Grants

NSF

This project aims to serve the national interest by improving teaching and assessment methods used for team projects in undergraduate computing education. By requiring students to collaborate in the development of a software product, team projects provide students with authentic learning experiences that prepare them for careers in the computing profession. In undergraduate education, a key challenge is to assess individual contributions to team projects. This project plans to develop a novel teaching and assessment approach in which students compile individual portfolios documenting and reflecting on their completed project tasks relative to the outcomes they address. Instructional staff and peers then assess a sample of each student’s portfolio entries against appropriate performance indicators associated with the learning outcomes targeted by the team project. Since the framework will be readily adaptable to any team project, the approach can be used for team projects in any STEM degree program. This Level 2 Engaged Student Learning project will thus help advance undergraduate STEM education by improving the ability to assess students engaged in team projects. Using a rigorous empirical approach that involves computing instructors at multiple institutions, computing students, software professionals, and a learning scientist, this project will iteratively develop and validate (a) an assessment framework to gauge attainment of student learning outcomes targeted by collaborative software development projects; and (b) a pedagogical approach that integrates the assessment framework into computing courses. By aiming to improve assessment methods for team projects, the framework will contribute to the development of exemplary practices in undergraduate STEM education. Through their participation in the framework, students will enter the workforce with better self-knowledge and documentation of their skills, thus helping employers to integrate new hires into positions that align with those skills. The framework will be designed to be flexible enough to facilitate its adoption across a broad range of STEM courses. Moreover, the framework aims to assess students' attainment of a variety of learning outcomes in addition to those captured by traditional assessments. In so doing, it aims to help broaden the participation of STEM students from different backgrounds. By documenting, reflecting on, and receiving feedback on their individual attainment of learning outcomes in team projects, students will be better prepared for employment in the professional workforce, where team projects are a central activity. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

This project aims to serve the national interest by improving teaching and assessment methods used for team projects in undergraduate computing education. By requiring students to collaborate in the development of a software product, team projects provide students with authentic learning experiences that prepare them for careers in the computing profession. In undergraduate education, a key challenge is to assess individual contributions to team projects. This project plans to develop a novel teaching and assessment approach in which students compile individual portfolios documenting and reflecting on their completed project tasks relative to the outcomes they address. Instructional staff and peers then assess a sample of each student’s portfolio entries against appropriate performance indicators associated with the learning outcomes targeted by the team project. Since the framework will be readily adaptable to any team project, the approach can be used for team projects in any STEM degree program. This Level 2 Engaged Student Learning project will thus help advance undergraduate STEM education by improving the ability to assess students engaged in team projects. Using a rigorous empirical approach that involves computing instructors at multiple institutions, computing students, software professionals, and a learning scientist, this project will iteratively develop and validate (a) an assessment framework to gauge attainment of student learning outcomes targeted by collaborative software development projects; and (b) a pedagogical approach that integrates the assessment framework into computing courses. By aiming to improve assessment methods for team projects, the framework will contribute to the development of exemplary practices in undergraduate STEM education. Through their participation in the framework, students will enter the workforce with better self-knowledge and documentation of their skills, thus helping employers to integrate new hires into positions that align with those skills. The framework will be designed to be flexible enough to facilitate its adoption across a broad range of STEM courses. Moreover, the framework aims to assess students' attainment of a variety of learning outcomes in addition to those captured by traditional assessments. In so doing, it aims to help broaden the participation of STEM students from different backgrounds. By documenting, reflecting on, and receiving feedback on their individual attainment of learning outcomes in team projects, students will be better prepared for employment in the professional workforce, where team projects are a central activity. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

This award supports research in relativity and relativistic astrophysics, and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. Gravitational waves are ripples in the fabric of spacetime caused by the violent acceleration of extremely compact objects, like black holes and neutron stars smashing together billions of light-years away, or exotic processes in the very early universe. Detecting the primordial stochastic gravitational-wave background is one of the most ambitious goals of gravitational-wave astronomy. This persistent signal that permeates all space encodes information about even earlier moments in the Universe’s history than those we can currently probe with traditional electromagnetic telescopes. The primordial background is likely too weak to be detected with the current LIGO-Virgo-KAGRA instruments that routinely observe gravitational waves from black hole and neutron star mergers, but it could lie within the reach of proposed next-generation detectors. However, even with improved data, existing analysis methods are insufficient for disentangling the contributions of the weak background from the much louder foreground of gravitational waves from compact-object mergers. This project focuses on developing a novel method for detecting the primordial background in the presence of the foreground from merger signals. This award also provides training in data analysis and science communication to the students involved, and to the broader local community via the Gravitational-Wave Open Data Workshops that the PI will host at their institution. This award will lay the groundwork for the data analysis strategies needed for the source-rich data expected for next-generation gravitational-wave detectors, facilitating the detection of the primordial background that would uniquely provide us with a glimpse into the moments immediately after the Big Bang when our Universe burst into existence. This work will be conducted at Princeton University by the PI and a graduate student funded by the award, who will gain experience with statistical data analysis techniques and a deep understanding of the physical concepts underlying the stochastic gravitational-wave background, in addition to opportunities for mentorship, networking, leadership, and career development. The fully Bayesian method for the simultaneous detection and characterization of the primordial stochastic background in the presence of astrophysical foregrounds that will be developed under this award hinges on modeling the statistical differences between the foreground—composed of individual and largely unresolved compact-object mergers—and the persistent, Gaussian, primordial background. Expanding upon the PI’s previous proof-of-concept, this project will specifically 1) investigate the effects on the inference of the primordial background properties of systematic errors introduced by uncertainties in the waveform approximations typically used in Bayesian inference of the gravitational-wave signal from individual binary black holes, 2) incorporate the simultaneous inference of the population properties of these binary black hole mergers along with their merger rate and the primordial background properties, and 3) begin to adapt the method to accommodate the foreground of binary neutron star mergers, whose statistical properties differ from those of the binary black hole foreground as the signals overlap in the frequency band of ground-based detectors due to their longer duration. By incorporating simultaneous inference of population properties, we will be able to learn about the high-redshift population of compact-object binaries at current detector sensitivities without detecting any of these events individually, probing the astrophysical processes governing their formation and evolution, which remain largely unknown. The simultaneous Bayesian search will also optimally enable the continued placement of upper limits on the Gaussian background at current detector sensitivities before it becomes detectable, to constrain cosmological sources of gravitational waves such as cosmic strings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases

