Love Data Week 2026, co-hosted by Laupus Health Sciences Library and Joyner Library, celebrates innovative work and fosters meaningful conversations around data in research, education, and community engagement. All events, except for the AI workshop, will be held virtually from February 9-13, 2026. We invite you to join us!
Innovative Data for Assessing Social Determinants of Health for You to Love
Date: Monday, Feb 9, 2026
Time: 12:00 PM – 1:00 PM
Join this session (Meeting ID: 229 624 376 650 6; Passcode: V7wb9C7b)
Abstract: Data on social determinants of health have been notoriously challenging to measure, and we are often relegated to secondary data to assess them. Using examples from the extant research literature and from the presenter’s own research studies and others, this presentation will showcase how data from unexpected sources can be used for population health surveillance and example. With an emphasis on socioeconomic position as a social determinant of health, we will discuss how everyday data outside of the health field, such as credit scores, public data sources, and even virtual reality, can be used in health studies.
Dr. Lorraine Dean, Associate Professor in Epidemiology, Johns Hopkins Bloomberg School of Public Health
Dr. Dean is a social epidemiologist, and her work focuses on privilege and health, with a specialty on identifying new metrics for assessing indicators of socioeconomic and racial privilege. She is co-author of the newly released book Power, Privilege and Public Health in the United States: Theory and Practice. She has led several studies as PI of NIH, Robert Wood Johnson Foundation, Center for AIDS Research, and institutional grants. She holds a doctorate from Harvard School of Public Health and was a J. William Fulbright program awardee to Venezuela.
Monday, Feb 9
Dr. Alexandre Rezende Vieira, School of Dental Medicine
Join this session (Meeting ID: 272 366 140 571; Passcode: sL2pe9HE)
Abstract: Currently, there is a massive production of unnecessary and suboptimal systematic reviews and meta-analyses. Given the major prestige and influence these types of studies have acquired, the large number of systematic reviews being produced can be harmful. Instead of promoting evidence-based health care, these publications often serve mostly as easily generated publishable products.
Tuesday, Feb 10
Dr. Alexander M. Schoemann, Department of Psychology
Join this session (Meeting ID: 287 639 814 747 0; Passcode: zX9Xr9oA)
Abstract: Many of the constructs we study cannot be directly observed, instead these latent variables must be inferred from other measured variables. For example, we cannot directly observe an individual's level of burnout, rather it is estimated based on responses to multiple variables. In this session we will discuss methods to assess and estimate latent variables. We will discuss different measurement strategies, and models for estimating latent variables including exploratory factor analysis, confirmatory factor analysis and structural equation models.
Dr. Hui Bian, Office for Faculty Excellence
Join this session (Meeting ID: 243 233 648 950 3; Passcode: f9bS3RN7)
Abstract: A Randomized controlled trial (RCT) is a type of experimental design used in clinical and intervention studies to test the effectiveness of a treatment, program, intervention, or experiment. This workshop will introduce the concept of RCTs, including internal validity, power analysis, randomization, blinding, and data analysis. A published RCT research paper will be discussed in detail. Power analysis and block randomization will be demonstrated using R.
Download both R and RStudio:
R for Windows: https://cran.r-project.org/bin/windows/base/
R for Mac: https://cran.r-project.org/bin/macosx/
RStudio: https://posit.co/download/rstudio-desktop/
Please go to https://myweb.ecu.edu/bianh/workshop.html to get workshop materials.
Dr. Carmen Cuthbertson, Department of Health Education and Promotion
Join this session (Meeting ID: 276 734 428 050 9; Passcode: qJ99PH2f)
Abstract: Physical activity is widely recognized to be beneficial for health and can be measured in many ways. One common way to measure physical activity is to track steps per day. This presentation will describe how the 10,000 steps per day goal developed and review new research that may suggest a more evidence-based target. Two studies that I conducted on steps per day and the risk of diabetes and cancer will be highlighted and placed into context with the ongoing research on steps per day and health outcomes.
