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"Genius" grant winner Susan Murphy Image: Courtesy of the John D. & Catherine T. MacArthur Foundation
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Of the 24 Fellows honored today with the MacArthur Foundation?s 2013 ?genius? awards, about half labor on the frontlines of science and technology. One of those is Susan Murphy, a 55-year-old statistician at the University of Michigan. In this interview she talks about her passion for using math to improve health care for people with mental illness. She and the other recipients earn a $625,000 prize to be paid out over five years (an increase from the $500,000 given in past years.) See a full list of winners here, and scroll to the bottom of this post for details about the other science researchers.
[An edited transcript of the interview follows.]
What is the greatest challenge currently facing us in the health care arena?
Achieving and maintaining behavioral change. You can have a great pill?a magic blue pill that will control your blood pressure?but if you don?t take that pill every single day as many times as required, your blood pressure will not be controlled. That?s behavior change. And it?s difficult to change. If you need to take that pill for a decade, that is a different thing entirely than taking it for a day or two.
Tell me about how your methods helped clinical trials compared with those that simply compare two treatments.
The idea is to allow you to look at the entire sequence of treatments [a person experiences in care]. We see how people do in [a] first treatment, and if they do well, we randomize them to different kinds of maintenance therapies; if they don?t do well, we randomize them to different kinds of secondary treatments?augmenting their current treatment or secondary treatments. Then you get all the people who didn?t do well on the first treatment or people who did do well on the first treatment and those groups are much more representative [of a population with a certain malady].
Our SMART [for sequential, multiple assignment, randomized trial] trials are now being applied all over the health field. They are listed on my Web site. Let?s think about a trial for little kids who have autism. These are kids who at age five are still nonverbal?this is a big problem because verbal ability is strongly related to success later in life. These kids have not responded well to past treatments. Initially they were randomized to two interventions designed to improve their ability to communicate. One is focused on using spoken language in play activities?something relevant to the child. The other would be focused on the kid using something like an iPad, where the kid could press it and [it would] speak for the child. Then what happened is the little kids were tracked over time, and they saw whether or not the interventions were improving their ability to communicate, either verbally or though the iPad. The iPad device is expensive, so normally you wouldn?t give it to the child initially. The kids in the study arm that were being encouraged to express themselves verbally in play, if those kids were still struggling to communicate, then that kid was rerandomized between using the iPad-like device or even more intensive treatment?seeing the therapist more frequently. The ultimate goal was to think more about what therapies you should start with.
Right now I know you're working on ways to deliver personalized health care via mobile devices. What's your approach there?
We are working on the innards?the algorithms that would be behind an app that you would see on your phone. You can imagine an app that would be a recovery app ?coach? application?helping you deal with trying to stay off drugs, for example, or trying to deal with cravings that you feel as you are moving through life and you are trying to keep your weight down. The goal is to tailor whatever strategies the coach recommends to you; so, as time goes on [and] you change, we want the app to change with you.
Source: http://rss.sciam.com/~r/ScientificAmerican-News/~3/UUxYDL9cw3A/article.cfm
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