University of Illinois at Chicago
University of Illinois at Chicago: UIC INDIGO (INtellectual property in DIGital form available online in an Open environment)Not a member yet
21439 research outputs found
Sort by
Does simultaneous alloplastic temporomandibular joint reconstruction affect the accuracy of Le Fort I osteotomy?
No full textSimultaneous alloplastic temporomandibular joint reconstruction (ATMJR) with Le Fort I osteotomy (LFI) may be indicated when significant temporomandibular joint (TMJ) pathology accompanies dentofacial deformities. Currently, the impact of concomitant ATMJR on LFI accuracy is not known. The purpose of this study was to assess the influence of patient-fitted ATMJR on the accuracy of simultaneous LFI. In this retrospective cohort study, patients undergoing LFI with and without ATMJR were enrolled. Preoperative and postoperative cone-beam computed tomography was analyzed using regional voxel-based registration. The primary predictor variable was use of ATMJR, and others included impaction at the maxillary central incisor (U1), age, and sex. The primary outcome variable was the mediolateral/superoinferior/anteroposterior absolute linear surgical error at U1 (U1AE). The secondary outcome variable was the three-dimensional surgical error at U1. In 20 subjects (eight ATMJR, 12 non-ATMJR), median U1AE ranged from 0.50 to 1.30 mm and median three-dimensional surgical error from 1.37 to 2.17 mm. ATMJR was associated with higher anteroposterior U1AE (median difference 0.8 mm, P = 0.012) and under-impaction (mean 0.86 mm, P = 0.036). Simultaneous ATMJR is associated with greater anteroposterior surgical error and a tendency towards under-impaction. Appropriate case selection and planning modifications should be considered as appropriate.</p
How to conceptualize, implement, and build on research initiatives in direct partnership with community members: An example from the field
No full textThis research was presented to the 2025 annual meeting of the Healthcare Systems Research Network. It presented a case study of community based participatory action research (CBPAR) performed in partnership with Advocate Health in Chicago, focused on racial inequities in the diagnosis of long COVID with community meetings and an advisory group of community leaders. The research informed recommendations for future CBPAR and also how to continue raising awareness about long COVID.</p
<b>Strengthening Health Systems for NCD Care in LMICs: Examining Pharmaceutical Industry Multisectoral Partnerships Beyond the Provision of Medicines</b>
No full textNoncommunicable diseases (NCDs) pose a major global health challenge, with 77% of NCDs-related deaths occurring in low- and middle-income countries (LMICs). Weak health systems and system barriers worsen inequities in NCDs management, hindering progress toward the Sustainable Development Goals (SDGs). In response, international organizations like the WHO and UN have called for multisectoral collaborations, including private sector engagement.The pharmaceutical industry is increasingly acknowledged for its potential to contribute to addressing these system challenges and strengthen health systems. In the current state, there is evidence suggesting that the pharmaceutical industry recognizes the value of strategic multisectoral partnerships and has initiated efforts in this area. However, significant practice gaps remain, including limited insights into the industry’s conceptual understanding of health equity, health system strengthening, and multisectoral partnerships, as well as its motivations and current approaches to partnership design. Existing research also provides little business-specific evidence or recommendations for future industry partnerships.This research aims to address these gaps by examining and informing the pharmaceutical industry’s approach to serving as a health system partner in LMICs. Through real-world examples of industry-led strategic multisectoral partnerships as well as insights from industry executives and health systems, the research seeks to answer three key questions: (1) What is the context for pharmaceutical industry partnerships with health systems to improve NCD care in LMICs? (2) How does the industry currently design these partnerships? (3) How can the industry improve its partnership approaches to enhance equitable NCD care?This research was guided by a conceptual framework based on the Bergen Model of Collaborative Functioning (BMCF), enriched with constructs from R = MC², Collective Impact, and the Social Ecological Model. The framework examined partnership context, inputs, throughput, and outputs, providing a comprehensive lens for understanding and improving pharmaceutical industry collaboration with LMIC health systems.An exploratory, multi-method, industry-level case study design was employed, focusing on four sub-units. Health system perspectives were included as an external unit to provide a more comprehensive and diverse view of the industry’s partnership efforts.Data collection included document analysis and semi-structured interviews with pharmaceutical executives and health system representatives. Findings were derived through integration across industry sub-units and triangulation with health system perspectives.By revealing evidence from real-world practice and proposing a mutual value-loop model for future partnership design, this research provides an initial step toward guiding the pharmaceutical industry to invest in and position itself as a health system partner. In doing so, it highlights how long-term business interests can be aligned with global health objectives in addressing system-level challenges and improving equitable NCD care in LMICs. Ultimately, such efforts contribute to the broader goal of “ensuring healthy lives and promoting well-being for all”, as outlined in SDG 3.</p
Centering and Advancing Health Equity within a Federal Maternal and Child Health Initiative: A Case Study of the Maternal, Infant, and Early Childhood Home Visiting Program
