John Alexis Schneider

Global positioning system (GPS) data capture fine-scale spatial and temporal mobility, enabling more precise, individualized assessments of neighborhood exposures than residential-based measures. Despite growing use, there is little consensus on how to define and quantify GPS-based exposures, highlighting the need for theory-informed approaches. This study demonstrates how GPS data can enhance neighborhood exposure assessment, address spatial misclassification, and inform future research on mobility and neighborhood environments. We integrated theoretical frameworks from psychology, sociology, and geography into GPS-based research using data from 2 cohort studies: the Neighborhoods and Networks Study and the Trying to Understand Relationships, Networks and Neighborhoods among Transgender Women of Color Study. The final GPS analytic sample was 649 participants. We constructed GPS-based neighborhood exposure measures, including direct exposure to specific locations and neighborhood psychosocial exposures, and compared these metrics with conventional residential-based measures. We also derived GPS-based mobility measures to characterize individual mobility patterns. Global positioning system-based measures captured higher variability in neighborhood exposures compared with residential-based measures. Global positioning system-derived mobility measures further characterized individual mobility patterns, providing additional context for understanding exposure beyond residential location. Accounting for spatial and temporal dimensions offers a robust foundation for future studies with more precise, spatially relevant health interventions.

Government-funded research consortia are increasingly deployed as R&D policy instruments to accelerate scientific progress, empirical evidence, however, on whether these institutional arrangements generate knowledge-diffusion benefits beyond individual funding, and how those benefits are distributed, remains limited. Using the Justice Community Opioid Innovation Network (JCOIN), a large NIH cooperative agreement, as a quasi-experiment, this study examines two mechanisms: social influence (whether co-authorship ties to above-average-impact researchers predict a researcher’s own transition to above-average citation impact) and social selection (whether higher-impact researchers preferentially form ties with one another) within the consortium. A quasi-experimental comparison design contrasted JCOIN researchers (N=125) with matched non-consortium NIDA R01 grantees (N=210) across pre- (2016-2019) and post-consortium (2020–2023) periods. Autologistic Actor Attribute Models (ALAAM) tested social influence on field-weighted citation impact (FWCI ≥ 1.0), while Exponential Random Graph Models (ERGM) and Temporal ERGMs (TERGM) tested social selection in collaboration formation. A significant citation-impact contagion effect was identified within JCOIN but not in the comparison group, consistent with co-authorship ties serving as conduits for knowledge spillovers. Collaboration formation was governed by preferential attachment to high-standing researchers, institutional homophily, and research-standing homophily; gender homophily was present only in the early consortium period. Women in JCOIN had significantly lower odds of achieving above-average citation impact, net of network position. These findings indicate that cooperative R&D network structures can generate social influence effects on citation impact beyond what individual funding achieves, while also showing that access to network benefits is stratified by gender and prior standing. Funders and coordinating centers should monitor not only whether collaboration increases but also who gains access to high-impact collaborative opportunities.

Objective: To evaluate the effectiveness and implementation of a multicomponent intervention to address the burden of drug use–related infectious diseases and overdose in rural settings. Design: Single-arm hybrid implementation-effectiveness design. Setting: Rural area comprising the Illinois counties of the Delta Regional Authority. Participants: People who use opioids and/or stimulants nonmedically. Intervention: Expansion of community-based harm reduction services, capacity-building for opioid use disorder and hepatitis C treatment. Main Outcome Measures: Harm reduction service expansion intervention Reach, Effectiveness (injection equipment sharing), Adoption and Cost (per participant and budget impact analysis). Results: Three hundred six people who use drugs were enrolled. Of the 207 of who were not previously engaged in harm reduction services, 121 (59%) accepted referral and were retained in services at 6 months past study enrollment (intervention reach). In regards to intervention efficacy, among these individuals, 41 (35%) completed follow-up surveys; compared with their baseline self-report, there was a significant increase in obtaining sterile equipment from the harm reduction organization (43.9% vs. 68.3%, P = 0.03) and decrease in sharing injection equipment (46.3%–19.5%, P = .02). The harm reduction organization experienced an increase of approximately 100–550 program participants and an increase in service delivery area coverage from 1258 to 5509 square miles after intervention implementation (adoption). Cost per participant served by the harm reduction organization was $1486 per year, with annual budget impact to the program of $817 295. In regards to treatment capacity building, a total of 80 providers in the study area completed training in opioid use and/or hepatitis C management. Conclusion: The pragmatic evaluation of harm reduction service expansion supported by a suite of implementation strategies serves to inform the practical considerations and decision-making by community-based organizations seeking to increase services in rural areas heavily affected by substance use, overdose, and related infectious diseases.