PROJECT SUMMARY Kidney stones are an increasingly prevalent disease in which the urinary tract becomes obstructed by mineral deposits (stones); it can cause debilitating pain and life-threatening infection or kidney failure. To avoid these negative consequences, the kidney stones must be removed surgically. This is most commonly performed through a minimally invasive procedure (ureteroscopy) in which a laser is used to fragment the stones into small pieces. These fragments, often numbering in the hundreds, are then either removed during surgery or left to be removed by passively washing down the urinary tract to the bladder as urine drains. However, residual fragments remain in approximately 40% of surgeries and can re-obstruct or grow into larger stones, leading to downstream clinical complications that range from unplanned medical visits for pain to requiring repeat surgery. The current standard of care for removing kidney stone fragments is a wire basket that generally removes only one fragment at a time, and it cannot effectively remove smaller stone fragments, leading to high rates of residual fragments. In contrast, the novel MagStone System uses a magnet to remove fragments: First, stone fragments are magnetized by coating them with a magnetic iron oxide-based hydrogel, then they are retrieved using a magnetic wire. This is especially effective on small fragments that the current standard of care cannot retrieve, and because fragments of any size can be coated en masse, the MagStone System enables the re- trieval of more stone fragments in a single pass. By more effectively removing residual fragments of all sizes, the MagStone System should reduce postoperative complications, hospitalizations, and interventions. The current prototype of the MagStone System has demonstrated more effective stone removal compared to baskets in benchtop models and a good safety profile in preliminary in vivo porcine models. Nevertheless, MagStone’s efficacy relies upon proper injection of the hydrogel precursors through an injection catheter to mag- netize the stone fragments. The current injector has several shortcomings, including a high user-dependent variability, premature gel formation and inappropriate mixing. The lack of appropriate dosage and unreliable injection has prevented us from studying the potential effects of residual hydrogel in the kidney. In the proposed Phase I SBIR, we will first develop robust candidate prototypes of the hydrogel delivery catheter that facilitates reliable injection and sufficient magnetization of stone fragments. Thereafter, we will evaluate and rank the performance of these candidate prototypes on a ureteroscopy simulation model with ex- perienced endourologists. The final design will then be used to conduct in vivo experiments demonstrating the removal and clearance of the magnetic hydrogel from the kidney. The successful completion of the proposed studies will give the MagStone System a solid foundation from which to launch downstream preclinical tests needed to secure regulatory approval, bringing the device one step closer to patients who continue to suffer from recurrent kidney stone disease and incomplete stone evacuation.

NIAID - National Institute of Allergy and Infectious Diseases

ABSTRACT: One of the most fundamental limitations in medicine is reliance on clinical phenotype as the primary way to diagnose and classify disease. For inflammatory diseases, clinical phenotype alone is not sufficient to describe underlying disease pathogenesis. For example, cytokines like interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-17A can all drive arthritis, but clinical features such as arthritis or rash may not reflect the causal cytokine. As a result, there are no precision biomarkers to guide targeted cytokine therapy: phenotypic classification systems do not stratify patients by causative mechanisms that guide therapy. The lack of precision medicine strategies is one of the most significant unmet needs in the field, leading to poor outcomes for over 40 million patients with inflammatory diseases. This includes >1 million patients with a phenotype-driven diagnosis of “rheumatoid arthritis”: 40-50% of whom fail first biologic therapy, and 10% with disease refractory to multiple consecutive targeted therapies. We propose addressing this problem by combining expertise in immunogenetics and translational immunology (Dr. Schwartz); systems immunology and machine learning (Dr. Das); and statistical genetics (Dr. Wang).We will leverage another key finding: shared molecular mechanisms like IL-6 signaling can drive different phenotypically defined diseases like arthritis, vasculitis, and scleroderma. Using machine-learning approaches, we will build a phenotype-blind molecular taxonomy for immune diseases. Drawing from the success of phenotype-blind tumor genotyping in cancer therapy, we will adapt machine learning approaches developed in the Das lab to build novel tools (SIDER, Significant Interaction Directional Effect Representation; MAGen Multiscale network Approach for Genetic architecture). We will use SIDER and MAGen to construct an “omnigenic model”, connecting a small number of disease-causal core genes to many peripheral genes through complex biological networks. We will ground our approach in human biology using Dr. Schwartz’s expertise to build on >500 core genes that cause monogenic inborn errors of immunity (IEI). We will use interpretable machine-learning and network approaches developed by Dr. Das to develop molecular modules that will be applied to large population databases leveraging Dr. Wang’s expertise We will investigate two aims: (1) understanding monogenic/oligogenic disease architecture and (2) developing novel molecular endotypes for common diseases. This approach will demonstrate a molecular taxonomy is a relevant and actionable approach that will transform the identification, study, and treatment of immune diseases and beyond.

NSF

This Developing and Testing Innovations project will continue the development of a nonvisual interface for the Scratch educational programming environment. Drag-and-drop programming environments like Scratch have done much to lower the barrier to learning and increase engagement for a variety of students. Such resources support K-12 students' exploration and preparation for careers in computer science, and in many other science, technology, engineering and mathematics fields that require programming skills. This project will continue the development of a tangible, nonvisual programming interface to allow blind and visually impaired (BVI) students to fully and independently participate in the same Scratch learning opportunities as their sighted peers. A key component of the approach is to translate visual aspects of Scratch into the haptic domain, focusing specifically on elements known to increase engagement and lower hurdles to learning programming and taking into account the differences in how the haptic and visual sensory systems process information. In addition, resources will be developed for teachers who may have students using the nonvisual interface alongside those using the visual interface for Scratch, including provision of some best practices. The goals of the project are threefold. First, the project will continue to develop the nonvisual interface for Scratch through a) using user feedback and observations of a two-day programming camp for BVI middle school students held at the end of the previous project term to improve the system design, b) automate components of the interface previously implemented using Wizard of Oz methods, and c) add components designed to increase engagement of a wide variety of learners, in a similar manner to visual Scratch. Second, the project will develop teaching resources, including curricula, support materials and training videos for K-12 teachers; these resources will incorporate how to integrate instruction for nonvisual and visual interfaces, and best practices for paired programming with the nonvisual interface. Third, the project will develop mentoring and educational guidance resources for students using the nonvisual interface. All of these components will be developed through the use of universal and participatory design techniques, as well as evidence-based design. Multiple five-day camps for mixed groups of BVI and sighted students will be held at collaborating science centers to provide an objective measurement of the effectiveness of the interface and teaching materials developed, and provide insight into the requirements for widespread deployment. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH

