Improving Measures of Physical Activity, Sedentary Behavior, and Context for Epidemiological Studies and Interventions in Older Adults
Dr. Kerr is a leader in physical activity research and assessment in older adults. Her webinar outlines the importance of improving measurement precision of both physical activity and sitting time using mobile sensors and machine learning techniques. Dr. Kerr discusses the infrastructure investments that have been necessary, challenges of working with computer scientists, and the need for stronger validation of new measurement techniques.
Improving the Efficiency of Prevention Research Using Responsive and Adaptive Survey Design Techniques
In this Methods: Mind the Gap presentation, Dr. Wagner starts from a definition of the basic principles of responsive and adaptive designs and then provides concrete examples of the implementation of these designs. These examples are drawn from a variety of settings, including face-to-face, telephone, and mixed-mode surveys.
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.
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.
Python is a free, open-source and powerful programming language that is easy to learn. This FAES course is intended for nonprogrammers who want to learn how to write programs that expand the breadth and depth of their daily research. Most elementary concepts in modern software engineering are covered, including basic syntax, reading from and writing texts files, debugging python programs, regular expressions, and creating reusable code modules that are distributable to peers. The course also focuses on potential applications of Python to bioinformatics, including sequence analysis, data visualization, and data analysis. Students also learn to use the Jupyter Notebook and the PyCharm integrated development environment (IDE), which are available at no cost.
R is a free statistics software that is becoming increasingly popular and important for data analysis in biology. During this FAES course, students first learn how to handle the R programming environment. Next, students learn how to simulate data for analysis, while the background for R programming is provided in accompanying lectures. At the end of the course, students become familiar with simple R programming, which they can then apply to their own data analysis.
This FAES class aims to introduce fundamental subjects in text mining such as tokenization, named entity recognition (NER), grammars, parsing, relation extraction, and document classification. The class is oriented towards hands-on experience with Python and Natural Language Toolkit (NLTK).
This course trains registrants on how to effectively and safely conduct clinical research. It focuses on the spectrum of clinical research and the research process by highlighting biostatistical and epidemiologic methods, study design, protocol preparation, patient monitoring, quality assurance, ethical and legal issues, and much more. This course will be of interest to physicians, scientists, medical and dental students, nurses, public health professionals, and others conducting or planning a career in clinical research.
In this Methods: Mind the Gap webinar, Dr. Max Crowley discusses key standards for economic evaluation as identified by a number of convergent efforts. In particular, the important role of administrative records for mapping the costs and benefits of prevention onto public budgets are discussed. Participants will gain a greater awareness of (1) best practices for economic evaluations of prevention, (2) how to increase utility of estimates for budget making, and (3) opportunities to include economic evaluation in ongoing and new studies.
In this Methods: Mind the Gap presentation, Dr. Tucker discusses the approaches to dietary assessment for estimating usual intake for the purpose of relating intake of nutrients, foods, and food patterns to chronic health conditions such as diabetes, heart disease, stroke, cognitive decline, bone loss, and others.
UMass Lowell, Zuckerberg College of Health Sciences
Many instruments in HealthMeasures are based on item response theory (IRT). IRT is a family of mathematical models that assumes that responses on a set of items or questions are related to an unmeasured “trait”. An example of such a trait may be physical function. IRT models assume a person’s level on physical function (e.g., high vs. low) will predict that person’s probability of endorsing each specific item.
Joint Models of Longitudinal and Time-to-Event Data for Informing Multi-Stage Decision Making in mHealth
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.
In his Methods: Mind the Gap presentation, Dr. Ransohoff illustrates challenges and practical realities in guidelines-making by describing the evolution of evidence and of guidelines for colon cancer screening. The lecture describes the relationship between evidence, policy, and politics and identifies current challenges in making high-quality guidelines.
These 12 webinars are intended for nutritionists, epidemiologists, statisticians, graduate students, and others with an interest in measurement error in dietary intake data. The goal of the webinar series is to provide participants with an understanding of:
- The sources and magnitudes of dietary measurement errors
- How measurement error may affect estimates of usual dietary intake distributions
- How measurement error may affect analyses of diet–health relationships
- How the effects of measurement error may be mitigated.
This 6-part webinar series provides an overview of physical activity as a multidimensional health behavior; an in-depth review of methods to measure active and sedentary behaviors by self-report; and an exploration of important issues when assessing physical activity in diverse populations.
These modules are designed to complement the Measures Registry and Measures Registry User Guides and assist researchers and practitioners with choosing the best measures across the four domains of the Measures Registry: individual diet, food environment, individual physical activity and physical activity environment.
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.