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Lam looks at population and development in next 15 years in UN commission keynote address

Mitchell et al. find harsh family environments may magnify disadvantage via impact on 'genetic architecture'

Frey says Arizona's political paradoxes explained in part by demography

Highlights

Raghunathan appointed director of Survey Research Center

PSC newsletter spring 2014 issue now available

Kusunoki wins faculty seed grant award from Institute for Research on Women and Gender

2014 PAA Annual Meeting, May 1-3, Boston

Next Brown Bag

Monday, April 21
Grant Miller: Managerial Incentives in Public Service Delivery

Learning Adaptive Treatment Strategies in Mental Health

a PSC Research Project

Investigator:   Susan A. Murphy

Chronic mental illnesses such as major depression and schizophrenia impose a heavy burden both on the individual and society. High quality clinical care can reduce the burden but such care demands sequential clinical decision making concerning treatment. The long term goal of this project is to improve sequential clinical decision making. The specific aims concern methodological approaches for helping clinicians address questions such as: How long should one wait to decide that a patient is not deriving sufficient benefit from treatment? If it is established that a patient is not sufficiently benefiting from treatment then which treatment should be provided next? Should the sequence of treatments vary according to patient characteristics and outcomes such as disease features, response, side effect burden, and adherence? In this project methods taken from computer science, engineering and statistics are generalized and adapted for use with clinical trial data so as to address these kinds of questions. The methods will be developed and validated using data from two large NIMH funded trials. This project will be conducted by a collaborative team involving a computer scientist, two psychiatrists and a statistician.

Funding Period: 05/01/2007 to 04/30/2012

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