Background: Women Veterans often report little or no exercise after leaving military service. Regular exercise contributes to significant benefits in physical and psychological health, including risk reduction for several chronic conditions, such as diabetes and cardiovascular disease. As such, women Veterans’ diminished exercise contributes to their increased risk for significant health conditions and can have a cumulative negative impact on their long-term health (e.g., obesity, cardiovascular disease, hypertension). Women Veterans lack access to effective approaches for increasing exercise, such as behavioral interventions (e.g., goal setting), that are tailored to their needs and can mitigate significant, preventable health conditions among this Veteran population. Psychological skills training (PST) interventions use evidence-based strategies (goal setting, imagery, self-talk, relaxation) to increase exercise participation and satisfaction. In the proposed project, we will adapt evidence-based strategies used in PST interventions to tailor a novel PST intervention known as STRIVE (Skills Training to Increase Veteran Exercise) to increase exercise adoption and adherence among women Veterans from the post-9/11 era. Significance/Impact: The post-9/11 era is the largest cohort of women Veterans and is rapidly growing. To mitigate the impact of significant, preventable health conditions among women Veterans and the subsequent burden on the VA healthcare system, approaches are needed to meet the distinct needs of this Veteran population. This proposal addresses (1) several objectives within the VA's Strategic Plan focused on women Veterans and improving their access to tailored health care and (2) HSR research priorities focused on women Veterans’ health care needs and interventions following military service. The proposed project is also timely and aligned with the recently signed Executive Order prioritizing research on women’s health issues. Findings will contribute to VA’s current exercise initiatives and efforts to tailor women Veterans’ health care. Innovation: Psychological skills training (PST) interventions have been effectively used and implemented in a variety of settings, such as the military, and have been found to increase exercise. PST interventions can also increase self-efficacy, which is one of the strongest determinants of consistent exercise. However, despite the demonstrated effectiveness of PST interventions on increasing exercise and self-efficacy, the application of PST interventions to increase exercise among women Veterans remains largely unexplored. Specific Aims: This study will determine exercise perceptions and support needs among women Veterans, (Aim 1), iteratively tailor a PST-based intervention protocol for exercise among women Veterans (Aim 2), and preliminarily pilot test the PST intervention for exercise to assess feasibility and acceptability (Aim 3). Methodology: This is a multimethod study. In Aim 1 we will use qualitative interviews to elicit perceptions of exercise behaviors from women Veterans (N=30). In Aim 2 we will assemble an advisory group (N=6-8) of VA clinicians and administrators to elicit input on how to tailor a PST-based intervention protocol for exercise for women Veterans. In Aim 3 we will conduct a preliminary pilot test using a sample of women Veterans (N=12) to qualitatively and quantitatively assess the feasibility and acceptability of the intervention developed in Aim 2. Implementation/Next Steps: We will develop implementation strategies in Aim 2 to facilitate broader testing, scalability, and future implementation of the STRIVE intervention. These strategies will be tested and refined in the planned future Merit Award application that will test STRIVE in a randomized controlled trial. More broadly, findings from Aim 1 and the implementation plan in Aim 2 can be used to augment existing services, such as the VA MOVE! Program or Whole Health. Adapted evidence-based strategies to promote exercise among women Veterans can also be implemented into clinical services (e.g., gynecology and primary care visits) and VA services that support women Veterans.

NIA - National Institute on Aging

Hispanic/Latino older adults are 1.5 times more likely to develop Alzheimer’s disease (AD) than White non-Hispanic older adults, yet they are diagnosed substantially later in the disease process, missing the early-stage window in which emerging therapies are most effective. Furthermore, they are excluded from AD clinical trials at nearly twice the rate of White non-Hispanic participants, often for being considered as too progressed. Although these disparities exist for a number of reasons, a contributing factor is that existing tests that are feasible for use in primary care to screening patients for the early signs of AD show worse diagnostic accuracy for Hispanics/Latinos, even when using normative data and controlling for differences in education. Thus, there is an urgent need for more universal screening tools, especially in preclinical stages of AD. The long-term goal of this research is to develop convenient methods for assessing and screening patients for AD risk across varying demographics. To meet this goal, an objective behavioral test has been newly developed that is associated with cognition and measures daily functioning, and has been shown to be sensitive and specific to AD staging. The brevity and simplicity of the test make it an ideal assessment to be paired with emerging blood tests for screening and monitoring in primary care. The central hypothesis is that the novel test (herein, bean game) proposed here will not vary significantly between Hispanic/Latino and White non-Hispanic adults within the current AT(N) framework of AD, and may be more acceptable, appropriate, and preferable than traditional cognitive tests. The overall objective of this R01 application is to leverage the existing MindCrowd electronic cohort to test this hypothesis. MindCrowd was developed to improve accessibility and inclusion in AD research, and collects lifestyle, health, cognitive, genetic, and medical history data via the internet to study AD risk. The latest MindCrowd cohort has an average monthly recruitment rate of 901 Hispanic/Latino adults over age 40. Consistent with the general U.S. population, 19.5% of the current MindCrowd cohort over age 40 identifies as Hispanic/Latinos, with countries of origin similar to the general Hispanic/Latino population, providing sufficient samples sizes for pursuing the proposed aims. In addition, the research proposed in this R01 application is innovative and rigorous because it utilizes an affordable version of the novel test that can be self-administered in-home and that is offered in English and Spanish, opening up alternative applications outside of primary care. Thus, the proposed research is significant because it offers a more universally applicable alternative to existing assessments used in AD care and research, which will lead to a clearer and more accurate understanding about AD.

NICHD - Eunice Kennedy Shriver National Institute of Child Health and Human Development

Project Summary Addressing the rising trends in maternal mortality and severe maternal morbidity (SMM) is a critical priority in the United States. About half of adverse maternal health outcomes were found to be attributable to preventable harm or unintended consequences arising from clinical practice and the system of delivering perinatal care. Significant resources are currently being invested to implement quality improvement (QI) initiatives in birthing hospitals across the country. There is great need to evaluate these efforts and demonstrate their effectiveness to reducing the burden of preventable SMM and maternal deaths. Virtually all QI initiatives in birthing hospitals use SMM as an outcome measure, but their evaluation is hindered by the need to risk-adjust SMM rates to control for differences in patient composition within and between hospitals. To date, 3 different research groups proposed obstetric comorbidity indices, yet all have significant limitations. The overarching goal of this study is to develop and validate a refined comorbidity index for obstetric patients that allows SMM rate comparisons across hospitals and adequate monitoring of QI initiatives in obstetrics. We will use Maryland’s unique, gold- standard, hospital-based, state-representative SMM Surveillance and Review data to identify a comprehensive list of comorbidities in patients with SMM events. Using electronic health record data from the Johns Hopkins Health System, we will employ variable importance estimation with machine learning techniques to develop the comorbidity index. Subsequently, we will ascertain its accuracy using receiver operating characteristic (ROC)/precision-recall (PR) curves and areas under the curve (AUC) for outcome discrimination and lowess- smoothed calibration plots. Also, we will compare the performance of the refined comorbidity index to predict SMM against that of previously published comorbidity indices. To further validate our refined comorbidity index and assesses its performance consistency across various sociodemographic groups, we will use national hospital discharge data from the Healthcare Cost and Utilization Project’s National Inpatient Sample. A Technical Advisory Group comprised of clinicians, community partners, patient safety experts, and certified medical coders will meet quarterly for data interpretation sessions. At the end of the study, we expect to have a refined comorbidity index developed in gold-standard data, with superior psychometric properties than the previously published comorbidity indices and validated in both EHR and national hospital discharge data. Our results will be disseminated in the peer-reviewed literature and through presentations at scientific meetings.

