In this Methods: Mind the Gap presentation, Dr. Rivera discusses the relevance of control engineering to mHealth using two interventions currently under development—Just Walk, an intervention to promote walking in sedentary adults, and Healthy Mom Zone, an intervention for managing gestational weight gain in overweight/obese pregnant women.
Arizona State University
Missing data present a common problem for prevention research and improperly handling missing data can severely compromise the validity of a study’s inferences. In this Methods: Mind the Gap webinar, Dr. Little highlights the power and utility of modern principled treatments for missing data to optimize inferences. He discusses the three issues that occur when data go missing and the three mechanisms that give rise to missing data.
The problem of overdiagnosis, the detection by screening of latent cancers that would never have surfaced, has been much in the news lately. What is overdiagnosis, and how significant is the problem? In this Methods: Mind the Gap webinar, Dr. Etzioni examines how overdiagnosis arises and discusses what it takes to validly estimate its frequency.
This course discusses machine learning (ML), which has become a core technology underlying many modern applications, especially in health care. Machine learning techniques provide powerful methods for analyzing large datasets such as medical images, electronic health records, and genomics. Recent advances in deep learning (DL) provide an analysis framework that can be used to automatically classify images and objects with (and occasionally exceeding) human-level accuracy.
In this Methods: Mind the Gap presentation, Dr. Li provides an overview of statistical models for the design and analysis of stepped wedge cluster randomized trials.
Yale University School of Public Health
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.
This training walks participants through writing programs that would help them solve scientific problems. During the course, participants get a brief introduction to the programming concepts, followed by hands-on walkthrough in writing scripts using the Unix Shell, R, Perl, and Python. The course will cover reading the data through processing and saving the processed data.
This course is designed for researchers, clinicians, students, and academics who are aspiring to learn to write their own scripts and programs, or for scientists in program administration interested in learning the standard tools and techniques for biomedical programming.
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.