A central goal of the field of youth intervention research is to conduct rigorous research that identifies which programs and approaches work, which do not, and why. Scientists working in this field face a variety of complex and sometimes controversial issues in the design and implementation of their studies. As a result, the potential for real or perceived bias in many areas of youth intervention research is high. Whether real or perceived, bias can undermine both the conduct of good research, and the process by which good scientific research is brought to bear in contributing to society and informing policy and programs. In February 2001, the U.S. National Institute for Child Health and Human Development (NICHD) held a workshop, Addressing Bias in Intervention Research. This event was designed to address how issues relating to bias affect youth intervention research and, in particular, to address three major goals: (a) increase awareness of the many sources of real and perceived bias in intervention research and the need to address them in the design and conduct of science; (b) articulate the ways in which investigators can guard against bias, measure it and report on it where it exists, and find ways of validating results when bias cannot be eliminated; and (c) through the above, provide a framework that can help to anchor discussions of potential bias in scientific results in domains in which passions and positions are strong. Bias has a range of meanings, both scientific and nonscientific. The workshop highlighted two definitions: deviation of the expected value of a statistical estimate from the quantity it estimates, and bent, tendency, an inclination of temperament or outlook, especially a personal and sometimes unreasoned judgment, prejudice, an instance of such prejudice [1]. In scientific terms, an estimate is biased if it systematically distorts the true value of a measured attribute or quantity. This type of bias can result from errors made in the process of observation and collecting, reporting, processing, and transforming data. It can also be built into the design of scientific studies: what is to be observed, what questions are asked, what hypotheses will be tested, how subjects are selected for a study, and how the control groups are conceptualized. These types of biases are always issues in scientific research. However, bias takes on a pejorative meaning when we think that it results from dishonesty or prejudice. We blame the researcher who selects samples, designs measurements, or analyzes data in ways that systematically bias results toward ideological beliefs or results that will benefit something in which the researcher has a financial interest. Although recognizing that no science is value-free, most scientists believe that an important aim of science is to strive toward an ideal of objectivity. It is important to understand and From the Demographic and Behavioral Sciences Branch, National Institute of Child Health and Human Development, Bethesda, Maryland. Address correspondence to: Susan F. Newcomer, Ph.D., Demographic and Behavioral Sciences Branch, National Institute of Child Health and Human Development, Building 61e, Room 8B07, Bethesda, MD 20892. Manuscript accepted March 15, 2002. JOURNAL OF ADOLESCENT HEALTH 2002;31:311–321