NSF

This project aims to serve the national interest by addressing the growing demand for skilled technicians in robotics and automation, critical to maintaining food security and supporting the manufacturing workforce. It plans to create an educational pathway that attracts and retains diverse students, preparing graduates for well-paying jobs in rural areas with limited opportunities. By aligning education with industry needs, the project will equip businesses to adapt to an increasingly automated future. Its innovative strategies, including industry partnerships and immersive summer institutes, will engage students, highlight career opportunities and provide industry-recognized credentials, demonstrating the significance of bridging educational gaps in advanced technologies. The project addresses the shortage of skilled robotics and automation technicians in the agricultural and industrial sectors through targeted approaches. The project goals include: (1) capturing student interest via immersive summer institutes, (2) increasing representation using evidence-based recruitment and retention strategies, and (3) reducing math anxiety through a pre-enrollment math jumpstart course. An introductory and advanced summer institute intends to provide hands-on experience and National Coalition of Certification Centers (NC3) certifications in entry-level robotics and automation. Faculty expertise will be strengthened through NC3 Teacher Certifications and professional development. The project plans to assess summer institutes' impacts on associate degree enrollment, pathway strategies on graduation rates, and the effectiveness of math jumpstart courses in reducing anxiety and boosting enrollment in math-heavy programs. Findings intend to offer data-driven insights to improve technician education and workforce development. This project is funded by the Advanced Technological Education program that focuses on the education of technicians for the advanced-technology fields that drive the Nation's economy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIAAA - National Institute on Alcohol Abuse and Alcoholism

Project Summary/Abstract People with fetal alcohol spectrum disorders (FASD) experience barriers to care and a lower quality of life (QOL). FASD- informed services and supports are lacking, especially during the transition to adulthood – a critical developmental period for QOL. The proposed project will develop and initiate testing of a scalable person-centered planning (PCP) intervention to support QOL for adolescents and adults with FASD. PCP is an evidence-based intervention for people with disabilities. Research suggests PCP is a good fit FASD; however, it has yet to be adapted or tested with this population. In this project, we will use rigorous implementation science frameworks to systematically adapt and test a PCP intervention for adolescents and adults with FASD. Given the importance of social support networks in PCP, we will also draw upon the growing literature and team expertise on social network interventions to inform the development and evaluation of the intervention. Consistent with other interventions in our lab, we expect the proposed intervention to leverage technology to offer scalable solutions to overcome current barriers to care. During the R61 phase of the project, we will use the implementation science framework “Intervention Mapping – Adapt” to carefully adapt the core principles and methods of PCP and social network interventions for FASD. This 6-step process involves a planning team of people with FASD and other stakeholders and careful attention to theory and logic models to guide adaptation decisions. Based on our preliminary logic models, self-determination theory is a strong fit with the proposed intervention that we are currently calling “Thrive.” Additional research activities in Aim 1 will also inform the planning group’s decision making as they refine logic models, determine intervention structure and components, develop materials, and finalize evaluation procedures. Specifically in Aim 1a, we will conduct individual and group interviews with adolescents and adults with FASD and members of their social networks to characterize key features of their support networks that may be amenable to intervention. Following initial production of intervention materials, we will complete two rounds of usability testing (5 participants per round) in Aim 1b to aid in refining intervention materials and evaluation procedures for the pilot randomized controlled trial (RCT) in the R33 phase. Following successful attainment of R61 milestones, we will conduct a type 1 hybrid effectiveness-implementation pilot RCT of the developed Thrive intervention (R33). This trial design involves gathering data on both effectiveness and implementation outcomes, which will help us optimize the intervention for future larger-scale trials and more rapid translation into community settings. We will recruit 60 adolescents and adults (ages 15-30) with FASD to participate in the pilot RCT, with random assignment to the 1) Thrive PCP intervention or 2) comparison group receiving social network and strengths assessments only. Although significance testing and effect sizes will be calculated, a larger emphasis will be placed on feasibility to guide the design of a fully powered larger-scale RCT R01 application. For example, in addition to the feasibility of the intervention itself, we will assess feasibility of recruitment and trial procedures, sensitivity of measures to intervention change, and intervention process. Our proposed PCP intervention has high potential to improve QOL of people with FASD at the critical transition to adulthood.

NSF

This Integrating Research and Practice project uses an iterative approach to develop a STEM tabletop role-playing game for informal science learning. The project supports the development of game materials, which include freely available rules and learning-centered adventures. The game targets players ages 15 and older and includes content from biology, chemistry, engineering, mathematics, and physics. Players acquire STEM content by engaging in gaming mechanics, player-driven customization, and claim-evidence-reasoning to resolve challenges and support scientific thinking. The project will also produce professional development material and workshops focused on student learning and informal learning settings. This project is informed by the game-based learning theoretical framework and uses descriptive data, observation, player artifacts, post-game discussions, playtest feedback, and follow-up interviews to examine the impact of tabletop role-playing games on informal STEM learning. The specific goals of this project will be examined through the following research questions: 1) What is the impact on participants' sense of STEM identity? To what extent does this impact differ among participant demographics? 2) In what ways can informal learning facilitators use an educational tabletop role-playing game to further their reach and impact? In what ways does facilitation align with or branch from facilitation of public engagement? How can facilitation be characterized as a model of informal education? 3) What factors support or inhibit the uptake of a tabletop role-playing game as a method of informal STEM education? This project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing everyone multiple pathways for accessing and engaging in STEM learning experiences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIAID - National Institute of Allergy and Infectious Diseases

