Online Training Resources

The Office of Behavioral and Social Sciences Research (OBSSR) has identified training needs in several areas relevant to the behavioral and social sciences.  

Good Clinical Practice for Social and Behavioral Research eLearning Course

In 2016, NIH issued a policy establishing an expectation that all NIH-funded investigators and staff involved in conducting, overseeing, or managing clinical trials should be trained in Good Clinical Practice (GCP) and should refresh their training at least every three years. The principles of GCP ensure the safety, integrity, and quality of clinical trials. GCP provides a standard for compliance, implementation, data collection, monitoring, and reporting, and outlines the responsibilities of Institutional Review Boards (IRBs), investigators, sponsors, and monitors. In 2024, course material was updated to provide additional training on regulatory changes and reporting requirements, enhanced accessibility features, and a new module on community and stakeholder engagement.

Accessing the Training Modules

The course materials are free to access and use. There are several ways to access the training:

Mixed Methods Research

 Download Full PDF version (292 KB)

Commissioned by the

Office of Behavioral and Social Sciences Research (OBSSR)
Helen I. Meissner, Ph.D., Office of Behavioral and Social Sciences Research


John W. Creswell, Ph.D., University of Nebraska-Lincoln
Ann Carroll Klassen, Ph.D., Drexel University
Vicki L. Plano Clark, Ph.D., University of Nebraska-Lincoln
Katherine Clegg Smith, Ph.D., Johns Hopkins University

With the Assistance of a Specially Appointed Working Group

Suggested citation:

Creswell JW, Klassen AC, Plano Clark VL, Smith KC for the Office of Behavioral and Social Sciences Research. Best practices for mixed methods research in the health sciences. August 2011. National Institutes of Health.

Introduction and Background

In November 2010, the OBSSR of the NIH commissioned the leadership team of John W. Creswell, Ann Klassen, Vicki L. Plano Clark, and Katherine Clegg Smith to develop a resource that would provide guidance to NIH investigators on how to rigorously develop and evaluate mixed methods research applications. Pursuant to this, the team developed a report of “best practices” following three major objectives.

To develop practices that:

  • assist investigators using mixed methods as they develop competitive applications for support from NIH;
  • assist reviewers and staff for review panels at NIH who evaluate applications that include mixed methods research;
  • provide the Office of Behavioral and Social Sciences Research (OBSSR), and the NIH Institutes and Centers, with "best practices" to use as they consider potential contributions of mixed methods research, select reviewers, plan new initiatives, and set priority areas for their science.

OBSSR convened a Working Group of 19 individuals (see Appendix A. NIH Working Group on Developing Best Practices for Mixed Methods Research [31 KB]) to review a preliminary draft of “best practices.” This Group was composed of experienced scientists, research methodologists, and NIH health scientists. These individuals were selected because of their expertise in NIH investigations, their specific knowledge of mixed methods research, and their experience in the scientific review process. The composition of the Working Group was diverse with members representing such fields as public health, medicine, mental health professions, psychology, sociology, anthropology, social work, education, and nursing. This Working Group met in late April 2011, and reviewed and made recommendations for the final document presented in this report.

This report consists of seven sections:

In 2018, OBSSR added then-active examples from the NIH portfolio and an updated bibliography to the Office’s mixed-methods resources. Download Supplemental Materials.

TADA-BSSR Webinar: Integrating Data Analytics into the Social and Behavioral Science Research Lifecycle

Presenters: Hannah L. F. Cooper, Sc.D., Rollins School of Public Health, Emory University; Lance Waller, Ph.D., Rollins School of Public Health, Emory University

May 20, 2021 | Video Recording | Webinar Description: The presenters explore the ways that elements of Cook and Campbell’s validity framework can strengthen analyses of “big data” that are designed to study, monitor, and intervene in drug-related harms. They also discuss the relevance of specific threats to internal validity, external validity, and statistical conclusion validity to these analyses, and strategies to minimize these threats.

TADA BSSR Webinar: Translating Domain Knowledge into Mechanistic Process Models

Presenters: Eric Hekler, University of California San Diego; Misha Pavel, Northeastern University; Donna Spruijt-Metz, University of Southern California

March 18, 2021 | Video Recording | Webinar Description: Translating Domain Knowledge into Mechanistic Process Models: Illustrating the Need with a Just-in-Time Adaptive Intervention

TADA-BSSR Webinar: Analyzing Complex Behavioral, Social and Population Health Data for COVID-19

Presenter: Carl T. Bergstrom, Ph.D., University of Washington

January 21, 2021 | Video Recording | Webinar Description: Selection bias occurs when the way a statistical sample is obtained prevents the sample from accurately representing the population about which one wishes to draw inferences. Straightforward as the issue may seem, selection bias is among the most pernicious perils of statistical inference. This lecture discusses some of the many ways that selection bias and related phenomena, from right censoring to the Will Rogers effect, can arise in medical research and beyond. It draws upon a range examples, including recent studies on COVID-19.

TADA-BSSR Webinar: Analyzing Complex Behavioral, Social, and Population Health Data for COVID-19 and New Opportunities for BSSR Data Science Training

Presenters: Lorene Nelson, Ph.D., M.S., Stanford University School of Medicine; Lance Waller, Ph.D., Emory University; Mick Tilford, Ph.D., University of Arkansas for Medical Sciences; Lucila Ohno-Machado, M.D., Ph.D., University of California, San Diego; and Maria Glymour, Sc.D., M.S., University of California, San Francisco

October 15, 2020 | Video Recording | Webinar Description: This video is a recording of the inaugural edition of the TADA-BSSR Webinar Series which features a brief introduction of the new NIH/OBBSR sponsored training program and highlights some of the exciting ongoing work at five of the training sites involving complex data related to the COVID-19 pandemic.

Training Webinar Cover

OBSSR Methodology Seminar: Text Mining for Behavioral and Social Sciences Research

August 9, 2019 | NIH Videocast Archive | Seminar Description: The age of Big Data has ushered in a wave of high-volume digital information and much of it is text based. Text mining is a form of data mining that involves collecting and analyzing large volumes of textual data to reveal patterns and relationships. Techniques for mining can be used to extract key concepts, spot trends, summarize content from documents and gain semantic understanding, and index and search text for use in predictive analytics. Text mining has become an important research process with many different commercial and academic applications, and it is becoming more widely applied in social science studies. This one-day methodology seminar sponsored by OBSSR presented a basic introductory overview of principles and techniques of text mining for behavioral and social research and showcased some innovative health research examples. 

OBSSR Methodology Seminar: Predictive Modeling for Behavioral and Social Sciences Health Research

October 12, 2018 | NIH Videocast Archive | Seminar Description: This one-day methodology seminar showcased principles and techniques for prediction modeling from machine learning via specific case examples presented by scientists who are applying predictive algorithms to health-related behavioral and social sciences data.

OBSSR Methodology Workshop: Emerging Nontraditional Survey Data Collections

August 25, 2017 | NIH Videocast Archive  | Seminar Description: Surveys via in-person interviews, telephone interviews, and mail questionnaires have been a traditional mainstay in the behavioral and social sciences for many decades. Vast technological and societal changes are driving inevitable change in the world of health research data collection. The past decade has seen an extraordinary expansion in the range of new technologies being applied in survey research. This seminar focused on health research involving emerging, nontraditional survey methodologies, including online non-probability panel surveys; survey participant recruitment via social media platforms; opportunities for using text messaging or SMS to recruit and engage survey participants for health research; “passive data collection” obtained from mobile devices or “sensor devices”; and the value of social media or web data in the context of health survey research.