Engagement in Research 101: Introduction to Engaging Patient & Community Partners in Research

Are you interested in learning about patient and community engagement and how it can benefit your research? Excited by the idea of engaging patient, community, or other partners in your research, but unsure about where to start? Want to know more about how to engage partners at different points throughout your study?

Engaging with patient and community partners who are impacted by your research can be instrumental to the success of your study. This online training will provide an overview of engagement in research, highlighting that engagement is not "all or nothing" or "one-size-fits-all", but instead encompasses a wide variety of low touch to high touch approaches that could be right for your study.

The session will cover common myths/misconceptions about engagement in research, benefits of and key considerations for engaging patient and community partners in research, and initial steps/existing resources you can leverage to begin engaging partners in your research.

Please note: This event may be recorded. Materials such as slides or handouts will be shared with documented attendees only. Attendance may be determined through Zoom meeting attendance reports.

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Engaging Patient, Community, and Other Partners in Your Research is a multi-part online training series. You may register for the entire series OR any single training session.

Part 1 will focus on the basics of research engagement, providing an overview of patient and community engagement and its benefits, debunking common myths and misconceptions, and providing considerations and next steps for incorporating engagement approaches into your research.

Part 2 will cover specific engagement methods, including consultative community feedback sessions, advisory boards, and working with patient and community partners as members of a research team.

Part 3 will focus on the nuances of building and maintaining partnerships, outlining best practices for developing and strengthening mutually beneficial partnerships and discussing common partnership challenges and solutions.

This training series was developed collaboratively with patient, community, and researcher partners and is co-sponsored by the UNC Lineberger Comprehensive Cancer Center and NC TraCS Institute.

Exploring high dimensional data - relationships amongst variables

The NC TraCS Biostatistics Seminar Series is appropriate for those with a basic familiarity with statistics. These seminars introduce topics not often included in STATS 101. In this seminar, Jeff Laux, PhD, will discuss how to look for relationships amongst multiple variables.

Please note: This event will not be recorded. Materials such as slides or handouts will be shared with documented attendees only. Attendance may be determined through Zoom meeting attendance reports.

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A Digital Health Behavior Intervention to Prevent Childhood Obesity: The Greenlight Plus Randomized Clinical Trial

This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:

Bill Heerman, MD, MPH
Associate Professor of Internal Medicine and Pediatrics
William K. Warren Foundation Chair in Medicine
Chief, Division of Academic General Pediatrics
Vanderbilt University Medical Center

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This course will be offered via Zoom, over two mornings (4/7/2025 & 4/9/2025).

This course introduces participants to discrete choice models. These econometric models are used to explain how people choose between discrete outcomes, such as mode of travel to work or type of treatment for pain. The course will cover the subset of discrete choice models known as random utility models, namely the multinomial logit and nested logit. These models are often used in disciplines such as economics, transportation, and public health. No prior knowledge of discrete choice modeling is expected. Hands-on exercises will be conducted in Python.

Why Take This Course?
Random utility models are used across many disciplines. They allow one to use regression techniques to model choices between multiple outcomes, something not possible with many other models. Unlike many other models of discrete outcomes, random utility models are interpretable—it is easy to see which predictor variables are associated with which choices. Random utility models are also consistent with rational economic theory, meaning that properly specified estimates can be interpreted as willingness-to-pay and transformed into dollar amounts to understand the welfare impacts of policy. This course will prepare participants both to estimate these models and to interpret and evaluate them when encountered in practice.

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Environmental Determinants of RTS,S Malaria Vaccine Efficacy in Children: Investigating Correlates of Protection and Perivaccination Influences

Join the Children's Research Institute for a hybrid seminar with Sahal Thahir, MD, Pediatric Infectious Diseases Fellow in the UNC Department of Pediatrics. Participate in the seminar either in person at 3116 Mary Ellen Jones Building (with lunch provided) or via Zoom.

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This course will be offered via Zoom, over two mornings (4/7/2025 & 4/9/2025).

