Dec. 02--Computational analysis and empathy may not sound like a match made in heaven. But a new study suggests that machine-learning systems can be harnessed to the task of detecting, measuring and enhancing a mental health professional's empathic response to clients in distress.
That, in turn, could make psychotherapy better, and more widely accessible where it's most needed.
To doubters, it might even help prove its worth.
In work performed at USC, researchers devised an engineering solution to a perennial problem in the training and assessment of psychotherapists: The systems in place for detecting empathy are basically other humans.
The process of distinguishing an effective therapist from one likely to send clients running for cover is, essentially, review by other humans. Since time immemorial, trained raters have watched a live or recorded therapy session and made note of the gestures, speech patterns and interactions that suggest either that a therapist is connecting to a client and prompting reflection, or prompting a defensive, immune response.
That process -- necessary to train therapists, maintain their skills, and rate the quality of their services -- is "expensive, time consuming, and quite literally, never used in the real world," says University of Washington psychologist David Atkins, one of the paper's co-authors.
But what if software programmed to detect the speech and behavioral patterns of empathy could do the job? USC electrical engineering student Bo Xiao and his doctoral advisor, Shrikanth S. Narayanan, set out to lash together a system that could give therapists -- as well as patients and even insurers -- real-time feedback on the quality of their services.
Their findings, published Wednesday in the journal PLoS, suggest that automated systems of speech and pattern recognition "are possible." And as they are further refined, they could -- via smart phone or tablet -- provide therapists "near-real time feedback" to rate and hone their psychotherapeutic skills.
Providers of "talk therapy" have come under increasing pressure in recent years to show that their services are effective in the treatment of a range of emotional ills and mental disorders. Proponents of cognitive behavioral therapy -- a brief, structured form of therapy aimed at concrete problem-solving -- can point to a wealth of research supporting its effectiveness. And newer neuroimaging studies have shown positive brain changes with some forms of talk therapy.
But for many other forms of talk therapy -- including "motivational interviewing," the anti-addiction treatment largely used in the current study -- proof of effectiveness has been harder to come by.
Psychologist Atkins said that focusing on empathy -- the glue that forms the psychotherapeutic relationship and starts the healing -- may be key to demonstrating the value of those less-studied forms of talk therapy as well.
"We name things differently, but if you look closely, there are some core common factors" to virtually all psychotherapy, said Atkins. "Empathy would be considered a core counseling technique," and to the extent that it can be efficiently assessed, measured, and improved, most forms of psychotherapy could benefit, he added.
Which raises the question: Can machines help make psychotherapy better? Atkins is optimistic.
"This is an intimate process that is incredibly unique to the person in front of me," said Atkins. "But if we don't have some guides -- some rules and some best practice guidelines, it's really the Wild West and anything goes."
The new research was funded by the National Institute on Drug Abuse and the National Institute on Alcoholism and Alcohol Abuse.
