networks using molecular epidemiology and phylodynamics (R01AI135970), 2) Evaluate uptake of HIV treatment and prevention services in public health with social network approaches (supported by R01AI169602), and 3) Pilot a network-based characterization of early syphilis infections to inform strategies to increase the uptake of injectable antiretrovirals for HIV treatment and prevention (supported by K24). With the support of the K24, she will leverage resources at UNC to support mentorship and professional development to strengthen new directions (implementation science, community-engaged research). Dr. Dennis is deeply committed to expanding her mentorship and dedicated to fostering diverse mentees with lived experiences that are critical for sustaining the HIV workforce. Dr. Dennis is Co-Director of the UNC Center for AIDS Research (CFAR) Scientific Working Group which focuses on Ending the HIV Epidemic efforts in North and South Carolina. She has strong institutional support and a multidisciplinary team of advisors, including the UNC CFAR, and is an advisor on the UNC T32 HIV/STI institutional training program. She has collaborated for the past 10 years with NC Division of Public Health and with multiple investigators and trainees at the UNC Gillings School of Public Health. She is active in the UNC Infectious Diseases Fellowship program, providing clinical and research mentorship to numerous ID fellows. Her clinical activity provides practical grounding and relevance in patient-oriented research. The K24 will provide 50% of Dr. Dennis’ salary and additional funds to support mentees’ research. The proposed research is timely and aligned with the National HIV/AIDS Strategy and will support the protected time needed to mentor the next-generation of investigators in HIV patient-oriented research.
TACTIC: Tuberculosis Active Case Tracking via Interpersonal Connections
PROJECT SUMMARY/ABSTRACT Tuberculosis (TB) remains the leading infectious cause of death worldwide. Interruption of transmission is the most effective strategy to reduce incident infections, yet current approaches often fail to reach individuals for timely testing and treatment. This study addresses that gap by leveraging social networks to identify individuals at highest risk of transmitting TB, specifically, people who use drugs (PWUD). We will evaluate respondent-driven sampling (RDS), a peer7 based community recruitment strategy, to identify TB cases among PWUD and the household contacts (HHCs) of those with TB disease (RDS-TB) in Kampala, Uganda. Conducting this work in a high-prevalence setting such as Kampala where our team has established expertise allows us to overcome recruitment challenges common in settings in the United States while generating findings that are directly translatable. This is particularly relevant given that higher TB prevalence and larger outbreaks in the United States have been associated with the use of methamphetamine, heroin, and crack/cocaine, drugs that we will study. In Aim 1, we will compare the effectiveness and reach of RDS-TB with a traditional clinic-based index case HHC approach for TB case finding. We will screen 2,000 PWUD and their HHCs, estimate the number needed to screen to identify one case of TB disease, and compare the demographic and network characteristics of RDS-TB recruits with clinic-based HHCs. Whole genome sequencing will be used to characterize transmission dynamics. In Aim 2, we will compare the yield of individual and combined TB diagnostic strategies for community-based active case finding. Participants will undergo chest radiography with computer-aided detection, tongue swab testing for TB nucleic acid amplification tests (NAAT), and sputum testing for NAAT and mycobacterial culture. We will identify the minimal combination of tests needed to meet World Health Organization target product profile thresholds for screening. In Aim 3, we will define the conditions under which RDS-based screening can effectively interrupt TB transmission. We will develop an agent-based model informed by social network data from individuals with and without TB, incorporating drug use patterns and demographic characteristics. This project will generate a practical, scalable roadmap for social network–based TB active case finding in high28 risk communities. The approach will be readily adaptable to settings in the United States and will inform strategies to interrupt transmission and advance progress toward TB elimination, in alignment with the NIH Strategic Plan for TB Research.