The opioid crisis has generated widespread public attention and messaging. However, persistent messaging may contribute to message fatigue, i.e., feelings of exhaustion and boredom due to excessive and redundant exposure. This study investigates the prevalence of opioid message fatigue among American adults, its association with individual characteristics, and its connection with opioid use disorder (OUD) stigma and policy support for OUD treatment. A nationally representative cross-sectional sample of U.S. household adults aged 18+ (N = 1,022) were surveyed August 7-15, 2024. Multiple regression models examined individual characteristics associated with message fatigue, and the associations of opioid message fatigue with stigma about OUD and support for OUD-related public policies. On average, participants reported a moderate level of message fatigue (M = 2.75, SD = 0.85, range = 1-5). Fatigue varied significantly by gender, education, income, political identity, and life experience. Findings suggest higher message fatigue was associated with greater stigma about OUD (B = 0.09, p < 0.001) and lower support for OUD treatment policies (B = -0.32, p < 0.001). Future research should continue to examine the social and policy implications of OUD message fatigue and improve public health communication by anticipating and mitigating message fatigue through strategic planning.

Background: Diabetic kidney disease (DKD) accounts for 44% of new chronic kidney disease cases and is associated with significant morbidity and mortality. Although sodium-glucose co-transporter-2 inhibitors (SGLT2is) can reduce cardiorenal outcomes, current DKD staging relying on eGFR and albuminuria (KDIGO risk categories) leaves SGLT2is underutilized in clinical practice. A new biomarker-enriched, AI-enabled risk score (KidneyIntelX™; Renalytix, Inc.) was developed to predict a progressive decline in kidney function in patients with early-stage DKD. KidneyIntelX categorizes patients as low, intermediate, or high risk for disease progression, which can guide resource utilization, prescribing of drugs such as SGLT2is, and improvements in efficiency of care. We report a cost-effectiveness analysis comparing DKD patient stratification with KidneyIntelX to KDIGO by generating an incremental cost effectiveness ratio (ICER). Methods: The model adopted a U.S. Medicare perspective and consisted of patients with DKD in stages G1-3b using KidneyIntelX or KDIGO. A 10-state Markov state transition structure was employed over a lifetime horizon which includes DKD stages 1–5, dialysis, kidney transplant, cardiovascular (CV) death, and non-CV death. Transition probabilities and risk group distributions for KidneyIntelX and KDIGO were sourced from a KidneyIntelX validation study. Evaluation resulting from KidneyIntelX or KDIGO informed SGLT2i use in the model. Cost inputs included testing, medications, and office visit costs, as well as annual costs for each DKD stage, dialysis, and kidney transplant. Quality of life for each disease state was captured as utility values informed by literature. Results: The modeled use of SGLT2i directed by KidneyIntelX led to a reduction in kidney disease progression (ESKD) and CV events, as well as dialysis starts, dialysis crashes, and kidney transplants compared to KDIGO-guided treatment. KidneyIntelX patients also spent less time in DKD stages 4 and 5 and more time in 1 through 3b. KidneyIntelX led to cost savings of about $514 per patient and quality-adjusted life year (QALY) gains of 0.028, resulting in a negative ICER. Combining SGLT2i with MRA’s further increased per patient cost savings to $530 for Medicare participants. Conclusions: Wide deployment of KidneyIntelX in Medicare patients with DKD G1-3b is expected to be cost-effective compared to KDIGO from the Medicare perspective, with a negative, dominant ICER.

Background: Heavy cannabis use may impact neurocognitive functions, particularly prefrontal and limbic systems responsible for risk/reward processing and executive function, which are essential for certain health behaviors, such as HIV prevention. Rigorous research into the effects of cannabis on neurocognitive functions remains limited, particularly among populations with a high burden of HIV. Objective: This study aims to (1) evaluate associations between cannabis use and neurocognition, (2) evaluate associations between cannabis use and engagement in HIV status–neutral care outcomes (eg, pre-exposure prophylaxis persistence, viral suppression), and (3) assess whether cannabis use motivations modify associations between cannabis use and engagement in HIV status–neutral care outcomes. Methods: This longitudinal cohort study is enrolling a community-based sample of individuals aged 16 to 29 years residing in Chicago using multiple recruitment strategies. Participants complete 3 in-person assessments annually over 2 years that include (1) computer-assisted questionnaires, (2) neurocognitive assessments (functional magnetic resonance imaging, executive function tasks), and (3) biospecimen collection. Triangulation approaches combine objective and self-reported measures. Results: The Frontal Lobe Outcomes and Well-Being (FLOW) Study was funded by the National Institutes of Health in April 2023, with data collection commencing in October 2023. As of April 2026, 148 participants have been enrolled and completed baseline assessments, with 63 participants completing their first follow-up appointment and 4 participants completing their second follow-up appointment. Following a temporary administrative pause from March to August 2025 and subsequent federal review confirming regulatory compliance, the study resumed operations in July 2025. Recruitment is currently ongoing, with data collection expected to continue through June 2027. Preliminary analyses are pending completion of longitudinal data collection. Conclusions: This study addresses critical knowledge gaps by examining potential associations between cannabis use, neurocognition, and HIV. While geographic specificity, structural barriers, measurement challenges, and sample size constraints present some limitations, our methodological approaches—including longitudinal design, triangulation of both objective and self-reported measures, and rigorous neurocognitive assessments—strengthen the investigation. Findings will advance understanding of how cannabis use impacts neurocognition and HIV-related health behaviors, potentially informing targeted interventions that address both substance use and HIV transmission.