PROJECT SUMMARY AND ABSTRACT Nontuberculous mycobacteria (NTM) cause chronic pulmonary infections in the elderly and those with immunosuppression or pre-existing lung disease. NTMs are intrinsically resistant to most classes of antibiotics, and patients require treatment with two or more antibiotics for at least 12 months. While phenotypic and genotypic AST antimicrobial susceptibility testing (AST) performed in clinical microbiology laboratories is used by physicians to select antibiotics, its many limitations result in delays and uncertainty in the treatment of NTM infections. Improved AST methods for NTMs are essential for advancing outcomes from these infections, whose burden in the US now exceeds that of tuberculosis. Transcriptomic AST is an exciting new approach that shows great promise in solving gaps in NTM AST. This K08 award proposes to develop rapid transcriptomic AST for identifying susceptibility to clarithromycin and imipenem for the effective treatment of Mycobacterium abscessus. Both aims will use a combination of RNA-Seq and the NanoString platform to develop and validate a 10-gene transcriptomic AST assay that uses multiplexed RNA quantification directly from specimens without the need for RNA amplification of purification. Clarithromycin resistance is mediated by multiple resistance mechanisms and requires a combination of genotypic and phenotypic AST that can take weeks to return. Aim 1 will develop a rapid transcriptomic AST method that detects inducible and acquired clarithromycin resistance in a single assay. The breakdown of imipenem (half-life 0.6 days) during phenotypic AST (3-5 days) can lead to false-positive AST results showing imipenem resistance and result in physicians not prescribing an effective antibiotic. Aim 2 will determine the true imipenem susceptibility of clinical isolates using time-kill assays and then develop transcriptomic AST to accurately predict imipenem susceptibility without false imipenem resistance due to antibiotic degradation. By developing transcriptomic AST for clarithromycin and imipenem, this project will allow the rapid and reliable selection of antibiotics critical for the effective treatment of Mycobacterium abscessus. Dr. Poonawala is a physician-scientist trained in infectious diseases and clinical microbiology dedicated to improving the diagnosis of mycobacterial infections. Dr. Poonawala will be mentored by Dr. Bree Aldridge (rational design of tuberculosis (TB) treatment combinations using quantitative measurements of antibiotic activity) and Dr. Charles L. Daley (evaluation of novel diagnostics and treatments for TB and NTMs). Dr. Rebecca Batorsky (bioinformatics), Dr. Reeti Khare (clinical microbiology of mycobacteria), and Dr. Linden T. Hu (diagnostic development and career advice) will form his scientific advisory committee. In developing transcriptomic AST to address gaps in the AST of Mycobacterium abscessus, Dr. Poonawala will gain skills in molecular diagnostic development, bioinformatics, and advanced antimicrobial susceptibility testing. Upon completion of this K08, Dr. Poonawala will be ready for an independent career in developing mycobacterial diagnostics.

NIMH - National Institute of Mental Health

Abstract Despite antiretroviral therapy (ART), HIV-associated brain injury (HABI) persists in over half of people with HIV (PWH), manifesting as chronic cognitive impairment. While HIV-1 primarily infects microglia, driving central nervous system (CNS) neuroinflammation, current preclinical models do not recapitulate the chronic, suppressed infection characteristic of the ART era. Furthermore, they do not capture complex patient genetics and multicellular, glial and neuronal, interactions in a scalable and efficient manner. To address this need for more physiologically relevant models, we propose the development of an AI-guided triculture platform comprising major CNS cell types. This platform will use induced pluripotent stem cell (iPSC)-derived microglia, astrocytes, and neurons, using both morphological profiling and other omics-based profiling to model HABI under ART suppression. AI/machine learning (ML)-driven analysis of cellular morphology, combined with multi-omic data integration, will facilitate rapid classification and prediction of microglial functional states and their impact on neuronal health. Leveraging Modulo's established triculture system, previously successful in yielding therapeutic candidates for amyotrophic lateral sclerosis/frontotemporal dementia (ALS/FTD) currently in Investigational New Drug (IND)-enabling studies, we will construct a scalable HABI model under ART suppression. Our objectives are to (1) develop and validate an HIV-infected, ART-suppressed triculture platform, utilizing AI/ML-driven morphological profiling to classify HABI-specific microglial states; and (2) comprehensively characterize this model through neuroinflammatory profiling, behavioral correlates, and integration with publicly available HABI patient datasets. We hypothesize that our combined computational lab-based triculture system can effectively model HABI pathophysiology under ART conditions, enabling both rapid disease state classification and identification of therapeutic targets. Through the integration of experimental and computational approaches, this platform will provide insights into HABI mechanisms and accelerate therapeutic development. We will disseminate this model to the scientific community through publication and collaboration. Connecting in vitro modeling with patient outcomes offers a powerful tool for investigating neuroimmune dysfunction in HIV and related neurological disorders. Successful implementation will yield a platform for modeling neuroHIV under ART suppression, advancing our understanding of disease mechanisms and facilitating the discovery of novel therapeutic strategies for PWH with cognitive impairment.

NSF

The NSF ECR Building Capacity of STEM Education Research (BCSER) program contributes to the NSF mission 42 U.S. Code Chapter 16 by building the US workforce undertaking STEM education research. The BCSER Individual Investigator Development in STEM Education Research (IID) track supports individual investigators who are experienced STEM education researchers to develop expertise in new areas that will contribute to advancing STEM education knowledge. STEM education research generates the knowledge, theories, and understandings on which viable strategies for improving U.S. STEM education and workforce outcomes are based. This study focuses on mathematical argumentation in the elementary classroom. It involves the development of a scalable tool to analyze and assess the quality of argumentation in elementary mathematics classrooms, combining AI, psychometrics, and argumentation theory. With two focused studies, it aims to improve learning for struggling students and enable large-scale analysis of classroom discourse in elementary mathematics contexts. This BCSER IID project will allow the PI to supplement their current expertise with new research skills to design and implement cutting edge STEM education research using modern methods and tools. The project will assist the PI to develop new expertise in three intersecting areas: psychometrics, argument theory, and technologies using Large Language Models (LLM) and AI. Specifically, the principal investigator will gain new expertise in classroom-based argumentation measures and argument mining techniques to develop an AI-supported tool for measuring mathematical argumentation in elementary classrooms. This project is supported by NSF's EDU Core Research Building Capacity in STEM Education Research (ECR: BCSER) program, which is designed to build investigators' capacity to carry out high-quality STEM education research. The project is also supported through a collaborative NSF activity with the Bill & Melinda Gates Foundation, Schmidt Futures, and the Walton Family Foundation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIDA - National Institute on Drug Abuse

