The goal of this FAES course is to introduce biomedical research scientists to R as an analysis platform rather than a programming language. Throughout the course, emphasis is placed on example-driven learning. Topics include: installation of R and R packages; command line R; R data types; loading data in R; manipulating data; exploring data through visualization; statistical tests; correcting for multiple comparisons; building models; and generating publication-quality graphics. No prior programming experience is required.
This is a free, 7-part, self-paced online course with instructional slide sets, readings, and guided activities.
- Part 1 provides an introduction and overview of the three kinds of randomized trials and their distinguishing characteristics.
- Part 2 considers the design of group-randomized trials (GRTs).
- Part 3 discusses analytical approaches to GRTs and individually randomized group-treatment trials (IRGTs).
- Part 4 explores important power and sample size considerations for GRTs.
- Part 5 provides examples of GRTs from the Health Care Systems Collaboratory, a project funded by the NIH.
- Part 6 reviews recent practices in GRTs and IRGTs based on literature reviews.
- Part 7 examines alternative designs to evaluate interventions in comparison to GRTs and IRGTs.
In this Methods: Mind the Gap webinar, Dr. Linda Collins discusses why behavioral interventions are important in many areas of public health, for example, smoking cessation, drug abuse prevention, treatment of obesity, management of heart failure symptoms, and promotion of physical activity.
Behavioral interventions are typically developed and evaluated using a treatment package approach, in which the intervention is assembled a priori and evaluated by means of a randomized controlled trial (RCT). Dr. Collins reviews an alternative approach called the Multiphase Optimization Strategy (MOST), an engineering-inspired framework for developing, optimizing, and evaluating behavioral interventions. MOST includes the RCT, as well as other empirical steps aimed at intervention optimization.
Research Domain Criteria (RDoC) is a research framework for new ways of studying mental disorders. It integrates many levels of information (from genomics to self-report) to better understand basic dimensions of functioning underlying the full range of human behavior from normal to abnormal.
RDoC Educational and Training Resources page includes links to RDoC office hours, webinars, and RDoC-influenced courses.
Interventions to change behavior have great potential to improve health and well-being. In this Methods: Mind the Gap webinar, Dr. Michie describes a method for specifying the "active ingredients" of interventions. Such a method allows data pooling to identify effective component techniques. She also presents a systematic method for developing interventions, linking a "behavioral diagnosis" of the behavior needing to be changed with general strategies and specific techniques.
In this Methods: Mind the Gap webinar, Dr. Jacob Bor reviews the theory behind regression discontinuity designs and their implementation, with a focus on examples in public health research.
Dr. Doug Luke provides a general overview of agent-based modeling (ABM) methods, and then discusses in more detail the utility of these methods for studying the design and implementation of new policies and practices related to chronic diseases, including obesity and tobacco control. The specific advantages of ABMs for dissemination and implementation science are also highlighted.
In this Methods: Mind the Gap presentation, Dr. Palmer addresses the relatively low performance of risk prediction models for breast cancer in Black women versus performance in other populations, and possible reasons for the observed disparity.
Boston University School of Medicine
During this webinar, Drs. Riley and Willis focus on scale-up of effective interventions both conceptually and empirically. They have recently contributed a chapter on scale-up to an edited volume focusing on Advancing Implementation Science in Cancer Control. The session includes approximately 25 minutes of comments from the speakers and 35 minutes for engaged discussion and Q&A with the audience.
NCI has developed two online resources for use in selecting instruments for various research questions: the Dietary Assessment Primer and the Measures Registry. Both are designed to provide knowledge transfer and facilitate adoption of best assessment practices. This webinar describes each of these resources with a focus on how we can minimize measurement error by opening up access to the best assessment methods.
Dr. Amy Kilbourne introduces the SMART design as well as other adaptive design variations to inform the development of adaptive interventions. Dr. Kilbourne explains the use of the designs in intervention trials, walks through their applicability to implementation studies, discusses differences between adaptive designs and adaptive interventions, and concludes with examples from her work of how adaptive designs have permitted the testing of implementation strategies.
This webinar introduces the SPADES platform which offers simple, uniform, and rapid ways for researchers and clinicians to collect, store, and analyze high resolution signals on physiologic, inertial, and location data. SPADES is a multi-tier, cloud-based service hosted on the highly scalable Amazon Web Services (AWS) platform.
In this Methods: Mind the Gap webinar, Dr. Jennifer Croswell demonstrates methods to critically assess the quality of published systematic reviews of clinical or public health interventions.
Part one of the two-part series, Measuring Success in Low-Income Nutrition Education and Obesity Prevention Programs, explores how to use the framework to evaluate nutrition education and obesity prevention programs.
Part two, Strategies and Tools for Measuring the Priority Indicators, highlights the seven SNAP-Ed priority indicators from the Evaluation Framework and shares practical examples of measuring healthy eating behaviors, physical activity, and reduced sedentary behaviors in low-income children and families.
In this Methods: Mind the Gap webinar, Dr. Monica Taljaard explains the unique characteristics of the stepped wedge cluster randomized design and its implications for sample size calculation and analysis, and discusses its strengths and weaknesses compared to traditional designs. Emphasis is on application, with examples in disease prevention and health promotion research.
In this Methods: Mind the Gap webinar, Dr. William Shadish reviews illustrative studies that demonstrate the direction such work is taking and the results that seem to be emerging in regard to nonrandomized control group designs, regression discontinuity designs, and interrupted time series designs.
This Methods: Mind the Gap webinar reviews the design and analysis considerations for assessing the implementation and impact of laws and policies on community, organizational, and individual-level outcomes.
Drs. Lori Ducharme, Hendricks Brown, and Brian Mittman review some of the key concepts discussed at the 6th Annual NIH Meeting on Advancing the Science of Dissemination & Implementation Research: Focus on Study Designs. Central to their discussion are the key issues for study design for implementation science, what works, and opportunities that remain ahead.
They are joined by Drs. Geoffrey Curran, Linda Collins, and Ken Wells in a wide-ranging discussion of common problems encountered by implementation researchers and four examples of study designs and the problems they address.
In this Methods: Mind the Gap webinar, Dr. Walsh presents preventive strategies that integrate clinical data science, informatics, and mental health expertise in an attempt to prevent suicidal thoughts and behaviors. He explains basic concepts in applied predictive modeling relevant to an audience interested in disease prevention. He also shares examples of active research and operational efforts in this domain in civilian and active duty military environments.
Dr. Sterman discusses systems approaches in public health, including the concepts of policy resistance, implementation feedbacks, and model boundaries and explores how these ideas can be applied to effect change in a complex system. He includes examples from healthcare and public health such as implementation of formulary drug lists and SARS epidemic modeling.
Dr. McLeroy discusses adoption of systems methodology, including multiple levels of analysis, utility for identifying points of change, testing models against reality, and applications to program evaluation and various research designs, including community-based participatory research and randomized clinical trials.