This course introduces participants to discrete choice models. These econometric models are used to explain how people choose between discrete outcomes, such as mode of travel to work or type of treatment for pain. The course will cover the subset of discrete choice models known as random utility models, namely the multinomial logit and nested logit. These models are often used in disciplines such as economics, transportation, and public health. No prior knowledge of discrete choice modeling is expected. Hands-on exercises will be conducted in Python.

Why Take This Course?
Random utility models are used across many disciplines. They allow one to use regression techniques to model choices between multiple outcomes, something not possible with many other models. Unlike many other models of discrete outcomes, random utility models are interpretable—it is easy to see which predictor variables are associated with which choices. Random utility models are also consistent with rational economic theory, meaning that properly specified estimates can be interpreted as willingness-to-pay and transformed into dollar amounts to understand the welfare impacts of policy. This course will prepare participants both to estimate these models and to interpret and evaluate them when encountered in practice.

Register

Engagement in Research Nuts & Bolts: Specific Approaches for Engaging Patient & Community Partners in Research

There is no "one-size-fits-all" approach to engaging patient, community, or other partners in your research. Rather, there are a variety of engagement methods to suit your study's needs, your research team's capacity, and your partners' interests.

This online training will describe three common approaches for working with patient, community, and other partners in your research: 1) consultative community feedback sessions; 2) advisory boards; and 3) sustained collaboration with partners as members of the research team.

The session will cover considerations for choosing these specific engagement methods, as well as concrete processes and steps for implementing each approach. Participation in our Engagement in Research 101 training is not required to attend this session; however, some knowledge of engagement, whether from prior training(s) or personal experience, may foster deeper understanding of the material in this session.

Please note: This event may be recorded. Materials such as slides or handouts will be shared with documented attendees only. Attendance may be determined through Zoom meeting attendance reports.

Register

Engaging Patient, Community, and Other Partners in Your Research is a multi-part online training series. You may register for the entire series OR any single training session.

Part 1 will focus on the basics of research engagement, providing an overview of patient and community engagement and its benefits, debunking common myths and misconceptions, and providing considerations and next steps for incorporating engagement approaches into your research.

Part 2 will cover specific engagement methods, including consultative community feedback sessions, advisory boards, and working with patient and community partners as members of a research team.

Part 3 will focus on the nuances of building and maintaining partnerships, outlining best practices for developing and strengthening mutually beneficial partnerships and discussing common partnership challenges and solutions.

This training series was developed collaboratively with patient, community, and researcher partners and is co-sponsored by the UNC Lineberger Comprehensive Cancer Center and NC TraCS Institute.

This session will introduce the Patient Centered Outcomes Research Institute (PCORI) goals, funding mechanisms, and strategies for preparing a competitive proposal to PCORI.

Presenter
Michael Kappelman, MD, MPH
Professor of Pediatrics, Division of Gastroenterology, UNC School of Medicine
Adjunct Professor of Epidemiology, UNC Gillings School of Global Public Health
Director, Patient and Community Engagement in Research (PaCER) Program, NC TraCS Institute

Facilitators
Susan Pusek, DRSc
Director of Education Programs, NC TraCS Institute

Paige Gray, MPH
Research Project Manager, NC TraCS Institute

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A Phase 2 Trial of Pridopidine in ALS, Studied as a Regimen with the Healey Platform Trial

This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:

Jeremy M. Shefner, MD, PhD
Professor of Neurology
Barrow Neurological Institute

Learn More

CTQA Risk-Based Audit Plan and Self-Assessment Review

Join NRP for a hybrid session with Jamie Kauwell, Emily Jones, and Bree Williams from the CTQA office as they identify high risk areas to be audited by CTQA as part of the Risk-Based Audit Plan and review the potential benefits of using the available Self-Assessments.

