tutorials

The following tutorials are narrated PowerPoint presentations by UNC faculty, research staff and other colleagues.

They provide brief overviews of selected topics in Implementation Science, particularly focusing on research methods applied in dissemination & implementation research.

Qualitative Methods in dissemination & implementation research

Explore a useful method to help tailor evidence, inform a social marketing campaign and evaluate an implementation effort.

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Overview
(Catherine Rohweder, DrPH)
Bryan Weiner, PhD
Randall Teal, MPH
Catherine Rohweder, DrPH
QM-Overview 14 minutes
Customizing Evidence
(Catherine Rohweder, DrPH)
Alexis Moore, MPH QM-Customizing Evidence 8 minutes
Dissemination Case Study
(Joan Cates, PhD, MPH)
Joan Cates, PhD, MPH QM-Dissemination Case Study 8 minutes
Implementation Case Study
(Joseph Kalna)
Bryan Weiner, PhD QM-Implementation Case Study 13 minutes

Qualitative Comparative Analysis (QCA) in dissemination & implementation research

Learn about a mixed methods analytic technique that can be used to explain how factors work together to contribute to a positive outcome of interest.

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Overview
(Catherine Rohweder, DrPH)
Bryan Weiner, PhD
QCA-Overview 23 minutes
A Crisp Set Illustration
(Leila Kahwati, MD, MPH)
Heather Kane, PhD
Leila Kahwati, MD, MPH
Megan Lewis, PhD
Pam Williams, PhD
QCA-Crisp 18 minutes Best practices in the Veterans Health Administration’s MOVE! Weight Management Program
A Fuzzy Set Illustration
(Randall Teal, MPH)
Bryan Weiner, PhD QCA-Fuzzy 14 minutes Organizational Designs for Achieving Treatment Trial Enrollment: A Fuzzy-Set Analysis of the Community Clinical Oncology Program

Systems Science in dissemination & implementation research

Systems science methodologies provide a way to address complex problems, while taking into account the big picture and context of such problems.

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Social Network Analysis
(Bryan Southwell, PhD)
Bryan Southwell, PhD
Christine Bevc, PhD
No transcript 9 minutes
Agent Based Modeling
(Georgiy Bobashev, PhD)
Georgiy Bobashev, PhD No transcript 15 minutes

Structural Equation Modeling (SEM)

Structural equation modeling (SEM) is a family of statistical methods designed to test a conceptual model. Some common SEM methods include confirmatory factor analysis, path analysis and latent growth modeling. If you’re interested in learning more about using SEM in Implementation Science, check out our Implementation Case Study.

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Implementation Case Study
(Sandy Diehl, MPH)
Sara Jacobs, PhD
No transcript 15 minutes

If you are interested in a particular topic but don’t see it here, please let us know as we are continually developing new tutorials.