The Crowne Plaza Hotel Times Square Manhattan, New York, NY

Scientifically informed prevention and treatment of psychopathology requires a sophisticated understanding of its causes and the processes by which those causes affect individuals.  In the last several decades, progress has been made by documenting various associations between risk factors and mental disorders, and by ground-breaking discoveries of pharmacologic agents that alleviate symptoms and increase functioning.

As psychopathology researchers move beyond the findings of the last decade to multiple effects of interventions as well as pathology process, they often rely on clinical trials, prevention trials, and natural experiments to make causal inferences.  These designs provide inferential strength, but they do not necessarily avoid ambiguous findings and controversial interpretations.  Issues of compliance, missing data, contamination of treatments, and confounding can undermine clear causal inference.

In this meeting, we review new approaches to causal analysis that are being discussed in the statistical and epidemiological literatures to address the challenge of interpreting experimental and observational findings. We examine how these approaches can inform studies of psychopharmacologic effects, of genetic effects, and of social and environmental effects on psychopathology.  We also examine novel ways to design epidemiological studies and clinical trials to provide efficient and useful information. We conclude the meeting with a consideration of how causal evidence can help refine the definition of diagnostic categories.