PROJECT ABSTRACT Substance use disorder (SUD) and overdose deaths represent a national public health crisis. Recovery is the recommended outcome for individuals with SUD, however, access to treatment and recovery supports varies greatly across the U.S., and many who could benefit from them do not receive services in part due to stigma, difficulty navigating a complex service continuum, wait times, and costs. Peer support specialists (PSS) are individuals in recovery from a SUD who are trained, certified, and employed to assist and provide guidance to patients in various states of recovery. The prima facie practical value of peers in support roles is high, as they can engage individuals outside traditional boundaries and extend the reach of care beyond clinical settings. PSS lived experience may make them more relatable than other medical or social service staff. Moreover, peer support represents a mechanism that could advance long-term recovery at lower expense relative to services delivered by other licensed clinical personnel. Regrettably, the evidence for PSS services is relatively scant in part due to methods that are ill-fitted to measure the dynamic, behavioral, and interactive process of recovery across time and within a complex service continuum. Consistently, the existing literature points to the lack of a uniform taxonomy (job titles, service roles, job-related activities, work settings) as an impediment to advancing the research on PSS provider service. In response, the Developing an Index of Peer Support Specialist Work Settings and Activities study will identify the fundamental components of PSS service delivery providing the foundation for subsequent researchers to perform rigorous effectiveness research on the public health impact of PRSS service provision. The following Aims will be accomplished building upon two preliminary studies characterizing PSS work roles and activities: 1) conduct a psychometric review of Survey 2.0 and align survey constructs within a social ecological systems framework; 2) verify PSS work roles and activities within regional recovery networks; 3) authenticate the Peer Support Specialist (PSS) Work Settings and Activities Index. A dynamic team, jointly led by investigators and consultants within the Consortium on Addiction Recovery Science (CoARS) in collaboration with state and national PSS associations and credentialing bodies, offer assurance of the successful execution of these Aims. This proposed work is innovative as it seeks to shift the standard paradigm of research design and survey construction by engaging working PSS and researchers with lived experience of SUD in the co-creation of survey instruments grounded in social ecological system theory. The proposed work is significant as it addresses a key barrier to the accurate assessment of PSS service. Results will open the door for high-quality scientific exploration into the effectiveness of PSS service provision and inform the effective deployment of PSS interventions across regional service systems.

NIMH - National Institute of Mental Health

Abstract Significance: Skin-picking disorder (SPD), also known as excoriation disorder or dermatillomania, is a debilitating condition affecting approximately 3.5% of the population. It causes significant morbidity, including physical skin damage and profound impacts on quality of life due to shame, distress, and social withdrawal. Although evidence-based behavioral therapies like Habit Reversal Training (HRT) are effective, their utility is limited by high relapse rates, low accessibility, and challenges with adherence. To address these gaps, this Phase I project seeks to adapt an existing wrist-worn gesture detection device (Keen2) and integrate it with a novel proximity-sensing wearable patch to assist in awareness and self-management of SPD. This project builds on HabitAware’s success with a similar system for trichotillomania, which demonstrated feasibility, acceptability, and preliminary efficacy. Hypothesis: A combined proximity-sensing patch and motion-detection wearable system will enhance the ability to detect and interrupt skin-picking behaviors effectively. By increasing awareness of skin-picking behaviors through real-time feedback, the system will support users in engaging in therapeutic strategies like stimulus control and HRT. Specific Aim 1: Optimize the system’s acceptability, utility, and feasibility by conducting 1:1 interviews with 10 expert SPD clinicians and 10 adults with SPD. Feedback will guide refinements to the hardware design, app interface, and system functionality. Final design specifications will be reviewed with the same stakeholders to confirm acceptability and feasibility. Specific Aim 2: We will establish the system’s ability to detect skin-picking behaviors accurately by collecting gesture data from 10 adults with SPD in lab-based video-recorded sessions. This data will inform optimization of the motion-detection algorithm and proximity-sensing parameters. A working prototype of the wrist sensor and patch system will then be tested for accuracy with 10 additional adults with SPD during in-person sessions simulating real-world conditions. We aim to achieve acceptable true positive detection and false positives per hour, consistent with prior HabitAware data. Long-Term Goal: The development of a scalable and effective system for SPD will address a critical public health need, offering an accessible alternative to traditional behavioral therapy. Pending successful completion of this Phase I project, we will pursue a Phase II proposal to further refine the system and test its clinical efficacy in a field-based randomized controlled trial.

NIMH - National Institute of Mental Health

PROJECT SUMMARY/ABSTRACT Women constitute an estimated 20% of new HIV diagnoses in the United States, with the highest burden of cases among women in the Southeast. Low pre-exposure prophylaxis (PrEP) utilization among women presents a challenge to addressing the burden of HIV in the Southeast and ending the US HIV epidemic. Only an estimated 2% of the 170,000 women who could benefit from PrEP are using it. Low PrEP use among women in the US may be attributable to lack of awareness and beliefs that PrEP is not appropriate for women. Fewer than 15% of women with HIV risk indications are aware of PrEP. Many women who are aware of PrEP believe that it can only be used by men, or believe that PrEP is not appropriate for them due to low perceived HIV risk. Building on an existing website prototype and prior PrEP messaging research, we propose a web-based awareness raising and demand creation approach consisting of a website with tailored PrEP information and decision support disseminated through social media to women throughout the Southeast. In Aim 1 we will develop a replicable social media targeting approach optimized to engage women with indications of PrEP need. This will generate ad campaigns refined through focus group discussions followed by a social media targeting study to identify social media platforms and targeting terms for engaging women with PrEP need. In Aim 2 we will build the PrEP decision support website based on existing prototype content. To update website content, we will conduct a preference elicitation study to expand the site to address long-acting PrEP methods followed by user testing to refine the website with input from women throughout the Southeast. In Aim 3 we will conduct a pilot trial of the PrEP decision support website with 100 women recruited through social media to evaluate intervention feasibility, acceptability, and appropriateness and to explore intervention effects on PrEP interest and uptake. Women will be randomized to receive either the decision support website or a standard education website and linked to a PrEP finder site to facilitate connections to PrEP providers. We will conduct in-depth interviews with women receiving the PrEP decision support website to understand their experience of the intervention. If the intervention proves feasible and shows promise to promote PrEP interest and uptake, this study will lay the foundation for a larger randomized controlled trial to evaluate the intervention effect on PrEP uptake among women in the Southeast with indications of PrEP need. Ultimately, the PrEP decision support website and social media dissemination strategy may provide a wide-reaching approach to promote need- proportionate PrEP uptake among women.

NIGMS - National Institute of General Medical Sciences

Abstract Iterative chemical innovation plays an essential role in the study and treatment of disease. In an aging population and with antimicrobial resistance on the rise we could not be more dependent on state-of-the-art medicines to battle cancer and infectious disease. However, despite nearly two centuries of important progress in chemical synthesis the cycle time for discovering new medicines lies far behind the pace of evolutionarily acquired resistance. The existential threat posed by this lack of synthetic agility requires bold new strategies which contract the time for data collection and chemical optimization. The research described in this proposal leverages a conceptually novel framework which dramatically simplifies access to small molecules and the processes to impact prioritize their reactions with biomacromolecules. In fragmentation-first experimentation the fundamental fragmentation patterns which underlie chemical reagents define precise barcodes for scrutinizing the outputs of high-throughput chemical synthesis. In contrast to existing strategies which require per-product customized protocols, this approach connects chemical reaction analysis directly to the synthetic origin of a chemical product. The net effect is a dramatic reduction in opportunity cost associated with making new chemical matter and a concomitant contraction of the cycle time for new discoveries. The net effect is a shift in focus away from making molecules and toward finding new functions. Empowered by high- content access to chemical matter we will unify these approaches with methods to directly study the reactions of small molecules with proteins and bacteria ribosomes to identify more effective covalent inhibitors. Parallelized interrogation of biological targets will provide detailed structure interactivity data to iteratively inform molecular designs. A unifying feature of these approaches are that small molecules can be directly utilized to determine their biological activity without purification, thereby eliminating another slow step in the molecule making process. If successful, our proposed research program will dramatically shorten the timeline for developing reactive small organic molecules (covalent inhibitors) and reduce the material burden for exploring their structure reactivity relationships. Fundamental new characteristics in the design of reactive small molecules uncovered throughout the course of our investigations will contribute to our ability to innovate on the molecular scale.

NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases

PROJECT SUMMARY/ABSTRACT Transplant is a valuable treatment option for many people with kidney failure, but in order to receive a kidney, patients must first be referred to a transplant center and complete a process of physical and psychosocial evaluation. Nephrologists and dialysis organizations are increasingly incentivized to refer greater numbers of patients with kidney failure to transplant centers in an effort to improve equitable access to this treatment. Such efforts can also be expected to increase the number and clinical complexity of patients engaging in the evaluation process. However, many patients will not ultimately receive a kidney and the evaluation process itself can be demanding, opaque, and lengthy and can take an emotional and psychosocial toll for patients and families. As more patients are drawn into this care process, multiple national stakeholder groups have emphasized the importance of minimizing burdens and improving patient experience. However, efforts to improve this patient experience are hampered by a lack of validated measures. In recent years, leading professional societies, regulators, and patient communities have called for the development of patient-reported outcome measures of the pre-transplant process. The aim of the proposed work is to develop and establish the content validity of a Kidney Transplant Evaluation Patient Reported Experience Measure (KTE-PREM). In Phase 1 (concept elicitation), we will perform a structured literature review, analyze existing qualitative interview transcripts, and conduct focus groups with patients who were referred to a transplant center, their family members, and clinicians who care for these patients (including primary nephrologists, social workers, and transplant team members). Patients will be recruited from Northwest Kidney Centers (a large non-profit dialysis organization based in Washington state which typically refers patients to three regional transplant centers) and the University of Washington. These sequential steps will result in a comprehensive set of concepts potentially relevant to a KTE-PREM. In Phase 2 (concept prioritization), we will identify items most relevant to patients to be included in a KTE-PREM by conducting a national survey among patients receiving care at two large non-profit dialysis organizations (Northwest Kidney Centers and Dialysis Clinic, Inc) who were referred to a kidney transplant center. In Phase 3 (instrument construction and refinement), we will design a draft KTE-PREM and iteratively refine the instrument through cognitive interviews with a local group of patients who were referred to a kidney transplant center. The proposed work directly extends from Dr. Butler’s recent NIH/NIDDK supported research (K23DK129777), which has identified a need and opportunities to improve person centricity of the kidney transplant evaluation process. Following development of the KTE-PREM, additional funding will be sought for validation. We anticipate that this validated instrument will have applications in clinical, research, and policy work intended to measure and improve patient experience in the kidney transplant evaluation.

NIDA - National Institute on Drug Abuse

Abstract Comorbid anxiety disorders and substance use disorders (SUD) are associated with poor clinical and functional outcomes. Identifying solutions for the treatment of this comorbidity is critical to improving public health. Theoretical models, clinical trials, and policy support the use of treatments that simultaneously address both problems in clinically meaningful ways, as opposed to separate treatments for each problem, which can lead to poorer clinical outcomes and barriers to care. Digital therapeutics specifically designed for those with comorbid anxiety disorders and SUD are lacking and yet have the potential to increase access to evidence-based behavioral treatment that is currently inaccessible. Although digital interventions exist separately for anxiety disorders and for SUD, none have been developed to address the unique needs of the prevalent and high-risk population of those with comorbid anxiety/SUD. This study builds upon Dr. Wolitzky-Taylor’s innovative program of work in developing and evaluating CBT protocols for this comorbidity by adapting her treatment model to a digital platform. This study aims to develop and evaluate the preliminary efficacy of a digital therapeutic for comorbid anxiety/SUD, Anxiety Management Treatment for SUD (AMT/SUD). As a first step, although the intervention is framed transdiagnostically and relevant across the anxiety and substance use disorders, the target population will be those with mild to moderate cannabis and/or alcohol use disorder, as digital therapy is an appropriate primary modality for this SUD population. First, an iterative, human-centered design process will be used to develop the mobile application-based intervention. This will include a series of focus groups to improve upon a prototype of the application, development of the application, and a small open trial (n=8) to assess for usability and to identify and address any issues prior to the randomized clinical trial (RCT). Next, a pilot RCT will be conducted with adults (N=60) with comorbid anxiety disorders and SUD (recruited from the community and several clinics who serve this population but do not provide integrated care for both problems). Participants will be randomized to either (a) “AMT/SUD”, in which they will engage with the digital therapy (which will include the option for on-demand clinical coaching on the digital content) for 12 weeks, or (b) “SUD-track”, an active control condition in which participants will be instructed to engage with Quitzilla, a publicly available substance use (and other behavior) tracking/monitoring app with motivational content, for 12 weeks. Participants will be assessed on treatment acceptability at post-treatment, and on anxiety and substance use outcomes at baseline, and 3- and 6-mo follow-ups. Following the RCT, additional patient focus groups will be conducted to inform additional refinements to the AMT/SUD mobile application-based CBT program. This digital therapeutic has the potential to make a substantial public health impact.