Wednesday, Feb 11
Chris Motteler, ITCS
Join this session (Meeting ID: 253 238 759 061 6; Passcode: sn9Nq3HY)
Abstract: Learn practical shortcuts and best practices to make REDCap work smarter for you! This session covers essential features, time-saving tips, and ways to streamline your projects. Perfect for beginners and those looking to sharpen their skills..
Dr. Chandra Speight, College of Nursing; Dr. Olga Smirnova, Department of Political Science
Join this session (Meeting ID: 268 865 085 935 7; Passcode: Jf3YV9iv)
Abstract: Crowdsourced data on illicit market drug purchases offer unique opportunities to understand trends in drug use and inform clinical and public health policy interventions. This session will explore challenges and opportunities related to analyzing data from an international crowdsourcing platform that collects data on "street drug" purchases. We will discuss practical issues including coding data from diverse countries; stratifying information relevant to research questions; and managing inconsistencies in spelling, drug names, and reporting practices. Attendees will gain insight into strategies for transforming crowdsourced reports into actionable research findings while maintaining compliance with data ownership requirements.
Dr. Nic Herndon, Department of Computer Science
Join this session (Meeting ID: 296 535 938 219 2; Passcode: 8JZ2f4NC)
Abstract: There are many challenges in implementing a system for automatic document processing of printed documents, such as poor data quality and inconsistency, different language and structure changes, limited data for training machine learning models, and sensitive content that requires special handling for privacy reasons. Overcoming these challenges requires a combination of advanced technologies, such as optical character recognition, natural language processing, machine learning, and human support and expertise. This talk highlights how important it is to solve these problems and their potential impact.
Thursday, Feb 12
Dr. John Hanna, Brody School of Medicine
Join this session (Meeting ID: 212 493 166 706 3; Passcode: sK34RC6c)
Abstract: This session will trace the evolution of how healthcare systems use data - from rule-based decision support to advanced predictive analytics and generative AI, and now into agentic AI workflows. We’ll review the current state of AI in healthcare, examine the data-governance, technical and ethical considerations, and discuss how health systems are maturing their data practices to responsibly deploy agentic AI.
Dr. John Hanna, Brody School of Medicine
Location: Laupus library, 2502G (In person)
Abstract: In this interactive workshop, participants will explore how agentic AI workflows can be constructed to solve real-world healthcare operations and data-driven challenges. No code is required: attendees will experiment with designing agentic workflows triggered by data events and iterate through simple workflow examples. By the end of the session, they’ll have hands-on experience in mapping a healthcare operational pain point, defining a data-driven agentic workflow, and prototyping an agentic solution.
Friday, Feb 13
Dr. Chukwudi Sunday Ubah, Brody School of Medicine
Join this session (Meeting ID: 297 509 188 468 4; Passcode: y6mK2br9)
Abstract: This work is particularly meaningful as it supports alumni engagement, reunions, advancement initiatives, and opportunities for giving back. Most importantly, it helps identify areas with gaps in care, which can guide future outreach and development efforts.
Dr. Rebecca Clark-Stallkamp, College of Education
Join this session (Meeting ID: 246 965 454 777 1; Passcode: Dp64LF3D)
Abstract: This presentation explores how autoethnography expands what “counts” as data by drawing from memory, emotion, personal artifacts, and lived experience. Using my recent autoethnographic study as an example, I will show how researchers can systematically collect, analyze, and interpret these rich forms of qualitative evidence to investigate complex organizational and educational phenomena. Participants will leave with practical strategies for identifying unconventional data sources and integrating them rigorously into research and reflective inquiry.
If you have any questions about the presentations and workshops, please contact:
Xiaolan Qiu qiux24@ecu.edu
Jamie Bloss blossj19@ecu.edu
Jeanne Hoover HOOVERJ@ECU.EDU
Allison Christine Kaefring kaefringa22@ecu.edu