How communication networks promote cross-cultural similarities: The case of category formation
Individuals vary widely in how they categorize novel phenomena. This individual variation has led canonical theories in cognitive and social science to suggest that communication in large social networks leads populations to construct divergent category systems. Yet, anthropological data indicates that large, independent societies consistently arrive at similar categories across a range of topics. How is it possible for diverse populations, consisting of individuals with significant variation in how they view the world, to independently construct similar categories? Through a series of online experiments, I show how large communication networks within cultures can promote the formation of similar categories across cultures. For this investigation, I designed an online “Grouping Game” to observe how people construct categories in both small and large populations when tasked with grouping together the same novel and ambiguous images. I replicated this design for English-speaking subjects in the U.S. and Mandarin-speaking subjects in China. In both cultures, solitary individuals and small social groups produced highly divergent category systems. Yet, large social groups separately and consistently arrived at highly similar categories both within and across cultures. These findings are accurately predicted by a simple mathematical model of critical mass dynamics. Altogether, I show how large communication networks can filter lexical diversity among individuals to produce replicable society-level patterns, yielding unexpected implications for cultural evolution. In particular, I discuss how participants in both cultures readily harnessed analogies when categorizing novel stimuli, and I examine the role of communication networks in promoting cross-cultural similarities in analogy-making as the key engine of category formation.
Networking—the key to success… especially in the brain
In our everyday lives, we form connections and build up social networks that allow us to function successfully as individuals and as a society. Our social networks tend to include well-connected individuals who link us to other groups of people that we might otherwise have limited access to. In addition, we are more likely to befriend individuals who a) live nearby and b) have mutual friends. Interestingly, neurons tend to do the same…until development is perturbed. Just like social networks, neuronal networks require highly connected hubs to elicit efficient communication at minimal cost (you can’t befriend everybody you meet, nor can every neuron wire with every other!). This talk will cover some of Alex’s work showing that microscopic (cellular scale) brain networks inferred from spontaneous activity show similar complex topology to that previously described in macroscopic human brain scans. The talk will also discuss what happens when neurodevelopment is disrupted in the case of a monogenic disorder called Rett Syndrome. This will include simulations of neuronal activity and the effects of manipulation of model parameters as well as what happens when we manipulate real developing networks using optogenetics. If functional development can be restored in atypical networks, this may have implications for treatment of neurodevelopmental disorders like Rett Syndrome.
Spike-based embeddings for multi-relational graph data
A rich data representation that finds wide application in industry and research is the so-called knowledge graph - a graph-based structure where entities are depicted as nodes and relations between them as edges. Complex systems like molecules, social networks and industrial factory systems can be described using the common language of knowledge graphs, allowing the usage of graph embedding algorithms to make context-aware predictions in these information-packed environments.
Motives and modulators of human decision making
Did we eat spaghetti for lunch because we saw our colleague eat spaghetti? What drives a risk decision? How can our breakfast impact our decisions throughout the day? Research from different disciplines such as economics, psychology and neuroscience have attempted to investigate the motives and modulators of human decision making. Human decisions can be flexibly modulated by the different experiences we have in our daily lives, at the same time, bodily processes, such as metabolism can also impact economic behavior. These modulations can occur through our social networks, through the impact of our own behavior on the social environment, but also simply by the food we have eaten. Here, I will present a series of recent studies from my lab in which we shed light on the psychological, neural and metabolic motives and modulators of human decision making.
Behavioral and neurobiological mechanisms of social cooperation
Human society operates on large-scale cooperation and shared norms of fairness. However, individual differences in cooperation and incentives to free-riding on others’ cooperation make large-scale cooperation fragile and can lead to reduced social-welfare. Deciphering the neural codes representing potential rewards/costs for self and others is crucial for understanding social decision-making and cooperation. I will first talk about how we integrate computational modeling with functional magnetic resonance imaging to investigate the neural representation of social value and the modulation by oxytocin, a nine-amino acid neuropeptide, in participants evaluating monetary allocations to self and other (self-other allocations). Then I will introduce our recent studies examining the neurobiological mechanisms underlying intergroup decision-making using hyper-scanning, and share with you how we alter intergroup decisions using psychological manipulations and pharmacological challenge. Finally, I will share with you our on-going project that reveals how individual cooperation spreads through human social networks. Our results help to better understand the neurocomputational mechanism underlying interpersonal and intergroup decision-making.
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