Background: Accurately predicting outcomes and stratifying risks remains a challenge in kidney transplant patients. The Pre-Transplant Risk Assessment (PTRA) predicts risk of early acute rejection (EAR) in deceased donor transplant recipients, enabling clinicians to tailor immunosuppression strategies using individual immune response risk. Objectives: We developed a cost-impact analysis of adding PTRA to the current standard of care to predict the risk of EAR compared with the current protocol-driven immunosuppression in standard-risk kidney transplant patients. Methods: A decision tree model evaluated 90-day and 2-year outcomes post kidney transplantation. PTRA testing stratified patients as either high or low risk for EAR. Reduced maintenance immunosuppression protocols were modeled in low-risk PTRA patients compared with standard protocol, reducing adverse drug event readmissions, cytomegalovirus infections, graft loss, and deaths with a functioning graft. An increased maintenance immunosuppressive regimen was modelled for high-risk PTRA patients, reducing acute rejections and graft loss. Results: The standard-risk population cohort consisted of 71.4% low-risk PTRA and 28.6% high-risk PTRA patients. The model generated per-patient cost savings of $358 in the first 90 days post transplantation and $13 234 per-patient over 2 years. If PTRA were used in all 14 468 patients falling into the standard risk immunosuppression protocol, $191 475 915 could be saved over 2 years at the cohort level. If PTRA were to impact induction immunosuppression protocols, per-patient savings would exceed $4000 over 90 days and $27 000 over 2 years. The definitions used for risk stratification and the assumed immunosuppression protocols for patient cohorts are generalized assumptions expected to align with most clinician approaches. We assumed that the reduction on clinical outcomes would be equivalent to the overall percentage of patients with expected treatment regimen impacts from PTRA. Variations in clinical decision-making regarding treatment pathways given PTRA risk stratification will influence the potential clinical impact. Conclusions: Risk stratification with PTRA utilization prior to kidney transplant in the standard-risk population could generate significant cost savings in the 90-day and 2-year time periods post kidney transplantation.

Background: Prostate cancer is one of the most common malignancies in men, and radiation therapy, most often stereotactic body radiation therapy or conventionally fractionated radiotherapy, is a standard curative treatment for advanced cases. Although genitourinary toxicity is a known side effect, with acute symptoms typically resolving and late toxicity causing lasting harm, individual risk varies substantially. However, no validated tool exists to predict patient-specific toxicity across radiation modalities, leaving treatment decisions to be made without personalized risk insights. Objective: The goal of this analysis was to estimate changes in cost and quality of life associated with reductions in late genitourinary toxicity attributable to personalized radiation therapy in individuals with prostate cancer. Implementation of PROSTOX ultra , a novel microRNA-based assay for toxicity risk assessment with stereotactic body radiation therapy, is expected to enable the personalization of radiation therapy, helping patients avoid toxic effects from specific types of radiation therapy. Methods: This study utilizes a hybrid decision-tree and Markov model approach to estimate the 5-year cost-impact and lifetime cost-effectiveness in prostate cancer patients of PROSTOX ultra vs current treatment standards that do not include toxicity risk assessment. High or low risk assessment influences whether patients receive stereotactic body radiation therapy, conventionally fractionated radiotherapy, or prostatectomy, impacting toxicity-related treatment costs and quality-of-life decrements. Results: Over 5 years, PROSTOX ultra patients totaled $47 683 in costs vs $67 298 with standard-care risk assessment. Cumulative savings over 5 years were $19 615 per tested patient. Over a lifetime, PROSTOX ultra was expected to save about $24 777 per tested patient while adding 0.24 quality-adjusted life-years compared with patients tested using standard assessment. Conclusions: Model results indicate that toxicity risk assessment with PROSTOX ultra would be cost saving over 5 years compared with standard risk assessment. Cost-effectiveness results show cost savings and quality-adjusted life-year gains over a lifetime, indicating that PROSTOX ultra would be a dominant strategy compared with treatment without risk assessment.