A collection of online chapters that provide an introduction to selected behavioral and social science research approaches, including theory development and testing, survey methods, measurement, and study design. eSource was developed in 2010, and these chapters have not been updated to reflect advances in the past decade. However, they can still be used as supplementary teaching materials.
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).
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 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.
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.
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.
Implementation science methodologies, approaches, and tools have a great interdisciplinary applicability. Dr. Alice Ammerman’s webinar discusses what new (and "new to") D&I investigators need to know to succeed in this burgeoning field.