In his Methods: Mind the Gap presentation, Dr. Robert Califf discusses the role and value of clinical trials in medical research given the rapid evolution of the science of clinical trials.
This innovative program will place a strong emphasis on mentoring, applying competencies and curriculum specifically focused on chronic disease disparities, and working with a diverse set of partners. Scholars are enrolled in the program for two years.
The objective of this FAES Graduate School course is to provide an introduction to the principles and methods of epidemiology, defined as the study of the distribution and determinants of disease in populations. Lectures, problem sets, and outside reading will cover ecologic, case-control, cohort, and experimental studies. Topics to be discussed will include study design, measures of disease risk, sources of bias, methods of controlling for extraneous factors, principles of screening, and interpretation of data. Illustrations will include classic and contemporary examples in acute and chronic disease.
This is the first part of a two-part course. Registration is required separately for each part of the course.
In this Methods: Mind the Gap presentation, Dr. Dempsey focuses on mHealth studies in which both longitudinal and time-to-event data are recorded per participant. From assessing levels of biomarker association with event risk, to defining risk strata for a stratified micro-randomized trial, to post-study analysis of the treatment effect on event risk, he discusses how joint models enter into various stages of the intervention development process. He also discusses how mHealth studies present novel methodological challenges for joint modeling and solutions in several case studies. In each instance, he connects the joint modeling perspective back to how scientists can use them to inform multi-stage decision making in mHealth.
The objective of this FAES Graduate School course is to learn the concepts and methodology used in the design and conduct of randomized clinical trials. Topics to be covered will include description of the main types of trial designs, principles of randomization and stratification, issues in protocol development (defining objectives and endpoints, blinding, choice of control), recruitment and retention, data collection and quality control issues, monitoring, and analyses of trials reports.
In this Methods: Mind the Gap presentation, Dr. Valerie Earnshaw provides a cross-cutting conceptual overview of stigma, identifies targets for stigma measurement, recommends methodological approaches for stigma research, and reviews the intervention toolkit to address stigma. She draws on examples from her own and others’ research, with a focus on two highly stigmatized disease contexts: HIV and substance use. She advocates for theory-based cross-cutting research to improve understanding of stigma and the development of intersectional, multilevel, and longitudinal interventions to enhance efforts to address stigma.
This week-long immersion program provides 30 selected investigators with a thorough introduction to selected mHealth methodologies that may be used to study behavioral and social dimensions of public health. Participants work with expert mentors to create their own inter-disciplinary mobile health projects.
The mHealth training institute is funded via the NIH BD2K Program. The NIH BD2K Program is funded by all the NIH Institutes and Centers and receives support from the NIH Common Fund and the NIH Office of Behavioral Health and Social Sciences Research (OBSSR).
Mixing qualitative and quantitative research methods can provide deeper exploration of causal mechanisms, interpretation of variables, and contextual factors that may mediate or moderate the topic of study. In this Methods: Mind the Gap webinar, Dr. Leonard Jason provides an introduction to the different approaches used in conducting mixed-methods research, including the benefits and challenges.
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.
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.
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 NIH-Duke Master's Program in Clinical Research, established in 1998, is one of the nation's first training programs in clinical research. This program allows participants to attend formal courses in research design, research management, medical genomics, and statistical analysis at the Clinical Center by means of video-conferencing from Duke or on-site by adjunct faculty.
The program leads to a Master of Health Sciences in Clinical Research, a professional degree awarded by the Duke University School of Medicine. There is also a non-degree option for qualified students who want to pursue specific areas of interest.
Applications will be accepted through August 1, 2020.
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?
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
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
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.