No full textAdverse maternal and child health outcomes affect women and infants across all racial and ethnic populations, with a disproportionate burden of loss among Black and Indigenous families. The study presents racial and ethnic disparity data. The intent is not to imply there is a White normative standard for maternal and child health outcomes, but merely to highlight the current gaps across populations. Health equity calls for us to eliminate disparities and improve the health of all people. The term “at-risk” is used only when describing the original language of program legislation, when it is in a direct quote, and when it is critiqued as a stigmatizing label for families and communities.</p
Risk, Adultification, Messaging, and Protection Scale (RAMPS): The development of a measure for Black girls
No full textAdultification, protection, and stereotyping of Black girls and their associated sexual and reproductive health risks are understudied concepts that are challenging to measure. This study developed and validated the Risk, Adultification, Messaging, and Protection Scale (RAMPS), designed to assess the relationship between sexual development, adultification, messaging, and protection, which are constructs of the Becoming a Sexual Black Woman framework. Preliminary items were derived from qualitative interviews with Black girls aged 9-18 years old. Adolescent responses (N = 575) to the RAMPS were subjected to several analyses to evaluate the measure's psychometric properties. Exploratory and confirmatory factor analyses (CFA) guided by the Becoming a Sexual Black Woman theory were used to test item fit; correlations between the refined measures and theoretically relevant measures were examined for validity; and measurement invariance of the RAMPS was evaluated across three age groups. CFA demonstrated a strong fit for a 3-factor model. The interpretation of the measure was fully invariant across age groups. Findings indicated that the RAMPS represents a valid framework for measuring factors impacting Black girls' sexual development. The final 12-item measure demonstrated respectable to very good internal consistency-adultification (α = .81, very good), protection (α = .76, respectable), messaging (α = .78, respectable), and total protection (α = .80, very good). This paper presents psychometric information about the RAMPS and the full set of items. The next steps will be to validate the measure within a larger sample and to explore its correlation with sexually transmitted infections and HIV risk.</p
Action Learning Brief: Approaches to Community Engagement and Its Role in Advancing Health Equity
No full textThis document is the second brief in a three-part action learning series examining community engagement within the Building Healthy Communities COVID‑19 Response, Recovery, and Resiliency Initiative led by the Cook County Department of Public Health. It summarizes how community-based organizations, technical assistance providers, and CCDPH defined and practiced community engagement, highlighting themes such as trust-building, gathering community input, cross-organizational collaboration, equity-centered approaches, capacity-building, and strategies that strengthened networks and advanced health equity in suburban Cook County</p
Neighborhood Deprivation Index for Year 2018 at Census Tract level for All US States
No full textThe NDI provides a measure of neighborhood deprivation at the census tract level, with higher values corresponding to more severe deprivation. Each state's values are analyzed independently. The NDI empirically summarizes eight census variables representing five domains: income/poverty, education, employment, housing, and occupation. The eight census variables include the percent of: (1) males in management and professional occupations; (2) crowded housing; (3) households in poverty; (4) female-headed households with dependents; (5) households on public assistance; (6) households with earnings less than $30,000 per year; (7) individuals with less than a high school education; and (8) individuals that are unemployed. The NDI is calculated using a principal components analysis (Messer et al. 2006), such that the NDI values produced depend on the study area that is used in the NDI calculation. Specifically, the NDI value calculated for a given census tract will differ if the NDI was calculated using, for example, all tracts in the county vs. all tracts in the state vs. all tracts in the United States. Prior to selecting, calculating, or using the NDI, it is critically important to define the study area and analytical goals so that the most appropriate study domain is used for the NDI calculation.</p
Great Lakes Center for Farmworker Health and Wellbeing Annual Report 2024-2025
No full textGreat Lakes Center for Farmworker Health and Wellbeing Annual Report for AY24-25. Includes information and data about the center, key personnel, research projects, outreach activities, center planning and evaluation, and additional publications / conferences throughout AY24-25. </p
Strengthening Disaster Response in Illinois: How Universities and Community Organizations Build Local Resilience
No full textExecutive SummaryIllinois faces mounting threats from both natural disasters and public health emergencies. The state has experienced a sharp rise in billion-dollar weather events and recorded over 40,000 deaths from COVID-19. This policy brief examines how universities and community organizations contributed to Illinois’s capacity for disaster response, drawing on interviews with 29 emergency professionals across 10 counties. The Federal Emergency Management Agency (FEMA) advocates a whole community approach, emphasizing collaboration among government agencies, private organizations, nonprofits, and individuals to enhance disaster resilience (Dai & Azhar, 2024; Kapucu et al., 2010). While many partnerships proved essential during the pandemic, persistent challenges remain. These include gaps in volunteer systems, resource disparities between rural and urban counties, and insufficient training for novel disaster scenarios.What did we learn from Illinois’s COVID-19 response?Illinois operates under a comprehensive framework for coordinated disaster response. The Illinois Emergency Operations Plan (IEOP) defines roles for state agencies, local governments, and nongovernmental partners