When Using Your Smartphone Can Be the Best Thing for Your Mental Health

My last post here took on Zeynep Tufekci and, by extension, others who believe the current trend of using robots and other forms of advanced technology for caregiving is, as she put it, “an abdication of a desire to remain human, to be connected to each other through care, and to take care of each other.”  I wonder how these self-appointed guardians of our humanity feel about the new iPhone app that provides automated diagnoses of imminent mood swings for people with bipolar disorder.

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I love this technology, for the reasons nicely enumerated in this Slate article by Aimee Swartz. Bipolar disorder is common – it affects almost 6 million American adults — and can be very hard to live with, both for people with the condition and for those around them. None of my loved ones have it, thankfully, but I’ve watched families I know well suffer greatly as they try to help one of their members cope with the illness.

Many of the people with it would like to moderate their severe mood swings, but this can be hard to do because as Swartz explains “once a manic episode has begun, the patient often becomes unreceptive to recommendations to seek medical care.” So it’s important to get to then as early as possible during the transition to that episode, when they’re still receptive. 

This is where PRIORI, a technology under development by Prof. Melvin McInnis and his colleagues at the University of Michigan, comes in. With informed consent and in accordance with privacy rules, PRIORI collects the patients’ sides of their smartphone calls, then analyzes these sound files using machine learning techniques to figure out which characteristics of speech are most strongly related to the onset of a manic episode. Importantly for privacy, the algorithms don’t track or analyze what patients are saying, only how they’re saying it.

This might well be enough. In an small initial trial involving a half dozen people with relatively rapid mood swings, the app was successful at predicting when one was coming 65% of the time. This is pretty good, and as Swartz points out it’ll only get better with more time and more data.

McInnis explains why this is so important: ““The classic way we have of monitoring individuals with bipolar disorder is what I call 18th-century medicine. People see their doctors, chat how their energy levels are during the day, how they’re sleeping at night, how they’re getting along at home and work to gauge how they’re going… [W]e [currently] diagnose an episode when it’s already started, and it’s already causing all kinds of problems.”

In other words, our current, human-centric system of taking care of these highly vulnerable people isn’t working. So what would work better? It looks like a small, unobtrusive piece of technology might work pretty well here, and improve caregiving via automation.

Anyone got a problem with that, or want to make a case for why taking care of our mentally ill loved ones should remain human-centric and low tech? If so, I’m all ears.