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NC TraCS Data Science Lab Seminar Series: Evaluation of Large Language Models

Please join the TraCS Data Science Lab as Shawn O'Neil, PhD, MS, a TraCS Data Science Lab fellow and an assistant professor in the TISLab, discusses approaches to the evaluation and scoring of Large Language Models (LLMs), as well as how to understand and interpret these scores in AI literature.

Seminars in the NC TraCS Data Science Lab Seminar Series will cover a range of topics related to health care data science, clinical data, data engineering, and working in these areas at UNC-Chapel Hill. These hybrid seminars will be held on the third Tuesday of each month from 12:30-1:30 p.m. in the NC TraCS suite on the 2nd floor of Brinkhous-Bullitt or via Zoom.

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Strengthening Engagement in Research: Building and Maintaining Relationships with Patient & Community Partners

Meaningful partnerships with patients, community members, or other collaborators involved in your research are invaluable. Projects are set up for success when care is intentionally given to developing and strengthening partnerships over time.

This online training will describe best practices for building mutually beneficial partnerships. The session will also cover common challenges that researchers and patient, community, and other partners experience when working together, along with suggested solutions.

Participation in our Engagement in Research 101 or Engagement in Research Nuts and Bolts trainings are not required to attend this session; however, some knowledge of engagement, whether from prior training(s) or personal experience, may foster deeper understanding of the material in this session.

Please note: This event may be recorded. Materials such as slides or handouts will be shared with documented attendees only. Attendance may be determined through Zoom meeting attendance reports.

Register

Engaging Patient, Community, and Other Partners in Your Research is a multi-part online training series. You may register for the entire series OR any single training session.

Part 1 will focus on the basics of research engagement, providing an overview of patient and community engagement and its benefits, debunking common myths and misconceptions, and providing considerations and next steps for incorporating engagement approaches into your research.

Part 2 will cover specific engagement methods, including consultative community feedback sessions, advisory boards, and working with patient and community partners as members of a research team.

Part 3 will focus on the nuances of building and maintaining partnerships, outlining best practices for developing and strengthening mutually beneficial partnerships and discussing common partnership challenges and solutions.

This training series was developed collaboratively with patient, community, and researcher partners and is co-sponsored by the UNC Lineberger Comprehensive Cancer Center and NC TraCS Institute.

This short course will introduce you to the major ideas behind structural equation modeling (SEM) and equip you with the knowledge necessary to get started on your own analysis using this method. SEM is a valuable tool beyond traditional regression models due to its flexibility, as it allows researchers to test more complex relationships among variables and to account for measurement error in analysis.

Participants should be familiar with regression modeling before taking this course. Experience using R will be helpful but is not required.

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They are Large, but should they be in Charge? Exploring the Possibility and Implausibility of Large Language Models in Social Science Research

Take a glance through recent news or social media and you would be hard-pressed not to see mentions of chatbots and artificial intelligence (AI) methods aimed at generating text, images and other content. Recent work by Eloundou and colleagues (2023) explored the potential impact of these types of generative AI on labor markets, and survey research, specifically was among the top two most impacted industries. In light of this finding, naturally, we wonder: how will this tech change the work in our field? How might chatbot technologies or related software be leveraged to support, enhance, or expand our work by assisting with a common research approach within the social sciences: surveys. And even still, how might survey and social science, more broadly, contribute to the improvement of large language models (LLMs)? In this workshop we will describe how LLMs work and showcase some of the current ways that these models are being used within the survey research process chronicling their applications in the design, collection, and analyses of survey data based on a large-scale systematic review of the social science, AI and computer science literature. We will also discuss some limitations of this technology as it relates to applications within the survey research process. We will also pose some relevant ideas around how survey research can also contribute to the development and refinement of large language models. And we note that no part of this abstract was generated using a chatbot.

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This one-day course will be offered via Zoom only. Attendance is required as it will not be recorded.

