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Daniel Almirall is a Research Associate Professor in the Institute for Social Research at the University of Michigan. In clinical or educational practice, it is often necessary to use an individually-tailored, sequential approach to intervention in order to improve change in outcomes. Adaptive interventions (also known as dynamic treatment regimens) are pre-specified multicomponent, multistage intervention packages that can be used to guide such sequential, intervention decision-making. Dr. Almirall is interested in the development and application of data collection designs and data analysis methods used to form high-quality adaptive interventions. This includes his methodological work on the use of sequential multiple assignment randomized trials (SMARTs), in which individuals or organizations are randomized repeatedly over time.
More recently, Dr. Almirall has also been interested in the use of micro-randomized trials (MRTs) to develop or optimize just-in-time adaptive interventions (JITAIs) in mobile health settings. As a statistician and methodologist in the Institute for Social Research, he takes part in research in a wide variety of areas of social science and treatment (or interventions) research, and is particularly interested in the substantive areas of mental health (depression, anxiety) and substance abuse, especially as related to children and adolescents.