Education & Training

In this webinar, Dr. Larry Palinkas introduces the use of mixed method designs in research on three interrelated facets of evidence-based practices implementation: provider social networks, use of research evidence, and cultural exchange between researchers and practitioners. Dr. Palinkas explains the multiple strategies through which qualitative and quantitative research methods can converge, specifically highlighting their use within three funded research studies of implementation.

Measuring and projecting the economic burden associated with cancer and identifying effective policies for minimizing its impact are increasingly important issues for health care policymakers and health care systems at multiple levels. 

Written by experts in health economics, epidemiology, health services research, health policy, and biostatistics, this publication highlights the multiple benefits of comparing patterns of cancer care, costs, and outcomes across health systems within a single country or across countries.

In this Methods: Mind the Gap webinar, Dr. Karina Davidson discusses single-patient trial design. The most scientifically rigorous—and potentially efficient—method for determining optimal clinical care for a specific patient is a single-patient (N-of-1) randomized controlled trial, in which data are collected objectively, continuously, and in the real world for a sufficient time period to determine whether the intervention, compared to a placebo, another intervention, or a different type of delivery or schedule, is optimal for that particular patient. With sufficient data from several N-of-1 trials of the same design, we can engage in inductive phenotype identification, but N-of-1 trials are only useful under certain circumstances.

The NINDS Clinical Trials Methodology Course (CTMC) is an intensive, engaging program designed to help junior investigators develop scientifically rigorous, yet practical clinical trial protocols, and to focus on early consideration of funding mechanisms as a key trial planning activity.

In collaboration with other academic institutions, professional organizations, and funding agencies, the Implementation Science team coordinates and supports several training and educational activities, including a monthly webinar series, training programs, and an annual conference.

In this presentation, Dr. Gortmaker presents the latest findings from the Childhood Obesity Intervention Cost-Effectiveness Study (CHOICES) project. CHOICES is a collaborative modeling effort designed to evaluate the effectiveness, costs, and reach of interventions to reduce childhood obesity in the United States.

This webinar describes the purpose and use of the latest mobile-friendly version of the Automated Self-Administered 24-Hour Recall/Record System (ASA24). The tool is freely available to researchers, clinicians, and educators for dietary intake collection. Speakers describe the background of the tool, its evaluation, and best practices for its use.

As part of the ODP’s 2012 Physical Activity and Disease Prevention Workshop: Identifying Research Priorities session #3: Measurement of Physical Activity Behavior, Dr. Intille discusses the devices that might be used to measure and study physical activity versus sedentary behavior.

The NIH Disaster Research Response Program (DR2) is the national framework for research on the medical and public health aspects of disasters and public health emergencies. The DR2 website, provided by the National Institute of Environmental Health Sciences and the National Library of Medicine, supports disaster science investigators by offering data collection tools, training and exercises, research protocols, disaster research news and events, and more.

The NINR Big Data in Symptoms Research Boot Camp, part of the NINR Symptom Research Methodologies Series, is a one-week intensive research training course at the National Institutes of Health (NIH) in Bethesda, Maryland. It provides a foundation in methodologies for using Big Data in research. The purpose of the course is to increase the research capability of graduate students and faculty.

Motivated by the analysis of intensive care unit data, this talk discusses new methods to automatically extract causal relationships from data and how these have been applied to gain new insight into stroke recovery. Finally, the speaker discusses recent findings in cognitive science and how they can help us make better use of causal information for decision-making. 

Clinical trial guidelines have remained similar for decades despite long timelines, high costs, and frequent failures. This forum, convened by the NIH Scientific Program and Review Interest Group (SPRIG), addresses alternative strategies and models for clinical trials.

The speakers address the following questions:

• What are some potential advantages of group-randomized clinical trials?
• How can we mitigate the impact of non-adherence and professional subjects?
• How receptive is the FDA to novel trial strategies?
• Might artificial intelligence better guide future clinical trials?

This journal supplement summarizes and builds upon a workshop which convened researchers from diverse sectors and organizations. The supplement discusses current technologies for objective physical activity monitoring, provides recommendations for the use of these technologies, and explores future directions in the development of new tools and approaches.

It presents best practices for using physical activity monitors in population-based research, explores modeling of physical activity outcomes from wearable monitors, and discusses statistical considerations in the analysis of accelerometry-based activity monitor data. It also examines monitor equivalency issues and discusses current use and best practices for accelerometry with particular populations—children, older adults, and adults with functional limitations.

In this Methods: Mind the Gap webinar, Dr. Stephen J. Mooney discusses approaches and useful tools for constructing measures of place from secondary data, including “ecometrics” (using psychometric techniques to build place-based scales), spatial interpolation, and assessing and correcting for sampling biases in crowdsourced data.

In this Methods: Mind the Gap presentation, Dr. Collins briefly describes MOST and contrasts it to the classical treatment package approach. She reviews examples of recent and current applications of MOST. Finally, she discusses where she sees the field of intervention optimization going, including future methodological directions.

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.

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.