Course Summary:
Statistical machine learning is an interdisciplinary research area which is closely related to statistics, computer sciences, engineering, and bioinformatics. Many statistical machine learning techniques and algorithms have proven to be very useful for various scientific areas. This course will cover a number of unsupervised learning techniques for finding patterns and associations in Big Data. These include dimension reduction techniques such as principal components analysis and non-negative matrix factorization, clustering analysis and significance analysis, and network analysis with graphical models. The main emphasis will be on the analysis of real data sets from various scientific fields. The techniques discussed will be demonstrated in R.

This course is intended for researchers who have some knowledge of statistics and machine learning, and want to be introduced to relatively more advanced statistical machine learning topics.

Prerequisite:
Participants should be familiar with matrix linear algebra, linear regression and basic statistical and probability concepts, as well as some familiarity with R programming.

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The NC TraCS Institute's new cycle of Clinical and Translational Science (CTS) Pilot funding has been announced. Proposals are due July 8, 2025.

First released in 2022, CTS Pilots are focused on translational science. In preparation for this cycle of CTS Pilots, NC TraCS is holding 1-hour information sessions for investigators interested in learning more about this funding opportunity. Join the CTS Pilot Program leadership to hear about this pilot funding opportunity and have your questions answered.

Presenters
David Peden, MD, MS
CTS Pilot Program Module Lead, NC TraCS Institute
Senior Associate Dean for Translational Research, UNC School of Medicine

David Carroll, PhD
Director of Research Funding Development, NC TraCS Institute

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The NC TraCS Institute's new cycle of Clinical and Translational Science (CTS) Pilot funding has been announced. Proposals are due July 8, 2025.

First released in 2022, CTS Pilots are focused on translational science. In preparation for this cycle of CTS Pilots, NC TraCS is holding 1-hour information sessions for investigators interested in learning more about this funding opportunity. Join the CTS Pilot Program leadership to hear about this pilot funding opportunity and have your questions answered.

Presenters
David Peden, MD, MS
CTS Pilot Program Module Lead, NC TraCS Institute
Senior Associate Dean for Translational Research, UNC School of Medicine

David Carroll, PhD
Director of Research Funding Development, NC TraCS Institute

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Data Visualization for Social Science Research

This course introduces modern visual data exploration and communication methods to social scientists with limited prior experience. Students will learn to effectively present data to diverse audiences across multiple formats. The course utilizes the R programming language, RStudio development environment, and the tidyverse suite of R packages—with particular emphasis on ggplot2—for data processing and visualization.

Students will develop skills to confidently explore data descriptively, communicate findings to both academic and general audiences, and refine model results for presentations and publications. The course emphasizes both clarity and aesthetic considerations in data visualization, while incorporating best practices for practical, efficient, and reproducible workflows. Through a unified toolset, students will learn to display visualizations effectively across web platforms, academic papers, reports, and presentations.

Prerequisites include a basic understanding of fundamental data and statistical concepts, as well as basic familiarity with the R language. No prior experience with the tidyverse or ggplot2 is required. The course materials will consist of a series of R Markdown chapters that will serve as our textbook, which will be made available to all participants.

For software and hardware requirements, we will be using Posit Cloud, a cloud version of R. This approach eliminates installation and troubleshooting time, allowing us to focus more on learning.

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Accelerate your ideas through customer discovery and market opportunity validation!

KickStart Venture Services is recruiting community startups as well as faculty, post-doctoral fellows, graduate students, and undergraduate students with innovations and an interest in commercialization to participate in their virtual NSF I-Corps program. They will teach you the principles of customer discovery to help you better understand the market potential of your innovation!

The National Science Foundation’s Innovation Corps Program (I-Corps) was launched in 2011 and has quickly become one of the world’s largest and most successful technology commercialization accelerators. The I-Corps regional program helps researchers and aspiring innovators determine if they are solving a real-world problem with true market opportunity. NSF’s I-Corps Program not only provides funding, mentoring, and networking opportunities to help commercialize promising technologies, it is offered at NO COST to the community.

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For more information about the I-Corps Program, visit KickStart Venture Services.