to ensure coordinated crisis response (IEOP Plan, 2021). The IEOP supports a scalable response structure through the Incident Command System (ICS), allowing flexibility depending on the scope of the emergency (Flint & Stevenson, 2010). Our research identified five key themes from interviews with EMA directors, public health officers, nonprofit leaders, university emergency staff, and local officials:Universities were central to COVID-19 response logistics. The University of Illinois system played a leading role in coordinating testing, vaccine deployment, and data collection. UIUC developed saliva-based testing kits that enabled rapid, scalable testing statewide (Yu & Gerber, 2025).Community organizations ensured equitable resource distribution. Organizations like United Way leveraged deep community ties to identify and support vulnerable families, particularly in rural areas where government reach is limited.Cross-sector collaboration strengthened during the pandemic. Partnerships forged during prior emergencies (e.g., floods, snowstorms, droughts) expanded local response capacity and built sustained communication networks that remain active today (Røiseland & Trætteberg, 2024).Rural counties faced disproportionate resource challenges. Limited healthcare infrastructure, staffing shortages, and slower access to PPE created disparities in response capacity. Without pre-stocked supplies, many rural counties waited up to 30 days for state support.Informal networks helped but need formalization. Much collaboration depended on personal relationships rather than on formal agreements such as memoranda of understanding (MOUs), leaving agencies vulnerable during high-stress situations.What are the implications?The COVID-19 pandemic tested the limits of cross-sector collaboration in Illinois. While many agencies collaborated effectively for routine emergencies, a crisis of this scale required specialized expertise and much faster resource mobilization. The pandemic was a stress test and wake-up call: trust-based partnerships must be formalized into sustainable policies and shared procedures to withstand future emergencies.These lessons, especially given rural vulnerabilities, underscore the need to invest in infrastructure, partnerships, and local leadership before—not during—the next crisis.Recommended ActionsThis policy brief outlines five strategic pathways to enhance disaster preparedness and response for local government agencies.Update Response Plans and Training.Revise emergency operations plans regularly and implement scenario-based exercises for large-scale public health events—not just routine training.Strengthen the Medical Volunteer System.Establish a centralized, statewide volunteer registry with standardized onboarding, regular training, and clear compensation mechanisms (stipends, per diem, or hazard pay).Expand Resource-Sharing for Rural Counties.Support regional resource-sharing networks and strategically located stockpiles. Reduce administrative burdens rural counties face when requesting state resources.Invest in Emergency Leadership Training.Develop cross-sector programs emphasizing adaptive leadership, coordinated command, and inclusive decision-making (Li, 2018; Røiseland & Trætteberg, 2024)—including authenticity and emotional intelligence.Integrate Universities into Emergency Operations Plans.Assign universities specific roles in data analytics, healthcare logistics, shelter management, and communication (Yu & Gerber, 2025; Weber et al., 2018). Fund university-county disaster partnerships.</p
Neurolode 1.7.0
No full textThe Neurolode EEGLAB Plugin is a modular extension for EEGLAB that streamlines batch EEG analysis, spectral metrics computation, and data export. It integrates interactive GUI workflows with fully scriptable pop_* functions, enabling reproducible, large-scale processing without sacrificing usability. Exports EEG metrics as Excel, DAT, TXT, and ASC for sLORETA. Includes PCA reduction by 1, conversion between continuous and epoched data, and spectral analysis (Centroid, Kurtosis, Skewness, Spread). Features a modified BSS UI for enhanced batch and preprocessing workflows.Key features include:Batch-Automation Framework o An AutoBatch system that records, edits, and re-runs EEGLAB command sequences on multiple datasets. o Integrated GUI for reviewing and modifying stored processing steps (pop_functionsettings), making pipelines editable and reusable.Custom Spectral Analysis Suite o Built-in functions to compute Spectral Centroid, Spectral Spread, Spectral Skewness, and Spectral Kurtosis, each in time-resolved, frequency-resolved, or user-defined custom modes. o Channel- and epoch-level averaging options. o Automatic time-axis computation for accurate temporal alignment. o Export in .xlsx with fallback to .csv or .txt for compatibility.Flexible Data Export Tools o pop_export2format for exporting channel, frequency, or epoch-based metrics with rich metadata. o Deterministic, descriptive filenames for batch reproducibility. o Supports grand averages, individual channels, and arbitrary channel groupings.Preprocessing Utilities o convert2continuous for reverting epoched datasets to continuous format while preserving events. o pop_reduce_pca_by_one for progressive dimensionality reduction in ICA pipelines. o pop_epochfile for creating epochs from external event files or custom triggers.sLORETA Integration o eeglab2sloreta and pop_eeglab2sloreta for direct export to sLORETA, with robust file/folder handling and bad-channel removal.GUI Enhancements & Safety Improvements o Modernized parent menu (eegplugin_Neurolode.m) with single-point callback handling, error-resistant history integration, and STUDY-aware menu items. o Hardened GUI utilities (pop_MoveButton, pop_RemoveButton, pop_PrintFigure) to ensure stability and compatibility across EEGLAB versions.Intended Use: • Ideal for researchers running multi-subject, multi-condition EEG studies who need reproducible pipelines that bridge interactive exploration and fully automated batch execution. • Suitable for both single-trial exploratory analysis and large-scale statistical workflows.</p
Data sources:
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