NIAAA - National Institute on Alcohol Abuse and Alcoholism

PROJECT SUMMARY Background. Firefighters are repeatedly exposed to potentially traumatic events and many experience posttraumatic stress (PTS) symptoms as a result. Over 50% of firefighters report past-month heavy alcohol use and many use alcohol to “self-medicate” from symptoms of hyperarousal, intense negative affect, and insomnia that follow traumatic events. Transcutaneous auricular neurostimulation (tAN) of the vagus nerve has shown promise for alleviating symptoms of PTS and opioid withdrawal symptoms but its effects have yet to be tested in a sample of firefighters with alcohol use disorders (AUD) and co-occurring PTS symptoms. Aims. We will collaborate with a firefighter Community Advisory Board to develop a culturally informed, Phase II randomized clinical trial (RCT) protocol testing tAN as an intervention that may reduce PTS symptoms driving heavy alcohol use for firefighters with AUD (Aim 1; Year 1). We will then conduct a feasibility trial of the protocol (Aim 2; Year 2; N = 20) using the Sparrow device—a patient-administered, ear worn device that delivers electrical stimulation to branches of the vagus and trigeminal nerves—to evaluate the acceptability and feasibility of the protocol, and the appropriateness of the tAN intervention for firefighters with PTS/AUD. Using data from the feasibility study, we will complete an FDA pre-submission with the revised trial protocol to support a PTS/AUD indication for Sparrow Ascent, finalize the protocol with FDA feedback, and write an R01 application for a fully powered Phase II RCT (Aim 3; Year 3). Methods. The feasibility trial will recruit firefighters who engage in heavy drinking, have at least a mild AUD, and report above-average PTS symptoms. Participants will use the Sparrow device for at least 1 hour/day for 5 days/week throughout the 4-week treatment phase, but may use the device more often if they wish. Participants in the active tAN condition (n = 10) will receive therapeutic stimulation from Sparrow; active sham participants (n = 10) will feel stimulation at the trigeminal site only, but below a therapeutic level. They will complete daily measures of traumatic event exposure (number and type), PTS symptom severity, alcohol use (standard drinks) and motivations (trauma-related drinking), and audio journals capturing their experience with symptoms and the device (e.g., helpfulness). Additionally, wearable sensors will record heart rate, heart rate variability, and sleep data throughout the intervention phase. Assessments immediately following treatment (Week 4) and one month later (Week 8) will measure protocol feasibility and tAN’s clinical effects outcomes including insomnia, mental health symptoms, and quality of life. Outcomes. The primary feasibility outcome is the mean of protocol ratings on the Feasibility of Intervention Measure. Secondary feasibility outcomes include ratings of protocol acceptability (Acceptability of Intervention Measure) and Sparrow Ascent appropriateness (Intervention Appropriateness Measure). Exploratory clinical outcomes include reductions in PTS symptom severity scores and heavy drinking events.

NIDA - National Institute on Drug Abuse

Project Summary Over 81,000 Americans died from opioid overdose in 2023. Opioid overdose and opioid use disorder (OUD) impose significant societal and economic burdens, making sustained OUD treatment a critical public health priority. Buprenorphine, an evidence-based therapy for OUD, reduces overdose and mortality risks with >6 months of therapy. Yet, >50% of patients discontinue it within 6 months of initiation, increasing relapse and mortality risks. Primary care providers (PCP) prescribe >60% of buprenorphine prescriptions and are expected to prescribe more following elimination of the federal waiver requirement, highlighting their role in treatment retention. Although PCPs may recognize some patients at risk of discontinuation, they face time constraints, competing demands, and a lack of systematic clinical decision support (CDS) tools to integrate multi-faceted risk factors to efficiently identify patients at high risk of buprenorphine discontinuation. Accurate prediction of buprenorphine discontinuation can better inform tailored interventions, such as long-acting injectable buprenorphine and peer recovery support, to improve retention and outcomes. Prior studies using traditional regression-based methods have identified individual risk factors of buprenorphine discontinuation; however, little is known about whether these single factors accurately predict such risk. In addition, using these methods to predict buprenorphine discontinuation proves to be challenging because of their limited ability to handle complex relationships between predictors and outcomes. Machine learning offers an alternative, uncovering hidden patterns in complex data and generating precise prediction algorithms and risk stratification subgroups to guide clinical care and interventions. Our prior work has successfully applied machine learning to claims data to identify commercially insured patients at high risk of buprenorphine discontinuation. Leveraging our prior work, we propose to develop and evaluate a machine-learning buprenorphine care discontinuity prediction e-tool (BUP-CARE) for PCPs within healthcare systems to identify patients at high risk of buprenorphine care discontinuity. We have 2 specific aims. Aim 1 will use OneFlorida+ electronic health records (EHR) data from 2014 to 2025 in the PCORnet Common Data Model to develop and validate machine-learning prediction algorithms to identify patients at high risk of buprenorphine discontinuation. We will expand our previous work by incorporating advanced deep learning (e.g., recurrent neural network) for risk prediction and by including social determinants of health as predictors. Aim 2 will identify barriers and facilitators for developing a BUP-CARE CDS tool to alert front-line PCPs for patients at high risk of buprenorphine discontinuation. We will use an iterative user-centered design approach to enhance BUP-CARE’s functionality and usability. Our proposed research is highly innovative and clinically relevant in its use of a machine learning- based CDS tool to guide clinical practice and tailor evidence-based interventions, thereby optimizing resource allocation and reducing patients’ buprenorphine care discontinuity.

NHLBI - National Heart Lung and Blood Institute

PROJECT SUMMARY Candidate’s Long-Term Career Goal: Dr. Elizabeth Munroe’s career goal is to become an independent physician-scientist leading novel clinical trials to improve the early management of critically ill patients. Clinical Problem to be Addressed: Intravenous fluids are a core component of sepsis management. Yet, administering both too much and too little fluid can cause harm, and the optimal fluid volume to prescribe is often unclear. Traditional clinical trials miss the critical window of initial fluid resuscitation and use one-size-fits- all approaches to fluid resuscitation. Furthermore, like most sepsis research, fluid trials have largely excluded patients who develop sepsis in the hospital (hospital-onset sepsis), an important and distinct population that experiences two-times higher mortality than patients with community-onset sepsis. Specific Aims: In this K23 proposal, Dr. Munroe aims to 1) understand the impact of initial fluid volume on outcomes in patients with hospital-onset sepsis through an electronic health record (EHR)-based cohort study, 2) develop a personalized, physiology (stroke volume) guided approach to initial fluid resuscitation for patients with hospital-onset sepsis, and 3) conduct a pilot pragmatic clinical trial comparing personalized, stroke volume guided initial fluid resuscitation vs usual care during rapid response evaluations. Candidate Background: Dr. Munroe is a clinical instructor in Pulmonary and Critical Care at the University of Michigan and current NHLBI NRSA F32 awardee. She will be promoted to Assistant Professor, not contingent on the outcome of this application. She is recognized as a rising star in the field of sepsis, with 6 first-author publications, 8 conference presentations, and 5 national invited lectures. Career Development Plan: Through this project, Dr. Munroe will build on her expertise in sepsis management and health services research to gain expertise in 1) EHR-data extraction, 2) implementation science-based intervention design and evaluation, and 3) pragmatic clinical trial design, execution, and analysis. Her 5-year training plan carefully pairs her training and research aims and is further supported by curated coursework and career development activities that will position her for successful transition to independence. Mentors: Dr. Munroe’s primary mentor, Dr. Hallie Prescott, is a sepsis expert who has mentored 5 clinician- scientists on K-series/career development awards. Dr. Munroe and Dr. Prescott have an excellent track record of success, working together since 2020. Dr. Munroe will receive complementary support from co-mentors: Dr. Michael Sjoding (EHR-based data science), Dr. Stephanie Parks Taylor (implementation science), and Dr. Robert Hyzy (clinical trials), as well a national advisory team with deep expertise in pragmatic clinical trials. Deliverables: Completing these aims will advance our understanding of fluid resuscitation in hospital-onset sepsis, generate preliminary data to compete for R-series awards for follow-up trials, and uniquely position Dr. Munroe to lead novel clinical trials of early interventions in critical care.