SEPTEMBER 23, 2019
Susan Murphy, PhD
Professor of Statistics, Radcliffe Alumnae Professor at the Radcliffe Institute and
Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences
Harvard University
About the Presentation: Mobile devices along with wearable sensors facilitate our ability to deliver supportive interventions anytime and anywhere. Indeed mobile interventions are being developed and employed across a variety of health fields, including to support HIV medication adherence, encourage physical activity and healthier eating as well as to support recovery in addictions. A critical question in the optimization of mobile health interventions is: “When and in which contexts, is it most useful to deliver treatments to the user?” This question is critical in forming the development of interventions that are adaptive to individuals as well as providing support just-in-time. In this talk we discuss our work on a variety of mobile health interventions and how data analysis methods can be harnessed to optimize Just-in-Time Adaptive Interventions.
About the Presenter: Susan Murphy is a Professor of Statistics, Computer Science and Radcliffe Alumnae Professor, Harvard University. Dr. Murphy’s lab develops data analysis methods and experimental designs to improve real time sequential decision-making in mobile health. In particular, her lab develops algorithms, deployed on wearable devices, to deliver and continually optimize individually tailored treatments. She developed the micro-randomized trial for use in constructing mobile health interventions; this trial design is in use across a broad range of health related areas. In these trials each participant can be randomized or re-randomized 100’s of times. Examples of micro-randomized trials that are completed or are in the field can be found at https://methodology.psu.edu/ra/adap-inter/mrt-projects#proj.
Dr. Murphy is a member of the National Academy of Sciences and of the National Academy of Medicine, both of the US National Academies. In 2013 she was awarded a MacArthur Fellowship for her work on experimental designs to inform sequential decision making.